Small changes to documentation

Author: mikaem

bitbucket-pipelines.yml

@@ -1,8 +1,3 @@
-# This is a sample build configuration for Python.
-# Check our guides at https://confluence.atlassian.com/x/x4UWN for more examples.
-# Only use spaces to indent your .yml configuration.
-# -----
-# You can specify a custom docker image from Docker Hub as your build environment.
 image: continuumio/miniconda3:latest
 
 pipelines:

conf/run_test.sh

@@ -2,4 +2,3 @@
 
 pushd tests
 ./runtests.sh
-

docs/source/conf.py

@@ -14,20 +14,23 @@
 #
 import os
 import sys
+import subprocess
 sys.path.insert(0, os.path.abspath('.'))
 sys.path.insert(0, os.path.abspath('../'))
 
 # -- Project information -----------------------------------------------------
 
 project = 'mpi4py-fft'
-copyright = '2018, Mikael Mortensen and Lisandro Dalcin'
+copyright = '2019, Mikael Mortensen and Lisandro Dalcin'
 author = 'Mikael Mortensen and Lisandro Dalcin'
 
 # The short X.Y version
-version = ''
-# The full version, including alpha/beta/rc tags
-release = '1.0-beta'
+p = subprocess.Popen(["git describe --tags | cut -d'-' -f 1"], stdout=subprocess.PIPE, shell=True)
 
+# The short X.Y version
+version = p.communicate()[0].rstrip().decode('utf-8')
+# The full version, including alpha/beta/rc tags
+release = version
 
 # -- General configuration ---------------------------------------------------
 
@@ -50,6 +53,9 @@
 napoleon_use_param = False
 napoleon_use_ivar = True
 
+# For some reason mathjax 2.7.5 renders bold type ugly. Use 2.7.1
+mathjax_path = 'https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML'
+
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ['_templates']
 
@@ -161,7 +167,7 @@
 #  dir menu entry, description, category)
 texinfo_documents = [
     (master_doc, 'mpi4py-fft', 'mpi4py-fft Documentation',
-     author, 'mpi4py-fft', 'One line description of project.',
+     author, 'mpi4py-fft', 'Parallel fast Fourier transforms',
      'Miscellaneous'),
 ]
 

docs/source/io.rst

@@ -4,7 +4,7 @@ Storing datafiles
 mpi4py-fft works with regular Numpy arrays. However, since arrays in parallel
 can become very large, and the arrays live on multiple processors, we require
 parallel IO capabilities that goes beyond Numpys regular methods.
-In the :mod:`.utilities` module there are two helper classes for dumping
+In the :mod:`mpi4py_fft.utilities` module there are two helper classes for dumping
 dataarrays to either `HDF5 <https://www.hdf5.org>`_ or
 `NetCDF <https://www.unidata.ucar.edu/software/netcdf/>`_ format:
 
@@ -109,7 +109,7 @@ two different ways when creating the datafiles:
 
         f0 = HDF5File('filename.h5', T, domain=((0, pi), (0, 2*np.pi), (0, 3*np.pi)))
 
-    2) One array giving the coordinates for each dimension. For example::
+    2) A sequence of arrays giving the coordinates for each dimension. For example::
 
         d = (np.arange(N[0], dtype=np.float)*1*np.pi/N[0],
              np.arange(N[1], dtype=np.float)*2*np.pi/N[1],
@@ -146,7 +146,7 @@ and `Visit <https://www.visitusers.org>`_, whereas NetCDF4 files can at the time
 opened with `Visit <https://www.visitusers.org>`_.
 
 To view the HDF5-files we first need to generate some light-weight *xdmf*-files that can
-be understood by both Paraview or Visit. To generate such files, simply throw the
+be understood by both Paraview and Visit. To generate such files, simply throw the
 module :mod:`.utilities.generate_xdmf` on the HDF5-files::
 
     from mpi4py_fft.utilities import generate_xdmf

docs/source/parallel.rst

@@ -31,7 +31,7 @@ to
 
 .. math::
 
-    \tilde{u}_{j_0/P,k_1,k_2} &= \mathcal{F}_1( \mathcal{F}_{2}(u_{j_0/P, j_1, j_2}), \\
+    \tilde{u}_{j_0/P,k_1,k_2} &= \mathcal{F}_1( \mathcal{F}_{2}(u_{j_0/P, j_1, j_2})), \\
     \tilde{u}_{j_0, k_1/P, k_2} &\xleftarrow[P]{1\rightarrow 0} \tilde{u}_{j_0/P, k_1, k_2}, \\
     \hat{u}_{k_0,k_1/P,k_2} &= \mathcal{F}_0(\tilde{u}_{j_0, k_1/P, k_2}).
 
@@ -126,7 +126,7 @@ objects by combining whenever possible. Take our example, the array
 :math:`u_{j_0/P,j_1,j_2}` can transform along both axes 1 and 2 simultaneously,
 without any intermediate global redistributions. By setting
 ``collapse=True`` only one object of ``rfftn(u, axes=(1, 2))`` will be
-used instead of two (like ``rfftn(rfftn(u, axes=2), axes=1)``).
+used instead of two (like ``fftn(rfftn(u, axes=2), axes=1)``).
 Note that a collapse can also be configured through the ``axes`` keyword,
 using::
 
@@ -282,12 +282,12 @@ get
     \widehat{ab}_k &= \int_{0}^{2\pi} \left( \sum_{p=-N/2}^{N/2-1} \hat{a}_p e^{i p x} \sum_{q=-N/2}^{N/2-1} \hat{b}_q e^{i q x} \right)  e^{-i k x} dx, \quad \forall \, k \in [-N/2, \ldots, N/2-1] \\
     \widehat{ab}_k &= \sum_{p=-N/2}^{N/2-1} \sum_{q=-N/2}^{N/2-1} \hat{a}_p  \hat{b}_q \int_{0}^{2\pi} e^{-i (p+q-k) x} dx, \quad \forall \, k \in [-N/2, \ldots, N/2-1]
 
-The final integral is unity for :math:`p+q=k` and zero otherwise. Consequently, we get
+The final integral is :math:`2\pi` for :math:`p+q=k` and zero otherwise. Consequently, we get
 
 .. math::
     :label: ab_convolve2
 
-    \widehat{ab}_k = \sum_{p=-N/2}^{N/2-1}\sum_{q=-N/2}^{N/2-1} \hat{a}_p  \hat{b}_{q} \delta_{p+q, k} , \quad \forall \, k \in [-N/2, \ldots, N/2-1]
+    \widehat{ab}_k = 2\pi \sum_{p=-N/2}^{N/2-1}\sum_{q=-N/2}^{N/2-1} \hat{a}_p  \hat{b}_{q} \delta_{p+q, k} , \quad \forall \, k \in [-N/2, \ldots, N/2-1]
 
 Unfortunately, the convolution sum :eq:`ab_convolve2` is very expensive to
 compute, and the direct application of :eq:`dft_convolve` leads to

tests/test_fftw.py

@@ -3,7 +3,7 @@
 import numpy as np
 from scipy.fftpack import dctn as scipy_dctn
 from scipy.fftpack import dstn as scipy_dstn
-import scipy.fftpack
+import scipy.fftpack # pylint: disable=unused-import
 from mpi4py_fft import fftw
 
 has_pyfftw = True