From 5c75cb8880c371282ec4ed7c1e67c16d3825d0f0 Mon Sep 17 00:00:00 2001 From: Jim Pivarski Date: Sat, 27 Jul 2019 11:52:19 -0400 Subject: [PATCH] first commit of nearly all materials --- .gitignore | 10 + 01-scientific-python-ecosystem.ipynb | 2775 ++++ 03-columnar-data-analysis.ipynb | 10635 ++++++++++++++++ 04-accelerating-python.ipynb | 2129 ++++ README.md | 66 + data/HZZ-objects.root | Bin 0 -> 443685 bytes data/HZZ.root | Bin 0 -> 217945 bytes data/Zmumu.root | Bin 0 -> 178971 bytes environment.yml | 25 + img/03-cheat-sheet.png | Bin 0 -> 100055 bytes img/abstraction-layers.png | Bin 0 -> 392389 bytes img/apl-keyboard.jpg | Bin 0 -> 1133915 bytes img/apl-timeline.png | Bin 0 -> 47802 bytes img/arrow-website.png | Bin 0 -> 309677 bytes img/awkward-logo.png | Bin 0 -> 26635 bytes img/benchmark-games.png | Bin 0 -> 16408 bytes img/coffea-logo.png | Bin 0 -> 165822 bytes img/commute-by-plane.png | Bin 0 -> 281027 bytes img/cython-logo.png | Bin 0 -> 38380 bytes img/dask-logo.png | Bin 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create mode 100644 img/abstraction-layers.png create mode 100644 img/apl-keyboard.jpg create mode 100644 img/apl-timeline.png create mode 100644 img/arrow-website.png create mode 100644 img/awkward-logo.png create mode 100644 img/benchmark-games.png create mode 100644 img/coffea-logo.png create mode 100644 img/commute-by-plane.png create mode 100644 img/cython-logo.png create mode 100644 img/dask-logo.png create mode 100644 img/github-alice-lin.png create mode 100644 img/github-cmssw-lin.png create mode 100644 img/iminuit.png create mode 100644 img/ligo-notebook.png create mode 100644 img/mentions-of-programming-languages.png create mode 100644 img/numba-logo.png create mode 100644 img/numerical-recipes.jpg create mode 100644 img/numpy-logo.png create mode 100644 img/numpy-memory-broadcasting.png create mode 100644 img/numpy-memory-layout.png create mode 100644 img/numpy-slicing.png create mode 100644 img/pandas-logo.png create mode 100644 img/pybind11-logo.png create mode 100644 img/pyobject.png create mode 100644 img/pypl-2019.png create mode 100644 img/python-r-cpp-googletrends-dataset.png create mode 100644 img/python-r-cpp-googletrends-machinelearning.png create mode 100644 img/root-logo.png create mode 100644 img/root-spark-pandas-google-trends.png create mode 100644 img/scikit-hep-page.png create mode 100644 img/scikit-learn-estimators.png create mode 100644 img/scikit-learn-logo.png create mode 100644 img/scipy-docs.png create mode 100644 img/scipy-logo.png create mode 100644 img/shells-1.png create mode 100644 img/shells-2.png create mode 100644 img/shells-3.png create mode 100644 img/shells-4.png create mode 100644 img/shells-5.png create mode 100644 img/swallows-coconut.jpg create mode 100644 img/tshirt.jpg create mode 100644 img/uproot-logo.png create mode 100644 misc-fractal.ipynb diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..f511cd8 --- /dev/null +++ b/.gitignore @@ -0,0 +1,10 @@ +.ipynb_checkpoints +COPYOVER*.ipynb +tmp.parquet +tmp.root +cpp_calculate.cpp +cpp_calculate.cpython*.so +global.lock +mydask.png +purge.lock +worker-* diff --git a/01-scientific-python-ecosystem.ipynb b/01-scientific-python-ecosystem.ipynb new file mode 100644 index 0000000..c11cf11 --- /dev/null +++ b/01-scientific-python-ecosystem.ipynb @@ -0,0 +1,2775 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "# The Scientific Python Ecosystem\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has ever used Python? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has used Python more than C or C++? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has ever used PyROOT? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has ever used Numpy? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has ever used Matplotlib? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has ever used Pandas? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Who has used Python for machine learning? (Show of hands.)

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### Part 1: Why Python in particle physics?\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

I could point to its broad adoption as a programming language...

\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

But it is more relevant to point to its use in data analysis.

\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

It's hard to overstate the scale of these communities.

\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

There is value in adopting popular tools: every question/error message is googlable...

\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

The growth of Python in astronomy is... astronomical.

\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

It's the language of choice for some—but not all—LHC experiments.

\n", + "\n", + "\n", + "\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

It's the language of choice for some—but not all—LHC experiments.

\n", + "\n", + "\n", + "\n", + "_(Can't measure ATLAS and LHCb because of private repos on GitLab.)_\n", + "\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + " _(Stolen from Jake Vanderplas.)_\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Drive to the airport, then take a plane:

\n", + "\n", + " * Not everything needs to be fast, only the part that scales with the number of events (or other large number, like number of histogram bins or MC toys).\n", + " \n", + " The rest of the analysis code is bookkeeping: convenience outweighs speed.\n", + " \n", + " * Need to step up from interactive tinkering to full-scale analysis __*in small steps*__. Scale-up \"quasistatically\" to avoid a big round of bug-hunting.\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "7307.679454485576 ns per pixel\n" + ] + } + ], + "source": [ + "# Example: code to compute a fractal (calendar/mousepad/T-shirt...).\n", + "import time, numpy\n", + "\n", + "def run_python(height, width, maxiterations=20):\n", + " y, x = numpy.ogrid[-1:0:height*1j, -1.5:0:width*1j]\n", + " c = x + y*1j\n", + " fractal = numpy.full(c.shape, maxiterations, dtype=numpy.int32)\n", + " for h in range(height):\n", + " for w in range(width): # for each pixel (h, w)...\n", + " z = c[h, w]\n", + " for i in range(maxiterations): # iterate at most 20 times\n", + " z = z**2 + c[h, w] # applying z → z² + c\n", + " if abs(z) > 2: # if it diverges (|z| > 2)\n", + " fractal[h, w] = i # color with the iteration number\n", + " break # we're done, no need to keep iterating\n", + " return fractal\n", + "\n", + "starttime = time.time()\n", + "fractal = run_python(800, 1200)\n", + "print(\"{0} ns per pixel\".format(1e9 * (time.time() - starttime) / (800 * 1200)))" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Pretty, isn't it?\n", + "\n", + "%matplotlib inline\n", + "import matplotlib.pyplot\n", + "fig, ax = matplotlib.pyplot.subplots(figsize=(10, 5)); ax.imshow(fractal);" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "# REMINDER: the original code...\n", + "\n", + "\n", + "def run_python(height, width, maxiterations=20):\n", + " y, x = numpy.ogrid[-1:0:height*1j, -1.5:0:width*1j]\n", + " c = x + y*1j\n", + " fractal = numpy.full(c.shape, maxiterations, dtype=numpy.int32)\n", + "\n", + "\n", + "\n", + " for h in range(height):\n", + " for w in range(width): # for each pixel (h, w)...\n", + " z = c[h, w]\n", + " for i in range(maxiterations): # iterate at most 20 times\n", + " z = z**2 + c[h, w] # applying z → z² + c\n", + " if abs(z) > 2: # if it diverges (|z| > 2)\n", + " fractal[h, w] = i # color with the iteration number\n", + " break # we're done, no need to keep iterating\n", + " return fractal\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "159.1240211079518 ns per pixel\n" + ] + } + ], + "source": [ + "# 50× to 100× faster...\n", + "import numba\n", + "\n", + "def run_numba(height, width, maxiterations=20):\n", + " y, x = numpy.ogrid[-1:0:height*1j, -1.5:0:width*1j]\n", + " c = x + y*1j\n", + " fractal = numpy.full(c.shape, maxiterations, dtype=numpy.int32)\n", + " return tight_loop(height, width, maxiterations, c, fractal)\n", + "@numba.jit\n", + "def tight_loop(height, width, maxiterations, c, fractal):\n", + " for h in range(height):\n", + " for w in range(width): # for each pixel (h, w)...\n", + " z = c[h, w]\n", + " for i in range(maxiterations): # iterate at most 20 times\n", + " z = z**2 + c[h, w] # applying z → z² + c\n", + " if abs(z) > 2: # if it diverges (|z| > 2)\n", + " fractal[h, w] = i # color with the iteration number\n", + " break # we're done, no need to keep iterating\n", + " return fractal\n", + "\n", + "starttime = time.time()\n", + "fractal = run_numba(3200, 4800)\n", + "print(\"{0} ns per pixel\".format(1e9 * (time.time() - starttime) / (3200 * 4800)))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

The \"catch\" is that code in the loop must be purely numerical: arrays and basic number types. In other words, code that doesn't take advantage of \"Pythonness,\" code that would be just as easy to write in C.

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That's what @numba.jit does: it compiles the Python function (directly to LLVM and then machine code).

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So... why not just write C code?

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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "

If you developed your analysis in interactive Python, in a notebook or command prompt, isolating the numerical part into a function (\"tight_loop\" in the previous example) is usually easier than linking to code written in another library.

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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Fully rewriting in C++ isn't a lot faster (30% in this case), but a lot more effort.

\n", + "\n", + "| Method | time (ns/px) | speedup |\n", + "|:-------------------------------------------|-------------:|--------:|\n", + "| Pure Python | 12000 | 1× |\n", + "| Vectorized Numpy | 368 | 30× |\n", + "| Vectorized CuPy (run on GPU) | 81 | 150× |\n", + "| **Compiled by Numba** | **136** | **90×** |\n", + "| Compiled & parallelized by Numba | 45 | 250× |\n", + "| Compiled & run on GPU by Numba | 7.8 | 1500× |\n", + "| Parallelized by Dask | 238 | 50× |\n", + "| Parallelized by Dask, compiled by Numba | 48 | 250× |\n", + "| Partially rewritten in Cython (Python/C++ hybrid) | 1485 | 8× |\n", + "| **Completely rewritten in Cython (pure C++)** | **99** | **120×** |\n", + "| **Completely rewritten in pybind11 (pure C++)** | **98** | **120×** |\n", + "| Completely rewritten in ROOT (pure C++ with `-O0`) | 379 | 32× |\n", + "\n", + "_(See [misc-fractal.ipynb](misc-fractal.ipynb) for a derivation of the above.)_" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Drive/bike/skateboard on your daily commute: do exploration and problem-solving in Python because it has simple data structures, doesn't seg-fault, and dumps stack traces...

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Fly to Europe: optimize the loop that scales with big numbers so that you can finish analyzing your 100 TB this year...

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... by replacing critical code in small steps.

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

Numpy is the common (in-memory) data format for scientific Python.

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Nearly every package can input/output data as Numpy arrays.

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Numpy also has a suite of functions for doing calculations a whole array at a time: a Single (Python) Instruction on Multiple Data.

\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Names of arrays in this dict:\n", + "\n", + "['Type', 'Run', 'Event', 'E1', 'px1', 'py1', 'pz1', 'pt1', 'eta1', 'phi1', 'Q1', 'E2', 'px2', 'py2', 'pz2', 'pt2', 'eta2', 'phi2', 'Q2', 'M'] \n", + "\n", + "\n" + ] + }, + { + "data": { + "text/plain": [ + "{'Type': ,\n", + " 'Run': array([148031, 148031, 148031, ..., 148029, 148029, 148029], dtype=int32),\n", + " 'Event': array([10507008, 10507008, 10507008, ..., 99991333, 99991333, 99991333],\n", + " dtype=int32),\n", + " 'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " 'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " 'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " 'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247]),\n", + " 'pt1': array([44.7322, 38.8311, 38.8311, ..., 32.3997, 32.3997, 32.3997]),\n", + " 'eta1': array([-1.21769, -1.05139, -1.05139, ..., -1.57044, -1.57044, -1.57044]),\n", + " 'phi1': array([ 2.74126 , -0.440873 , -0.440873 , ..., 0.0370275, 0.0370275,\n", + " 0.0370275]),\n", + " 'Q1': array([ 1, -1, -1, ..., 1, 1, 1], dtype=int32),\n", + " 'E2': array([ 60.62187459, 82.20186639, 81.58277833, ..., 168.78012134,\n", + " 170.58313243, 170.58313243]),\n", + " 'px2': array([ 34.14443725, -41.19528764, -40.88332344, ..., -68.04191497,\n", + " -68.79413604, -68.79413604]),\n", + " 'py2': array([-16.11952457, 17.4332439 , 17.29929704, ..., -26.10584737,\n", + " -26.39840043, -26.39840043]),\n", + " 'pz2': array([ -47.42698439, -68.96496181, -68.44725519, ..., -152.2350181 ,\n", + " -153.84760383, -153.84760383]),\n", + " 'pt2': array([38.8311, 44.7322, 44.7322, ..., 72.8781, 72.8781, 72.8781]),\n", + " 'eta2': array([-1.05139, -1.21769, -1.21769, ..., -1.4827 , -1.4827 , -1.4827 ]),\n", + " 'phi2': array([-0.440873, 2.74126 , 2.74126 , ..., -2.77524 , -2.77524 ,\n", + " -2.77524 ]),\n", + " 'Q2': array([-1, 1, 1, ..., -1, -1, -1], dtype=int32),\n", + " 'M': array([82.46269156, 83.62620401, 83.30846467, ..., 95.96547966,\n", + " 96.49594381, 96.65672765])}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Numpy arrays of physics data:\n", + "import uproot\n", + "arrays = uproot.open(\"data/Zmumu.root\")[\"events\"].arrays(namedecode=\"utf-8\")\n", + "\n", + "print(\"Names of arrays in this dict:\\n\")\n", + "print(list(arrays), \"\\n\\n\")\n", + "\n", + "arrays" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Take arrays out of the dict and make each one a variable.\n", + "for n in arrays:\n", + " exec(f\"{n} = arrays['{n}']\")\n", + "\n", + "# Example array: energy of first muon in each event\n", + "E1" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 7.17219282, 6.13819068, 5.81117254, ..., 43.50036668,\n", + " 44.28500082, 44.19520441])" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Compute pT of all muon pairs:\n", + "\n", + "import numpy\n", + "\n", + "pt = numpy.sqrt((px1 + px2)**2 + (py1 + py2)**2)\n", + "pt" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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BSWxjk9hjPMY90TfQ2/v8MvDRKdbxy/Q+On0VeLr7uwH4W+DZrn0nsG7CdV1Kb8/7M8BzJ/sI+GlgF/BSd3nuFPrsx4FvAz/Z1zbx/qL35nIY+D96o6ZbT9U/wEe77W0f8N4J17Wf3nzsyW3sM926v9m9vs8ATwG/PuG6Br5u0+yvrv1e4PfnrTvJ/hqUDWPfxjz9gCQ1aDVPy0iSBjDcJalBhrskNchwl6QGGe6S1CDDXZIaZLhLUoP+HyiGPpN0uy9lAAAAAElFTkSuQmCC\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# And __LOOK__:\n", + "\n", + "matplotlib.pyplot.hist(pt, bins=100, range=(0, 200));" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([116.61271581, 117.90010197, 117.36645448, ..., 230.90205217,\n", + " 232.63405045, 232.88789491])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Compute p of all muon pairs:\n", + "\n", + "p = numpy.sqrt(pt**2 + (pz1 + pz2)**2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# And __LOOK__:\n", + "\n", + "matplotlib.pyplot.hist(p, bins=100, range=(0, 500));" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.46269156, 83.62620401, 83.30846467, ..., 95.96547966,\n", + " 96.49594382, 96.65672765])" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Compute mass of all muon pairs:\n", + "\n", + "mass = numpy.sqrt((E1 + E2)**2 - p**2)\n", + "mass" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# And __LOOK__:\n", + "\n", + "matplotlib.pyplot.hist(mass, bins=100, range=(0, 120));" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Start adding cuts, exploring different regions, etc.\n", + "\n", + "matplotlib.pyplot.hist(mass[Q1 != Q2], bins=100, range=(0, 120));\n", + "matplotlib.pyplot.hist(mass[Q1 == Q2], bins=100, range=(0, 120));" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

This is the point: you calculate one thing and then you LOOK at the result.

\n", + "\n", + "
\n", + "\n", + "

Array-at-a-time logic gives you a statistical view of each step in your calculation as you develop it.

\n", + "\n", + "
\n", + "\n", + "

It's not always about the speed; sometimes it's about the interactivity.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Welcome to JupyROOT 6.18/00\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# As physicists, we know this. That's why we have TTree-at-a-time operations.\n", + "\n", + "import ROOT\n", + "canvas = ROOT.TCanvas(\"canvas\", \"\", 400, 300)\n", + "file = ROOT.TFile(\"data/Zmumu.root\")\n", + "tree = file.Get(\"events\")\n", + "tree.Draw(\"sqrt((E1 + E2)**2 - (px1 + px2)**2 - (py1 + py2)**2 - (pz1 + pz2)**2)\")\n", + "canvas.Draw()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

The hard part is turning those TTree::Draw expressions into a full analysis.

\n", + "\n", + "
\n", + "\n", + "

How many of you have started with TTree::Draw and had to rewrite everything as a C++ loop?

\n", + "\n", + "
\n", + "\n", + "

Our goal is to do initial exploration in a convenient way and then scale up without having to change everything.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### Part 2: There's an app for that\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "(Stolen from Jake Vanderplas.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "(Stolen from Jake Vanderplas.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "(Stolen from Jake Vanderplas.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "(Stolen from Jake Vanderplas.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "\n", + "(Stolen from Jake Vanderplas.)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Much of what we do, as physicists, are not new problems. You can learn a lot by attempting to write an algorithm yourself, but eventually you'll want to plug together functions from established libraries (that you understand!).

\n", + "\n", + "
\n", + "\n", + "

Wikipedia (to learn the names of things) + StackOverflow (to find common solutions) is a good way to develop analysis code.

\n", + "\n", + "
\n", + "\n", + "

Most of these solutions come in Numpy-shaped pieces.

\n", + "\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

=

\n", + "\n", + "

" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

SciPy was originally the \"all in one\" scientific package, but today, much of the development is beyond SciPy.

\n", + "\n", + "| Date | Development |\n", + "|:----:|:-----|\n", + "| 1994 | **Python** 1.0 released. |\n", + "| 1995 | **Numeric** was the first array package (a.k.a. Numerical, Numerical Python, Numpy). |\n", + "| 2001 | **SciPy** gathered scientific functions into one codebase, including **Numeric**. |\n", + "| 2003 | **Matplotlib** released (at that time, one of many plotters... R.I.P. **Biggles**). |\n", + "| 2003 | **Numarray** introduced as a competitor to **Numeric** with more features (memory-mapped files, alignment, record arrays). |\n", + "| 2005 | **Numpy** unified features of **Numeric** and **Numarray** and became the common array library. |\n", + "| 2008 | **Pandas** first released. |\n", + "| 2010 | **Scikit-Learn** first released. |\n", + "| 2011 | **AstroPy** first released. |\n", + "| 2012 | **Anaconda** first released. |\n", + "| 2014 | **Jupyter** first released. |\n", + "| 2015 | **Keras** first released. |" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\u001b[0;31mType:\u001b[0m module\n", + "\u001b[0;31mString form:\u001b[0m \n", + "\u001b[0;31mFile:\u001b[0m ~/miniconda3/lib/python3.7/site-packages/scipy/stats/__init__.py\n", + "\u001b[0;31mDocstring:\u001b[0m \n", + "==========================================\n", + "Statistical functions (:mod:`scipy.stats`)\n", + "==========================================\n", + "\n", + ".. currentmodule:: scipy.stats\n", + "\n", + "This module contains a large number of probability distributions as\n", + "well as a growing library of statistical functions.\n", + "\n", + "Each univariate distribution is an instance of a subclass of `rv_continuous`\n", + "(`rv_discrete` for discrete distributions):\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " rv_continuous\n", + " rv_discrete\n", + " rv_histogram\n", + "\n", + "Continuous distributions\n", + "========================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " alpha -- Alpha\n", + " anglit -- Anglit\n", + " arcsine -- Arcsine\n", + " argus -- Argus\n", + " beta -- Beta\n", + " betaprime -- Beta Prime\n", + " bradford -- Bradford\n", + " burr -- Burr (Type III)\n", + " burr12 -- Burr (Type XII)\n", + " cauchy -- Cauchy\n", + " chi -- Chi\n", + " chi2 -- Chi-squared\n", + " cosine -- Cosine\n", + " crystalball -- Crystalball\n", + " dgamma -- Double Gamma\n", + " dweibull -- Double Weibull\n", + " erlang -- Erlang\n", + " expon -- Exponential\n", + " exponnorm -- Exponentially Modified Normal\n", + " exponweib -- Exponentiated Weibull\n", + " exponpow -- Exponential Power\n", + " f -- F (Snecdor F)\n", + " fatiguelife -- Fatigue Life (Birnbaum-Saunders)\n", + " fisk -- Fisk\n", + " foldcauchy -- Folded Cauchy\n", + " foldnorm -- Folded Normal\n", + " frechet_r -- Deprecated. Alias for weibull_min\n", + " frechet_l -- Deprecated. Alias for weibull_max\n", + " genlogistic -- Generalized Logistic\n", + " gennorm -- Generalized normal\n", + " genpareto -- Generalized Pareto\n", + " genexpon -- Generalized Exponential\n", + " genextreme -- Generalized Extreme Value\n", + " gausshyper -- Gauss Hypergeometric\n", + " gamma -- Gamma\n", + " gengamma -- Generalized gamma\n", + " genhalflogistic -- Generalized Half Logistic\n", + " gilbrat -- Gilbrat\n", + " gompertz -- Gompertz (Truncated Gumbel)\n", + " gumbel_r -- Right Sided Gumbel, Log-Weibull, Fisher-Tippett, Extreme Value Type I\n", + " gumbel_l -- Left Sided Gumbel, etc.\n", + " halfcauchy -- Half Cauchy\n", + " halflogistic -- Half Logistic\n", + " halfnorm -- Half Normal\n", + " halfgennorm -- Generalized Half Normal\n", + " hypsecant -- Hyperbolic Secant\n", + " invgamma -- Inverse Gamma\n", + " invgauss -- Inverse Gaussian\n", + " invweibull -- Inverse Weibull\n", + " johnsonsb -- Johnson SB\n", + " johnsonsu -- Johnson SU\n", + " kappa4 -- Kappa 4 parameter\n", + " kappa3 -- Kappa 3 parameter\n", + " ksone -- Kolmogorov-Smirnov one-sided (no stats)\n", + " kstwobign -- Kolmogorov-Smirnov two-sided test for Large N (no stats)\n", + " laplace -- Laplace\n", + " levy -- Levy\n", + " levy_l\n", + " levy_stable\n", + " logistic -- Logistic\n", + " loggamma -- Log-Gamma\n", + " loglaplace -- Log-Laplace (Log Double Exponential)\n", + " lognorm -- Log-Normal\n", + " lomax -- Lomax (Pareto of the second kind)\n", + " maxwell -- Maxwell\n", + " mielke -- Mielke's Beta-Kappa\n", + " moyal -- Moyal\n", + " nakagami -- Nakagami\n", + " ncx2 -- Non-central chi-squared\n", + " ncf -- Non-central F\n", + " nct -- Non-central Student's T\n", + " norm -- Normal (Gaussian)\n", + " norminvgauss -- Normal Inverse Gaussian\n", + " pareto -- Pareto\n", + " pearson3 -- Pearson type III\n", + " powerlaw -- Power-function\n", + " powerlognorm -- Power log normal\n", + " powernorm -- Power normal\n", + " rdist -- R-distribution\n", + " reciprocal -- Reciprocal\n", + " rayleigh -- Rayleigh\n", + " rice -- Rice\n", + " recipinvgauss -- Reciprocal Inverse Gaussian\n", + " semicircular -- Semicircular\n", + " skewnorm -- Skew normal\n", + " t -- Student's T\n", + " trapz -- Trapezoidal\n", + " triang -- Triangular\n", + " truncexpon -- Truncated Exponential\n", + " truncnorm -- Truncated Normal\n", + " tukeylambda -- Tukey-Lambda\n", + " uniform -- Uniform\n", + " vonmises -- Von-Mises (Circular)\n", + " vonmises_line -- Von-Mises (Line)\n", + " wald -- Wald\n", + " weibull_min -- Minimum Weibull (see Frechet)\n", + " weibull_max -- Maximum Weibull (see Frechet)\n", + " wrapcauchy -- Wrapped Cauchy\n", + "\n", + "Multivariate distributions\n", + "==========================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " multivariate_normal -- Multivariate normal distribution\n", + " matrix_normal -- Matrix normal distribution\n", + " dirichlet -- Dirichlet\n", + " wishart -- Wishart\n", + " invwishart -- Inverse Wishart\n", + " multinomial -- Multinomial distribution\n", + " special_ortho_group -- SO(N) group\n", + " ortho_group -- O(N) group\n", + " unitary_group -- U(N) group\n", + " random_correlation -- random correlation matrices\n", + "\n", + "Discrete distributions\n", + "======================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " bernoulli -- Bernoulli\n", + " binom -- Binomial\n", + " boltzmann -- Boltzmann (Truncated Discrete Exponential)\n", + " dlaplace -- Discrete Laplacian\n", + " geom -- Geometric\n", + " hypergeom -- Hypergeometric\n", + " logser -- Logarithmic (Log-Series, Series)\n", + " nbinom -- Negative Binomial\n", + " planck -- Planck (Discrete Exponential)\n", + " poisson -- Poisson\n", + " randint -- Discrete Uniform\n", + " skellam -- Skellam\n", + " zipf -- Zipf\n", + " yulesimon -- Yule-Simon\n", + "\n", + "An overview of statistical functions is given below.\n", + "Several of these functions have a similar version in\n", + "`scipy.stats.mstats` which work for masked arrays.\n", + "\n", + "Summary statistics\n", + "==================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " describe -- Descriptive statistics\n", + " gmean -- Geometric mean\n", + " hmean -- Harmonic mean\n", + " kurtosis -- Fisher or Pearson kurtosis\n", + " mode -- Modal value\n", + " moment -- Central moment\n", + " skew -- Skewness\n", + " kstat --\n", + " kstatvar --\n", + " tmean -- Truncated arithmetic mean\n", + " tvar -- Truncated variance\n", + " tmin --\n", + " tmax --\n", + " tstd --\n", + " tsem --\n", + " variation -- Coefficient of variation\n", + " find_repeats\n", + " trim_mean\n", + " gstd -- Geometric Standard Deviation\n", + " iqr\n", + " sem\n", + " bayes_mvs\n", + " mvsdist\n", + " entropy\n", + " median_absolute_deviation\n", + "\n", + "Frequency statistics\n", + "====================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " cumfreq\n", + " itemfreq\n", + " percentileofscore\n", + " scoreatpercentile\n", + " relfreq\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " binned_statistic -- Compute a binned statistic for a set of data.\n", + " binned_statistic_2d -- Compute a 2-D binned statistic for a set of data.\n", + " binned_statistic_dd -- Compute a d-D binned statistic for a set of data.\n", + "\n", + "Correlation functions\n", + "=====================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " f_oneway\n", + " pearsonr\n", + " spearmanr\n", + " pointbiserialr\n", + " kendalltau\n", + " weightedtau\n", + " linregress\n", + " siegelslopes\n", + " theilslopes\n", + "\n", + "Statistical tests\n", + "=================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " ttest_1samp\n", + " ttest_ind\n", + " ttest_ind_from_stats\n", + " ttest_rel\n", + " kstest\n", + " chisquare\n", + " power_divergence\n", + " ks_2samp\n", + " epps_singleton_2samp\n", + " mannwhitneyu\n", + " tiecorrect\n", + " rankdata\n", + " ranksums\n", + " wilcoxon\n", + " kruskal\n", + " friedmanchisquare\n", + " brunnermunzel\n", + " combine_pvalues\n", + " jarque_bera\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " ansari\n", + " bartlett\n", + " levene\n", + " shapiro\n", + " anderson\n", + " anderson_ksamp\n", + " binom_test\n", + " fligner\n", + " median_test\n", + " mood\n", + " skewtest\n", + " kurtosistest\n", + " normaltest\n", + "\n", + "Transformations\n", + "===============\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " boxcox\n", + " boxcox_normmax\n", + " boxcox_llf\n", + " yeojohnson\n", + " yeojohnson_normmax\n", + " yeojohnson_llf\n", + " obrientransform\n", + " sigmaclip\n", + " trimboth\n", + " trim1\n", + " zmap\n", + " zscore\n", + "\n", + "Statistical distances\n", + "=====================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " wasserstein_distance\n", + " energy_distance\n", + "\n", + "Random variate generation\n", + "=========================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " rvs_ratio_uniforms\n", + "\n", + "Circular statistical functions\n", + "==============================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " circmean\n", + " circvar\n", + " circstd\n", + "\n", + "Contingency table functions\n", + "===========================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " chi2_contingency\n", + " contingency.expected_freq\n", + " contingency.margins\n", + " fisher_exact\n", + "\n", + "Plot-tests\n", + "==========\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " ppcc_max\n", + " ppcc_plot\n", + " probplot\n", + " boxcox_normplot\n", + " yeojohnson_normplot\n", + "\n", + "\n", + "Masked statistics functions\n", + "===========================\n", + "\n", + ".. toctree::\n", + "\n", + " stats.mstats\n", + "\n", + "\n", + "Univariate and multivariate kernel density estimation\n", + "=====================================================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " gaussian_kde\n", + "\n", + "Warnings used in :mod:`scipy.stats`\n", + "===================================\n", + "\n", + ".. autosummary::\n", + " :toctree: generated/\n", + "\n", + " PearsonRConstantInputWarning\n", + " PearsonRNearConstantInputWarning\n", + "\n", + "For many more stat related functions install the software R and the\n", + "interface package rpy.\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import scipy.stats\n", + "\n", + "?scipy.stats" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\u001b[0;31mSignature:\u001b[0m \u001b[0mscipy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstats\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcrystalball\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mType:\u001b[0m crystalball_gen\n", + "\u001b[0;31mString form:\u001b[0m \n", + "\u001b[0;31mFile:\u001b[0m ~/miniconda3/lib/python3.7/site-packages/scipy/stats/_continuous_distns.py\n", + "\u001b[0;31mDocstring:\u001b[0m \n", + "Crystalball distribution\n", + "\n", + "As an instance of the `rv_continuous` class, `crystalball` object inherits from it\n", + "a collection of generic methods (see below for the full list),\n", + "and completes them with details specific for this particular distribution.\n", + "\n", + "Methods\n", + "-------\n", + "rvs(beta, m, loc=0, scale=1, size=1, random_state=None)\n", + " Random variates.\n", + "pdf(x, beta, m, loc=0, scale=1)\n", + " Probability density function.\n", + "logpdf(x, beta, m, loc=0, scale=1)\n", + " Log of the probability density function.\n", + "cdf(x, beta, m, loc=0, scale=1)\n", + " Cumulative distribution function.\n", + "logcdf(x, beta, m, loc=0, scale=1)\n", + " Log of the cumulative distribution function.\n", + "sf(x, beta, m, loc=0, scale=1)\n", + " Survival function (also defined as ``1 - cdf``, but `sf` is sometimes more accurate).\n", + "logsf(x, beta, m, loc=0, scale=1)\n", + " Log of the survival function.\n", + "ppf(q, beta, m, loc=0, scale=1)\n", + " Percent point function (inverse of ``cdf`` --- percentiles).\n", + "isf(q, beta, m, loc=0, scale=1)\n", + " Inverse survival function (inverse of ``sf``).\n", + "moment(n, beta, m, loc=0, scale=1)\n", + " Non-central moment of order n\n", + "stats(beta, m, loc=0, scale=1, moments='mv')\n", + " Mean('m'), variance('v'), skew('s'), and/or kurtosis('k').\n", + "entropy(beta, m, loc=0, scale=1)\n", + " (Differential) entropy of the RV.\n", + "fit(data, beta, m, loc=0, scale=1)\n", + " Parameter estimates for generic data.\n", + "expect(func, args=(beta, m), loc=0, scale=1, lb=None, ub=None, conditional=False, **kwds)\n", + " Expected value of a function (of one argument) with respect to the distribution.\n", + "median(beta, m, loc=0, scale=1)\n", + " Median of the distribution.\n", + "mean(beta, m, loc=0, scale=1)\n", + " Mean of the distribution.\n", + "var(beta, m, loc=0, scale=1)\n", + " Variance of the distribution.\n", + "std(beta, m, loc=0, scale=1)\n", + " Standard deviation of the distribution.\n", + "interval(alpha, beta, m, loc=0, scale=1)\n", + " Endpoints of the range that contains alpha percent of the distribution\n", + "\n", + "Notes\n", + "-----\n", + "The probability density function for `crystalball` is:\n", + "\n", + ".. math::\n", + "\n", + " f(x, \\beta, m) = \\begin{cases}\n", + " N \\exp(-x^2 / 2), &\\text{for } x > -\\beta\\\\\n", + " N A (B - x)^{-m} &\\text{for } x \\le -\\beta\n", + " \\end{cases}\n", + "\n", + "where :math:`A = (m / |\\beta|)^n \\exp(-\\beta^2 / 2)`,\n", + ":math:`B = m/|\\beta| - |\\beta|` and :math:`N` is a normalisation constant.\n", + "\n", + "`crystalball` takes :math:`\\beta > 0` and :math:`m > 1` as shape\n", + "parameters. :math:`\\beta` defines the point where the pdf changes\n", + "from a power-law to a Gaussian distribution. :math:`m` is the power\n", + "of the power-law tail.\n", + "\n", + "References\n", + "----------\n", + ".. [1] \"Crystal Ball Function\",\n", + " https://en.wikipedia.org/wiki/Crystal_Ball_function\n", + "\n", + "The probability density above is defined in the \"standardized\" form. To shift\n", + "and/or scale the distribution use the ``loc`` and ``scale`` parameters.\n", + "Specifically, ``crystalball.pdf(x, beta, m, loc, scale)`` is identically\n", + "equivalent to ``crystalball.pdf(y, beta, m) / scale`` with\n", + "``y = (x - loc) / scale``.\n", + "\n", + ".. versionadded:: 0.19.0\n", + "\n", + "Examples\n", + "--------\n", + ">>> from scipy.stats import crystalball\n", + ">>> import matplotlib.pyplot as plt\n", + ">>> fig, ax = plt.subplots(1, 1)\n", + "\n", + "Calculate a few first moments:\n", + "\n", + ">>> beta, m = 2, 3\n", + ">>> mean, var, skew, kurt = crystalball.stats(beta, m, moments='mvsk')\n", + "\n", + "Display the probability density function (``pdf``):\n", + "\n", + ">>> x = np.linspace(crystalball.ppf(0.01, beta, m),\n", + "... crystalball.ppf(0.99, beta, m), 100)\n", + ">>> ax.plot(x, crystalball.pdf(x, beta, m),\n", + "... 'r-', lw=5, alpha=0.6, label='crystalball pdf')\n", + "\n", + "Alternatively, the distribution object can be called (as a function)\n", + "to fix the shape, location and scale parameters. This returns a \"frozen\"\n", + "RV object holding the given parameters fixed.\n", + "\n", + "Freeze the distribution and display the frozen ``pdf``:\n", + "\n", + ">>> rv = crystalball(beta, m)\n", + ">>> ax.plot(x, rv.pdf(x), 'k-', lw=2, label='frozen pdf')\n", + "\n", + "Check accuracy of ``cdf`` and ``ppf``:\n", + "\n", + ">>> vals = crystalball.ppf([0.001, 0.5, 0.999], beta, m)\n", + ">>> np.allclose([0.001, 0.5, 0.999], crystalball.cdf(vals, beta, m))\n", + "True\n", + "\n", + "Generate random numbers:\n", + "\n", + ">>> r = crystalball.rvs(beta, m, size=1000)\n", + "\n", + "And compare the histogram:\n", + "\n", + ">>> ax.hist(r, density=True, histtype='stepfilled', alpha=0.2)\n", + ">>> ax.legend(loc='best', frameon=False)\n", + ">>> plt.show()\n", + "\u001b[0;31mClass docstring:\u001b[0m\n", + "Crystalball distribution\n", + "\n", + "%(before_notes)s\n", + "\n", + "Notes\n", + "-----\n", + "The probability density function for `crystalball` is:\n", + "\n", + ".. math::\n", + "\n", + " f(x, \\beta, m) = \\begin{cases}\n", + " N \\exp(-x^2 / 2), &\\text{for } x > -\\beta\\\\\n", + " N A (B - x)^{-m} &\\text{for } x \\le -\\beta\n", + " \\end{cases}\n", + "\n", + "where :math:`A = (m / |\\beta|)^n \\exp(-\\beta^2 / 2)`,\n", + ":math:`B = m/|\\beta| - |\\beta|` and :math:`N` is a normalisation constant.\n", + "\n", + "`crystalball` takes :math:`\\beta > 0` and :math:`m > 1` as shape\n", + "parameters. :math:`\\beta` defines the point where the pdf changes\n", + "from a power-law to a Gaussian distribution. :math:`m` is the power\n", + "of the power-law tail.\n", + "\n", + "References\n", + "----------\n", + ".. [1] \"Crystal Ball Function\",\n", + " https://en.wikipedia.org/wiki/Crystal_Ball_function\n", + "\n", + "%(after_notes)s\n", + "\n", + ".. versionadded:: 0.19.0\n", + "\n", + "%(example)s\n", + "\u001b[0;31mCall docstring:\u001b[0m \n", + "Freeze the distribution for the given arguments.\n", + "\n", + "Parameters\n", + "----------\n", + "arg1, arg2, arg3,... : array_like\n", + " The shape parameter(s) for the distribution. Should include all\n", + " the non-optional arguments, may include ``loc`` and ``scale``.\n", + "\n", + "Returns\n", + "-------\n", + "rv_frozen : rv_frozen instance\n", + " The frozen distribution.\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "?scipy.stats.crystalball" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "x = numpy.linspace(-10, 10, 100)\n", + "y = scipy.stats.crystalball.pdf(x, beta=0.5, m=3) # logpdf, cdf\n", + "\n", + "matplotlib.pyplot.plot(x, y);" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([-1.72036316e+01, 8.08046936e-01, -1.85733936e+00, 4.92263362e-01,\n", + " 9.26366172e-01, -2.30836227e+00, 3.53437752e-01, -3.06067775e+00,\n", + " 6.25901639e-01, -1.98501416e+00, -1.65142187e+00, -2.32275116e+00,\n", + " -1.13710699e+00, 9.74515753e-01, 7.30925579e-01, -1.94252669e+00,\n", + " 2.52104159e-01, 5.55644666e-01, -8.07996359e-01, -2.37753843e+00,\n", + " -2.12872716e-01, -1.07055842e+00, -1.56621942e+01, -1.09019963e+01,\n", + " -6.11083898e-01, 4.79215244e-01, 1.47046094e-01, -4.08126405e+00,\n", + " 2.60885207e+00, -2.56094530e+00, -4.06260669e+00, -1.54755267e+00,\n", 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "masses = uproot.open(\"data/Zmumu.root\")[\"events\"].array(\"M\")\n", + "\n", + "y, edges = numpy.histogram(masses, bins=100)\n", + "yerr = numpy.sqrt(y)\n", + "\n", + "# the middle of each bin\n", + "x = (edges[1:] + edges[:-1])/2\n", + "\n", + "matplotlib.pyplot.errorbar(x, y, yerr, fmt=\"o\", capsize=3);" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import scipy.optimize\n", + "\n", + "def f(x, a, b, c, d):\n", + " return a*scipy.stats.cauchy.pdf(x, b, c) + d/x**2\n", + "\n", + "parameters, errors = scipy.optimize.curve_fit(f, x[y > 0], y[y > 0], sigma=yerr[y > 0]) # exclude y == 0\n", + "\n", + "matplotlib.pyplot.plot(x, f(x, *parameters))\n", + "matplotlib.pyplot.errorbar(x, y, yerr, fmt=\"o\", capsize=3);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Five minute challenge: using only commands from the previous cell, plot the fit residuals.

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import iminuit\n", + "\n", + "def chi2(a, b, c, d):\n", + " return ((y[y > 0] - f(x[y > 0], a, b, c, d))**2 / yerr[y > 0]**2).sum()\n", + "\n", + "m = iminuit.Minuit(chi2, errordef=1,\n", + " a=3350, b=91, c=2, d=30,\n", + " error_a=100, error_b=1, error_c=0.1, error_d=10)\n", + "m.migrad()\n", + "m.hesse()\n", + "m.minos()\n", + "m.draw_mncontour(\"a\", \"b\", nsigma=4);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "
\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

To branch out in a modular way, SciPy introduced the idea of \"SciKits\"—separate packages from SciPy that have a similar interface.

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\n", + "\n", + "

The most famous of these is Scikit-Learn, a package that gathered all machine learning algorithms under one roof—just before the deep learning revolution...

\n", + "\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import sklearn.datasets\n", + "X1, y1 = sklearn.datasets.make_gaussian_quantiles(\n", + " cov=2.0, n_samples=800, n_features=2, n_classes=2, random_state=1)\n", + "X2, y2 = sklearn.datasets.make_gaussian_quantiles(\n", + " mean=(3, 3), cov=1.5, n_samples=1200, n_features=2, n_classes=2, random_state=1)\n", + "X = numpy.concatenate((X1, X2))\n", + "y = numpy.concatenate((y1, -y2 + 1))\n", + "\n", + "# Example of a hard classification problem.\n", + "matplotlib.pyplot.scatter(X[y == 0, 0], X[y == 0, 1], c=\"deepskyblue\", edgecolor=\"k\");\n", + "matplotlib.pyplot.scatter(X[y == 1, 0], X[y == 1, 1], c=\"orange\", edgecolor=\"k\");" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "predictions:\n", + " [0 1 1 ... 0 0 1]\n", + "truth:\n", + " [0 1 1 ... 0 0 1]\n" + ] + } + ], + "source": [ + "import sklearn.tree\n", + "\n", + "# Example model: decision tree classifier\n", + "model = sklearn.tree.DecisionTreeClassifier(max_depth=10)\n", + "\n", + "# Consistent interface: nearly every model has a fit method with this signature\n", + "model.fit(X, y)\n", + "\n", + "print(\"predictions:\\n\", model.predict(X))\n", + "print(\"truth:\\n\", y)" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "predictions:\n", + " [0 1 0 ... 1 1 1]\n", + "truth:\n", + " [0 1 1 ... 0 0 1]\n" + ] + } + ], + "source": [ + "import sklearn.ensemble\n", + "\n", + "# Another model: boosted decision tree\n", + "model = sklearn.ensemble.AdaBoostClassifier(\n", + " sklearn.tree.DecisionTreeClassifier(max_depth=2), algorithm=\"SAMME\", n_estimators=100)\n", + "\n", + "model.fit(X, y)\n", + "\n", + "print(\"predictions:\\n\", model.predict(X))\n", + "print(\"truth:\\n\", y)" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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DKnIKUWFh4iqrzl//HGphr3nmeNKF4lGLQ2RZqCpDGYLUrCgNQZqHuFkK/uKd81WVHQeFH1gEtGWibQeKu69Jr4U/L3EPR3fcPq5qoZ0J3Op7dTtuEJsJrrtIGk3RrQWU1mjTIK1CrO4Klu2hZyMKKZjPDlgZl3cWh7xImQYBVmMFghW0YTCfD3HHY8ZiSuVa5CLBN0zcKGemKhJLozoLCNcjPBrRmic4lcavHGbxkMIOiB2F7K6hywjtNpiqAhUdkZcxzvJl4irDOtpAZCl+Y5VSTElJ0e0eVmMBVR0gtQPNBfIkRd4TC7kdCFeGIDYTSkcgjADmWyzpx68nmAYWurFA2rARwSJpOkeGMeV0VOevP4Ja2GteSB66OBQpg/EWyenTWMEaQimM4Yy8jMnSEbbTJatmRPNdVJUzZUJD+1jiWOBFUSJkBuLuBmEyz5D6s24f8ZAWuKUjMO02XpaRRjcphpt4629glBFB7wLScKjsZeT+Bn7zAvnsJo0HRLKhFfNJH91dQ1sOAy9HuR0a9jJzNWGgjrCyBG/hHJEqsPweorOEbqwyev+f0SsNFBpxuEtcKvTKGsb4CG+0T+o5iPXXMHeuYRz1qdI/RygTI6nwhQ9egakFWRVTFZpstomV5ZSqhWE4ZBQ07/ncpSlAQtQ0MZormNK+ZbXvE4weT5Bvf+6YGKO3jmF5KMulyPbw6/z1R1ILe80vDbZ0saIhxTQkj0OUUICkbLboH76LFBaVIWm5qzQ7S8QSpnZFO0kxFNjhBC0kVde74+KxxkcIrajMzmdiAjl3XQjJ/CaaHro5JalC4skOUKIoERqUUqRMKYUGHeJqh+KeNgVTZlAdkbsmKkuQ2/soXaC9FjKumLRSDGcRbUB8dJPSKY9FcD7EmI+gsQR+g8zx8OYpC846w0mfZl5SHfSht4LqnsXAo4oiWs2LzDwQ8ynCsbHmJcnOh9jKIWsaiIVT6DJHNBeI0xR7dogY7R9nGd2qRk1UzMyaYrin8LTGFAK0RpoefWeMJ6tf6He//bRTqgjzlltMSJvSEF9pWuXzTi3sNS80DwbvSinx7Q5RywK3QeJZ6EaTrGnj2V1M00IUJmkU4s8SsiRkPt2nk7ss3E6NTO+6eBYLEzCIsvvdPsAd/7JnOBjZmNHwU6J4C1bO4V34NYoiZG5J5HSbmd6F5hKyVLh+g3EyRXgCJ7hASc7Ea5DbAs9bxAlOQRGRXf9LbL+FaC0i1s8gbB+ONigmfXQnwHED2n6HKh6T9Tcw5nOYDfBEh7TVpKgCCssgSCXJaB9JAV4LOymplnu4rk86HVAlGcVszuIwIWxIrMZpCEcEZgM1PyQvZmRbn3Bu7GCbzTvuE7dxnqmlEd1F4jTCiSbo0S6l55AGp6hkC5lnJIMjFmcPt+BvP+2YCFSZHrdVUDlmpev89c+hFvaaF5aHBe+y6XViHWI3r5CSIoMlCp1id09TorDdBWZ7H2N4Hvl8Tk8uodWEbtW44+t/mP//wdfGxvy+QivpNNC9ZbTMMIMVKDOseUSWHTLtNTBOncFrrlON9kibNioa0eqsoqRg3DYxVt/A6C5QjAcIXWAZNrmhsd0mhtvALySlSqikwjGbGGGKbIJhNcBR6MPrdN1TyGifsG0RLy+ijHXyg08xO0uIaIavXfJwdLxAtBaQZY6rTJZlFxlodHwTTwraLFGGOakZURoCrzQwU/tOV8l7i8xa8YDscItSV5RHBxiVprhwEdNwsWihVU7iOkw/ufZQv/vtQLjdaBON9lDBIjqd42cl1XRU568/glrYa14IHpZW97AqVquxyCDZxlZLpCJFxhzvlNM8R54Oydogeku4vUuU1lXC8ZhWlvJgYc4vSuO7t9Cq0BnzpomSKwhyvIWLlNNdtOOirQWMbhMjTamO3sHxesiVS1T9XaTbJFUVqhlQ2hbKdNDxEMNbQA72cEsL4gnC8qGpscsSazzB8ZZxS4fZx39J2lg8DhJnE0ZVgS0L8uVTWKeuYCuNEc2o0gh98CmFUviNVeKWhzncwhwf0osMLNtBG/rOE4mqMizTxbq1mFVlilDWQz97U7SgMvAaSygrYs4Y3BZeYSCEQBgOVrDG3L3KUvLZ3/VuIPwAd5BTiE+wMLHrrJjPpRb2mueeR6XVlUn8mTL6vLeAubdNEQ1RDRctNGawTq4LSOZoQ2CYDqrKkeJWFowQoB/9flk1YzzfxZuPcLVNozDvK7RKzQqjuYIRHSCzOdl0hzQZQLAMpcLuncW2W9hdgehv4Pg9QuM4MJtZBoXvgd/CcFxkZx3DaiL7O1jCxgkz5GyL+Wgby+vgViUCgYnBUtpgIuZUDQcnF2AZTFY9lCNxZ3uIJMZrLSDaK+SjfVq08JRNOR1BXtLLPDy7C9wtEnucOoP7NvQQDs15RjTfgKNtpExxohzTCe58n1opxOd4VO4Ewh+kttQfSS3sNc8l91rMiYpxgkvYD/SXSdIRTpWhtCIVKTMzpSptKiqwLFyrTYUBjk+Vx4g8xun3kVpTToY0pxkN5YLtkCcPf79ZvMeRn1EtNbDsiiXVpswK/HFKfEsACwtkVaEPt8jtnKoYoxwbEXSp9vrI+YjSLdBeF0OlGNEQexJiaZN4qY1RadKjm5SbE5zmKrmqSKM+jdGAyrFxOudoFBYqGcP8EJ3FqGCd0JEUlo2ZK8zlixjBCkm8Sakz8sEG7aVXoL1MfPQphm3hE9CqfDw8QjIyC1x9t2rWkRVY4I9T8jh5ZJ3Bg+IvK40/neLPTQ5tmA2vUfbO4BhtJFANt2ildROvk6QW9prnjgct5lnZp2r7GFF2JzVRGg4WJtlog2RlBWPhHIWMyMwK7Zn4Cy+hTCgHm8jJEQFN5oc3cLoC3w5uFf90qFRKdU9/l3vfrxjs0e8JjNd+B7uxQH7jp+zvfUpDFCRewcJ4Rh4nYKdU4wMq36Fx6TcobZN5vEu1+xFWXlH2N/ACH3k4Jtm5gRqGXIxKTF0xibbJzBR7/Qp25yJ5FZNvvk3jqI+3/Dqi1SFLR5CEWOGMhWFG3O1SOE0qH7RtU1UpTrCCaHUxnAyj4aFaijyNccuCKjzAKitcDBBgWT7tTDMffUJSyvv2O737dJLjlvZD3SEPqyO4vaWg3VoDG2bFmPn4Ju2oojkvCVSjtsBPkFrYa547HvSd28KhdJuk2ejY78ux68BVFmWSYSjQ4SGaEP/8N8m9Dmk6wPLPYHRP4xwOWKRJN2qByFBByUzEzPQueTzEMkNaTpu2VihySkOTNW3S6Ri9/h0QkA2uURZj9IWLxJMBjbaH6If0piVNJenbI/LuZXy7gW3aWKJDIgUQs15cI8gtisNP6VY7uI0cR56hYVbkeULfWkZkkiqLsUWOal3AsTfxnBFmfkTDNFFSgdMhauzSajuoMiSeVMyWW6S+JA6v4jmXkO1FrCxEJxFZ/yaSGzjjA3zlYVl33VZSGgTF8fd7e7/TQmckQQO5/CZZf4MExU5ygBePCXKHoPLviPzDthTMW02mCz7Cb2GjwPQoBu/TDh1s824Mo94h6cmphf0F5D//4f/xmdf+1vf/Pbz3d5/CbE6eBztAutplNh2Q6ZKm9u7z+049QUAHkQsqsyDJUlTTpUiHmI0AZZnkliA93GKx8inGM/rViNlyF7V6Htf/NZJsyHwWU0ymmE4Tq3GOUmsyW6CbPlanQzHZpjx3Gbl4Bg42KTLNXuNDRtc/ZbX7Bp6IyE2H8vBHNIoMX3Sp7BZ69AG9TkUQHrLeGvLGqy4qy9nfv8ZgfEhXBoyiDYz2cffMQXSTlfRtAvcaXbNPw/cplMU4i6nEmLKVs+CmxNpi2FhErbxGU86w5nvk6XXykYXltpF5CvMYP83o5E3SMqRqpp/xmw/tmFJHVFVELjIs+xzCdpkYM3R3iarzG5SzKXqWUuwfPjJtMZUFYcdBnnoZy26gVUkVjzHbh+RxdKcQq94h6WSohf2XhL/3h/8Nf/C933/a0zgRHuwAaVk+jWhEOtygkP79ft9syDQ7QFsWlcpQ4RHSO4UTpxibHyLzHCOKyJIJU69LogpEewlv5RJi8QzSsFC+h7JGpChcbJpej/zwY8rxHlU+oRrkEPYxv/1XUCqnMjXm+hXyts/cgrCzTnW0zbn2hGCphaUaWGYDY2+XkZ7h9VZZKPe41MlpuzGuE9NzFEdLJdbRlMnkPcIYohxOJz/jty4XBLKg0ROMJiMMy6Bszzi7INnaS2gsJPSnh1SVQE5+SG+pBdUGpbfGweSIsPs9kBKjd5posENrOGAlksSTjwldjRbH7ZgLJZm7miJwELZHKhJMHUE0IfMs3CvfxfQ7VIebFH5IkmZE6eihgc6CkspxcezGrWwYC2W6KGnct+NTvUPSyVAL+y8Re//aBdb/0c2nPY0n5mGZGSIKWc1ad626W9WPacti1nWgu47K5oTpHvb2lJbVxcksVDiC4BTa6mCZq8zKPrFvgGXiyOPbwxYuUZWjDY2lJMl4i9BKsddeJs9KtFGQJxOs4Raoiiuvznnlzetsv79P5R7xe/9KzOAHb3N+xcJaXGS4PafbyIh2+vzcmhO0N7nkhnxrJWHVSmh7it2jEjWOUY7k0usTmq/MCQ8iit2Q1y/aFElGEg341msWN/sVbjvn26+ZbC/HpFbMBRbx9nY4NfiUC996lZmzwNEHOe29PT7Yfgsj6CGIScnYN1K80oHuKdr3fKf7008ogy4sriBbq0gVk80OyW58iHvqNaTfRasC07SRwSq5v/fQbfkALG0gxwPKxSmmF6CLBDU5xETeV2T0dW/c8aJSC3vNM8W9/tUymWJacyxbo3MbO+vSMDvY0sUfTximI3JHYmeKhcTCvlUgc5upEZOfvkzT75FmKTNLoUSDYjggbTmUk138QmKsXcZM9hBCYAuH1LLJyxhblQjDQiiFN0/Jj/roEmZlhLjyLTQZxuJpUIrKa6Ou/ghv6QqLv25RRAnpp9foZXvEV12mmyFaZkw/2kBN5shFxZXVimwd3v/ZnF/5hkEVpRRuibQ1TQeub4LbVLSqhOmne7R8A6+VkByGUEp0ruh2BJ9MNM0GTI8EywuSnWmKnh0y+hQM2yTa3KI876OVzULL4mJ+CGdXsdZfRVYmB9dvcuPjHVYsG8NRxMUBYXnItJuCTnG3I9z2KXR3mUqU6HyO6QZUyRRR5pjaRgjIi4hExRw5wK2NTXCONwA3S01nrpjc2vHJMlycUiFmk8+2ISj72MLB1S6W5X+mwrT2wf9iamGveWa4179a5XPcU3MWF9YIKoeiiNnq7zMaJLjapgh8mt3Ld6zLeNrHesAPO3cVVrB2nEteDrHWL2NYLnnxQ7y116mCEdGNd2lNB5iFYlzuMtMR6Tijmgqk0ljd06jJAfZwQHOQILSmv2yjOotYvRVynWKaPu7p7xBt/QR17R3KsxmD/S3ObL7HS2cEzsEy63KKc5Byqlux0IkwNIwmknNrNv2NlNFBRawUr65DmsH+GJIc/uVvCka5Zmte4NklZlxSZPDmS4q3PoCDI03TgqYLu3saZVWEueLUQsWaB6fOtAjzEfs3r8PVMelc03A7lCsXsew2UsFSt0HUiCmsHbTMGXgG2evfoTr/GqLIicd7JHs3aAPCcFFFRrzxE8TgBo2lK4jWMunRpxBPcRfOg+0Tese7VrUzm0JlTGfbqPwIW7nk8YzMkhizkPUh2PbKnd/eCS5RtX1Kt8lsOqARjRBReCdPvvbBPx4nJuxCCAN4C9jVWv+Nkxq35mRJ3jj1hc/5vKBrrlKkOcEwMqrKQZWdh95gj2Nl3etfVcU1Vs+exnY80tE+NAKWu13iq2NisUQZtLFTgXFrA+XbfliKe/LNSXHz5FaRkEL6x2XyVZKS731EWszIpzcw4oi514Cldey130RUKfGNvyS59kPSPMOrTJqxzQI9jl7ykW5OVoyxey/j5hlVMqdUE7ysRB5s4r/zPkvVhL/ypqbdMdnZ+oQ0LwmaitFOyRuvQ17AtU9KPhlW2FlFrwOWgOt9+OEU2k1YXABDCgotuPySwdvvZFzsGRyOS4ZjSAv46SYYBqQK2g5MptBqaD64rvFdaImIFglWEnPhVMDPNuaUmGTREbrho4uYjmsLqmgAACAASURBVDPilQuCmdXEjvYw05TdzivMXQdlgj71GyjHZr75CY7RxH3p17DnGaYTkO59gI7eQoQTFlrncdweMyPG7qyjlWK+/TE0A6z1X6c8uEnqSpTr0Jpr/GCVghH5NL3z29umixFlpNmITJekw437XGz3XiOFzkgdRbbUIUlvsJrxlYj78/iEcJIW+98CPgLaJzhmzQnyP/zH/+WXPvdhgddcpbSbfZbbFpZ0KVTJYdgnnK/ed+E/rpV1r39VyhTbbSGEILM0vh9gCBND7lOYFlawRlru30lvlIZDInLKwLvzPm6xz3y+DUKgPVBpSNW/juE3MRdfwjAq7FaPNArRtgetgGq2R5mFKN9Ht17BmoUYpUU46HPmb+/xV4sNgrUWf/KjDRx/G8vPKaqQRB3xz/2rQ8Rgm2AeomaKljQwEljxc3RT4DqaGzcVhzMDrWG9XRElsHwKDo+g6cGpdRDA1f3jjcL/70xz+VXJq+cN/uk/0ZhnDUIt+eFVxTyG00vw8Q4YNlztw3QGb16B86ugBAyHJedPQRKWtLsxv9WB1DbY9v+CPLhGUiguv5Ty0UchRnyDldMG87LFpvdDNuebfGx9E3thmbKfY7CF/+1fxfzoFMw/oDMryXQbazDAwsNzlo9/R0NgShshITJyGt01pOkS29DuXUZIiUj3cIVPFdhE8c07v32hszu98u3SwuThrRput2kwmivYwqLIEqZhduKW+/P6hHAiwi6EOA38deA/A/72SYxZ8+wjzQnLbQvbOO4TYhsWy22YpxNQq3eOe9xMh3uzXZRyydMZtuMhACEtsiREKRdTCyqlKI27AbWsmjE1YqylczhCYeZzpO2jZEK4/1OktCjHfbQAc/E802yP3LHxhUC6LZLpLtVCFywb9CJ5+yI6HGAUIfNeD7oG3rVPufwra+yMDX69e429T/fxy4JTnQodzFlQkt39kHa74hvfEFxcrVBa8O5Vwc2+xpSK1QWBZ8F4XLHaE0xyQZUqGg4UJbx1DSoFr5+Cl85Aago+3Cr4x38Mu7HkUmVwal0Q7udcXNP0GtD14JVz0A8F729rKgHzCEZTMEy4vg+jRLG0YOGuWIwPQ6IPP4TeAoNBSudKk2Q/5ndfS1CVxWBWUk4+wrLGbE1LYs9H9HdxqpDg5XXCaxWOMGlVPk3tkWCSqZixeYgwHUSZ4+YhUtpopZGmi1Y5Qh//u9Q5iZlTGgJDKkxZ4JYWWTUjCRp3ereXWUh1tEGe3RVRszyuhJ3YKaXRw8onmMrAFg5G0D3x7JnnNUvnpCz2/wr4T4HWow4QQnwf+D7A2injhN625mliGBnWA1aLJU0MIwV197XHzXS4L9tFr9Hf2mBxwcdWmiQaMdgdIDmNrV3C4dZx4REuWTVjEu9QBG1Uq0mmS0qvpO2s0hEW8/CnWPMIPZoQe4Ko10P1FnF65zHTjOTgE8pRgr16iVLlFOkYtXYOWi3KdIr1q38NHU/Zvva/8tH2AGM04PXA4KzcYaUNKlc4RkJ8U6EiRekpZrHkB+9o1hYFi13Nn7+vOBprvvc69I8qhgPNwRiEBTsH8K0L8N1L8Cc/gdUuXDuA3SEsdhTfesnkT98tWF2weOunBWvL8GuXBG+/rzkcwXIXtIIk1nQCyYc3FH/zTXjzPCgNf/RTqAwYhIrTK/DSRRNTTxFmxlsjRa8IkSJCxC4dz8TxClIc2l24uf8x7x+exSbHX1mkmM4oZiHBrd2hsmpGZFfo7llUsISxcJo8nZCO92iEKU6umMRbZKRASln0wW9hNRcx7d4d8W6PS8bzXeTymwhpo8oUwiF+Y40oPrgjonZWMlQTstVL2MuXKbOQbOt9FguNdE8+e+Z5zdJ5YmEXQvwN4FBr/bYQ4l981HFa6z8E/hDg9W/adRPlF4CqcihUecdiByhUSVU5911YD+adAw/tpX1vKbphCtJ+RX9zH2nnxIaH4V7Gbyygqgzv4AAzySjsA+JijDx9AXtxFb16gZyMMp6QTmf4ZpeOuYDfPkO18zGJGiLsJoYCI0uQZhPZXqRCUcwGGK0eVZWjVQFVCd01KttAVw5VcxnrwgJicsR8c8LrvYhzCxWTSUXLA+EZyEwxHym8M4JXXhVsHyj+4p2Ktz6F88uC6VhT+RDnkMXw6YFGAr/pwsEIZim80oQrBry3BeMY6JcsNQ1+/69Kfv52yR/9oOLd98CS8Cvn4WBy/J8wod3SrHVgP4RpITCU5mwPfrYHhxP4zWXB1pbiO9/18DzoLAtubCQsLWuK6ZyVwGJjmuDOc3SW0Z0IVpOK5pvfJKuWOfiTH2D2Ozhli4qUaL6L9DqYa69g64p8sIeuUtRwiNzfJWs2SHMfb+0NdO8S4eQaRlGyKNr3iXceH+DNc8qDXUq5i6kFvnYxnS6FeXhHRHPHpGUvUo2GVAgsYeH465TR/lfSn/1xr91njZOw2H8L+JtCiL8GuEBbCPEPtNb/1gmMXfMMo8oOh2Gf5faxpX7sYy9Q5cJ9fT8epyPgw3CtNo2iBwUoI2ZeHZLPD2mkggXVwJY9yCByE+zlyyAlyWyI6gXI5Yskh/8UczzBLFNCS1HaGcpxsbWBdJdJypS4mFBOtxFo2HgP2V5FpgN0mVIFyxgr56iyiNbWX9IMtwh/PEJu7tLrzcnDjBDFmxcl0pK8v6uoELxyQTIvJNtDTZHC0rLBqUXFv/3XDfKpotkQ7BxqJmPFUQhLPfhwA7YPjz1B+yFYBlw6DWuLcDiFd/cUP/5nGUsdwfdeg59vQxKCKMBtgNMSxBjc7Fc0LDh31mA6VMxSQWcBqn3NjR1NfwSGJ3Fd2D/QFHFFlSiUo/nZp9DyS1q+oFnaeKctXllfoUGHjTwnnEE5GGEP5oxzyVJk4xmQrS0hTRchBCZNCpURtxLmswPU8jK22aAabCK1gZPGiMmUXA9wSvc+8TYzTV4VIO8aCrdF9HYAc+hlOLZBkAnSKMdotsCxyPUGThieeH/2L3vtPm2eWNi11n8H+DsAtyz2/6QW9V8ObOkSzleZpxMMI72VFbPwWE2hHuwICA8PVA1HG2ghcbsv073nxmJ6d0dpLUBKiWG6eFlKcbBL7o9gsI3wTiHPvApCUBglqDlWXlDtX6diDn4bo6wAk2LaRzhNLOFQjQ8R0wFVWfJK+XMWRUjbGNOjoEiO8FTK2a7maAzpXFFqRVUYpLmge8qkfyjI5xUmkkQpVhYNuk2BE5iMQ41pKuYZHE1gHsOZBTi3fJwt8+OP4PwKLC1COIf3bkJZaGKhCXOIQ4iH8PpZaDeOz7t5oGmswkwYWIbi2k3FG2fhjfOC7YFGa8gl/PjtjCAwUSUETSBXXD4rsJEMR8d58XkhuL6Z4nVt1i47vP+TCbPGRRqvXURcvEj1A5t48x1G2QEeHiqZ3dndqNQ5M7sg8yzypR7i8hvYmPjaRiQRRuRT5RFeLmjhAcf93MlSioZPGbSxgjUqpQiHW3gHB7Szkmn3OCju6Iiqs0CVRbhhTJlmZDrHOtwnuLdA7QSv8ce5dp816jz2ml/IdKLu7L35YLqXLd3jQKm6dTE9wop56ObSD/CwQFXSbpC5FrmtMasEFwPjgeBVM5WE031EZx3DcGiqitngAFOZqEbAON6mKOcIkePaHZLhBmr5DPal30aogvit/wsWljBWL1CODrCEi958H43mN1vX+e4VkzYhpxcLZkcjCr+iSCUChW1DmB3nnB+MFV7PQXkWk7jAUbC8AGhwLc27H2lePycYjjVpXBG48NvfgtkUSnVsrb+8Ajfc4xTGn16HWQyBD7/3KxAnMJtDmsL3XoblNigFe0MQEnb3KmzfYm8KL3Ur2k04mGrev6G5sATBmoHrSFptwc5uSeMlg/2JZrUDXkPwve86hOOKdgtOL1V8cHWPQekwylbpffcSRFPMjmTgWMhv/y6x8xd0Yp8k3aPa/xh79WVmMiExSqTUeMtXKIJFSqHJBiO89iLFYJNivMfcamKoJk4lEFEIQuB2z2KngrTcJxMluc5Q5ZTCs3Ab7eOFu1DMwyG0FyislEYmcaaTr0TUv8i1+6xxosKutf4z4M9Ocsyaz2c6UYz2C/JEY3uC3ppF0Dm5K286Uby3u4xeu/CVp3s9GKgqdEbcctCtHrnZJKZgHk0JpgrznuBVUPkUOzsUaYayHWSe0R3sMYsPGK0uIc68jGG3qfKQaLiHf22PWTxBiwotwDBsnNf/JSrXJZ9P8QqborHMpfCf8N2lmLPAop+w3DPRluLToWZnrAja0O0JokRQaLh4wWArl/zFz0vO98ATUOawd6hxlGL3QNB24OauxpMwSeC3viU4GsHOkWYeQdiCbhvOr0FvKvizjzUL7eMslySDpQBe0WAbx+d/8yw02rA1gnAXLl8w+dk1xQD4/z6GNFMEgeS3XxP85FNQCDY3Sz6+XvLhlsZ0DW7ulPzut2GlpxmMJUdHirPnTdR4yji8Ru/9m8TzkOVvnkZ1egwXfg/DMKksE9ds03Eh2f8QPTggsyOa699AdxYx2svo0YBieYWsnGFFkqSY4gqToojYt2LM2YSzRwodLCANB0MIKDPKpkOjdwZVmRSWSSVMZBpjWT7NJCZJdsmm2zQT57mwoL9uaov9OWZ7s2TvvZiVQLAYgGUZjDcV4JyYuG8euHirS/yH/+OP7ryWzEuswXW++XL+uefem/v+OEUetwNVyhCkZsXMzMl1idIZ9tIVLMOmyiOG6l1WdjNub1dnS5fFWUqU9u8Z32bmWMgzr+IuXkBIg6oMmJuS9NrP8YsucRxhOD6V4WI0F5B5jGG0kKZNr+Hz8lLJa/98D3s24Vxg4FYJERnlXOHamh9+DCsLklZLMEol80QQe5K9w4JmWbHWEfi24srysSjvTzU3+scW9uXV402Z3r+qUQZM58cFRpfPS4YRbI+gEQh8R9NdFny0X7HWhqyCheZxsNSQx43BrBT6Q9gewq/+vsPNo4zv/raPiiqSSYUvKopSMx5W/Oa3Jae+ZfD+qua9HYHhCBJLsndYcWOj4mCoOfuSidO1sMYl3zsTc8EWvD3eQvRDPv3QZe3X18kKi6Zxg8GfW9jSxJE+a+nxbkuieZrclGjbo1EI4s0bZBvvkCoTu6zQ3WXcc79Cw21TRkP2PvoBS3shxgM7TmmlMLXEFDZl0GMeXccUKaXUiKIgmEOX5nNhQX/d1ML+nDKdKHZ+HvOdy4LFniBJ4XBY0W0bDPcLgo7ziwd5DGaxTadxf3qq2zCYbNnA5wv7bT6vyAO4I/hkGen4OvnpC1jBGgUz0tmcKjlCTT7FcLuIIqWMD5laCWY1P+4zct8YKR4RlqMR1hiRxqBKkAYSiR3FpEZF02oyT0JaDQnpTcqrf0RiLeIaLtpr4w9TvLZJEUVM9+d00xhTFfSHFYfT44SZwgRzDcJUkAErV1yGI82oUlxeA1PC7q5CF5qsgrc+gm9dlkznClVBpwVrreP89enkeExDaBZaBuNSQEuyPy1oDjSegE4AaBjM4cc34MoqXD8AN4Srh7ByysKyBJ01g/0RrPdMpocVByMYT+HUiqDpwuBAkVUCoTS9hmZQwCyBb5wRXFwXpJXm3bcyLp2TvLQmcIqc/tE+i40Cxg7v/ej/4bDzKq1TZ5ktdfDnKbZrkGcpjVQwG25hLKyTxWOE6WIlOUHWQpUJiW1SnX+NvNXAqErMRgdx5nWywx9iPrjj1KSPr10oDSazQ2JX0WwvkuuEPB6SNwT+dHJnE+2au9TC/pwy2i/oNGCxJxBC4HvH/tz9aUVenpwJ0/Jz0qjCa969VNKoouU/nqjDo4s8pvOr0AzuE/x08jHm+JA8Dqk8hdlbQnSXKSaHVNkY8hQrWAaxgC6bHBxdJXPkcYvdomRVbLJsQCcRaBsOk0843JUox8dAItOUhr9Cp/TpRh/SWF6k6hbkh/8vU+s0e87LuGlEMRjhXlZc/2jIglfyFx9kmLrClLDagyyHg/Gxm+X0ecnp8xY/+aDg9IrkVKARSYVQmrPBsf98OoNzXfjeq5rhCrz9Ibx5CWznOOslzOBwDv/njzRBo6QyJekROE0JaNYW4WgKO0MYhfDtl47ncHUfUgnf+FWbxRWLt98paC1YfLKRs7uvsRyTsJSMJxnnFjTZtGSzr9gPJZSarT1Nryl45XWLSkiGhxXhqGTB04yHmqta0bI1372cI+SA0HGId8eocESncwUpPSazI1YNl74zxcJEHW4gZxOkBYmO0VmMDCtEmhBe6GEaCrOIwG5RGBWO4VB6LsG0OG4LYacwC2ka7f+fvTcJsiS9rvS+32f3Nw8xz5EZOdaMAgiAINkUJbJJWLdp2aveda+0kJm01EY7ybTSlqs2mRatBc0oa6qbEpvNAQBRqLkq54yMeX7z6LP/vxaemagpWVVgFVlVqLsKs3jhz/2Fv3Ovn3vuuZimB4A2bqHpKX7cwawsUC7MQSXkYvcdlntf7SnQf4r4Fti/phEHikpVMPWh+Hj5jOvA+BCs5he3P3JtLuTWSRvmZ3AKOuE0Izhvc3kp5LM+Az9ryGPoSCqV+Q8Bvja7jhFlmJaLXpulrQ3Q5jcxNQsMC6mDO0mRg3eIkwnnFUjn53F1m8K0TbFsY2RFwrRFPbHIkhYT6sjSK2ThCHmxSzExSbwhm8trxLoimK+juUUcqTM4vkXkm2RnI8a7Z1ScGM+ERGRUPOj6eUPzx//MxDQVf/ITxUlL8rCdcNpS3JjV8W3Bgz3F5iw4Btw/g8UqvHgJdKVYmxG8qytOezngm2buDWPFcNTOZ7uyTHI2kWxsmiwvGQzbgt2DlDSCaQS3jnJV4MKyoD+FX7ybYRVg0M+4dtNiadXAtgRn54pOKnh0BtOuZKYEl1cE370COyfw2kPJ2rLJzesmQgj2i4K7g4yVOUV7rIgGGRc+bKwK0kzSrCh+VNEpDibMNjooY8ojU9EuNClXVyirJjLp0h3tkqHjFJeoGivodsqZPIVKjaQxS6KBbO9jRBKVjPGCCEtrYGVQmBoMjRCtUkWpx/RcOKbo1dFK6+h6rqZRtkVUX2A6PnvaSP86+rp8GfEtsH9Nw3IFjq5z1EpZmdUoeNDpKS6GimvPm59+gM8YlarG87Q4uBgxOLQoeTGXl8LPxOE/2eT0/gOLpHn0oao/mKTc+9kpL/9+HyF+mYjeu61xsJfx0z9/BcvQsCJF1D4k7Z2RaQph2CRBhgiGtE2LZGkTfeu7EGWYe49IRZ9RmOEoRYMyaXfA6fQXjI8v+L1/dQ/9UpvKpVXSyODKqs5br0WM9Hm0xpSFRcWNNOIwatB4/W2uN+H7l20mvZiHIfzwORhP4bALoS9RrqDiCv7gt3Te2YVolDFtK67MwXEEq3P50FG7C/MN8Ez46zfB1BVlD3QFz61CtQp3D2H/PJc5rs9Draxx2JZEuiTLdEgl11eABHYv8pSqNCjbiskY5hzJXCmjtgCxluAfplxIgziRlJTiO1satTRDk3DSUrQHGaMAzjpwLYKJrzAN6PUklabO3ZOUR4eSog7XVuD+o4zRJMMoCOYvl4lOYgb7XarKoGoIRl4BXxN0ww7BTJGsvoVtlCjaTfzhGdFkQLS0hfL7JHtvkc0sgmGSnD8g6w+oCcE0HRDbBqktYOKTjQdkj21/KzJhXFAYHxgUUjLGwnzqAf919XX5MuJbYP+aRn3BZHAgKdUMDnsZw13FYArLL3pfqCoGcnB/oRrzS0798x3/WVX/5sLkQzTPZCwZ+A7BdEimJGM1JklHmPfPEcUKSWMOUahimCmRe4A0NYy5TQgD5tMDFlbrrLgG4mSPcOqTJYuUfINyT+AZMb9384ia4/Mf36sgzSpHxzpRaYnSXJOy02C6t49b15kf7TNXTLDSmIom0VzJjdWcqvdMcG1wlOIXtySbKwaGLhhP897DbDGhUdLJ5jV6vqIfKY5HMDeEkgbf3QI/AhP427twZRkagK1BfwzfvZJr05cXNSwDjjsZDx4qbi7AjJVz5d/bhEYpp2Hu7ebN1JqrWC7C8zcMdi4kO2ew6kkCS2NpVuPv3koZS1iqwEwRJnF+PbYFb2xLhtOUtVno9iSEKcFY8eqWwJ8ouj3QDPjtF+D9/Zg7t3o4WomXNgyCeoHSnQ7J6Sm7xUv4ToJTmyEMOoS2QRYMiBouqVcmmVtGZg10JVFSIetzqPYBWrHKaLVKfHrETPOlp6CcDc/x+uMc7A1BODpB+QvY3ixKxmSTLm6cPZ0C/br6unwZ8S2wf00jB287lzoKDWdRcOMLljpC3qQ9uHAY+3m1vjb32ar1j57rJ1X9wIcAf/9Ih8Bndt7CtIqkKAyvTjRsUypsYaUWajBC+WMyt0AYXqCPWhTDDs2rc2TaGv3eWzSTKatFi+1Ji3bsEYo5nFQ9PneDSzvH/PltA8usIKJj5FjnOJb4B0MqpSmFcZurxYCZUspwJAkCxVoT7h3ljontCZgtyTsPYZpm7J1KCgs2NQWB0ugMwCvodNspmsgliodn8Ls3YXMR7uzljdLVJrz1AE57cNaDSQSX5qBQ0rBthWsqpgG0TyRZBdp+3pAtuuBa+c91GzwDluu5j3unJ/FQJBHYnuLuo4xhG9pn0CzA4ia4Zu4hI3UYRNATMLdhMRxn7OwnNEqCS8uCqqFINZha8OYB1FoQBBnRJGBz06PiZEStkJqRMFeSnBUEw0BHejoyAcMpMiwA9Xnk4R0S4aOKZTTbRhc2ZnUGufIceqtNtlRlHA5pKPnUijktlLnQA6rFDVzdRkYtuq17SKuFoxdw4wxt2Hu6qOPr6uvyZcS3wP41jkpV+9zql8+je3+iYXfnZ6g+rrRvnbR5ntavBO6fVPV/EPDjI51acwZz8yqVv1ihkIZERPQtD3l0n6JVh9AncATa7Dx6aKE7VezJLmIAKSkXF1PSVsJUSvYinaT0Km6jhswibp3MsjY8J/OaFJtlwuoK2+/6JEcazZLGzPd/AI/eJ350l2Y9ZKaqkygNP8w478LpAMKCQRgrbF8xU5dcXhLsncO4k9Lr5qP5s7MaC2WNsdI5bafoHuztQ2uUe6if9yBKYGsO9luwXoPOIKd5HpzAqzcVwzEcdxRnF7m08eEJIOGlNah60BnlWnZdgyDJv8gFD1otiVDQugARgz+F2SJszYImoD8A34JKCYTInz6u1KFUFBQtjcUZwXIxo30Bc8vQrOV9gIUqFOy8ERwHGf2zHkeWoHtRIoxscF2sShGac1BbhnGLuL2LXFoH10PaFrJ1iH79h2RpTBYOsFoBtlNH1/sI20EU64R+iEneMI10haovoEuHJPFRhomXuqTnOxiZh5YBSjF0HYx0AnH8tfR1+TLiW2D/NYrhQDI4iFidFxQ8wdRXHB9EPEv3/kTD/oQqcYsGzM9wcDF6DNKf770/KaF8EPBFqvP2I49ydoo23QFzDld3SGMLGY/RVUKchnilqxQyE9/voUZTUqNK1N7HcBxK0qVQ/S4D5TOSOgWVe5joRn4tb7zls/adBa5Jn//nrQnmj/4A93SHebuPk43BBbQMqWv0R4owgUeH+dRnqa7z6k2bmim5/V5MoaRz3oUby2AUFWxq/Mn/l9EdphzsCTxP0Q81lpc0LnopkyB3YYRcXnjYg4MOjIKc6nDt3APmdKAQ5DYAjgXfuwaL5dyGNwjhfAidITgmLNVht0UO5oP8aaI3ya0KWn0oFiEO8yQgVL6tzo8gVGC6Aq+is7go6B1ELC/qLNdgqQgnLThoQ+Hx08BcDeJUsL6scC0oOSnTJEDoi2BAGDuMD+4SZzskloftNUn9PqKlo9qHCNPBUDrp7ruIcIrQbYyNVxFxjJlpyM4xruaSivTpPZMQY1EmSXwmrkKrrWPrNsLbRl20SJXErq8/9XBJe/sk/UOc2urXytfly4hvgf3XKHpnCavzgmIhv8uLBcHyvOTwGbr3L0LDDp+eUIYDyZ1tk4tHCdVwwExxln/zP97i4OQtBpnBX/y7a6SOTTC/xDRs8eK/PGDTO+LGypCLnsmjfR3/7Xv86DeLXL2ug67z07c0rlzbopz8jMtX8tt83M+486hIWNXQUETtHrMLOnYkaZYLVLMW1csz3L3totshnV6GbWusLBkMfMlQ6Tw6zJh3JAVHsDwPnlBkmWL/COozgkZV0CgLpqOMuZpGECnMTPLchsb+seTHL+aDSA/Pco48UbDQANOAuTrs92AwgZILgync3IRSSdBuK0wdkgze2ckr/2tLoGk5LXPUy8F+HELJgZc3IE6hF4BhQNXNq+1UQrUIOx0Yd6ETKLr9hEZVZ2IrXEtwOhBcXlRUK4LjI8Vf3c0VOHNVxXkHmhUYTUGTARcnewRS5yRymbz4LzHXnkcJRXT3Z8hHpxTdOrFtYF75PnppFtqPyO78BDsYIq0HaEGKPokQowtiQEQZRcNB03S0UQ+rUiAUKVptHd10ibMpqaboz1fQxiNmPkDd2PV1suP7iPDr5evyZcS3wP5rFHGgKHgflkIWPEF88smPqp9Vw/5p9M5HEwpSoYcp7/51Sn3J5NGwSdCHxZqNG8PB2ycsbxZZLmQMdiVauoWjF5BJiik1NNuiP9YoFAUvLEi21mLejjScBYvd8wzdFVhLFcxagelhnpgmg5i7uwUKmx5ZdYZ2J0FG57T/37+mZESsLKXUr3jEQYauRxgKXryiYxvQGyiGQ8VhV9Lug7uQMt/UCaeKWlEyTSCMFK225Pe/pzHwNTxTZ21Zo3E/4Y07GesrAiODX+xAEudUzCsb0JnC770Eb+3m+nQlc2olTXPq5/ICyExh6zCc5q6PZ48XaJz1cyOwLIOeD+uz8PAcfuu5nH+/ewS7O/CHL+eeMnO13DnyJw/h4Sn87vfhOy/rvPN2xrCTEg7zHdTbJzA/A4ammPj5U8LSDBj6YxqoD2EM37uaEPcThplipjPgeDKF8z3SLEDKd9dfQQAAIABJREFUFDSLxO+hlzfQJiOIQszpFFsvU+jsk53/HM9uIN0CXnkNmcZocsTAP6LSC5lJdXx6xGUbU7eJsynTZECxskDmWWT9cyahohjkVgOabhMZAuPXj3n5WHwL7F+B+LL9Xp6E5ebVcrHwS3Cf+oooVezdiz72/p9Fw/73VeOQg/rurYjyNQEzuQxzfJawMQdJouiPdEQ7Yrms8/JNhyBQFPQJ0aDNfNHgbldhphpidimf9JQu+vSCGJfTjs+KCAnO29y8HGKvlJ8moeJYcme/TUFFKGWzfyAJpYXHkNdek5Qvb3DpD5e4/+4UXI+EU8bdgHh/m7WZEF1XBBOYXxDMFAUWcNBTGEaKqUE0TBgNwarltrlNV3H/RPKj5wzaI3Drgl5LstqAvapABgqV5r4uJQv2TsGyIBrBfgduH+Sbk2oFKNdzALVOQAeWy3kFH4W5k+XiTG4EVvJy87FU5tX6Yg10AXEMx708gWgCVAq2kTdNZyv5QNTVTViYNxhOFKadmzNMQtiYg8szsH8BkwSaVVibgTTLOfmFClQtcIqwuGBwujNDqR6zZescZce0Zl9FtPYQElRjgTT0scMYvd9Bqy2iiwK2MYMjz1joGXTdCUlpFjuIcFId05gj9FyC8SOwHRgP0PyI2HZJNUWxsoBpV9DjAbpmoNWahOE+Jh5x1CcoWtjFL9/X6Kse31hg/8cCy39ofF7e+9OO9fddc33B5PggYnlePn2ve9sZhiZYratPBOaKf8zJT8+JsJhZFDy/lfy91fgTeufOw4iKDavzAvuSoGzmgD6JYXNBICXYnmDc0njlps3RUUwcQaGgc/Wyxb07Uy6vTjnsWvznn0pS10SrzGDpFpX5HoO33+eod8bm9ybMFn2OfJs3fzahtlJjbTnF0BSL2TYlbcDgnstoT8PcbDLVl9i4tMEw9Jh2J2yV7yOQbL92gqx3eWV9wKRmYLqwMAfYgmkgWVrSKbyfogWw6OUcuW7CGztg61CqZkRS4ye/SLBdHSODuapg50zSGyhUGWZnoFg1GPYzIqU4GOR7Sk97+TH+6+egP8257d4IXl6F9/ah4kJvnMsg9zrw0ib8yc/yZR2alnP0Ax/2LiCKcvVOFOdgPlvOB5oeXsBCALHIufhaE6aRhsok8zM6y6WMn92BpWpO1QwjqOjgh3A80TCRLBVzgM8khBNotTL8ZMp4qONV6pTa53QOH6AKJczr30cYDkYUo+IYvXOOORwjplPcUUh5mFAw6vjalHJWyWcZxGPjt7KHUguYxjwyi7B7+6iLFsHcLLpZIksC9N4FQtfBEaRCkqUh/vSMwrdyR+AbCuxfJFh+2fF5ee9nxWe55icSycOzhPgkr9RbF5LLszBsSWgaFEsay/OSu9sxZUtxY1Xw3WsZU9/n+FzxBPCfxLPonf5pws0fmBQLGumcydGjGE9l7D1KsWKDUaKzctVibz+m4GqYjkG7lzJTN9A1yKKQ43ONa9cl8fAMcekGmm6hkgBLTrnyvRlqF3vUHJ+37pQw3CKL9Zheb8R7BzHPL7X4/tX48TVPuGh7hM0K4zNJse5SEjAtGBAKNtehXZb8xvM6a3MFDrdj2m+MuLmpEQSK03PJaJShK1hrwEJdsCAVtpmD4PYZ6JZGw4TtU8XLN0DFGZOeYu8EaiWQpkZ7JHl0muJWdHwH9seSUaRoVKDVzekRy8gdG197mHPxkwhuHeTqlyvr+aJrg5ySWW7AYhNkG+YrOWDXi/lrNmZzC4KaB2eDHOBPu/mUslT5ntT5puDRI8l0Imk6eTIoFQVhqtAEFMs6K5d17jzIWJk1WChLto+gPZDoAoqOIpExBhbRaMpYeagsQV+4hBx3sWJFRW8yUeeo7hmOOYNMpgynF0RmQKAyzDB9av4FEBoZwqlgjkZPm95PuPP0aJckCrCETVU5YOhML/ahfYRIHGwtw65/eDunptsEWkKfT7ad/qbGNxLYvyiw/MeIz8t7Pys+6zU/kUg+SQSRIfGEZHAMxzsJy9dsFpd0eicRN35gferxntA7SMWwk9LrSLrdjJMDycUKpHMmhg6GUCQShn7eeJOPtyPOzaS0DwcYXhVz1uPgzGd43EdakuqaS6Wq4fUnpNt/ieVqZKJEWRviGBm6zHh0R7EyXyAVJsMhOJMJM+sFCq72oSRedBTBoINGkdiP0HSdqNMnCD1822P2SkDfrPL+z0eUxJCTc5/iuxGXlgRZlJFlgulUUV4Ewxb0Bor2RT4petqHSlXn+mWdtx8q7h5nDFoKkeZUiOeAH0g25kFTOb8e+rCyZTJbSfnt64pHOwpPy3lzP8obn7eOcwCvF8Bxco+a0z78zb1cG785nzdfSy4slPOnh2oB+hOYBPng0uYcHHWg7MKbu1CNcn+a0x68SMZ3rwv+418pHh3nXkOpgijVcBxJfyixHJiMMtwlnUYJ9jSFbuYJZKEJk56gPc04etCnLwakkzfAcXATKOBg21VU95xk1APXxK8WsVd+BHFKEkQE59u4nYcUm1dyjlzFaMMOjvol8Gq6TWY7zAc6w1GEXqmhGTnV4g2HVPwilubQZ/IxuWOUjYkcHbvy60XPfCOB/YsCy3+MeBbvbbmfz+/l815z7yyh4iq6WcZsQXBzRdAdKN57EILmAOIzHa++YPLgbkhVpVRKCjtOWSoK3DUoIemdxEQZXFnXkVInMg2aBSi40L5IqM/p3Hl7RHk+JW27FPUYZyli6UbhqWJmuTSlXi2D6xDKgNLFIyorNgYBrm4wllWsZp3agoHRC3i4PcSo6bxw9ZfnOT+XYZsD4nabvT87RNN1+n2JlLDbzrhyOeRELqNdu0xnd4cLYl673+boLKHmQaOosDRojSFDoJmCs76i5IJhQdBL2L2b0m8rXKHxR79v0m8lhBPojmGmnAPhOIGdjqS+rhFogkJZ4+giw7bAFDBfhXf2c0ljnObN02mY690DAde3NPb7irKpGPj5a8pW3nRVCl5Ze2w6Ns392v0wTy6zJbi5BFdXck7/fAp/+3ZKmsHtI7gc59LKw4JirpYrcLoDRaMpWF/T2TtX3N4HG8W1TQ2p4E/flpzuC1RW5HhYoHr9JSa2IsMBIyO1E+LhKUwH1K0F4kKF4toLGHYRGfvI8wPs1ZeQ7/014ixXspjSx2msYzr1p/+7J1r0j24zIgpBCIaujZFOsKIU/yNr7KaTE4qFhV87euYbCexfFFj+Y8Qn8d7H54r6mgV89l7B573mOFCEKuPGlsl0mlIMoV4R1F14cD+ltmj+vcf74HmdnKVERcX+keTyksbCoslsKDk6zFhdN3j/bko2LzhuK1Y2LAwdBu2EezuKzed11n9QJPUz4mCK6Qpcz8qnXfcs/IsRi66GDAN0o4CewZw25OBnIxYqY8ZOCWu9iuXmjVnT0hgeTbl/r4/di6kvWVRnDcQo5PjBHiXL4rc2DHpnGnFZoJUsnIUqB49iSi85WH5Iezfl5suLNBIP8/QER4a4nuTV5xVv3lX8+esZywsa7VARnuTLNK6saCzNKO7vg4wl5+f5+P9iCQ5bOfBWCjktM50olpbg9t2E65c03nig2KhDzQHPzoePri7k6hjXzuWLgwDe2wHNU+iGYnZRJ8skga+YL0Ka5Jr2VOXA3p3A5XnYa+Xve+8sT6YlB5Zq0A/g+Q0NMolSEPiwe543XV0HGjW4mOa7Ui9vWZhZyvq8oNvJ2LlQrK3o/PjHDn/z77cYJBreRCOKMoqTCcHgNWR1hjTN0C66mMMejrtE385QIoa4jUBDy0ZUrRKp61CbFB/7vegMpyMyw3sKzlFvH0PGtO3pUyqFBIaVKvoHQNx/YkHgB0/ljq6IsSq1D937vw7TqN9IYP80sPwqxUd5b8sV1Nesp9XqpylOngC+4ekcnyef+ZotVzA8VVx/TmMyMTnvp0xOFBMJTtVg7Yr9zM/wo+dlTwWWCV00tq7oBAGEicXxACaHigf7MZV5WFmzqD5JSprJppknqo9ex8Fk/um0a39wQVR20aZ9hmEXzxyyYV2weT1FdzTu3IuYtIeYbgMZp/RvnzCjBvzmK4LnrgjeeDfkF29oLF8qsWyPWCjCg23B8nIZYRfwsTgfxtTma5w86DI56jFTMDnYU0gR8zvXqzQqCXsPByRkxFnKfgtGqSIIYXsffutFGESK3XcVCzW43ADTljwa5PNO81WYq8BaE94/Bt+H0ShDxbBVVSxfhckwb4B2p7ny5aXNfKhoFEC9BJUKjG7BL95X2A50A0HJ1Ficz+j08mGk+TK8dwAoWJ2BkwG8vpsPUJU9iGVerXdHcHwB5VKGBmwtwrCXO1AOQ6iXYaYqqFc0xrGg0dBYWrZ5eCdFOBD7isUVE80QhJHFwXhMT80T2hrCq1IMErSRJJv28C5a2EGCP+eAY5DUq+iFOqp/gVWsMkknFIPwl66MHzEAIwpRBQ996epTAB8Oz2E8QK9c+1glHvsBtaz4FLT7+uRDy1tSXSCiEC/+5aKWb2J8I4H97wPLr2I8yxrgWbz5k8bmhwD/PEGrmtw5SOifJoDKq9VnvGd9weTudkSnpzB0xWAMrY7CqunojvjEz9CoGvTOEg4fxFxaAGRu9VquCkoGnJxLOl1FP6wgrQKNKzp60UGMesRigGGCUuppkjCqxscS19++pdCuVX+pnXcspvUaTlTEy2I26iU0p4UfjDBiSMYRo7s7uFrA8CwkuOjznedMFmogEISRy9a6g96sMIk9Ij3GEUPGgcP82gxJaNG7FzOMEoYPD7EKLtf+m5ukScLefzinVcsgiNg5zKh5Kf/qdwQHLfClTi+QWEhWGrB/qnhhIwfYUQr+OK/OxyEs1GGnDbqTyxR1Adt7ua78oq9olgVuQbE0B2/v5lOop4+B+qQP0ySv4pMY5srwGy9ovHckOZrqhJng4W6KSnIpY8nNl29IcjWMMHJ/m9tH+eCTaQAqB/nDU9hagEE7b6oWHLjswN/dh6InWGhAJVVEowxbaHgLJt0pTFG8e6IoVTQenkkeZgUmM5cxN24g7CLJqI3RPscdDKgkDqkQiDjCVBbRuIfSbVQ4RqqMbNxDj1OG1Q+7MmbD89yf3bTRa6sfA/BR0qf6GXxhColBp39IsLyMWVlASEnWPSR1beLJN5dn/0YCO/xqPipftXgWb/6sxuadg4SKDTd/YH6qGqhS1Vh+0eMnr00pZClX1jVefE7noi8YpIrhQH7oM/xglU5TsTEnaJ8lgEmlaTA6jREavLetU19wiBKJKLt0xorF76wy6GYc9vwPJdpPSlz1kk13FDAp6EzOp5zsp/TGU8pIalqCrhscj2zUSON3vgvrNcGf/2xCZ6fFNNOZmzOYL0c0qwmdgYnhudTKgvNRSieuojk6I6lQkUtvZBD6IVqtidZPsUpVzGqBLIwwHRO75LLfiXh0lDHjKOZqglGoESYK15L0O5KqB0VbUCvDclWhq1yTbhk5Z73XzZdUl0r5EFIW5ZOby7O5Q2N7ArePFKEPL29BrQGpAdttKFagVASp5SD96mVIBcxUYTPW6Cqdm1s6vU7GZkWRJDmNUvLyYaLOFDBzieRKHf7oRcgU3D3Jf2fogMzPo1TOgX91Nm/KVjyFhiC2BW/cTrEsjagg+OGPc9XJ/Xsap32NO2OPcXkFp7FGOmhBISFOffzJIeFwF0vZZI6BN80IaVOIJsTqNko30PpdZrMmUaGAKpTx8UnlFAOBVSgz9S+eaeylBMRRn9iAVCgMJbBSMD/iC2NpDua0SzIcIf0AQwkKykGrrzONvrk8+zcW2L8J8Sze/FmNzQ9KDOHT1UArawaDlk1NaiS6YJjB3KbBnMbH/uaDIGx7GkrlKorzTsrShkXbMNg+DDk5TjCLA7zZIvM3NOa2KhQqJoOhy8b1D3+Lznc/nrjq1ZQH+z7/6X+7yWzFwnckjYbBcO8+HV8RK5P3/v06l7w6g78qoJTgsCsZK4+H3RH/+r+7T91N8TyNsGWgOzrjIKMbWgz0OUbHXeRQEAYpnTiAconyZpHJ+R7lxTLe8gyP3thlddHmle/VObyfMryYstaAJFY4IuM3Lmk0aortg7yK/ss3FWkKKsppl+EYZmvQGYOfwvEImGrIMF+Zp+s5wJa8HPxbfVieFwxjQXekSBKFWRL81V3FUgNGA1htQKbD1csmpx2JZUg6xymv+5LWVFA38unUdw9zfftMEW6uQyCh0wXXBd2FyIcfXIVb+7DbzidIN2ZzPl03cpfJDMFpX1ApQ5pIGkWdf/4vHLZPBBfbIf/r//LPEbUFTCyixpi05GFHkAweMjUilKajyDDWrjAY+agoYOQGmGFCqbqK5dbJkgANga17TGXEtGCh1xcxDAeZhoxaewhtiC5sBAPsGFJNkYp836kx8RmVBhizN9CtEmk8Jjy+y0KUfhzVbIeKPfch33+l1BfKs3/VFnx8C+xf4XhWr6C2aDwD8D+/GsjS4fI162M3/Uf/5oNPD41Zg6OTmOUZQRLCxXnKvdsxz21q/O4rJqpU57yX0c4S4Nmr9D6auAYDyfB8zPGbEcXCCRNzjjTL0DPBXGWO2+ic21XqxilmxWE0mhB0Q4Scpy4sqqmiMSc5aiscR6KymFbX4qQlOE9MZucnzDYt+iMLUSrx8OGErlfhaiHEL1YphVO8mQYybNE6u4Cx4nRqYBV0fKmxXAMHhWdBq60wFMxWc2B8fw8OL3I73lc2cmniX9yGSjXXvm93FEUvV8YkEcgMjlugsrzxaaF454HCtEWuVZeKwwtw7HySdK6e898PdhNafdha02kUFJQ1dAWeB5szeYM0U7m3+/Z5TrGsL0CznHuvR1FeoTfKuY/MOMqbu8fDnPI57YJrKgxLcb1iYHmAD7feTxilOofJHNbaIlnlGr4KmLQfIGVAaARYS1sUKw0m/jk4LiKCqSmQR/exrDIMR8TTY/TpGcQhhTglmrQwMkFWLJJqMZmMQcbEjRJmOs+MmqGfDRlUbIreEqZukwzPUNMSrlZADXukeh8jU7hWk9iOKHwErJ8sSf+yXB+/igs+vgX2r3A8q1dQhQ8B/ulZxoP7KWGgeHQ3ZmHVpFjKq/ZPUwN9VjXNB1+XN0AtHhwknLQVRiej3hS8fEVHE5Ljns9Co0A6iOnsjSiVkk9cpffBxJUkitOdBFfA5orGIEgZBMf0/SKJioktFxpzHOnLDM+PKEcpBjXiYETNmBArH4lDZcWmf5HwX95PGfQj3ustkG0+z/5bLWTq00vHzK4WKSw2uTS7QHKqI1bWMQojisNtujvnZIGNJ1yCYEy9lPEbP4CzRwbdSURVkxxn8M7DvDqfhFC0YHkmB88//Tm8ugVZH354LVeaOBbcfaS4vgKnHajZcGkWKjb81R04HYKf5Vrzf/HbBuenKVGoWHShWhOgCaJUYot86OjlTYFX1TiLBKVli6rKkGNFuQzlkmKhCn/6d/nxMDVOupLTbj5MpWe5rHIc5X7sV9cEb+4oji9yF8cXV3M1zkUf/vq1lI01eGlL4DgSTdrc3tWZxAcMqWF7M1jLzzM5ehvpmiAkKpqgajMIy8HvnWEu3URToI8mRN0TdHSk0ihpJTRXoab5xg9fSzBrK2hmAT/qkMRjnDOBaRcwwyGmVSGenGOnFpVUZziziowyypn3tOpWel6Fx8mHq+dPkkF+ka6PX8UFH98C+1c8PspzP1GQxJngzoEiCSTpOOXmDQPLEZzuJFzsxqgNE6GLT1UDfVYF0UdfZ5hgFg1eumlzvhtj+TEFDyYT0KY9+kcD+i1BVLT44R9+skTzg4nr8EHCpQWB73jMbtWZbrssFifIsMVEK9FJRqT6GjoWgX2Ns/Eps0WNcumUpmHTGeus1DzkIGHtis0L33P5+RsGM+EW48xkpTBh/eosRa9ORbYZ+xdMuxnsBBg3PDav2QzP5zn9T9t44wGxLag0I16YDygKSWZpvPNAsVwRzNQFuiWZqUPnAH5yL6cwXrkEnpV7tqzNgqXBNIatNcFP7ylcO7fDtRr56/tTGIXwR7+t8c5dydYiBGOJIRWtMdxcgTd3FCtNxa0juLGSDxa5jkJNFIurJnsnCYuu4rwHJx1FfwDDBgwDWGrmni79LiyUoFKEgzP4y1tw1M+fNoSuOLjIJeHXV3I5pGfn7/3ubl7hRzEkkaCdVDGKdbKiQza/RuRPUbaNQKGPRoTpGcp2wHkeUWpCoQK2iyyUkP0ull7Eri7jDIbUYhcEZDWXUdrFEy5yMiLTx0CMY5RyYT6AaVNyF8iCQ0pZ/ncWKQnBh+4nmUUQRwwrH16Q/kkyyC/S9fGruODjW2D/msRHJYZPqvTRVHFzU6NQ0CiWNMQlwdFBws9eT1i9an+qGuizKoievO7Ow4j+acJ0KrEcjcZQ4U8ziprioqXIpinrs4KNOUmlrNgbK8B8mpR6rYxeJ0XG4LiC2mIurYwDxeUtwfsPHLyaxXjc5vK8RVDOKFWqdLePwWpQshvIZpGzM8X07AGrhiTBwqBE2bapFRS3fj6lOWfy7jtliv+sijzs483bqCjB1xxkd8rmpkAMe9hXoFY+xj81iFsR115tsrU4w/B4iGeHHPUmtLfP6E8zFtctnl+FpiO5i6LbUyxUYGM+93dpujktc9LJq3jTzqc839kR1MqKgg2OBnGWg7qf5BOc2VTSG0FpC1SY4Rm5H8tFP2/EhhGYWi6FHIYQAJeXDUoVxes/jyjMCqYTxexCrpe/fwpHF48nUxOo1wX9seKonS/smJuH+cV8WrXXg5oFmZlvd+qP8mGmahEenYEmBZ5ucHtfZ1wpklTmUbNraEuXka0DgtNdZBpQb1yCUZ9x0kPpVu7FnqYwOEMXBtmki224pIaOkeWAnaiIgTamYwdok4c42jIVrYYQGWnWRhc5PBlKkMZjjEyRqIjQyAgzn2R0QlSwseza0yocpdA/siD9k2SQX6Q/+5dN9fxK5/QPPYAQYgX4P4B5cpXVHyul/vd/6HG/jQ/HB5uXg4Ek6qe8uiV4707Kxpz2VKFSrWpUKhbZtmLj+mdTBX1WBdFoKJmeJ3hCUXJSNlYN0BRRxeDtNxMevB3ynVXFpCAYxxpJyeLqNYPDx/LMiqtI04S5QkZlFpy6wVEn4ei2RNk6U1/hOQndixDNqXO3NeW4F2GlOo61gD3ZJyvOIHSbzDDQkoy6uYSl51+ocTxm/1ZI0FOUZqGmRTz8m0PuHXqsb10h8S+oahnpMKPon+GojCsvNLCXBG5R8N77NpOupDP0cGYXaC4LkjChf9ugou2zcVmnN8x4dCjYOcmwfMWleYgkbC3D6/dyu4DTbq5Jb09gcQ7K5dzkK4rg0iI8tw5RCiftnA+/GOQDQ/tn4BdgfQaeX4dfPIBmES7P5Q1Rw4bLK+A4GmcXGeFUcXkJdo4kaQA/eR8W67mtwOZi3pQ96kr+2x/ClZsa3Y6kUMyTiqHygab/6ga89wCiLH+acG0oWGCZECuBUSkSOzoHPYux1wSjgDJqqHBCYgjSk9sUE4HsnmLpLp60mZ7soOIRpuahjDxLOVoRjYS0e0SaGXT0hKmVEczMY4YljJl14tYu3cE9qqMM0ythKAOlFFYK4fFdTKPMuFpFOgWScYBWnqU9PaJ88YiiVqKSGAxdB+0fuXouJEaurf+SqJ5fJb6Iij0F/gel1NtCiBLwlhDiL5RSd7+AY38bj+ODzctuK2V1VqPggaZp+D5occaDNzPm1w0MV8Ny9U854ueL4UByesvn1S3BoCeZ8TSmkSRWgtZxTFllPDpNGTR0/BSCTFEpK8pFwRtvxdiXCuzvQENk3LikcF3oTCVXVg3un0p8pXF8DjYBp4c2en2GYDKPdFxiLaUe2wyTiMnZPrGKMFtnOIkOXn6dYRrhuCdcWxQsNAT+SGdwJmlHKUlhhmTzJY7GI9p3f0pxYvAffl5ENHSeG0vG22c0txbwbMVOW8fxTFZmZN5Q1nTsSoFuy6ExJ5GuxqUNRbVmsf3elNunGXfPNNbnJKnIK2oM6Ib5AowggOUVDXcC+JL9NoyiHHxdE84nOaCvzuRSxaM2DEZ503PnPN+BWivk6pqZEiw0BXs9yZ09QdmGxVmNxVlJp6WY9/IF1dVyrndHQHuc6+aVoZEoyVIT4gTuHsPWfK6KqVRzT5oHx/kw1KgCd09hp29TtB3KRpGkaKKvrXNxOGAaCOLePsIsoJdmMFe3UMfbGOMEaQlKUQU5aqO5JTSrgEKRTXtEnSOikkey+QqaEoSegTItSnqJDB1j7SXU2S5ZfEzlooc59UnsAWaqWIhSuu6AVPgkiYdbXMBs1kijEdn2WxSGObVipB/3i/myq+ePWh18FRZ8/IOBXSl1Bpw9/nkshLgHLAHfAvsnxK9qJ2y5gtZFRhpIjh4mNK5CHOp4FY2H93NFSlJVlAzFO7cTFl7+Yqdse2cJcxVBsy5oncHMskDrw6O9lDJw4zqoyGBjTWNpxUTXYb8New9TTodFriwsY01H+AON97d9SkbAJBVcfT5XddiGoLpm8fprMERjb28CXpOyJkkNHT+ZoLQmJgbB8JCC6uMbEcejkLliA0XAfCVl7CumZp3IaXD5ZYv7v5D4gaL3079jsZwS2SXa3sskwxbf/4M5jnp9qtNdot2HuIFF2K+QzAlU6hKFGt3dFoN2wNG4wZ/9dEzDTokzF78f0/YtLt2skQ4nFO0+jpEwW8mIs3wo6PACVAI/eS/FLhu4UrJchiuLoFmCk7birA/rSzmdU7QEhycKXUBnkvvAmHq+vWh5UWd1UTDqZzx4F7x5g+UFeHVDsH+QUrfhSk3SH0MoYa4Jb93P1+cNQxhMcyrGsXMjtpILzZogyODSpk5noEhPMv7LPfj5jobu2JRffR6jXODtkxb7vsXJ+wm9kYc0TSynSeb3UEmE1e/iVS5hxWdUlMMoidDtOQqRxWjcYhzc+s/WAAAgAElEQVS1kSRk5Qru+itgO0x7OySJoLjxmwgpcOKMZDQg7p2SdvZpjhtYWgOixzegAb42RdgNnPrS06rcsMvE5TpTf4CV/dNVz5bm5I3SL4Hq+VXiC+XYhRDrwMvALz7hd/8W+LcAC0tfbDX5dYlfxU74SSI42U+4cxDz/Vd0NpbzRcX7xylaQWd1y+SgJTnpwlpBcPmGydDP+CL/vXGgaFbybTphCu/fzRj2UyYTKNd04liwtqYTp3B8mnH1skYYKN7fNShfnkMiiKRAn6Rc37Aoi5hQZRzvpwyUTrWRT7t6c0VuvrTIvf88x6xtYQiTwJ9yeHrOZKSInR4rtYzGyjyaHBKMjjns75FlJppp8H//n2t49TqBaRI7FcJOj+KcjahdIXH2yGLJ8LzL2KxSXaoQVV2SwwnFcsAPvxtQchMeBlXu3OnDdEyoeZjrz2M1JEFT5/Vf7OF6JnvjPBHN2x3qsxq7j8ZoScZyNePquqA3EizUFLW6xkEP3j2Gs8BAFyn+DtSritNevofUtnLrgM05+M518Ed5Ylidg7kSHHagWIdaDKcjgVYyeP67NpPTmE5fITUNlaZ0hlDxQJM5Tx5muYrm9Ydw51RRdQVNcuOyUQDDieIiBruo0QkEmWPiLro4NZv+UEM4NUbCpeOauD/aQPTnidsx8lwgju/hDkaU7DWSeEJkpvgMKGUe5ukFTgyJDhQtipU14tlF/JKJMl1cvYBoCCZpn8w0yFKJY7poSqELj2JkfWK1a6SKmARb+2XRItMQE4v0MdXyVaye/yniC/vmCyGKwJ8A/71SavTR3yul/hj4Y4CbL1hfPZvFLyk+WKF3LhKuX9IpPt4j+mkDREcHKae3fOYqghmRsnFdcHicEaFhI9lY0Tk9k5TWDYZFjVeu5l4sSina2+pj7//RJ4ThQHK4HdM7iYFfNjKfZTKWxDqvvxESDzPMkmTGkVRtwdlU8fo9xcqCRiwV9x9IDvuCP/t313g0bmLO/oDX7CNcccGV2SLZvo+duaigwskg4Y2HJdLgBQCm5hn6bI1YCvp+imMmBGECA4eqPSBxPapFj5LdY75qYS6u4rdPuLUzQRMWtTI0GyahSDkYnjLsZVS2Spj1GuPQI60YGK3b+PcD/q//+VWUUkT7FuVegabUiBJB32tg19f58f/0t0xL65zuhyxslKjO2HQnHpNhiNNoELseP3nwkOTd22h9m0szGpluYvdTXt3KiKaCi1DQrAquxIr7QUa1qnFwLnnQhtEo92XZmBc0i4JHR5JRBJ4BngtFR9AZK1IB22eKsdToxhalDZMJBqeTlNkZQdCLUUJw61gxX87X4HUHuRmY44LtaizXFc+tQ3ek0Y8Va0XBXlvSCUzahkuqdI71AsXnZym4Ia0Tg4vw/2fvPZ4ky84sv9+97z7t2kNHZETqzNIFUQAawPT0zHA4RrPezJIL8i8gN1zRuOWaXHBJGmlcUKxIM85wOKRNSwDdEAWgJCp1RIYWrt2fFvdyEVWFquoqiK7ENFDAMYuNW7j7C3OP8+73fed8R/Hm33yFSWEIuteIZvtYWU3TizFeC89UuP4SWZUgpUYqDywXS/m0U0EsK9zGNeaBQdgKx2uhmx2y4ycgBHpyTppMsDo3qJw+1cVj7LMD+qn9qcwUlorJ+JSqs4ZyW+gqQ09OCWrxsVbLb9vp+R8Cz4TYhRA2l6T+vxpj/s9n8ZpfBHzyhH4/hmxcMQ3kh8uwPstANJtqjt667Gkv9QRPHwpsZejfshmXgv6KYnRecm+/wu1/fMHWBzr0X7ZE7Pi9jL6p+PKrgvnC8Oa7Cd+/l7P5vMf2rY8rY1RgcfAgwxPw3HWYTiWv39dcua5wmpJoULHaMCx3IXAFhzPDP//Pn/DP+iPc64a60jz9zjE73ZrZMKdejFlfG3JlSbI+lbSXnjB9mtPtQOYt8+f/y58wWGguohY9HnNtxSYPJIVTEKgRy80Orm1jMEhb0G9HRCVM5wGZLEBpTieavHTpVSXm4BHN1gCZFvRuG65fn/Pin/6Y6ckc8/YbfH1nwMvPVcSJ4cETzXEW8IO/WcG70aXIahzvcmGULUt2355S2DVREdLYuQvffpFr4zfoW08xixOiIqOIIs7HhncPBe2OTV3C3TXDzSsC375cQXB9DR48rTmfCQIfbBvOT6HfhtxVaFswSGs21gV1oehuKqKx4IVvh1zZUaxcdXjnz2bstBVJqnH9mlEO8+gy9LrZgY0tyTsnkgdv1uyeGW7cUnzlmw6dluD7P6r58U8ddHOZrBJc1CH5bIm2jrnyoqLqL/H6XwuY7GNVLoGlsOwePiGJ1mgBUTFCVzl6dEQjE4SWi+xuE2d7H8oAVZ1CVaOMRTI+o9QR3vaX8YIQ/fQt9OFfkccprdxmpWgQqk/fcORIj9XhlEH9E4pWDxuHoBaIeH658fHXJPDfNrfos8SzUMUI4H8E7hlj/tvPf0lfHHxyF8oHy7IGFxWdzmU5+VkGovFpSSe8DGkYnFZkiwrpXO4MKWxFpyNRts2db9jYjvlwwdbFec29+xWqqTh5WvDSrU+vEABaVs3VNUldQTqq2Glo3t2tOP5hyWDX4dY3LgkEoEpqbj5v8+BNTakU3SuCr2/ajEcGx4XnbltMa8H3v1OQl2Bsw+Ss5PrzMw4HT+ne3WTpVpuWX9NZnnNzxaPRlOw9qTh7z6BjyZ0th1674vBiiB4e01MWi8lDrvU7hHaDuk6opIdjXSCFJtZQZSkBI+6sKQYzHwrJ3vGUwr6G5S/RLB8h7v0U1wl54R+dU2GT6yZmOSSPciZvPuGrywtuXCkRQlKVBh2XHD/RrK2Av+0zyjvcfwJmPuL+vZpBtoJz5Xlkp8dwnmLHA+ISqrBBWjb46W5MMZd01kISo/Fqi1EmCBqC/WHGi1cyTsfQ61hoDct9eHdPs9G8lJVtbUiaSxajueDuSxaWbzE9M2gpWOsLDt5LabUvP5uLmz7dRs3TgWERGzqO5sYm3N4SaCX50S5sLHucjiWZgCCQhG5JUcC08JBXVlF3ryJLl521Fc7SPrO9M/7yvwupywzLG9IuHJT0kckUYXJMqDCLGdH+T8h9gd/awQ2XMa2AKJ7TSGrM+2Sp6xwPizxekHs2FFOkbVOdPsAbTVjK+zjeGmKyR1c3fikjhaqDPcuIk+nnIuTfRrfos8SzOLF/C/hPgHeEEG++/9h/ZYz5f57Ba/9O45NLvD5YljWbmo9tOfw0A1GRGmwHhkcVV9YESzcU04uKx09KGtcsolhzdGbYvnV5+j44LZk+qMmmFXfuKjbWLd74UUU9q4je17jDxysEmWmiseHgSUWgK0IPntsQ9PoQ1zXvvZ4AAVVSs/tOznM3BP1VxcqWoBEKjDHMUs3BcUVgg13CKy859Fua4wPDd94VDJ/a9FZGJD+dkQUNBDFfuV0SNizOzyr+8nWXm6+sYuYxE2Nx/LSg70+xq5TAdDlzEvKgR10n2GXN07NTBmofKTQ4S+SlTdO3KeYC33ZYDvu0i5T7oxkUBjVpEEYVvT58/c6ILE7ZO9IMhkukrz/mir7gtbuaRtNiOr0MBlkKbW5t+4zrktf/tx+SCZc5XSZliN6+xeqrtzk5qHCzirLQUBqOUo+1psOqcGje2eLdJ+dsKEXtWaxc9zl7VNHo2SSpJC0KLiaG+4c2qgs6LxACIiOpQ8GTqWTbhUFkuPWKy+EANjYMWyuCRWaz/47ku/+uZGmpJp9VnGcG15Os3rYZn1YME401kPT6gsEiIOtuU68rHmrD4lDwk70BDT9lQkD7+etcVMtk7hLXw4xOOmSQa8zaNezjXdxKUaUDePQjmu2raGAkTsnn5+hOF3X1LtrrUOWaWTzB8gTp/JilPCPUIbPZGVZ7jSAqyZKHZNkRTnubbuHSpoltub/23pZn0Wr5bXSLPks8C1XM97iMWfwDPoFP2vUbTUncVowvat569IvXCTu+IJsYImOoakHoQ2VbDBPD+ZHBWfn4c9sdlz1ytu/IDyuEdlfS8C8j6xrNj1cIUWTIhzU3e5LA0nQ8sIUhURJlS/qeJv1ZypuTin/8Tzxady8DqaOp5v6u4O51iRAG5QlkQxE2Yc3XtJXhZ49ChPLRus/eXpvX3wsw44r5E4XDFf6NmmJZOVOt0b2Ao5+2KeQFV7YaKNtBzy5I/RGRzJnqNdpLfRxg8vQBV/pH3LrVweiCbpjxZP+cs+Q62ULSwKbjVfjKxdEp0ciiXW2SFBlFdcz/9F+uUxQBVb75YbmfmgMe/e8zHKVJyoSbKx6FV/CobPLSt0/42nrMotDkjs3ZyTlHkaQIb7G06VO7IbbSZKlCN5cYri2R/WzEijDkfkiy1CPLDPfOUvwllxTNbFjydtRkri1mx9BfdUnGY/o9w/Ydl6+sKp4eGU7nijf2awa4hJ7hpW3N0STAajYR3YpqWrP3sGJ7PSE/i1mxa25ftxg6ksFU4Pcli8xmITqc2V/noXFYiJC1ZIy9uICsJjmxmf7VDkW7QbVxjT+PxshoQiPYoKvaVHJA1+pTt1rUR/dRyTEja4ZIGmhfINZu4q7cpfAs5uMj/M4NxHhImU4pYwMLaM9KZtED4rZNw+sRim1o3oA8hqgC/mHMPL+NbtFniT84T3+D+DS7/iQWvPhH4aeS+cdXBsDJCXzrJYv9kWE2M0wTw6t/EjDNrE81H32yQuivKAZHBUUJG5/Yg372XoIeaH6Y1jiVRroayxIkhWalJ2kG0A8NjWXQ8xq7qYgXFdc2JLvnmvsnhtMTTeeqy9Yriv2fJDTymrFucVE0KQlxrmxSnaRYfpuFbzMYPcVLEjzTwEk9Zo0Ky7KYFBeo/hbTZEq3aSi0IFIeF6rBwrnNaXZKry0o3AGvPOcT9PucVz1OypLU32dvf0RL3yIwTY4nEf/iP3udVgQv/tFlX3y6n7P1sd31b9HZ+fmcoWMqdjYF935W0g3hB/ddXvJW2WzU3Lkbcm8PYkfhIbCZ8ea9Xdw7L5NNpihl0VmxUWmT8dkFnuOw0hri9TxWr/dIVJvp7hlJXDKISh4c+KhWg9bOOngBzpNd4ouc1ZUmS5T0hcZrttB1AK+uE7U9rNEhZ1nFeKAYDhIO5wEvv7hMHhiOkzkvb01olFPeeqDZXLdpioq9C3jrseK4sYbxDI9e/Se483XyyWM4+XPsWBH0X8I6eUy5GFJnfXSdIqUhEikmTvHN5Xfpg8zRMLUYtTuwvk3dsKibTdLhE2SrD60l9GxGNXiKHydknSZnxSlreRMlHXqNa1jKoywTovkIWn3SdIQszD+Imee30S36LPEHYv8N4tcJ/Pi0QefwKTw6h27DIlgTXFlRKBuS8acXSJ+sEDodSZwo9p7U5I9+HpahpyW3VgTXXnHYe1zz/R/WLObwL14T+J7g/jt3uZhfGo7ccJ3GO22OJxZadBB6wt7ZnMq+RS2XsJ0AgHzxkGXnTdobDsb32Vxvo7ot6iQni3wKGbDYuImY95AyYFQMkcrDrGxzWvyEFc9hXC4zORswOYl5mrbJ+jdxm8sMwhss9Jgu3yFzPQpniUZvmaaQ+N0+Dw9+QEWJEg7zTPI//Nc7zFo9+J97ZLXPCzshjv3zdldRFuwOLr/615crymxKzgVFNmK7C6djzfqVDrmXIWaKs4lGujaZcPE9CYsZkeiw/zjHHp7jRTGuEyKydeZsMfz+91jq5Ww8kdSB4HRxlUUpUdE5T+MrjL0vEYx9ZDHDHjfpb6wxzY+Ivxth1wVGBbx5VHKw+S9xVYB3/B1WxS5y9TZplhJ0GjwZK85HFvnZAeVqgB1NOR9p6jccynrCo5OE89ohvfV1Mv0f4U89RKdP6gbkuw9p2wa7EbLwS5zmGlU6xVm6hlQelS2ZPfgRzfJSnfIB4cV2hfTapL7A2rqF7G1SVhH5wdsE6ipMhpgyw1t/AdttUbg+s8GUKk3w3z8d23aAtxgyi+6RpQNMoi5VMNJjYkX/3gaZv41u0WeJPxD758QvkxP+qmakTwudeO62zes/yujelbjKkGeas5H4zKVen1YhLNKPVwh79y5vHjMpsG3Bq1+22NxWfPdvC05izckipL2fMoosxgPDcm9OlZWYYYGTVRgjsS46uNoCJu//gKUtzrsu3kqPVthkEs8p0oy5vcK4iphnhqR7E5mcoewWauV5iv03iaePOK0lZ8dzGvEEbQJ0eZfYShG6wOpvIJ2AmhWmzjVm1ZTLBEsNSIp4wWm2xNlEc2aO6bYuuL4e8HKYkupjHp9cUD28jq2aVCyoSYASM6ywpSYZS6atBqKzhgqWOE0H1PkedeJRaMPpRYXjtTDpDBmA3XKphhnFD/4SeVDjJy6tzg5BqbAnF3ipYRCtkeeG+eQQO5xTao2TpYyrFrl3Ha0c4pv/IWU2xls7YkmdMJ77JCcPkUaRJTkP4y5FHqOmY7x0BcmMrWSBR0Q5qxlVNpm1hdQhxWiKnM2wzhVZ0EB7txCWh8KQJwp2H1Cv38QkLub0Ifb5CWXQZe5W1J4PrSbGtrHHIzSaytHQajOLJ4hqjpyN37fr10gkVtACy6dKF9ieTyltyqOfoY726C+/iOt30HWOKxx0u8esOCWxZrjCQaU5WdPHbW0RTFcImxaj4UMKO0Usb+NgI5OI4eIMUU1QwibMBG0dPlOi/6Lr3f9A7J8Dv0xO+OuYkT7ZRokWGreqWF+VOMHl/u9pXLH1SvALbxydnc+uEP7T/+a/YP1f/RU3lz0qUxAGI3qhwhKSt0/mjBaSuJzR74EWAYXdxLIkthtQhpIIQ3wWkxcrTNSI2DMYAY1M0iZgkqwzO13BHpyzsB2y5Q102CI7nULvOv7SJvloQK4rTJEw64X4O18G22KenDCU+3TVMr63hDi/R5KP0CLFxcIqKyb1Dm+8+5gvPV/R7CYki5Q37y1YyK9hNTM6MuGF201kQ5ErGxlVLNcRxxePWJNN1tsNVloZSVVg2SnLzQaVPWe956GtCcLfIEuXefv0jItzQc8NWe8ZtjcURW04PV1wcKiQrmLbH1O0X8JkEk/PkOMHeGnAvLDwutsEoktW3qaKBkg95+LikFl7nczL0WmEGexSVgk5hovzIWt+TdleQkvFBQnZzjexrn+VMhoQ//jfEKY50yTBsyUFNotRimyNCJwuB4NDunFGZpYwXothBLVYoasgH5wxH/yQevcNamnwFime00Ut36IanUNZUSzOaWy8glUtsPwACVSTU4o6Jl1MWZ5oHNW5tOsLQytzWIzPkF6ArjLC0RgOH9KkheuvXJ5+oxFeUZO0AlS1jhSKqt1jLg5xW8tYeYxfK7QF8/UlZGuFQLVYxCcsnAKxdZuwVNh2j8XogOr8nP5HouyehVTxi6x3/wOxfw588pRdlYYyqnjzr0qUKz5TavhpZqRPtlFmw4pmINjYUty4fXlCj2LNwfjSUfrBTaUfGsqyZjGE+09ymjse/i/4VOvapdQVjuUSJ33SIqIyCWfjJlW+yaRh0GFBoyfQ7Rb7F2c8fjRB6zWQXfJ4DC2bdHULq7+NlJL57JTsaA8T5Sy0jfBfYW4VZMaDUYYllnBbffRihO8uUaUJSXaKvf0CXriEqgpy5cPOy6SHj9DGQzeaWAno6QlF0COfHUPo8r38Wzx58xFdd84i95iqb+K6NqHVxjf3UK5CNJdIixLFLs9tdajLKXf7Gl2MkZbLPKp5abPJJFbksqBtL5C25vH5E/A2CDdfZTw457X/OOLpHuymQybzit20T7Pf4RuvNHE9ybUnPyHJ9rj27eusdwu2lxP++i/nbH5tBWP7DAc1KlngmZy9vQLnVsgP97cpfI+D1/9f6G+h7rzKdPuPKd/+M9rMiCsP+fItdrYtZGOPeWKTPp5z447CD11KY+FLg9vtEw3P6ax4zN+b8o9ePWCWnNO+PaWx3qDROSWaFrzz0OP/+u/v4osmOo2IFk/IwxlisI9nhbjNa4zzU9JyQuyBZ4GKIpqmgSOXCNoByeI+hRWRiYI0OsWrrtCJbLJ4SpWM8UcpwYWhdCKKi0e4wqFRWWSOhfAaeKqFl0my/IRaTyiNRbsKsYXLwkoQQRctILVKqqVVxOZXMRrykz0apUQt7ZCmEWflAF/WkGeUzQCve+0LKVV8Fvi9J/a/7+4W+Pgp+wOp3J11QdMRjOfmF0oNP/neRQ33RjXP3br8vfnUkNmG/pb94e9/9Pnj05J+aNDzmvW+4PoqHB1p/vpvIr75Tz02blmXmvbv5aimordiUWUxuupwMT9jpQW2dCjLFoO5jyjXSOyEcucWQ8flSJ/gyhXy5W3qckFL+zQSyIMI3QopV9YoPAurNpSexXCriZjmWMWCap4jPAcVnWJJH8ftUJ/uQWUI3U3K+ROK9Iym/bVL56dOMY6LWrmBGA9wV25TOzblwx9hjh5iNu8gtKHavIEf9hiX32ZuB+j5EHvvIWZ6RrPzKlneIC5nNC2HKp+y0VPYlSCtOixy8EXE2SKlrDxanmISV3hC0/ULnKDJyaRkrkFIm6wIOU9S8laTur/GyNWIi4Kdr9zCrC2hVIz/9JivvVoxy45w5iXNTsaXtgt+9GiF7qsbNPwRS2shZ7tzXrwxplYnvJk3iZxN5NoGKghhfIhYXqG8+xqjaET66BGb62uUJyeUxTGLcUqjijFCsv7qDqdPI9LBHHN8joljRDvkT/60yZLfYwkol1ofBoGfXUj8rXUC7aGAxJYkV3cwQqGWrpFlCYvRHmU0ojocI1vr2A2JVaToyRjP+GhTM+t5tJwVPDlnNT9h/PTPKP3rhG4fp6iRs5Sg9kjKmmJ6Rh50KZXLwspR4xm90sb2A2wCTGkojMQWl4ebyhJIIymKOc76DYp0AEELmSeo5hLFZIYtPZKmS2CtY6s1Zvk5VbuFkwksIb5wUsVngd9rYv/77G75KD56yv5g46KUYHvQtsRnSg0/670fPLkMz3DV5RKo526oD92kn3x+kV6e1Nf7guD9xxypWW1rnrxXcL4vKeOaGxuSwqpZ7Un6xT4gmEdrRNkUI+ZEKDLRxrMrZirHaa+T1HPS9i3i1hJCSKzR20hvnTh6SGUqsqaLvbSFZdnk8QUT10N2v0l4MUIqj2j4Dq7Vwo8lqrsJaUQwy2E+RKsY9+KUfp1SjE6owzaGAmnVlJMjiKdE44fI5gomDHCOEsK4ZpIO0a0WtvKpnACzGGGrECtLCTOBpSHnBo+P/pbbzSmmjJB1yd5FxdQ0KewLmq4icGqcWhOLEVlts9r00KVgUTdRjYBVx2L8ziPktMmJ2aL/xy8jLIv4Xz+msx7TceZMd2Nam4qL/BZva48Xuz/jj7+U02hKkshCzKEYLbi6aiNti0r4NDsOWWkx/0nAsD2h6q0gGteRXhPnve9h53Oi8YA0qjj4zhjV3aHurVKrM2SvTzT8GY//7wRdnaNCj2ik2B8+z8G7ffb+Dw8zOqSdWu+bbi4HguPqjLrZQbpQhU2mjkO1skp98B7GRFgbmxQdD60k4mQXtZij0xxL+6gsw/b6TLMzpNei716w0nZQ6gpJMub46G3i8ys4xrlMKOo2sdprNIqIERG1VaPiArd7hUxlqDTBtgPcWlCOT6kbl+t1RZ6hkpRC5GghEShYjNF5imOF1MzQJkXaAY4oEEJczgPa62TVKfb7RP5Fkio+C/xeE/unDSx/Ubvkk/josDJPNKInuBhBe90mrPlMqeHevZyDBwU31gFtI8Sl4efODTgYC64957I2dZju50TxZWzc0X71obxwNtU4vmAxvFwc9QHOTw060zRlia+hUWsO3hOMUfRXbZa7LnN1gdJrxIXHoBug37dml7UgzTPIpiRNhVq+Qek76KqksmrqMqHOxqiqRtoBQlcI5ZDpBLF9B5lmCCko2k1U7+vU+/cIvR52sAzNLczJLm69QCZjbBR27VA/vYe7/SpaaaKwpB4eoLafxyxfoZyeYpU5ZbOFa3dgtkvtKuJOiCUdLCmRiwSloV24ZJMDyqVl7mfP8fTNfZpmxKjtEoVXoTUldQVxVzKfzgiVy6PxjLiKcRJNHc8ZJGMKtcay5yIHFXZ6hXYjIz0+p92CfqeidlapB7tcdWKsmUuerFLUU3aei2g0L78vaemws10wGpxQux66ylnSEcPHKXPaeJ0W7vJttGdR7b/HViNnuVsjVIMqjJjtnrMfjan9Jkwu0IsBsVCMioA+D1i5toN2QgaThCXfZipXiM+PaVXm7w4EdYIREmt1h2kDTHsTp7dFPjpGtzuU6Yii3UK5TZreCurskFpouBiB7VJXGVlyht+08fqS0tKIuiQIemy1J4yjAqV7TNzow3CLioTm+ssIKakv9sHwvrTxGFlJRDxndVJRLC6vMShyHN9FNTzy0z2EyREXj3E765imjSgysuicMJd45lK+qoyg1prK+jmRf5Gkis8Cv9fE/smBJfzy8OeP4mPRbkOBbfOJvNFPlxpurwlYMlxbFR8GZDSa8mPv/dHEovlRydVNwR99y0FYl3mnqmNzMjMMx7DUgziB+081N3vQbAtkVnPziuBsqPnRyWWbqK5rjFgwEA5nKxpr7Rau1yWxJbPZKWbiMR29h+y/Rilr6nhCPdjHthyys8cszUoqy6eKUvKLp6jlHco6hyzFjI7RrRVM2MQOu2RP3qB02gRRRiEisqM3kaVC9a6QeQ1kkeOc78Fbf0Xpa6yVZZzeBlgexfSEMpsitcbuXWG+2COvF1jKR7RWqG2HKhojJ4fY0ZSgajE3GvKcwOmiU8U4aiCyU1rbKa22z8LzORjUpNUaIh6SjATNekbfs+k5bTrditPpnNPDNfJ0C+W1+NZX5jwZTHCXukw7OaPjC4piwe1vCJTKePcHA3Znmt6qxWJe8+hewU9+mGBWbNyGjZXY6NjQs2GsK+yeTcgUN0kxtYVfpKyJFKVdal0T5oL15auko3khUXcAACAASURBVBGz1gr6yVtIUePc/iPm6g6D4RHRwKDzKY61ycZKh+R8QJqNCUsb5McHgnFVspeeUdQNSncVURYwOEDZIUXQQl+MUOE1XBS0XczFIX6wTjp/m2CcU2cCGQqclo+3tIoxFUkyw4sSXCOxrBz0z80+ZZkw1zNEOcFCYlHRjirSdEQ+O6SRupfKE9W5DJyuAUKKKGOWTKmr+/jNVZYKRTp+Slz8GD8qcCtNuHIH27uU1nrGYz46wNJg8L5wUsVngd9rYv9Vg5x/ET5IH+qt20z3c5B8uC7gs6SGjVDiBhJjYKUPZ++3az7tvRejiq1lQRCI90/28rKqGNdsvBTw47cSOqGh3RHkBrQEIS7Jvq5BC4FrG66sSMrxEVM/IOlvIzY3oNljlpzhuz3s7iqV/YDi8HXUxVPqYo7VWEZKD0lMmgyotCGXGooYuT+iPHqA0AtENKZutaiCJmiDXgyw4xjXbZPmT7GKChnHlDe/hNO6gi0DSp0QB+A9eUir9ullXU7mY4rGKZZt4+GgkznCOEQXD/CuPA+VpNx9l1JnkKWUF09oplC4Crd3leADs0ljiVy1OU5gojdpxCldkSK27hBYHpwdQPYGd7rXCWTMsu9hS4lrpTw4zpB6BVVVKGm4uTLmdBQTTEcsBWCHFXtPS8gz5tEVjpvXOZ495Uffz2g7Nf/yn1nMq4z7RzU//k7Cq19dodnRZAvF3jDF1wmti4eoxlU8vUCdHqGqEttt0HJXsBt9urNzbO8qiTPB9lqUkxlusYutXKS7jBsNCfMSU46wJjPaM4Ujmx/73hQ6I+k2CVyHoiogXlBncxynSenZSCGodYWVxEhhU1o5pSghX6AWczaSPrFd0W6ukkcD0myKDAIKX5ENjunnmrpuo3h/nW4+IWm4WK1rmLVr6KqgSsYQ14S1RSN1L6PpPoV4HemxjEd7mBHPzqiUoFsZtsoGjvQu97rEc2oVIC0XKST++TkqzSmd8y+cVPFZ4Pea2H/VIOeP4rOGrb+KGemjFUJ/RXF4XLC1LCizS8XLgyeaSgke/DSjqEHkNT3H8PItQZbD44c5owSSWc3pAO58I2DrlctdLovUUFoV7W3Fv/53t+g3NK7J8QOHB6eGd8ZbTN/Y5bT5LQo/pSYCLbGXtqgmE7zgUh3uqQYEPUIaVINTCmmQrWWcxjJpp02lJFLa+GGPanSMiDVRliG6W+iqojx9F330Hk3ZQXhQ6pxABNS9Laztl8irjHx0ytyrKHshkzHYeULtnFHVAul4WJ0NRFXgqAYt06Qqa1RuSIZH1FaNrXwcv49xO9CoydLiQwMMQFkmTJhR9pdIvFWy9hqifI+ecinLDKtIqdIF3voKUVTzqKwQdYbSNaUxSDXFyT3SswH+2jI3dwqsk4RNd0bDSjGWS13mvHHvNktmzvlBiSM0tzYkoQvtZkQ0czm0LA6fDmDbYYxCXdmm8a6NPTiDwqUoBrgMaOGg+ktUNpRFDLpNcfIe9uw+y2KLPLJIp2e0OgWUJygjadKliGPEOAbanNoTSipsY+EZh0oUWO07tCxBYUrq5ib50jb64B51NMUUc6yywJpPqYIGzBZIx0MPjwlKSakzZnYFtqZIDEcHu6ysL+PYAVq4HJqKuvBQ6tLscxKfwsZX8CyHeHaGUQ5ec5N4/pQgzn6l0/RnyQ8/TXPeLxWO7P08iOMPJ/WP4fea2H8dZyj88mHrL8sO/WiFcDkUdXiwX3I8MPQAoQ0v7Fy2ZB6/V1DUhkoJklRQVYZkUmFnmm/fVUx3YO8444c/1HgNSXfVorVhs8g1/lNBuwNxWXNvcsZJEkCYc+TepHzpa9S2RLgBiSrJswg3PkEKiZiPCUWbYjEjcF0WeYzs9pCzMbouUWs72O/3TlU1ZiFSamVoDqYko79F+z62F2C7qwgnYFSdQjIkyEKMBVJI8nTORE2RG89RKRtTLqiVizYl9c5dbMujjua4WY23dJX8yc9wsgocF7u/gXPleUBQHr6LOxkThOtk2VPc9+3haTpk7OUkgYXldiCNyMM551xltHuKmh/iRgon7jEvE3q9TaQRUB2TRSOanqERDjifCtTFAYPHZ+Q4UBXceKVgdU0xnUYcPijYcsd4VoE6zzBoVrs2oS8Yz2qaIdy67WACj+0XuxRHPkVlU9ouRW8VEe4g91IKPaSyF+jhLibdYFgpFkmbjfz7dLwUS9ZYEmZo5jOPjokpyynj6pTZMCM313A3r5K1AoTXIJsN0XHMuDjBdzI84dCY5szlY+xGm3h6ir90BRHnOElJPHmDuruC1IKwMDRmGV5nh4E9RPSuIlavYsQmg3RCNY2wyanHLZTaxHbPCd8Pt3CzlGo6olaSoMhBCIyy0bNT2nHjc5+mv8ia898Efq+JHX71IGd4tsPWMBAoG+yG4tUX3MvX3raoSth9VHK8V7G2BJNccnghKCNNyzEEgaCsBFoKvLTgWzvQWBV4TfjbN0v2a4t3DmB3fMLakkCFiuXuBvvjktReRrWWEUqSpENUb4vKnlPuxaSTd1mLDLUdIscz4iAl7jWRy2uINKOaHKEBJR2wHbxcUrkOudOkbi4jFhPK+By7v06aThEtD9ZewxYes737OOenpHs/JW4q9AvfQHY2MPNjdHcJvXIFvfsWWIqqTCEd41xMsZ0lZFHiaI9EXnZtmVxQlTEMDrGzjKShqWRFPn6K1Vph7Jdw/RWsco7ttmF8ijw5ps5n1FkBkwkhIcPa5uFFzgtXclQ5J5QRlmtxfaNFoCv8YEhbl/zJP7WIk4QHTzQHZ4awqXn6pCAsK5YaGrfl8qUtwdER3H+k+dZrFr22Yf88Y142GO6lDCcSe83H1lMGT2akrWVUfs6mM2C9tY1jJtTTA86P95jGOyzJXXa2Gri9W2QNDxwf7BMeHacM82U6RQtde0xY0Fi6SukqhN+gVJC2Pep6gN26QhV2KJ0GaXKBihLEYo4/OKedN6kbIU73NnJxSO0uU148ph0pGjRJA4O2NC0ConhM1Wlir98lOn6El1U0VB+lfEp18SHRetrGFBaW9gAfDNRphii8P7RI/gHwO0fsn0d3/nnxWcPW8f0ayH/pNf2iCuFs11CWhslxyfaKpH8HPAFn9yqsaz5P93PEwnDtimBlSbH3ds4rNwWLDOJCsNyXfPNVxb99XVPqnM31Ho1GQEpNTEDdbROOCrLpgLrbQykfOR5Snz7AT1K64XXq6ARnPiUTEebmtwiCAOP3QURUnSXG9Tmu08eqF8x1zLzXRzV3cBprlPmcKlulQmGaHqq7ieO0ke0V6sUYWUAx3KMOV5Bpiq6PkXVGvbqN7ixjuqtY3XUoYqgFcpzgVALiGFe1Ccc1F9kDqnYbrzQIt4e15SH9NYSpiecXpNN3ybav04gXtLVFQY7pX0HWFkq7tKZTgsyQdJs0WpschKuMTn5GMH/ClzZ9/OAanj+lKiKub0sOdgW3nzc0mpI7N+C9g0vV0jtvV/zzrwpyfxXHGrG+pagLzXffrnj5eQsBHB7lLMo5t19dYzq1qaOEi9OISf4avd5zyPgJS40WvmhiTBNtG240FCIRpEoTdK9iKReZFhTFHOMKlCoJzQ7CcbEAoU4pHIuCksK3ke1lsAzGVZi0IB0/Qe+8jOjcRl8c4U4nWJWF1iUmjUmz9zA6xw5atIsGXbsNwIwpDg62cGlEOXl+TFVkyMkpDVaw7YC6yj6mQvn3vXvlixyS8SzwO0Xsn1d3/nnxacPWk9OaalGxfVf+Stf0WRWC4wuO9kvubkgaoUAKm/FRyfqSpEprljcVk0NDb8smCARZbAg8mGaXuvnFwpAtKi6eVHhBjRXcQvoNrDqi02jTnIE9KzG1pDh5gmVqXLuJnyrc0kGkEXp2Sj9uEPsalVXoYkKZLlCNJcq1G2T7b6Gkj+6vMsuOsJevYgU90sUF9tpN7LxLevQWob+OtXwLMTpC5wssv03lTVFI7MkMhqcUvo9xFLq9iUkmWF4TazpAWxZFOiWa7dM6y1ifCBKlSaqEMIXCRBiviWiuYqUHlPMzTLON6K9Snf8M2VknI8HVAX4uyPMx+eAR/iCinTeJXYXVXsMhobB9ovA1ajFH9jKUFpRaIm2HRhvOIpcfv+Xx3I2ElTWJYxmuPedy8KCgtwryvkupbJQFnVWbXJX8+VtQlIbz2uK1VyvGszPiI4XT7/DlVx2+/29rqirDMTM8qcCAqUusymBLhWVlZLjUBj6aDFwKKGRA+JHHbBwKSiphEI0OlnKp9RzltlCNkPrkPtZ0gp7PqU4fYdc26eoqVWDTC3awpYO4eITe/Rl+sIWxLjceiugU11ulVDmZqlFGUkYj3NpCuT51lVHPzrDTmIMwpXAlTq5pjTQmSX/ju1e+6CEZzwK/U8T+eVshn4VftQr4oJXS9CuyRc1sanj8pOK1r3uf+5p66zZvv5vx3OalWgYBC2EhGnDviWH5qo3pCQ4HGs/TYMG9PYNqKMK2ZD4ocQVc3wR5ZlPrEWlu4yibKo+xMk1RNinGBxhlEGGbqogJJ1N6dQeZSupMEtsVqa2xlUXDakGpmc8ukK6De36GsiLM6jYinmE5LVzlU1QZSTZG5TlmPqYKVzE6Q1QZziBHVCXV/JxwNKS1eZ00q7A7fRZ2hTl7Amf7WDe+jikzxGyOGhxixylh7QIlZRhcOg3b64g6Z7J4jL03ICg9sGzorZL6Nibt4Xe3ST3B9PyIfu3i1AI5i/Eri5lfE4uMhq5RtWaanCA6NyjLmxzkb7PCgJb0cU3KNMporVmYxPDj7xbcftXC8S9dwN0NxaPDkjwvqdpNDs8Mw5nmla+63HzO5ejMYB3XhErz3PMV336+5NGJ4nwR4FQp2XCfxCQIqdGyoI6GNCqL0lTUtQulzfkkZqlbUjR9jNNgMqjIwg0iR9GIcmzhfmj2kZ0lyjyhKFPK2T6116DO5gjbJQy3KJMRadChDLu4m7ew5qek0QQ3KXGEizOKcWbHHxLyal4xaw9J2x52ex2lNe7FI8x8QFpO8LSNncYMt3qoredxnSZ1sWB49B7rJzHd+v1ou9/QWeuLHpLxLPA7ReyfV3f+afhlVcAnST+VFmcPM1bbgpVlwXAguNjNmFwo2n1Jf0VhScPBg+Lv3Ch+0Q2k3ZF0rrrsnZc4FigXVq47IKHqXJqWZlPN/sOcv3i7Yryw2T2r+OM/klRZjSvg0bFm44bLyU88BDnjxQnt7hLpLOJ0r8CMKsTobbywTdlu46gGlpHoOqNYDBG+i9W7SqMcEpcRc6VRxpDrDHN+imdstOPgWB6+bJHPzij8EKu1BlJhlEEVIMcjyuTHWAZsexkxH9M8HRPmLqkIcSJDuvcQ18yp8gliMUXEKdbKVZTfQbp9miG4ssWofI9G9xZOJsiqUyxLEBYKL8noBktM7JS0jslrG0xNcf4Qp3eF0rKIB49wLs5xagtr8/al05Epc1kg0xxPLjE7fUhhaR7MbOLAoati2pUizyv+gy8b1jslF7Hhp9/P+dKfXhLJzm2Xw3c1j041utYcNiUXsaTdtDkYX7bXjk5imrYhmVXUBfStKXkRYaJTmiOHyhRcdGash4qmdjBYXMxLdNWnDQyHNedVhV1b5EVBOYvoqzm1qlloRduYD80+o/iQOl8QeQIRhFRSABYCTb44JV+c4fWuU5AilI1rBXhBiEhOaOBTek26efjzwaSCJB5RzuboJEUZQde0kL0O4nSPbt3gIExRW89je5ftG+m1Yet5RpO/JSzf/3/9DbVLvughGc8Cv1PE/ix055/EL6oCwP47pP+jH+a88Lx6Xx2hCZ2SuxsC49SEHcnDxwVlbthclrx46+c3ivnM/tCc9Fktm+1bDtN9Q/9joRCX8ssPbgquEjgti0ZtmJeSf/UXJXlq+NpXFNvP+7Tbku9Ghsqz2M8t5NxiMA05T5bpFCV66y7G9aDIoYRa2WSnu/ilxNq6i6U8mqZHeX7OLNDUUqBNhREC+8pNFDZJr01VXlA+fRNpO4i6Rh8eY4dLhO2r5PEF1mCCzDPysqITGZYmNdOWg84STDojFIoQGDU8inAJIX1kuIKVRjilRaNykZZLqmqEU1MriaqhkUtC02FW7FI7GaaOiYIC/HXUlReo8zn50Rt4i5Rg8v66gff/LoDQBMycmjgdIqgQq9t43WXi+BUeD94kjN5lNZ9we6mBkTXnoxLP0Sw3YHpRcWVHXX5eL/oc/X9blDpGtx2WOwLnI70Tg+DiuOLuNYv2CswWcHGR0yxcPPogoJh0GSymjK2curbQVf9D4utHGSc6JTeGFfuMrZUQZdnE9RknyTH1aPNyla3qYOcZ+4s59todWLtOKQ315AhL2SS7P8BvbWK7LcpkQb04w6sdhLSpLIHOP8Ox6Xq03VUuI43f/5s+EmFXuBLX+bh23nKa5K6E8uftEhP2yS1DScFsPmZ5kn1mWPWvii96SMazwO8Usf99dOe/DL+oCvg00u+EUCaXGxZHFxXP37IpoooyEqxsQGBqHo8Mr73gfrgqYGtN8xffS3hu6/9n701i7Ury9L5fRJzpztObZ07JJKsyq7uqq0vdag22JVgLwZJ3ggHDO60ECPDKW+8EeCXA3jQMr7zw2gbUECTLqu7s6lYNWUMOnMk3j3cezhiDF5dkkplkJlnJUlV18VvxvXdf3Mt3zvniH1988f0FvQPBKJz3P91YEc9JNi/bXIXPIoCHfcPsTspmS7D5LY+88Ph//yJnYd1nfWN+OXtZg2nuc1qUSOx1skYTXwzoi3u0lndQKsTZHDPtUZ8UIMsQPq56iphUpKTZANtcQjY6hEahO0voeEQx7KF8D2/nfcJ7P8SdHyH6J/jpFK80IC+XUbmmWdvBNRR27xcsDDRFZwHTKFEsreEw5P1DAhHQrCwyHu9TKAvn+5RzjyjRRFpyXuzRL+VMF0PKqk5kJHo6ojSa0RgViMkjCtVHhyu4zgJiYRNPbSFaS4if/YBKmkI4zyR5Al+E1JOUdNwnVgX+zlVCG+KVqxQLv88on7LIBVfeWWd5RzE6m+IyS9OL2b+f8953o6fXyja3mbSnNELYWOG5CTuJLe0tj0HmOB/N90Haqx5C8rSqDGQEdgXs4wfxGekikBGNQuNsyk67g/+4UUhdKErhgAtZ4BE9fa1NzyiEoTz4hDoFRtSJl68SnpwR9Prk5XuEWqNnMaK9hRUWkaWY0eiFG5xfRZ5BZjH5ZF6pP4bJJwSZBeZyiat0iKshsrVK4EXobMzZw5+y0f96Wvjf9CYZbwK/VcT+ur7zV8GXrQJeRPqNpmAymv87TxzL64ILqTg+tBQH0JtAs6OeC+8qCsfkuODSdwLKJUhSOD8pqK545MkX/4+f1+afPbH6k79IubHsCJRj/17BlRsh3/t9jw9+klOvS0ZJRC/U9NwlsspNSlGHEjDulNGjI3AOIQRChVDtEE8fUX/8sD45PShbO9g0wL/6PrJ/jBfnlLwm47IhHx9Rno6QRYEc9VBW4JzEX76ODcu4tcu4w7sIG+CUQNWWGQ73KDXauFqArVXxqgtMWxX6ez9Bne4RGEllpDCpRlmfMPe4KGvGckaw/T0o1YhrTfRkRrkImU3vslxIYj8naZTw/SqFCtC+wuYzStbDhSUQ0xcSlLKwlEScBSlYSG1KxggnZzjRZNqfkPYk015MuV1hmlWYJinHFxNGQ/tUVpPDPRrTR6ir+rnMn40VyycfOxIjWFxWWOM4PdE8OjQYNyO3r0ZslcIjTk6QrOOcw5kCM+1SswH9x8f5nyBTjq1KyspyC88P0UXG6VmXU2HZSWuMLoaoxgo2McwO7lKkfRqjgoYpv/CzfBV5dhKfk8NPYeMm6rHGrg8/ZTWZd13SniBTDtlaRfklALywTtZeZTY5+Vpa+N/0JhlvAr9VxA6v5zt/FXzZKqB/UnyB9KOa4uBEszmzBBF0+444E1x5P6Jak+TGkern3+NwT7O+KnFuHgtQLs2jBB4eaIL6V682nkww04llfFKw/a4gDGD2yBF3NUsdSW4E/+FuBy0q3Ck6zDrv4VtBZXIBfsDMjcFo8otHBIvzFmjWGIrJGZVifhs8OT0ovQjrNAgIKkuY6SOsyTHlCp5fxW+ukSZdTKUCnWVUYxWZG0anH6LMGBwUIsMnJKo1GFQFzrOE9RVknDFM7jCpOKhW8JbfwVv/JunhL/B375P2j5mVa4jyMtHSNbyr38X2D5GDC/LRGXY0xo/7nC20cdU2XqdNWvdxkz6qe4z1Q2ZpTH06Qyto5M8TVJ4NiGcnhJ7AH40ZPPpr7LVv4ddW8EyLOBlzerDNzx+dUb2UEpzO0CLgoG8Ithf45N6IGjOGuxkb8pC8WnBpmS9k/lQqgqjt8em+4fhhTrvsWG5ILq/kXAz2SWZbXyCiL2jS1iMaK/T5PjL0UdpR1QqHwhj13MNbd1MW/BilOgAoJVnwY2I3JZAR5cGQXtp/6mBZTXwqXvulFe5XkWfFa7J6PKQ3+AHZc2POZRZPz+WX4JkJ1dmcAB/9BrTwtweWvhy/dcT+pvHlq4AXt5qrbUf89YcZ/TOLMppv/0GJlapgOrOMjcI6x3T22e+cHFtufjPg4NywuSSplMEYx+6R473r/ld9xKerilFX01mUTGOHQ1CuCtoNuLtn0EGJxW9scThbwrVuooSPaTbpugNqQQ0xGuMv7ZCkMenJz1FeSJgaGv2UQM7J4MnpQe0NiOIR+vwY1VjHCUXcf0ThayimMDtBX+wi16+RJn3Kez2K2gLhwiVSabDtBUQ8IaCFq0tsb4+JmNKwljzyMc0NvGYV6isU53uI3n10vUbaLKOyELmxg5OSKKogjEF1NrHWgaeQpQVU7pBrNxhmJ2hfU9TauPoO5nQPv1RHDXqEK21myUd4eoZOBEnax+qEaSPEdVaIgwomriGyhLDbRxUeUueEwyl68T2OpheMc8lSK0Bah7IZ5Blnd3O2rhbc/Ab87P6IvYNDPvhzw+aaZZrDtW+GzGJH2PD4+X2f6ZnkRttwec0Sa8FWq0LVH/Px3jmw9fQav8zCVx7USYZDluoevvQonH66yfosmTWdIxz2QUiMCpAmJxz2aTr3NDem+kz1HY9OYTAkD73nNjeBL254msfk/Mz75TYlDz1K0qeWPH7dMyReKTxG4z46m9svn0h/pdy81cL/M+B3ntjh5auAF5G+1/SoDAuuf9unUhYcnxju3NacjKC5qFi/Ob+5908KhncM8cwwLSAZW8oNj/2BJT92aKC+8Wr9Ub2y4sc/ihETTeRZ/p//qGkEjmZHcHLu8dNdSXi9zlE34sJbhHoD4hHFtIfL530+y9OYolJGrb4DJ3s44ZjEu5RcQe7m0sCzpwerbpHewR6zWR8TDymERmBw1Ra5LNDNBn69jRYp43GPSnUDpUqY6SHB2t9BFQXm4CG5yag0tpicf0y3XqNYvETqJtiDA2gvI67/Hkk8xVXr2OkZZQTejT8h6+2SGkN0MU+RzPQMKRXF8IDETzCVmLhWQkU1orBKGg9xUiN9D5cMSXSIt7BMXLY0wmWkmXA6u4e4/C2C5WtoHTMqzij6RwTn96nPpkR+narsUKhzfL9EeUWSCgm24Dt/y+OnH02pejHnD3OOVYXAN7z/nTUK0cc6w9m9KUd9nzv3HV3XYPlyg9Ggy9ZCyO1zzdXthEpQwq8X3A56kH9G7C+z8OVx8jQ/X6kUY8LnNlmfICoaBL0haIHzFEIbGA2JisYLx9aVOmcqoVn9rAtRd7CPcJaw/eWdiV7FRx7IiMVBytnDn5K1VwnwKeUGOerPJ5C3FfavFG+J/SvwedJ/Vu8GWF/zaDTk0xz1z+Ajc8v7132KwnH8oEBqzdIlnzh23Lqt8WqOR7cyvLJ6qWMGwA4Lrr3jcetDTe/QMo4dUSQZxzC4sLiSohoV/PSwzsJ3Vwg6O8hsQja4S2AUYV4QaZ+S1yHpnzJNT6lUVvEXduiFPbLhdO5WsNFT2QLnkMYQDIegNV6jRu5yTFCBzW/i8gl5dxdXa+NMTlwKEfkEa3N07wDlPMS4R6m2ia4lqEcTkt4uamkVqRy6UoFKBS+qoUdn4DVxi6uY00NM9wBbxGTDY4xXhuEu+vwBYWkBU2mTry5TbGzjlKSYjXDVCu68i7AGK6BkPWS5gWksUuw+ROuEkZoyrfgIlRL075JVy7B+Dbm4jju6T+G1iCY5eTnAPzsilGMefdDEL7WomJDj1NCr/Ji//7dzChHQHyp2GjHloxL3T6/yiXHsn1wwLTpU2huE6zsM9iZMHv2E+ukK5SDi9p+dUwGsY35W4Rm8yMJnrcF5F/N8HhNSZMvztENStDxFqewx0TeRLJGe71Mv+ojAw+Wa8cAi7To6NF8YO1MO1159HAEwJ/tiYXEeffwV/vBX9ZFXvCYb/ZTZ5OTtCdH/zHgjxC6E+EfAv2Z+WO5/d879qzcx7m8iXtVL/3lHjbgiONgr+Pffz2lUBNff9VhbVY8tlDHfuOm9sD8q8HgcRf/Mp47l/e8prBI02orjM8eJ9rjVKwjFmGKWAqCkR5QWeCKiqh06EHhBHTEZUamsIsoNZHsVEY9gmnH28Kcsd1OYxvTzcyYqRS1fpk6NItBQXWYUzqNfy8pDqgCnJN61P8Dc/TFWClyzjSxyKBI0PsoYTDZjMtvHrzYoV1bB+igpyNMuVnmY4TnOWOh3EX4Zs3YZV6mDX8Upi42zefu1RGMW68h3voNXJBR5igkDqDTQpQquSPDLdaLMUvOamHId60fkesK03iBrLmNlFa7+HoktELU2cjrCZDHMxpidd+gmd6kkM5zfQC3cRIUZflGQFT2Sbo/lq5IMwUlXcnaUEoQxg0mK77UYiwi/EdDMfIxMIDlDCA8R1Tjt91lfWkVJyDLNwSBD50s495mmntgYayYoFZJ6hswmLASP2GynLIo2hdWcRkyXZAAAIABJREFUj0/pjZt06kOW6j6+jJ5+fzxdIZltkWXDx4RfxeomgYzmTag/t4FckBNQf+6etUGIsHNmfuKO0sKCnz5HyK/jI3+rhf968LWJXQihgP8N+IfAIfAjIcT/7Zz79OuO/ZuIV/XSf34CaDYljUbA0UXOH37Pf6mF8gmenSyejONJKNcl0rccnjqKENrrHrMumHOP9y71+OA//idGd8YEIqRUCLJkD1+u4QKFzsZko2NcrYFrbiGFJtQFXlgnaS5wYc4pNbZR9TK+iJHNNfRsxsgNYbFNUNsmPb1DZmPM9AwZtZCjPnpwhLSglrYwQiELg0hjCg/GyTEyTYmWryOWLxFPjpHtVYLKImmWYY5uQzLDKYm4/kfY9gpFMcWGNYJSE//0LrXKJtPFTXQeY5VAqCpMjnEXe2ByZHsLmqu4ZEa+/xEzWSUd93GFJiomVFurOHOBv7iJzZJ516AghMYC8sHPKMeG4uAW7ugWnm0gO9c5HH+KKw5ZKhX4xmc4jilVyzzY7dOMMhrVgH5vzOFxwYQ1skoLofeohIalBQ9/QVFY2Jspdk8UsyLHn2b4hWIwqWNNnWnrMznDZQP66SmquUTY3iacPaDj+8hJGR3nBCpkqQ6j7IilepNAzfdmAuWzVIdpOsSzKy+0T77I4SLHfYJG5TkGkHkGhaawMdOSQ7Z2kELgpGLUHz2VWt76yH/z8SYq9j8E7jvnHgIIIf4v4J8Af2OI/Vn9O9OOOwPH9St8qZf+ZRMAfLmF8tnXPpksnowTlAQ6lbhAsLgpWFrziRNHYR1KaQ4nC3RuriE+WSTVMWn3iMbBEdLL8DxBdnYXUaug6028xS1sOkKnMUUcY5RC1dsUoYdXWyDMh+hyjSQdIdrb6DzFS31Kqood9NEnu8jlS8jBOX5rk6i1TXp+Dzc+QQ0G+DIgm5zgBXXKscGvhIiwgjJVsv4eSIfKxviNVcSV94gPPsScP8BGNRwaORsgZwkuLGFKIUVpBX16F33vPyGFRNsY8f7fQxQZjIfQPUCcHaHjKfbSVUIZURRDxpMz1OQRBTkyqeE5iS5itD1AyQDZOyUorWPznJquEgRVZuWQcnsFW28xSw9gMuEk9aiOBX+0LuiULIORYzYLKJdDeiOBHQ8Yj1J2rixS9UukyQivVGW94bO/77N/EtBM2mgdIgTYyimqHGGdRQlBGLUJ8pRsfIGfGUp6l8ZyA1WvkeRH+BZ86REEMVBjLAuMJ1DaERmJUvo5++Nz9+ILHC6LmSWmj2kET8neH1wgnGVWB9G8Nm9vN+1RpYxslJ5KLW995L/5eBPEvg4cPPP1IfC9z79ICPHPgX8OsLquPv/j31h8MXIAbt2zfLoPgXq5l/6lNsr14EstlC+aLJ6M015S3DkxdD81vPe+zyy27B05xsKDUHEat4kWl1CL26hyjax0myyxjApJZTBDFCnUy+Qnd7ClMn65RR4oiu4epSLBJ0IrgScDAlWhGHXJXIqqtPDG53DvIyQGWWrB8TF6Osatv0NUaoPn46TEK7cxgx5yfRvKIbKxyvT+h+T9+5jigry9gGwuUw6bTB/+JcamEM9PqbpKC5HGuIO72MYCYut9VGnAVBiKwRQTRPO9A88Dm8P4gidM4jmBM5pg85vU6jvodIQpJvhbNxiO+8g0Rffuoxw4pbB5jL+wQ6lzDdXaxJ5+hAzL5MUEX4WsXLmEF5ZJ46vIJKU2+oCzWx9S27F4nqBZzxjmZUKT0zu+D/Fl4kqdNIdKSRAkBdPeHUajnCKr4Cdtcl15KqNMowgakovxPoN8C98vIypNSmlAS3VwdgoYhHpsD8yhsJok8xmWIGqu4ykfZwqGwxOyQvBlyvUXJBEP/M+R/ULhAYojdwK1OspCVSt8EeLUZ6dO3/rIf/PxJoj9Ref5v7Amc879KfCnAN94P/itWbO96PTpjWu8YLP0ebzMRtmEF1oo194rs983z7lvnqwSciP4ZM8RegKxGJCVfH5wzwDziWLrWsCHf9Hi6s2QB7vnYK4hB+d4fhm98w7K1LgYPyJJ+njlCiKdkNz7AW71BmFzC/wyOj1EygWEcTib4wVVSrMu+mSXLJvhnKMSLqCkNz+Gngny01PC6iWy6TFxf3d++MmCXlzG5hOscuSBwW1v4WYG6YdYncLhJ0S0sKpKvvk+mZmh1t5BlduwcAlzcYqtL5B2H6FliNh4B9NuYs8ewfkB9I5hdRvSKa6+hFIKz0/IJ32iUoopdtF6RtRZxSlHNj7F27yOa3fQXkA4HuHf/wXu5BHSlaB7TtM40nqN/OyM2nCGZBmbT/HyHDcd4qkSCqhFUC3DLAFfWKSDwJWATbzknMHxjOngHM8m5F4FHb5DqdWYWyyHP+Nq2RIoH88UIAVLjYDJxQWw/VQKQYFmkfPRPgvVHK+w5KbgfFww0kv4psSKmz+8xkHP1Jhgv5TYX4SX6d/NXOMSOZdaHj/dn5daXkU7fxut++vDmyD2Q2Dzma83gOM3MO5vBL5O8NjnHTVPJJ3+0HF4rClXFM1F9UzF7z193ReCyU6h+WWnbN28CUejFVAJWqTpMWphA4qcdBaT1qq49Q1MexUVVPCGh7i928hJQhinhLbCMD8lCAXpZA+iKmRDlAU9PEWtXKFodnDGYQ/v0hobvNQjrpxTBDHewiKytcpseoxZWMZFNZzJkdYiG++Qn+6iKk2802OC6goiNvhRBZVY0ot7qNVr2CLFHcy1cxWV0LMRducmNu5jkiEUCbazAqMT2LiOt3EdJiPULMb4Pkz6qCWBArT0cX6A8zSeDDDNNiKqwMkDhFGosEKVBuXUQaWGqnaQriCOz5lNjxj/9N9R8xVSKSAijfssfqOC9hOCCnjCsLOkeHA/ZqHcJlfzjc18bGlSJ/FyqC8xnIIRS/hehFeroFUODkpaMZ12kZUOHgm5Tp9KIcZr4nkleskS/Yu7NBONcCWs7uCVDCO9yeyiiyditIvQ7gqEB5+1ifuaeBNSy9to3V8v3gSx/wi4JoS4BBwB/wz4797AuL8ReFPBY8+S9Y0NxSyWHJ46mi+ICP6qYLIX+d0vr0658+gE5S9jdIYpZrjZiJLxSEwP0WgTrrxLXowQvo+/9XvYyRh1MaTuaiRLJYKew08LZnqIGZ9RyixJoIg6m/i5pLjYJ5v2qU8tUQ5+IbjQPeJSCbm0hRUOPTxB7NyAzjJieIGQCm0K9MUDPLOJjyasLDM6/xFeX1OkXVSlBO1lVHUBzvco/J8wX4/k6KiEK5WhXIaoAp0NGJ1C9xDjhTinYTZFmoJAlsnjHkXoo7MJbpDNNwpLTWit41WaYBRCa+RoijWWqT/Dq1cxqiBTmkptg0Ku4+nvs7PeoOZFpMMeD5MjOjdb9MyAwW7OYsVxMfU4GfjUg0VkKJmmKePpCsP4nLR0jiogY/npU2ZEjUz0wIEv500sxrN9kp56TgqZZXOJw9eOStHBl+vzASR4eoqTCuFtY5gX1FKniJdsXOY2RXrD56yRX0Wsb0JqeRut++vF1yZ255wWQvwL4N8ytzv+H865T772J/sNwZsKHnudLPmXrRKGdwwyt89V8rc+TtgPFaXEEp19Qh520Z+W0eS4fIYWIVk6QDWaSC8kmjoKN0E7i8sS7GzIICjPT7KKAM8r0V69gdEJk7NPoNVBNpfxkoKW38GECSJ7hFYTZp0SUW2DsTvBVOs4T6EWtzB5gtAa5/k4L4BUw8pl7NpVijsfknoGtXmTaJTA6ACtgN1biHIDNziHoDRvf9deBeHmWnpzARZWwfeh1oJgnkXDwmXM6SPkxT3orFArr5EJD+Mpskc/Iyx3cJe+QTE5x4zP8PwywhmkNtj+MVmrTq21ii7GUMTI5gLt4T6RqHF+XjAY3yLKytTNAtWooLni8bO7OeOqYK/nSNIW9XKIcw6lUqyGZtlSanbwltaxCM5Hcx3d2jq9cU6zWuBLD+ckycijkazMSfNJ82YDeTGXMUYlg6enT2WM16mmc5tSr57Sqlp0IMjEjN5gwGy4+pUJi1/Xpvg2WvfXizfiY3fO/Rvg37yJsX7T8KaCx/Jk3vruwd1nctqX1BdCwODFq4TzM8P+vYxoR3Fm5rnvAGVjCKxl5apH1fb4xZ0+tV2FLrXBC/Halyj7LSbZBPp71GSToLBMTx/hjEO1NzH1JsJodJzNfd0mYRzkpNtbeO1tdKlGsfcxjMY4P8SaPmUb4+o7UK5Sid6h0IK82UF2NrFBiL33ISRTxNYNKGbQXERWOojOKmb3DgEV3GREM5bImkdxdoKvBhTxAL2yhaiUUUEdffpoTuR+GaQP934KjWWoNiCZIGdjsBajBG55i1kQ4TmPkrcEUZf05BbWxYjkEnL7PUxUguNHuOEpUa+L0hojPwFhKK9cR1ZLqNGntL0FyrKONgEtWyLxUh7e+oRr/ZTluqNVBaV8FmqOoshwbn6ISHrzzVHhFNNZD1VdYLHuMzo9wsU++XCVh3H6padIv0rGeNVqWnpDWlVL3iihqguUlM9Sc8bdR0P88a+2F+lbS+SvF29Pnr4CXhQ58Lq9VzM9P336zpaksj5319x9UJCVvpgV8/lVwvmZ4fbHBZfXJN/7hiBO4OAoZ5IKbmwKHhw4pqeab1wSvLvl+PjPNOOoTm8SotNTMhPjBmOKfg+zdB3pBH5/D5llKELyfIhsrWGW1yh2f04hxrD5Hv7wDFWuM8t6uGYdXTaE5QXUrEeeZgTakOUTXHudrPcQbUeYZIK8mIKe4vwSLptB7wghArzxFNKUsLlF6AKCFMqhxfptdCkglCX66QR/YQeXjRAbV6Beg94hfPIB1BZgNgSjwWpEmuI1N7HaYCTYSpu8toTzy8R2hhfeAD0haKxjLk5xx49QQuE5j+jomJpo4XtbTBNLVq/ivACnc5LpDFlVODFvWQdQWEORGMplgdOK06FBW8dCyeNcD+mNaljdwQ/P8GU0T3qcZiTpESjwhynVZIfAa85tiS+I6n2Cr5IxXrWaVipDBwJVXUB68xVmEFYIawWzRP9KJZG3lshfL36niP1NNcL+ZXqvCiGIPJCPfywlRB7MxBe1+s+vErpnhhs3fcgsaTaXcTaXJH/xowK57ZGnlqUdj3JJ4Ny8+9Jyq8KsO0N420Sqgiskg5PbpOeHhFpQKhz1xZtk7QZBVGEqLNPAMfWnuP49wlqNqqiRDk8o7AgaK4jTffx+RkWEqNoSejYgTVLMwnuEpSuIwQH25CHMpoQqwjZ9iu4xUgaE9RWiziWK03uY4QWz0QH+TOMVZVTvFF0JCWs7eLnBTMYom5A9/ClYC2cP5o1B1t+F1UtwfA+mE4TV8+hgI0Bb8myA6myQywzhFKq+iKu2Kcolqlf+IXI8QuQJxek9PBReYZFSUU0sTI+ZDo6QpQZB2qRrBnTUCc1CklPQmw355uWI73x7Hs87mTg+PK7wsNujO67hsrmcok1IYfXTA0QVErSOCfSrV8faEwhrkMUenkjRLsK6BdxryhjGhGRiRkl9VjxoXWBEDe2lv1JJ5K0l8teL3xlif5ONsF+kl7cqmo/+asbCsv/CSSNQsHTJ57Rn0BePW99d8pmcfvFzPjv5rFyeV1prq4LZVHJ+UrDUgXLJkaaOvSOHddA/15xlUDhHkToiAZ5ImZoJvYpmttQmbPwe9dIqdjbAHt5jqhJMtIQRKanNKPwGYusmngGEJZkeY1yB32zjrCQ0Hr7z0OUKmU3JpkM8fwd7cB/XXiE0hqC0jk728TOL6E/QUYDc+iYmnmCy27izfSjXkeU6Ogjpds+oHB9TLQRpeZfAjLFFgl7o4DoNxJVv4Zyda+2HtxFZhqu3oNHBzUYU/QPstA/dE1w6JS0KnOcjPYUdjfCMxSvVMcmY3IyoVFcI175BMo3pTzO8/qfU6js0w1XKyYC4u0eYGoaFxQAj32GMwokqQX3Cg3saxbxxhl9r4asUYVbxHxOW1U3Ox6e0qhnN6ohqJOhOFJutMuN4fvQf+PINzSyl4T1gpV3F88poXXDaf8Aws/BcO+svh9VNeoMBjXIfz8txekZ3JknyK5T0CzTAN4y3cQK/PvzOEPubbIT9+c3N6cRiRpp2AN+69uJJIygJhIL1S59tuk5n9jl3zbOTjzOOh3dy/uL7U0YJyHHA5es+subx8e2MYd9yOgavCy1raYYCvwp3Dxw1ZRh394mLZXqLkqTexEmHjmqMdE7VVnC1BiPTpdL6DkYaTAAinVILl7BBiMwTisgiS4soP4JBl3J1nUzmpOMLJCUYKgphKM00zPYQhSYxM3wLFRfRnkTMpimD5EOYdvGth1jaRMcpoSzjVVs4GaB7PTp5mSCJyG2V+xcDpnaCt/YnuO4Zrshg9SqibVFHD4lMmSTT2PEAW23iyk3Y6SDyFBwIz8NW6zgZIRsKXSToLKUUtHHDM2Z2Rliu4Levw/ke0/SMUveAyAWsFcFTkv1XP/jzp9fmox+llEcZEY7VJYG18F9d+jPu/DPFH/yj3ecm8dHQ8vFfzWgHjkZrvh/SbEqmM8v/+E//Nq2KfWHWy5P3rTGjo0CJKgBKQEdNHvNj55Xv00BGDPttTPiQjZUaIqqxoCJceh+TtV/56X/rR//tw+8Msb/JRtif39wcdTW1sqAhxHNddJ6dNF7FXfNk8sHC+cOcBWm59oeS20eOyUnOnamm0RBc2lJcNCRXv+Px4U8Ksorih7cNS4uSjR3FTrvEDx/2meURhX9EkYeEV76D833SZEKeHhIFEBYR6nyfVI9w5RKisUiWDWAc41tFOtwHKSmpGmHUpGj55I0GRKv4owneomEqYvJsRMVvYMKAoL2FcxYVF6S9Po0kpBprsotT8tCiKwVRcw0/aIAG54ck1Tqn+YCSnGd1B5MZ3kIHv7mNJyU6MxRhDV0k+M6nrKqYSoQG1NZNdO8Q12ijphPMtIdY3ILOKjz6FNvrEZYXyG7/JXr5HVxnlah6BS86Jp0mKKGJGitk6S5R8fJr7pxD+IKw7dGdabpnjnt7hrNC8PFfzT47k/B4pbaw7POta+K5nqGVssALeizVl16Y9YKdV/Oh72gmglQfoR/HBjQLych3T/uJvqqFsRo5NlUbM5YYr6Ckcy5JOHjcPeqr8NaP/tuJ3xlif5ONsD9P0uOhI/UdnQ2f6cQy6mqK1LF/5J4+6K/irnky+RzvFgQ4tlYEpQiOh4LtHckHP8g5H0hExaOz4dNsSs4ONEuLguZiyKiruRjDxThAFxWqfotcVHD1BQolkMs7+EGJLPAZDj+gmYJJxvhWU7TLiI3r2NEpajom0TNQy/iFxUs0ZeMzOHmAC67BrI/MBEW1gmpuUMQjUq+GcZpgeIEtUnR5Ab3YJtm/Q2OQs5LVGBUzzloTEjOjSFICVcEWKUUpQm5epm4aWJORT1JkHGOHx9DexK8sYrunmGKGV1isSFH9EUiBP8shzbHtMugBLk9hfIFyCjns4Q0HqPGEMCmo1rbIPIUZnmOFZBY5rJqx1LqGsAbnqvT6u7TifUJ/Hqn85PqFnqCxpPj0QcGoaykSS6MGs4ucTQ+UMKg84PYHGV7NI40N53XF8spnj9gsdggxz3x5Fr70UOozojUmBAx1G0H++N6gmDe8fmxh/LKK/1kolVH2Kggrno7lPPfc+30Zfhk/+i/jnX+LN4vfGWJ/042wx7ngg7/KAUGmLX/wvo+nYHJSsNIRmApMcsHwGUnmq9r65Qbuf5ozONaE1rDRUswSQRAJVpckK4uS2pLHlXc++8xPAsQ2Lkuqtfn3rW4g3PzQi7QGawqMcBgbo4dnWD1FbVzDm0oiVWNw/nNI69jeISKdYlcu4SUTvMGQsLqGDWPyg32cX+B0Rr22g5ED9OIiWieI/VsY6SNba8izI8LqAi5w83yRbEKM5jwwJKGPDX3U8jaFzpmc3cV29yktXUWNc4QQWCWwaztU0hHx0S7aL+GsJTg7w7v914jCkDUayOVLBLUlvNEY3/hMkjHSjwiDJkJWIZ0RjVMqkxyXDejGFyRnP0Y6QbB0CbVwBZsPEeMNdH6fWnaMFQs0GhNWmzltanR8w63HRD3oGlTd8N33PA4fWewIdo8c2wsBJSR79zJyU3D5qsdUwqUrHj//cc7ysqZRFRQWxkbxP/wvt7m5dfupJAhzSe7TfahW/+pp0JynHdevyOfu1eZ2OF/Vtd0Xfv9lERePbmVstR3fN7/Hw385l3EKqzEmfKWH/3X96PlrTjxv8avB7wyxvyk/+hMd/OaWoPLuvA3anQeW43NHPJj3v7QWDi8cm9sBns8r6fijoUVkhtw4NpZBzBy7DzWZJ9m+GpCk4JTAfM5FE9UUdx9pvE8yfAmFhaPRDKu3qACj8QRVjxDWoQdn2N4+QX0NLxXo/By/ukBY36BkAuyD+0zlDOFF+FaCcQhtsM6hR0eUs4y4tUza9EnNAL/1TWQ2JaiuUE5zAl0mVh6uvQxBiB6dkdeqiMtXmA6OqdU2CIcnZPd/SL68hlraQmRTXHMFXZxTxBmpZyjXNoh1wVJSIv74I3Izg+NdOnmJsLHGMJswPnlI3D/Eay5DvYO79wCtJDJJCLwaXrWNNx5ToJm0IrylbyPXr5OPDkjsFHd2B1PM2LSP+Af/dMyV5ikq+ZSkGyNNyrvXNNNTw7evSC5iQ1lbeqeG8Yri/NiwUAvpjS21umIyVtR9Q6Oec3Xd4/s/0yyt+Cy1BGdnBt9XGCGwztFc8jg8LZ4rMO48sAjr2NpSXxk0d/rw9STFJwVNWtY45x4T7Rdb670Mr+tHf+Lj/zKp6S1+9fidIXZ4M42wX7QJe/0KfLoPD44sReEIy4LOekCzKXHOvZKO3z8puHFNoQvFwaOCi1ODLByVtsD3YffQUlR8Uiee66d62oWoKkj13BFjhMA9XmI/aU/WdXcoNzxqvsdsOiIvreGHdfLkHj1zh0TP8BPFRt7GK1ewrkrmG2R7nbC5jYyHFMpHliJCp4htjK7WMaNDypOEMKoTAcPhQ+IwJ1xcQBQZyWCAvPQuMmyQmyGiGiJlh7h3D6FA6BRmY8pxgV9fYZrukXoOq6fIyRjhWfxKhC9qGCsJOlvEkQeNBVQoCTxHcXgLe3oPv7pIJCIslmL0CUI7smSKXl6ndOm/wCs1yNI+LigjogrGWir9uywuL1CqJ0xGhnYac6nj2NtNOL9vkAJqZZ88lXQais0OfPTA8PNPBe9fEuzsBIRGc21dcu+eoNASYwVLi4LThxnfvK64dyS58a35PTevrA3t7ecLDO0JvrEtXylo7nUlxScFze5dyd7Fyw9FvQyv60dXKnvqEHqCz0tNb/Grx+8Usb8JvGwTNlCOrevBF5bJr6rjPxl3NnW0m4JgO2DQ1/zsvqX3OMXx2jfmUsvnSeG7v+8/954brQoPi3mF5MuI665PJX2AKq+Ql0Z0Rz/lwC0hltaotN/Bm/ZIjj9mHFm8JGfYvY+o1ilFi7gigeEpqtyAqIoMysh4RiAUxelDkrCMj0/hIB8cEJZbyN4RhXLoWoPw0nvYcQ8RN5g1S4iSB2qL0ta30eNTPK+EHZyQN1eIKwoV1XBYVHOFoR0Qqggly9hKg36U45ZXcdUG4fIWTkgcgmg8JVh7F31yHxOGeOvXMeeHFPEJ+c5lPF+i/JCQDunRJ5hSGTGNWZ2cUm6WmA41xcmMxSVB0h1zfVmzuSTwFfzodk60HlKvC1o1yeIilNo+jY5Hp6746OOCy9sWC/Smgv1zx/q64uNPDNby3LUvCsf+neetrI2m5M6H6StX4b+MpNhoSmrXFhDF8ksPRb0Mr+tHN5/z8cPrST9v8Wbw9m/9mviyiunr6PhBaX7C1I4NKx1BaUnS7fvE0nHz71afk4yeXXU8IYUnm7Y6A+mNcMIHVpDekK1GHWEr6MGE3OZYdUjXGOzKHyKdRaUJrXCFYniMuzjG9QtY3CKNjgkICI3ABQ2SwENWWoSZJO+socoN8qNb6EmX8WxIoAXNhfdIioKiXkGFSxTZkGJ4SOiFFEWKNSmBM2SDPdR0jLe4jXfRJzm9jTAFZTUjDwTTxRas/jHJ+Bw36mMDizY9wtoNPKfx/QhnDaLaxMxiUqEpyj7h5nukniY3ffzKNnLtOgkWRE7kB/i1FWzaZ1v1ubRWZ7NVsOWdc9Lrkvia7U5OqSaRvsMToKxDIGgseOw9zNEIFhYc3dRjmhmmKuAv70B/EjKbGK5+VxEEAivhw1uWUlVy6+cZg7Glu1/g4dCyQNZ9jgYGbkavVIU/e77hsxhnfmlJ8XXwOn70Jz7+pfq8Un9d6ect3gzeEvtr4gl5tyqaIjZMRnA2cqy9V/5aOr5XVnzw76d8a1MyETALPboTx/V357nsL5OQvjAhRNC4XkL6jrHfInBTwk6dOBBEE4+SX8OYLuH5fXK7jPBKlFUFVW9h4hF5tUTY2MasbKGcgP4Zlakks4I8sJQzwXA6wEwilB9RK68Q5CFFkiFlQObNG0rnJ3cxnWXo7lKqrmJqFfLhI8TFEULVMd0DlCphlY/xPPxpymK0ie9XGORnaAE5Mc5M8JfWkeuXKe7/ANlo4CZjmHaRyiMoHLm01ESITWO0TTCBIli/ihz38dIJudDka8swGmDMmProIeurFfKgyjA95b9cGbPxnuHoKEdVFZkSHA0hHhlqSwqrHEgYCm/e9MLPGRnI2m1KZcN0nLK9VBCWCk6mgg/vWvLIxxsX3LwsKYeO73+SUS0M3/r9kOVFycm55iy27N+TbF0LvrQg+KVinD+H/771A/7lN//FK9/nXwfn+So926W8d/ja0s9bvBm8JfbXRKMpGY98Pvl5TLMyd6VcW/aYDAtGja92vnweo6Fl/17OcDfDaUFiHY/2HBe9jOaKz1rJMBwCN178++1Vn1sfZHz7ypzUZzH8/X/85/zXLY+R+SEAW20HFv7n//O/IfjRLkV+TDucOUK2AAAgAElEQVR32PhjsmCHIvSYuRmjKCVSSzQqW6QywHkBYW2dbLxLMB5SzHJobBN6dXxbRT/4FJVliF4X6QyzskDPTua5M9EC+eIS3sNbcHZAZifItW3CtRvUFt6l6B3CpE+++xGNbkqpkMiNeWctLR1UqqjmCibP0MtrOJ2BlBR7v8Crr5Of3KZSXkP2e+hxD4ILKqZCmsTcuLHP8o1l8tM+xWSf8f450/5P4PyAnegOy9sj/t4/WKC5ViFLHae7Mxq+4bAL128IGmXBdOKIhcQUkmFXQEewfjOi0ZRsvxNy9GmK541wImBWzul3Y1oNn6it2NlQ3P5xTDo1/Lv/z2AKh0st/+RveyRAKRKsLYPpWn52lPPedyO+rCB4U4fr/vWf/q+v/No3gf/pj//b15Z+3uLN4C2x/xLQseEPvxd80XL2+EF71UyaJ5VYy2q+/V3J0YFlMrQsNiTvXREMUkfoQzrUjIb2hWM0mhKv5nERG4768/frrAc4HB/9OKfaUpw/0Nx410PIgIo5Y6Xe52pUQlf3OU7HPDLndP3LeFGDcGWHbDYhmhXkqiCbXCBHJ3RmVepWcHHvJ9hKgBKKimxg8gtcuY1uVAk8EGGVYXKMK1Lk8BSiCjMmSM8nCOp4hcEikI0VzLhHZaZZyWrzv8fjTTojDM5o9OAE/ACqDZwUuPVrBNMZ3qCLPNpFsYuMp5SnE+TMwyqPLDmj8d0Aq5eIAksz6rO6k5Kc7HOtfJt//Ccp5ycaLzuj/wuP6rLkD76lmc1Con3BX/wg48aWZGNLsr3tcesALv9+ic1t77m/OTejx9e4oLUmuPKdGo2mZDS0HH2asmg0f/wnCgf88EPN3qFDu3nCJ0AYzONvnrQo+rKC4E0ernuL3w28JfZfAl/2oL1OJs2TSqx3ICiXYHXNZ3SWMHWOxiXF7ilI+9VyTHtJsdz+zFUxHFqOHxRcWRUsrAvufOL4D/824fBnP6bl9bmy2KQWBkzcFD+/YDgaM+vOMMvfQZabiKiGOd2jGiyR6S7N/LOI18o0RmcT0iLGlFZQ1sHKDsIMaNKk74aECzuYR78gWL0CtQZm3MWZgjAt8CcTmN0BHP7pIZ2Jezr2k006gjEwJPzm3yEzM0z/ENc7QRUFKknxTYCaTFjJFZWiSmE9LpIZot6mPikIDn9B/+4D1rckzVKBHQxpTB7xd/8oZnklIIwk/aOc91YM4wJmM8XtjwveuyLY+lsRvQvHvQNDe11y9aZiFBs+/6i8jIj7JwV1ZahvSTwPolDwzrYgnkl++PH/396ZxkaWXff9d9579WphkSzue7PZ09t0z6bWaDKjESzFkm05UmQg8AcHSGDYHwwDWZwghh1bQD4ncBAngIMEgp18sbJBsWHFSbQ6iSIpM55Ra3qm1cuwu9nc92IVWWRVvXrvnXwoks3u4VIki1vV/QGDGXIeX537Xt3/Pffcc89VLl8q72JdzChjcyEt5/fugtXcXGeoD4ywH4DdOtpBDtTIRiFfgMZGIdVqMzIZ8tYdWPKEl553aW4W5od39s6eXbQdHy2RcCDWbLM0WeLjl21evWLx3v0iQyEIFmulAmHo0e4WSRTStNDEcgCl5QW0sQ3VAL+4jKSnkfwqj+NZsu0x3GiKVDhAopRnYekxecfDzUGk6GO1t2C5CRIdV8jPjkGqAzvWDOpSLKaxVrJEfYcmTeIXlwnTyzQHiScHTFgxKBWIWxFW14qUHt5CwjyyOoB98RUCy6Y0M4Y1MkzbWkiLJPEosNbSSLy5Fc+18aJxhlqXeLHhNoU5l+52m+fO5wlbVrE8IZMJSaUswGV+tsTdh0qssVw9018O6e2Cvm7hwgWHsSXo7bF3ffbP4uWVhAXt7TbpxYDWZqW93UYkYDwNzWtC5k5IOgvaGuXi5b1DKdXeXGeofYywH4DdOtrMI6/iafPGANHc7mxWbXRiQmu7TUOrzcB6LvyzxcKe5dlF25l55c3XIszNBJzrtEg2lMv5ug7EsSmEaQZTCeIxj3wQ8HBxjZgos/49FjJXKeWWCWceESyv0JydZLWvkVLLIHbfJ5BIlPnHN3GKIJd/imhmFrf3KkF+keXcIlKw8XOLYNlEPLByc/iFDM7COE2RHvyVcbzSBNZymq6lENdJbrZjoy5JtPki8SYh0t7N8vhNrHgSf2EUGwfb84i0nyffNImXLWxueXedGLH1POkbn24l/c40P/3Ta5sD7OSITaOjzM/5pFLl5+pEIhQTgpdXenuEqWJIvgCJODQkwJtSpqYDFmYDuElFpZ7duFBaBiwh0e6wkPFZzkIh4RIbsJgPLSgqrc+VDyGvZPGzWpvrDPWDEfYDsFtHS+9j2vxkgBCS3Q6Pxn0+HBFCS7jxnENzc3kzUiXe2dbQQLmSpJZnBH3lz80X4POfegTLHglRrl2wiNvwja+30Ri1yHkRBlyblfm7aMGheSFLf0OOcADscylKOkV69fvMJl5H2/vIecs0t/Tj59eQ5UWc5nbCvIfMjrK28AjHThJrActJ4q/Nk8q6BDpPJDtLyovRUHJxnaczJbaKdMvKCml7HjuawCsViPVdxfaFSLGAPzdONNbE6pr/kS3vv/L73yQ7nmPirsdsR4lsgw2lkNxSyMKyz3JoceFS5KnBOD1demqAbYqHZJcChu8r4R2Pl1+Lc/5CZaWeW3vKaYyPJ3wG+4R4k81EVmkdtHn5hfiBxbgam+u2Uq2zCQynEyPsB2SnjrbVmy+VlIlRn+mpkNT56EcWQJ8aIPLgNrl8/AvljR3p6RLzwwfzzjZsyK2FPH4YQiCkc0rPBZcHPwpYRfnB7ZDWJpgMW2lo78ZaLKBxjwa3QFPyGnZrjMbmBorhA871RBAnSd6C98ff5qFeIojHUA1x3QbcwKY4P0WwMELjQpaB5YD5C8Ly6PeJtvTQGEthX7oA6WmS8X68iLCKEkGIEyPiJgBY9RaJ9Pfji2DRQcovUFjO4Xkr2EtTWBEXiTTgdHbgzcZZiUzTKItoYplCbBDP6aA4nqGnUWi7pjQSMnbHY+hShKErFhMTNvdvBvzgZkBrp73luT4ZYCVpc/uDAss5xY0KV85ZrE4VuZexIQK5VeXxSIlzV6I7iqHvCLceKG/f9kk02fQ85zJ4ef91/4+Kap5NYDidGGGvMhvpkN/9v6vkZ3zOD1i89HKUZDPbdp6dBoiDeGdbvbB0RlkYVzJ2yOUhi/4Bi8VswJrr0JESioslAgd++gujNLVOkC4JXX3O+jb2t7h/s0CjlliYiuIMufz4m0OEVkhXMmBi6hG2esSXR7GDZoLYALFIM1E/QVOpSMpN8m//y5+SzYSMzsZYWXNpTHi0xNYYzXUT7+4g1mCzMFVg6d4kg8lF7JjweDyC1dpDojVKsruBZMrle98LGZmO0/XJGImWOKW1Igs/vkd89Ye83LbAx64qyzSxFLzH6DzENIlVWGPoAsw9CLnUZ5FdDllNWuR84c1Px8gG9lNb9bcOsGP3ffq6I3S32Nx5t0Bh3qe5QcishMRjQn8UGl2b/taPiuGGYF4fFF57PvZU8a7TJJjVPJvAcDqpC2E/zmlnNhMSZkpc6LG4csPFtoW5xQAaLfq75cg6z7Ne2IM7AV3PWSQ7XPxCyHRW8QGrycYPQl54MUI0CECV23c9Wi9Enwr5uHEhO6Vcv1Dg1uQ0H/s58H0f67ZHaXWGa9cjNF/sJ9GRYnr2PZY95ULTJK9fTT/1bBvDFaKquKEwPpcgfqGDeNIhl/Gw0itcea6ZldEshckVujylIBbJ5k5Wx0rkVxtpCHK8djHCyPAtsrFmXCmSmrrPhdYcX3hDSSaF6dll4n6BuaWQYDbDxY9DstEmPWUzn/N5+5ZPT7/S1uXQkhDm5z663rExwKbnAgLf59F7eUpZn65+oadD+G/f8/nUGy5uRJibKpeNeFYMz4pgHlf65D/94Z9W9X4G+MZgZdfVvLAf97Rzo3OPPyh3bBGhsw1mFnx6z0eOLPf4WVFxbWFwAMYz4WaZX1Vl8rseF69FWMmFTGQFrxgSaXSYnFdeeOPJM2ntiXBnuEhoCS/3TXNvdImJWYdmr8Df+HSJVz4R5dHYGhMjCVrzAY0UeP016yPe69bnfvduQNtAQC4TMvr2DOeSJbI5i4mfFPnFz1g0NgiPppaZmytQkjgri9N85vmQ0Vw3HX3LpPM+E+8vkQpmudy7SlurjYjQ0wWRXIkLAyFWXEk2rsfuI1BYUT71CYdLlyO7HiC+YbO/4hOPBty4YfH4ocXD8QBVoTmp5HM+qxEHN1beSPWsGJ6VfHOTPln71LywH7cXtdG5y50Hkg0Qj4E/f7Sd51lRcaLlA7O9/BNRWV1TQOntsRF58upVlVvD+pEQUf/LCW5+sEZXs9DdX2Tgss/77/tcv+GSbLR46XrAS6xs+fsni6HbPfeL/QEf3F6iM2XR4fpcu+Ty4fsrtLtFGhM2sSgkE9A3FDKdzbHgR2hqdmmem2DywQyCS3+Q54WXiriezWq+fH3UhdUcuE0RxmdDhtdLGI8+8mkSZWCoLMS7HSC+YfPzVx2mPvCxLIueLotEFN6+G2K7NsPj8PwrNk2htfk8t77P/QjmSS5emvTJ2qfmhf24vaiNzt3W6TA+6THQaSGieAFV6zzbicKzorK1aJWqPum8fW7F4jMw6NDUnCQ9XWIhr7gloalfiESeXDs54TN8u8j4tDI+UiKRsmhrsXl4t0hwTnCs8iDX1ulwoT/gB1+f5dpf7SXnR1jOBPira1w8pyzMB3R0OdhueSBcGQMvxmbt+09cDVhdW+Mv3/aINVisecr9sYDLA0KpBJMLypJlkcspw/dLxKKQz4f0nrOZz1lk8lAKILRgbsRjJPlRMfXySme/zcqiy2TaRz2LohfS2ecwOOTwwV2fhQx0DtnbZis9K5hzswF37/k4jQ7w5DSmk168NOmTtc+hhF1Efg/465QP3XoI/IqqZqphWLU47mlna0+E+3cKNNkB+VXlBz8qsZwXuq/GOFeFzrOTKDipyFMHOGwtWnVrS3ZNCvblrT27uJvNhJt/n0kHjL5XoK9FeOXTFtnZEiMzipV0abF8mgpC38UICoxPekRbHFKRFbLDj1mch4WSR3erT3unzfDDkIIq7f0OC2llNqvEo1pOBd1a+/6qw/CHPn29No8/DHjnA59cAVovxkgQ8vOftGlvdVhdg7d+5NHeaqGx8kC3Ml2iIS7YLnRts/i58V3pPuewMq109girOZuRuwHvPRKszhiLrs3KzPZVFbcKZuZ+QCHjc+WqQ2+P/ZR4PzubIVS8JZ/v/r88bd0RWnqdbbNoqunlVzt90nC6ENWDe64i8rPAX6iqLyL/DEBVf3uvv7v+kqv/4c+7Dvy5+2FDCPufqox3dJkK2UzI+O08MQmx1w++KKjFwCFymLeycdTZdkejtfZEKq5Rs9N1lYjHRuGyd7+9wo1BOHfewbaE/nZYzin//e2Qz77pspb2caLCwFBZrP/PeyFORHjzutDeKszOKX/5nsfSoqIoTS02lgVBxObyGw2sLfofORBaVfnm90q4QbhZhC3WaHP/nk9LVPkrr9ib109OB9x/UKK106WxGZoisLBcnrVsbPzaepjF1u+KBsrMuM/jSaWpP7LvdMXd3pOX18125VZC5h55JEOfuRxcvhJheFxZs+2nvjPH/T02nE5eGZz4kaq+utd1h/LYVfVbW358C/jFw9zvKDjuaefGSUjJhicLdFsLhB2W3UJLO3lh24n1dudjVhoiWM6GrM16RAKlu1Hx0j6LS0oy4tDZLuRXQro6hZWEw+07AQUHbLdczvuFSw6PHxVZnIZkozDYZ5NeCrj+UpSmBjbPBm1qtvDXtp9tOZby2qtPF2Ebve+RnSvx+MMIDY2QTDn0dlvceewwmYPCtPL8c09Ottr63LY+n6IPy2PlxWe3yeXFKwfzind7T1tnkdkFnwY7pDkpFGyLxqTF5XPKvamQ0Q+LNDZaeHllYbbE88/ZJBvK6wWnNePGcDqoZoz9V4H/XMX7VY3jnHYedUx/v6GlgxQl222hOZsJmbi1xqVuZblJaYsrLY1KKqJMP/bJFx2siDD8YYmwBI4rtPWtH6P2E4+o79N5wcYvhKzm4MF9j5akRXNScKLQ3u7QY5VPidppkS/RYKOBMjnikV4ISS+GzIx5JKMwtxCQyMKDuyVyocXIAlz+WBwIiDXam6K+8dyKvj7zfKjYE95tdlPpgSylghIUlNmi0tG7MeDA2krI8lqJ62+6NCSEe6tQSPtkEtZHBiaD4Vn2FHYR+Q6w3Sm0X1bVP1u/5suAD3x1l/v8GvBrAD199oGMPQscJqZfSRhkvxkNBylKtpVnxSM9XSLVAFpSPv5ShMdTHvGYkmyA+499vv3jgGSLw/17JQb7bJ477zD7yCMjDpYLyYTQ2mYBNmtrSvJeiaYm5dJAuezB3HSJZLeDl995trU87DE34mGJsjzt4RZCehNKtgSLc0qyT1BfGX3g0dgeJaE+HV0WD+6UAJ7EvGcUEaG/m31nTe01YO72np7aEDWpxHx48YpDqnkj26Z8/6EhZ9OuppTQ6LBZ66Z8nUlRNGzPnsKuqp/b7f+LyC8DXwQ+q7sE7FX1K8BXoBxj36edZ4aDppJV6lnvN7S0nxlEJYOSl1eaU0J2VnnjusVEIsrtkRL3H4UElkVrK3zqEw55TxmbU7LjEE8K2QKUCspPflJisNeis8dhbtoHV3Gi5bh4Ig6dbfBo3Mdtcjfb+6zAqirzGcVbKPHGVQjzkF2Bv3wA3f3C6JyFHfh85lWX85dsRuYDghL0nrO5+zBgPmdtPrfCPoq2bWWvAXOv97TRrtaeCJN3CmSWfZobQ8KQcoy9JHQPbKkB3+6wPOWRzejTWU4mRdGwDYfNivk88NvAp1V1rTomnW0OGtPfj2e9n9DSfmYQlQxKblyI2TZTIyXm05SzVhIuc6s+r7wSYXxKGbriICIMripjS9DZbTP9A4/L5y26GxwyS8rb75TwAjh3wWVmPiS3qjQkIAiUx5PKi1e230QEEHUEkoIsK2ueUChadPUIQysBtiOkMyGdCciXlGIJIiL0dlqMpZX2rghXbmzJtz/gDKuSAbOS97RxaMfYsMfwex4gtPRG6L0qyJaJbbLRYrXZIT0XPJXlZBZODdtx2Bj7HwBR4NvrmQhvqeqvH9qqU0ql6WYHiekfVWx+PzOISgal1p4ImdGQ9vMuNx8VSU0JvkKkycFHaOqwPlL6dmbcp6fXYmAwQnrS4/x5m6Eh5d1bPoXQov+qy9hSiDdVLnvQ1L/zgmU2E7IwWyI/VaInJVgxm/4uITvngyijjwMGWoRL3ZBsFibHA4K4TUMCso+UWO/Tz/igM6xqptE2p6zy8XifeDLgbE0r3bBraVV44Y0GI+aGPTlsVszFahly2jnqTSVHlW+/3xnEXoPSxv3S0yW03WJ6LSDRYBPYAXazTU+DtVlbPgjKQj0xqbz6WmTzgIuxOZ/imjK1ajHQZjPYZtGQeBL3Hhzc/vM33sGLl2xmAqEzCQ8e+QwMOCgWc6sWS8shbR02sVaLoBTiWspyAAtpJbMK13qenglstOfOsEd6skjZY3ZI7fFcj3r3ptlEZDgMNb/zdL/s5JUfdWmCSoTioBtUqp0VtHG/oS0HbGczIUujxXKq4Xpt+Y0c8KZ+NnerplIWqZRLbjWEtnIbthOv7dr65B3YoHHmHxRw4/DuvYCuvggLvnLj5xKIrwzP+rQ2ObiNIaMPlZmC0v9yYsfn1eQq195wKx60j0N4zSYiw0GpO2Hfa3POTl75UYRKnrXFSUUYSwfbCsVJb0Pfi+1qy2/kgG8XVtiaIfKseG1bQOx2nsnxgMRFIRsTmtsdGl6Jk5kvMVJQoueinGsJ6R0oD765lQjZBZ+ljGJ3wNVdQhgHHbSN8BpOK3Ul7HuJ424dvNqhkm1tmSnRukP+9FkoCbtzbfn9ebcbbSWEqccl0gshxfkS8dCit83BtstpkY09EVJdES5EyrtHnxpAkgKWw0qovPDi7oPfWanKaDBUSl0J+17iuFsH777gVjWmul+hPuvisx/v1ssrGii5GZ/uNiFYDrl02eKd2yHDY0pvG5RWfd77fgk/7tD7YmJz9pPOKBNTPokGm1SHXVF45CyVsTVH2hkqoa6EfS9x3K2D7+V17rfD7Veoz5L4HBY3LsyMl7jQLSTigleERBucP28zvabcvu+TioNXglSrMvz9XPmc2I9HeP6GzeqaVd49WqHo7ba+cZqE9LSH4wynh7oS9r3Eca8FzN1qsey3w+1XqOuphnZrT4QP7hYZ7ABVCBRGpstVF8duBbz+cRevEKKPAq5ftOmOl1jMKsUln+z6lvv9hKl2GrSBUyWkZyEcZzgd1JWwVyLcR725qFJbnqWe0t+aUxZN/RHeHfZYnApYWgywVbmSgbU1RcRm5HHA4HmbRFyI2hBzYaDTYmx9y/1+w1TbDdojd4unSkjPejjOcHzUlbBXIo7HtbnoIEJdT1kYLV0RHj0scLUHLr/uML8U8sN3faZyFl2PIZKw6WgvP6tiAFiyuSEKqhOmqvS9Hle4pp7CcYbDUVfCDtsfHDFyt3ioTnnQDldPQr1f/LWA1mYL9UsMP4BITHj9kzEeLCrpnNLXIazlFVVY8mwcS1lIK26MbU83OgiVvNfjjHvXUzjOcDjqTti3Uq1OaTpc9cnMB8QKPtdecIhFoejBYiYgalmEjQ5LlsXIO0V6ei36L0bwCsrN9WPoiunqhKkqea/HGfeup3Cc4XDUtbBXq1OaDld91lYD2hotVEFEiEUh6ior2ZDO63Y5b/2SS3q6xOic4sYtrn4qVvWdn3u91+OOe5tZnqES6lrYq9kpTYerLrGETdEPeTQVMNQjhAqjMyGZvMPVnp0rP1abvd6riXsbTiN1LeymU55eWjttmm1YmLb4zvs+GkK8xaHnypNaMqchFdGE4QynkboW9nrtlJUeWH2SG3M2ygM/dzXCSzfcpw5vhoOF0fbbpkquN2E4w2mkroW9HjtlJZ7uafCG93o3+w2j7bdN+7nehOEMp426Fnaov05Ziad7WnY47vZu9htG22+bTsszMBgOQt0Le71Riae7H294p3DFUYdy9htG29qm3EpIdsGnVFDGJnVb28wuT8NZxgh7nVGJp1upN7xTuGI5GyHMlI40lLPfMNpGmwiVlelSuWpkA6x4QmYb28zCuuEsY4S9zqjE063UG94pXPHWzTyv34hUHMY4jpOhNtpkF3yGuiAMYWJeGRh0cSJ8xLZ6XVg31AZG2OuMSuvlVOIN7xSuKKzsL5RzHAu1G21673/7lEpKNCG09bmkUhaq+hHb6nFh3VA7GGGvQyrxdMsCFtn0pNPTJSBSUbgi1lh5GOO4t+Sfu+JyrlU3P2832yp5TiedFmowbIf5Bhq2ZdOTblVeviSca1Uyo0WymXDzmtaeCBMzSm41RFU3i2+duxbf9vet2+wY3XGRMn80i5Q72bydbXtRyTMyGE4C47EbtqUST3q3cEW22aoojHHci5TVDLGYlEjDacUIu2FbKk332+0A60rE7SQWKau1d8GkRBpOK0bYDdtSLU96rxj0QT3o0xDbNimRhtNKVYRdRH4T+D2gQ1UXqnFPw8lSDU+60oyX/XrQp6HkAZiUSMPp5dDCLiIDwM8AY4c3x3BaqEYs+qhi0Kcltm1SIg2nlWp47L8P/BbwZ1W4l+EUcdhY9FHFoE9TbLveag0ZzgaHci1E5EvApKrequDaXxORd0Xk3aW0SQerBza38W+hGjHoo7qvwVAr7Omxi8h3gO5t/teXgd8FfraSD1LVrwBfAbj+kmvSBuqAo4pBm9i2wbA7ewq7qn5uu9+LyIvAEHBLRAD6gZsi8pqqzlTVSsOZ5Khi0NW872nIrjEYqs2BY+yq+gHQufGziDwGXjVZMYatHFUMuhr3PS3ZNQZDtTHfXkPdkp4u0b+eXSNS/nd/t6zXxTEYzi5V26CkquerdS/D0WLCD2VOU3aNwVBNzM7TOsOEH55gdo4aapX66skGE37YQjUrPRoMpwnjsdcZJvzwBLNz1FCrGGGvM0z44WnMzlFDLWJckzrDhB8MhtrHeOx1hgk/GAy1jxH2OsSEHwyG2sa4aQaDwVBjGGE3GAyGGsMIu8FgMNQYRtgNBoOhxhDV49+YIiLzwOgxfFQ7UCvVJmupLVBb7amltkBttaeW2gJwRVUb97roRLJiVLXjOD5HRN5V1VeP47OOmlpqC9RWe2qpLVBb7amltkC5PZVcZ0IxBoPBUGMYYTcYDIYao9aF/SsnbUAVqaW2QG21p5baArXVnlpqC1TYnhNZPDUYDAbD0VHrHrvBYDDUHUbYDQaDocaoC2EXkd8UERWR9pO25TCIyO+JyD0ReV9E/lREUidt034Rkc+LyH0ReSAi//ik7TkMIjIgIv9LRO6KyE9E5DdO2qbDIiK2iPxYRP78pG05LCKSEpGvrfeZuyLyxknbdFBE5B+uf8dui8h/FJHYbtfXvLCLyADwM8DYSdtSBb4NvKCqLwEfAr9zwvbsCxGxgX8N/DxwDfibInLtZK06FD7wj1T1eeB14O+c8fYA/AZw96SNqBL/CviGql4FXuaMtktE+oC/D7yqqi8ANvBLu/1NzQs78PvAbwFnfpVYVb+lqv76j28B/SdpzwF4DXigqo9U1QP+E/ALJ2zTgVHVaVW9uf7fK5SFo+9krTo4ItIPfAH4w5O25bCISBPwU8AfAaiqp6qZk7XqUDhAXEQcIAFM7XZxTQu7iHwJmFTVWydtyxHwq8D/PGkj9kkfML7l5wnOsBBuRUTOAx8D3j5ZSw7Fv6TsBIUnbUgVuADMA/9+PbT0hyLScNJGHQRVnQT+OeWowzSQVdVv7fY3Z17YReQ763GnZ//5BeDLwD85aRv3w5o+IzkAAAHWSURBVB7t2bjmy5TDAF89OUsPxHYHq575mZSIJIH/CvwDVV0+aXsOgoh8EZhT1R+dtC1VwgFuAP9GVT8GrAJnck1HRFooz2yHgF6gQUT+1m5/c+ZPUFLVz233exF5kfKDuCUiUA5b3BSR11R15hhN3Bc7tWcDEfll4IvAZ/XsbUKYAAa2/NzPHlPK046IRCiL+ldV9U9O2p5D8CbwJRH5a0AMaBKRP1bVXQXkFDMBTKjqxgzqa5xRYQc+B4yo6jyAiPwJ8Engj3f6gzPvse+Eqn6gqp2qel5Vz1N+0TdOs6jvhYh8Hvht4EuqunbS9hyAd4BLIjIkIi7lBaCvn7BNB0bKHsMfAXdV9V+ctD2HQVV/R1X71/vKLwF/cYZFnfV+Pi4iV9Z/9VngzgmadBjGgNdFJLH+nfsseywEn3mPvc74AyAKfHt9FvKWqv76yZpUOarqi8jfBb5JeWX/36nqT07YrMPwJvC3gQ9E5L313/2uqv6PE7TJ8IS/B3x13Yl4BPzKCdtzIFT1bRH5GnCTcgj2x+xRWsCUFDAYDIYao2ZDMQaDwVCvGGE3GAyGGsMIu8FgMNQYRtgNBoOhxjDCbjAYDDWGEXaDwWCoMYywGwwGQ43x/wFH8X2wUzadkgAAAABJRU5ErkJggg==\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "xx, yy = numpy.meshgrid(numpy.arange(-5, 8, 0.02), numpy.arange(-5, 8, 0.02))\n", + "Z = model.predict(numpy.c_[xx.ravel(), yy.ravel()])\n", + "Z = Z.reshape(xx.shape)\n", + "\n", + "# Overlay the training points on the decision boundary.\n", + "matplotlib.pyplot.contourf(xx, yy, Z);\n", + "matplotlib.pyplot.scatter(X[y == 0, 0], X[y == 0, 1], c=\"deepskyblue\", edgecolor=\"k\", alpha=0.2);\n", + "matplotlib.pyplot.scatter(X[y == 1, 0], X[y == 1, 1], c=\"orange\", edgecolor=\"k\", alpha=0.2);\n", + "matplotlib.pyplot.xlim(-5, 8);\n", + "matplotlib.pyplot.ylim(-5, 8);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

Notice that we have the same Numpy interfaces everywhere, and everything acts one array at a time, rather than one value at a time.

\n", + "\n", + "
\n", + "\n", + "

The new deep learning frameworks define their own array types (e.g. PyTorch tensors, TensorFlow tensors), but these are very similar to Numpy arrays, with the addition that they can move data to and from GPUs.

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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

Example 1: pyjet, a Numpythonic wrapper for FastJet

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(0.08220963, 0.01673939, -0.07650449, 0.02500557),\n", + " (0.61890405, 0.55747803, -0.0677895 , 0.26012509),\n", + " (0.36398172, 0.01831549, 0.30128464, -0.20340796),\n", + " (0.36103217, 0.05255898, -0.34410183, 0.09578994),\n", + " (0.36571832, 0.07214153, 0.29491113, -0.20389436)],\n", + " dtype=[('E', '

\n", + "\n", + "

Example 2: particle, an interface to Particle Data Tables

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$\\Sigma^{-}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Sigma}^{+}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\Lambda$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Lambda}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\Sigma^{+}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Sigma}^{-}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\Xi^{-}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Xi}^{+}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\Xi^{0}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Xi}^{0}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\Omega^{-}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + }, + { + "data": { + "text/latex": [ + "$\\bar{\\Omega}^{+}$" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n" + ] + } + ], + "source": [ + "import particle\n", + "from hepunits.units import cm\n", + "\n", + "import IPython.display\n", + "\n", + "# Find all strange baryons with c*tau > 1 cm\n", + "for x in particle.Particle.findall(lambda p:\n", + " p.pdgid.is_baryon and p.pdgid.has_strange and p.width > 0 and p.ctau > 1 * cm):\n", + " \n", + " IPython.display.display(IPython.display.Latex(\"$\" + x.latex_name + \"$\"))\n", + " print(repr(x), end=\"\\n\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

Example 3: pyhf, limit-setting similar to HistFactory and CmsCombine

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import pyhf # (scale to 125%)\n", + "import awkward\n", + "\n", + "s, b, obs = [[0.0, 0.0, 0.1, 0.2, 0.5, 1.0, 1.8, 2.7, 2.0, 0.3], # signal peaks around bin 8\n", + " [6.0, 5.5, 4.5, 3.8, 3.3, 2.6, 2.0, 1.8, 1.5, 1.0], # background steadily falls\n", + " [ 6, 7, 4, 4, 4, 3, 4, 3, 4, 0]] # observations perfer 3/4 signal\n", + "model = pyhf.simplemodels.hepdata_like(signal_data=s, bkg_data=b, bkg_uncerts=numpy.sqrt(b).tolist())\n", + "def hypotest(mu):\n", + " return pyhf.utils.hypotest(mu, obs + model.config.auxdata, model, return_expected_set=True)\n", + "\n", + "mus = numpy.linspace(0, 2, 30)\n", + "CLs = awkward.fromiter([hypotest(mu) for mu in mus])\n", + "CLs_observed = CLs[:, 0, 0] # mucking around with indexes\n", + "CLs_minus2, CLs_minus1, CLs_expected, CLs_plus1, CLs_plus2 = [CLs[:, 1, i, 0] for i in range(5)]\n", + "\n", + "matplotlib.pyplot.fill_between(mus, CLs_minus2, CLs_plus2, facecolor=\"yellow\");\n", + "matplotlib.pyplot.fill_between(mus, CLs_minus1, CLs_plus1, facecolor=\"limegreen\");\n", + "matplotlib.pyplot.plot(mus, CLs_expected, c=\"black\", linestyle=\"dotted\");\n", + "matplotlib.pyplot.plot(mus, CLs_observed, c=\"black\", marker=\"o\");" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### Part 3: ROOT data in Python\n", + "\n", + "




" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning in : Deleting canvas with same name: canvas\n" + ] + }, + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import ROOT # PyROOT\n", + "\n", + "file = ROOT.TFile(\"data/HZZ-objects.root\") # PyROOT transliterates C++ to Python\n", + "tree = file.Get(\"events\")\n", + "\n", + "canvas = ROOT.TCanvas(\"canvas\", \"\", 400, 300) # JupyROOT only: must create TCanvas\n", + "tree.Draw(\"muonp4.Pt()\")\n", + "canvas.Draw() # and Draw it to see plots inline" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "event 0\n", + " 54.16810703140204\n", + " 37.74415265978988\n", + "event 1\n", + " 24.41791248135961\n", + "event 2\n", + " 53.58826697278532\n", + " 29.811997139120674\n", + "event 3\n", + " 88.63194310332618\n", + " 77.95148447265454\n", + "event 4\n", + " 81.01140452083426\n", + " 47.17504574667714\n", + "event 5\n", + " 41.591052358050575\n", + " 30.844215085173435\n", + "event 6\n", + " 44.35777431661225\n", + " 29.874452374029385\n", + "event 7\n", + " 38.37087544930784\n", + "event 8\n", + " 106.28355631699014\n", + " 12.311635885539262\n", + "event 9\n", + " 85.53881159059787\n", + " 39.506103898783294\n", + "event 10\n", + " 51.64914852288953\n", + " 46.49716868294783\n", + "event 11\n", + " 75.51093887887036\n", + " 50.514888290524446\n" + ] + } + ], + "source": [ + "# PyROOT can iterate over the data directly, in a Python-friendly way.\n", + "\n", + "for i, event in enumerate(tree):\n", + " print(\"event\", i)\n", + " for muon in event.muonp4:\n", + " print(repr(muon), muon.Pt())\n", + " if i > 10:\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

But be forewarned: PyROOT was not made to be used in a loop over big data. (Actually, it's as much slower than Python as Python is from C++.)

\n", + "\n", + "
\n", + "\n", + "

You can start this way, but if you'll be analyzing TB of data, you'll have to rewrite your code.

\n", + "\n", + "
\n", + "\n", + "

We want to explore data in a way that doesn't have to be completely rewritten for speed.

\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[0.00927101],\n", + " [0.00033064],\n", + " [0.00507963],\n", + " ...,\n", + " [0.00415307],\n", + " [0.00882933],\n", + " [0.00875541]])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# PyROOT's new AsMatrix method gives you Numpy arrays directly (loops run in C++).\n", + "\n", + "tree.AsMatrix([\"eventweight\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "ename": "Exception", + "evalue": "Reading of branch ['MET'] is not supported (branch has unsupported data-type ['TVector2']).", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mException\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# But it's only for purely numeric data, not objects...\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mtree\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAsMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"MET\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/ROOT.py\u001b[0m in \u001b[0;36m_TTreeAsMatrix\u001b[0;34m(self, columns, exclude, dtype, return_labels)\u001b[0m\n\u001b[1;32m 331\u001b[0m raise Exception(exception_template.format(\n\u001b[1;32m 332\u001b[0m [k for k in invalid_cols_dtype], \"branch has unsupported data-type {}\".format(\n\u001b[0;32m--> 333\u001b[0;31m [invalid_cols_dtype[k] for k in invalid_cols_dtype])))\n\u001b[0m\u001b[1;32m 334\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 335\u001b[0m \u001b[0;31m# Check that given data-type is supported\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mException\u001b[0m: Reading of branch ['MET'] is not supported (branch has unsupported data-type ['TVector2'])." + ] + } + ], + "source": [ + "# But it's only for purely numeric data, not objects...\n", + "\n", + "tree.AsMatrix([\"MET\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [ + { + "ename": "Exception", + "evalue": "Reading of branch ['muoniso'] is not supported (branch has unsupported data-type ['vector']).", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mException\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# ... and not variable number of values per event, like vector\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mtree\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mAsMatrix\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"muoniso\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/ROOT.py\u001b[0m in \u001b[0;36m_TTreeAsMatrix\u001b[0;34m(self, columns, exclude, dtype, return_labels)\u001b[0m\n\u001b[1;32m 331\u001b[0m raise Exception(exception_template.format(\n\u001b[1;32m 332\u001b[0m [k for k in invalid_cols_dtype], \"branch has unsupported data-type {}\".format(\n\u001b[0;32m--> 333\u001b[0;31m [invalid_cols_dtype[k] for k in invalid_cols_dtype])))\n\u001b[0m\u001b[1;32m 334\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 335\u001b[0m \u001b[0;31m# Check that given data-type is supported\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mException\u001b[0m: Reading of branch ['muoniso'] is not supported (branch has unsupported data-type ['vector'])." + ] + } + ], + "source": [ + "# ... and not variable number of values per event, like vector\n", + "\n", + "tree.AsMatrix([\"muoniso\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# ROOT's new preferred way of processing TTrees is called RDataFrame.\n", + "# You can define a dataflow in Python with C++ in strings (convenient!).\n", + "\n", + "rdf = ROOT.RDataFrame(\"events\", \"data/HZZ-objects.root\")\n", + "h = (rdf.Filter(\"muonp4.size() >= 2\")\n", + " .Define(\"zmass\", r\"\"\"(muonp4[0] + muonp4[1]).M()\"\"\")\n", + " .Histo1D((\"\", \"\", 120, 0, 120), \"zmass\"))\n", + "h.Draw(); canvas.Draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'zmass': numpy.array([90.22779777, 74.74654928, 89.75736376, ..., 92.06495256,\n", + " 85.44384208, 75.96066262])}" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# And you can get the result of this dataflow as Numpy arrays (even better!).\n", + "\n", + "array = (rdf.Filter(\"muonp4.size() >= 2\")\n", + " .Define(\"zmass\", r\"\"\"(muonp4[0] + muonp4[1]).M()\"\"\")\n", + " .AsNumpy(columns=[\"zmass\"]))\n", + "array" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "numpy.array([ object at 0x5a08b5f8f790>,\n", + " object at 0x5a08b5f8f7b8>,\n", + " object at 0x5a08b5f8f7e0>,\n", + " ...,\n", + " object at 0x5a08b5fa7160>,\n", + " object at 0x5a08b5fa7188>,\n", + " object at 0x5a08b5fa71b0>],\n", + " dtype=object)" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# You can also get arrays of objects and arrays of vectors of objects.\n", + "\n", + "array = rdf.AsNumpy(columns=[\"muonp4\"])[\"muonp4\"]\n", + "array" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "event 0\n", + " 54.16810703140204\n", + " 37.74415265978988\n", + "event 1\n", + " 24.41791248135961\n", + "event 2\n", + " 53.58826697278532\n", + " 29.811997139120674\n", + "event 3\n", + " 88.63194310332618\n", + " 77.95148447265454\n", + "event 4\n", + " 81.01140452083426\n", + " 47.17504574667714\n", + "event 5\n", + " 41.591052358050575\n", + " 30.844215085173435\n", + "event 6\n", + " 44.35777431661225\n", + " 29.874452374029385\n", + "event 7\n", + " 38.37087544930784\n", + "event 8\n", + " 106.28355631699014\n", + " 12.311635885539262\n", + "event 9\n", + " 85.53881159059787\n", + " 39.506103898783294\n", + "event 10\n", + " 51.64914852288953\n", + " 46.49716868294783\n", + "event 11\n", + " 75.51093887887036\n", + " 50.514888290524446\n" + ] + } + ], + "source": [ + "# But looping over them is back to PyROOT. The array is an array of PyROOT objects.\n", + "\n", + "for i, event in enumerate(array):\n", + " print(\"event\", i)\n", + " for muon in event:\n", + " print(repr(muon), muon.Pt())\n", + " if i > 10:\n", + " break" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

To get efficient processing in ROOT, you have to do the heavy work in C++. That's just how it works. What's new is that the C++ can be expressed as inline strings in Python.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

uproot is an alternative ROOT I/O implemented in Python + Numpy (i.e. it's pip-installable).

\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import uproot\n", + "\n", + "file = uproot.open(\"data/HZZ-objects.root\")\n", + "tree = file[\"events\"]\n", + "\n", + "array = tree.array(\"muonp4\")\n", + "array" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " layout \n", + "[ ()] JaggedArrayMethods(starts=layout[0], stops=layout[1], content=layout[2])\n", + "[ 0] ndarray(shape=2421, dtype=dtype('int64'))\n", + "[ 1] ndarray(shape=2421, dtype=dtype('int64'))\n", + "[ 2] ObjectArrayMethods(content=layout[2, 0], generator=. at 0x7bac2e39e6a8>, args=(), kwargs={})\n", + "[ 2, 0] Table( fBits=layout[2, 0, 0], fUniqueID=layout[2, 0, 1], fBits2=layout[2, 0, 2], fUniqueID2=layout[2, 0, 3], fX=layout[2, 0, 4], fY=layout[2, 0, 5], fZ=layout[2, 0, 6], fE=layout[2, 0, 7])\n", + "[2, 0, 0] ndarray(shape=3825, dtype=dtype('uint64'))\n", + "[2, 0, 1] ndarray(shape=3825, dtype=dtype('uint64'))\n", + "[2, 0, 2] ndarray(shape=3825, dtype=dtype('uint64'))\n", + "[2, 0, 3] ndarray(shape=3825, dtype=dtype('uint64'))\n", + "[2, 0, 4] ndarray(shape=3825, dtype=dtype('float64'))\n", + "[2, 0, 5] ndarray(shape=3825, dtype=dtype('float64'))\n", + "[2, 0, 6] ndarray(shape=3825, dtype=dtype('float64'))\n", + "[2, 0, 7] ndarray(shape=3825, dtype=dtype('float64'))\n", + "\n", + "array for TLorentzVector.fX:\n", + "[-52.89945602 37.73778152 -0.81645936 ... -29.75678635 1.14186978\n", + " 23.9132061 ]\n" + ] + } + ], + "source": [ + "# Although this looks like an array of variable-length arrays of TLorentzVectors,\n", + "# it's implmented in terms of columnar arrays, not objects.\n", + "print(array.layout)\n", + "print(f\"\\narray for TLorentzVector.fX:\\n{array.layout[2, 0, 4].array}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "good_events: [ True False True ... False False False]\n", + "\n", + "first: [TLorentzVector(-52.899, -11.655, -8.1608, 54.779) TLorentzVector(48.988, -21.723, 11.168, 54.74) TLorentzVector(22.088, -85.835, 403.85, 413.46) ... TLorentzVector(53.006, -24.486, 13.952, 60.032) TLorentzVector(55.72, 26.37, -24.588, 66.368) TLorentzVector(34.507, 28.84, -150.66, 157.23)]\n", + "second: [TLorentzVector(37.738, 0.69347, -11.308, 39.402) TLorentzVector(0.82757, 29.801, 36.965, 47.489) TLorentzVector(76.692, -13.956, 335.09, 344.04) ... TLorentzVector(-30.209, 19.269, 18.661, 40.399) TLorentzVector(-26.914, -9.8128, -0.38995, 28.65) TLorentzVector(-31.568, -10.424, -111.26, 116.13)]\n", + "\n", + "z_mass: [90.22779777 74.74654928 89.75736376 ... 92.06495256 85.44384208\n", + " 75.96066262]\n" + ] + } + ], + "source": [ + "# So the interface is array-at-a-time: neither for loops nor call-outs to C++.\n", + "\n", + "good_events = (array.counts >= 2)\n", + "print(f\"good_events: {good_events}\")\n", + "\n", + "first = array[good_events, 0]\n", + "second = array[good_events, 1]\n", + "print(f\"\\nfirst: {first}\")\n", + "print(f\"second: {second}\")\n", + "\n", + "z_candidates = first + second\n", + "print(f\"\\nz_mass: {z_candidates.mass}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Which one should you use?

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Both!

\n", + "\n", + "




" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/03-columnar-data-analysis.ipynb b/03-columnar-data-analysis.ipynb new file mode 100644 index 0000000..d218d0d --- /dev/null +++ b/03-columnar-data-analysis.ipynb @@ -0,0 +1,10635 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "# Columnar data analysis\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "

Array programming is a programming language paradigm like Object-Oriented Programming (OOP) and Functional Programming (FP).

\n", + "\n", + "
\n", + "\n", + "

As physicists, we are mostly familiar with imperative, procedural, structured, object-oriented programming (see this list).

\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " \n", + " " + ], + "text/plain": [ + "" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from IPython.display import IFrame \n", + "IFrame(\"http://zoom.it/6rJp\", width=\"100%\", height=\"440\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

Array programming is common to languages and systems designed for interactive data analysis.

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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
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Special keyboard for all the symbols.
A program was a struggle to write, but T-shirt fodder when it worked.
\n", + "\n", + "
\n", + "\n", + "

APL (1963) pioneered programming language conciseness—and discovered the mistake of being too concise.

\n", + "\n", + "| APL |
| Numpy |\n", + "|:---:|:----:|:-----:|\n", + "| ι4 |
| numpy.arange(4) |\n", + "| (3+ι4) |
| numpy.arange(4) + 3 |\n", + "| +/(3+ι4) |
| (numpy.arange(4) + 3).sum() |\n", + "| m ← +/(3+ι4) |
| m = (numpy.arange(4) + 3).sum() |\n", + "\n", + "(The other extreme is writing for loops for each of the above.)\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "

The fundamental data type in this world is an array. (Some array languages don't even have non-arrays.)

\n", + "\n", + "
\n", + "\n", + "

Unlike the others (APL, IDL, MATLAB, R), Numpy is a library, not a language, though it goes all the way back to the beginning of Python (1995) and significantly influenced Python's grammar.

\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19]\n", + "\n", + "[-5. -4.5 -4. -3.5 -3. -2.5 -2. -1.5 -1. -0.5 0. 0.5 1. 1.5\n", + " 2. 2.5 3. 3.5 4. 4.5 5. ]\n", + "\n", + "[0.007812 0. 0. ... 0.01394 0.01394 0.01394 ]\n", + "\n", + "[[999 999 999 999 999 999 999]\n", + " [999 999 999 999 999 999 999]]\n", + "\n", + "[-0.99976933 -1.00019534 -1.00011246 ... -0.99993442 -1.00016844\n", + " -1.00002186]\n", + "\n", + "[82.20186639 62.34492895 62.34492895 ... 81.27013558 81.27013558\n", + " 81.56621735]\n", + "\n" + ] + } + ], + "source": [ + "# Assortment of ways to make Numpy arrays\n", + "\n", + "import numpy, uproot\n", + "print(numpy.arange(20), end=\"\\n\\n\")\n", + "print(numpy.linspace(-5, 5, 21), end=\"\\n\\n\")\n", + "print(numpy.empty(10000, numpy.float16), end=\"\\n\\n\")\n", + "print(numpy.full((2, 7), 999), end=\"\\n\\n\")\n", + "print(numpy.random.normal(-1, 0.0001, 10000), end=\"\\n\\n\")\n", + "print(uproot.open(\"data/Zmumu.root\")[\"events\"][\"E1\"].array(), end=\"\\n\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

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\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "data:\n", + " [1073741824 1140850688 -1 0 1090519040 1074790400]\n", + "\n", + "type: \n", + "\n", + "dtype (type of the data it contains): int32\n", + "\n", + "shape: (size of each dimension): (6,)\n", + "\n" + ] + } + ], + "source": [ + "a = numpy.array([2**30, 2**30 + 2**26, -1, 0, 2**30 + 2**24, 2**30 + 2**20], numpy.int32)\n", + "# a = a.view(numpy.float32)\n", + "# a = a.reshape((2, 3))\n", + "# a = a.astype(numpy.int64)\n", + "\n", + "print(\"data:\\n\", a, end=\"\\n\\n\")\n", + "print(\"type:\", type(a), end=\"\\n\\n\")\n", + "print(\"dtype (type of the data it contains):\", a.dtype, end=\"\\n\\n\")\n", + "print(\"shape: (size of each dimension):\", a.shape, end=\"\\n\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scalar:\n", + " 0.0009193883860658306\n", + "\n", + "array:\n", + " [ 0.00091939 0.00521689 0.00540031 ... -0.005628 -0.00614183\n", + " 0.00124659]\n", + "\n" + ] + } + ], + "source": [ + "# Any mathematical function that would map scalar arguments to a scalar result\n", + "# maps array arguments to an array result.\n", + "\n", + "a_array = numpy.random.uniform(5, 10, 10000); a_scalar = a_array[0]\n", + "b_array = numpy.random.uniform(10, 20, 10000); b_scalar = b_array[0]\n", + "c_array = numpy.random.uniform(-0.1, 0.1, 10000); c_scalar = c_array[0]\n", + "\n", + "def quadratic_formula(a, b, c):\n", + " return (-b + numpy.sqrt(b**2 - 4*a*c)) / (2*a)\n", + "\n", + "print(\"scalar:\\n\", quadratic_formula(a_scalar, b_scalar, c_scalar), end=\"\\n\\n\")\n", + "print(\"array:\\n\", quadratic_formula(a_array, b_array, c_array), end=\"\\n\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ 0.00091939, 0.00521689, 0.00540031, ..., -0.005628 ,\n", + " -0.00614183, 0.00124659]),\n", + " array([ 0.00091939, 0.00521689, 0.00540031, ..., -0.005628 ,\n", + " -0.00614183, 0.00124659]))" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Each step in the calculation is performed over whole arrays before moving on to the next.\n", + "\n", + "a, b, c = a_array, b_array, c_array\n", + "\n", + "roots1 = (-b + numpy.sqrt(b**2 - 4*a*c)) / (2*a)\n", + "\n", + "tmp1 = numpy.negative(b) # -b\n", + "tmp2 = numpy.square(b) # b**2\n", + "tmp3 = numpy.multiply(4, a) # 4*a\n", + "tmp4 = numpy.multiply(tmp3, c) # tmp3*c\n", + "tmp5 = numpy.subtract(tmp2, tmp4) # tmp2 - tmp4\n", + "tmp6 = numpy.sqrt(tmp5) # sqrt(tmp5)\n", + "tmp7 = numpy.add(tmp1, tmp6) # tmp1 + tmp6\n", + "tmp8 = numpy.multiply(2, a) # 2*a\n", + "roots2 = numpy.divide(tmp7, tmp8) # tmp7 / tmp8\n", + "\n", + "roots1, roots2" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ True, True, True, ..., True, True, True])" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Even comparison operators are element-by-element.\n", + "\n", + "roots1 == roots2" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# So use a reducer (e.g. sum, max, min, any, all) to turn the array into a scalar.\n", + "\n", + "(roots1 == roots2).all()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Just as a Numpy array is a common data type, this is a common function type: \"universal functions\" or \"ufuncs.\"

\n", + "\n", + "




" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.20179848, 62.34483942, 62.34483942, ..., 81.27006689,\n", + " 81.27006689, 81.56614892])" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "px, py, pz = uproot.open(\"data/Zmumu.root\")[\"events\"].arrays(\"p[xyz]1\", outputtype=tuple)\n", + "\n", + "p = numpy.sqrt(px**2 + py**2 + pz**2)\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# But what if there are multiple values per event?\n", + "\n", + "uproot.open(\"data/HZZ.root\")[\"events\"].array(\"Muon_Px\")" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# JaggedArray can be used in place of a Numpy array in some contexts,\n", + "# such as array-at-a-time math. Functions like numpy.sqrt recognize it.\n", + "\n", + "px, py, pz = uproot.open(\"data/HZZ.root\")[\"events\"].arrays([\"Muon_P[xyz]\"], outputtype=tuple)\n", + "\n", + "numpy.sqrt(px**2 + py**2 + pz**2)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "
\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]))" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "E, px, py, pz = uproot.open(\"data/Zmumu.root\")[\"events\"].arrays([\"E1\", \"p[xyz]1\"], outputtype=tuple)\n", + "\n", + "# Numpy arrays\n", + "# array array array scalar\n", + "energy = numpy.sqrt(px**2 + py**2 + pz**2 + 0.1056583745**2)\n", + "energy, E" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "E, px, py, pz = uproot.open(\"data/HZZ.root\")[\"events\"].arrays([\"Muon_E\", \"Muon_P[xyz]\"], outputtype=tuple)\n", + "\n", + "# JaggedArrays\n", + "# array array array scalar\n", + "energy = numpy.sqrt(px**2 + py**2 + pz**2 + 0.1056583745**2)\n", + "energy, E" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "scalar + flat: [1100 1200 1300]\n", + "\n", + "scalar + jagged: [[1001.1 1002.2 1003.3] [] [1004.4 1005.5]]\n", + "\n", + " flat + jagged: [[101.1 102.2 103.3] [] [304.4 305.5]]\n" + ] + } + ], + "source": [ + "import awkward # the library that defines JaggedArrays and other \"awkward\" arrays\n", + "\n", + "scalar = 1000\n", + "flat = numpy.array([100, 200, 300])\n", + "jagged = awkward.fromiter([[1.1, 2.2, 3.3], [], [4.4, 5.5]])\n", + "\n", + "# With JaggedArrays, there are more broadcasting cases:\n", + "print(f\"scalar + flat: {scalar + flat}\")\n", + "print(f\"\\nscalar + jagged: {scalar + jagged}\")\n", + "print(f\"\\n flat + jagged: {flat + jagged}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "multi per event: [[] [2.669215] [] ... [-1.6703207] [2.8687775 -2.0823672] []]\n", + "one per event: [ 0.40911174 -0.58348763 2.5796134 ... 1.2252938 -0.58017296\n", + " -0.18039851]\n", + "\n", + "difference: [[] [3.2527027] [] ... [-2.8956146] [3.4489505 -1.5021942] []]\n" + ] + } + ], + "source": [ + "# Using jagged broadcasting in physics\n", + "\n", + "jetx, jety, metx, mety = uproot.open(\"data/HZZ.root\")[\"events\"].arrays(\n", + " [\"Jet_P[xy]\", \"MET_p[xy]\"], outputtype=tuple)\n", + "\n", + "jet_phi = numpy.arctan2(jety, jetx)\n", + "met_phi = numpy.arctan2(mety, metx)\n", + "\n", + "print(f\"multi per event: {jet_phi}\")\n", + "print(f\"one per event: {met_phi}\")\n", + "\n", + "print(f\"\\ndifference: {jet_phi - met_phi}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Q: What about ensuring that each delta-phi is between -pi and pi without if/then?\n", + "# A: You start to pick up tricks, like this:\n", + "\n", + "raw_diff = jet_phi - met_phi\n", + "\n", + "bounded_diff = (raw_diff + numpy.pi) % (2*numpy.pi) - numpy.pi\n", + "\n", + "# Should dphi be a library function? That's the kind of question we think about...\n", + "\n", + "raw_diff, bounded_diff\n", + "# bounded_diff.flatten().min(), bounded_diff.flatten().max()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Reducers: any, all, count, count_nonzero, sum, prod, min, max

\n", + "\n", + "




" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(-3.141034, 3.1297169)" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Another way JaggedArrays extend Numpy arrays:\n", + "\n", + "# Reducers, like sum, min, max, turn flat arrays into scalars.\n", + "\n", + "met_phi.min(), met_phi.max()" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([ inf, 2.669215 , inf, ..., -1.6703207, -2.0823672,\n", + " inf], dtype=float32),\n", + " array([ -inf, 2.669215 , -inf, ..., -1.6703207, 2.8687775,\n", + " -inf], dtype=float32))" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Another way JaggedArrays extend Numpy arrays:\n", + "\n", + "# Reducers, like sum, min, max, turn jagged arrays into flat arrays.\n", + "\n", + "jet_phi.min(), jet_phi.max()" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([6., 0., 9.])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The meaning of flat.sum() is \"sum of all elements of the flat array.\"\n", + "# The meaning of jagged.sum() is \"sum of all elements in each inner array.\"\n", + "\n", + "jagged = awkward.fromiter([[1.0, 2.0, 3.0], [], [4.0, 5.0]])\n", + "jagged.sum() # min, max" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(15.0, 15.0)" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# jagged.sum().sum() completes the process, resulting in a scalar. But,\n", + "# jagged.flatten().sum() does the same thing. Why?\n", + "\n", + "jagged.sum().sum(), jagged.flatten().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ nan, 2.66921496, nan, ..., -1.67032075,\n", + " 0.39320517, nan])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# mean, var, std are also available, just like Numpy, but these aren't associative.\n", + "\n", + "# \"Don't do a mean of means unless you mean it!\"\n", + "\n", + "jet_phi.mean()" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "same_hemicircle: [[] [False] [] ... [False] [False True] []]\n", + "same_hemicircle.any(): [False False False ... False True False]\n", + "same_hemicircle.any().any(): True\n", + "same_hemicircle.any().all(): False\n", + "same_hemicircle.all(): [ True False True ... False False True]\n", + "same_hemicircle.all().any(): True\n", + "same_hemicircle.all().all(): False\n" + ] + } + ], + "source": [ + "# Also worth noting that any and all are reducers... of booleans.\n", + "\n", + "same_hemicircle = (abs(bounded_diff) < numpy.pi/2)\n", + "\n", + "print(f\"same_hemicircle: {same_hemicircle}\")\n", + "print(f\"same_hemicircle.any(): {same_hemicircle.any()}\")\n", + "print(f\"same_hemicircle.any().any(): {same_hemicircle.any().any()}\")\n", + "print(f\"same_hemicircle.any().all(): {same_hemicircle.any().all()}\")\n", + "print(f\"same_hemicircle.all(): {same_hemicircle.all()}\")\n", + "print(f\"same_hemicircle.all().any(): {same_hemicircle.all().any()}\")\n", + "print(f\"same_hemicircle.all().all(): {same_hemicircle.all().all()}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

Slicing: single-item extraction, filtering (cuts), rearrangement

\n", + "\n", + "




" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a[3] = 3.3\n", + "a[3:] = [3.3 4.4 5.5 6.6 7.7 8.8 9.9]\n", + "a[:3] = [0. 1.1 2.2]\n", + "a[3:7] = [3.3 4.4 5.5 6.6]\n", + "a[3:7:2] = [3.3 5.5]\n", + "a[::2] = [0. 2.2 4.4 6.6 8.8]\n", + "\n", + "a[-3] = 7.7\n", + "a[-3:] = [7.7 8.8 9.9]\n", + "a[:-3] = [0. 1.1 2.2 3.3 4.4 5.5 6.6]\n", + "a[-7:-3] = [3.3 4.4 5.5 6.6]\n", + "a[-7:-3:2] = [3.3 5.5]\n", + "a[::-1] = [9.9 8.8 7.7 6.6 5.5 4.4 3.3 2.2 1.1 0. ]\n" + ] + } + ], + "source": [ + "# Basic array slicing is the same as Python list slicing\n", + "\n", + "a = numpy.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n", + "\n", + "for expr in [\"a[3] \", \"a[3:] \", \"a[:3] \",\n", + " \"a[3:7] \", \"a[3:7:2] \", \"a[::2] \"]:\n", + " print(expr, \"=\", eval(expr))\n", + "\n", + "print()\n", + "for expr in [\"a[-3] \", \"a[-3:] \", \"a[:-3] \",\n", + " \"a[-7:-3] \", \"a[-7:-3:2]\", \"a[::-1] \"]:\n", + " print(expr, \"=\", eval(expr))" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a[2:, 1:] =\n", + "[[21 22 23 24 25]\n", + " [31 32 33 34 35]]\n", + "\n", + "a[:, 1:-1] =\n", + "[[ 1 2 3 4]\n", + " [11 12 13 14]\n", + " [21 22 23 24]\n", + " [31 32 33 34]]\n", + "\n", + "a[::2, ::2] =\n", + "[[ 0 2 4]\n", + " [20 22 24]]\n", + "\n", + "a[:, 3] =\n", + "[ 3 13 23 33]\n", + "\n" + ] + } + ], + "source": [ + "# But multidimensional arrays can be sliced with an extension of list slicing.\n", + "a = numpy.array([[ 0, 1, 2, 3, 4, 5],\n", + " [10, 11, 12, 13, 14, 15],\n", + " [20, 21, 22, 23, 24, 25],\n", + " [30, 31, 32, 33, 34, 35]])\n", + "for expr in \"a[2:, 1:]\", \"a[:, 1:-1]\", \"a[::2, ::2]\", \"a[:, 3]\":\n", + " print(expr, \" =\\n\", eval(expr), sep=\"\", end=\"\\n\\n\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "
\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a[mask] =\n", + "[5.5 7.7 9.9]\n", + "\n", + "a < 5 =\n", + "[ True True True True False False False False False]\n", + "\n", + "a[a < 5] =\n", + "[1.1 2.2 3.3 4.4]\n", + "\n" + ] + } + ], + "source": [ + "# Masking: using an array of booleans as a slice\n", + "\n", + "a = numpy.array([ 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n", + "mask = numpy.array([False, False, False, False, True, False, True, False, True])\n", + "# 5.5 7.7 9.9\n", + "\n", + "for expr in \"a[mask]\", \"a < 5\", \"a[a < 5]\":\n", + " print(expr, \" =\\n\", eval(expr), sep=\"\", end=\"\\n\\n\")" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dict_keys(['Type', 'Run', 'Event', 'E1', 'px1', 'py1', 'pz1', 'pt1', 'eta1', 'phi1', 'Q1', 'E2', 'px2', 'py2', 'pz2', 'pt2', 'eta2', 'phi2', 'Q2', 'M'])\n" + ] + } + ], + "source": [ + "# Five-minute exercise: plot masses with (1) opposite charges and\n", + "# (2) both muon abs(eta) < 1\n", + "arrays = uproot.open(\"data/Zmumu.root\")[\"events\"].arrays(namedecode=\"utf-8\")\n", + "print(arrays.keys())\n", + "for n in arrays:\n", + " exec(f\"{n} = arrays['{n}']\")\n", + "\n", + "import matplotlib.pyplot\n", + "matplotlib.pyplot.hist(M, bins=100);" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "q: [[1 -1] [1] [1 -1] ... [-1] [-1] [-1]]\n", + "\n", + "q > 0: [[True False] [True] [True False] ... [False] [False] [False]]\n", + "\n", + "E: [[54.7795 39.401695] [31.690445] [54.739788 47.488857] ... [62.39516] [174.20863] [69.55621]]\n", + "\n", + "E[q > 0]: [[54.7795] [31.690445] [54.739788] ... [] [] []]\n" + ] + } + ], + "source": [ + "# What if the boolean mask is jagged?\n", + "\n", + "E, px, py, pz, q = uproot.open(\"data/HZZ.root\")[\"events\"].arrays(\n", + " [\"Muon_E\", \"Muon_P[xyz]\", \"Muon_Charge\"], outputtype=tuple)\n", + "\n", + "print(f\"q: {q}\")\n", + "print(f\"\\nq > 0: {q > 0}\")\n", + "print(f\"\\nE: {E}\")\n", + "print(f\"\\nE[q > 0]: {E[q > 0]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x = [[1.1 2.2 3.3 4.4] [5.5 6.6] [7.7 8.8 9.9]]\n", + "\n", + "x[:2] = [[1.1 2.2 3.3 4.4] [5.5 6.6]]\n", + "\n", + "x[:, :2] = [[1.1 2.2] [5.5 6.6] [7.7 8.8]]\n", + "\n", + "x[[True, False, True]] = [[1.1 2.2 3.3 4.4] [7.7 8.8 9.9]]\n" + ] + } + ], + "source": [ + "# JaggedArray slicing does what Numpy does in the cases that overlap...\n", + "\n", + "x = awkward.fromiter([[1.1, 2.2, 3.3, 4.4], [5.5, 6.6], [7.7, 8.8, 9.9]])\n", + "print(f\"x = {x}\")\n", + "\n", + "# take the first two inner arrays\n", + "print(f\"\\nx[:2] = {x[:2]}\")\n", + "\n", + "# take the first two of each inner arrays\n", + "print(f\"\\nx[:, :2] = {x[:, :2]}\")\n", + "\n", + "# mask outer lists\n", + "print(f\"\\nx[[True, False, True]] = {x[[True, False, True]]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x[mask] = [[1.1 2.2 3.3] [6.6 7.7 8.8]]\n", + "\n", + "x[jmask] = [[1.1 3.3] [] [6.6 7.7 8.8]]\n" + ] + } + ], + "source": [ + "# ... and naturally extend it in the new cases.\n", + "\n", + "x = awkward.fromiter([[ 1.1, 2.2, 3.3], [ 4.4, 5.5], [ 6.6, 7.7, 8.8]])\n", + "mask = awkward.fromiter([ True, False, True ])\n", + "jmask = awkward.fromiter([[True, False, True], [False, False], [True, True, True]])\n", + "\n", + "print(f\"x[mask] = {x[mask]}\") # mask outer array\n", + "print(f\"\\nx[jmask] = {x[jmask]}\") # mask inner arrays" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "selects elements, possibly out of order\n", + "a[[3, 5, 0, 9]] = [3.3 5.5 0. 9.9]\n", + "\n", + "may use negative indexing, just like single integers and slices\n", + "a[[3, 5, 0, -1, -2, -3]] = [3.3 5.5 0. 9.9 8.8 7.7]\n", + "\n", + "may include repetitions(!)\n", + "a[[3, 5, 0, 9, 9, 9, 3, 5, 0]] = [3.3 5.5 0. 9.9 9.9 9.9 3.3 5.5 0. ]\n" + ] + } + ], + "source": [ + "# In Numpy, arrays of integers can also be used as indexes.\n", + "\n", + "a = numpy.array([0.0, 1.1, 2.2, 3.3, 4.4, 5.5, 6.6, 7.7, 8.8, 9.9])\n", + "\n", + "print(\"selects elements, possibly out of order\")\n", + "index = numpy.array([3, 5, 0, 9])\n", + "print(\"a[[3, 5, 0, 9]] =\", a[index])\n", + "\n", + "print(\"\\nmay use negative indexing, just like single integers and slices\")\n", + "index = numpy.array([3, 5, 0, -1, -2, -3])\n", + "print(\"a[[3, 5, 0, -1, -2, -3]] =\", a[index])\n", + "\n", + "print(\"\\nmay include repetitions(!)\")\n", + "index = numpy.array([3, 5, 0, 9, 9, 9, 3, 5, 0])\n", + "print(\"a[[3, 5, 0, 9, 9, 9, 3, 5, 0]] =\", a[index])" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "permutation:\n", + "[ 63 64 65 ... 136 135 133]\n", + "\n", + "\n", + "sorted eta1:\n", + "[-2.41404 -2.41404 -2.41404 ... 2.42365 2.42365 2.42365]\n", + "\n", + "\n", + "E1 sorted by eta1:\n", + "[ 6.03288979 6.03288979 6.03288979 ... 11.8752667 11.8752667\n", + " 11.8752667 ]\n" + ] + } + ], + "source": [ + "# What is integer indexing good for?\n", + "\n", + "permutation = eta1.argsort() # also try abs(eta1).argsort()\n", + "\n", + "print(f\"permutation:\\n{permutation}\")\n", + "\n", + "print(f\"\\n\\nsorted eta1:\\n{eta1[permutation]}\")\n", + "\n", + "print(f\"\\n\\nE1 sorted by eta1:\\n{E1[permutation]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "x[index] = [[7.7 8.8 9.9] [1.1 2.2 3.3 4.4] [1.1 2.2 3.3 4.4]]\n", + "\n", + "x[jindex] = [[1.1 1.1 4.4] [5.5 5.5 6.6] [7.7 7.7 9.9]]\n" + ] + } + ], + "source": [ + "# Integer indexes with JaggedArrays:\n", + "\n", + "x = awkward.fromiter([[ 1.1, 2.2, 3.3, 4.4], [5.5, 6.6], [7.7, 8.8, 9.9]])\n", + "index = awkward.fromiter([-1, 0, 0])\n", + "jindex = awkward.fromiter([[0, 0, -1], [0, 0, -1], [0, 0, -1]])\n", + "\n", + "print(f\"x[index] = {x[index]}\") # rearrange outer array\n", + "print(f\"\\nx[jindex] = {x[jindex]}\") # rearrange inner arrays" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "eta: [[-0.1500926 -0.2952755] [0.7538137] [0.20692922 1.0412954] ... [-1.2350469] [1.6653314] [1.062699]]\n", + "\n", + "maxabseta: [[1] [0] [1] ... [0] [0] [0]]\n", + "\n", + "eta[maxabseta]: [[-0.2952755] [0.7538137] [1.0412954] ... [-1.2350469] [1.6653314] [1.062699]]\n", + "\n", + "E[maxabseta]: [[39.401695] [31.690445] [47.488857] ... [62.39516] [174.20863] [69.55621]]\n" + ] + } + ], + "source": [ + "# Use case for jagged indexing: argmin and argmax\n", + "\n", + "E, px, py, pz, q = uproot.open(\"data/HZZ.root\")[\"events\"].arrays(\n", + " [\"Muon_E\", \"Muon_P[xyz]\", \"Muon_Charge\"], outputtype=tuple)\n", + "\n", + "eta = numpy.arctanh(pz / numpy.sqrt(px**2 + py**2 + pz**2))\n", + "print(f\"eta: {eta}\")\n", + "\n", + "maxabseta = abs(eta).argmax()\n", + "print(f\"\\nmaxabseta: {maxabseta}\")\n", + "\n", + "print(f\"\\neta[maxabseta]: {eta[maxabseta]}\") # eta with max |eta| per event\n", + "\n", + "print(f\"\\nE[maxabseta]: {E[maxabseta]}\") # energy with max |eta| per event" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "G∘F = [13 5 3 3 5 13 25 41 61 85]\n", + "g∘f = [13 5 3 3 5 13 25 41 61 85]\n" + ] + } + ], + "source": [ + "# Array indexing is useful in surprising ways because it's a basic mathematical\n", + "# operation: thinking of f[x] as a function, array indexing is function composition.\n", + "\n", + "# Take any two non-negative functions of integers...\n", + "def f(x):\n", + " return x**2 - 5*x + 10\n", + "def g(y):\n", + " return max(0, 2*y - 10) + 3\n", + "\n", + "# ... and sample them as arrays\n", + "F = numpy.array([f(i) for i in numpy.arange(10)]) # F is f at 10 elements\n", + "G = numpy.array([g(i) for i in numpy.arange(100)]) # G is g at enough elements to include max(f)\n", + "GoF = numpy.array([g(f(i)) for i in numpy.arange(10)]) # GoF is g∘f at 10 elements\n", + "\n", + "print(\"G\\u2218F =\", G[F]) # integer indexing\n", + "print(\"g\\u2218f =\", GoF) # array of the composed functions" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": {}, + "outputs": [], + "source": [ + "# Consider the following application:\n", + "\n", + "text = \"\"\"Four score and seven years ago our fathers brought forth on this continent, a new nation,\n", + "conceived in Liberty, and dedicated to the proposition that all men are created equal.\n", + "\n", + "Now we are engaged in a great civil war, testing whether that nation, or any nation so conceived and\n", + "so dedicated, can long endure. We are met on a great battle-field of that war. We have come to\n", + "dedicate a portion of that field, as a final resting place for those who here gave their lives that\n", + "that nation might live. It is altogether fitting and proper that we should do this.\n", + "\n", + "But, in a larger sense, we can not dedicate—we can not consecrate—we can not hallow—this ground. The\n", + "brave men, living and dead, who struggled here, have consecrated it, far above our poor power to add\n", + "or detract. The world will little note, nor long remember what we say here, but it can never forget\n", + "what they did here. It is for us the living, rather, to be dedicated here to the unfinished work which\n", + "they who fought here have thus far so nobly advanced. It is rather for us to be here dedicated to the\n", + "great task remaining before us—that from these honored dead we take increased devotion to that cause\n", + "for which they gave the last full measure of devotion—that we here highly resolve that these dead\n", + "shall not have died in vain—that this nation, under God, shall have a new birth of freedom—and that\n", + "government of the people, by the people, for the people, shall not perish from the earth.\"\"\"\n", + "\n", + "words = text.replace(\".\", \" \").replace(\",\", \" \").replace(\"-\", \" \").replace(\"\\u2014\", \" \").split()" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "len(words) = 272 \n", + "words[:25] =\n", + "['Four' 'score' 'and' 'seven' 'years' 'ago' 'our' 'fathers' 'brought'\n", + " 'forth' 'on' 'this' 'continent' 'a' 'new' 'nation' 'conceived' 'in'\n", + " 'Liberty' 'and' 'dedicated' 'to' 'the' 'proposition' 'that']\n", + "\n", + "len(dictionary) = 142 \n", + "dictionary[:25] =\n", + "['But' 'Four' 'God' 'It' 'Liberty' 'Now' 'The' 'We' 'a' 'above' 'add'\n", + " 'advanced' 'ago' 'all' 'altogether' 'and' 'any' 'are' 'as' 'battle' 'be'\n", + " 'before' 'birth' 'brave' 'brought']\n", + "\n", + "len(index) = 272 \n", + "index[:25] =\n", + "[ 1 109 15 111 141 12 94 49 24 55 92 124 34 8 86 84 31 69\n", + " 4 15 38 127 120 102 119]\n" + ] + } + ], + "source": [ + "# Dictionary encoding: for compression or textual analysis\n", + "\n", + "words = numpy.array(words)\n", + "dictionary, index = numpy.unique(words, return_inverse=True)\n", + "\n", + "print(\"len(words) =\", len(words), \"\\nwords[:25] =\\n\" + str(words[:25]))\n", + "print(\"\\nlen(dictionary) =\", len(dictionary), \"\\ndictionary[:25] =\\n\" + str(dictionary[:25]))\n", + "print(\"\\nlen(index) =\", len(index), \"\\nindex[:25] =\\n\" + str(index[:25]))" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array(['Four', 'score', 'and', 'seven', 'years', 'ago', 'our', 'fathers',\n", + " 'brought', 'forth', 'on', 'this', 'continent', 'a', 'new',\n", + " 'nation', 'conceived', 'in', 'Liberty', 'and', 'dedicated', 'to',\n", + " 'the', 'proposition', 'that', 'all', 'men', 'are', 'created',\n", + " 'equal', 'Now', 'we', 'are', 'engaged', 'in', 'a', 'great',\n", + " 'civil', 'war', 'testing', 'whether', 'that', 'nation', 'or',\n", + " 'any', 'nation', 'so', 'conceived', 'and', 'so', 'dedicated',\n", + " 'can', 'long', 'endure', 'We', 'are', 'met', 'on', 'a', 'great',\n", + " 'battle', 'field', 'of', 'that', 'war', 'We', 'have', 'come', 'to',\n", + " 'dedicate', 'a', 'portion', 'of', 'that', 'field', 'as', 'a',\n", + " 'final', 'resting', 'place', 'for', 'those', 'who', 'here', 'gave',\n", + " 'their', 'lives', 'that', 'that', 'nation', 'might', 'live', 'It',\n", + " 'is', 'altogether', 'fitting', 'and', 'proper', 'that', 'we',\n", + " 'should', 'do', 'this', 'But', 'in', 'a', 'larger', 'sense', 'we',\n", + " 'can', 'not', 'dedicate', 'we', 'can', 'not', 'consecrate', 'we',\n", + " 'can', 'not', 'hallow', 'this', 'ground', 'The', 'brave', 'men',\n", + " 'living', 'and', 'dead', 'who', 'struggled', 'here', 'have',\n", + " 'consecrated', 'it', 'far', 'above', 'our', 'poor', 'power', 'to',\n", + " 'add', 'or', 'detract', 'The', 'world', 'will', 'little', 'note',\n", + " 'nor', 'long', 'remember', 'what', 'we', 'say', 'here', 'but',\n", + " 'it', 'can', 'never', 'forget', 'what', 'they', 'did', 'here',\n", + " 'It', 'is', 'for', 'us', 'the', 'living', 'rather', 'to', 'be',\n", + " 'dedicated', 'here', 'to', 'the', 'unfinished', 'work', 'which',\n", + " 'they', 'who', 'fought', 'here', 'have', 'thus', 'far', 'so',\n", + " 'nobly', 'advanced', 'It', 'is', 'rather', 'for', 'us', 'to', 'be',\n", + " 'here', 'dedicated', 'to', 'the', 'great', 'task', 'remaining',\n", + " 'before', 'us', 'that', 'from', 'these', 'honored', 'dead', 'we',\n", + " 'take', 'increased', 'devotion', 'to', 'that', 'cause', 'for',\n", + " 'which', 'they', 'gave', 'the', 'last', 'full', 'measure', 'of',\n", + " 'devotion', 'that', 'we', 'here', 'highly', 'resolve', 'that',\n", + " 'these', 'dead', 'shall', 'not', 'have', 'died', 'in', 'vain',\n", + " 'that', 'this', 'nation', 'under', 'God', 'shall', 'have', 'a',\n", + " 'new', 'birth', 'of', 'freedom', 'and', 'that', 'government', 'of',\n", + " 'the', 'people', 'by', 'the', 'people', 'for', 'the', 'people',\n", + " 'shall', 'not', 'perish', 'from', 'the', 'earth'], dtype='
\n", + "\n", + "

Summary of slicing

\n", + "\n", + " * **if X is an integer:** selects individual elements;\n", + " * **if X is a slice:** selects a contiguous or regularly strided subrange (strides can be backward);\n", + " * **if X is a tuple** (any commas between square brackets): applies selections to multiple dimensions;\n", + " * **if X is a boolean array:** filters arbitrarily chosen elements (preserving order);\n", + " * **if X is an integer array:** applies a function of integers, arbitrarily chosen, in any order, and may have duplicates.\n", + "\n", + "
\n", + "\n", + "See [Numpy's advanced indexing documentation](https://docs.scipy.org/doc/numpy/reference/arrays.indexing.html#advanced-indexing) for more (e.g. slicing by a tuple of arrays)." + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




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Awkward arrays: extensions to Numpy for particle physics

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" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
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We've seen some examples of jagged arrays and how they extend Numpy.

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JaggedArray is one of the classes in awkward-array to provide the kinds of data structures needed by particle physics in array form.

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" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Welcome to JupyROOT 6.18/00\n" + ] + }, + { + "data": { + "text/plain": [ + "{'Muon_E': numpy.array([ object at 0x5a1921818080>,\n", + " object at 0x5a19218180a8>,\n", + " object at 0x5a19218180d0>,\n", + " ...,\n", + " object at 0x5a192182fa50>,\n", + " object at 0x5a192182fa78>,\n", + " object at 0x5a192182faa0>],\n", + " dtype=object)}" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# PyROOT's jagged array is an RVec object for every event (viewed through PyROOT).\n", + "\n", + "import ROOT\n", + "rdf = ROOT.RDataFrame(\"events\", \"data/HZZ.root\")\n", + "rdf.AsNumpy(columns=[\"Muon_E\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(array([54.7795 , 39.401695], dtype=float32),),\n", + " (array([31.690445], dtype=float32),),\n", + " (array([54.739788, 47.488857], dtype=float32),), ...,\n", + " (array([62.39516], dtype=float32),),\n", + " (array([174.20863], dtype=float32),),\n", + " (array([69.55621], dtype=float32),)], dtype=[('Muon_E', 'O')])" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# root_numpy's jagged array is a Numpy array for every event.\n", + "\n", + "import root_numpy\n", + "root_numpy.root2array(\"data/HZZ.root\", \"events\", branches=[\"Muon_E\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " layout \n", + "[ ()] JaggedArray(starts=layout[0], stops=layout[1], content=layout[2])\n", + "[ 0] ndarray(shape=2421, dtype=dtype('int64'))\n", + "[ 1] ndarray(shape=2421, dtype=dtype('int64'))\n", + "[ 2] ndarray(shape=3825, dtype=dtype('float32'))\n" + ] + }, + { + "data": { + "text/plain": [ + "(array([ 0, 2, 3, ..., 3822, 3823, 3824]),\n", + " array([ 2, 3, 5, ..., 3823, 3824, 3825]),\n", + " array([ 54.7795 , 39.401695, 31.690445, ..., 62.39516 , 174.20863 ,\n", + " 69.55621 ], dtype=float32))" + ] + }, + "execution_count": 41, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Awkward/uproot's jagged array consists of three arrays: starts/stops and content.\n", + "#\n", + "# The number of Python objects does not scale with the number of events.\n", + "\n", + "import uproot\n", + "array = uproot.open(\"data/HZZ.root\")[\"events\"].array(\"Muon_E\")\n", + "\n", + "print(array.layout)\n", + "\n", + "array.starts, array.stops, array.content" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "\n", + "[\n", + " [\n", + " 54.7795,\n", + " 39.4017\n", + " ],\n", + " [\n", + " 31.6904\n", + " ],\n", + " [\n", + " 54.7398,\n", + " 47.4889\n", + " ],\n", + " [\n", + " 413.46,\n", + " 344.042\n", + " ],\n", + " [\n", + " 120.864,\n", + " 51.2846\n", + " ],\n", + " [\n", + " 44.0933,\n", + " 52.8815\n", + " ],\n", + " [\n", + " 132.118,\n", + " 39.8392\n", + " ],\n", + " [\n", + " 160.195\n", + " ],\n", + " [\n", + " 112.1,\n", + " 21.3757\n", + " ],\n", + " [\n", + " 101.379,\n", + " 70.207\n", + " ],\n", + " ...\n", + " [\n", + " 66.3678,\n", + " 28.6503\n", + " ],\n", + " [\n", + " 160.12\n", + " ],\n", + " [\n", + " 46.6828\n", + " ],\n", + " [\n", + " 77.4331\n", + " ],\n", + " [\n", + " 157.226,\n", + " 116.125\n", + " ],\n", + " [\n", + " 74.603\n", + " ],\n", + " [\n", + " 165.204\n", + " ],\n", + " [\n", + " 62.3952\n", + " ],\n", + " [\n", + " 174.209\n", + " ],\n", + " [\n", + " 69.5562\n", + " ]\n", + "]" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Recent projects outside of particle physics (Arrow, Parquet, Zarr, XND, and\n", + "# TensorFlow) also have jagged arrays represented as contiguous flat arrays.\n", + "# \n", + "# Using a similar format lets us easily (and quickly!) convert between them.\n", + "\n", + "awkward.toparquet(\"tmp.parquet\", array)\n", + "awkward.toarrow(array)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

In particular,

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TypeRunEventE1px1py1pz1pt1eta1phi1Q1E2px2py2pz2pt2eta2phi2Q2M
entry
0b'GT'1480311050700882.201866-41.19528817.433244-68.96496244.7322-1.2176902.741260160.62187534.144437-16.119525-47.42698438.8311-1.051390-0.440873-182.462692
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2304 rows × 20 columns

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\n", + "2303 32.3997 -1.570440 0.037027 1 170.583132 -68.794136 -26.398400 \n", + "\n", + " pz2 pt2 eta2 phi2 Q2 M \n", + "entry \n", + "0 -47.426984 38.8311 -1.051390 -0.440873 -1 82.462692 \n", + "1 -68.964962 44.7322 -1.217690 2.741260 1 83.626204 \n", + "2 -68.447255 44.7322 -1.217690 2.741260 1 83.308465 \n", + "3 -68.447255 44.7322 -1.217690 2.741260 1 82.149373 \n", + "4 44.513955 21.8913 1.444340 -2.707650 -1 90.469123 \n", + "5 -31.689894 27.2981 -0.990688 0.583351 1 89.757663 \n", + "6 -31.702509 27.2981 -0.990688 0.583351 1 89.773943 \n", + "7 -31.702509 27.2981 -0.990688 0.583351 1 90.485532 \n", + "8 -49.502056 72.7634 -0.637934 -0.793162 -1 91.773701 \n", + "9 -108.150553 77.0336 -1.140270 0.393582 1 91.948820 \n", + "10 -107.565069 77.0336 -1.140270 0.393582 1 91.704015 \n", + "11 -107.565069 77.0336 -1.140270 0.393582 1 91.529367 \n", + "12 -22.411636 40.6637 -0.525298 2.873290 1 94.648246 \n", + "13 19.545333 44.5173 0.426044 -0.070413 -1 94.530698 \n", + "14 19.573817 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+ "output_type": "execute_result" + } + ], + "source": [ + "# Pandas is a data analysis environment built around in-memory tables.\n", + "# \n", + "# \"Numpy with an index\" ... \"Programmatic Excel\" ... \"SQL with an ordering\"\n", + "\n", + "uproot.open(\"data/Zmumu.root\")[\"events\"].pandas.df()" + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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..................
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3825 rows × 4 columns

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"execution_count": 50, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# One-per-event data must be duplicated for each particle, and are inaccessible\n", + "# when there are no particles.\n", + "\n", + "# (Switch between flatten=False and flatten=True.)\n", + "uproot.open(\"data/HZZ.root\")[\"events\"].pandas.df([\"MET_*\", \"Jet_P[xyz]\"],\n", + " flatten=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": {}, + "outputs": [ + { + "ename": "ValueError", + "evalue": "cannot use flatten=True on branches with different jagged structure, such as electrons and muons (different, variable number of each per event); either explicitly select compatible branches, such as [\"MET_*\", \"Muon_*\"] (scalar and variable per event is okay), or set flatten=False", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;31m# (Switch between flatten=False and flatten=True.)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 4\u001b[0m uproot.open(\"data/HZZ.root\")[\"events\"].pandas.df([\"Muon_P[xyz]\", \"Jet_P[xyz]\"],\n\u001b[0;32m----> 5\u001b[0;31m flatten=True)\n\u001b[0m", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/uproot-3.8.0-py3.7.egg/uproot/_connect/_pandas.py\u001b[0m in \u001b[0;36mdf\u001b[0;34m(self, branches, namedecode, entrystart, entrystop, flatten, flatname, awkwardlib, cache, basketcache, keycache, executor, blocking)\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbranches\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnamedecode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"utf-8\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystart\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatten\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mawkwardlib\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbasketcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeycache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecutor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 31\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 32\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_tree\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marrays\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbranches\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbranches\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutputtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDataFrame\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnamedecode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mnamedecode\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystart\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mentrystart\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mentrystop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatten\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mflatten\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mflatname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mawkwardlib\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mawkwardlib\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcache\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbasketcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbasketcache\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeycache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mkeycache\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecutor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mexecutor\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mblocking\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 33\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 34\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0miterate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbranches\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrysteps\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnamedecode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"utf-8\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystart\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatten\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatname\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mawkwardlib\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbasketcache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeycache\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexecutor\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/uproot-3.8.0-py3.7.egg/uproot/tree.py\u001b[0m in \u001b[0;36marrays\u001b[0;34m(self, branches, outputtype, namedecode, entrystart, entrystop, flatten, flatname, awkwardlib, cache, basketcache, keycache, executor, blocking)\u001b[0m\n\u001b[1;32m 538\u001b[0m \u001b[0;31m# if blocking, return the result of that function; otherwise, the function itself\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 539\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 540\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 541\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 542\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mwait\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/uproot-3.8.0-py3.7.egg/uproot/tree.py\u001b[0m in \u001b[0;36mwait\u001b[0;34m()\u001b[0m\n\u001b[1;32m 522\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0muproot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_connect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pandas\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 523\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwait\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 524\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0muproot\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_connect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_pandas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfutures2df\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfutures\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutputtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystart\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mentrystop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatten\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflatname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mawkward\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 525\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 526\u001b[0m \u001b[0;32melif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0missubclass\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutputtype\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdict\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/uproot-3.8.0-py3.7.egg/uproot/_connect/_pandas.py\u001b[0m in \u001b[0;36mfutures2df\u001b[0;34m(futures, outputtype, entrystart, entrystop, flatten, flatname, awkward)\u001b[0m\n\u001b[1;32m 125\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 126\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mstarts\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstarts\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mawkward\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnumpy\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray_equal\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstarts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstarts\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 127\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"cannot use flatten=True on branches with different jagged structure, such as electrons and muons (different, variable number of each per event); either explicitly select compatible branches, such as [\\\"MET_*\\\", \\\"Muon_*\\\"] (scalar and variable per event is okay), or set flatten=False\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 128\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 129\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstarts\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mValueError\u001b[0m: cannot use flatten=True on branches with different jagged structure, such as electrons and muons (different, variable number of each per event); either explicitly select compatible branches, such as [\"MET_*\", \"Muon_*\"] (scalar and variable per event is okay), or set flatten=False" + ] + } + ], + "source": [ + "# And there isn't a way to deal with different jaggedness in the same table.\n", + "\n", + "# (Switch between flatten=False and flatten=True.)\n", + "uproot.open(\"data/HZZ.root\")[\"events\"].pandas.df([\"Muon_P[xyz]\", \"Jet_P[xyz]\"],\n", + " flatten=True)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "
\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'MET': TVector2(5.9128, 2.5636),\n", + " 'muonp4': [TLorentzVector(-52.899, -11.655, -8.1608, 54.779),\n", + " TLorentzVector(37.738, 0.69347, -11.308, 39.402)],\n", + " 'muonq': [1, -1],\n", + " 'jetp4': []},\n", + " {'MET': TVector2(24.765, -16.349),\n", + " 'muonp4': [TLorentzVector(-0.81646, -24.404, 20.2, 31.69)],\n", + " 'muonq': [1],\n", + " 'jetp4': [TLorentzVector(-38.875, 19.863, -0.89494, 44.137)]},\n", + " {'MET': TVector2(-25.785, 16.237),\n", + " 'muonp4': [TLorentzVector(48.988, -21.723, 11.168, 54.74),\n", + " TLorentzVector(0.82757, 29.801, 36.965, 47.489)],\n", + " 'muonq': [1, -1],\n", + " 'jetp4': []},\n", + " {'MET': TVector2(8.6199, -22.787),\n", + " 'muonp4': [TLorentzVector(22.088, -85.835, 403.85, 413.46),\n", + " TLorentzVector(76.692, -13.956, 335.09, 344.04)],\n", + " 'muonq': [-1, 1],\n", + " 'jetp4': [TLorentzVector(-71.695, 93.572, 196.3, 230.35),\n", + " TLorentzVector(36.606, 21.839, 91.666, 101.36),\n", + " TLorentzVector(-28.866, 9.3207, 51.243, 60.084)]},\n", + " {'MET': TVector2(5.3931, -1.3101),\n", + " 'muonp4': [TLorentzVector(45.171, 67.249, -89.696, 120.86),\n", + " TLorentzVector(39.751, 25.404, 20.115, 51.285)],\n", + " 'muonq': [-1, 1],\n", + " 'jetp4': [TLorentzVector(3.8802, -75.234, -359.6, 367.59),\n", + " TLorentzVector(4.9796, -39.232, 68.457, 79.242)]},\n", + " {'MET': TVector2(-3.7595, -19.417),\n", + " 'muonp4': [TLorentzVector(9.2281, 40.554, -14.642, 44.093),\n", + " TLorentzVector(-5.7937, -30.295, 42.954, 52.882)],\n", + " 'muonq': [1, -1],\n", + " 'jetp4': [TLorentzVector(-46.328, 27.259, 51.401, 74.443),\n", + " TLorentzVector(27.738, -14.542, 5.2849, 32.553)]},\n", + " {'MET': TVector2(23.962, -9.0492),\n", + " 'muonp4': [TLorentzVector(12.539, -42.549, -124.45, 132.12),\n", + " TLorentzVector(29.542, -4.4455, -26.357, 39.839)],\n", + " 'muonq': [-1, -1],\n", + " 'jetp4': [TLorentzVector(-82.066, 47.652, -262.34, 279.42)]},\n", + " {'MET': TVector2(-57.533, -20.488),\n", + " 'muonp4': [TLorentzVector(34.884, -15.983, 155.53, 160.19)],\n", + " 'muonq': [1],\n", + " 'jetp4': [TLorentzVector(27.92, -32.921, 231, 235.11)]},\n", + " {'MET': TVector2(42.416, -94.351),\n", + " 'muonp4': [TLorentzVector(-53.167, 92.03, 35.639, 112.1),\n", + " TLorentzVector(11.492, -4.4174, -17.474, 21.376)],\n", + " 'muonq': [-1, 1],\n", + " 'jetp4': []},\n", + " {'MET': TVector2(-1.9145, -23.963),\n", + " 'muonp4': [TLorentzVector(-67.015, 53.159, 54.413, 101.38),\n", + " TLorentzVector(-18.119, -35.106, 58.037, 70.207)],\n", + " 'muonq': [1, -1],\n", + " 'jetp4': [TLorentzVector(37.886, -8.8927, -69.188, 79.851)]}]" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Awkward-array is designed to handle arbitrary data structures in a way that\n", + "# fits both ROOT and Arrow/Parquet.\n", + "\n", + "array = awkward.Table(uproot.open(\"data/HZZ-objects.root\")[\"events\"].arrays(\n", + " [\"MET\", \"muonp4\", \"muonq\", \"jetp4\"], namedecode=\"utf-8\"))\n", + "\n", + "array[:10].tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": 53, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "pyarrow.Table\n", + "MET: struct< fBits: uint64, fUniqueID: uint64, fX: double, fY: double>\n", + " child 0, fBits: uint64\n", + " child 1, fUniqueID: uint64\n", + " child 2, fX: double\n", + " child 3, fY: double\n", + "muonp4: list>\n", + " child 0, item: struct< fBits: uint64, fUniqueID: uint64, fBits2: uint64, fUniqueID2: uint64, fX: double, fY: double, fZ: double, fE: double>\n", + " child 0, fBits: uint64\n", + " child 1, fUniqueID: uint64\n", + " child 2, fBits2: uint64\n", + " child 3, fUniqueID2: uint64\n", + " child 4, fX: double\n", + " child 5, fY: double\n", + " child 6, fZ: double\n", + " child 7, fE: double\n", + "muonq: list\n", + " child 0, item: int32\n", + "jetp4: list>\n", + " child 0, item: struct< fBits: uint64, fUniqueID: uint64, fBits2: uint64, fUniqueID2: uint64, fX: double, fY: double, fZ: double, fE: double>\n", + " child 0, fBits: uint64\n", + " child 1, fUniqueID: uint64\n", + " child 2, fBits2: uint64\n", + " child 3, fUniqueID2: uint64\n", + " child 4, fX: double\n", + " child 5, fY: double\n", + " child 6, fZ: double\n", + " child 7, fE: double" + ] + }, + "execution_count": 53, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# ROOT has objects like TLorentzVector, but they translate to generic Tables\n", + "# in Arrow/Parquet.\n", + "\n", + "awkward.toarrow(array)\n", + "# awkward.fromarrow(awkward.toarrow(array))[:10].tolist()" + ] + }, + { + "cell_type": "code", + "execution_count": 54, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "new event TVector2(5.9128, 2.5636)\n", + " muon TLorentzVector(-52.899, -11.655, -8.1608, 54.779)\n", + " muon TLorentzVector(37.738, 0.69347, -11.308, 39.402)\n", + "new event TVector2(24.765, -16.349)\n", + " muon TLorentzVector(-0.81646, -24.404, 20.2, 31.69)\n", + " jet TLorentzVector(-38.875, 19.863, -0.89494, 44.137)\n", + "new event TVector2(-25.785, 16.237)\n", + " muon TLorentzVector(48.988, -21.723, 11.168, 54.74)\n", + " muon TLorentzVector(0.82757, 29.801, 36.965, 47.489)\n", + "new event TVector2(8.6199, -22.787)\n", + " muon TLorentzVector(22.088, -85.835, 403.85, 413.46)\n", + " muon TLorentzVector(76.692, -13.956, 335.09, 344.04)\n", + " jet TLorentzVector(-71.695, 93.572, 196.3, 230.35)\n", + " jet TLorentzVector(36.606, 21.839, 91.666, 101.36)\n", + " jet TLorentzVector(-28.866, 9.3207, 51.243, 60.084)\n", + "new event TVector2(5.3931, -1.3101)\n", + " muon TLorentzVector(45.171, 67.249, -89.696, 120.86)\n", + " muon TLorentzVector(39.751, 25.404, 20.115, 51.285)\n", + " jet TLorentzVector(3.8802, -75.234, -359.6, 367.59)\n", + " jet TLorentzVector(4.9796, -39.232, 68.457, 79.242)\n", + "new event TVector2(-3.7595, -19.417)\n", + " muon TLorentzVector(9.2281, 40.554, -14.642, 44.093)\n", + " muon TLorentzVector(-5.7937, -30.295, 42.954, 52.882)\n", + " jet TLorentzVector(-46.328, 27.259, 51.401, 74.443)\n", + " jet TLorentzVector(27.738, -14.542, 5.2849, 32.553)\n", + "new event TVector2(23.962, -9.0492)\n", + " muon TLorentzVector(12.539, -42.549, -124.45, 132.12)\n", + " muon TLorentzVector(29.542, -4.4455, -26.357, 39.839)\n", + " jet TLorentzVector(-82.066, 47.652, -262.34, 279.42)\n", + "new event TVector2(-57.533, -20.488)\n", + " muon TLorentzVector(34.884, -15.983, 155.53, 160.19)\n", + " jet TLorentzVector(27.92, -32.921, 231, 235.11)\n", + "new event TVector2(42.416, -94.351)\n", + " muon TLorentzVector(-53.167, 92.03, 35.639, 112.1)\n", + " muon TLorentzVector(11.492, -4.4174, -17.474, 21.376)\n", + "new event TVector2(-1.9145, -23.963)\n", + " muon TLorentzVector(-67.015, 53.159, 54.413, 101.38)\n", + " muon TLorentzVector(-18.119, -35.106, 58.037, 70.207)\n", + " jet TLorentzVector(37.886, -8.8927, -69.188, 79.851)\n", + "new event TVector2(19.71, 4.6455)\n", + " muon TLorentzVector(15.983, 49.114, 118.15, 128.94)\n", + " muon TLorentzVector(34.684, -30.967, 193.68, 199.18)\n", + " jet TLorentzVector(-54.198, 23.507, 160.17, 171.15)\n", + " jet TLorentzVector(3.6567, -50.272, 142.22, 151.16)\n", + "new event TVector2(-35.538, -14.754)\n", + " muon TLorentzVector(-70.512, -27.018, -15.325, 77.05)\n", + " muon TLorentzVector(-38.029, 33.25, -70.318, 86.582)\n" + ] + } + ], + "source": [ + "# You can iterate over these objects in for loops, like PyROOT...\n", + "\n", + "for i, event in enumerate(array):\n", + " print(\"new event\", event.MET)\n", + " for muon in event.muonp4:\n", + " print(\" muon\", muon)\n", + " for jet in event.jetp4:\n", + " print(\" jet \", jet)\n", + " if i > 10:\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": 55, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([90.22779777, 74.74654928, 89.75736376, ..., 92.06495256,\n", + " 85.44384208, 75.96066262])" + ] + }, + "execution_count": 55, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# ... but if you need to scale up, use array-at-a-time operations.\n", + "\n", + "mu1 = array.muonp4[array.muonp4.counts >= 2, 0]\n", + "mu2 = array.muonp4[array.muonp4.counts >= 2, 1]\n", + "(mu1 + mu2).mass" + ] + }, + { + "cell_type": "code", + "execution_count": 56, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 56, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The \"combinatorics\" we need for particle physics requires a few new operations.\n", + "\n", + "# Take any two muons from events that have them, not necessarily the first two.\n", + "pairs = array.muonp4.choose(2)\n", + "pairs" + ] + }, + { + "cell_type": "code", + "execution_count": 57, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 57, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get the first and second element of each pair.\n", + "\n", + "first, second = pairs.unzip()\n", + "first, second" + ] + }, + { + "cell_type": "code", + "execution_count": 58, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# Compute the mass and plot.\n", + "# \n", + "# (\"flatten\" because Matplotlib needs a flat array, not a jagged array.)\n", + "\n", + "matplotlib.pyplot.hist((first + second).mass.flatten(), bins=100, range=(0, 150));" + ] + }, + { + "cell_type": "code", + "execution_count": 59, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 59, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Five-minute exercise: plot masses with (1) opposite charges and\n", + "# (2) both muon abs(eta) < 1\n", + "# This time, it's jagged.\n", + "\n", + "array.muonq, array.muonp4.eta\n", + "\n", + "# first, second = array.muonp4.choose(2).unzip()\n", + "# matplotlib.pyplot.hist((first + second).mass.flatten(), bins=100, range=(0, 150));" + ] + }, + { + "cell_type": "code", + "execution_count": 60, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(,\n", + " )" + ] + }, + "execution_count": 60, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Step 1: jet-muon pairs with a doubly-jagged structure\n", + "# so we have one of these for every jet\n", + "jets, muons = array.jetp4.cross(array.muonp4, nested=True).unzip()\n", + "jets, muons" + ] + }, + { + "cell_type": "code", + "execution_count": 61, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 61, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Step 2: ΔR between each jet and muon\n", + "distance = jets.delta_r(muons)\n", + "distance" + ] + }, + { + "cell_type": "code", + "execution_count": 62, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mask: [[] [False] [] ... [False] [False False] []]\n", + "index: [[] [[0]] [] ... [[0]] [[0] [0]] []]\n" + ] + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Step 3: mask those that have any within ΔR < 1.0\n", + "mask = (distance < 1.0).any()\n", + "print(f\"mask: {mask}\")\n", + "\n", + "# Step 4: index of the closest one\n", + "index = distance.argmin()\n", + "print(f\"index: {index}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 63, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 63, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Step 5: select those jets\n", + "jets_near_muons = jets[index][mask]\n", + "jets_near_muons\n", + "\n", + "# (Use this to see just the events that have one.)\n", + "# jets_near_muons[jets_near_muons.counts > 0]" + ] + }, + { + "cell_type": "code", + "execution_count": 64, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[TLorentzVector(-71.695, 93.572, 196.3, 230.35) TLorentzVector(36.606, 21.839, 91.666, 101.36) TLorentzVector(-28.866, 9.3207, 51.243, 60.084)]\n", + "[TLorentzVector(36.606, 21.839, 91.666, 101.36)]\n", + "\n", + "[TLorentzVector(27.92, -32.921, 231, 235.11)]\n", + "[TLorentzVector(27.92, -32.921, 231, 235.11)]\n", + "\n", + "[TLorentzVector(-54.198, 23.507, 160.17, 171.15) TLorentzVector(3.6567, -50.272, 142.22, 151.16)]\n", + "[TLorentzVector(3.6567, -50.272, 142.22, 151.16)]\n", + "\n", + "[TLorentzVector(31.497, -17.628, -62.282, 72.257)]\n", + "[TLorentzVector(31.497, -17.628, -62.282, 72.257)]\n", + "\n", + "[TLorentzVector(21.356, 62.524, -5.7835, 67.663) TLorentzVector(-27.65, 44.137, -0.13917, 52.654)]\n", + "[TLorentzVector(-27.65, 44.137, -0.13917, 52.654)]\n", + "\n", + "[TLorentzVector(-40.948, -31.722, -80.552, 96.232) TLorentzVector(-16.573, -29.426, 150.39, 154.29)]\n", + "[TLorentzVector(-40.948, -31.722, -80.552, 96.232)]\n", + "\n", + "[TLorentzVector(27.171, 80.23, -510.04, 517.28) TLorentzVector(11.629, -75.596, -41.266, 87.971)]\n", + "[TLorentzVector(11.629, -75.596, -41.266, 87.971)]\n", + "\n", + "[TLorentzVector(64.824, -62.463, 160.93, 185.03)]\n", + "[TLorentzVector(64.824, -62.463, 160.93, 185.03)]\n", + "\n", + "[TLorentzVector(68.463, 212.86, -224.87, 318.17) TLorentzVector(38.278, -103.76, -93.173, 145.77)]\n", + "[TLorentzVector(38.278, -103.76, -93.173, 145.77)]\n", + "\n", + "[TLorentzVector(125.64, -49.116, 24.744, 137.96) TLorentzVector(-46.494, -32.776, 69.935, 90.52) TLorentzVector(-46.887, 19.261, -111.82, 123.02) TLorentzVector(-26.125, 39.972, -76.258, 90.419)]\n", + "[TLorentzVector(125.64, -49.116, 24.744, 137.96)]\n", + "\n", + "[TLorentzVector(-53.67, -17.336, -50.13, 75.848) TLorentzVector(12.165, 48.596, -128.01, 138.11) TLorentzVector(11.551, 29.967, -6.6644, 33.493)]\n", + "[TLorentzVector(11.551, 29.967, -6.6644, 33.493)]\n", + "\n", + "[TLorentzVector(-105.25, -20.333, -81.811, 135.79)]\n", + "[TLorentzVector(-105.25, -20.333, -81.811, 135.79)]\n", + "\n", + "[TLorentzVector(-6.6179, -45.551, -15.031, 50.115) TLorentzVector(-8.2169, 35.941, 75.798, 84.534)]\n", + "[TLorentzVector(-8.2169, 35.941, 75.798, 84.534)]\n", + "\n" + ] + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Choice A: we want just those jets. Need to flatten the inner arrays so that\n", + "# the result is singly jagged, like the original jets.\n", + "\n", + "array[\"jets_near_muons\"] = jets_near_muons.flatten(axis=1)\n", + "\n", + "for i, event in enumerate(array):\n", + " if mask[i].any():\n", + " print(event.jetp4)\n", + " print(event.jets_near_muons)\n", + " print()\n", + " if i > 100:\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": 65, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[TLorentzVector(-71.695, 93.572, 196.3, 230.35) TLorentzVector(36.606, 21.839, 91.666, 101.36) TLorentzVector(-28.866, 9.3207, 51.243, 60.084)]\n", + "[None TLorentzVector(76.692, -13.956, 335.09, 344.04) None]\n", + "[None 0.9723260392266933 None]\n", + "\n", + "[TLorentzVector(27.92, -32.921, 231, 235.11)]\n", + "[TLorentzVector(34.884, -15.983, 155.53, 160.19)]\n", + "[0.5151781676187408]\n", + "\n", + "[TLorentzVector(-54.198, 23.507, 160.17, 171.15) TLorentzVector(3.6567, -50.272, 142.22, 151.16)]\n", + "[None TLorentzVector(34.684, -30.967, 193.68, 199.18)]\n", + "[None 0.8552674867146833]\n", + "\n", + "[TLorentzVector(31.497, -17.628, -62.282, 72.257)]\n", + "[TLorentzVector(22.55, -3.6572, -86.198, 89.174)]\n", + "[0.8043891928764596]\n", + "\n", + "[TLorentzVector(21.356, 62.524, -5.7835, 67.663) TLorentzVector(-27.65, 44.137, -0.13917, 52.654)]\n", + "[None TLorentzVector(-33.282, 6.8754, 14.864, 37.093)]\n", + "[None 0.9134786608897545]\n", + "\n", + "[TLorentzVector(-40.948, -31.722, -80.552, 96.232) TLorentzVector(-16.573, -29.426, 150.39, 154.29)]\n", + "[TLorentzVector(-61.252, -13.58, -104.55, 121.93) None]\n", + "[0.44482740336138665 None]\n", + "\n", + "[TLorentzVector(27.171, 80.23, -510.04, 517.28) TLorentzVector(11.629, -75.596, -41.266, 87.971)]\n", + "[None TLorentzVector(8.994, -24.182, -48.572, 54.999)]\n", + "[None 0.8969664161548911]\n", + "\n", + "[TLorentzVector(64.824, -62.463, 160.93, 185.03)]\n", + "[TLorentzVector(-5.7951, -32.959, 55.086, 64.454)]\n", + "[0.9805841829511657]\n", + "\n", + "[TLorentzVector(68.463, 212.86, -224.87, 318.17) TLorentzVector(38.278, -103.76, -93.173, 145.77)]\n", + "[None TLorentzVector(7.7383, -32.497, -1.8239, 33.456)]\n", + "[None 0.7209285627334554]\n", + "\n", + "[TLorentzVector(125.64, -49.116, 24.744, 137.96) TLorentzVector(-46.494, -32.776, 69.935, 90.52) TLorentzVector(-46.887, 19.261, -111.82, 123.02) TLorentzVector(-26.125, 39.972, -76.258, 90.419)]\n", + "[TLorentzVector(28.162, 8.2601, 28.208, 40.707) None None None]\n", + "[0.9399263291374779 None None None]\n", + "\n", + "[TLorentzVector(-53.67, -17.336, -50.13, 75.848) TLorentzVector(12.165, 48.596, -128.01, 138.11) TLorentzVector(11.551, 29.967, -6.6644, 33.493)]\n", + "[None None TLorentzVector(37.372, 25.221, 3.7339, 45.24)]\n", + "[None None 0.6742104078323463]\n", + "\n", + "[TLorentzVector(-105.25, -20.333, -81.811, 135.79)]\n", + "[TLorentzVector(-63.821, -40.861, -112.77, 135.87)]\n", + "[0.6149240480957036]\n", + "\n", + "[TLorentzVector(-6.6179, -45.551, -15.031, 50.115) TLorentzVector(-8.2169, 35.941, 75.798, 84.534)]\n", + "[None TLorentzVector(9.1534, 32.494, 25.071, 42.049)]\n", + "[None 0.9270685739048289]\n", + "\n" + ] + } + ], + "source": [ + "# Advanced combinatorics: muons that are close to jets\n", + "\n", + "# Choice B: we want to link to the relevant muons, with the ΔR distance\n", + "\n", + "array[\"nearest_muon\"] = muons[index].pad(1, axis=1).flatten(axis=1)\n", + "array[\"distance\"] = distance[index].pad(1, axis=1).flatten(axis=1)\n", + "\n", + "# Set link to None if nearest_muon or distance doesn't pass the cut\n", + "array.nearest_muon.content.mask |= ~mask.flatten()\n", + "array.distance.content.mask |= ~mask.flatten()\n", + "\n", + "for i, event in enumerate(array):\n", + " if mask[i].any():\n", + " print(event.jetp4)\n", + " print(event.nearest_muon)\n", + " print(event.distance)\n", + " print()\n", + " if i > 100:\n", + " break" + ] + }, + { + "cell_type": "code", + "execution_count": 66, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 66, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Apologies for using functions that have not yet been introduced: just as with\n", + "# Numpy, working with awkward arrays means learning a vocabulary of single-step\n", + "# functions and putting them together.\n", + "\n", + "a = awkward.fromiter([[1.1, 2.2, 3.3], [], [4.4, 5.5], [6.6, 7.7, 8.8, 9.9]])\n", + "\n", + "# \"pad\" means fill inner arrays with None until it has at least N elements.\n", + "a.pad(3)" + ] + }, + { + "cell_type": "code", + "execution_count": 67, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[ 1.1, 2.2, 3.3],\n", + " [999. , 999. , 999. ],\n", + " [ 4.4, 5.5, 999. ],\n", + " [ 6.6, 7.7, 8.8]])" + ] + }, + "execution_count": 67, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Apologies for using functions that have not yet been introduced: just as with\n", + "# Numpy, working with awkward arrays means learning a vocabulary of single-step\n", + "# functions and putting them together.\n", + "\n", + "a = awkward.fromiter([[1.1, 2.2, 3.3], [], [4.4, 5.5], [6.6, 7.7, 8.8, 9.9]])\n", + "\n", + "# You can use it with \"fillna\" and \"regular\" to make a regular Numpy array.\n", + "a.pad(3, clip=True).fillna(999).regular()" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 68, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Apologies for using functions that have not yet been introduced: just as with\n", + "# Numpy, working with awkward arrays means learning a vocabulary of single-step\n", + "# functions and putting them together.\n", + "\n", + "a = awkward.fromiter([[1.1, 2.2, 3.3], [], [4.4, 5.5], [6.6, 7.7, 8.8, 9.9]])\n", + "\n", + "# In the previous example, we used it with argmax, which makes inner arrays of\n", + "# length 0 or 1, to ensure that they're always length 1.\n", + "a.argmax().pad(1)" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Apologies for using functions that have not yet been introduced: just as with\n", + "# Numpy, working with awkward arrays means learning a vocabulary of single-step\n", + "# functions and putting them together.\n", + "\n", + "a = awkward.fromiter([[1.1, 2.2, 3.3], [], [4.4, 5.5], [6.6, 7.7, 8.8, 9.9]])\n", + "\n", + "# Once we've done that, we don't need the inner structure anymore and can flatten\n", + "# it to get a non-jagged array.\n", + "a.argmax().pad(1).flatten()" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Apologies for using functions that have not yet been introduced: just as with\n", + "# Numpy, working with awkward arrays means learning a vocabulary of single-step\n", + "# functions and putting them together.\n", + "\n", + "a = awkward.fromiter([[[1.1, 2.2, 3.3]], [[], [4.4, 5.5]], [[6.6, 7.7, 8.8, 9.9]]])\n", + "\n", + "# But all of that happened inside a doubly-jagged array, in which we wanted to\n", + "# collapse the inner dimension, so we used axis=1. (Same meaning as in Numpy.)\n", + "a.argmax().pad(1, axis=1).flatten(axis=1)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Although we've only talked about variable-length lists, objects, and None, awkward-array types form a complete type system:

\n", + "\n", + "
    \n", + "
  • Primitive types: numbers, booleans, and fixed-size binary blobs via Numpy,\n", + "
  • Lists: variable-length lists via JaggedArray,\n", + "
  • Union (sum) types: heterogeneous lists via UnionArray,\n", + "
  • Record (product) types: objects (Table), implicitly in our previous examples,\n", + "
  • Pointers: cross-references and circular references via IndexedArray,\n", + "
  • Non-contiguous data: via ChunkedArray,\n", + "
  • Lazy data: via VirtualArray.\n", + "
\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "metadata": {}, + "outputs": [], + "source": [ + "# Just to demonstrate, let's make a tree...\n", + "\n", + "tree = awkward.fromiter([\n", + " {\"value\": 1.23, \"left\": 1, \"right\": 2}, # node 0\n", + " {\"value\": 3.21, \"left\": 3, \"right\": 4}, # node 1\n", + " {\"value\": 9.99, \"left\": 5, \"right\": 6}, # node 2\n", + " {\"value\": 3.14, \"left\": 7, \"right\": None}, # node 3\n", + " {\"value\": 2.71, \"left\": None, \"right\": 8}, # node 4\n", + " {\"value\": 5.55, \"left\": None, \"right\": None}, # node 5\n", + " {\"value\": 8.00, \"left\": None, \"right\": None}, # node 6\n", + " {\"value\": 9.00, \"left\": None, \"right\": None}, # node 7\n", + " {\"value\": 0.00, \"left\": None, \"right\": None}, # node 8\n", + "])\n", + "\n", + "left = tree.contents[\"left\"].content\n", + "right = tree.contents[\"right\"].content\n", + "left[(left < 0) | (left > 8)] = 0\n", + "right[(right < 0) | (right > 8)] = 0\n", + "\n", + "tree.contents[\"left\"].content = awkward.IndexedArray(left, tree)\n", + "tree.contents[\"right\"].content = awkward.IndexedArray(right, tree)" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Physical layout:\n", + "------------------------------------------------------------------\n", + "(0, 0) [False False False False True True True True True]\n", + "(0, 1, 0) [1 3 5 7 1 0 1 2 3]\n", + "(1, 0) [False False False True False True True True True]\n", + "(1, 1, 0) [2 4 6 0 8 0 0 0 1]\n", + "(2,) [1.23 3.21 9.99 3.14 2.71 5.55 8. 9. 0. ]\n", + "\n", + "Logical meaning:\n", + "------------------------------------------------------------------\n", + "{\n", + " \"left\": {\n", + " \"left\": {\n", + " \"left\": {\n", + " \"left\": null,\n", + " \"right\": null,\n", + " \"value\": 9.0\n", + " },\n", + " \"right\": null,\n", + " \"value\": 3.14\n", + " },\n", + " \"right\": {\n", + " \"left\": null,\n", + " \"right\": {\n", + " \"left\": null,\n", + " \"right\": null,\n", + " \"value\": 0.0\n", + " },\n", + " \"value\": 2.71\n", + " },\n", + " \"value\": 3.21\n", + " },\n", + " \"right\": {\n", + " \"left\": {\n", + " \"left\": null,\n", + " \"right\": null,\n", + " \"value\": 5.55\n", + " },\n", + " \"right\": {\n", + " \"left\": null,\n", + " \"right\": null,\n", + " \"value\": 8.0\n", + " },\n", + " \"value\": 9.99\n", + " },\n", + " \"value\": 1.23\n", + "}\n" + ] + } + ], + "source": [ + "print(\"Physical layout:\")\n", + "print(\"------------------------------------------------------------------\")\n", + "for i, x in tree.layout.items():\n", + " if x.cls == numpy.ndarray:\n", + " print(\"{0:10s} {1}\".format(repr(i), x.array))\n", + "\n", + "import json\n", + "print(\"\\nLogical meaning:\")\n", + "print(\"------------------------------------------------------------------\")\n", + "print(json.dumps(tree[0].tolist(), indent=4))" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# For those of you who were here yesterday, do you remember this?\n", + "import sklearn.datasets, matplotlib.pyplot\n", + "X1, y1 = sklearn.datasets.make_gaussian_quantiles(\n", + " cov=2.0, n_samples=200, n_features=2, n_classes=2, random_state=1)\n", + "X2, y2 = sklearn.datasets.make_gaussian_quantiles(\n", + " mean=(3, 3), cov=1.5, n_samples=400, n_features=2, n_classes=2, random_state=1)\n", + "X = numpy.concatenate((X1, X2))\n", + "y = numpy.concatenate((y1, -y2 + 1))\n", + "matplotlib.pyplot.scatter(X[y == 0, 0], X[y == 0, 1], c=\"deepskyblue\", edgecolor=\"black\");\n", + "matplotlib.pyplot.scatter(X[y == 1, 0], X[y == 1, 1], c=\"orange\", edgecolor=\"black\");" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "# We made a decision tree using Scikit-Learn...\n", + "import sklearn.tree\n", + "decision_tree = sklearn.tree.DecisionTreeClassifier(max_depth=8)\n", + "decision_tree.fit(X, y)\n", + "xx, yy = numpy.meshgrid(numpy.arange(-5, 8, 0.02), numpy.arange(-5, 8, 0.02))\n", + "Z = decision_tree.predict(numpy.c_[xx.ravel(), yy.ravel()]).reshape(xx.shape)\n", + "matplotlib.pyplot.contourf(xx, yy, Z);\n", + "matplotlib.pyplot.scatter(X[y == 0, 0], X[y == 0, 1], c=\"deepskyblue\", edgecolor=\"black\", alpha=0.2);\n", + "matplotlib.pyplot.scatter(X[y == 1, 0], X[y == 1, 1], c=\"orange\", edgecolor=\"black\", alpha=0.2);\n", + "matplotlib.pyplot.xlim(-5, 8); matplotlib.pyplot.ylim(-5, 8);" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'feature': 1,\n", + " 'threshold': 4.358384370803833,\n", + " 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4.378947734832764,\n", + " 'left': {'feature': None,\n", + " 'threshold': None,\n", + " 'left': None,\n", + " 'right': None,\n", + " 'value': 5.0},\n", + " 'right': {'feature': None,\n", + " 'threshold': None,\n", + " 'left': None,\n", + " 'right': None,\n", + " 'value': -1.0},\n", + " 'value': 4.0},\n", + " 'right': {'feature': None,\n", + " 'threshold': None,\n", + " 'left': None,\n", + " 'right': None,\n", + " 'value': 53.0},\n", + " 'value': 57.0},\n", + " 'value': 0.0}" + ] + }, + "execution_count": 75, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Scikit-Learn is already using columnar trees: we can just cast it.\n", + "mask = decision_tree.tree_.children_left < 0\n", + "left = decision_tree.tree_.children_left.copy()\n", + "right = decision_tree.tree_.children_right.copy()\n", + "left[mask] = 0\n", + "right[mask] = 0\n", + "\n", + "tree = awkward.Table()\n", + "tree[\"feature\"] = awkward.MaskedArray(mask, decision_tree.tree_.feature)\n", + "tree[\"threshold\"] = awkward.MaskedArray(mask, decision_tree.tree_.threshold)\n", + "tree[\"left\"] = awkward.MaskedArray(mask, awkward.IndexedArray(left, tree))\n", + "tree[\"right\"] = awkward.MaskedArray(mask, awkward.IndexedArray(right, tree))\n", + "tree[\"value\"] = decision_tree.tree_.value[:, 0, 0] - decision_tree.tree_.value[:, 0, 1]\n", + "\n", + "tree[0].tolist()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

Columnar data structures are more general than the array-at-a-time programming paradigm. There are ongoing efforts to use the same awkward arrays in several programming paradigms:

\n", + "\n", + "
    \n", + "
  • conventional imperative programming in Numba (compiled Python, using awkward arrays as data types),\n", + "
  • truly vectorized programming on GPUs with CuPy and Numba,\n", + "
  • declarative languages (user specifies the what, not the how). Examples: LINQ, SQL-per-event, combinatorical pattern-matching...\n", + "
\n", + "\n", + "
\n", + "\n", + "

Columnar data structures provide a zero-copy medium between all of these paradigms.

\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "
\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "file is a read-only dict, from object names to objects:\n", + "\n", + "file.keys() → [b'one;1', b'three;1']\n", + "\n", + "file['one'].keys() → [b'two;1', b'tree;1']\n", + "\n", + "file['one']['two'].classes() → {b'tree;1': }\n", + "\n", + "file['one']['two']['tree'] → \n", + "\n", + "file['one/two/tree'] → \n" + ] + } + ], + "source": [ + "# We've been using uproot for many of our examples so far.\n", + "# \n", + "# As a re-write of ROOT I/O in Python, uproot presents the data in a Pythonic way:\n", + "\n", + "file = uproot.open(\"http://scikit-hep.org/uproot/examples/nesteddirs.root\")\n", + "\n", + "print(\"file is a read-only dict, from object names to objects:\\n\")\n", + "print(f\"file.keys() → {file.keys()}\\n\")\n", + "print(f\"file['one'].keys() → {file['one'].keys()}\\n\")\n", + "print(f\"file['one']['two'].classes() → {dict(file['one']['two'].classes())}\\n\")\n", + "print(f\"file['one']['two']['tree'] → {file['one']['two']['tree']}\\n\")\n", + "print(f\"file['one/two/tree'] → {file['one/two/tree']}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[b'Type',\n", + " b'Run',\n", + " b'Event',\n", + " b'E1',\n", + " b'px1',\n", + " b'py1',\n", + " b'pz1',\n", + " b'pt1',\n", + " b'eta1',\n", + " b'phi1',\n", + " b'Q1',\n", + " b'E2',\n", + " b'px2',\n", + " b'py2',\n", + " b'pz2',\n", + " b'pt2',\n", + " b'eta2',\n", + " b'phi2',\n", + " b'Q2',\n", + " b'M']" + ] + }, + "execution_count": 77, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# TBranches of TTrees are also presented as dicts.\n", + "events = uproot.open(\"data/Zmumu.root\")[\"events\"]\n", + "events.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 78, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])" + ] + }, + "execution_count": 78, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Get an array with TBranch.array().\n", + "\n", + "events[\"E1\"].array()" + ] + }, + { + "cell_type": "code", + "execution_count": 79, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])" + ] + }, + "execution_count": 79, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Or TTree.array(branchname).\n", + "\n", + "events.array(\"E1\")" + ] + }, + { + "cell_type": "code", + "execution_count": 80, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{b'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])}" + ] + }, + "execution_count": 80, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The plural form, arrays, returns a dict from branch names to arrays.\n", + "\n", + "events.arrays(\"E1\")" + ] + }, + { + "cell_type": "code", + "execution_count": 81, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{b'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " b'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " b'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " b'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247])}" + ] + }, + "execution_count": 81, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# You get the arrays you ask for.\n", + "\n", + "events.arrays([\"E1\", \"px1\", \"py1\", \"pz1\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 82, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{b'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " b'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " b'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " b'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247])}" + ] + }, + "execution_count": 82, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# With wildcards.\n", + "\n", + "events.arrays([\"E1\", \"p[xyz]1\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 83, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{b'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " b'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " b'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " b'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247]),\n", + " b'pt1': array([44.7322, 38.8311, 38.8311, ..., 32.3997, 32.3997, 32.3997]),\n", + " b'phi1': array([ 2.74126 , -0.440873 , -0.440873 , ..., 0.0370275, 0.0370275,\n", + " 0.0370275])}" + ] + }, + "execution_count": 83, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# These are the same wildcard patterns as matching files in UNIX.\n", + "\n", + "events.arrays([\"E1\", \"p*1\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 84, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{b'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " b'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " b'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " b'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247]),\n", + " b'pt1': array([44.7322, 38.8311, 38.8311, ..., 32.3997, 32.3997, 32.3997]),\n", + " b'phi1': array([ 2.74126 , -0.440873 , -0.440873 , ..., 0.0370275, 0.0370275,\n", + " 0.0370275])}" + ] + }, + "execution_count": 84, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Or with slashes, they become regular expressions.\n", + "\n", + "events.arrays([\"E1\", \"/p.*[0-1]/\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 85, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'E1': array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735]),\n", + " 'px1': array([-41.19528764, 35.11804977, 35.11804977, ..., 32.37749196,\n", + " 32.37749196, 32.48539387]),\n", + " 'py1': array([ 17.4332439 , -16.57036233, -16.57036233, ..., 1.19940578,\n", + " 1.19940578, 1.2013503 ]),\n", + " 'pz1': array([-68.96496181, -48.77524654, -48.77524654, ..., -74.53243061,\n", + " -74.53243061, -74.80837247])}" + ] + }, + "execution_count": 85, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The \"b\" before each string (for bytestring) can be removed in Python 3 by\n", + "# specifying an encoding (strings in ROOT have no default encoding).\n", + "\n", + "events.arrays([\"E1\", \"px1\", \"py1\", \"pz1\"], namedecode=\"utf-8\")" + ] + }, + { + "cell_type": "code", + "execution_count": 86, + "metadata": {}, + "outputs": [], + "source": [ + "# And we can change the container from a dict to something else by passing a\n", + "# class name; tuple is useful because it lets us assign each array.\n", + "\n", + "E, px, py, pz = events.arrays([\"E1\", \"px1\", \"py1\", \"pz1\"], outputtype=tuple)" + ] + }, + { + "cell_type": "code", + "execution_count": 87, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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E1px1py1pz1
entry
082.201866-41.19528817.433244-68.964962
162.34492935.118050-16.570362-48.775247
262.34492935.118050-16.570362-48.775247
360.62187534.144437-16.119525-47.426984
441.82638922.78358215.036444-31.689894
548.981407-19.862307-9.20422543.817098
648.981407-19.862307-9.20422543.817098
749.760726-20.177373-9.35414944.513955
8132.78075571.14371129.542308-108.150553
988.07833051.050486-51.849400-49.631328
1088.07833051.050486-51.849400-49.631328
1187.79565950.870937-51.669728-49.502056
1248.61914444.406988-3.13200319.545333
1346.404351-39.20884410.779752-22.356568
1446.404351-39.20884410.779752-22.356568
1546.519913-39.30648510.807865-22.411636
1657.36815027.2497883.083568-50.388830
1780.894157-42.020547-5.051576-68.939166
1880.894157-42.020547-5.051576-68.939166
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2350.59211133.72827229.70148223.233082
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2655.3929783.99632340.21190737.886709
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2931.419951-5.91154130.099173-6.804086
...............
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230381.56621732.4853941.201350-74.808372
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2304 rows × 4 columns

\n", + "
" + ], + "text/plain": [ + " E1 px1 py1 pz1\n", + "entry \n", + "0 82.201866 -41.195288 17.433244 -68.964962\n", + "1 62.344929 35.118050 -16.570362 -48.775247\n", + "2 62.344929 35.118050 -16.570362 -48.775247\n", + "3 60.621875 34.144437 -16.119525 -47.426984\n", + "4 41.826389 22.783582 15.036444 -31.689894\n", + "5 48.981407 -19.862307 -9.204225 43.817098\n", + "6 48.981407 -19.862307 -9.204225 43.817098\n", + "7 49.760726 -20.177373 -9.354149 44.513955\n", + "8 132.780755 71.143711 29.542308 -108.150553\n", + "9 88.078330 51.050486 -51.849400 -49.631328\n", + "10 88.078330 51.050486 -51.849400 -49.631328\n", + "11 87.795659 50.870937 -51.669728 -49.502056\n", + "12 48.619144 44.406988 -3.132003 19.545333\n", + "13 46.404351 -39.208844 10.779752 -22.356568\n", + "14 46.404351 -39.208844 10.779752 -22.356568\n", + "15 46.519913 -39.306485 10.807865 -22.411636\n", + "16 57.368150 27.249788 3.083568 -50.388830\n", + "17 80.894157 -42.020547 -5.051576 -68.939166\n", + "18 80.894157 -42.020547 -5.051576 -68.939166\n", + "19 81.311450 -42.242553 -5.076551 -69.291673\n", + "20 79.487794 -27.243260 -23.405122 70.910530\n", + "21 50.507597 33.674921 29.653424 23.187934\n", + "22 50.507597 33.674921 29.653424 23.187934\n", + "23 50.592111 33.728272 29.701482 23.233082\n", + "24 41.470909 -2.951523 -36.093120 -20.208917\n", + "25 55.392978 3.996323 40.211907 37.886709\n", + "26 55.392978 3.996323 40.211907 37.886709\n", + "27 55.542907 4.007466 40.319935 37.990083\n", + "28 112.883981 -2.419678 -45.436617 -103.307507\n", + "29 31.419951 -5.911541 30.099173 -6.804086\n", + "... ... ... ... ...\n", + "2274 23.712817 16.962188 -15.219455 6.552776\n", + "2275 23.684190 16.941295 -15.201413 6.545172\n", + "2276 66.967245 -56.585255 10.765311 -34.158714\n", + "2277 33.717409 32.980637 -1.925555 -6.739611\n", + "2278 33.717409 32.980637 -1.925555 -6.739611\n", + "2279 33.853678 33.113825 -1.934790 -6.766947\n", + "2280 42.580187 -36.045090 -8.456551 -21.030915\n", + "2281 53.526322 36.668310 38.486189 6.269309\n", + "2282 53.526322 36.668310 38.486189 6.269309\n", + "2283 53.508055 36.655204 38.472433 6.274452\n", + "2284 46.432408 22.435607 -22.743227 -33.694904\n", + "2285 52.581357 4.606652 43.856122 28.639261\n", + "2286 52.581357 4.606652 43.856122 28.639261\n", + "2287 52.533500 4.603120 43.818284 28.609906\n", + "2288 45.205618 -41.878716 2.697471 -16.805758\n", + "2289 58.235411 47.751704 9.223864 -32.031970\n", + "2290 58.235411 47.751704 9.223864 -32.031970\n", + "2291 58.054571 47.607872 9.197612 -31.925170\n", + "2292 107.167787 -15.258505 -33.719314 100.573900\n", + "2293 35.364583 12.966984 30.974506 11.094139\n", + "2294 35.364583 12.966984 30.974506 11.094139\n", + "2295 35.460376 13.001270 31.059021 11.123455\n", + "2296 27.742542 -16.891371 -15.335677 -15.784044\n", + "2297 32.676344 19.037577 14.820723 22.037447\n", + "2298 32.676344 19.037577 14.820723 22.037447\n", + "2299 32.701650 19.054651 14.833954 22.051323\n", + "2300 168.780121 -68.041915 -26.105847 -152.235018\n", + "2301 81.270136 32.377492 1.199406 -74.532431\n", + "2302 81.270136 32.377492 1.199406 -74.532431\n", + "2303 81.566217 32.485394 1.201350 -74.808372\n", + "\n", + "[2304 rows x 4 columns]" + ] + }, + "execution_count": 87, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# outputtype=pandas.DataFrame is a synonym for TTree.pandas.df.\n", + "\n", + "import pandas\n", + "events.arrays([\"E1\", \"px1\", \"py1\", \"pz1\"], outputtype=pandas.DataFrame)" + ] + }, + { + "cell_type": "code", + "execution_count": 88, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "asking for array...\n", + "reading array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])\n", + "asking for it with a cache...\n", + "reading array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])\n", + "asking for it again...\n" + ] + } + ], + "source": [ + "# Use an explicit cache to avoid reading many times from the same file.\n", + "\n", + "uproot.asdtype.debug_reading = True\n", + "\n", + "print(\"asking for array...\")\n", + "events.array(\"E1\")\n", + "\n", + "mycache = {} # or maybe uproot.ArrayCache(\"1 GB\")\n", + "\n", + "print(\"asking for it with a cache...\")\n", + "events.array(\"E1\", cache=mycache)\n", + "\n", + "print(\"asking for it again...\")\n", + "events.array(\"E1\", cache=mycache)\n", + "\n", + "uproot.asdtype.debug_reading = False" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

Three ways to get data:

\n", + "\n", + "\n", + " \n", + "
\n", + "

Direct

\n", + "

Read the file and return an array.

\n", + " \n", + "
\n", + "

Lazy

\n", + "

Get an object that reads on demand.

\n", + " \n", + "
\n", + "

Iterative

\n", + "

Read arrays in batches of entries.

\n", + " \n", + "
\n", + "\n", + "

*Lazy arrays or iteration over sets of files.

" + ] + }, + { + "cell_type": "code", + "execution_count": 89, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([82.20186639, 62.34492895, 62.34492895, ..., 81.27013558,\n", + " 81.27013558, 81.56621735])" + ] + }, + "execution_count": 89, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Direct:\n", + "\n", + "events.array(\"E1\")" + ] + }, + { + "cell_type": "code", + "execution_count": 90, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "getting lazy array...\n", + "len(lazyarray.chunks) = 5\n", + "before looking at the array...\n", + "reading array([ 82.20186639, 62.34492895, 62.34492895, 60.62187459,\n", + " 41.82638891, 48.98140695, 48.98140695, 49.76072566,\n", + " 132.78075492, 88.07833019, 88.07833019, 87.79565929,\n", + " 48.61914427, 46.40435116, 46.40435116, 46.51991282,\n", + " 57.36815016, 80.8941568 , 80.8941568 , 81.31144951,\n", + " 79.48779395, 50.50759651, 50.50759651, 50.59211055,\n", + " 41.47090944, 55.39297755, 55.39297755, 55.54290677,\n", + " 112.8839809 , 31.41995067, 31.41995067, 31.42339926,\n", + " 73.34548002, 33.0810183 , 33.0810183 , 32.45151863,\n", + " 36.76969687, 78.54927722, 78.54927722, 76.95658284,\n", + " 71.38162765, 37.11945042, 37.11945042, 37.10875051,\n", + " 41.34095485, 41.21802884, 41.21802884, 14.25833323,\n", + " 14.25833323, 14.25833323, 14.25833323, 41.2330742 ,\n", + " 105.725502 , 68.35271716, 68.35271716, 68.45669076,\n", + " 196.16113519, 29.90997935, 29.90997935, 8.67840117,\n", + " 8.67840117, 8.67840117, 8.67840117, 6.03288979,\n", + " 6.03288979, 6.03288979, 6.03288979, 6.03288979,\n", + " 6.18369895, 6.18369895, 6.18369895, 6.18369895,\n", + " 6.18369895, 6.18369895, 6.91442071, 6.91442071,\n", + " 6.91442071, 6.91442071, 6.91442071, 6.91442071,\n", + " 6.91442071, 29.87514879, 71.06802615, 51.68004106,\n", + " 51.68004106, 51.64925183, 72.89894806, 37.59135117,\n", + " 37.59135117, 3.68022577, 3.68022577, 3.68022577,\n", + " 3.68022577, 37.62769734, 27.88268925, 41.50209382,\n", + " 41.50209382, 41.54058015, 85.5567314 , 29.89152216,\n", + " 29.89152216, 29.82530216, 76.69810457, 86.97126468,\n", + " 86.97126468, 86.43256899, 127.50778607, 39.79195384,\n", + " 39.79195384, 39.74407998, 115.53811359, 47.29833494,\n", + " 47.29833494, 47.44418685, 46.58616153, 45.20271281,\n", + " 45.20271281, 45.48398147, 52.70709049, 62.26050977,\n", + " 62.26050977, 62.27436398, 33.03261707, 83.95840602,\n", + " 83.95840602, 83.76388426, 48.29133168, 41.31743732,\n", + " 41.31743732, 41.42258624, 105.99649959, 82.74679137,\n", + " 82.74679137, 11.8752667 , 11.8752667 , 11.8752667 ,\n", + " 11.8752667 , 83.09219982, 93.40588737, 51.97474787,\n", + " 51.97474787, 51.9919392 , 62.27836012, 38.43790063,\n", + " 38.43790063, 38.39228365, 161.5912558 , 39.65170143,\n", + " 39.65170143, 39.76693154, 66.88012568, 42.39460789,\n", + " 42.39460789, 42.48039832, 46.92335006, 46.92455779,\n", + " 46.92455779, 46.60761536, 50.06497373, 55.9734727 ,\n", + " 55.9734727 , 55.84905046, 102.20124345, 39.61899834,\n", + " 39.61899834, 39.65573994, 67.47956761, 57.80467657,\n", + " 57.80467657, 57.76942704, 51.04741038, 38.47067848,\n", + " 38.47067848, 38.85771495, 64.97495956, 35.76287676,\n", + " 35.76287676, 35.76622753, 51.02758661, 40.16542196,\n", + " 40.16542196, 40.21951192, 92.98845663, 30.88757883,\n", + " 30.88757883, 30.878293 , 62.54839167, 37.26885489,\n", + " 37.26885489, 37.34925284, 91.94361717, 39.52334744,\n", + " 39.52334744, 39.37759624, 48.2271562 , 59.57496608,\n", + " 59.57496608, 59.75775839, 77.57064047, 92.84879252,\n", + " 92.84879252, 95.99500573, 42.71818808, 52.4885467 ,\n", + " 52.4885467 , 52.51843993, 88.64234354, 31.64410794,\n", + " 31.64410794, 31.64959256, 87.4056862 , 49.38242655,\n", + " 49.38242655, 49.27349107, 53.50000015, 67.64285194,\n", + " 67.64285194, 67.76791299, 100.28242941, 23.36178732,\n", + " 23.36178732, 23.33391632, 50.40529434, 254.76182152,\n", + " 254.76182152, 258.89666354, 72.76396876, 41.46279188,\n", + " 41.46279188, 41.6119257 , 41.93974732, 48.29596747,\n", + " 48.29596747, 48.34900079, 78.74030586, 66.05473351,\n", + " 66.05473351, 65.88471968, 87.34089322, 33.2601818 ,\n", + " 33.2601818 , 33.19079216, 63.87067872, 75.36016204,\n", + " 75.36016204, 76.60169876, 107.15594485, 23.8806628 ,\n", + " 23.8806628 , 23.90109599, 40.2949981 , 56.86658408,\n", + " 56.86658408, 56.81195823, 122.17847187, 34.46781762,\n", + " 34.46781762, 34.54308174, 71.33230751, 40.34913239,\n", + " 40.34913239, 3.7887485 , 3.7887485 , 3.7887485 ,\n", + " 3.7887485 , 40.31016759, 131.45150914, 28.26313485,\n", + " 28.26313485, 28.16323056, 66.23584194, 96.52045244,\n", + " 96.52045244, 96.42160657, 82.4771798 , 34.72916771,\n", + " 34.72916771, 34.86326179, 136.91245633, 176.10798619,\n", + " 176.10798619, 179.18672432, 107.02007991, 46.58701508,\n", + " 46.58701508, 46.79108367, 116.13180937, 74.16383242,\n", + " 74.16383242, 74.04477484, 81.63601162, 89.92101662,\n", + " 89.92101662, 89.81354226, 40.39614676, 58.81178525,\n", + " 58.81178525, 58.83806348, 69.51646816, 31.21703518,\n", + " 31.21703518, 31.18352384, 104.41725376, 184.9226554 ,\n", + " 184.9226554 , 185.9655727 , 126.11541216, 42.446788 ,\n", + " 42.446788 , 42.47991382, 98.58850005, 52.37490921,\n", + " 52.37490921, 52.18606965, 94.83143467, 36.13129471,\n", + " 36.13129471, 36.15666544, 48.28351078, 42.95434659,\n", + " 42.95434659, 42.95856584, 52.74409028, 43.33089038,\n", + " 43.33089038, 43.34744671, 61.90488395, 44.52607703,\n", + " 44.52607703, 44.53126836, 46.27753806, 46.95140984,\n", + " 46.95140984, 46.94968131, 60.2129981 , 37.8612658 ,\n", + " 37.8612658 , 37.8285843 , 67.7653656 , 37.10912077,\n", + " 37.10912077, 37.04726169, 118.89463886, 48.99630469,\n", + " 48.99630469, 49.01124244, 100.11067561, 40.22610505,\n", + " 40.22610505, 2.80131924, 2.80131924, 2.80131924,\n", + " 2.80131924, 40.40268363, 126.87239391, 60.69529477,\n", + " 60.69529477, 60.41347555, 60.45034273, 47.80394443,\n", + " 47.80394443, 47.85848542, 56.76804815, 138.26451913,\n", + " 138.26451913, 4.88393134, 4.88393134, 4.88393134,\n", + " 4.88393134, 138.08959514, 40.25440134, 61.67817632,\n", + " 61.67817632, 61.72165702, 199.44834987, 41.601314 ,\n", + " 41.601314 , 41.59079094, 86.53026194, 76.35054423,\n", + " 76.35054423, 76.08791093, 67.61662778, 59.72331911,\n", + " 59.72331911, 59.80469062, 50.57086751, 110.42820932,\n", + " 110.42820932, 109.89557663, 104.2172648 , 86.06284772,\n", + " 86.06284772, 87.03293319, 139.23854951, 54.9396813 ,\n", + " 54.9396813 , 3.31356021, 3.31356021, 3.31356021,\n", + " 3.31356021, 54.65006448, 46.78336013, 43.53657461,\n", + " 43.53657461, 43.58139103, 110.73400727, 66.06582381,\n", + " 66.06582381, 64.56707909, 127.01099668, 55.5268161 ,\n", + " 55.5268161 , 55.41932963, 82.02574047, 92.01408361,\n", + " 92.01408361, 90.42667708, 45.69709417, 43.26503587,\n", + " 43.26503587, 43.2322141 , 115.23484945, 108.4062278 ,\n", + " 108.4062278 , 106.84622683, 68.25083863, 59.50132924,\n", + " 59.50132924, 59.45330573, 159.94779602, 94.3388382 ,\n", + " 94.3388382 , 93.2629199 , 108.198462 , 58.93886755,\n", + " 58.93886755, 3.52188742, 3.52188742, 3.52188742,\n", + " 3.52188742, 58.5886036 , 62.66659673, 50.82144749,\n", + " 50.82144749, 51.09930061, 89.26461232, 92.94113586,\n", + " 92.94113586, 92.66318339, 121.49702189, 41.3100944 ,\n", + " 41.3100944 , 41.22465063, 65.64283286, 33.73566654,\n", + " 33.73566654, 33.74026326, 39.85707511, 42.00168437,\n", + " 42.00168437, 42.05068821, 79.10783081, 42.85746059,\n", + " 42.85746059, 42.97136038, 60.16055065, 39.80387256,\n", + " 39.80387256, 39.80157369, 42.42033794, 39.06837782,\n", + " 39.06837782, 39.08969083, 141.78830565, 92.4850421 ,\n", + " 92.4850421 , 92.50799062, 69.71747155, 33.8122598 ,\n", + " 33.8122598 , 33.82700499, 150.17946048, 52.55095505,\n", + " 52.55095505, 52.48577273, 164.44335303, 87.92602083,\n", + " 87.92602083, 87.96504678, 61.67544744, 53.37824702,\n", + " 53.37824702, 53.17784156, 181.51530925, 90.93224422,\n", + " 90.93224422, 91.33359669, 50.5125538 , 45.7959062 ])\n", + "reading array([ 46.0752809 , 46.0752809 , 45.93225789, 51.01950403,\n", + " 84.91115834, 84.91115834, 85.40183438, 58.61087121,\n", + " 35.85560212, 35.85560212, 35.80270221, 65.69128374,\n", + " 34.92194525, 34.92194525, 35.1131883 , 63.33409091,\n", + " 28.33785313, 28.33785313, 28.29919652, 129.93892751,\n", + " 76.2413413 , 76.2413413 , 19.43559742, 19.43559742,\n", + " 19.43559742, 19.43559742, 77.06603846, 88.87206301,\n", + " 76.9896967 , 76.9896967 , 77.13454466, 80.46643455,\n", + " 50.22352215, 50.22352215, 50.32671059, 156.86919654,\n", + " 25.07053007, 25.07053007, 25.0157658 , 41.21248819,\n", + " 59.74725995, 59.74725995, 60.03458757, 114.59109646,\n", + " 46.09001797, 46.09001797, 45.3606167 , 6.63621225,\n", + " 6.63621225, 47.14487282, 47.14487282, 47.14487282,\n", + " 46.57451906, 46.57451906, 46.57451906, 46.57451906,\n", + " 47.21938272, 46.53882963, 46.53882963, 42.44033505,\n", + " 50.28127027, 50.28127027, 50.34189109, 49.22061868,\n", + " 50.13765098, 50.13765098, 50.41556485, 58.55740104,\n", + " 66.25855582, 66.25855582, 66.16414935, 42.0899355 ,\n", + " 85.2964904 , 85.2964904 , 85.76539914, 43.67188221,\n", + " 47.86001375, 47.86001375, 48.00145743, 51.89875501,\n", + " 46.86844432, 46.86844432, 46.79679221, 196.5144228 ,\n", + " 42.0469666 , 42.0469666 , 41.91187501, 174.62404314,\n", + " 81.09396457, 81.09396457, 81.69445412, 103.13230108,\n", + " 135.07364701, 135.07364701, 134.47187143, 60.14923662,\n", + " 37.89763776, 37.89763776, 37.87535674, 106.8741986 ,\n", + " 26.20362085, 26.20362085, 26.19512521, 44.39885681,\n", + " 25.448428 , 25.448428 , 25.46106481, 66.66163274,\n", + " 109.35030321, 109.35030321, 110.34275706, 99.71032777,\n", + " 24.01901969, 24.01901969, 24.08372758, 36.8158374 ,\n", + " 73.91941444, 73.91941444, 73.67659173, 56.80244434,\n", + " 52.11974215, 52.11974215, 52.11422256, 76.57235623,\n", + " 35.56797446, 35.56797446, 35.52918684, 20.29029808,\n", + " 20.29029808, 66.41965668, 66.41965668, 66.41965668,\n", + " 43.62290835, 43.62290835, 43.62290835, 43.62290835,\n", + " 66.27032084, 43.65965777, 43.65965777, 117.96089673,\n", + " 116.02402051, 116.02402051, 115.86429844, 181.14963955,\n", + " 46.32347932, 46.32347932, 46.34264138, 39.84007354,\n", + " 49.90479604, 49.90479604, 49.90611076, 68.83940379,\n", + " 32.99969725, 32.99969725, 33.04348861, 45.97343103,\n", + " 64.15355709, 64.15355709, 64.59826631, 173.71874741,\n", + " 96.815185 , 96.815185 , 96.7923539 , 110.36657744,\n", + " 37.06940706, 37.06940706, 37.17311116, 153.61763637,\n", + " 69.92084398, 69.92084398, 5.37746271, 5.37746271,\n", + " 5.37746271, 5.37746271, 69.94007349, 134.30583511,\n", + " 62.46127367, 62.46127367, 62.53647059, 48.2570493 ,\n", + " 43.66442238, 43.66442238, 43.62529629, 116.8518384 ,\n", + " 66.4364895 , 66.4364895 , 8.5442139 , 8.5442139 ,\n", + " 8.5442139 , 8.5442139 , 66.24139308, 60.95001814,\n", + " 31.95453952, 31.95453952, 31.98177713, 126.41108732,\n", + " 76.72380447, 76.72380447, 6.49166823, 6.49166823,\n", + " 6.49166823, 6.49166823, 6.83012466, 6.83012466,\n", + " 6.83012466, 6.83012466, 6.83012466, 75.9084579 ,\n", + " 132.38057047, 60.03479514, 60.03479514, 60.25783347,\n", + " 75.08545414, 33.16996819, 33.16996819, 33.26996319,\n", + " 54.99507245, 44.04162012, 44.04162012, 44.14031972,\n", + " 108.00555628, 63.034422 , 63.034422 , 63.08933334,\n", + " 54.3102105 , 38.59888976, 38.59888976, 38.56231294,\n", + " 109.16387103, 154.1797389 , 154.1797389 , 3.61754968,\n", + " 3.61754968, 3.61754968, 3.61754968, 154.48788823,\n", + " 65.37227648, 45.59964124, 45.59964124, 45.66147668,\n", + " 34.17148 , 62.50570717, 62.50570717, 62.53544859,\n", + " 131.59670502, 42.7932255 , 42.7932255 , 42.86945165,\n", + " 104.8499588 , 144.20170261, 144.20170261, 144.13072657,\n", + " 41.49020922, 49.39629022, 49.39629022, 49.37720121,\n", + " 34.97314075, 32.78697141, 32.78697141, 32.78248453,\n", + " 56.30050249, 45.91174393, 45.91174393, 45.85791096,\n", + " 88.43999667, 51.04219402, 51.04219402, 51.14641243,\n", + " 129.30699652, 69.25134207, 69.25134207, 68.0527026 ,\n", + " 72.21726793, 23.71281669, 23.71281669, 23.6841903 ,\n", + " 66.9672454 , 33.71740911, 33.71740911, 33.85367838,\n", + " 42.58018682, 53.52632157, 53.52632157, 53.50805529,\n", + " 46.43240844, 52.58135709, 52.58135709, 52.53349992,\n", + " 45.20561751, 58.23541104, 58.23541104, 58.0545706 ,\n", + " 107.16778698, 35.36458334, 35.36458334, 35.46037568,\n", + " 27.74254176, 32.67634359, 32.67634359, 32.70165023,\n", + " 168.78012134, 81.27013558, 81.27013558, 81.56621735])\n", + "lazyarray = [82.2018663875 62.3449289481 62.3449289481 ... 81.2701355756 81.2701355756 81.5662173543]\n", + "chunks read = [True, False, False, False, True]\n", + "before computing a value...\n", + "reading array([ 45.7959062 , 45.7108209 , 98.03548137, 53.53706097,\n", + " 53.53706097, 4.28311024, 4.28311024, 4.28311024,\n", + " 4.28311024, 3.34694302, 3.34694302, 3.34694302,\n", + " 3.34694302, 3.34694302, 53.75729904, 61.65428429,\n", + " 30.50362009, 30.50362009, 30.48102741, 66.45346224,\n", + " 52.87763186, 52.87763186, 52.7489543 , 52.81819208,\n", + " 40.46748228, 40.46748228, 40.57985174, 49.87412519,\n", + " 42.38993305, 42.38993305, 42.42833527, 85.1168695 ,\n", + " 29.74828806, 29.74828806, 29.78374733, 6.26765716,\n", + " 6.26765716, 55.36001619, 55.36001619, 55.36001619,\n", + " 39.7280774 , 39.7280774 , 39.7280774 , 39.7280774 ,\n", + " 54.94426763, 39.67636193, 39.67636193, 99.34784156,\n", + " 45.42959847, 45.42959847, 45.44501852, 54.68992715,\n", + " 54.68992715, 12.75976687, 12.75976687, 12.75976687,\n", + " 57.39367803, 57.39367803, 57.39367803, 57.39367803,\n", + " 7.00286458, 7.00286458, 7.00286458, 7.00286458,\n", + " 7.00286458, 7.00286458, 12.68173287, 57.44959026,\n", + " 57.44959026, 101.53475973, 42.18366415, 42.18366415,\n", + " 42.09498675, 104.22280101, 35.11128285, 35.11128285,\n", + " 35.1792105 , 41.48633092, 53.31312003, 53.31312003,\n", + " 53.35794746, 84.23382316, 35.71756911, 35.71756911,\n", + " 35.7474641 , 115.19581372, 67.50189087, 67.50189087,\n", + " 4.19541226, 4.19541226, 4.19541226, 4.19541226,\n", + " 4.62997718, 4.62997718, 4.62997718, 4.62997718,\n", + " 4.62997718, 67.62712635, 185.83802383, 86.48156096,\n", + " 86.48156096, 86.3818981 , 56.31038767, 39.97209441,\n", + " 39.97209441, 39.8840657 , 102.38123414, 43.94217292,\n", + " 43.94217292, 43.99002748, 100.04272633, 70.24205214,\n", + " 70.24205214, 69.11271174, 130.71140503, 132.22381792,\n", + " 132.22381792, 130.01674985, 106.01039066, 26.64366929,\n", + " 26.64366929, 26.61515679, 63.66102206, 88.0854839 ,\n", + " 88.0854839 , 87.9880279 , 85.49519198, 41.30918442,\n", + " 41.30918442, 41.18976548, 104.31691475, 35.54820434,\n", + " 35.54820434, 35.66256274, 70.71747547, 39.00228623,\n", + " 39.00228623, 38.96979595, 51.07988131, 45.05343019,\n", + " 45.05343019, 45.10348183, 81.20814467, 47.37554772,\n", + " 47.37554772, 47.42293478, 98.05420899, 26.10426866,\n", + " 26.10426866, 26.09762088, 32.47578224, 72.22923901,\n", + " 72.22923901, 73.36826693, 151.47113505, 49.90717523,\n", + " 49.90717523, 49.89694439, 161.31761553, 119.27281392,\n", + " 119.27281392, 119.70045634, 140.05499557, 132.87811786,\n", + " 132.87811786, 132.86267445, 98.60536577, 80.01514369,\n", + " 80.01514369, 79.89862041, 122.08858858, 49.79971391,\n", + " 49.79971391, 49.99184253, 63.9882154 , 46.19279341,\n", + " 46.19279341, 46.16046742, 77.87514338, 44.30757733,\n", + " 44.30757733, 6.53977097, 6.53977097, 6.53977097,\n", + " 6.53977097, 44.3190834 , 48.63772687, 54.59493952,\n", + " 54.59493952, 54.40286569, 109.31942576, 65.18370533,\n", + " 65.18370533, 65.24505329, 64.72993111, 34.15084224,\n", + " 34.15084224, 34.18045716, 72.7108244 , 38.78628712,\n", + " 38.78628712, 38.50068439, 39.5214725 , 55.58932065,\n", + " 55.58932065, 55.54991079, 106.33464446, 36.26492573,\n", + " 36.26492573, 36.33648773, 54.88383867, 41.8747026 ,\n", + " 41.8747026 , 41.77922379, 52.44967779, 30.44120514,\n", + " 30.44120514, 30.42208232, 79.20400522, 32.24336313,\n", + " 32.24336313, 32.24839943, 41.78042315, 34.85421797,\n", + " 34.85421797, 34.7893323 , 104.77473824, 43.87055856,\n", + " 43.87055856, 43.74426568, 89.13739949, 29.57737014,\n", + " 29.57737014, 29.5497005 , 91.21108515, 23.18379625,\n", + " 23.18379625, 9.77244189, 9.77244189, 9.77244189,\n", + " 9.77244189, 6.31468205, 6.31468205, 6.31468205,\n", + " 6.31468205, 6.31468205, 23.16692195, 168.9530304 ,\n", + " 45.90640042, 45.90640042, 45.3792689 , 154.39628754,\n", + " 47.32312717, 47.32312717, 47.29104124, 106.46022706,\n", + " 25.33144007, 25.33144007, 25.3134871 , 83.29414824,\n", + " 47.83020624, 47.83020624, 47.90649003, 52.12348834,\n", + " 54.68925628, 54.68925628, 54.76102821, 97.59331015,\n", + " 57.78942366, 57.78942366, 57.56590666, 162.76580385,\n", + " 129.23633072, 129.23633072, 129.83296938, 115.07087628,\n", + " 25.61296822, 25.61296822, 25.61417704, 88.4707355 ,\n", + " 88.4707355 , 154.79119067, 154.79119067, 154.79119067,\n", + " 103.26737836, 103.26737836, 103.26737836, 103.26737836,\n", + " 155.47754162, 73.67104443, 73.67104443, 69.14082468,\n", + " 38.59115679, 38.59115679, 38.58866085, 53.72302145,\n", + " 49.13936795, 49.13936795, 49.16618927, 62.11370828,\n", + " 59.62325187, 59.62325187, 59.75978119, 64.85815719,\n", + " 33.00204113, 33.00204113, 32.98092661, 148.05788423,\n", + " 49.22212446, 49.22212446, 48.98901268, 146.42375697,\n", + " 85.65230769, 85.65230769, 84.9637478 , 108.84529674,\n", + " 24.25055762, 24.25055762, 24.29936628, 162.56684145,\n", + " 175.68453974, 175.68453974, 174.85906213, 93.93125898,\n", + " 44.5743831 , 44.5743831 , 44.49115314, 98.52795552,\n", + " 119.27605689, 119.27605689, 127.37162122, 55.86022748,\n", + " 45.98907071, 45.98907071, 46.04934389, 87.24116205,\n", + " 113.94820563, 113.94820563, 5.24352718, 5.24352718,\n", + " 5.24352718, 5.24352718, 113.98667479, 107.69987257,\n", + " 34.24606857, 34.24606857, 34.2446843 , 138.15901091,\n", + " 69.87744168, 69.87744168, 70.05707369, 61.99775521,\n", + " 76.79482364, 76.79482364, 76.53515249, 94.63039592,\n", + " 54.94052163, 54.94052163, 54.8002539 , 49.33780419,\n", + " 38.92494135, 38.92494135, 39.0913323 , 53.34153036,\n", + " 44.01008919, 44.01008919, 44.08910084, 67.3954523 ,\n", + " 78.39492994, 78.39492994, 78.33691191, 28.33533554,\n", + " 60.46259485, 60.46259485, 60.38914582, 156.78645186,\n", + " 39.35421489, 39.35421489, 39.32233898, 105.81882781,\n", + " 27.38177059, 27.38177059, 3.8709433 , 3.8709433 ,\n", + " 3.8709433 , 3.8709433 , 27.36033778, 55.98393702,\n", + " 40.89664424, 40.89664424, 40.76408159, 42.23246082,\n", + " 77.90711073, 77.90711073, 77.84074297, 66.34244997,\n", + " 39.64593693, 39.64593693, 39.72442892, 77.80849186,\n", + " 64.94160775, 64.94160775, 65.07075998, 53.36433748,\n", + " 34.39941847, 34.39941847, 34.40378151, 113.63242151,\n", + " 29.22937035, 29.22937035, 29.25656902, 42.08471589,\n", + " 48.52077628, 48.52077628, 48.7463367 , 52.26365025,\n", + " 43.24592044, 43.24592044, 3.64463352, 3.64463352,\n", + " 3.64463352, 3.64463352, 43.33534913, 93.33287974,\n", + " 61.9911916 , 61.9911916 , 61.77179705, 113.12035244,\n", + " 139.20614758, 139.20614758, 139.34886893, 75.25672558,\n", + " 88.34705061, 88.34705061, 87.4025814 , 77.4127299 ,\n", + " 33.48086164, 33.48086164, 33.50100921, 96.90269271,\n", + " 63.0483831 , 63.0483831 , 62.50613703, 136.15024344,\n", + " 58.806859 , 58.806859 , 60.09654507, 86.92501951,\n", + " 27.32269359, 27.32269359, 27.30074396, 60.97549967,\n", + " 56.82716595, 56.82716595, 56.78276581, 75.41102742,\n", + " 29.29019096, 29.29019096, 29.28753266, 138.64731902,\n", + " 117.3083541 , 117.3083541 , 6.49244094, 6.49244094,\n", + " 6.49244094, 6.49244094, 5.539486 , 5.539486 ,\n", + " 5.539486 , 5.539486 , 116.58433927, 186.07993924,\n", + " 34.00666394, 34.00666394, 8.07988506, 8.07988506,\n", + " 8.07988506, 8.07988506, 34.08564671, 50.38776963,\n", + " 43.233991 , 43.233991 , 43.3016364 , 75.23979433,\n", + " 85.64195821, 85.64195821, 10.09580037, 10.09580037,\n", + " 10.09580037, 10.09580037, 85.71685245, 54.66240321,\n", + " 43.41598115, 43.41598115, 43.23279531, 47.94760868,\n", + " 50.51232263, 50.51232263, 50.58091877, 54.08179249])\n", + "reading array([ 31.4488924 , 31.4488924 , 31.39073377, 64.85457285,\n", + " 46.92904281, 46.92904281, 46.8175341 , 84.6534656 ,\n", + " 45.81122985, 45.81122985, 45.72320407, 8.52845353,\n", + " 8.52845353, 140.6693251 , 140.6693251 , 140.6693251 ,\n", + " 38.57074364, 38.57074364, 38.57074364, 38.57074364,\n", + " 129.65292757, 38.57931862, 38.57931862, 94.07558437,\n", + " 42.48658583, 42.48658583, 42.4151989 , 41.79667879,\n", + " 46.97568581, 46.97568581, 46.91438364, 47.88026421,\n", + " 65.80416363, 65.80416363, 65.73851191, 45.9266897 ,\n", + " 45.1790785 , 45.1790785 , 45.26093575, 47.00117345,\n", + " 52.12766819, 52.12766819, 52.18124402, 95.70457827,\n", + " 75.54771532, 75.54771532, 75.18366823, 55.00114597,\n", + " 37.90007709, 37.90007709, 37.9755793 , 50.58215299,\n", + " 53.30375152, 53.30375152, 53.26814353, 75.84185475,\n", + " 28.59411263, 28.59411263, 28.68261954, 111.88531423,\n", + " 57.36268368, 57.36268368, 6.58675997, 6.58675997,\n", + " 6.58675997, 6.58675997, 57.75593688, 131.14501416,\n", + " 75.56420348, 75.56420348, 74.65934666, 148.59365577,\n", + " 63.91324124, 63.91324124, 63.32768472, 123.20052575,\n", + " 104.62365577, 104.62365577, 105.40810206, 66.77391623,\n", + " 43.22690942, 43.22690942, 43.34562432, 45.04418514,\n", + " 46.03056228, 46.03056228, 46.25180594, 80.23695946,\n", + " 105.24013119, 105.24013119, 105.36834033, 76.86389423,\n", + " 36.7415667 , 36.7415667 , 36.67212226, 55.57071625,\n", + " 37.94350241, 37.94350241, 37.78544236, 113.4729771 ,\n", + " 63.14417237, 63.14417237, 63.61101002, 46.29740831,\n", + " 58.65535456, 58.65535456, 58.61838778, 72.35168843,\n", + " 39.41519906, 39.41519906, 39.32425573, 67.55979748,\n", + " 80.3605257 , 80.3605257 , 79.01197416, 50.20175762,\n", + " 40.70177574, 40.70177574, 40.71954516, 193.49259154,\n", + " 192.08741173, 192.08741173, 3.49314832, 3.49314832,\n", + " 3.49314832, 3.49314832, 199.78585219, 126.14711465,\n", + " 35.70256876, 35.70256876, 6.12356886, 6.12356886,\n", + " 6.12356886, 6.12356886, 35.68050675, 89.6149403 ,\n", + " 54.94942972, 54.94942972, 54.9944288 , 139.45738731,\n", + " 44.73282214, 44.73282214, 44.72127253, 65.9614742 ,\n", + " 81.14295401, 81.14295401, 81.37989984, 135.29792495,\n", + " 117.44689675, 117.44689675, 117.76391219, 138.62043705,\n", + " 57.0550187 , 57.0550187 , 57.21952763, 106.00198323,\n", + " 40.15668284, 40.15668284, 40.25908618, 65.86126085,\n", + " 34.01748813, 34.01748813, 34.06649924, 58.95234108,\n", + " 47.45024139, 47.45024139, 47.41402621, 61.09417096,\n", + " 36.83197785, 36.83197785, 36.74283534, 67.67943419,\n", + " 41.46868604, 41.46868604, 41.38648411, 68.80726237,\n", + " 45.98922476, 45.98922476, 45.81039032, 50.06660335,\n", + " 49.41124973, 49.41124973, 49.51266435, 134.83978531,\n", + " 134.83978531, 9.71719936, 9.71719936, 9.71719936,\n", + " 178.30141267, 178.30141267, 178.30141267, 178.30141267,\n", + " 9.67078461, 178.16562619, 178.16562619, 83.35622549,\n", + " 33.9541694 , 33.9541694 , 33.98370116, 47.06118081,\n", + " 59.89729485, 59.89729485, 59.74856876, 54.36884537,\n", + " 36.33107491, 36.33107491, 36.27463258, 127.20182732,\n", + " 54.14574607, 54.14574607, 54.52750913, 45.23627798,\n", + " 47.02058933, 47.02058933, 47.03036801, 73.10174692,\n", + " 53.15281967, 53.15281967, 53.18444035, 81.49764647,\n", + " 58.48350435, 58.48350435, 58.32154461, 80.72365482,\n", + " 39.43517589, 39.43517589, 9.2963854 , 9.2963854 ,\n", + " 9.2963854 , 9.2963854 , 39.34363722, 56.66361595,\n", + " 35.92201525, 35.92201525, 35.47212723, 92.63370683,\n", + " 31.33836172, 31.33836172, 31.3649048 , 44.10335413,\n", + " 47.27571161, 47.27571161, 47.37883659, 91.36722307,\n", + " 38.00938872, 38.00938872, 4.18237505, 4.18237505,\n", + " 4.18237505, 4.18237505, 38.01516864, 63.24757346,\n", + " 39.23690233, 39.23690233, 39.24763076, 124.0373808 ,\n", + " 160.57288382, 160.57288382, 160.12708292, 66.29024719,\n", + " 42.00766598, 42.00766598, 41.98317147, 57.4994334 ,\n", + " 35.38813432, 35.38813432, 35.34335344, 162.18675388,\n", + " 81.59126589, 81.59126589, 81.97797001, 50.65732915,\n", + " 35.88156401, 35.88156401, 35.85498094, 85.74685874,\n", + " 157.09995907, 157.09995907, 159.15569656, 106.14531765,\n", + " 36.80681662, 36.80681662, 36.7877665 , 58.19332724,\n", + " 36.16418444, 36.16418444, 36.3060183 , 90.18447565,\n", + " 32.83003331, 32.83003331, 32.81875221, 25.5257341 ,\n", + " 50.72328444, 50.72328444, 50.26798457, 28.8753221 ,\n", + " 89.68452678, 89.68452678, 89.80278913, 81.39770281,\n", + " 39.97641963, 39.97641963, 39.92173475, 59.3078787 ,\n", + " 41.36455376, 41.36455376, 41.50486542, 52.4601721 ,\n", + " 57.68929594, 57.68929594, 57.46945135, 55.63842232,\n", + " 37.75185787, 37.75185787, 37.76478786, 46.53648948,\n", + " 47.35393503, 47.35393503, 47.22743504, 56.30050302,\n", + " 48.33331548, 48.33331548, 48.09129658, 155.76784771,\n", + " 132.21353292, 132.21353292, 4.38533679, 4.38533679,\n", + " 4.38533679, 4.38533679, 8.30139305, 8.30139305,\n", + " 8.30139305, 8.30139305, 8.30139305, 132.47394194,\n", + " 59.54844134, 51.504863 , 51.504863 , 51.61476222,\n", + " 70.81148033, 53.29767937, 53.29767937, 53.34290138,\n", + " 118.23647833, 25.87546347, 25.87546347, 25.85750241,\n", + " 191.39862737, 192.24372946, 192.24372946, 195.5932536 ,\n", + " 46.45756811, 81.37588868, 81.37588868, 80.9311136 ,\n", + " 177.12737645, 36.88688646, 36.88688646, 36.66077341,\n", + " 68.33844149, 58.60561528, 58.60561528, 58.44816444,\n", + " 46.69831351, 43.08413939, 43.08413939, 43.08248701,\n", + " 61.0932906 , 34.58304616, 34.58304616, 34.62902074,\n", + " 84.9792777 , 64.39072755, 64.39072755, 64.60560743,\n", + " 82.32344215, 31.10353562, 31.10353562, 31.08032059,\n", + " 35.07619529, 66.78312173, 66.78312173, 66.75157152,\n", + " 102.63208391, 38.15247107, 38.15247107, 38.22679269,\n", + " 134.83849682, 42.67985473, 42.67985473, 8.75909962,\n", + " 8.75909962, 8.75909962, 8.75909962, 42.6712094 ,\n", + " 44.55825461, 55.56842885, 55.56842885, 55.59828677,\n", + " 126.54943174, 27.53784736, 27.53784736, 27.5864764 ,\n", + " 49.69973228, 78.8832333 , 78.8832333 , 78.82477173,\n", + " 34.15450328, 54.08846337, 54.08846337, 54.14960405,\n", + " 41.24178457, 29.58892632, 29.58892632, 29.6000208 ,\n", + " 126.20425014, 61.92781948, 61.92781948, 61.77394446,\n", + " 72.58083777, 122.01695089, 122.01695089, 5.62108403,\n", + " 5.62108403, 5.62108403, 5.62108403, 123.40631695,\n", + " 41.93704858, 60.81892182, 60.81892182, 60.96308968,\n", + " 77.03104458, 61.5504854 , 61.5504854 , 61.60392341,\n", + " 48.68073463, 46.45499905, 46.45499905, 46.38494697,\n", + " 60.07226622, 53.72846903, 53.72846903, 53.70981226,\n", + " 187.84060356, 106.64471537, 106.64471537, 5.11110008,\n", + " 5.11110008, 5.11110008, 5.11110008, 106.76445632,\n", + " 153.71976689, 65.49757892, 65.49757892, 65.41798709,\n", + " 110.18294498, 44.79879731, 44.79879731, 44.95452363,\n", + " 126.24616223, 55.48556728, 55.48556728, 55.17005504,\n", + " 29.40470563, 43.08177972, 43.08177972, 43.19388382,\n", + " 75.79013003, 73.8556512 , 73.8556512 , 74.19072 ,\n", + " 51.13070941, 57.97649292, 57.97649292, 57.72312704,\n", + " 48.74933215, 44.59500552, 44.59500552, 44.55242615,\n", + " 89.18427674, 28.86139525, 28.86139525, 28.90460426,\n", + " 173.68655524, 56.53795841, 56.53795841, 56.99324511,\n", + " 44.30160232, 46.01758815, 46.01758815, 45.8590885 ,\n", + " 43.83963267, 75.73319987, 75.73319987, 75.35943451,\n", + " 60.90552118, 41.63869736, 41.63869736, 41.71851674])\n", + "reading array([ 88.35872379, 52.5560163 , 52.5560163 , 52.38402383,\n", + " 75.34015706, 84.01117306, 84.01117306, 83.2373654 ,\n", + " 106.88381294, 65.43826332, 65.43826332, 65.37243421,\n", + " 141.90546639, 86.08603046, 86.08603046, 83.28055127,\n", + " 54.52800442, 37.03419192, 37.03419192, 37.24423078,\n", + " 39.58212088, 55.75818653, 55.75818653, 55.84985555,\n", + " 194.26994459, 88.07882208, 88.07882208, 88.99732661,\n", + " 39.86478824, 60.71323622, 60.71323622, 60.53554808,\n", + " 119.70698665, 38.38845541, 38.38845541, 38.28409161,\n", + " 148.21968334, 86.61116176, 86.61116176, 86.64023146,\n", + " 63.95492154, 35.06499746, 35.06499746, 35.07012158,\n", + " 46.31873677, 46.82008975, 46.82008975, 46.96458725,\n", + " 60.78954319, 126.77855001, 126.77855001, 126.85285711,\n", + " 114.43787142, 27.72746034, 27.72746034, 27.71332446,\n", + " 48.76798976, 53.65188163, 53.65188163, 53.65621191,\n", + " 43.69934575, 47.53830966, 47.53830966, 47.51236032,\n", + " 138.63509723, 41.00929514, 41.00929514, 4.15050499,\n", + " 4.15050499, 4.15050499, 4.15050499, 40.98031325,\n", + " 83.89978937, 29.49288876, 29.49288876, 29.49198093,\n", + " 48.31683784, 40.77728909, 40.77728909, 40.73416733,\n", + " 96.84527167, 38.23212049, 38.23212049, 38.19896576,\n", + " 41.97697145, 59.11541224, 59.11541224, 59.13724726,\n", + " 142.11510277, 125.97153601, 125.97153601, 126.47181489,\n", + " 99.9833478 , 38.42392612, 38.42392612, 38.56362086,\n", + " 49.03291187, 39.16130492, 39.16130492, 39.39670097,\n", + " 48.87202496, 42.84786043, 42.84786043, 42.65177685,\n", + " 56.01151818, 38.65341322, 38.65341322, 38.7210157 ,\n", + " 67.03218227, 57.03356075, 57.03356075, 56.8859121 ,\n", + " 81.6689029 , 37.45563694, 37.45563694, 37.41202517,\n", + " 51.33743919, 55.9648835 , 55.9648835 , 55.87676228,\n", + " 138.13105399, 66.83212765, 66.83212765, 6.94737829,\n", + " 6.94737829, 6.94737829, 6.94737829, 66.68009327,\n", + " 109.30278048, 55.05934844, 55.05934844, 8.64005241,\n", + " 8.64005241, 8.64005241, 8.64005241, 6.6121817 ,\n", + " 6.6121817 , 6.6121817 , 6.6121817 , 6.6121817 ,\n", + " 54.94315159, 44.71474232, 40.73927362, 40.73927362,\n", + " 40.72549763, 41.89352537, 49.36862504, 49.36862504,\n", + " 49.48685818, 86.36778291, 61.02616496, 61.02616496,\n", + " 61.00348324, 128.70881964, 34.88502957, 34.88502957,\n", + " 34.89370529, 74.72118667, 47.77258133, 47.77258133,\n", + " 47.97332653, 56.38417177, 62.38924825, 62.38924825,\n", + " 62.65597136, 81.67930561, 55.50236703, 55.50236703,\n", + " 55.6054619 , 54.52221047, 49.50808521, 49.50808521,\n", + " 49.70673506, 46.94119806, 47.20457096, 47.20457096,\n", + " 47.27352645, 69.16063149, 78.27794572, 78.27794572,\n", + " 6.88735305, 6.88735305, 6.88735305, 6.88735305,\n", + " 78.30233386, 92.54436268, 84.70456403, 84.70456403,\n", + " 84.62002427, 72.29216599, 64.47691155, 64.47691155,\n", + " 64.83070059, 409.70843731, 160.74479615, 160.74479615,\n", + " 163.36004442, 77.12662191, 36.4389926 , 36.4389926 ,\n", + " 36.48197059, 129.92691183, 108.49883823, 108.49883823,\n", + " 108.18200249, 125.71083638, 32.56283369, 32.56283369,\n", + " 32.4862329 , 40.30271939, 51.90848058, 51.90848058,\n", + " 51.93461855, 101.51062133, 52.16636996, 52.16636996,\n", + " 52.0906679 , 88.58158208, 67.82574561, 67.82574561,\n", + " 69.5514503 , 134.60140717, 90.41470397, 90.41470397,\n", + " 90.64924556, 79.24987047, 35.33510234, 35.33510234,\n", + " 35.3535795 , 27.53395757, 121.82959442, 121.82959442,\n", + " 116.62133185, 62.33117478, 28.83015743, 28.83015743,\n", + " 28.8661648 , 49.54779545, 44.79715196, 44.79715196,\n", + " 44.69443085, 162.501742 , 36.47521066, 36.47521066,\n", + " 36.4260609 , 57.10597806, 37.7327282 , 37.7327282 ,\n", + " 37.90999717, 181.49442371, 53.52900596, 53.52900596,\n", + " 53.30788681, 62.66511308, 49.2001532 , 49.2001532 ,\n", + " 49.6272703 , 87.49270976, 34.19603319, 34.19603319,\n", + " 34.20167053, 64.27707984, 45.98148272, 45.98148272,\n", + " 5.32186092, 5.32186092, 5.32186092, 5.32186092,\n", + " 3.71645488, 3.71645488, 3.71645488, 3.71645488,\n", + " 3.71645488, 4.02573771, 4.02573771, 4.02573771,\n", + " 4.02573771, 4.02573771, 45.8294583 , 137.65706675,\n", + " 137.82609948, 137.82609948, 140.20672477, 41.88661378,\n", + " 50.16451528, 50.16451528, 50.13918696, 189.55187797,\n", + " 69.52900147, 69.52900147, 69.7803922 , 85.25403166,\n", + " 82.32694367, 82.32694367, 81.02631313, 35.62161555,\n", + " 194.51280497, 194.51280497, 181.86885876, 42.7649914 ,\n", + " 53.98975366, 53.98975366, 53.90081822, 123.49325457,\n", + " 34.00198053, 34.00198053, 33.97869612, 76.31482064,\n", + " 31.43538407, 31.43538407, 31.39348273, 55.50769971,\n", + " 44.1654036 , 44.1654036 , 44.12535269, 119.60071504,\n", + " 66.86543217, 66.86543217, 65.36171674, 117.93673295,\n", + " 38.60248887, 38.60248887, 38.67384561, 88.91621543,\n", + " 59.42153971, 59.42153971, 59.42249302, 94.62096642,\n", + " 60.38681019, 60.38681019, 60.41091483, 88.23490563,\n", + " 97.96885753, 97.96885753, 6.21784619, 6.21784619,\n", + " 6.21784619, 6.21784619, 97.84301613, 60.25213133,\n", + " 37.26279999, 37.26279999, 37.23898709, 88.86714968,\n", + " 26.18230782, 26.18230782, 26.15467977, 41.78539303,\n", + " 52.57705471, 52.57705471, 52.59537149, 103.67200391,\n", + " 33.52673117, 33.52673117, 33.57273198, 28.81186182,\n", + " 96.43871617, 96.43871617, 96.7089768 , 78.80892722,\n", + " 38.47606001, 38.47606001, 38.51433212, 168.6169744 ,\n", + " 167.29382107, 167.29382107, 2.91617992, 2.91617992,\n", + " 2.91617992, 2.91617992, 165.05592512, 73.85954974,\n", + " 43.43238226, 43.43238226, 43.38908576, 146.20343866,\n", + " 29.30296565, 29.30296565, 29.24821931, 77.89716846,\n", + " 145.83657724, 145.83657724, 145.85632055, 90.97179694,\n", + " 85.106841 , 85.106841 , 84.57031801, 64.82293368,\n", + " 45.01080002, 45.01080002, 2.79681986, 2.79681986,\n", + " 2.79681986, 2.79681986, 44.7796283 , 72.21666028,\n", + " 46.88331176, 46.88331176, 46.95373218, 49.57418466,\n", + " 41.8504303 , 41.8504303 , 41.59197996, 98.98271995,\n", + " 27.27257313, 27.27257313, 27.28854242, 50.19167426,\n", + " 40.93017852, 40.93017852, 41.0371756 , 104.85338073,\n", + " 35.26710829, 35.26710829, 35.28818523, 48.08172951,\n", + " 65.78774878, 65.78774878, 65.7083212 , 66.63296497,\n", + " 45.62787515, 45.62787515, 46.06484524, 217.45932153,\n", + " 217.45932153, 133.11227194, 133.11227194, 133.11227194,\n", + " 4.03261614, 4.03261614, 4.03261614, 4.03261614,\n", + " 5.71913642, 5.71913642, 5.71913642, 5.71913642,\n", + " 133.25826192, 4.02460498, 4.02460498, 58.07883492,\n", + " 42.43225951, 42.43225951, 42.60982669, 73.60908903,\n", + " 106.45029258, 106.45029258, 107.14272357, 71.38401806,\n", + " 48.54296413, 48.54296413, 48.55283683, 64.78400858,\n", + " 66.70646985, 66.70646985, 66.82286037, 95.45053473,\n", + " 34.4063727 , 34.4063727 , 34.47878715, 58.33219777,\n", + " 44.09805157, 44.09805157, 44.32610925, 63.46597266,\n", + " 35.33450637, 35.33450637, 35.23524194, 47.16827756,\n", + " 49.05516008, 49.05516008, 48.95690634, 35.43846735,\n", + " 34.11459445, 34.11459445, 34.12961079, 86.72754807,\n", + " 53.83141463, 53.83141463, 53.91570024, 48.18659673,\n", + " 44.05035771, 44.05035771, 44.0047877 , 91.04789737,\n", + " 40.45785665, 40.45785665, 7.79383044, 7.79383044,\n", + " 7.79383044, 7.79383044, 40.42914143, 128.26366808,\n", + " 55.89699092, 55.89699092, 55.96852373, 265.20089663,\n", + " 132.67809643, 132.67809643, 132.61278621, 67.53918671])\n", + "numpy.sqrt(lazyarray) = [9.066524493293999 7.89588050492787 7.89588050492787 7.786005047127827 6.467332441741339 6.998671799263057 6.998671799263057 ...]\n", + "before computing another value...\n", + "lazyarray**2 = [9.066524493293999 7.89588050492787 7.89588050492787 7.786005047127827 6.467332441741339 6.998671799263057 6.998671799263057 ...]\n" + ] + } + ], + "source": [ + "# Lazy:\n", + "\n", + "uproot.asdtype.debug_reading = True\n", + "\n", + "print(\"getting lazy array...\")\n", + "lazyarray = events.lazyarray(\"E1\", entrysteps=500)\n", + "print(f\"len(lazyarray.chunks) = {len(lazyarray.chunks)}\")\n", + "\n", + "print(\"before looking at the array...\")\n", + "print(f\"lazyarray = {lazyarray}\")\n", + "print(f\"chunks read = {[x.ismaterialized for x in lazyarray.chunks]}\")\n", + "\n", + "print(\"before computing a value...\")\n", + "print(f\"numpy.sqrt(lazyarray) = {numpy.sqrt(lazyarray)}\")\n", + "\n", + "print(\"before computing another value...\")\n", + "print(f\"lazyarray**2 = {numpy.sqrt(lazyarray)}\")\n", + "\n", + "uproot.asdtype.debug_reading = False" + ] + }, + { + "cell_type": "code", + "execution_count": 91, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{b'E1': array([ 82.20186639, 62.34492895, 62.34492895, 60.62187459,\n", + " 41.82638891, 48.98140695, 48.98140695, 49.76072566,\n", + " 132.78075492, 88.07833019, 88.07833019, 87.79565929,\n", + " 48.61914427, 46.40435116, 46.40435116, 46.51991282,\n", + " 57.36815016, 80.8941568 , 80.8941568 , 81.31144951,\n", + " 79.48779395, 50.50759651, 50.50759651, 50.59211055,\n", + " 41.47090944, 55.39297755, 55.39297755, 55.54290677,\n", + " 112.8839809 , 31.41995067, 31.41995067, 31.42339926,\n", + " 73.34548002, 33.0810183 , 33.0810183 , 32.45151863,\n", + " 36.76969687, 78.54927722, 78.54927722, 76.95658284,\n", + " 71.38162765, 37.11945042, 37.11945042, 37.10875051,\n", + " 41.34095485, 41.21802884, 41.21802884, 14.25833323,\n", + " 14.25833323, 14.25833323, 14.25833323, 41.2330742 ,\n", + " 105.725502 , 68.35271716, 68.35271716, 68.45669076,\n", + " 196.16113519, 29.90997935, 29.90997935, 8.67840117,\n", + " 8.67840117, 8.67840117, 8.67840117, 6.03288979,\n", + " 6.03288979, 6.03288979, 6.03288979, 6.03288979,\n", + " 6.18369895, 6.18369895, 6.18369895, 6.18369895,\n", + " 6.18369895, 6.18369895, 6.91442071, 6.91442071,\n", + " 6.91442071, 6.91442071, 6.91442071, 6.91442071,\n", + " 6.91442071, 29.87514879, 71.06802615, 51.68004106,\n", + " 51.68004106, 51.64925183, 72.89894806, 37.59135117,\n", + " 37.59135117, 3.68022577, 3.68022577, 3.68022577,\n", + " 3.68022577, 37.62769734, 27.88268925, 41.50209382,\n", + " 41.50209382, 41.54058015, 85.5567314 , 29.89152216,\n", + " 29.89152216, 29.82530216, 76.69810457, 86.97126468,\n", + " 86.97126468, 86.43256899, 127.50778607, 39.79195384,\n", + " 39.79195384, 39.74407998, 115.53811359, 47.29833494,\n", + " 47.29833494, 47.44418685, 46.58616153, 45.20271281,\n", + " 45.20271281, 45.48398147, 52.70709049, 62.26050977,\n", + " 62.26050977, 62.27436398, 33.03261707, 83.95840602,\n", + " 83.95840602, 83.76388426, 48.29133168, 41.31743732,\n", + " 41.31743732, 41.42258624, 105.99649959, 82.74679137,\n", + " 82.74679137, 11.8752667 , 11.8752667 , 11.8752667 ,\n", + " 11.8752667 , 83.09219982, 93.40588737, 51.97474787,\n", + " 51.97474787, 51.9919392 , 62.27836012, 38.43790063,\n", + " 38.43790063, 38.39228365, 161.5912558 , 39.65170143,\n", + " 39.65170143, 39.76693154, 66.88012568, 42.39460789,\n", + " 42.39460789, 42.48039832, 46.92335006, 46.92455779,\n", + " 46.92455779, 46.60761536, 50.06497373, 55.9734727 ,\n", + " 55.9734727 , 55.84905046, 102.20124345, 39.61899834,\n", + " 39.61899834, 39.65573994, 67.47956761, 57.80467657,\n", + " 57.80467657, 57.76942704, 51.04741038, 38.47067848,\n", + " 38.47067848, 38.85771495, 64.97495956, 35.76287676,\n", + " 35.76287676, 35.76622753, 51.02758661, 40.16542196,\n", + " 40.16542196, 40.21951192, 92.98845663, 30.88757883,\n", + " 30.88757883, 30.878293 , 62.54839167, 37.26885489,\n", + " 37.26885489, 37.34925284, 91.94361717, 39.52334744,\n", + " 39.52334744, 39.37759624, 48.2271562 , 59.57496608,\n", + " 59.57496608, 59.75775839, 77.57064047, 92.84879252,\n", + " 92.84879252, 95.99500573, 42.71818808, 52.4885467 ,\n", + " 52.4885467 , 52.51843993, 88.64234354, 31.64410794,\n", + " 31.64410794, 31.64959256, 87.4056862 , 49.38242655,\n", + " 49.38242655, 49.27349107, 53.50000015, 67.64285194,\n", + " 67.64285194, 67.76791299, 100.28242941, 23.36178732,\n", + " 23.36178732, 23.33391632, 50.40529434, 254.76182152,\n", + " 254.76182152, 258.89666354, 72.76396876, 41.46279188,\n", + " 41.46279188, 41.6119257 , 41.93974732, 48.29596747,\n", + " 48.29596747, 48.34900079, 78.74030586, 66.05473351,\n", + " 66.05473351, 65.88471968, 87.34089322, 33.2601818 ,\n", + " 33.2601818 , 33.19079216, 63.87067872, 75.36016204,\n", + " 75.36016204, 76.60169876, 107.15594485, 23.8806628 ,\n", + " 23.8806628 , 23.90109599, 40.2949981 , 56.86658408,\n", + " 56.86658408, 56.81195823, 122.17847187, 34.46781762,\n", + " 34.46781762, 34.54308174, 71.33230751, 40.34913239,\n", + " 40.34913239, 3.7887485 , 3.7887485 , 3.7887485 ,\n", + " 3.7887485 , 40.31016759, 131.45150914, 28.26313485,\n", + " 28.26313485, 28.16323056, 66.23584194, 96.52045244,\n", + " 96.52045244, 96.42160657, 82.4771798 , 34.72916771,\n", + " 34.72916771, 34.86326179, 136.91245633, 176.10798619,\n", + " 176.10798619, 179.18672432, 107.02007991, 46.58701508,\n", + " 46.58701508, 46.79108367, 116.13180937, 74.16383242,\n", + " 74.16383242, 74.04477484, 81.63601162, 89.92101662,\n", + " 89.92101662, 89.81354226, 40.39614676, 58.81178525,\n", + " 58.81178525, 58.83806348, 69.51646816, 31.21703518,\n", + " 31.21703518, 31.18352384, 104.41725376, 184.9226554 ,\n", + " 184.9226554 , 185.9655727 , 126.11541216, 42.446788 ,\n", + " 42.446788 , 42.47991382, 98.58850005, 52.37490921,\n", + " 52.37490921, 52.18606965, 94.83143467, 36.13129471,\n", + " 36.13129471, 36.15666544, 48.28351078, 42.95434659,\n", + " 42.95434659, 42.95856584, 52.74409028, 43.33089038,\n", + " 43.33089038, 43.34744671, 61.90488395, 44.52607703,\n", + " 44.52607703, 44.53126836, 46.27753806, 46.95140984,\n", + " 46.95140984, 46.94968131, 60.2129981 , 37.8612658 ,\n", + " 37.8612658 , 37.8285843 , 67.7653656 , 37.10912077,\n", + " 37.10912077, 37.04726169, 118.89463886, 48.99630469,\n", + " 48.99630469, 49.01124244, 100.11067561, 40.22610505,\n", + " 40.22610505, 2.80131924, 2.80131924, 2.80131924,\n", + " 2.80131924, 40.40268363, 126.87239391, 60.69529477,\n", + " 60.69529477, 60.41347555, 60.45034273, 47.80394443,\n", + " 47.80394443, 47.85848542, 56.76804815, 138.26451913,\n", + " 138.26451913, 4.88393134, 4.88393134, 4.88393134,\n", + " 4.88393134, 138.08959514, 40.25440134, 61.67817632,\n", + " 61.67817632, 61.72165702, 199.44834987, 41.601314 ,\n", + " 41.601314 , 41.59079094, 86.53026194, 76.35054423,\n", + " 76.35054423, 76.08791093, 67.61662778, 59.72331911,\n", + " 59.72331911, 59.80469062, 50.57086751, 110.42820932,\n", + " 110.42820932, 109.89557663, 104.2172648 , 86.06284772,\n", + " 86.06284772, 87.03293319, 139.23854951, 54.9396813 ,\n", + " 54.9396813 , 3.31356021, 3.31356021, 3.31356021,\n", + " 3.31356021, 54.65006448, 46.78336013, 43.53657461,\n", + " 43.53657461, 43.58139103, 110.73400727, 66.06582381,\n", + " 66.06582381, 64.56707909, 127.01099668, 55.5268161 ,\n", + " 55.5268161 , 55.41932963, 82.02574047, 92.01408361,\n", + " 92.01408361, 90.42667708, 45.69709417, 43.26503587,\n", + " 43.26503587, 43.2322141 , 115.23484945, 108.4062278 ,\n", + " 108.4062278 , 106.84622683, 68.25083863, 59.50132924,\n", + " 59.50132924, 59.45330573, 159.94779602, 94.3388382 ,\n", + " 94.3388382 , 93.2629199 , 108.198462 , 58.93886755,\n", + " 58.93886755, 3.52188742, 3.52188742, 3.52188742,\n", + " 3.52188742, 58.5886036 , 62.66659673, 50.82144749,\n", + " 50.82144749, 51.09930061, 89.26461232, 92.94113586,\n", + " 92.94113586, 92.66318339, 121.49702189, 41.3100944 ,\n", + " 41.3100944 , 41.22465063, 65.64283286, 33.73566654,\n", + " 33.73566654, 33.74026326, 39.85707511, 42.00168437,\n", + " 42.00168437, 42.05068821, 79.10783081, 42.85746059,\n", + " 42.85746059, 42.97136038, 60.16055065, 39.80387256,\n", + " 39.80387256, 39.80157369, 42.42033794, 39.06837782,\n", + " 39.06837782, 39.08969083, 141.78830565, 92.4850421 ,\n", + " 92.4850421 , 92.50799062, 69.71747155, 33.8122598 ,\n", + " 33.8122598 , 33.82700499, 150.17946048, 52.55095505,\n", + " 52.55095505, 52.48577273, 164.44335303, 87.92602083,\n", + " 87.92602083, 87.96504678, 61.67544744, 53.37824702,\n", + " 53.37824702, 53.17784156, 181.51530925, 90.93224422,\n", + " 90.93224422, 91.33359669, 50.5125538 , 45.7959062 ])}\n", + "{b'E1': array([ 45.7959062 , 45.7108209 , 98.03548137, 53.53706097,\n", + " 53.53706097, 4.28311024, 4.28311024, 4.28311024,\n", + " 4.28311024, 3.34694302, 3.34694302, 3.34694302,\n", + " 3.34694302, 3.34694302, 53.75729904, 61.65428429,\n", + " 30.50362009, 30.50362009, 30.48102741, 66.45346224,\n", + " 52.87763186, 52.87763186, 52.7489543 , 52.81819208,\n", + " 40.46748228, 40.46748228, 40.57985174, 49.87412519,\n", + " 42.38993305, 42.38993305, 42.42833527, 85.1168695 ,\n", + " 29.74828806, 29.74828806, 29.78374733, 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8.75909962, 8.75909962, 8.75909962, 42.6712094 ,\n", + " 44.55825461, 55.56842885, 55.56842885, 55.59828677,\n", + " 126.54943174, 27.53784736, 27.53784736, 27.5864764 ,\n", + " 49.69973228, 78.8832333 , 78.8832333 , 78.82477173,\n", + " 34.15450328, 54.08846337, 54.08846337, 54.14960405,\n", + " 41.24178457, 29.58892632, 29.58892632, 29.6000208 ,\n", + " 126.20425014, 61.92781948, 61.92781948, 61.77394446,\n", + " 72.58083777, 122.01695089, 122.01695089, 5.62108403,\n", + " 5.62108403, 5.62108403, 5.62108403, 123.40631695,\n", + " 41.93704858, 60.81892182, 60.81892182, 60.96308968,\n", + " 77.03104458, 61.5504854 , 61.5504854 , 61.60392341,\n", + " 48.68073463, 46.45499905, 46.45499905, 46.38494697,\n", + " 60.07226622, 53.72846903, 53.72846903, 53.70981226,\n", + " 187.84060356, 106.64471537, 106.64471537, 5.11110008,\n", + " 5.11110008, 5.11110008, 5.11110008, 106.76445632,\n", + " 153.71976689, 65.49757892, 65.49757892, 65.41798709,\n", + " 110.18294498, 44.79879731, 44.79879731, 44.95452363,\n", + " 126.24616223, 55.48556728, 55.48556728, 55.17005504,\n", + " 29.40470563, 43.08177972, 43.08177972, 43.19388382,\n", + " 75.79013003, 73.8556512 , 73.8556512 , 74.19072 ,\n", + " 51.13070941, 57.97649292, 57.97649292, 57.72312704,\n", + " 48.74933215, 44.59500552, 44.59500552, 44.55242615,\n", + " 89.18427674, 28.86139525, 28.86139525, 28.90460426,\n", + " 173.68655524, 56.53795841, 56.53795841, 56.99324511,\n", + " 44.30160232, 46.01758815, 46.01758815, 45.8590885 ,\n", + " 43.83963267, 75.73319987, 75.73319987, 75.35943451,\n", + " 60.90552118, 41.63869736, 41.63869736, 41.71851674])}\n", + "{b'E1': array([ 88.35872379, 52.5560163 , 52.5560163 , 52.38402383,\n", + " 75.34015706, 84.01117306, 84.01117306, 83.2373654 ,\n", + " 106.88381294, 65.43826332, 65.43826332, 65.37243421,\n", + " 141.90546639, 86.08603046, 86.08603046, 83.28055127,\n", + " 54.52800442, 37.03419192, 37.03419192, 37.24423078,\n", + " 39.58212088, 55.75818653, 55.75818653, 55.84985555,\n", + " 194.26994459, 88.07882208, 88.07882208, 88.99732661,\n", + " 39.86478824, 60.71323622, 60.71323622, 60.53554808,\n", + " 119.70698665, 38.38845541, 38.38845541, 38.28409161,\n", + " 148.21968334, 86.61116176, 86.61116176, 86.64023146,\n", + " 63.95492154, 35.06499746, 35.06499746, 35.07012158,\n", + " 46.31873677, 46.82008975, 46.82008975, 46.96458725,\n", + " 60.78954319, 126.77855001, 126.77855001, 126.85285711,\n", + " 114.43787142, 27.72746034, 27.72746034, 27.71332446,\n", + " 48.76798976, 53.65188163, 53.65188163, 53.65621191,\n", + " 43.69934575, 47.53830966, 47.53830966, 47.51236032,\n", + " 138.63509723, 41.00929514, 41.00929514, 4.15050499,\n", + " 4.15050499, 4.15050499, 4.15050499, 40.98031325,\n", + " 83.89978937, 29.49288876, 29.49288876, 29.49198093,\n", + " 48.31683784, 40.77728909, 40.77728909, 40.73416733,\n", + " 96.84527167, 38.23212049, 38.23212049, 38.19896576,\n", + " 41.97697145, 59.11541224, 59.11541224, 59.13724726,\n", + " 142.11510277, 125.97153601, 125.97153601, 126.47181489,\n", + " 99.9833478 , 38.42392612, 38.42392612, 38.56362086,\n", + " 49.03291187, 39.16130492, 39.16130492, 39.39670097,\n", + " 48.87202496, 42.84786043, 42.84786043, 42.65177685,\n", + " 56.01151818, 38.65341322, 38.65341322, 38.7210157 ,\n", + " 67.03218227, 57.03356075, 57.03356075, 56.8859121 ,\n", + " 81.6689029 , 37.45563694, 37.45563694, 37.41202517,\n", + " 51.33743919, 55.9648835 , 55.9648835 , 55.87676228,\n", + " 138.13105399, 66.83212765, 66.83212765, 6.94737829,\n", + " 6.94737829, 6.94737829, 6.94737829, 66.68009327,\n", + " 109.30278048, 55.05934844, 55.05934844, 8.64005241,\n", + " 8.64005241, 8.64005241, 8.64005241, 6.6121817 ,\n", + " 6.6121817 , 6.6121817 , 6.6121817 , 6.6121817 ,\n", + " 54.94315159, 44.71474232, 40.73927362, 40.73927362,\n", + " 40.72549763, 41.89352537, 49.36862504, 49.36862504,\n", + " 49.48685818, 86.36778291, 61.02616496, 61.02616496,\n", + " 61.00348324, 128.70881964, 34.88502957, 34.88502957,\n", + " 34.89370529, 74.72118667, 47.77258133, 47.77258133,\n", + " 47.97332653, 56.38417177, 62.38924825, 62.38924825,\n", + " 62.65597136, 81.67930561, 55.50236703, 55.50236703,\n", + " 55.6054619 , 54.52221047, 49.50808521, 49.50808521,\n", + " 49.70673506, 46.94119806, 47.20457096, 47.20457096,\n", + " 47.27352645, 69.16063149, 78.27794572, 78.27794572,\n", + " 6.88735305, 6.88735305, 6.88735305, 6.88735305,\n", + " 78.30233386, 92.54436268, 84.70456403, 84.70456403,\n", + " 84.62002427, 72.29216599, 64.47691155, 64.47691155,\n", + " 64.83070059, 409.70843731, 160.74479615, 160.74479615,\n", + " 163.36004442, 77.12662191, 36.4389926 , 36.4389926 ,\n", + " 36.48197059, 129.92691183, 108.49883823, 108.49883823,\n", + " 108.18200249, 125.71083638, 32.56283369, 32.56283369,\n", + " 32.4862329 , 40.30271939, 51.90848058, 51.90848058,\n", + " 51.93461855, 101.51062133, 52.16636996, 52.16636996,\n", + " 52.0906679 , 88.58158208, 67.82574561, 67.82574561,\n", + " 69.5514503 , 134.60140717, 90.41470397, 90.41470397,\n", + " 90.64924556, 79.24987047, 35.33510234, 35.33510234,\n", + " 35.3535795 , 27.53395757, 121.82959442, 121.82959442,\n", + " 116.62133185, 62.33117478, 28.83015743, 28.83015743,\n", + " 28.8661648 , 49.54779545, 44.79715196, 44.79715196,\n", + " 44.69443085, 162.501742 , 36.47521066, 36.47521066,\n", + " 36.4260609 , 57.10597806, 37.7327282 , 37.7327282 ,\n", + " 37.90999717, 181.49442371, 53.52900596, 53.52900596,\n", + " 53.30788681, 62.66511308, 49.2001532 , 49.2001532 ,\n", + " 49.6272703 , 87.49270976, 34.19603319, 34.19603319,\n", + " 34.20167053, 64.27707984, 45.98148272, 45.98148272,\n", + " 5.32186092, 5.32186092, 5.32186092, 5.32186092,\n", + " 3.71645488, 3.71645488, 3.71645488, 3.71645488,\n", + " 3.71645488, 4.02573771, 4.02573771, 4.02573771,\n", + " 4.02573771, 4.02573771, 45.8294583 , 137.65706675,\n", + " 137.82609948, 137.82609948, 140.20672477, 41.88661378,\n", + " 50.16451528, 50.16451528, 50.13918696, 189.55187797,\n", + " 69.52900147, 69.52900147, 69.7803922 , 85.25403166,\n", + " 82.32694367, 82.32694367, 81.02631313, 35.62161555,\n", + " 194.51280497, 194.51280497, 181.86885876, 42.7649914 ,\n", + " 53.98975366, 53.98975366, 53.90081822, 123.49325457,\n", + " 34.00198053, 34.00198053, 33.97869612, 76.31482064,\n", + " 31.43538407, 31.43538407, 31.39348273, 55.50769971,\n", + " 44.1654036 , 44.1654036 , 44.12535269, 119.60071504,\n", + " 66.86543217, 66.86543217, 65.36171674, 117.93673295,\n", + " 38.60248887, 38.60248887, 38.67384561, 88.91621543,\n", + " 59.42153971, 59.42153971, 59.42249302, 94.62096642,\n", + " 60.38681019, 60.38681019, 60.41091483, 88.23490563,\n", + " 97.96885753, 97.96885753, 6.21784619, 6.21784619,\n", + " 6.21784619, 6.21784619, 97.84301613, 60.25213133,\n", + " 37.26279999, 37.26279999, 37.23898709, 88.86714968,\n", + " 26.18230782, 26.18230782, 26.15467977, 41.78539303,\n", + " 52.57705471, 52.57705471, 52.59537149, 103.67200391,\n", + " 33.52673117, 33.52673117, 33.57273198, 28.81186182,\n", + " 96.43871617, 96.43871617, 96.7089768 , 78.80892722,\n", + " 38.47606001, 38.47606001, 38.51433212, 168.6169744 ,\n", + " 167.29382107, 167.29382107, 2.91617992, 2.91617992,\n", + " 2.91617992, 2.91617992, 165.05592512, 73.85954974,\n", + " 43.43238226, 43.43238226, 43.38908576, 146.20343866,\n", + " 29.30296565, 29.30296565, 29.24821931, 77.89716846,\n", + " 145.83657724, 145.83657724, 145.85632055, 90.97179694,\n", + " 85.106841 , 85.106841 , 84.57031801, 64.82293368,\n", + " 45.01080002, 45.01080002, 2.79681986, 2.79681986,\n", + " 2.79681986, 2.79681986, 44.7796283 , 72.21666028,\n", + " 46.88331176, 46.88331176, 46.95373218, 49.57418466,\n", + " 41.8504303 , 41.8504303 , 41.59197996, 98.98271995,\n", + " 27.27257313, 27.27257313, 27.28854242, 50.19167426,\n", + " 40.93017852, 40.93017852, 41.0371756 , 104.85338073,\n", + " 35.26710829, 35.26710829, 35.28818523, 48.08172951,\n", + " 65.78774878, 65.78774878, 65.7083212 , 66.63296497,\n", + " 45.62787515, 45.62787515, 46.06484524, 217.45932153,\n", + " 217.45932153, 133.11227194, 133.11227194, 133.11227194,\n", + " 4.03261614, 4.03261614, 4.03261614, 4.03261614,\n", + " 5.71913642, 5.71913642, 5.71913642, 5.71913642,\n", + " 133.25826192, 4.02460498, 4.02460498, 58.07883492,\n", + " 42.43225951, 42.43225951, 42.60982669, 73.60908903,\n", + " 106.45029258, 106.45029258, 107.14272357, 71.38401806,\n", + " 48.54296413, 48.54296413, 48.55283683, 64.78400858,\n", + " 66.70646985, 66.70646985, 66.82286037, 95.45053473,\n", + " 34.4063727 , 34.4063727 , 34.47878715, 58.33219777,\n", + " 44.09805157, 44.09805157, 44.32610925, 63.46597266,\n", + " 35.33450637, 35.33450637, 35.23524194, 47.16827756,\n", + " 49.05516008, 49.05516008, 48.95690634, 35.43846735,\n", + " 34.11459445, 34.11459445, 34.12961079, 86.72754807,\n", + " 53.83141463, 53.83141463, 53.91570024, 48.18659673,\n", + " 44.05035771, 44.05035771, 44.0047877 , 91.04789737,\n", + " 40.45785665, 40.45785665, 7.79383044, 7.79383044,\n", + " 7.79383044, 7.79383044, 40.42914143, 128.26366808,\n", + " 55.89699092, 55.89699092, 55.96852373, 265.20089663,\n", + " 132.67809643, 132.67809643, 132.61278621, 67.53918671])}\n", + "{b'E1': array([ 46.0752809 , 46.0752809 , 45.93225789, 51.01950403,\n", + " 84.91115834, 84.91115834, 85.40183438, 58.61087121,\n", + " 35.85560212, 35.85560212, 35.80270221, 65.69128374,\n", + " 34.92194525, 34.92194525, 35.1131883 , 63.33409091,\n", + " 28.33785313, 28.33785313, 28.29919652, 129.93892751,\n", + " 76.2413413 , 76.2413413 , 19.43559742, 19.43559742,\n", + " 19.43559742, 19.43559742, 77.06603846, 88.87206301,\n", + " 76.9896967 , 76.9896967 , 77.13454466, 80.46643455,\n", + " 50.22352215, 50.22352215, 50.32671059, 156.86919654,\n", + " 25.07053007, 25.07053007, 25.0157658 , 41.21248819,\n", + " 59.74725995, 59.74725995, 60.03458757, 114.59109646,\n", + " 46.09001797, 46.09001797, 45.3606167 , 6.63621225,\n", + " 6.63621225, 47.14487282, 47.14487282, 47.14487282,\n", + " 46.57451906, 46.57451906, 46.57451906, 46.57451906,\n", + " 47.21938272, 46.53882963, 46.53882963, 42.44033505,\n", + " 50.28127027, 50.28127027, 50.34189109, 49.22061868,\n", + " 50.13765098, 50.13765098, 50.41556485, 58.55740104,\n", + " 66.25855582, 66.25855582, 66.16414935, 42.0899355 ,\n", + " 85.2964904 , 85.2964904 , 85.76539914, 43.67188221,\n", + " 47.86001375, 47.86001375, 48.00145743, 51.89875501,\n", + " 46.86844432, 46.86844432, 46.79679221, 196.5144228 ,\n", + " 42.0469666 , 42.0469666 , 41.91187501, 174.62404314,\n", + " 81.09396457, 81.09396457, 81.69445412, 103.13230108,\n", + " 135.07364701, 135.07364701, 134.47187143, 60.14923662,\n", + " 37.89763776, 37.89763776, 37.87535674, 106.8741986 ,\n", + " 26.20362085, 26.20362085, 26.19512521, 44.39885681,\n", + " 25.448428 , 25.448428 , 25.46106481, 66.66163274,\n", + " 109.35030321, 109.35030321, 110.34275706, 99.71032777,\n", + " 24.01901969, 24.01901969, 24.08372758, 36.8158374 ,\n", + " 73.91941444, 73.91941444, 73.67659173, 56.80244434,\n", + " 52.11974215, 52.11974215, 52.11422256, 76.57235623,\n", + " 35.56797446, 35.56797446, 35.52918684, 20.29029808,\n", + " 20.29029808, 66.41965668, 66.41965668, 66.41965668,\n", + " 43.62290835, 43.62290835, 43.62290835, 43.62290835,\n", + " 66.27032084, 43.65965777, 43.65965777, 117.96089673,\n", + " 116.02402051, 116.02402051, 115.86429844, 181.14963955,\n", + " 46.32347932, 46.32347932, 46.34264138, 39.84007354,\n", + " 49.90479604, 49.90479604, 49.90611076, 68.83940379,\n", + " 32.99969725, 32.99969725, 33.04348861, 45.97343103,\n", + " 64.15355709, 64.15355709, 64.59826631, 173.71874741,\n", + " 96.815185 , 96.815185 , 96.7923539 , 110.36657744,\n", + " 37.06940706, 37.06940706, 37.17311116, 153.61763637,\n", + " 69.92084398, 69.92084398, 5.37746271, 5.37746271,\n", + " 5.37746271, 5.37746271, 69.94007349, 134.30583511,\n", + " 62.46127367, 62.46127367, 62.53647059, 48.2570493 ,\n", + " 43.66442238, 43.66442238, 43.62529629, 116.8518384 ,\n", + " 66.4364895 , 66.4364895 , 8.5442139 , 8.5442139 ,\n", + " 8.5442139 , 8.5442139 , 66.24139308, 60.95001814,\n", + " 31.95453952, 31.95453952, 31.98177713, 126.41108732,\n", + " 76.72380447, 76.72380447, 6.49166823, 6.49166823,\n", + " 6.49166823, 6.49166823, 6.83012466, 6.83012466,\n", + " 6.83012466, 6.83012466, 6.83012466, 75.9084579 ,\n", + " 132.38057047, 60.03479514, 60.03479514, 60.25783347,\n", + " 75.08545414, 33.16996819, 33.16996819, 33.26996319,\n", + " 54.99507245, 44.04162012, 44.04162012, 44.14031972,\n", + " 108.00555628, 63.034422 , 63.034422 , 63.08933334,\n", + " 54.3102105 , 38.59888976, 38.59888976, 38.56231294,\n", + " 109.16387103, 154.1797389 , 154.1797389 , 3.61754968,\n", + " 3.61754968, 3.61754968, 3.61754968, 154.48788823,\n", + " 65.37227648, 45.59964124, 45.59964124, 45.66147668,\n", + " 34.17148 , 62.50570717, 62.50570717, 62.53544859,\n", + " 131.59670502, 42.7932255 , 42.7932255 , 42.86945165,\n", + " 104.8499588 , 144.20170261, 144.20170261, 144.13072657,\n", + " 41.49020922, 49.39629022, 49.39629022, 49.37720121,\n", + " 34.97314075, 32.78697141, 32.78697141, 32.78248453,\n", + " 56.30050249, 45.91174393, 45.91174393, 45.85791096,\n", + " 88.43999667, 51.04219402, 51.04219402, 51.14641243,\n", + " 129.30699652, 69.25134207, 69.25134207, 68.0527026 ,\n", + " 72.21726793, 23.71281669, 23.71281669, 23.6841903 ,\n", + " 66.9672454 , 33.71740911, 33.71740911, 33.85367838,\n", + " 42.58018682, 53.52632157, 53.52632157, 53.50805529,\n", + " 46.43240844, 52.58135709, 52.58135709, 52.53349992,\n", + " 45.20561751, 58.23541104, 58.23541104, 58.0545706 ,\n", + " 107.16778698, 35.36458334, 35.36458334, 35.46037568,\n", + " 27.74254176, 32.67634359, 32.67634359, 32.70165023,\n", + " 168.78012134, 81.27013558, 81.27013558, 81.56621735])}\n" + ] + } + ], + "source": [ + "# Iterative:\n", + "\n", + "for arrays in events.iterate(\"E1\", entrysteps=500):\n", + " print(arrays)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Advantages and disadvantages of each:

\n", + "\n", + "\n", + " \n", + "
\n", + "

Direct

\n", + "

Simple; returns pure Numpy arrays if possible.

\n", + "
\n", + "

Lazy

\n", + "

Transparently work on data too large to fit into memory.

\n", + "
\n", + "

Iterative

\n", + "

Control the loading of data into and out of memory.

\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 92, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Lazy or iteration steps as a fixed number of entries:\n", + "500\n", + "500\n", + "500\n", + "500\n", + "304\n", + "\n", + "Lazy or iteration steps as a fixed memory footprint:\n", + "717\n", + "717\n", + "717\n", + "153\n" + ] + } + ], + "source": [ + "# Controlling the chunk size:\n", + "\n", + "print(\"Lazy or iteration steps as a fixed number of entries:\")\n", + "for arrays in events.iterate(entrysteps=500):\n", + " print(len(arrays[b\"E1\"]))\n", + "\n", + "print(\"\\nLazy or iteration steps as a fixed memory footprint:\")\n", + "for arrays in events.iterate(entrysteps=\"100 kB\"):\n", + " print(len(arrays[b\"E1\"]))" + ] + }, + { + "cell_type": "code", + "execution_count": 93, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "event TStreamerInfo None\n", + "TObject TStreamerInfo None\n", + "fUniqueID TStreamerBasicType asdtype('>u4')\n", + "fBits TStreamerBasicType asdtype('>u4')\n", + "\n", + "fType[20] TStreamerBasicType asdtype(\"('i1', (20,))\")\n", + "fEventName TStreamerBasicType asstring(4)\n", + "fNtrack TStreamerBasicType asdtype('>i4')\n", + "fNseg TStreamerBasicType asdtype('>i4')\n", + "fNvertex TStreamerBasicType asdtype('>u4')\n", + "fFlag TStreamerBasicType asdtype('>u4')\n", + "fTemperature TStreamerBasicType asdtype('>f4', 'float64')\n", + "fMeasures[10] TStreamerBasicType asdtype(\"('>i4', (10,))\")\n", + "fMatrix[4][4] TStreamerBasicType asdtype(\"('>f4', (4, 4))\", \"('i4')\n", + "fEvtHdr.fRun TStreamerBasicType asdtype('>i4')\n", + "fEvtHdr.fDate TStreamerBasicType asdtype('>i4')\n", + "\n", + "fTracks TStreamerObjectPointer None\n", + "fTracks.fUniqueID TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fBits TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fPx TStreamerBasicType asjagged(asdtype('>f4'))\n", + "fTracks.fPy TStreamerBasicType asjagged(asdtype('>f4'))\n", + "fTracks.fPz TStreamerBasicType asjagged(asdtype('>f4'))\n", + "fTracks.fRandom TStreamerBasicType asjagged(asdtype('>f4'))\n", + "fTracks.fMass2 TStreamerBasicType asjagged(asfloat16(0.0, 0.0, 8, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fBx TStreamerBasicType asjagged(asfloat16(0.0, 0.0, 10, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fBy TStreamerBasicType asjagged(asfloat16(0.0, 0.0, 10, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fMeanCharge TStreamerBasicType asjagged(asdtype('>f4'))\n", + "fTracks.fXfirst TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fXlast TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fYfirst TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fYlast TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fZfirst TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fZlast TStreamerBasicType asjagged(asfloat16(0, 0, 12, dtype([('exponent', 'u1'), ('mantissa', '>u2')]), dtype('float32')))\n", + "fTracks.fCharge TStreamerBasicType asjagged(asdouble32(-1.0, 1.0, 2, dtype('>u4'), dtype('float64')))\n", + "fTracks.fVertex[3] TStreamerBasicType asjagged(asdouble32(-30.0, 30.0, 16, dtype(('>u4', (3,))), dtype(('i4'))\n", + "fTracks.fValid TStreamerBasicType asjagged(asdtype('>i2'))\n", + "fTracks.fNsp TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fPointValue TStreamerBasicPointer None\n", + "fTracks.fTriggerBits.fUniqueID\n", + " TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fTriggerBits.fBits TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fTriggerBits.fNbits\n", + " TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fTriggerBits.fNbytes\n", + " TStreamerBasicType asjagged(asdtype('>u4'))\n", + "fTracks.fTriggerBits.fAllBits\n", + " TStreamerBasicPointer asjagged(asdtype('uint8'), 1)\n", + "fTracks.fTArray[3] TStreamerBasicType asjagged(asdtype(\"('>f4', (3,))\"))\n", + "\n", + "fHighPt TStreamerObjectPointer asgenobj(TRefArray)\n", + "fMuons TStreamerObjectPointer asgenobj(TRefArray)\n", + "fLastTrack TStreamerInfo asgenobj(TRef)\n", + "fWebHistogram TStreamerInfo asgenobj(TRef)\n", + "fH TStreamerObjectPointer asgenobj(TH1F)\n", + "fTriggerBits TStreamerInfo None\n", + "fTriggerBits.TObject (no streamer) None\n", + "fTriggerBits.fUniqueID (no streamer) asdtype('>u4')\n", + "fTriggerBits.fBits (no streamer) asdtype('>u4')\n", + "\n", + "fTriggerBits.fNbits TStreamerBasicType asdtype('>u4')\n", + "fTriggerBits.fNbytes TStreamerBasicType asdtype('>u4')\n", + "fTriggerBits.fAllBits TStreamerBasicPointer asjagged(asdtype('uint8'), 1)\n", + "\n", + "fIsValid TStreamerBasicType asdtype('bool')\n", + "\n" + ] + } + ], + "source": [ + "# Reading complex data: mostly simplified by the fact that C++ classes are \"split\"\n", + "# into TBranches, and most TBranches are simple arrays.\n", + "\n", + "tree = uproot.open(\"http://scikit-hep.org/uproot/examples/Event.root\")[\"T\"]\n", + "tree.show()\n", + "\n", + "# branch name streamer type, if any uproot's interpretation" + ] + }, + { + "cell_type": "code", + "execution_count": 94, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([20.28261757, 20.47114182, 20.5931778 , 20.5848484 , 20.80287933,\n", + " 20.2972393 , 20.30301666, 20.87490845, 20.56552505, 20.67128181,\n", + " 20.74524879, 20.85200119, 20.26188469, 20.82903862, 20.02412415,\n", + " 20.97918129, 20.71551132, 20.60189629, 20.11310196, 20.53161049])" + ] + }, + "execution_count": 94, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# In this view, class attributes are NOT special types; they're just numbers.\n", + "\n", + "tree.array(\"fTemperature\", entrystop=20)" + ] + }, + { + "cell_type": "code", + "execution_count": 95, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([[[ 1.54053164, 0.09474282, 1.52469206, 0. ],\n", + " [-0.13630907, 0.80078429, 1.70623565, 0. ],\n", + " [-1.16029346, 2.012362 , 4.02206421, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]],\n", + "\n", + " [[ 0.41865557, 1.60363352, -0.56923842, 0. ],\n", + " [ 0.06950195, 0.79105824, 2.0322361 , 0. ],\n", + " [ 0.05688119, 2.52811217, 3.91394544, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]],\n", + "\n", + " [[-1.24031985, 2.3477006 , -0.67482847, 0. ],\n", + " [ 1.22933233, 1.39499295, 2.17524433, 0. ],\n", + " [ 0.18559125, 2.40421987, 4.56326485, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]],\n", + "\n", + " [[-0.43785933, -0.05061727, 0.28988785, 0. ],\n", + " [-0.90204114, 0.88527524, 2.34751844, 0. ],\n", + " [ 0.3241719 , 0.79971647, 4.13229847, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]],\n", + "\n", + " [[-0.98912323, 0.97513503, 1.03762376, 0. ],\n", + " [-0.96955669, -0.05892833, 3.02420664, 0. ],\n", + " [ 1.10181248, 3.31268907, 6.04244947, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]],\n", + "\n", + " [[ 1.1283927 , 1.20095801, 0.7379719 , 0. ],\n", + " [ 0.32370013, 1.08198583, 2.96736264, 0. ],\n", + " [ 1.19329214, 2.01726198, 3.93975949, 0. ],\n", + " [ 0. , 0. , 0. , 0. ]]])" + ] + }, + "execution_count": 95, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Fixed-width matrices are multidimensional arrays,\n", + "\n", + "tree.array(\"fMatrix[4][4]\", entrystop=6)" + ] + }, + { + "cell_type": "code", + "execution_count": 96, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([(1.1, 1, 97), (2.2, 2, 98), (3.3, 3, 99), (4. , 4, 100),\n", + " (5.5, 5, 101)], dtype=[('x', '" + ] + }, + "execution_count": 97, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# and anything in variable-length lists is a JaggedArray,\n", + "\n", + "tree.array(\"fTracks.fMass2\", entrystop=6)" + ] + }, + { + "cell_type": "code", + "execution_count": 98, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 98, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# even if it's fixed-width within jagged or whatever.\n", + "\n", + "tree.array(\"fTracks.fTArray[3]\", entrystop=6)" + ] + }, + { + "cell_type": "code", + "execution_count": 99, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + " ] at 0x791849fe97b8>" + ] + }, + "execution_count": 99, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# There are some types that ROOT does not split because they are too complex.\n", + "# For example, *histograms* inside a TTree:\n", + "\n", + "tree.array(\"fH\", entrystop=6)" + ] + }, + { + "cell_type": "code", + "execution_count": 100, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "b'Event Histogram'\n", + "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0.]\n", + "b'Event Histogram'\n", + "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0.]\n", + "b'Event Histogram'\n", + "[0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 1. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0. 0.\n", + " 0. 0. 0. 0.]\n", + "\n", + "...\n", + "\n", + "b'Event Histogram'\n", + "[14. 18. 14. 11. 15. 13. 12. 13. 8. 8. 9. 10. 10. 7. 7. 10. 8. 12.\n", + " 6. 8. 7. 9. 10. 12. 10. 11. 10. 10. 10. 8. 14. 13. 9. 7. 12. 10.\n", + " 7. 6. 9. 13. 11. 8. 10. 9. 7. 4. 7. 10. 8. 8. 9. 9. 7. 12.\n", + " 11. 9. 10. 7. 10. 13. 13. 11. 9. 9. 8. 8. 10. 12. 7. 5. 9. 10.\n", + " 12. 13. 10. 14. 10. 10. 8. 12. 12. 11. 16. 12. 8. 12. 7. 9. 8. 7.\n", + " 10. 7. 11. 11. 8. 13. 9. 8. 14. 16.]\n", + "b'Event Histogram'\n", + "[14. 18. 14. 11. 15. 13. 12. 13. 8. 8. 9. 10. 10. 7. 8. 10. 8. 12.\n", + " 6. 8. 7. 9. 10. 12. 10. 11. 10. 10. 10. 8. 14. 13. 9. 7. 12. 10.\n", + " 7. 6. 9. 13. 11. 8. 10. 9. 7. 4. 7. 10. 8. 8. 9. 9. 7. 12.\n", + " 11. 9. 10. 7. 10. 13. 13. 11. 9. 9. 8. 8. 10. 12. 7. 5. 9. 10.\n", + " 12. 13. 10. 14. 10. 10. 8. 12. 12. 11. 16. 12. 8. 12. 7. 9. 8. 7.\n", + " 10. 7. 11. 11. 8. 13. 9. 8. 14. 16.]\n", + "b'Event Histogram'\n", + "[14. 18. 14. 11. 15. 13. 12. 13. 8. 8. 9. 10. 10. 7. 8. 10. 8. 12.\n", + " 6. 8. 7. 9. 10. 12. 10. 11. 10. 10. 10. 8. 14. 13. 9. 7. 12. 10.\n", + " 7. 6. 9. 13. 11. 8. 10. 9. 7. 4. 7. 10. 8. 8. 9. 9. 7. 12.\n", + " 11. 9. 10. 7. 10. 13. 13. 11. 9. 9. 8. 8. 10. 12. 7. 5. 9. 10.\n", + " 12. 13. 10. 14. 10. 10. 8. 12. 12. 11. 16. 12. 8. 12. 7. 9. 9. 7.\n", + " 10. 7. 11. 11. 8. 13. 9. 8. 14. 16.]\n" + ] + } + ], + "source": [ + "# Uproot can read objects like this because ROOT describes their layout in\n", + "# \"streamers;\" uproot reads the (most common types of) streamers and generates\n", + "# Python classes, some of which have specialized, high-level methods.\n", + "\n", + "for histogram in tree.array(\"fH\", entrystop=3):\n", + " print(histogram.title)\n", + " print(histogram.values)\n", + "print(\"\\n...\\n\")\n", + "for histogram in tree.array(\"fH\", entrystart=-3):\n", + " print(histogram.title)\n", + " print(histogram.values)" + ] + }, + { + "cell_type": "code", + "execution_count": 101, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([2.000e+00, 3.000e+00, 1.000e+00, 1.000e+00, 2.000e+00, 4.000e+00,\n", + " 6.000e+00, 1.200e+01, 8.000e+00, 9.000e+00, 1.500e+01, 1.500e+01,\n", + " 3.100e+01, 3.500e+01, 4.000e+01, 6.400e+01, 6.400e+01, 8.100e+01,\n", + " 1.080e+02, 1.240e+02, 1.560e+02, 1.650e+02, 2.090e+02, 2.620e+02,\n", + " 2.970e+02, 3.920e+02, 4.320e+02, 4.660e+02, 5.210e+02, 6.040e+02,\n", + " 6.570e+02, 7.880e+02, 9.030e+02, 1.079e+03, 1.135e+03, 1.160e+03,\n", + " 1.383e+03, 1.458e+03, 1.612e+03, 1.770e+03, 1.868e+03, 1.861e+03,\n", + " 1.946e+03, 2.114e+03, 2.175e+03, 2.207e+03, 2.273e+03, 2.276e+03,\n", + " 2.329e+03, 2.325e+03, 2.381e+03, 2.417e+03, 2.364e+03, 2.284e+03,\n", + " 2.188e+03, 2.164e+03, 2.130e+03, 1.940e+03, 1.859e+03, 1.763e+03,\n", + " 1.700e+03, 1.611e+03, 1.459e+03, 1.390e+03, 1.237e+03, 1.083e+03,\n", + " 1.046e+03, 8.880e+02, 7.520e+02, 7.420e+02, 6.730e+02, 5.550e+02,\n", + " 5.330e+02, 3.660e+02, 3.780e+02, 2.720e+02, 2.560e+02, 2.000e+02,\n", + " 1.740e+02, 1.320e+02, 1.180e+02, 1.000e+02, 8.900e+01, 8.600e+01,\n", + " 3.900e+01, 3.700e+01, 2.500e+01, 2.300e+01, 2.000e+01, 1.600e+01,\n", + " 1.400e+01, 9.000e+00, 1.300e+01, 8.000e+00, 2.000e+00, 2.000e+00,\n", + " 6.000e+00, 1.000e+00, 0.000e+00, 1.000e+00], dtype=float32),\n", + " array([-4. , -3.92, -3.84, -3.76, -3.68, -3.6 , -3.52, -3.44, -3.36,\n", + " -3.28, -3.2 , -3.12, -3.04, -2.96, -2.88, -2.8 , -2.72, -2.64,\n", + " -2.56, -2.48, -2.4 , -2.32, -2.24, -2.16, -2.08, -2. , -1.92,\n", + " -1.84, -1.76, -1.68, -1.6 , -1.52, -1.44, -1.36, -1.28, -1.2 ,\n", + " -1.12, -1.04, -0.96, -0.88, -0.8 , -0.72, -0.64, -0.56, -0.48,\n", + " -0.4 , -0.32, -0.24, -0.16, -0.08, 0. , 0.08, 0.16, 0.24,\n", + " 0.32, 0.4 , 0.48, 0.56, 0.64, 0.72, 0.8 , 0.88, 0.96,\n", + " 1.04, 1.12, 1.2 , 1.28, 1.36, 1.44, 1.52, 1.6 , 1.68,\n", + " 1.76, 1.84, 1.92, 2. , 2.08, 2.16, 2.24, 2.32, 2.4 ,\n", + " 2.48, 2.56, 2.64, 2.72, 2.8 , 2.88, 2.96, 3.04, 3.12,\n", + " 3.2 , 3.28, 3.36, 3.44, 3.52, 3.6 , 3.68, 3.76, 3.84,\n", + " 3.92, 4. ]))" + ] + }, + "execution_count": 101, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# As we've seen, histograms have some convenience methods.\n", + "# They're mostly for conversion to other formats, like Numpy.\n", + "# \n", + "# Numpy \"histograms\" are a 2-tuple of counts and edges.\n", + "\n", + "uproot.open(\"http://scikit-hep.org/uproot/examples/\"\n", + " \"hepdata-example.root\")[\"hpx\"].numpy()" + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " ...,\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.],\n", + " [0., 0., 0., ..., 0., 0., 0.]], dtype=float32),\n", + " [(array([-4. , -3.8, -3.6, -3.4, -3.2, -3. , -2.8, -2.6, -2.4, -2.2, -2. ,\n", + " -1.8, -1.6, -1.4, -1.2, -1. , -0.8, -0.6, -0.4, -0.2, 0. , 0.2,\n", + " 0.4, 0.6, 0.8, 1. , 1.2, 1.4, 1.6, 1.8, 2. , 2.2, 2.4,\n", + " 2.6, 2.8, 3. , 3.2, 3.4, 3.6, 3.8, 4. ]),\n", + " array([-4. , -3.8, -3.6, -3.4, -3.2, -3. , -2.8, -2.6, -2.4, -2.2, -2. ,\n", + " -1.8, -1.6, -1.4, -1.2, -1. , -0.8, -0.6, -0.4, -0.2, 0. , 0.2,\n", + " 0.4, 0.6, 0.8, 1. , 1.2, 1.4, 1.6, 1.8, 2. , 2.2, 2.4,\n", + " 2.6, 2.8, 3. , 3.2, 3.4, 3.6, 3.8, 4. ]))])" + ] + }, + "execution_count": 102, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Similarly for 2-dimensional histograms.\n", + "\n", + "uproot.open(\"http://scikit-hep.org/uproot/examples/hepdata-example.root\")[\"hpxpy\"].numpy()" + ] + }, + { + "cell_type": "code", + "execution_count": 103, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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countvariance
Real-Time to write versus time
[-inf, 0.0)0.0218390.000477
[0.0, 1.0)0.3335220.111237
[1.0, 2.0)0.3040300.092434
[2.0, 3.0)0.3245190.105313
[3.0, 4.0)0.3509730.123182
[4.0, 5.0)0.3689420.136118
[5.0, 6.0)0.3072830.094423
[6.0, 7.0)0.3068120.094134
[7.0, 8.0)0.3415630.116665
[8.0, 9.0)0.1615080.026085
\n", + "
" + ], + "text/plain": [ + " count variance\n", + "Real-Time to write versus time \n", + "[-inf, 0.0) 0.021839 0.000477\n", + "[0.0, 1.0) 0.333522 0.111237\n", + "[1.0, 2.0) 0.304030 0.092434\n", + "[2.0, 3.0) 0.324519 0.105313\n", + "[3.0, 4.0) 0.350973 0.123182\n", + "[4.0, 5.0) 0.368942 0.136118\n", + "[5.0, 6.0) 0.307283 0.094423\n", + "[6.0, 7.0) 0.306812 0.094134\n", + "[7.0, 8.0) 0.341563 0.116665\n", + "[8.0, 9.0) 0.161508 0.026085" + ] + }, + "execution_count": 103, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# It can also be useful to turn histograms into Pandas DataFrames (note the IntervalIndex).\n", + "\n", + "uproot.open(\"http://scikit-hep.org/uproot/examples/Event.root\")[\"htime\"].pandas()" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "dependent_variables:\n", + "- header:\n", + " name: counts\n", + " units: null\n", + " qualifiers: []\n", + " values:\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.33352208137512207\n", + " value: 0.33352208137512207\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.3040299415588379\n", + " value: 0.3040299415588379\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.32451915740966797\n", + " value: 0.32451915740966797\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.35097289085388184\n", + " value: 0.35097289085388184\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.3689420223236084\n", + " value: 0.3689420223236084\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.3072829246520996\n", + " value: 0.3072829246520996\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.306812047958374\n", + " value: 0.306812047958374\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.34156298637390137\n", + " value: 0.34156298637390137\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.16150808334350586\n", + " value: 0.16150808334350586\n", + " - errors:\n", + " - label: stat\n", + " symerror: 0.0\n", + " value: 0.0\n", + "independent_variables:\n", + "- header:\n", + " name: Real-Time to write versus time\n", + " units: null\n", + " values:\n", + " - high: 1.0\n", + " low: 0.0\n", + " - high: 2.0\n", + " low: 1.0\n", + " - high: 3.0\n", + " low: 2.0\n", + " - high: 4.0\n", + " low: 3.0\n", + " - high: 5.0\n", + " low: 4.0\n", + " - high: 6.0\n", + " low: 5.0\n", + " - high: 7.0\n", + " low: 6.0\n", + " - high: 8.0\n", + " low: 7.0\n", + " - high: 9.0\n", + " low: 8.0\n", + " - high: 10.0\n", + " low: 9.0\n", + "\n" + ] + } + ], + "source": [ + "# Or HEPData's YAML format. As Python objects, it's just a little work to make different formats.\n", + "\n", + "print(uproot.open(\"http://scikit-hep.org/uproot/examples/Event.root\")[\"htime\"].hepdata())" + ] + }, + { + "cell_type": "code", + "execution_count": 105, + "metadata": {}, + "outputs": [], + "source": [ + "# At the moment, only two kinds of objects can be *written* to ROOT files:\n", + "# TObjString and histograms.\n", + "# \n", + "# To write, open a file for writing (create/recreate/update) and assign to it\n", + "# like a dict:\n", + "\n", + "file = uproot.recreate(\"tmp.root\", compression=uproot.ZLIB(4))\n", + "file[\"name\"] = \"Some object, like a TObjString.\"" + ] + }, + { + "cell_type": "code", + "execution_count": 106, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'Some object, like a TObjString.'" + ] + }, + "execution_count": 106, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import ROOT\n", + "\n", + "pyroot_file = ROOT.TFile(\"tmp.root\")\n", + "pyroot_file.Get(\"name\")" + ] + }, + { + "cell_type": "code", + "execution_count": 107, + "metadata": {}, + "outputs": [], + "source": [ + "# During assignment, uproot recognizes Pythonic types, such as Numpy histograms.\n", + "\n", + "file[\"from_numpy\"] = numpy.histogram(numpy.random.normal(0, 1, 10000))" + ] + }, + { + "cell_type": "code", + "execution_count": 108, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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MI6QAmEZIATCNkAJgGiEFwLT/Av2s9ws48hxMAAAAAElFTkSuQmCC\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pyroot_file = ROOT.TFile(\"tmp.root\") # refresh the PyROOT file\n", + "pyroot_hist = pyroot_file.Get(\"from_numpy\")\n", + "\n", + "canvas = ROOT.TCanvas(\"canvas\", \"\", 400, 300)\n", + "pyroot_hist.Draw(\"hist\")\n", + "canvas.Draw()" + ] + }, + { + "cell_type": "code", + "execution_count": 109, + "metadata": {}, + "outputs": [], + "source": [ + "# 2-dimensional Numpy histograms.\n", + "\n", + "file[\"from_numpy2d\"] = numpy.histogram2d(numpy.random.normal(0, 1, 10000), numpy.random.normal(0, 1, 10000))" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "pyroot_file = ROOT.TFile(\"tmp.root\") # refresh the PyROOT file\n", + "pyroot_hist = pyroot_file.Get(\"from_numpy2d\")\n", + "\n", + "pyroot_hist.Draw()\n", + "canvas.Draw()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/04-accelerating-python.ipynb b/04-accelerating-python.ipynb new file mode 100644 index 0000000..63f31d6 --- /dev/null +++ b/04-accelerating-python.ipynb @@ -0,0 +1,2129 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "# Accelerating Python\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### 1. Vertical scaling (making a single thread faster)\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "

Apart from clever algorithms, the speed of a program is determined by how laden it is with work unrelated to its main task.

\n", + "\n", + "
\n", + "\n", + "

Python is slower than C because of dynamic type checking, garbage collection, everything-is-a-hashtable, pointer chasing, string equality checks...

\n", + "\n", + "
" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Compare to Java, which has garbage collection but not dynamic type checking, and C, which has neither (on a variety of benchmark algorithms).

\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

If you care about speed more than ease of development, use C or C++ (or Rust!).

\n", + "\n", + "
\n", + "\n", + "

If you want to use Python for all of its conveniences—dynamic type checking, garbage collection, everything-is-a-hashtable, interactive development and debugging—and need to speed up a critical section, there are ways to do it.

\n", + "\n", + "
\n", + "\n", + "

But you have to give up Python's dynamism in that section.

\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "Pointy(1, 2)" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Some wacky things you can do to types and objects in Python:\n", + "class Point:\n", + " def __init__(self, x, y):\n", + " self.x, self.y = x, y\n", + "p = Point(1, 2)\n", + "\n", + "# dynamically add an attribute to an instance (attributes are really a hashtable)\n", + "p.z = 3\n", + "\n", + "# dynamically add a method to a class (class is a hashtable of functions)\n", + "Point.mag2 = lambda self: self.x**2 + self.y**2 + self.z**2\n", + "p.mag2()\n", + "\n", + "# dynamically add a method to an instance (differs only in assigning \"self\")\n", + "p.mag = (lambda self: self.mag2()**0.5).__get__(p)\n", + "p.mag()\n", + "\n", + "class Pointy(Point):\n", + " def __repr__(self):\n", + " return \"Pointy({0}, {1})\".format(self.x, self.y)\n", + "\n", + "# dynamically change the class of an object (type is just an attribute)\n", + "p.__class__ = Pointy\n", + "p" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "<__main__.Point object at 0x7b6d2d60a940>\n", + "\n", + "{'x': 1, 'y': 2}\n", + "\n", + "{'x': 1, 'y': 2}\n" + ] + } + ], + "source": [ + "# That's because in Python, this:\n", + "\n", + "print()\n", + "print(Point(1, 2))\n", + "\n", + "# is not fundamentally different from this:\n", + "\n", + "print()\n", + "print({\"x\": 1, \"y\": 2})\n", + "\n", + "# as you can see by this:\n", + "\n", + "print()\n", + "print(Point(1, 2).__dict__)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

As a statically compiled program, Python has only one data type, PyObject* with a pointer to its runtime type, which is yet another PyObject*.

\n", + "\n", + "
\n", + "\n", + "

That gives us the flexibility to do all the wacky things on the previous slide, but at a runtime cost of checking those types every time they are used.

\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "ename": "TypeError", + "evalue": "can only concatenate str (not \"int\") to str", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mx\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m\"hello\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# do an operation on x that only works for integers\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mx\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;31mTypeError\u001b[0m: can only concatenate str (not \"int\") to str" + ] + } + ], + "source": [ + "# x is an integer\n", + "x = 0\n", + "\n", + "for i in range(1000000):\n", + " # in the millionth step, replace x with a string\n", + " if i == 999999:\n", + " x = \"hello\"\n", + " # do an operation on x that only works for integers\n", + " x += 1" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "ename": "TypingError", + "evalue": "Failed in nopython mode pipeline (step: nopython frontend)\nCannot unify int64 and Literal[str](hello) for 'x', defined at (5)\n\nFile \"\", line 5:\ndef f():\n x = 0\n ^\n\n[1] During: typing of assignment at (9)\n\nFile \"\", line 9:\ndef f():\n \n if i == 999999:\n x = \"hello\"\n ^\n\nThis is not usually a problem with Numba itself but instead often caused by\nthe use of unsupported features or an issue in resolving types.\n\nTo see Python/NumPy features supported by the latest release of Numba visit:\nhttp://numba.pydata.org/numba-doc/dev/reference/pysupported.html\nand\nhttp://numba.pydata.org/numba-doc/dev/reference/numpysupported.html\n\nFor more information about typing errors and how to debug them visit:\nhttp://numba.pydata.org/numba-doc/latest/user/troubleshoot.html#my-code-doesn-t-compile\n\nIf you think your code should work with Numba, please report the error message\nand traceback, along with a minimal reproducer at:\nhttps://github.com/numba/numba/issues/new\n", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mTypingError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 12\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 14\u001b[0;31m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/numba/dispatcher.py\u001b[0m in \u001b[0;36m_compile_for_args\u001b[0;34m(self, *args, **kws)\u001b[0m\n\u001b[1;32m 349\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpatch_message\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 350\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 351\u001b[0;31m \u001b[0merror_rewrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'typing'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 352\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0merrors\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mUnsupportedError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 353\u001b[0m \u001b[0;31m# Something unsupported is present in the user code, add help info\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/numba/dispatcher.py\u001b[0m in \u001b[0;36merror_rewrite\u001b[0;34m(e, issue_type)\u001b[0m\n\u001b[1;32m 316\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 317\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 318\u001b[0;31m \u001b[0mreraise\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 319\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 320\u001b[0m \u001b[0margtypes\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/numba/six.py\u001b[0m in \u001b[0;36mreraise\u001b[0;34m(tp, value, tb)\u001b[0m\n\u001b[1;32m 656\u001b[0m \u001b[0mvalue\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 657\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__traceback__\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtb\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 658\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 659\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 660\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mTypingError\u001b[0m: Failed in nopython mode pipeline (step: nopython frontend)\nCannot unify int64 and Literal[str](hello) for 'x', defined at (5)\n\nFile \"\", line 5:\ndef f():\n x = 0\n ^\n\n[1] During: typing of assignment at (9)\n\nFile \"\", line 9:\ndef f():\n \n if i == 999999:\n x = \"hello\"\n ^\n\nThis is not usually a problem with Numba itself but instead often caused by\nthe use of unsupported features or an issue in resolving types.\n\nTo see Python/NumPy features supported by the latest release of Numba visit:\nhttp://numba.pydata.org/numba-doc/dev/reference/pysupported.html\nand\nhttp://numba.pydata.org/numba-doc/dev/reference/numpysupported.html\n\nFor more information about typing errors and how to debug them visit:\nhttp://numba.pydata.org/numba-doc/latest/user/troubleshoot.html#my-code-doesn-t-compile\n\nIf you think your code should work with Numba, please report the error message\nand traceback, along with a minimal reproducer at:\nhttps://github.com/numba/numba/issues/new\n" + ] + } + ], + "source": [ + "import numba\n", + "\n", + "@numba.jit(nopython=True)\n", + "def f():\n", + " x = 0\n", + " for i in range(1000000):\n", + " # in the millionth step, replace x with a string\n", + " if i == 999999:\n", + " x = \"hello\"\n", + " # do an operation on x that only works for integers\n", + " x += 1\n", + " return x\n", + "\n", + "f()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "ename": "AttributeError", + "evalue": "f", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 15\u001b[0m }\"\"\")\n\u001b[1;32m 16\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 17\u001b[0;31m \u001b[0mROOT\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", + "\u001b[0;32m~/miniconda3/lib/python3.7/site-packages/ROOT.py\u001b[0m in \u001b[0;36m__getattr2\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m 683\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 684\u001b[0m \u001b[0;31m# reaching this point means failure ...\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 685\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mAttributeError\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mname\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 686\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 687\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m__delattr__\u001b[0m\u001b[0;34m(\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m \u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", + "\u001b[0;31mAttributeError\u001b[0m: f" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[1minput_line_33:7:17: \u001b[0m\u001b[0;1;31merror: \u001b[0m\u001b[1massigning to 'int' from incompatible type 'const char [6]'\u001b[0m\n", + " x = \"hello\";\n", + "\u001b[0;1;32m ^~~~~~~\n", + "\u001b[0m" + ] + } + ], + "source": [ + "import ROOT\n", + "\n", + "ROOT.gInterpreter.Declare(\"\"\"\n", + "int f() {\n", + " int x = 0;\n", + " for (int i = 0; i < 1000000; i++) {\n", + " // in the millionth step, replace x with a string\n", + " if (i == 999999) {\n", + " x = \"hello\";\n", + " }\n", + " // do an operation on x that only works for integers\n", + " x += 1;\n", + " }\n", + " return x;\n", + "}\"\"\")\n", + "\n", + "ROOT.f()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

My unsurprising, conventional answer to \"how do I make it fast?\"

\n", + "\n", + "
    \n", + "
  1. Determine all data types statically: i.e. one variable ↔ one type and all values in a list/array have the same type.\n", + "
  2. Take advantage of the static types by converting the program into machine code: i.e. verify those types and generate code without runtime type-checks.\n", + "
\n", + "\n", + "
\n", + "\n", + "

We usually call this \"compiling.\"

\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

But: \"compiling\" does not necessarily mean \"rewrite in C or C++.\"

\n", + "\n", + "
    \n", + "
  • Any language can be compiled.\n", + "
  • Compilation does not need to be a separate phase from running the program.\n", + "
  • The compiled section can be as little or as much as you want.\n", + "
  • If you're using Python to organize your analysis, focus only on the part that needs to be fast. Which part scales with the number of events?\n", + "
\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

Numba is a just-in-time compiler of Python code.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "CPUDispatcher()" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import numpy\n", + "\n", + "@numba.jit(nopython=True)\n", + "def mag(xarray, yarray):\n", + " out = numpy.empty(min(len(xarray), len(yarray)))\n", + " \n", + " for i in range(len(out)):\n", + " out[i] = numpy.sqrt(xarray[i]**2 + yarray[i]**2)\n", + " \n", + " return out\n", + "\n", + "mag" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "mag.overloads.keys() = []\n", + "\n", + "mag(a, a).sum() = 707106074079.7664\n", + "mag.overloads.keys() = [(array(int32, 1d, C), array(int32, 1d, C))]\n", + "\n", + "mag(a, b).sum() = 707106074079.7664\n", + "mag.overloads.keys() = [(array(int32, 1d, C), array(int32, 1d, C)),\n", + " (array(int32, 1d, C), array(int64, 1d, C))]\n", + "\n", + "mag(b, b).sum() = 707106074079.7664\n", + "mag.overloads.keys() = [(array(int32, 1d, C), array(int32, 1d, C)),\n", + " (array(int32, 1d, C), array(int64, 1d, C)),\n", + " (array(int64, 1d, C), array(int64, 1d, C))]\n" + ] + } + ], + "source": [ + "a = numpy.arange(1000000, dtype=numpy.int32)\n", + "b = numpy.arange(1000000, dtype=numpy.int64)\n", + "\n", + "gap = \",\\n \"\n", + "print(f\"mag.overloads.keys() = [{gap.join(str(x) for x in mag.overloads.keys())}]\")\n", + "print(f\"\\nmag(a, a).sum() = {mag(a, a).sum()}\")\n", + "print(f\"mag.overloads.keys() = [{gap.join(str(x) for x in mag.overloads.keys())}]\")\n", + "print(f\"\\nmag(a, b).sum() = {mag(a, b).sum()}\")\n", + "print(f\"mag.overloads.keys() = [{gap.join(str(x) for x in mag.overloads.keys())}]\")\n", + "print(f\"\\nmag(b, b).sum() = {mag(b, b).sum()}\")\n", + "print(f\"mag.overloads.keys() = [{gap.join(str(x) for x in mag.overloads.keys())}]\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

Numba compiles a subset of the Python language and a subset of Numpy functions to machine code (through LLVM).

\n", + "\n", + "
\n", + "\n", + "

It also sets up conversions between Python/Numpy and the compiled code.

\n", + "\n", + "
\n", + "\n", + "

A good way to use it: develop in Python because it's easy, eliminate dynamic features from the part that needs to be fast, and try @numba.jit until successful.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Numba has a particular affinity for Numpy (and an unfortunate name).\n", + "#\n", + "# Most of the type declarations (int this, float that) come from Numpy dtypes.\n", + "\n", + "# numba.vectorize lets you define a Numpy ufunc from a scalars → scalar function:\n", + "@numba.vectorize\n", + "def mag(x, y):\n", + " return numpy.sqrt(x**2 + y**2)\n", + "\n", + "mag(a, b)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(, 135707916558384)" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Given a signature, it can even compile Python into a pure C function\n", + "# (accessible via a function pointer).\n", + "\n", + "@numba.cfunc(numba.float64(numba.int32, numba.int32))\n", + "def mag(x, y):\n", + " return numpy.sqrt(x**2 + y**2)\n", + "\n", + "mag, mag.address" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

ROOT does many things, but one of them is automatically binding C++ to Python.

\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [], + "source": [ + "%%cpp -d\n", + "\n", + "//# Of course, you can also write the part that needs to be fast in C++.\n", + "\n", + "void mag(int n, double* xarray, double* yarray, double* out) {\n", + " for (int i = 0; i < n; i++) {\n", + " out[i] = sqrt(xarray[i]*xarray[i] + yarray[i]*yarray[i]);\n", + " }\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "xarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "yarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "out = numpy.empty(1000000, dtype=numpy.float64)\n", + "\n", + "ROOT.mag(len(out), xarray, yarray, out)\n", + "\n", + "out" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

After you import ROOT,

\n", + "\n", + "
    \n", + "
  • %%cpp at the top of a Jupyter cell evaluates as a line of C++ ROOT,\n", + "
  • %%cpp -d at the top of a Jupyter cell defines a C++ function,\n", + "
  • ROOT.gInterpreter.ProcessLine in Python evaluates a line of C++ ROOT,\n", + "
  • ROOT.gInterpreter.Declare in Python defines a C++ function,\n", + "
\n", + "\n", + "

and PyROOT lets you call C++ functions from Python.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "
\n", + "\n", + "\n", + "\n", + "
" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "25.0" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\u001b[1minput_line_38:3:12: \u001b[0m\u001b[0;1;31merror: \u001b[0m\u001b[1mredefinition of 'cpp_func'\u001b[0m\n", + " double cpp_func(double x) {\n", + "\u001b[0;1;32m ^\n", + "\u001b[0m\u001b[1minput_line_36:3:12: \u001b[0m\u001b[0;1;30mnote: \u001b[0mprevious definition is here\u001b[0m\n", + " double cpp_func(double x) {\n", + "\u001b[0;1;32m ^\n", + "\u001b[0m" + ] + } + ], + "source": [ + "# You can't redefine C++ functions, which makes interactive work difficult.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "ROOT.gInterpreter.Declare(r\"\"\"\n", + "\n", + " double cpp_func(double x) {\n", + " return x*x;\n", + " }\n", + "\n", + "\"\"\")\n", + "cpp_func = ROOT.cpp_func\n", + "\n", + "cpp_func(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "25.0" + ] + }, + "execution_count": 17, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# You can't redefine C++ functions, which makes interactive work difficult.\n", + "# \n", + "# Here's a way to make a redefinable function:\n", + "\n", + "pyname = \"cpp_func\"\n", + "cppname = pyname + \"_%d\" % sum(1 if x.startswith(pyname) else 0 for x in dir(ROOT))\n", + "ROOT.gInterpreter.Declare(r\"\"\"\n", + "\n", + " double \"\"\" + cppname + r\"\"\"(double x) {\n", + " return x*x;\n", + " }\n", + "\n", + "\"\"\")\n", + "exec(f\"{pyname} = ROOT.{cppname}\")\n", + "\n", + "cpp_func(5)" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0., 1., 4., 9., 16., 25., 36., 49., 64., 81.])" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Also, you need to be very careful about data types because ROOT does not\n", + "# read them off of Numpy arrays.\n", + "\n", + "if not hasattr(ROOT, \"assumes_double\"):\n", + " ROOT.gInterpreter.Declare(\"\"\"\n", + "void assumes_double(int n, double* xarray, double* out) {\n", + " for (int i = 0; i < n; i++) {\n", + " out[i] = xarray[i]*xarray[i];\n", + " }\n", + "}\n", + "\"\"\")\n", + "\n", + "xarray = numpy.arange(10, dtype=numpy.float64) # change to int64\n", + "out = numpy.empty(10, dtype=numpy.float64) # change to int64\n", + "\n", + "ROOT.assumes_double(10, xarray, out)\n", + "out" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# If you're sending arrays of data to and from ROOT, you should probably let\n", + "# ROOT control the type, size, and memory of those arrays as C++ std::vector.\n", + "\n", + "# a_vector = std::vector(1000000);\n", + "a_vector = ROOT.std.vector(\"double\")(1000000)\n", + "\n", + "# a_array only WRAPS it as a Numpy array.\n", + "a_array = numpy.asarray(a_vector)\n", + "\n", + "# Assigning to this Numpy array changes the memory owned by the std::vector.\n", + "a_array[:] = numpy.arange(1000000, dtype=numpy.float64)\n", + "\n", + "# See?\n", + "list(a_vector[:10])" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([ 0., 1., 4., 9., 16., 25., 36., 49., 64., 81.])" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "if not hasattr(ROOT, \"verifies_double\"):\n", + " ROOT.gInterpreter.Declare(\"\"\"\n", + "std::vector verifies_double(std::vector xarray) {\n", + " std::vector out;\n", + " out.reserve(xarray.size());\n", + " \n", + " for (int i = 0; i < xarray.size(); i++) {\n", + " out.push_back(xarray[i]*xarray[i]);\n", + " }\n", + " \n", + " return out; // safe because of C++ move semantics\n", + "}\n", + "\"\"\")\n", + "\n", + "a_vector = ROOT.std.vector(\"double\")(1000000) # change to \"int\"\n", + "a_array = numpy.asarray(a_vector)\n", + "a_array[:] = numpy.arange(1000000, dtype=numpy.float64)\n", + "\n", + "b_vector = ROOT.verifies_double(a_vector)\n", + "b_array = numpy.asarray(b_vector)\n", + "\n", + "b_array[:10]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

\n", + "\n", + "

Reminder: a Numpy object is a Python object that points to memory, maybe someone else's memory.

\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "a_array.flags.owndata = False\n", + "\n", + "a_vector[:10] = [0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]\n" + ] + } + ], + "source": [ + "# The Numpy object of the array does not \"own\" the data, so it does not try to\n", + "# delete it when it gets garbage collected.\n", + "\n", + "print(f\"a_array.flags.owndata = {a_array.flags.owndata}\")\n", + "\n", + "del a_array\n", + "\n", + "# Make sure the garbage collector deletes the Numpy object.\n", + "import gc\n", + "gc.collect()\n", + "\n", + "# The std::vector and its data still exist.\n", + "print(f\"\\na_vector[:10] = {[a_vector[i] for i in range(10)]}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "b_array[:10] = [ 0. 1. 4. 9. 16. 25. 36. 49. 64. 81.]\n", + "b_array[:10] = [100. 1. 4. 9. 16. 25. 36. 49. 64. 81.]\n", + "b_array[:10] = [100. 200. 4. 9. 16. 25. 36. 49. 64. 81.]\n", + "b_array[:10] = [100. 200. 300. 9. 16. 25. 36. 49. 64. 81.]\n", + "b_array[:10] = [100. 200. 300. 400. 16. 25. 36. 49. 64. 81.]\n", + "b_array[:10] = [100. 200. 300. 400. 500. 25. 36. 49. 64. 81.]\n" + ] + } + ], + "source": [ + "# But if you delete it on the C++ side, the Numpy object does not know!\n", + "b_vector.clear()\n", + "# b_vector.shrink_to_fit()\n", + "print(f\"b_array[:10] = {b_array[:10]}\")\n", + "\n", + "b_vector.push_back(100)\n", + "print(f\"b_array[:10] = {b_array[:10]}\")\n", + "\n", + "b_vector.push_back(200)\n", + "print(f\"b_array[:10] = {b_array[:10]}\")\n", + "\n", + "b_vector.push_back(300)\n", + "print(f\"b_array[:10] = {b_array[:10]}\")\n", + "\n", + "b_vector.push_back(400)\n", + "print(f\"b_array[:10] = {b_array[:10]}\")\n", + "\n", + "b_vector.push_back(500)\n", + "print(f\"b_array[:10] = {b_array[:10]}\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

pybind11 manually binds C++ to Python, suitable for production code.

\n", + "\n", + "

(I just want you to be aware of it.)

\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000e+00, 1.00000e+00, 4.00000e+00, ..., 9.99994e+11,\n", + " 9.99996e+11, 9.99998e+11])" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "open(\"cpp_calculate.cpp\", \"w\").write(r\"\"\"\n", + "#include \n", + "#include \n", + "void cpp_func(pybind11::array_t inarray, pybind11::array_t outarray) {\n", + " size_t N = inarray.request().size;\n", + " double *in = (double*)inarray.request().ptr;\n", + " double *out = (double*)outarray.request().ptr;\n", + " for (size_t i = 0; i < N; i++) {\n", + " out[i] = in[i] * in[i];\n", + " }\n", + "}\n", + "PYBIND11_MODULE(cpp_calculate, m) {\n", + " m.def(\"cpp_func\", &cpp_func, \"\");\n", + "}\n", + "\"\"\")\n", + "\n", + "import os\n", + "os.system(r\"c++ -Wall -shared -std=c++11 -fPIC -O3 `python -m pybind11 --includes` cpp_calculate.cpp -o cpp_calculate`python3-config --extension-suffix`\")\n", + "\n", + "import cpp_calculate\n", + "inarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "outarray = numpy.empty(1000000, dtype=numpy.float64)\n", + "cpp_calculate.cpp_func(inarray, outarray)\n", + "outarray" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "



\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

Cython lets you mix C++ and Python code in a half-and-half syntax.

\n", + "\n", + "

(I just want you to be aware of it.)

\n", + "\n", + "



" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": {}, + "outputs": [], + "source": [ + "%load_ext Cython" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + " \n", + " Cython: _cython_magic_cecd2a8bfd7e960023961ae04fa3521e.pyx\n", + " \n", + "\n", + "\n", + "

Generated by Cython 0.29.12

\n", + "

\n", + " Yellow lines hint at Python interaction.
\n", + " Click on a line that starts with a \"+\" to see the C code that Cython generated for it.\n", + "

\n", + "
+01: import cython, numpy
\n", + "
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+       "  __Pyx_GOTREF(__pyx_t_1);\n",
+       "  if (PyDict_SetItem(__pyx_d, __pyx_n_s_numpy, __pyx_t_1) < 0) __PYX_ERR(0, 1, __pyx_L1_error)\n",
+       "  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;\n",
+       "/* … */\n",
+       "  __pyx_t_1 = __Pyx_PyDict_NewPresized(0); if (unlikely(!__pyx_t_1)) __PYX_ERR(0, 1, __pyx_L1_error)\n",
+       "  __Pyx_GOTREF(__pyx_t_1);\n",
+       "  if (PyDict_SetItem(__pyx_d, __pyx_n_s_test, __pyx_t_1) < 0) __PYX_ERR(0, 1, __pyx_L1_error)\n",
+       "  __Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;\n",
+       "
 02: cimport numpy
\n", + "
 03: 
\n", + "
 04: @cython.boundscheck(False)
\n", + "
 05: @cython.wraparound(False)
\n", + "
+06: def cython_calculate(inarray, outarray):
\n", + "
/* Python wrapper */\n",
+       "static PyObject *__pyx_pw_46_cython_magic_cecd2a8bfd7e960023961ae04fa3521e_1cython_calculate(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/\n",
+       "static PyMethodDef __pyx_mdef_46_cython_magic_cecd2a8bfd7e960023961ae04fa3521e_1cython_calculate = {\"cython_calculate\", (PyCFunction)(void*)(PyCFunctionWithKeywords)__pyx_pw_46_cython_magic_cecd2a8bfd7e960023961ae04fa3521e_1cython_calculate, METH_VARARGS|METH_KEYWORDS, 0};\n",
+       "static PyObject *__pyx_pw_46_cython_magic_cecd2a8bfd7e960023961ae04fa3521e_1cython_calculate(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {\n",
+       "  PyObject *__pyx_v_inarray = 0;\n",
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+       "      Py_ssize_t kw_args;\n",
+       "      const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);\n",
+       "      switch (pos_args) {\n",
+       "        case  2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);\n",
+       "        CYTHON_FALLTHROUGH;\n",
+       "        case  1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);\n",
+       "        CYTHON_FALLTHROUGH;\n",
+       "        case  0: break;\n",
+       "        default: goto __pyx_L5_argtuple_error;\n",
+       "      }\n",
+       "      kw_args = PyDict_Size(__pyx_kwds);\n",
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+       "        case  0:\n",
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+       "        else goto __pyx_L5_argtuple_error;\n",
+       "        CYTHON_FALLTHROUGH;\n",
+       "        case  1:\n",
+       "        if (likely((values[1] = __Pyx_PyDict_GetItemStr(__pyx_kwds, __pyx_n_s_outarray)) != 0)) kw_args--;\n",
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+       "    } else {\n",
+       "      values[0] = PyTuple_GET_ITEM(__pyx_args, 0);\n",
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+       "    __pyx_v_inarray = values[0];\n",
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+       "  goto __pyx_L4_argument_unpacking_done;\n",
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+       "\n",
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+       "  __Pyx_LocalBuf_ND __pyx_pybuffernd_inarray_raw;\n",
+       "  __Pyx_Buffer __pyx_pybuffer_inarray_raw;\n",
+       "  __Pyx_LocalBuf_ND __pyx_pybuffernd_outarray_raw;\n",
+       "  __Pyx_Buffer __pyx_pybuffer_outarray_raw;\n",
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+       "  /* function exit code */\n",
+       "  __pyx_r = Py_None; __Pyx_INCREF(Py_None);\n",
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+       "
+07:     cdef numpy.ndarray[numpy.float64_t, ndim=1, mode="c"] inarray_raw = inarray
\n", + "
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+       "    __pyx_t_7 = __pyx_v_i;\n",
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+       "  }\n",
+       "
" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 25, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%cython --cplus -c-O3 -a\n", + "import cython, numpy\n", + "cimport numpy\n", + "\n", + "@cython.boundscheck(False)\n", + "@cython.wraparound(False)\n", + "def cython_calculate(inarray, outarray):\n", + " cdef numpy.ndarray[numpy.float64_t, ndim=1, mode=\"c\"] inarray_raw = inarray\n", + " cdef numpy.ndarray[numpy.float64_t, ndim=1, mode=\"c\"] outarray_raw = outarray\n", + " cdef int N = len(inarray)\n", + " for i in range(N):\n", + " outarray_raw[i] = inarray_raw[i] * inarray_raw[i]" + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000e+00, 1.00000e+00, 4.00000e+00, ..., 9.99994e+11,\n", + " 9.99996e+11, 9.99998e+11])" + ] + }, + "execution_count": 26, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "inarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "outarray = numpy.empty(1000000, dtype=numpy.float64)\n", + "\n", + "cython_calculate(inarray, outarray)\n", + "\n", + "outarray" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### 2. Horizontal scaling (distributing the work across threads)\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

Dask is a parallel processing framework for Numpy arrays.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "
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Array Chunk
Bytes 8.00 MB 800.00 kB
Shape (1000000,) (100000,)
Count 41 Tasks 10 Chunks
Type float64 numpy.ndarray
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" + ], + "text/plain": [ + "dask.array" + ] + }, + "execution_count": 27, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The following code computes NOTHING.\n", + "\n", + "import dask.array\n", + "\n", + "def compute(xarray, yarray):\n", + " return numpy.sqrt(xarray**2 + yarray**2)\n", + "\n", + "xarray = dask.array.from_array(numpy.arange(1000000, dtype=numpy.float64), 100000)\n", + "yarray = dask.array.from_array(numpy.arange(1000000, dtype=numpy.float64), 100000)\n", + "\n", + "outarray = compute(xarray, yarray)\n", + "outarray" + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 28, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The following computes it on all cores.\n", + "\n", + "outarray.compute()" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# What is \"outarray\"? It's a description of work to be done.\n", + "\n", + "outarray.visualize()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0" + ] + }, + "execution_count": 30, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# dask-schedulers and dask-workers could be running remotely...\n", + "\n", + "os.system(r\"dask-scheduler &\")\n", + "os.system(r\"dask-worker --nthreads 8 127.0.0.1:8786 &\")" + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\n", + "\n", + "
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" + ], + "text/plain": [ + "" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import dask.distributed\n", + "\n", + "maybe_remote = dask.distributed.Client(\"127.0.0.1:8786\")\n", + "maybe_remote" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Now we can run those same array operations anywhere, distributed by its \"chunks.\"\n", + "\n", + "outarray.compute(scheduler=maybe_remote)" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": {}, + "outputs": [], + "source": [ + "!killall dask-scheduler dask-worker" + ] + }, + { + "cell_type": "code", + "execution_count": 35, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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v+4url/hJ7PddYnK/v2fPHm3evJkXIcJ3OB/qDtPnQ7dt26bLL7/cSCwACIX6+npJcvK5gP7qDlP9dfHixQoEArr++utDGgdwEfNNd9iYb27fvl0jRowwFg+A/zAvd4fp34fzPE87d+7kEj8AsIjnNXeYfl6bP3+++vbtq2uuucZIPABAeGLf5Q7T50kWLFigSZMmKSMjI2jfk0v8cFFSU1OtvkRGkh588EEVFBRo48aNVvOIdM8++6x69OjBixcBdFpqaqq6deumPXv2GI995513qnv37vr5z39uPDY+sWnTJr399tt68MEHbacC+EZMTIxuvPFGoy88p17a55d6GRUVpdbWVttpAEBIpKenq6WlRVVVVVbi9+nTR1/+8pf11FNPUWstamlp0dNPP625c+eqV69ettMBLlp+fr7Wr1+vffv2hTwW9csNfqhfCQkJqqmpsZ0GgBCi/0QeP/QfIJIMHjxY48ePZ78QYfyyXwAiEecv0YbzlwAAAAAAAAD8hvmyG5gv+0tjY6NiY2Ntp9Eu9vtuML3fnz9/vnr27Klp06YZiQcEC+dD3WDjfOjWrVs1atQoI7EAIBQaGxsluXmJH/3VDSb7a0FBga655hr16NEjpHEAVzHfdIPp+WZra6tKS0s1cuRII/EA+BPzcjfY+H24jz76SHV1dVziBwCW8bzmBtPPawsWLNAtt9yimJgYI/EAAOGJfZcbTJ8naWlp0euvv678/Pygfl8u8cNFSU1NVVVVlZqbm63lcOONN2rChAl68sknreUQ6Y4dO6b//u//1re+9S3Fx8fbTgeAzwQCAWVkZKi8vNx47Pj4eD388MP65S9/qerqauPxccrjjz+u8ePHa9asWbZTAXwlPz9ff//734281JF66Qa/1MtAIMCgCkDYSk9PlyTt37/fWg6PPfaYdu7cqZdfftlaDpFu3rx52rVrl77zne/YTgW4JDfccIOSkpL06quvGolH/bLPD/UrKSlJtbW1ttMAEEL0n8jjh/4DRJr8/HzNnz/fyByX/YIb/LJfACIR5y8hcf4SAAAAAAAAgD8xX7aP+bL/nDhxwtlL/Njvu8H0fn/BggW6+eab1aVLFyPxgGDifKh9ps+HNjU1aefOnVy2AcDXGhsbFQgEnH0uoL/aZ6q/ep6nt99+W7m5uSGNA7iM+aZ9Nuabe/bsUUNDg0aMGGEkHgB/Yl7uBhu/D1dcXCxJXOIHAJbxvGaf6ee1iooKrV+/PugX7wAAIhP7LvtMnydZuXKlDh8+rFtuuSWo35dL/HBRUlNT1draqkOHDlnN45FHHtErr7yirVu3Ws0jUj377LOKjo7WN7/5TdupAPCpwYMHW7nET5IeeOABRUdH69e//rWV+JFu27ZtevXVV/WDH/xAgUDAdjqAr8yaNUtxcXF6/fXXjcSjXtrlp3oZFRUlz/NspwEAIZGWlibJ7iV+Q4cO1ezZs/XTn/6UemuB53l64okndOedd2r48OG20wEuSWxsrHJzc7VgwQIj8ahfdvmlfsXFxam+vt52GgBCiP4TWfzSf4BIc9ttt+nAgQNat26dkXjsF+zy034BiEScv4TE+UsAAAAAAAAA/sV82S7my/5z4sQJdevWzXYa58R+3y7T+/2qqir9/e9/16233hryWEAocD7ULhvnQ0tKStTU1KRRo0YZiQcAodDY2KjY2Fhnz3PSX+0y2V83bdqkyspKLvFDxGO+aZeN+eb27dsliUv8AFwQ83K7bP0+XHFxsXr37q2+ffsaiwkAaB/Pa3aZfl5buHChEhISdP311xuJBwAIb+y77LJxnmTBggUaO3Zs0ONxiR8uSmpqqiSpsrLSah633367Lr/8cj311FNW84hEdXV1+vWvf62HHnpISUlJttMB4FODBg2ydolf9+7ddf/99+vZZ59VbW2tlRwi2U9+8hONGDFCN998s+1UAN+Ji4vTzJkzjb3wnHppl5/qZVRUlFpbW22nAQAhERcXp169eqmiosJqHo8++qi2bNmiN954w2oekWjhwoX68MMP9cgjj9hOBQiK/Px8FRYW6vDhw0biUb/s8Uv96tatm06cOGE7DQAhRv+JHH7pP0CkGT16tLKystgvRAg/7ReASMT5S3D+EgAAAAAAAICfMV+2h/myP504cUKxsbG20zgn9vt2md7vv/rqq+ratatmzpxpJB4QCpwPtcfG+dBt27YpOjra2EveACAUGhoanL7YW6K/2mSyvy5atEj9+/fX+PHjQx4LcBnzTXtszTe3b9+utLQ09ejRw1hMAP7EvNwuW78PV1xcrKysLKMxAQDt43nNHhvPawsWLFBeXp7zs1MAgH+w77LH9HkSz/P06quvKj8/P+jfm0v8cFHaXiJj+8XlgUBAjzzyiP72t79p8+bNVnOJND/72c/U1NSkhx56yHYqAHxs0KBB2rNnj7X4Dz/8sE6ePKn//M//tJZDJHrvvff04osv6gc/+IGiovg4ClyM/Px8LVu2TNXV1UbiUS/t8Fu9DAQCXOIHIKylp6dr//79VnMYO3asbr75Zj322GNqbm62mkskaWpq0ve//33ddtttGj16tO10gKC46aabFBMTo7feestIPOqXHX6qX3FxcWpoaLCdBoAQo/9EBj/1HyAS5efn6+WXXzYWj/2CHX7bLwCRiPOX4PwlAAAAAAAAAD9jvmwP82V/cv0SP4n9vi029vsLFizQrFmzlJCQYCQeEAqcD7XD1vnQbdu2KTMzU3FxccZiAkCwNTY2Ov8iavqrHab76+LFi5Wbm6tAIBDyWIDLmG/aY2u+uWPHDo0cOdJoTAD+xbzcDpu/D8clfgDgDp7X7DH9vFZdXa1Vq1aF5OIdAEDkYt9lh43zJO+++6727dun2267Lejfm7f04KIkJCQoKSlJlZWVtlPRl7/8ZWVnZ+vrX/86F0YYUlpaqqefflo//vGP1atXL9vpAPCxwYMHa+/evdbqd9++ffXDH/5QTz75pIqLi63kEGlaW1t1//33a/LkybrjjjtspwP41he+8AUFAgEtWrTISDzqpXl+rJdRUVHyPM92GgAQMunp6dZfqCxJTz/9tEpLS/WLX/zCdioR49lnn1VZWZmeeuop26kAQZOUlKTp06drwYIFxmJSv8zzU/3q1q2bGhsbbacBIMToP5HBT/0HiET5+fnas2eP3n//fSPx2C+Y58f9AhCJOH8Z2Th/CQAAAAAAACAcMF82j/myPzU1Nam1tdX5CzvY75tnY79fU1OjFStW8CJEhAXOh5pn63zotm3bdPnllxuNCQDB1tjY6IvLSOmv5pnsr8ePH9e6deuUm5sb8liAHzDfNM/mfHPHjh0aMWKE0ZgA/It5uXm2fx+OS/wAwC08r5ln43nt9ddfl+d5ysvLMxIPABA52HeZZ+M8yYIFCzRkyBCNHTs26N+bS/xw0VJTU514iUwgENBvf/tbvffee/rzn/9sO52I8PDDD2v48OH65je/aTsVAD43aNAgnThxQgcPHrSWw8MPP6wRI0booYcespZDJPnDH/6goqIi/epXv1IgELCdDuBbPXv21LRp0zR//nxjMamXZvmxXkZFRbHoAhDW0tPTtX//fttpaOjQofrOd76jH/3oR07kE+727dunxx9/XI8++qgyMzNtpwMEVX5+vpYsWaLa2loj8ahfZvmtfsXFxXGJHxAh6D/hzW/9B4hE2dnZGjBggF555RVjMdkvmOXH/QIQqTh/Gbk4fwkAAAAAAAAgHDBfNo/5sj+dOHFCkhQbG2s5kwtjv2+Wjf3+G2+8oebmZt10001G4gGhxPlQs2yeD922bZtGjRplNCYABFtjY6PzF3tL9FfTTPfXxYsXq7W1VZ/73OdCHgvwA+ab5tmcb+7YsUMjR440HheAfzEvN8vm78M1NDRo3759XOIHAA7hec08G89rCxYs0IwZM9SzZ09jMQEAkYF9l1m2zpPMnz9ft99+e0i+N5f44aK58hIZSRozZozuv/9+fec739Hhw4dtpxPW5s2bp4KCAv32t79VTEyM7XQA+NygQYMkSeXl5dZyiImJ0a9+9Su9/fbbRl9WGYmOHDmixx57TA8//LDGjRtnOx3A9+644w698cYbOn78uJF41Etz/FovA4EAl/gBCGtpaWnODOEfffRRpaam6tvf/rbtVMLev/zL/2PvPgOiutavga8ZhqZiI1YGLKB0YtQ0WxC7Ym9YIbkmxqgxiamvMZpiEnM1V2+MMc2CBewtJmpiuTZsaKQJiIqCvQCKUmaYeT/4l4SAijBz9jln1u/TDcx1r5Bkb87ez9nPG6hfvz7efvtt0VGILK5///4wGAzYtGmTZGNy/pKO0uYvJycn5OXliY5BRBLg+qNuSlt/iGyRRqPB4MGDERUVBbPZLMmYPF+QjlLPF4hsFesvbRPrL4mIiIiIiIiIiEhNuL8sHe4vK1d+fj4AZTTx4/m+dESd70dHR6Nz585wdXWVbEwia2J9qHRE1YcajUacOnUKfn5+ko5LRGRpSmniB3B9lZLU6+umTZvQtm1b1K5dW5LxiJSA+5vSEbm/efXqVdy4cQM+Pj6SjktEysb9cumIfh8uNTUVJpOJTfyIiGSGz2vSEfG8duvWLfz2228YOnSoJOMREZHt4XmXdETUkxw+fBhpaWkICwuzyp/PJn5UYXK6RAYAPvnkEzg4OOCdd94RHUW1bt68icmTJ+Oll17C888/LzoOEamAXq+HTqdDenq60Bzt2rVDeHg43njjDWRlZQnNomZvvvkmHB0dMW3aNNFRiFRh0KBBMJlMkl54zvlSGkqdL7VaLZv4EZGqubm5yaaJn6OjI/7zn/9g5cqV2LJli+g4qrVp0yasXbsW8+bNU8wLUkSP44knnkDnzp2xcuVKycbk/CUNJc5fTk5OxRfVEJG6cf1RLyWuP0S2atiwYTh9+jSOHDki2Zg8X5CGUs8XiGwV6y9tD+sviYiIiIiIiIiISI24v2x93F9WtoKCAgDKaOIH8HxfKiLO97Ozs7Ft2zarXV5EJALrQ6Uhsj40LS0NBQUFbOJHRIqnpCZ+XF+lIfX6WlRUhK1bt6J3795WH4tIabi/aX2i9zdPnjwJAPD19ZV8bCJSNu6XS0P0+3ApKSmws7ODp6enkPGJiOjB+LxmfaKe19atWweTyYS+fftKNiYREdkWnndJQ1Q9SVRUFLy8vNCqVSur/Pls4kcV1rBhQ1ldIlO9enV8//33WLJkCZYtWyY6juqYzWaEh4dDq9Xiq6++Eh2HiFTCzs4Oer0e586dEx0F//73vwEAL774Isxms+A06nN/ff7+++/h4uIiOg6RKtSqVQtdunRBdHS0pONyvrQuJc+XWq2W/04Qkao1bNgQ2dnZuHPnjugoAICePXti9OjRiIiIkE1zQTXJyMjASy+9hBdffBHdunUTHYfIaoYOHYqtW7fi5s2bko3J+cu6lDp/OTs7Iy8vT3QMIpII1x/1Uer6Q2SrWrduDW9vb0RFRUk6Ls8XrEvJ5wtEtor1l7aF9ZdERERERERERESkVtxfti7uLyvf/SZ+SmnYAfB839pEne+vW7cOANCvXz/JxiSSAutDrUt0fWhiYiK0Wi28vb0lH5uIyJLy8/Ph7OwsOka5cX21LhHr64EDB3D9+nU28SMqA/c3rUsO+5vJycmoXr06GjRoIGR8IlI27pdblxzeh0tJSUHjxo3h6OgoZHwiInowPq9Zl8jntejoaPTo0QO1a9eWdFwiIrItPO+yLlH1JCaTCatXr8aIESOsNgab+FGFNWjQQFaXyABA79698cYbb+DVV1/FyZMnRcdRldmzZ2Pr1q2Iioriww0RWVSjRo2Qnp4uOgaeeOIJrF69Gr/++ivmzp0rOo6qpKamYuLEiXj77bfRq1cv0XGIVCUsLAzbt2/HjRs3JBuT86X1KH2+1Gq1MJlMomMQEVmNm5sbAMhqP2z+/PmoU6cOhg0bBqPRKDqOahiNRgwbNgz16tXDvHnzRMchsqr+/fvDzs4O69evl3Rczl/WoeT5y8nJCfn5+aJjEJFEuP6oi5LXHyJbFhYWhujoaBQVFUk2Js8XrEfp5wtEtor1l7aF9ZdERERERERERESkZtxfth7uLyvf/SZ+Srr8lef71iPyfD86Oho9e/ZEjRo1JB2XSAqsD7UOOdSHJiUloUmTJqhSpYqQ8YmIgxsj/AAAIABJREFULCU/P19Rjb0Brq/WImp9/eWXX+Dp6cnGuEQPwP1N65HD/mZycjJ8fX2h0WiEjE9Eysb9cuuRy/twKSkp/D2ZiEjG+LxmPaKe165fv44dO3YgLCxMsjGJiMh28bzLOkTWk+zatQsXLlzAsGHDrDYGm/hRhTVs2BCXLl2S9EKv8pg5cyaCgoIwZMgQ3L17V3QcVTh8+DCmTJmCGTNmoG3btqLjEJHKNGnSBGfPnhUdAwDw3HPPYfr06Xj33XcRExMjOo4q5OfnY8iQIfD19cVnn30mOg6R6vTt2xc6nQ7r1q2TdFzOl5anhvlSo9GwiR8RqZperwcAZGRkCE7yl6pVq2LVqlWIjY3FtGnTRMdRjSlTpiA2NhYrVqzgS56ketWrV0ePHj0QHR0t6bicv6xDyfOXs7Mzm/gR2RCuP+qi5PWHyJaNHDkSly9fxu7duyUdl+cLlqeG8wUiW8X6S9vB+ksiIiIiIiIiIiKyBdxftjzuL6vD/dpIJTXxA3i+bw0iz/evXbuGXbt28SJEUi3Wh1qHHOpDExMT4e/vL2RsIiJLysvLU1wTP66v1iFqfd28eTP69u0r2XhESsT9TcuTy/5mUlISfH19hY1PRMrH/XLLk9P7cMnJyfDx8RGagYiIHo7Pa5Yn8nlt9erVcHBwQGhoqKTjEhGRbeJ5l3WIrCeJiopC69at4e3tbbUx2MSPKkyv18NoNOLKlSuio5Rgb2+PFStW4MKFC5gwYYLoOIp35coVDBkyBJ07d8Y777wjOg4RqZCnpydOnz4tOkax999/HyEhIRgxYgSuXbsmOo6imc1mvPLKK8jIyCjeJCMiy3JxcUGvXr0kv/Ac4HxpSWqZL7VaLcxms+gYRERWU7duXTg7O+P8+fOio5QQEBCAuXPn4ssvv8Qvv/wiOo7ibdy4Ef/+97/x3Xff4cknnxQdh0gSYWFh2LVrl+R7/Zy/LEvp85eTkxPy8vJExyAiCXH9UQelrz9EtszLywutW7dGVFSU5GPzfMFy1HK+QGSrWH9pG1h/SURERERERERERLaC+8uWxf1l9SgoKACgvCZ+AM/3LUn0+f7KlSvh6OiIXr16SToukZRYH2pZcqkPPXHiBOtTiUgV8vPzFdfED+D6ammi1tczZ87g5MmTvBid6BG4v2lZctrfjI+PR0BAgNAMRKR83C+3HNH75X9nMpmQnJwMf39/YRmIiOjR+LxmWaKf16Kjo9GnTx9Uq1ZN8rGJiMg28bzLskTWkxQWFmL9+vUYNmyYVcdhEz+qMHd3dwBAZmam4CSlNW7cGEuXLsXSpUsxdepU0XEU69atW+jZsyccHBwQGRkJjUYjOhIRqZCnpyfS09NhMBhERwFwrwHR0qVLodVq0bNnT9y+fVt0JMWaMmUKoqOjsWLFCnh4eIiOQ6RaYWFh2L17Ny5cuCDpuJwvLUct86VWq4XJZBIdg4jIajQaDfR6veya+AHAmDFj8NJLL2Ho0KE4ePCg6DiKtX//fgwbNgxjx45FRESE6DhEkunduzeqVq2K1atXSz425y/LUMP85eTkhPz8fNExiEhCXH+UTw3rD5GtGzZsGFavXi3572E8X7ActZwvENkq1l+qH+sviYiIiIiIiIiIyNZwf9kyuL+sLveb+CmxYQfP9y1H9Pl+dHQ0+vXrh6pVq0o+NpGUWB9qGXKpD83Ly8OpU6cQGBgoLAMRkaUotYkfwPXVUkSur5s2bUKNGjXQrl07ScclUiLub1qGnPY3b968iUuXLrGJHxFVGvfLLUf0fvnfpaen486dO/Dz8xOag4iIHo3Pa5Yh+nnt4sWL2LdvH8LCwiQdl4iIiOddliG6nmTLli3Izs7G0KFDrToOm/hRhbm5uUGr1SIjI0N0lDL16tULixYtwowZMzBnzhzRcRSnsLAQgwcPRmZmJrZs2QJXV1fRkYhIpby8vGA0GmW1ntSpUwfbt29HZmYm+vXrV/ySDJXf/Pnz8eWXX+L7779Ht27dRMchUrVevXrBxcUFa9askXxszpeVp6b5UqPRsIkfEameh4eHrJ5d/m7BggXo3r07QkNDkZSUJDqO4iQlJaFPnz7o0qULvvnmG9FxiCTl5OSE3r17Izo6Wsj4nL8qRy3zl5OTE/Ly8kTHICIJcf1RNrWsP0S2LiwsDHfu3MHWrVslH5vnC5WnpvMFIlvF+kt1Y/0lERERERERERER2SruL1cO95fV5/55uKOjo+AkFcPz/coTfb6fkZGBAwcOWP3yIiK5YH1o5cipPjQxMRFFRUUICgoSmoOIyBLy8/Ph7OwsOkaFcX2tHNHr6+bNm9GjRw/Y29tLPjaREnF/s3Lktr8ZHx8PAGwOTkQWwf3yyhO9X/5PiYmJ0Gg08PX1FR2FiIjKgc9rlSOH57WoqChUq1ZNFr8HEBGR7eF5V+WIPu8C7v0u8cILL8DNzc2q47CJH1WYg4MD6tSpg8zMTNFRHmjkyJGYMWMGJk+ejJUrV4qOoxgmkwmjRo3CwYMHsXXrVjRr1kx0JCJSMS8vLwBAWlqa4CQlNW3aFNu3b8exY8cQERHBpkSPITo6GhMnTsRXX32FF198UXQcItVzcnJCnz59hF14zvmy4tQ2X2q1WpjNZtExiIisysPDA+fPnxcdo0x2dnZYtmwZ/Pz80LVrV5w7d050JMW4cOECevTogYCAAKxcuRI6nU50JCLJhYWF4cCBA0hPT5d8bM5fFaem+cvZ2Rn5+fmiYxCRxLj+KJOa1h8iW9ewYUN06NABUVFRQsbn+ULFqe18gchWsf5SvVh/SURERERERERERLaO+8sVw/1ldbpfG6nUJn4Az/crQw7n+9HR0ahZsya6du0qZHwiqbE+tOLkVh8aFxcHZ2fn4vtIiIiULC8vD05OTqJjVBjX14oTvb7eunUL+/btQ+/evSUdl0jpuL9ZMXLc34yPj0etWrXQsGFD0VGISCW4X15xctgv/6ekpCTo9XrUqFFDdBQiIionPq9VjFye16KjozFw4EBF75USEZFy8byr4kSfdwHA7du3sWXLFgwbNszqY7GJH1WKXq+X9SUyAPDBBx9g4sSJCA8Px/r160XHkT2j0YiXX34ZmzZtwsaNG/HUU0+JjkREKlerVi3UqlULp0+fFh2llMDAQKxduxbr16/HK6+8gqKiItGRZG/dunUIDw/HG2+8gbffflt0HCKbERYWhkOHDuHs2bNCxud8+fjUOF9qtVoWlRCR6sm5iR9wrwHSxo0bUbNmTXTv3l3WWeXi/Pnz6NSpE2rUqIGNGzfycJ9sVrdu3VC7dm2sWrVKyPicvx6f2uYvJycnNvEjskFcf5RHbesPEQHDhg3Dpk2bkJOTI2R8ni88PjWeLxDZMtZfqg/rL4mIiIiIiIiIiIju4f7y4+H+snoVFBQAABwcHAQnqRye7z8+uZzv378IUcmNJIkeF+tDH58c60Pj4+MREBAAOzs70VGIiCotPz9fFnNrZXB9fXxyWF+3bt2KoqIidOvWTfKxiZSO+5uPR677m4mJiQgMDBQdg4hUhvvlj08u++X/lJSUBD8/P9ExiIjoMfF57fHI5Xnt9OnTiI2NRVhYmJDxiYiIAJ53VYQczrsAYP369TAajRgwYIDVx2ITP6oUd3d32V8iAwBff/01XnrpJQwePBg//PCD6DiylZeXh4EDByI6Ohpr165FcHCw6EhEZCM8PT1l2cQPAEJCQrBmzRqsWLECgwYN4mXiD7FgwQIMGTIEr7zyCmbNmiU6DpFN6dq1K+rUqYOVK1cKy8D5svzUOl9qNBo28SMi1XN3d8e5c+dEx3ioWrVqYfv27bC3t0fbtm2RmJgoOpJsJSQkoE2bNnB0dMT27dtRs2ZN0ZGIhLG3t0f//v0RHR0tLAPnr/JT4/zl5OSEvLw80TGISGJcf5RFjesPEQGDBg2C2WzGxo0bhWXg+UL5qfV8gciWsf5SXVh/SURERERERERERFQS95fLh/vL6lZQUAAHBwdotcq/2oXn++Unl/P9tLQ0HDt2jBchkk1ifWj5ybU+NC4uDkFBQaJjEBFZhBqa+AFcXx+HXNbXzZs3o127dnB1dRUyPpHScX+zfOS8v5mQkICAgADRMYhIhbhfXn5y2S8vS2JiIvz9/UXHICKiCuDzWvnI6XktKioKTzzxBEJCQoRlICIiAnje9Tjkct4F3PtdokePHpKceSm/0pOE0uv1yMjIEB3jkbRaLebPn48ZM2Zg7NixeP/990VHkp2srCx069YNe/fuxfbt29GzZ0/RkYjIhnh5eSEtLU10jAcKDQ3Frl27sG/fPnTs2BE3btwQHUl2Zs6ciXHjxuHtt9/GN998A41GIzoSkU3R6XTo16+f0AvPAc6X5aHm+VKr1cJsNouOQURkVR4eHrh7967s17iGDRtiz549aNKkCdq3b499+/aJjiQ7hw4dQnBwMLy8vLBnzx7Ur19fdCQi4cLCwnD8+HGkpKQIy8D569HUOn85OzujsLCQjcGJbBDXH2VQ6/pDRPeKC7t3746oqCihOXi+8GhqPl8gsmWsv1QP1l8SERERERERERERlcb95Ufj/rL6FRQUwNHRUXQMi+H5/qPJ6Xw/KioK9erVk9Xl+URSYn3oo8m5PjQ+Pp5N/IhINdTSxA/g+loecllfi4qKsHXrVoSGhgoZn0gNuL/5aHLf32QTPyKyJu6XP5qc9sv/yWQyITk5GX5+fqKjEBFRBfB57dHk9ry2cuVKDBo0CDqdTmgOIiIigOdd5SGX8y4AuHbtGv744w+EhYVJMh6b+FGl6PV6ZGZmio5Rbu+99x4WLFiAWbNmYfz48TAYDKIjyUJ6ejrat2+P9PR07N+/H23bthUdiYhsjKenJ06fPi06xkM9++yz2L17NzIzMxESEqKIS9SkUFhYiLFjx2LKlCn48ccf8eWXX4qORGSzhg8fjhMnTiA+Pl5oDs6XZbOF+VKr1bLhBhGpXqNGjQAA58+fF5zk0WrWrIlt27ahQ4cO6NatGzZu3Cg6kmysXbsWHTt2RIcOHbB161bUqFFDdCQiWQgODkbDhg2xbNkyoTk4fz2Ymuev+y+i5ufnC05CRFLj+iN/al5/iOie4cOH448//sClS5eE5uD5Qtls4XyByJax/lIdWH9JRERERERERERE9HDcXy4b95dtQ35+vqqa+AE8338QOZ7vL1u2DEOGDIGdnZ3oKETCsD70weRcH3rx4kVcu3aNTfyISDXU1MQP4Pr6MHJaX/ft24fr16+jT58+wjIQqQX3N8sm9/3NjIwMZGdns4kfEVkV98vLJsf98n86d+4c7ty5wyZ+REQKx+e1ssntee3PP/9EQkIChg8fLjQHERHR3/G868HkdN4FAFFRUXB2dpbszItN/KhS9Ho9Ll68iKKiItFRym3s2LFYtWoVlixZguDgYEVcum5NGzduRMuWLWFnZ4cDBw7A19dXdCQiskH3m/iZzWbRUR7K398f+/fvh8lkwlNPPYVffvlFdCSh0tPT0aFDB6xYsQJr1qzBmDFjREcismkdOnRA06ZNERkZKToK58t/sJX5UqPRsIkfEameh4cHNBoNzp07JzpKuTg7O2Pt2rUYNWoU+vfvj3feecemiwwKCwvx1ltvYfDgwYiIiMDq1atV9eITUWXZ2dlh+PDhWLp0qfDf6zh/lWQL8xeb+BHZLq4/8mUL6w8R3dOvXz/UqFFDeENVgOcL/2Qr5wtEtoz1l8rH+ksiIiIiIiIiIiKi8uH+ckncX7YdBQUFqqy54fl+SXI834+JiUFqairCw8NFRyESjvWhJSmhPjQuLg4AEBgYKDgJEZFl5OXlyW6urSyuryXJcX1dv349/P390bx5c6E5iNSC+5slKWF/MyEhAcC9fSwiImvifnlJctwvL0tiYiIAyHINIyKix8PntZLk+LwWGRmJJk2aCG8mSERE9E887ypJjuddALB48WIMGTIEVapUkWQ8NvGjStHr9TAYDLh69aroKI9lwIABOHr0KHJzcxEUFIQ1a9aIjiQ5o9GI999/H/3790doaCgOHDgAvV4vOhYR2SgvLy/k5eXh4sWLoqM8koeHB44cOYIRI0agT58+mDRpEgoLC0XHktymTZvQqlUr3Lp1CzExMejXr5/oSEQ2T6PRYMSIEVi6dCmMRqPoOJwv/48tzZdarVb2DXmJiCrLyckJderUUdQhvZ2dHRYsWIAlS5ZgwYIFaNu2Lc6ePSs6luTOnz+Pjh07YsGCBfjhhx8wf/582NnZiY5FJDsRERE4d+4c9uzZIzoK56//Yyvzl7OzM4B7L6USke3h+iM/trL+ENE9Dg4OGDp0KH7++WfRUQDwfOE+WzpfILJlrL9ULtZfEhERERERERERET2+f+4vf/TRR6IjSY77y7anoKAAjo6OomNYBc/375Hr+X5kZCT8/PzQqlUr0VGIZIH1ofcopT70xIkT0Ov1cHV1FR2FiMgi8vPzi9+dUhOur/fIdX3dtGmTbJ5PiNSC9bPK2t9MSEiAm5sbateuLToKEdkA7pffI9f98rIkJSVBr9ejZs2aoqMQEZEF8HlNvs9rRqMRUVFRCA8Ph0ajER2HiIioFJ533SPX8674+HgcP34cERERko3JJn5UKe7u7gCAjIwMwUken4+PD2JiYjBw4EAMGTIEkydPtpnLYdPS0tC2bVt8++23WLp0KSIjI1G1alXRsYjIhnl6egIATp8+LThJ+Tg5OWHu3LlYvHgxfv75Z7zwwguKyV5ZeXl5ePPNN9GvXz8MGDAAsbGxCAgIEB2LiP7P6NGjcfXqVfz++++iowDgfGlr86VWq4XJZBIdg4jI6jw8PBS5FzZq1CgcPnwYeXl5aN26NdatWyc6kmTWrFmDFi1aIDc3F8eOHcOYMWNERyKSLX9/f7Rs2RKRkZGioxTj/GUb85eTkxOAey+lEpHt4fojL7a0/hDRXyIiIpCSkoJDhw6JjgKA5wu2dr5AZMtYf6lMrL8kIiIiIiIiIiIiqjgfHx8sXrwY9vb2+Oyzz7i/zP1l1VNzEz+A5/tyPd8vLCzE6tWrER4eLjoKkeywPlQZ9aHx8fEICgoSHYOIyCKKiopgMBiK351SI66v8ltfjx8/jrNnz6Jv376ioxCpDutnlbO/mZCQgMDAQNExiMiGcL9cnvvlD5KUlAQ/Pz/RMYiIyIL4vCbP57WtW7fiypUrGDlypOgoRERED8XzLvmddwHAwoUL4eXlhbZt20o2Jpv4UaW4ublBo9EgMzNTdJQKqVKlCn7++WcsWbIEP/74IwICAvDrr7+KjmU1eXl5mD59OgIDA1FYWIijR49ixIgRomMREaFBgwaoWrWq4g6aRo8ejSNHjuDu3bsIDAzEJ598ouqLxjdv3gx/f38sXLgQS5cuxY8//ghnZ2fRsYjob7y8vNCmTRtZXXgOcL60lflSo9GwiR8R2QQPDw+cP39edIwK8fX1xaFDhzBgwAAMGjQIffr0wdmzZ0XHspozZ84gNDQUQ4YMweDBg3Hw4EH4+PiIjkUke+Hh4Vi9ejVyc3NFRynG+Uv989f9ZyZbKX4jotK4/ohni+sPEf3l6aefRlBQEBYvXiw6Sgk8X7CN8wUiW8b6S2Vh/SURERERERERERFR5ZjNZnzzzTd47rnncP36dcyePZv7y6R6am/idx/P9+V1vr9x40ZkZWVh+PDhoqMQyRLrQ+VfHxoXF8cmfkSkGvd/L1ZzEz+A66vc1teNGzfCzc0NrVu3Fh2FSJVYP6uM/c2EhATZN5AiInXifrm89ssfJDExEf7+/qJjEBGRhfF5TX7Pa5GRkWjfvj08PT1FRyEiInoknnfJ67zLYDBg+fLliIiIgEajkWxcNvGjSnF0dESdOnUUe4nMfaNGjUJKSgratm2L0NBQ9O7dG/v378fJkydFR7OYHTt2oGXLlpg1axbee+89HDp0CN7e3qJjEREBuNf0p0mTJopr4gfc+6U6NjYWX3zxBWbNmoWAgAD89ttvomNZVGZmJkaPHo0+ffrA398fCQkJstuUI6K/hIeHY8OGDcjOzhYdpQTOl+qn1WrZxI+IbIKSm/gB94oMfvzxR+zevRtnzpyBv78/pk+fjvz8fNUU/RkMBsydOxdBQUE4deoUtm3bhu+//14RRX5EcjBixAgUFhZiw4YNoqOU8KD5q6CgQHQ0i7Hl+ev+i6hqWYuI6PFx/RHHltcfIipp1KhRiIqKkl1jZZ4vEJGasf5SOVh/SURERERERERERFQ5Fy9eRJcuXfDGG2+gsLAQ3t7eePPNN0vtL6enp4uOalHcX6b8/HzVN+u4j+f78hEZGYkuXbpAr9eLjkIkW6wPla/CwkKkpKQgMDBQdBQiIouwlSZ+ANdXOVm/fj369+8v6YWmRLaorPpZ7m/KQ1FREU6ePMnmTEQkDPfL5c1sNiM5ORl+fn6ioxARkZXweU0ecnJy8MsvvyA8PFx0FCIionLjeZd8/PLLL7hx4wZGjRol6bhs4keVptfrFX+JDAA0aNAAkZGR2L59OxISEtC+fXvMnz8fN27cEB2tUmJjY9G7d2907twZQUFBSElJwfTp0+Hg4CA6GhFRCV5eXkhLSxMdo0J0Oh0mTZqEpKQkPPXUU+jZsyf69++Pn3/+WdG/WF+/fh1TpkyBt7c3jhw5gh07dmDz5s1wd3cXHY2IHmLo0KHQarVYvXq16CilPGi+PH78uOholcL58h6tVguz2Sw6BhGR1bm7uyu6id99HTp0wPHjxzFt2jTMmjUL9evXx6JFi1BUVCQ6WoUZjUYsW7YMfn5++PDDDzFt2jQkJCSgS5cuoqMRKYqrqyt69OiBJUuWiI5Spn/OX0FBQVixYgXnL4VjEz8i4vojPa4/RPRPo0aNwt27d7Fx40bRUUrh+QIRqRnrL+WN9ZdERERERERERERElbd27Vr4+flhz549MJlMcHBwwMCBAwGU3F8+deoUAgICMHXqVO4vk2oUFBTA0dFRdAzJ8HxfvKtXr2Lbtm28CJGonFgfKj8nT55EYWEhgoKCREchIrKIvLw8ALbRxO8+rq9ipaenIy4uDn379hUdhcgmcH9TntLS0pCXl8fm4EQkFPfL5evcuXPIzc1lEz8iIpXj85p4UVFRAFBcI0RERKQkPO8Sb/HixejUqRM8PDwkHZdN/KjS3N3dVXGJzH12dna4du0adDodoqOj0bhxY7z99tu4fPmy6GiPZf/+/ejZsydat26Ny5cv4/fff8fKlSvh5uYmOhoRUZk8PT1x+vRp0TEqRa/XY/Xq1di6dSsSEhIwZswYDBw4EDExMaKjPZZLly5h8uTJaNy4MX788UdMnz4dJ06cQEhIiOhoRFQO1atXR58+fWR74TlQcr48f/48WrVqhdDQUM6XCqfVamEymUTHICKyOg8PD1y+fBmFhYWio1Savb09Xn/9dTz33HPIy8vDxIkT4ePjg4ULFyrq76+wsBA//fQTfHx88OKLL+L5559HUlIS3nnnHdjb24uOR6RI4eHh2LlzJzIyMkRHKZO9vT3ee+89JCUl4ZlnnsHo0aM5fymcs7MzgL9eTCUi28T1Rxpcf4joQerVq4fu3btj0aJFoqM8EM8XiEiNWH8pT6y/JCIiIiIiIiIiIqq8W7du4eWXX8agQYNw+/ZtGAwGAPdqF3r16lXis507d0ZcXBymTp2KBQsWcH+ZVMPWmvjdx/N9cZYvXw5nZ2c27CB6DGqpD922bZsq6kPj4uLg6OgIb29v0VGIiCwiPz8fwF/vTtkKtayvSnz/Yt26dahZsyY6dOggOgqRTVHD/ubdu3fxww8/qGJ/MyEhAVqtFj4+PqKjEBGpZr/84MGDePnllxW1X/4giYmJAABfX1/BSYiISApqeF4DlFmPEhkZif79+6NGjRqioxAREVUIz7vEuXr1Kn777TdERERIPjab+FGl6fV62V6k+LhWrVqFbt264c6dO/D390d6ejo+/vhjrFixAk2aNMH48eMRFxcnOuYDFRYWYtOmTQgJCUG7du1w+/Zt/Pbbbzhy5Ag6d+4sOh4R0UN5enoiLS1NdAyLyM/Px7lz5+Dl5YWsrCy0adMGnTp1wubNm4tfNJOjEydO4LXXXkPTpk0RHR2NTz/9FGfPnsU777wDBwcH0fGI6DGMHj0a+/fvR2pqqugoD9WtWzfExsbil19+4XypAhqNhk38iMgmNGrUCCaTSRWXKmdnZ6Nz587YsWMHWrRogZSUFLzwwgsYN24cmjVrhjlz5uDatWuiYz7QtWvXMGfOHDRr1gzjx49HSEgIUlJSEBkZCXd3d9HxiBStV69eqF27NpYtWyY6ykN5eHhg6dKlnL9UwMnJCcBfL6YSkW3i+mNdXH+IqDwiIiLwxx9/yL4OiOcLRKQmrL+UD9ZfEhEREREREREREVlOTEwMAgMDsXjxYgAo8b5JjRo18Oyzz5b6/zg4OOC9997j/jKpiq028buP5/vSi4yMxODBg1GlShXRUYgUR+n1oX369MG4ceMUXx8aHx8PX19f2V4UR0T0uO6/K3X/3Slbo/T1VYnvX2zYsAGhoaGyf3YhUiOl72+GhoZi7NixuHTpkuL3NxMSEuDp6YmqVauKjkJEVEzp++XBwcFYtGgR3nzzTcXslz9IUlIS3NzcUKtWLdFRiIhIIkp/XlNiPUpaWhoOHjyI8PBw0VGIiIgqjedd0lu2bBmcnZ3Rr18/ycdmEz+qNL1er4pLy//73/8iLCwMRqMROp0OLVu2RNWqVfHWW2/hzJkzmD17NrZt24Ynn3wSTz75JGbPno1Lly6Jjg0AOHToECZOnAg3Nzf0798fDg4O2L17N/bu3Yvu3buLjkdEVC5eXl7Izs7GjRs3REeplOjoaAwcOBAGgwFPP/009u/fj507d8LOzg79+vWDm5sbXn/9dRw5ckR0VADAxYsXMWvWLASbNbzhAAAgAElEQVQFBaFFixb4/fff8fXXX+PMmTN48803WYRApFBdu3aFm5sbli9fLjpKufTs2ZPzpQpotVqYzWbRMYiIrM7DwwMAcP78ecFJKufixYto06YNjhw5Aq1Wi8DAQHh6euKnn35CWloa+vTpg48++ghubm7o06cP1qxZI4vGSvn5+Vi1ahV69+4NNzc3fPTRR+jXrx9Onz6NH374AU2bNhUdkUgVHBwcMHTo0OLLc+SO85fyOTk5QaPRyOKfFRGJw/XH8rj+ENHjCg0NhaurK5YuXSo6SrnwfIGI1ID1l+Kx/pKIiIiIiIiIiIjIcgwGA6ZNm4Z27drhwoULMBqNJb6v0+nQp08f2NnZPfDP4P4yqUl+fr7NNuv4O57vSyMhIQF//vknL0IkqiSl1ofWqVMHGo0Gw4YNU3R9aFxcHIKCgkTHICKyGFtv4nefUtdXpb1/cf36dRw4cEDIhaZE9Bcl72+6uroiPT1d9hc4P0pCQgICAgJExyAiKpNS98v//e9/w2QyYdmyZcjJyREdsVKSkpLg5+cnOgYREQmg5Oc1pdWjLFmyBA0aNECnTp1ERyEiIrIYnndJJzIyEmFhYahSpYrkY7OJH1WaXq/HhQsXYDKZREepELPZjGnTpmHSpEkwm80wm83QarXw9/cv/oyTkxNee+01nDp1Cnv37sVzzz2Hzz77DO7u7ujatStmz56N48ePS/YzyM3NxdatW/Huu+/C29sbzz33HHbs2IG33noL6enp2Lp1K1544QVJshARWYqnpycA4PTp04KTVNyyZcswYsQImEwmODo6wsvLCwDQsWNHbN++HWfPnsWkSZPw+++/45lnnoGvry/ee+89bNu2DXfu3JEko8lkwrFjxzBr1ix06dIFHh4e+Pzzz9GmTRvs27cPqampGDduHBwdHSXJQ0TWYWdnh2HDhmHJkiWK+j2d86WyabVaRf37RkRUUXXr1oWzs7Oim/idOXMGbdq0QVpaGgwGA+zs7EoUl7m7u+Obb77B5cuXsWjRIhQWFiIsLAwNGjRAREQEli5digsXLkiWNzMzE5GRkRg9ejTq16+P4cOHo6ioCIsXL8bly5cxd+5c6PV6yfIQ2Yrw8HCkpqbi8OHDoqOUG+cv5dJoNHB0dEReXp7oKEQkGNefyuP6Q0SV4eDggOHDh2Px4sUwm82i45QbzxeISMlYf8n6SyIiIiIiIiIiIiK1SEpKQqtWrTBjxgyYTCYUFRWV+kxRURFCQ0PL9edxf5nUoKCggOfDf8PzfetavHgxGjdujHbt2omOQqQKSqsPbdeuHQwGA3r16qWoOtx/OnHiBAIDA0XHICKyGDbxK0ku62tBQQEA9b1/sXHjRuh0OnTt2lV0FCKCMvc39Xo9srOzERwcjFOnTkmSyxoSEhL4XEFEsqe0/fKJEyfCxcUF6enp6NChA65cuSJJNmtITEws8c4LERHZHiU+rympHsVsNmP58uUYOXIk7OzsRMchIiKyOLmcd92ntvOu2NhYnDhxAhEREULG1wkZlVRFr9fDYDDg6tWrqF+/vug4j6WwsBARERFYuXJlqa+XtaGm0WjQrl07tGvXDnPnzsXmzZuxevVqzJw5E2+//TZcXV3xwgsvoGPHjggICICPj0+lfyZGoxFnz55FSkoKjhw5gh07duDw4cMwGAzw8/NDr169sHz5crRu3bpS4xARidaoUSM4ODggLS0NzzzzjOg4j23BggV47bXXii+zNBqNpTpKe3h4YMqUKZgyZQoOHz6MFStWYPPmzfjqq6/g4OCAZ555BiEhIXj66afh7e2NJk2aQKer3K9rly9fRnJyMhISErBr1y7s3r0bN2/eRJ06dRASEoKVK1ciNDRUUS+REFH5REREYNasWdi7d6+iNtyBis2Xx44dq9T6wfmy8jQajWIvFyUiehwajQZ6vV6xTfxiY2PRtWtX3Lp1C0ajEQBgMBjg6+tb6rNVqlTBiBEjMGLECFy8eBFRUVHYvHkzXn75ZRQUFMDb2xsdO3ZE+/bt4ePjg+bNm6NatWqVypebm4vU1FScPHkS+/btw86dO5GamgpHR0c8//zz+OijjzB8+HDF7UMSKdHTTz+NgIAALFmyRHF7NRWZv1JTUxEUFFThvRjOX5Xn5ORU/GIqEdkurj+Ph+sPEVnDv/71L8ydOxf79+9X3KVuFTlfyM3NxdWrV9G8efMKjcnzBSKqLNZfsv6SiIiIiIiIiIiISOlMJhPmzJmD999/H2azuczmffdptdrHvkie+8ukZGziVzYp37c+fvw4AgICcOPGDVWf7xuNRqxYsQKvvPIKNBqN6DhEqqKU96vq1KkDe3t7FBYWolOnTtizZw+eeuqpyv7tS+ratWu4fPkygoKCREchIrKYvLw8AICzs7PgJPIien2dOXMmCgoKVPf+xYYNG9C1a1e4uLiIjkJEf6Ok/U29Xo8TJ04gJycH7du3R0xMDJo0aVKpLFIrKChAWloamzMRkWIo6X7SevXq4datWzh//jzatGmDAwcOoF69epXKIjWz2Yzk5GS8/PLLoqMQEZEMSP28dvjwYbRs2VL19Sj/+9//cPbsWYwcOVJ0FCIiIquS8rzr8OHDeOaZZ2zivrHFixejefPmeO6554SMzyZ+VGnu7u4AgIyMDEX9x5ibm4sBAwZg586dZTaaeNTBi5OTEwYPHozBgwfDbDYjPj4eO3fuxM6dOzF16lRkZ2cDAGrUqAFvb280b94cbm5uqFatGqpWrYpq1aqhZs2a0Gq1KCgoQG5uLrKysnDnzh3k5ubi7NmzSE5OxunTp2EwGAAAXl5eCA4Oxvjx49GxY0dF/byJiB7Fzs4OHh4eOH36tOgoj+2rr77Ce++9V+JrRUVFpZr4/d0zzzxTfAHxpUuXsGvXLuzcuRPLly/HJ598AgBwcHCAp6cnfHx80LhxY1SrVq14/ahWrRocHR1hMpmQnZ2N3Nxc5Obm4s6dO7hw4QJSUlKQmpqKnJwcAECtWrXQvn17fPTRRwgJCUFAQABfwiBSOX9/f7Rs2RKRkZGKa+L3d+WZL+3t7WFnZ4cePXpwvhRIq9UWN7MlIlI7Dw8PZGRkiI7x2Hbt2oXQ0FAUFhYWN/C7r6wmfn/XsGFDTJ48GZMnT8bdu3dx4MAB7Ny5E7t27cLPP/9cvH/l7u6O5s2bo3nz5qhevTpq1apVYj8MQPFafH8/LCcnB6dOnUJKSgoyMzMB3FvfW7VqhUGDBiEkJARt2rThS0pEAowcORJfffUVvv76a8VeSFHe+cvJyQlPPvkkWrZsyflLECcnp+IXU4nItnH94fpDRGIFBgaiRYsWWLx4seKa+P1dec9jq1evDr1ej44dO/J8gYiEYP0l6y+JiIiIiIiIiIiI1MBgMMBkMj30jEyj0eD5559HzZo1KzwO95dJadjE79Gs/b71zp07kZWVVVyjqtbz/e3bt+Py5csYNWqU6ChEqibn96vq1KkDrVYLg8GA/Px8dO7cGQcOHIC3t7c0PxwLOHHiBACwiR8RqUp+fj6Ae8+zVDYR66tGo0HHjh0xf/581bx/kZubiz/++APz5s0THYWIHkLu+5sNGjSATqeDwWDAjRs3EBwcjJiYGDRs2FCSn48lJCUlwWg0IiAgQHQUIqLHJvf7Sd3d3XHq1CkYDAZkZGSgY8eO2Lt3L1xdXa3/w7GQ8+fP4/bt22z2SkREpUjxvPbbb7+hqKio+P4/tdajREZGonXr1ggMDBQdhYiISDLWPu9atWoV7O3tceXKFQDqvW+ssLAQ0dHReOutt4TV9LGJH1WaXq+HRqNBZmYmnn76adFxyuXy5cvo2rUrkpOTUVRUVOr7VapUgZubW7n/PI1Gg6CgIAQFBeGNN94AcG/DMzk5GampqcUblSdPnizexMzNzS3euNTpdHBxcSne9KxatSoaNWqEwYMHw9fXF82bN4e3t3eFO6MSESmFl5eX4pr4ffnll/jggw/K/J6np2e5/owGDRpg+PDhGD58OADg9u3bxetHcnIyUlJSEBMTU/yLc3Z2Nm7fvl286VajRo3iA7Rq1aqhfv36aNeuHf71r3+hefPm8PHxQYMGDSzzN0xEihIeHo4PP/wQc+fOVcXvkg+aL//f//t/+P333wGA86VAWq22zAs6iYjUyMPDA+fPnxcd47GsX78eQ4cOhclkKrUf5ujoCA8Pj3L/WVWqVEHnzp3RuXNnAIDRaMSZM2eKn19SU1ORlJSE27dvF6/Hd+7cwd27d4v//38vAqxevTq8vLzQvXt3eHt7w8fHB02aNIFOx+1rItFGjhyJKVOmYNOmTRg8eLDoOJX2oPlr3bp1+OCDD+Do6Mj5SyBnZ+fiF1OJyLZx/eH6Q0TiRUREYOrUqfjPf/4DFxcX0XEq7UHnC8ePH8f48eORnZ3N8wUiEob1l6y/JCIiIiIiIiIiIlI6rVaL9957D506dcLgwYNx4cKF4gtH/k6n06Ffv34WG5f7y6QE+fn5bNbxGKzxvrVOp4ODgwM2bNiAwMBA1Z7vL168GO3atSv3u+1EVHlye7+qTp06xe/4Go1G3Lp1C8HBwTh48CAaNWpknR+ChcXFxaFOnTqquaSWiAj4q4kfm3uXjxTrq7u7O6pWrYr9+/dj0aJFqrjQFAC2bt0Kg8GA3r17i45CROUkx/3NevXqwc7ODkajEUajEZcuXUK7du1w4MABxfyenpCQAEdHRzRr1kx0FCKiSpHj/aQeHh6ws7NDUVERDAYD0tLS8MILL2DPnj2oXbu2xX8G1pCUlAQA8PX1FZyEiIjkzBrPaw0bNkRhYSG6du2KGTNmqLYeJTc3F2vWrMGMGTNERyEiIhLG0uddLi4uuHXrFnx9ffHjjz+q+r6xDRs2ICsrC6NGjRKWQX0/VZKco6MjnnjiCWRmZoqOUi5nzpxBp06dHvgCAAD4+flVurNmgwYN0KBBA3Ts2PGhnzMajaqc4IiIKsLT0xMnTpwQHaNczGYz3nnnHXz99ddlft/BwaHCL3K4uLigVatWaNWq1UM/xzWEiB5l9OjR+OCDD7Bs2TK8+uqrouNYnIuLC+rWrYtdu3bBbDbj9ddfR3BwcKnPcb6UhkajYRM/IrIZHh4eOHTokOgY5TZ//nxMmDABwL1nmX/y8vKCVqut8J+v0+nQvHlzNG/e/KGfu79OVGYsIpKWm5sbevbsiQULFqiiidI/3Z+/tmzZAgAIDAzEvHnzSn2O85c0HB0dUVBQIDoGEckA1597uP4QkUjh4eGYMmUKIiMjMX78eNFxLO7+eezmzZtRWFgInU6HmJiYUp/j+QIRSYH1l2Vj/SURERERERERERGR8rRu3RpxcXGYNGkSFi1aBI1GU6J22WAwIDQ01KoZuL9MclNQUMBmHZVgifeta9WqhZycHKSlpaFr167WiCncpUuXsGHDBixcuFB0FCKbJvr9qrp165Y4xzcajbhx4waCg4MRExOjiIYb8fHxaNGihegYREQWlZ+fD0dHR74XUEHWWF/T09NhMplw584dTJo0CatWrbJIVtGio6MRHByMunXrio5CRJUgen+zXr16Je4OMhgMyMzMREhICPbu3QtXV1eLj2lpiYmJ8PHxgb29vegoREQWJYf7SRs2bAidToeioiIA99aJ1NRUBAcH43//+x9q1apllXEtKTExEQ0bNlREViIikpfKPq/t2rUL69atw44dO7BgwQJVNvADgMjISBiNRowYMUJ0FCIiItmo7HlXYmIiAgICkJCQgEaNGqFZs2ZWyyravHnz0Lt3b+j1emEZeKpLFqHX6xVxiczhw4fRunXrh14go9PpJC3oYoE/EdFfPD09kZaWJjrGI91vFPX111+X2QADuLc2WruAjmsIET1KzZo1MXTo0DIvAVeLTz/9FABgb2+Po0ePlvkZzpfS0Gq1D1wXiYjUxt3dHefOnRMdo1xmzpyJCRMmwGw2lzlP29nZISgoSJIsWq2WLxoRKdC4ceOwc+dOJCYmio5iFX/88Qf27dsHADhw4ECZn+H8JQ2dTgej0Sg6BhHJBNcfrj9EJFbNmjUxfPhwfPvtt6rd983JycHs2bMBAKdPn8atW7dKfYbnC0QkFdZfVhznaiIiIiIiIiIiIiJ5cXFxQbVq1fDEE0+gatWqJS5Kdnd3h7e3t8B0f+H+MkmlsLAQDg4OomOo3oP+mz537hyys7MBANOnT0deXp6UsSTzww8/oEaNGhg0aJDoKERUDtaqD61Tp06prxkMBly4cAEhISHIysqy+JiWFhcXJ9l7bkREUmFjb2k8zvp6/vx5APfuj1q9ejW2bNlizWiSuH37Nn799VcMHTpUdBQikoi19jfr169f6j1fg8GAtLQ0BAcHF++zyFl8fDwCAgJExyAiEsaaZ2ANGjQo0ewVuLdOJCcno1u3brh9+7bVxraUpKQk+Pv7i45BREQq9qC1ODY2Fvb29tBoNPj8888lTiWdBQsWYPjw4ahdu7boKERERIrzoPOuw4cPw87ODnZ2dvj4448FJJNGQkIC9u7diwkTJgjNwRvfyCLc3d1lf4lMVlYWBg8ejKysrAdeIAMAGo2GG2pERIJ4eXnh8uXLsj6AKSoqwosvvoj58+c/9MJKubxMRkQ0ceJEJCYmYv/+/aKjWFx6ejoWLVoEg8EAk8n0wCZ+JA2tVluqwIKISK0aNWqEO3fu4MaNG6KjPFBRURHGjh2L999//6HPLnZ2dvD19ZUwGREpTffu3dGsWTP88MMPoqNYxdSpU4uLnxITEx96fkDWZW9vz58/ERXj+kNEJN7rr7+OkydPYufOnaKjWMWcOXOQn58P4N4lHEeOHBGciIhsGesviYiIiIiIiIiIiEgtfvvtN8ybNw9z585FXFwcWrRoUXx5yIABA0THI5KcwWAo0cySpHXkyBFoNBoAwM2bN7FgwQLBiSzPaDTip59+wpgxY+Dk5CQ6DhEJVFYTP+Cvhhtdu3ZFbm6uxKnKz2g0IikpCYGBgaKjEBFZFBt7y8/58+eLL0DVarUYO3Ys7ty5IzhV5WzYsAFGo5F7L0RUafXq1SvzbgqDwYCUlBR069ZN1s8VwL2LnlnLTERkHQ0aNCjzfRKDwYA///wTXbp0kf06kZSUBD8/P9ExiIjIBh05cgQmkwkGgwELFy7EmTNnREeyuD179iA+Ph6vvvqq6ChERESqcujQIWi1WhiNRqxfvx7x8fGiI1nF3Llz4evri5CQEKE52MSPLEKv1yMjI0N0jIeqVasWEhMTMW3aNDg4ODyw2NlgMCAgIEDidEREBACenp4AgLNnzwpOUjaDwYBhw4ZhyZIlD21S5ODggGbNmkmYjIjowZ566im0bt0a3333negoFjdt2rTil+iKiooQExMjOJFt02g0bOJHRDbDw8MDwL0XNeQqJycHRqMRWq32oS/4GAwGNvEjoofSaDR4+eWXsWTJEsW/jPZPv/76Kw4ePAij0Qjg3kuRCQkJglPZLjbxI6K/4/pDRCReQEAA2rdvj2+//VZ0FIvLycnB7Nmzi+diBwcHHD58WHAqIrJlrL8kIiIiIiIiIiIiIjW4cuUKXnzxRYSHh2P48OFo0qQJDhw4gA8++ABmsxmhoaGiIxJJjk38xIqNjS1+n6KoqAiffPIJbt++LTiVZW3cuBEXL17EK6+8IjoKEQn2oCZ+wL316MSJE+jduzfy8/MlTFV+qampyM/PR1BQkOgoREQWxWcC+Tl37lzxPxOTyYQrV67giy++EJyqclauXIlu3brB1dVVdBQiUrh69eo98HsGgwHHjx+X9XPFrVu3kJGRwebgRERW0rBhwwd+z2Aw4NixY+jduzfy8vIkTFV+ZrMZycnJbOJHRERCxMTEoKioCACg1Wrx8ccfC05kefPnz8ezzz6L1q1bi45CRESkKnv37i2+n1Gn0+GTTz4RnMjysrOzERUVhQkTJhT3GxCFTfzIIvR6PTIzM0XHeKRq1aph+vTpOH36NMLDw6HRaMoscPD39xeQjoiImjZtCq1Wi7S0NNFRyqTT6TBq1CgEBgZCo9HAzs6uzM+ZzWY0bdpU4nRERA82btw4rF69GleuXBEdxWJOnTqFZcuWlWjwkJGRgZs3bwpMZdu0Wi3MZrPoGEREknB3d4dGo5F1E7/atWvj559/RmJiIkJDQ6HRaKDT6Up9zmw2s7iMiB7ppZdeQkFBAVasWCE6ikVNnTq1xNyo0+lw9OhRgYlsm729fXETFSIigOsPEZEcjB8/Hps2bUJ6erroKBY1Z86cEi8DGo1GxMTECExERLaO9ZdEREREREREREREpHQmkwmjRo1CtWrV8N///rf46zqdDp9++il27dqFDh06CExIJIbRaCyzjp+kcfDgQRQWFhb/dW5uLubPny8wkeXNnz8fPXv2RJMmTURHISLBateuDa32wVeJGQwG7Nu3D0OHDpVl3X58fDx0Oh18fX1FRyEisig28ZOfjIwMmEym4r82Go2YOXMmkpKSBKaquKysLPz+++8YOnSo6ChEpAL169d/6PfvP1cMGDCgxJ1PcpGQkACz2cxaZiIiK3lYEz/gr3WiT58+KCgokChV+WVkZCAnJ4f3LBERkeSysrJKvD9qMBiwbNkyJCcnC0xlWZcvX8b69esxbtw40VGIiIhU5e7du0hJSSn+a4PBgLVr1yI+Pl5gKsv76aefoNVqMXLkSNFR2MSPLMPDwwOZmZnFnbzlTq/XY8CAATCbzQgKCgKA4kZMLi4uaNCggch4REQ2y8nJCXq9HqdOnRIdpUwajQa9e/dGXFwctm/fDj8/vzKb+RkMBnh6egpKSURU2rBhw1C1alUsXLhQdBSLmTp1aqn512w24/jx44ISkVarLVGsTESkZs7Ozqhbt64iLrD38fHB2rVrsX37djg7OwNAiTXUzs6Ozy9E9Eiurq4YMmQIvvvuO9FRLGb9+vU4duxYiZfPNRoNYmNjBaaybTqdTpYv7RCROFx/iIjEGzBgAOrVq4fvv/9edBSLycnJwezZs0vMxSaTiU38iEgo1l8SERERERERERERkdLNnj0bu3fvxvLly+Hi4lLq+x06dICDg4OAZERisWGHOGazGbGxsTCbzcVfMxqN+Pzzz3Hr1i2BySwnOTkZu3btwquvvio6ChHJgFarRY0aNR75uS1btiA6OlqCRI/n+PHj8Pb2hpOTk+goREQWxWcC+Tl79mypd9g0Gg3GjBlT4vlBKdauXQs7Ozv07dtXdBQiUoEaNWqUax9379692LZtmwSJHs+JEydQo0YNNG7cWHQUIiJVql+/PjQazQO/f/8OuuTkZBw6dEjCZOWTkJAAjUaDgIAA0VGIiMjG/PPcGrj3PubHH38sKJHl/fTTT3BxccGQIUNERyEiIlKVY8eOlbqDQqfT4dNPPxWUyPKKiorw3XffISIiAtWrVxcdh038yDIaNWoEg8GAy5cvi45SLkVFRXj33XcxcOBAHD16FJs3b0bTpk0BAP7+/oLTERHZNm9v7xJdneWqc+fOOHjwIOrXr4+6deuWauZ3f10hIpIDZ2dnjBkzBt988w0KCgpEx6m0xMRErFq1qlRhrIODA44ePSooFWk0GjbxIyKb0qRJE5w9e1Z0jHLbuXMndDodIiMj0bhxY2i197aG3d3d4ejoKDgdESnBhAkTcPz4cfzxxx+io1Sa2WzGhx9+WKoxuMFgYOMOgezt7dnEj4hK4fpDRCSWvb09XnvtNSxYsAA5OTmi41jEnDlzkJeXV+rr169fR0ZGhoBERESsvyQiIiIiIiIiIiIiZYuNjcWHH36Izz77DM8++6zoOESyYjAYoNPpRMewSWfOnMHt27dLff3u3buYO3eugESWN2vWLHh5eaFHjx6ioxCRTLi6upb5dZ1OB2dnZ7z22mtIS0vDyJEjJU72aLGxsWjdurXoGEREFldYWMgmfjJz5syZUl8zGAw4ePAgFi9eLH2gSlq0aBH69u0LFxcX0VGISCXKeq7QarXQarVwdXXFlClTcP78eYSGhgpI93DHjx9HixYtHtpgioiIKs7R0bHMy/Tvn4M0b94cixYtwpkzZ9ChQwep4z3Sn3/+iUaNGqFmzZqioxARkY05evRoqYbpBoMBK1euRFxcnKBUlpOXl4d58+ZhzJgxcHZ2Fh2HiIhIVQ4dOlTqrNFgMGDNmjWIj48XlMqy1qxZg3PnzmHixImiowBgEz+ykEaNGgEAzp07JzhJ+SxatAgpKSn44osvAAChoaFISkrC999/j+7duwtOR0Rk25o3b66IJn4A8NNPPyErKwuHDh3C0qVL4eHhAeBeE6MmTZoITkdEVNJbb72FrKwsRRaN/tOHH35Y5suLRqMRR44cEZCIgHvrn9lsFh2DiEgySmrid/HiRcydOxcffvghRo0aheTkZHz33XeoU6cOgoKCRMcjIoV4+umn0alTJ3z55Zeio1TaqlWrcPLkSRQVFZX6XlJSkiqanysRm/gRUVm4/hARiTdhwgQAwLfffis4SeXdunULs2fPhtFoLPU9jUaDw4cPC0hFRMT6SyIiIiIiIiIiIiJSrjt37mDEiBF4/vnnMXnyZNFxiGTHaDSyYYcgR48eLfPCdqPRiJkzZ+LmzZsCUllOZmYmli5dinfffRdaLa8OIqJ76tWrV/y/7ezsoNFo4OTkhFdeeQUXLlzA3Llz0bhxY3EBH8BsNuP48eNo2bKl6ChERBZnMBhKXdBNYl24cOGB33vjjTdw7do1CdNUTkpKCmJiYvCvf/1LdBQiUpG/P1fcv9/JxcUF06ZNQ2ZmJqZPn45atWqJivdQ95v4ERGR9fx9nbh//lGrVi189913SEpKwujRo2V7LhIXF8d7loiISIgjR46Uec+ITqfD9OnTpQ9kYQsXLkROTg4mTZokOgoREZHqHDx4ECaTqdTXdTodPv30UwGJLMtsNuPzzz/HkIyrrRYAACAASURBVCFD0KxZM9FxALCJH1lIw4YNYW9vr4hLZPLy8vDxxx/j/7N33/FRlXn7x6+ZDAkghN5LZjIRBJGOGnXdfWRVdHf9oShKURRRShQIhBp6DQklgBQXQVkUXVbX3l11i4WShGYBZkgIvQkYISFtfn+4ySOPdGbmPpN83n+tgdf9vV6v1ZyZc+5zXwMGDDjjP0SHw6Enn3xSEydONJgOANC8eXN9//33pmNcUF5enpKTkzVo0CA1adJEvXr1ksfj0Zo1a/Tb3/5WlSpVMh0RAM5Qv3599enTR8nJyWc9nDZUbNmyRW+++eZZix2Ki4v19ddfG0gFSbLb7We9qQMAZVUolfhNnDhRderUUVxcnKT/vQ+WlZWl8ePHG04HIJSMGTNG//jHP/TVV1+ZjnLZioqKNG7cuLMeyiH9fDDHli1bgpwK0s/Xp1D+vgogcLj+AIBZ1apVU1xcnObOnauffvrJdJwrkpqaqtzc3LP+WYUKFbR27dogJwKAn7H/EgAAAAAAAAAQqp566ikdPXpUq1evVlhYmOk4gOUUFBSUHnaO4EpLSzvnQcH5+fmaO3dukBP515w5c1SnTh098sgjpqMAsJAGDRqU7lVt3bq1Xn75ZTmdTuXn51u2ZEOSsrKydPToUXXo0MF0FADwu4KCAssWWJRHP/zwwzn3Evt8PuXm5iohISHIqS7fsmXLFBUVpdtuu810FABlSOPGjUv/980336z3339fDRs21O7du1WxYkWDyc6vsLBQW7duVbt27UxHAYAyrWnTppIkm82mO+64Q//+979VvXp1paWlnfMdaqvYtGmT2rRpYzoGAKAc+vrrr89a4ldQUKA33nhDGRkZBlL5R2FhoWbPnq2+ffuqQYMGpuMAAFDmfPHFF+f8HPHqq6+G/Jllb775prZs2aIxY8aYjlKKEj/4RVhYmBo1ahQSh8gkJyfrxIkTSkxMNB0FAHAWzZs31w8//KCjR4+ajnJeixYt0vHjxzVy5MjSn9ntdj3wwAP67LPPDCYDgHMbOXKksrOztWbNGtNRLtuoUaPO++Li3r17dfjw4SAmQglK/ACUNy6XS1lZWaZjXNC2bdv0wgsvaOrUqYqIiDjjzypXrqyOHTsaSgYgFHXu3Fk33XSTkpOTTUe5bKtXr5bX6z3nZ1eHw6ENGzYEORWkn0tTzlbYDgBcfwDAvPj4eJ0+fVp//vOfTUe5bD/++KPmzJlzzuLo/Px8ffHFF0FOBQA/Y/8lAAAAAAAAACAUvfrqq1q5cqWWL1+uhg0bmo4DWFJhYSGFHYZ8/fXXys/PP+ufFRQUaO7cuTp06FCQU/nH0aNH9dxzz2n48OEKDw83HQeAhTRo0EBdu3bVF198ofT0dD344IMaMmSIVq1apQMHDpiOd07p6emy2+0cog6gTKLEz1qys7PP++cFBQVatWqVPv300yAlunyFhYV66aWX9Nhjj8lu5zhRAP7TpEkTPfTQQ0pPT9fnn3+uLl26aOjQoVq1apX2799vOt45ff/998rLy1Pbtm1NRwGAMi06OlqPPPKItm7dqnfeeUe33HKLEhIStGrVKu3bt890vHPKzc3Vjh071Lp1a9NRAADlzJEjR857jXQ4HBo3blwQE/nX6tWrtWfPHiUkJJiOAgBAmXPo0KHz3pN1OByaNm1aEBP534wZM9S1a1ddd911pqOU4qkb/CYqKsryh8gcOnRIc+bM0dixY1WvXj3TcQAAZ9G8eXNJPxdNWNXJkyeVkpKip556iusJgJASHR2t7t27a/r06SFZtrZhwwZ98MEHFyx1yMjICFIi/BIlfgDKG5fLpZycHB05csR0lPMaNWqUWrZsqV69epmOAqCMGDlypN58801t3brVdJRLVlRUpIkTJ8pms53z79hsNqWlpQUxFUpQ4gfgfLj+AIBZtWr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+ "text/plain": [ + "" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# The problem with Dask... do you remember the \"compute a fractal\" example?\n", + "\n", + "def run_dask(height, width, maxiterations=20, hchunks=3, vchunks=4):\n", + " chunked = lambda a: dask.array.from_array(a, chunks=(height // hchunks, width // vchunks))\n", + " y, x = numpy.ogrid[-1:0:height*1j, -1.5:0:width*1j]\n", + " c = chunked(x + y*1j)\n", + " fractal = chunked(numpy.full(c.shape, maxiterations, dtype=numpy.int32))\n", + " z = c\n", + " for i in range(maxiterations):\n", + " z = z**2 + c # applying z → z² + c\n", + " diverged = numpy.absolute(z) > 2 # |z| > 2 is \"divergence\"\n", + " diverging_now = diverged & (fractal == maxiterations) # some are already done\n", + " fractal[diverging_now] = i # just set the new ones\n", + " z[diverged] = 2 # clamp diverged at 2\n", + " return fractal\n", + "\n", + "run_dask(1600, 2400, maxiterations=3, hchunks=3, vchunks=4).visualize()" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# There are too many little tasks!\n", + "# \n", + "# Numba is not only good for compiling a complex function, it can also combine\n", + "# operations to hide them from Dask, simplifying the graph.\n", + "\n", + "# Make a Numpy ufunc...\n", + "@numba.vectorize([numba.int32(numba.complex128, numba.int32)])\n", + "def run_numba_ufunc(c, maxiterations):\n", + " z = c\n", + " for i in range(maxiterations):\n", + " z = z**2 + c\n", + " if abs(z) > 2:\n", + " return i\n", + " return maxiterations\n", + "\n", + "# Dask recognizes Numpy ufuncs...\n", + "def run_dask_numba(height, width, maxiterations=20, hchunks=3, vchunks=4):\n", + " chunked = lambda a: dask.array.from_array(a, chunks=(height // hchunks, width // vchunks))\n", + " y, x = numpy.ogrid[-1:0:height*1j, -1.5:0:width*1j]\n", + " return run_numba_ufunc(chunked(x + y*1j), maxiterations)\n", + "\n", + "run_dask_numba(1600, 2400, maxiterations=20, hchunks=3, vchunks=4).visualize()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "

This is a good example of two libraries not explicitly talking to each other, but both speaking the common language of Numpy ufuncs.

\n", + "\n", + "




" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "

Applying all the acceleration methods to the same fractal example:

\n", + "\n", + "| Method | time (ns/px) | speedup |\n", + "|:-------------------------------------------|-------------:|--------:|\n", + "| Pure Python | 12000 | 1× |\n", + "| Vectorized Numpy | 368 | 30× |\n", + "| Vectorized CuPy (run on GPU) | 81 | 150× |\n", + "| Compiled by Numba | 136 | 90× |\n", + "| Compiled & parallelized by Numba | 45 | 250× |\n", + "| Compiled & run on GPU by Numba | 7.8 | 1500× |\n", + "| Parallelized by Dask | 238 | 50× |\n", + "| Parallelized by Dask, compiled by Numba | 48 | 250× |\n", + "| Partially rewritten in Cython (Python/C++ hybrid) | 1485 | 8× |\n", + "| Completely rewritten in Cython (pure C++) | 99 | 120× |\n", + "| Completely rewritten in pybind11 (pure C++) | 98 | 120× |\n", + "| Completely rewritten in ROOT (pure C++ with `-O0`) | 379 | 32× |" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "




\n", + "\n", + "### Multithreading/multiprocessing\n", + "\n", + "




" + ] + }, + { + "cell_type": "code", + "execution_count": 37, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 37, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import threading # part of Python\n", + "\n", + "class Minion(threading.Thread):\n", + " def __init__(self, i, j, xarray, yarray, outarray):\n", + " super(Minion, self).__init__()\n", + " self.i, self.j = i, j\n", + " self.xarray, self.yarray, self.outarray = xarray, yarray, outarray\n", + "\n", + " def run(self):\n", + " i, j, outarray = self.i, self.j, self.outarray\n", + " outarray[i:j] = numpy.sqrt(self.xarray[i:j]**2 + self.yarray[i:j]**2)\n", + "\n", + "xarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "yarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "outarray = numpy.empty(1000000, dtype=numpy.float64)\n", + "\n", + "minions = []\n", + "for i, j in zip(range(0, 10), range(1, 10+1)):\n", + " minions.append(Minion(i*100000, j*100000, xarray, yarray, outarray))\n", + "\n", + "for minion in minions: minion.start() # start all the threads\n", + "for minion in minions: minion.join() # wait for all the threads to finish\n", + "\n", + "outarray" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([0.00000000e+00, 1.41421356e+00, 2.82842712e+00, ...,\n", + " 1.41420932e+06, 1.41421073e+06, 1.41421215e+06])" + ] + }, + "execution_count": 38, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import multiprocessing, ctypes # part of Python\n", + "\n", + "class Minion(multiprocessing.Process):\n", + " def __init__(self, i, j, xarray, yarray, outarray):\n", + " super(Minion, self).__init__()\n", + " self.i, self.j = i, j\n", + " self.xarray, self.yarray, self.outarray = xarray, yarray, outarray\n", + "\n", + " def run(self):\n", + " i, j, outarray = self.i, self.j, numpy.frombuffer(self.outarray, numpy.float64)\n", + " outarray[i:j] = numpy.sqrt(self.xarray[i:j]**2 + self.yarray[i:j]**2)\n", + "\n", + "xarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "yarray = numpy.arange(1000000, dtype=numpy.float64)\n", + "outarray = multiprocessing.RawArray(ctypes.c_double, 1000000) # shared memory!\n", + "\n", + "minions = []\n", + "for i, j in zip(range(0, 10), range(1, 10+1)):\n", + " minions.append(Minion(i*100000, j*100000, xarray, yarray, outarray))\n", + "\n", + "for minion in minions: minion.start() # start all the threads\n", + "for minion in minions: minion.join() # wait for all the threads to finish\n", + "\n", + "numpy.frombuffer(outarray, dtype=numpy.float64)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "

Why separate processes? Look up \"Global Interpreter Lock\" (GIL).

\n", + "\n", + "
\n", + "\n", + "

Short story: a single Python process can be concurrent, but not parallel.

\n", + "\n", + "
\n", + "\n", + "(Longer story: compiled code like Numpy and Numba can release the GIL and truly run in parallel, but Python operations on the same arrays can act as a _barrier_. Only independent Python processes are completely unconstrained.)\n", + "\n", + "


" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "


\n", + "\n", + "
\n", + "\n", + "
\n", + "\n", + "

Coffea is a suite of Python tools for particle physics, including parallelization.

\n", + "\n", + "


" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Preprocessing: 100%|██████████| 1/1 [00:00<00:00, 813.01it/s]\n", + "Processing: 100%|██████████| 1/1 [00:01<00:00, 1.00s/items]\n" + ] + }, + { + "data": { + "text/plain": [ + "(
,\n", + " ,\n", + " {None: [,\n", + " ]})" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "import coffea.hist\n", + "import coffea.processor\n", + "\n", + "class Minion(coffea.processor.ProcessorABC):\n", + " def __init__(self):\n", + " self.histograms = coffea.processor.dict_accumulator(dict(\n", + " pt = coffea.hist.Hist(\"pt\", coffea.hist.Bin(\"pt\", \"pt\", 100, 0, 200)),\n", + " m = coffea.hist.Hist(\"m\", coffea.hist.Bin(\"m\", \"m\", 100, 0, 200))\n", + " ))\n", + " @property\n", + " def accumulator(self):\n", + " return self.histograms\n", + " def process(self, df):\n", + " out = self.accumulator.identity()\n", + " out[\"pt\"].fill(pt=numpy.sqrt((df[\"px1\"] + df[\"px2\"])**2 + (df[\"py1\"] + df[\"py2\"])**2))\n", + " out[\"m\"].fill(m=df[\"M\"])\n", + " return out\n", + " def postprocess(self, accumulator):\n", + " return accumulator\n", + "\n", + "out = coffea.processor.run_uproot_job({\"signal\": [\"data/Zmumu.root\"]},\n", + " treename=\"events\", processor_instance=Minion(), executor=coffea.processor.futures_executor)\n", + "\n", + "%matplotlib inline\n", + "coffea.hist.plot1d(out[\"pt\"])" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "['run_parsl_job', 'run_spark_job', 'run_uproot_job']" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "[x for x in dir(coffea.processor) if x.startswith(\"run_\")]" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.3" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/README.md b/README.md new file mode 100644 index 0000000..039a197 --- /dev/null +++ b/README.md @@ -0,0 +1,66 @@ +# 2019-07-29-dpf-python + +Tutorials for the [IRIS-HEP tutorial at APS DPF](https://indico.cern.ch/event/782953/sessions/302485/#20190729), July 29, 2019, 2‒6pm in Shillman 425, Northeastern University. + +## How to participate + +The preferred way to participate is to run the JupyterLab code with us, altering examples and asking us "what if" questions as we go along, as well as using the notebooks as starting points for the five-minute exercises. + +You can run all of these notebooks on a public cloud service called Binder: + +

+ + Launch Binder + +

+ +Navigate in the JupyterLab file view (left sidebar) to the desired lesson. Note that Binder cannot save data permanently (reloading your web browser will take you to a new instance), and it may take a minute or two to start up. + +## Running everything on your own computer + +Alternatively, you might want to follow along using your own computer so that you can save data and have copies of the software after the tutorial. If you want a copy of all software packages (a few GB) and you have a non-Windows computer, install [conda](https://docs.conda.io/en/latest/miniconda.html) and [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git) and clone this repository: + +```bash +git clone https://github.com/jpivarski/2019-07-29-dpf-python.git +cd 2019-07-29-dpf-python +``` + +Then use + +```bash +conda env create -f environment.yml +``` + +to install nearly everything in an isolated environment named `dpf-python`. You can delete this without affecting anything else with the command + +```bash +conda remove --name dpf-python --all +``` + +To _use_ the software, you have to enter the isolated environment. Type + +```bash +conda activate dpf-python +``` + +to enter the environment. One additional package, JupyterLab, must be installed manually in the isolated environment: + +```bash +conda install jupyterlab +``` + +Start JupyterLab by typing + +```bash +jupyter lab +``` + +A web browser tab should open with the same environment as the Binder site above, or a URL will be provided that you can copy-paste into a web browser. However, the software will be running on your computer. + +## Cherry-picking software packages or manually installing + +Chances are, you won't want _everything_ in the `environment.yml`, only the packages most relevant to your work. They can be installed individually with pip or conda. There are, however, a few constraints: + + * ROOT can be installed with conda on Macs and UNIX-like computers (e.g. Linux), but not with conda on Windows and not with pip. You can install ROOT manually, but be sure to install the latest version, [release 6.18/00](https://root.cern/content/release-61800) to get the `RDataFrame.AsNumpy` feature. Also, interaction between ROOT and Python might not work if the compile-time and runtime versions of Python differ. Note that conda installs a custom Python version and pip doesn't. + * We do very little with `root-numpy`, but if you install this package, it should be with pip and it should be after ROOT and Python are already installed because it compiles against both of them. + * The tutorial examples use Python [f-strings](https://realpython.com/python-f-strings/) for formatting; these require at least Python 3.6. 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