diff --git a/.coveragerc b/.coveragerc
deleted file mode 100644
index e1881654..00000000
--- a/.coveragerc
+++ /dev/null
@@ -1,14 +0,0 @@
-[RUN]
-omit =
- brainrender/gui/*
- brainrender/gui
-
-[report]
-omit =
- brainrender/gui/*
- brainrender/gui
-
-
-exclude_lines =
- def keypress
- pragma: no cover
diff --git a/.gitignore b/.gitignore
index 79580bbb..18169a56 100644
--- a/.gitignore
+++ b/.gitignore
@@ -28,7 +28,6 @@ brexport.html
*.vtk
*.nrrd
*.tdms
-paper/created_videos
*.mp4
diff --git a/MANIFEST.in b/MANIFEST.in
index 4bd89592..7dfa90d4 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,9 +1,7 @@
global-include *.svg
include brainrender/gui/icons*
-recursive-exclude paper *
recursive-exclude tests *
recursive-exclude examples *
recursive-exclude imgs *
recursive-exclude videos *
-recursive-exclude benchmark *
diff --git a/README.md b/README.md
index 7ed79337..589d9840 100644
--- a/README.md
+++ b/README.md
@@ -7,8 +7,8 @@
[](https://pypi.org/project/brainrender)
[](https://pypi.org/project/brainrender)
[](https://github.com/brainglobe/brainrender/actions)
+[](https://codecov.io/gh/brainglobe/brainrender)
[](https://www.gnu.org/licenses/gpl-3.0)
-[](https://coveralls.io/github/brainglobe/brainrender)
[](https://github.com/python/black)
diff --git a/benchmark/README.md b/benchmark/README.md
deleted file mode 100644
index 160b9696..00000000
--- a/benchmark/README.md
+++ /dev/null
@@ -1,80 +0,0 @@
- TheseCode to evaluate how fast brainrender is and how it compares to other software.
-
-Note: the exact duration on your system will depend on various factors like if other processes are
-running or the size of the rendering window/screen.
-
-Note: the duration reported in the results does not include scene creation (`scene = Scene()`) which takes <2s and mst of this time is spent accessing atlas data.
-
-## Machines tested
-* **[1]** macOS - Mojave 10.14.6 - MacBook Pro (15-inch, 2019) - 2.3 GHz Intel Core i9 - Radeon Pro 560X 4 GB GPU
-* **[2]** Ubuntu - 18.04.2 LTS x86_64 - Intel i7-8565U (x) @ 4.5GHz - NO GPU
-* **[3]** Windows 10 - Intel(R) Core i7-7700HQ 2.8GHz - NO GPU
-* **[4]** Windows 10 - Intel(R) Xeon(R) CPU E5-2643 v3 3.4GHz - NVIDIA GeForce GTX 1080 Ti
-
-## Tests
-### N cells
-Render N cells + the root object. The timer counts how long it takes to create a Points actor
-representing N cells, adding this to a scene and rendering the scene full screen/
-
-### Slice N cells
-Render N cells + the root object and slice them. The timer counts how long it takes to create a Points actor
-representing N cells, adding this to a scene and slicing the actor + the root mesh
-through the midline, as well as rendering the scene full screen.
-
-### Brain regions
-Render >1k brain region meshes. Measures how long it takes to fetch and render the meshes
-for almost all brain regions in the mouse brain.
-
-### Animation
-Make a short animation
-
-### Volume
-Parse a numpy array to create a Volume actor (10 times) and render
-
-## Results
-| Test | Machine | GPU | # actors | # vertices | FPS* | run duration | benchmark file |
-| ---- |:-------:|:---:|:--------:|:----------:|:---:|:------------:| --------------:|
-| 10k cells | [1] | yes | 3 | 1029324 | 24.76 | 0.81s | bm_cells.py |
-| | [2] | No | 3 | 1029324 | 22.46 | 1.16s | bm_cells.py |
-| | [3] | No | 3 | 1029324 | 20.00 | 1.41s | bm_cells.py |
-| | [4] | Yes | 3 | 1029324 | 100.00 | 1.34s | bm_cells.py |
-| 100k cells | [1] | yes | 3 | 9849324 | 18.87 | 3.23s | bm_cells.py |
-| | [2] | No | 3 | 9849324 | 14.91 | 4.34s | bm_cells.py |
-| | [3] | No | 3 | 9849324 | 0.43 | 7.94s | bm_cells.py |
-| | [4] | Yes | 3 | 9849324 | 1.20 | 1.13s | bm_cells.py |
-| 1M cells | [1] | yes | 3 | 98049324 | 2.65 | 31.01s | bm_cells.py |
-| | [2] | No | 3 | 98049324 | 2.55 | 96.49s | bm_cells.py |
-| | [3] | No | 3 | 98049324 | 0.03 | 86.75s | bm_cells.py |
-| | [4] | Yes | 3 | 98049324 | 0.13 | 36.57s | bm_cells.py |
-| Slicing 10k cells | [1] | yes | 3 | 237751 | 37.64 | 0.96s | bm_cells.py |
-| | [2] | No | 3 | 237751 | 39.10 | 1.25s | bm_cells.py |
-| | [3] | No | 3 | 237751 | 26.32 | 1.88s | bm_cells.py |
-| | [4] | Yes | 3 | 237751 | 200.00| 1.34s | bm_cells.py |
-| Slicing 100k cells | [1] | yes | 3 | 276092 | 31.79 | 7.77s | bm_cells.py |
-| | [2] | No | 3 | 276092 | 25.98 | 9.09s | bm_cells.py |
-| | [3] | No | 3 | 276092 | 21.28 | 16.88s | bm_cells.py |
-| | [4] | Yes | 3 | 276092 | 111.11 | 9.65s | bm_cells.py |
-| Slicing 1M cells | [1] | yes | 3 | 275069 | 11.23 | 91.31s | bm_cells.py |
-| | [2] | No | 3 | 275069 | 5.39 | 104.79s | bm_cells.py |
-| | [3] | No | 3 | 275069 | 5.03 | 158.99s | bm_cells.py |
-| | [4] | Yes | 3 | 275069 | 37.04 | 97.43s | bm_cells.py |
-| brain regions | [1] | yes | 1678 | 1864388 | 9.38 | 11.78s | bm_brain_regions.py |
-| | [2] | No | 1678 | 1864388 | 7.61 | 27.40s | bm_brain_regions.py |
-| | [3] | No | 1678 | 1864388 | 6.49 | 46.79s | bm_brain_regions.py |
-| | [4] | Yes | 1678 | 1864388 | 11.90 | 35.83s | bm_brain_regions.py |
-| animation | [1] | yes | 8 | 96615 | 9.91 | 18.98s | bm_animation.py |
-| | [2] | No | 8 | 96615 | 22.12 | 12.63s | bm_animation.py |
-| | [3] | No | 8 | 96615 | 15.15 | 11.92s | bm_animation.py |
-| | [4] | Yes | 8 | 96615 | 47.62 | 12.29s | bm_animation.py |
-| volume | [1] | yes | 12 | 49324 | 1.79 | 2.31s | bm_volume.py |
-| | [2] | No | 12 | 49324 | 1.66 | 1.95s | bm_volume.py |
-| | [3] | No | 12 | 49324 | 3.55 | 2.15s | bm_volume.py |
-| | [4] | Yes | 12 | 49324 | 23.26 | 1.21s | bm_volume.py |
-* the FPS measured are approximate and are meant only as an indication of the expected performance.
-
-Note: Volume actors don't have a number of "vertices" so are not counted heres
-
-Note: these tests are designed to push brainrender to the limits, in practice several steps can be taken to speed up rendering times
-and increase FPS. This includes decimating/smoothing Actors to reduce the number of vertices or creating meshes with lower resolution to
-begin with. For most cases a significant increase in performance can be achieved with no noticeable loss in rendering quality.
-For instance on computer [4] lowering the resolution of the Points actor from 8 to 4 when rendering 1M points tripled the FPS.
diff --git a/benchmark/__init__.py b/benchmark/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/benchmark/bm_animation.py b/benchmark/bm_animation.py
deleted file mode 100644
index a3526961..00000000
--- a/benchmark/bm_animation.py
+++ /dev/null
@@ -1,23 +0,0 @@
-from benchmark.timer import Timer
-from brainrender import Animation, Scene
-
-# Create a brainrender scene
-scene = Scene(title="brain regions", inset=False)
-
-with Timer(scene, name="Animation"):
- # Add brain regions
-
- for br in ("TH", "MOs", "MOp", "CA1", "CB", "MB"):
- scene.add_brain_region(br, silhouette=False)
-
- anim = Animation(scene, "examples", "vid3")
-
- # Specify camera position and zoom at some key frames
- # each key frame defines the scene's state after n seconds have passed
- anim.add_keyframe(0, camera="top", zoom=1.3)
- anim.add_keyframe(1, camera="sagittal", zoom=2.1)
- anim.add_keyframe(2, camera="frontal", zoom=3)
- anim.add_keyframe(3, camera="frontal", zoom=2)
-
- # Make videos
- anim.make_video(duration=3, fps=10)
diff --git a/benchmark/bm_brain_regions.py b/benchmark/bm_brain_regions.py
deleted file mode 100644
index 63127590..00000000
--- a/benchmark/bm_brain_regions.py
+++ /dev/null
@@ -1,15 +0,0 @@
-from benchmark.timer import Timer
-from brainrender import Scene
-
-scene = Scene(inset=False)
-regions = scene.atlas.get_structure_descendants("root")
-
-with Timer(scene, name="Brain regions"):
- for reg in regions:
- try:
- scene.add_brain_region(reg)
- except FileNotFoundError:
- pass
-
-
-scene.close()
diff --git a/benchmark/bm_cells.py b/benchmark/bm_cells.py
deleted file mode 100644
index 4af2f5f1..00000000
--- a/benchmark/bm_cells.py
+++ /dev/null
@@ -1,38 +0,0 @@
-import random
-
-import numpy as np
-
-from benchmark.timer import Timer
-from brainrender import Scene, actors
-
-# create N random cells coordinates
-
-
-def get_n_random_points_in_region(region, N):
- """
- Gets N random points inside (or on the surface) of a mes
- """
-
- region_bounds = region.mesh.bounds()
- X = np.random.randint(region_bounds[0], region_bounds[1], size=10000)
- Y = np.random.randint(region_bounds[2], region_bounds[3], size=10000)
- Z = np.random.randint(region_bounds[4], region_bounds[5], size=10000)
- pts = [[x, y, z] for x, y, z in zip(X, Y, Z)]
-
- ipts = region.mesh.inside_points(pts).coordinates
- return np.vstack(random.choices(ipts, k=N))
-
-
-for N_cells in (10000, 100000, 1000000):
- scene = Scene(inset=False)
- coordinates = get_n_random_points_in_region(scene.root, N_cells)
-
- with Timer(scene, name=f"Rendering {N_cells} cells"):
- scene.add(actors.Points(coordinates))
-
- scene = Scene(inset=False)
- with Timer(scene, name=f"Slicing {N_cells} cells"):
- scene.add(actors.Points(coordinates))
- scene.slice("sagittal")
-
- scene.close()
diff --git a/benchmark/bm_napari.py b/benchmark/bm_napari.py
deleted file mode 100644
index 7968ed8f..00000000
--- a/benchmark/bm_napari.py
+++ /dev/null
@@ -1,42 +0,0 @@
-"""
-Compare performance on napari
-"""
-import napari
-import numpy as np
-
-from benchmark.timer import SimpleTimer
-from brainrender import Scene
-
-# get a couple meshes with brainrender
-scene = Scene()
-
-print("Getting mesh data")
-regions = scene.atlas.get_structure_descendants("root")
-for reg in regions[:400]:
- try:
- scene.add_brain_region(reg)
- except FileNotFoundError:
- pass
-
-surfaces = []
-for act in scene.clean_actors:
- surfaces.append(
- (act.vertices, act.cells, np.ones(len(act.vertices)) * 0.5)
- )
-
-# render stuff in napar
-timer = SimpleTimer("napari")
-with napari.gui_qt():
- print("creating viewer")
- viewer = napari.Viewer(ndisplay=3)
-
- print("Adding surfaces")
- timer.start()
- for surface in surfaces:
- try:
- viewer.add_surface(surface)
- except Exception:
- pass
-
- print("done")
- timer.stop()
diff --git a/benchmark/bm_napari_volume.py b/benchmark/bm_napari_volume.py
deleted file mode 100644
index 492f3612..00000000
--- a/benchmark/bm_napari_volume.py
+++ /dev/null
@@ -1,16 +0,0 @@
-import napari
-import numpy as np
-
-from benchmark.timer import SimpleTimer
-
-data = np.load("benchmark/volume.npy")
-
-timer = SimpleTimer("napari volume")
-with napari.gui_qt():
- print("creating viewer")
- viewer = napari.Viewer(ndisplay=3)
-
- timer.start()
- for i in range(10):
- viewer.add_image(data)
- timer.stop()
diff --git a/benchmark/bm_volume.py b/benchmark/bm_volume.py
deleted file mode 100644
index ef4730ec..00000000
--- a/benchmark/bm_volume.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import numpy as np
-
-from benchmark.timer import Timer
-from brainrender import Scene
-from brainrender.actors import Volume
-
-scene = Scene(inset=False)
-data = np.load("benchmark/volume.npy")
-
-with Timer(scene, name="Render volume"):
- for i in range(10):
- actor = Volume(
- data,
- voxel_size=200, # size of a voxel's edge in microns
- as_surface=False, # if true a surface mesh is rendered instead of a volume
- c="Reds", # use matplotlib colormaps to color the volume
- )
- scene.add(actor)
diff --git a/benchmark/timer.py b/benchmark/timer.py
deleted file mode 100644
index 2422a9d6..00000000
--- a/benchmark/timer.py
+++ /dev/null
@@ -1,173 +0,0 @@
-import multiprocessing
-import os
-import sys
-import time
-
-import pyinspect as pi
-from myterial import (
- amber,
- blue_light,
- orange,
- orange_darker,
- pink_light,
- salmon,
-)
-from rich import print
-from rich.layout import Layout
-from rich.panel import Panel
-
-
-def is_GPU_available():
- """
- Check NVIDIA with nvidia-smi command
- Returning code 0 if no error, it means NVIDIA is installed
- Other codes mean not installed
- """
- code = os.system("nvidia-smi")
- return code == 0
-
-
-class SceneContent:
- def __init__(self, scene):
- self.scene = scene
-
- def __rich_console__(self, console, dimension):
- actors = pi.Report(
- "Scene actors", accent=salmon, dim=orange, color=orange
- )
- for act in self.scene.clean_actors:
- try:
- points = act.npoints
- except AttributeError:
- points = 0
- actors.add(
- f"[bold][{amber}]- {act.name}[/bold][{orange_darker}] (type: [{orange}]{act.br_class}[/{orange}]) - [white dim]points: {points}"
- )
- yield Panel(actors.tb)
-
-
-class Empty:
- def __rich_console__(self, *args):
- yield ""
-
-
-class Timer:
- def __init__(self, scene, name=None):
- """
- Class to time how long it takes for a brainrender
- scene to render and print a nice summary of the results
-
- Arguments:
- scene: brainrender.Scene instance
- """
- self.name = name
- self.scene = scene
-
- # re add root to make sure it's included in timer
- scene.remove(scene.root)
- scene.add_brain_region("root", alpha=0.2)
-
- def __rich_console__(self, console, dimension):
- points = []
- for act in self.scene.clean_actors:
- try:
- points.append(act.npoints)
- except AttributeError:
- pass
- tot_points = sum(points)
-
- yield ""
- yield ""
- if self.name is not None:
- yield f" [b {orange}]{self.name}"
-
- yield ""
- yield f" [bold {amber}]Scene info:"
- yield f"[{blue_light}]Total number of [b]actors[/b] in scene: [b {pink_light}]{len(self.scene.actors)}"
- yield f"[{blue_light}]Total number of [b]vertices[/b] in scene: [b {pink_light}]{tot_points}"
-
- yield ""
- yield f" [bold {amber}]Duration and FPS:"
-
- t0 = self._pre_render_stop - self.start
- t1 = self.stop - self.start
- t_ratio = t0 / t1
-
- yield f"[{blue_light}]Scene preparation timer duration: [b {pink_light}]{t0:.2f} seconds"
- yield f"[{blue_light}]Total timer duration: [b {pink_light}]{t1:.2f} seconds"
- yield f"[{blue_light}]Fraction of time spent preparing scene: [b {pink_light}]{t_ratio:.2f}"
- yield f"[{blue_light}]Rendering [b]FPS[/b]: [b {pink_light}]{self.render_fps:.2f} frames per second"
-
- yield ""
- yield f" [bold {amber}]System info:"
- yield f"[{blue_light}]Platform: [{pink_light}]{sys.platform}"
- yield f"[{blue_light}]Number of cores: [{pink_light}]{multiprocessing.cpu_count()}"
- yield f"[{blue_light}]GPU available: [{pink_light}]{is_GPU_available()}"
-
- def make_report(self):
- layout = Layout(direction="horizontal", height=20)
- layout.split(
- Layout(SceneContent(self.scene), name="scene", ratio=1),
- Layout(
- Empty(),
- ratio=0.2,
- ),
- Layout(self, name="summary", ratio=2),
- )
- print(layout)
-
- def __enter__(self):
- self.start = time.perf_counter()
- return self
-
- def __exit__(self, *args):
- self._pre_render_stop = time.perf_counter()
-
- try:
- self.scene.render(interactive=False)
- except AttributeError:
- # it will fail when timing video creation
- pass
-
- self.stop = time.perf_counter()
-
- self.render_fps = (
- 1 / self.scene.plotter.renderer.GetLastRenderTimeInSeconds()
- )
- self.make_report()
-
-
-class SimpleTimer:
- def __init__(self, name):
- self.name = name
-
- def start(self):
- self.start = time.perf_counter()
-
- def stop(self, *args):
- stop = time.perf_counter()
-
- print(
- f"Timer [{pink_light}]{self.name}[/{pink_light}] terminated in [{pink_light}]{stop-self.start:.3f} seconds"
- )
-
- def __enter__(self):
- self.start = time.perf_counter()
- return self
-
- def __exit__(self, *args):
- stop = time.perf_counter()
-
- print(
- f"Timer [{pink_light}]{self.name}[/{pink_light}] terminated in [{pink_light}]{stop-self.start:.3f} seconds"
- )
-
-
-if __name__ == "__main__":
- from brainrender import Scene
-
- scene = Scene(root=True, inset=False)
-
- with Timer(scene, name="Test timer") as timer:
- for br in ["TH", "MOs", "CA1"]:
- timer.scene.add_brain_region(br, silhouette=False)
diff --git a/benchmark/volume.npy b/benchmark/volume.npy
deleted file mode 100644
index 8a5477fa..00000000
Binary files a/benchmark/volume.npy and /dev/null differ
diff --git a/getting_started.ipynb b/getting_started.ipynb
deleted file mode 100644
index 34fc4553..00000000
--- a/getting_started.ipynb
+++ /dev/null
@@ -1,244 +0,0 @@
-{
- "cells": [
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "## Getting started with brainrender\n",
- "This notebooks shows how to get started using brainrender.\n",
- "It assumes that you have already installed, if not please install it now:\n",
- "```\n",
- "pip install brainrneder\n",
- "```\n",
- "\n",
- "For more details about how to install brainrender, [please check the docs](https://brainglobe.info/documentation/brainrender/installation.html)\n",
- "\n",
- "### Content of this example\n",
- "This notebook shows how to:\n",
- "* Create a `Scene` in brainrender\n",
- "* add `brain regions` to your scene\n",
- "* add a `neuronal morphology` to your scene\n",
- "\n",
- "You can check the [examples](https://github.com/brainglobe/brainrender/tree/master/examples) and the [documentation](https://brainglobe.info/documentation/brainrender/) to learn more about how to use brainrender.\n",
- "\n",
- "In particular, if you are planning to use brainrender in a Jupyter Notebook, please read the [docs](https://brainglobe.info/documentation/brainrender/usage/using-notebooks.html) about using brainrender in a notebook, and have a look at the [notebooks workflow example](https://github.com/brainglobe/brainrender/blob/master/examples/notebook_workflow.ipynb)"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/plain": [
- "False"
- ]
- },
- "execution_count": 1,
- "metadata": {},
- "output_type": "execute_result"
- }
- ],
- "source": [
- "import vedo\n",
- "vedo.settings.default_backend == \"k3d\""
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Creating a scene and adding brain regions"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 1,
- "metadata": {},
- "outputs": [
- {
- "data": {
- "text/html": [
- " acronym id name\n",
- "0 root 997 root\n",
- "1 grey 8 Basic cell groups and regions\n",
- "2 CH 567 Cerebrum\n",
- "3 CTX 688 Cerebral cortex\n",
- "4 CTXpl 695 Cortical plate\n",
- "
\n"
- ],
- "text/plain": [
- " acronym id name\n",
- "\u001b[1;36m0\u001b[0m root \u001b[1;36m997\u001b[0m root\n",
- "\u001b[1;36m1\u001b[0m grey \u001b[1;36m8\u001b[0m Basic cell groups and regions\n",
- "\u001b[1;36m2\u001b[0m CH \u001b[1;36m567\u001b[0m Cerebrum\n",
- "\u001b[1;36m3\u001b[0m CTX \u001b[1;36m688\u001b[0m Cerebral cortex\n",
- "\u001b[1;36m4\u001b[0m CTXpl \u001b[1;36m695\u001b[0m Cortical plate\n"
- ]
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ],
- "source": [
- "# Import Scene\n",
- "from brainrender import Scene # Scene handles the creation of your rendering!\n",
- "\n",
- "scene = Scene(title='My first rendering') # create an instance of scene\n",
- "'''\n",
- "If you want to use any of the atlases supported by BrainGlobe's AtlasAPI,\n",
- "specify the atlas name when creating an instance of `Scene`!\n",
- "'''\n",
- "\n",
- "# Adding brain regions\n",
- "scene.add_brain_region('MOs', 'TH', alpha=.5)\n",
- "\n",
- "'''\n",
- "You can add any number of brain regions at once, just specify the regions' acronym or ID numbers.\n",
- "If you are not sure what the acronym/ID is for your region, have a look try:\n",
- "\n",
- "`scene.atlas.lookup_df`\n",
- "\n",
- "or:\n",
- "`print(scene.atlas.hierarchy)`\n",
- "\n",
- "which will show the hieararchical organization of the atlas' regions:\n",
- "\n",
- "root (997)\n",
- "├── VS (73)\n",
- "│ ├── AQ (140)\n",
- "│ ├── V3 (129)\n",
- "│ ├── V4 (145)\n",
- "│ │ └── V4r (153)\n",
- "│ ├── VL (81)\n",
- "│ │ ├── SEZ (98)\n",
- "│ │ └── chpl (108)\n",
- "│ └── c (164)\n",
- "├── fiber tracts (1009)\n",
- "│ ├── cbf (960)\n",
- "│ │ ├── arb (728)\n",
- "...\n",
- "\n",
- "'''\n",
- "\n",
- "scene.atlas.lookup_df.head()"
- ]
- },
- {
- "cell_type": "markdown",
- "metadata": {},
- "source": [
- "### Adding a neuronal morphology\n",
- "Brainrender can load neuronal morphologies from .swc files"
- ]
- },
- {
- "cell_type": "code",
- "execution_count": 3,
- "metadata": {
- "scrolled": true
- },
- "outputs": [
- {
- "data": {
- "text/html": [
- "╭──────────────────────────────────╮\n",
- "│ │\n",
- "│ Scene actors │\n",
- "│ ──────────── │\n",
- "│ │\n",
- "│ - root (type: brain region) │\n",
- "│ - title (type: title) │\n",
- "│ - MOs (type: brain region) │\n",
- "│ - TH (type: brain region) │\n",
- "│ - neuron1.swc (type: Neuron) │\n",
- "│ - neuron1.swc (type: Neuron) │\n",
- "│ │\n",
- "╰──────────────────────────────────╯\n",
- "