Update internal documentation and string formatting

README.rst

@@ -26,37 +26,32 @@ The following external libraries are required:
 Installation
 ------------
 
-For performance and convenience reasons we highly recommend to use
-`Conda`_ (miniconda for simplicity) to manage your Python installation.
-Once installed, you can use the following steps to create a new environment
-with the *sfa* toolbox.
+For performance and convenience reasons we highly recommend to use `Conda`_ (miniconda for simplicity) to manage your Python installation. Once installed, you can use the following steps to receive and use *sfa*, depending on your use case:
 
-#. Create new Conda environment from the specified requirements:
-   ``conda env create --file environment.yml``
+A.  By cloning (or downloading) the repository and setting up a new environment **[recommended]**:
 
-#. Activate the environment:
-   ``source activate sfa``
+    ``git clone https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py.git``
 
-#. Install *sfa* from **either** source:
+    ``cd sound_field_analysis-py/``
 
-   By cloning (or downloading) the repository **[recommended]**:
+    Create a new Conda environment from the specified requirements:
+    ``conda env create --file environment.yml``
 
-   ``git clone https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py.git``
+    Activate the environment:
+    ``source activate sfa``
 
-   ``cd sound_field_analysis-py/``
+    **Optional:** Install additional requirements in case you want to locally run the *Jupyter Notebooks* with examples:
+    ``conda env update --file environment_jupyter.yml``
 
-   ``pip install -e .``
+B.  From PyPI **[NOT recommended - code outdated]**:
 
-   From `conda-forge`_ channel **[not recommended - code currently outdated]**:
+    Install into an existing environment (without example *Jupyter Notebooks*):
+    ``pip install sound_field_analysis``
 
-   ``conda install -c conda-forge sound_field_analysis``
+C.  From `conda-forge`_ channel **[NOT recommended - code outdated]**:
 
-   From PyPI **[Not recommended - code currently outdated]**:
-
-   ``pip install sound_field_analysis``
-
-#. **Optional:** Install additional requirements in case you want to locally run *Jupyter Notebooks*:
-   ``conda env update --file environment_jupyter.yml``
+    Install into an existing environment:
+    ``conda install -c conda-forge sound_field_analysis``
 
 
 Documentation
@@ -113,6 +108,9 @@ miro or `SOFA`_ files.
 Version history
 ---------------
 
+*v2019.11.6*
+    * Update of internal documentation and string formatting
+
 *v2019.8.15*
     * Change of version number scheme to CalVer
     * Improvement of Exp4

contribute.md

@@ -2,29 +2,28 @@
 ## Dev environment
 Given you have [anaconda](https://www.continuum.io/downloads) installed, run the following commands to clone the repository into a new folder `sound_field_analysis-py`, install necessary tools into a new conda environment and activate it:
 ```
-git clone https://github.com/QULab/sound_field_analysis-py.git
-conda create -n sfa_dev scipy numpy plotly pip ipython
-source activate sfa_dev
-pip install -e sound_field_analysis-py
+git clone https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py.git
+cd sound_field_analysis-py/
+conda env create --file environment.yml
+source activate sfa
 ```
-You can now work on the *sfa* toolbox inside the  `sound_field_analysis-py` folder. Using `ipython`, you may use the following magic commands to ensure reload on any changes inside the package:
+
+You can now work on the *sfa* toolbox inside the `sound_field_analysis-py` folder. Using `ipython`, you may use the following magic commands to ensure reload on any changes inside the package:
 ```
 %load_ext autoreload
 %autoreload 2
 ```
 
 ## Documentation
 If you want to compile the documentation (pdf and/or html), you need to additionally install sphinx and sphinx_rtd_theme and clone the gh-pages branch:
-
 ```
-conda install sphinx sphinx_rtd_theme
-git clone --single-branch --branch gh-pages https://github.com/QULab/sound_field_analysis-py.git sound_field_analysis-docs
+conda env update --file environment_gh-pages.yml
+git clone --single-branch --branch gh-pages https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py.git sound_field_analysis-docs
 ```
 
 Now you can compile the pdf readme (given you have latex installed) and html pages by running `make latexpdf` or `make html` from the `sound_field_analysis-py\doc` directory.
 
 If you decide on a different folder structure, you may edit the following line in `doc/Makefile` to decide on where to move the html documentation:
-
 ```
 HTMLDIR       = ../../sound_field_analysis-docs
 ```

environment_gh-pages.yml

@@ -0,0 +1,5 @@
+channels:
+  - defaults
+dependencies:
+  - sphinx
+  - sphinx_rtd_theme

setup.py

@@ -1,23 +1,33 @@
-from setuptools import setup
-
-version = open("sound_field_analysis/_version.py").readlines()[-1].split()[-1].strip("\"'")
+from setuptools import find_packages, setup
 
 setup(
     name='sound_field_analysis',
-    version=version,
-    description='Analyze, visualize and process sound field data recorded by spherical microphone arrays.',
     url='https://github.com/AppliedAcousticsChalmers/sound_field_analysis-py/',
+    version=open('sound_field_analysis/_version.py').readlines()[-1].split()[-1].strip('"\''),
+    license='GPLv3',
+    # license='MIT',
+
+    description='Analyze, visualize and process sound field data recorded by spherical microphone arrays.',
+    long_description=open('README.rst', mode='r', encoding='utf-8').read(),
+    keywords='sound field analysis spherical microphone array',
+
     author='QU Lab / Christoph Hohnerlein',
+    # author='Chalmers University of Technology / Jens Ahrens',
     author_email='[email protected]',
-    license='GPLv3',
+    # author_email='[email protected]',
+
     classifiers=[
         'Development Status :: 4 - Beta',
+        # 'Development Status :: 5 - Production/Stable',
         'Intended Audience :: Science/Research',
         'Topic :: Multimedia :: Sound/Audio',
         'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
-        'Programming Language :: Python :: 3',
+        # 'License :: OSI Approved :: MIT License',
+        'Programming Language :: Python :: 3.7',
+        'Operating System :: OS Independent',
     ],
-    keywords='sound field analysis spherical microphone array',
+
+    python_requires='>=3.7',
     install_requires=[
         'scipy',
         'numpy',
@@ -27,9 +37,11 @@
     package_data={
         'examples': ['examples'],
     },
+
     extras_require={
         'plotting': ['plotly'],
         'examples': ['jupyter'],
     },
-    packages=['sound_field_analysis'],
+
+    packages=find_packages(),
 )

sound_field_analysis/__init__.py

@@ -2,7 +2,7 @@
 
 from ._version import __version__
 
-__all__ = ["io", "gen", "process", "sph", "utils", "lebedev"]
+__all__ = ['io', 'gen', 'process', 'sph', 'utils', 'lebedev']
 
 try:
     import plotly

sound_field_analysis/_version.py

@@ -1,2 +1,2 @@
 """Version information."""
-__version__ = '2019.8.15'
+__version__ = '2019.11.7'

sound_field_analysis/gen.py

@@ -6,7 +6,7 @@
 `gauss_grid`
    Gauss-Legendre quadrature grid and weights
 `lebedev`
-   Lebedev quadrature grid and weigths
+   Lebedev quadrature grid and weights
 `radial_filter`
    Modal radial filter
 `radial_filter_fullspec`
@@ -20,8 +20,8 @@
 from scipy.special import spherical_jn
 
 from .io import ArrayConfiguration, SphericalGrid
-from .process import spatFT, iSpatFT
-from .sph import sph_harm, sph_harm_all, cart2sph, array_extrapolation, kr, sphankel2, dsphankel2
+from .process import iSpatFT, spatFT
+from .sph import array_extrapolation, cart2sph, dsphankel2, kr, sph_harm, sph_harm_all, sphankel2
 
 
 def whiteNoise(fftData, noiseLevel=80):
@@ -101,7 +101,7 @@ def lebedev(max_order=None, degree=None):
     Returns
     -------
     gridData : array_like
-       Lebedev quadrature positions and weigths: [AZ, EL, W]
+       Lebedev quadrature positions and weights: [AZ, EL, W]
     """
     if max_order is None and not degree:
         raise ValueError('Either a maximum order or a degree have to be given.')
@@ -117,8 +117,7 @@ def lebedev(max_order=None, degree=None):
         raise ValueError('Maximum order can only be between 0 and 11.')
 
     if degree not in allowed_degrees:
-        raise ValueError('{} is an invalid quadrature degree. Choose one of the following: {}'.format(
-            degree, allowed_degrees))
+        raise ValueError(f'{degree} is an invalid quadrature degree. Choose one of the following: {allowed_degrees}')
 
     from . import lebedev
     leb = lebedev.genGrid(degree)
@@ -336,8 +335,8 @@ def sampled_wave(order, fs, NFFT, array_configuration,
 
     # TODO : Investigate if limit_order works as intended
     if max_order_fullspec > limit_order:
-        print('Requested wave front needs a minimum order of {} but was limited to order {}'.format(
-            max_order_fullspec, limit_order))
+        print(f'Requested wave front needs a minimum order of {max_order_fullspec} but was limited to order '
+              f'{limit_order}')
     Pnm = ideal_wave(min(max_order_fullspec, limit_order), fs, wave_azimuth, wave_colatitude, array_configuration,
                      wavetype, distance, NFFT)
     Pnm_resampled = spatFT(iSpatFT(Pnm, gridData), gridData, order_max=order)

sound_field_analysis/io.py

@@ -1,6 +1,5 @@
-"""
-Input-Output functions"""
-
+"""Input-Output functions"""
+import sys
 from collections import namedtuple
 
 import numpy as _np
@@ -48,10 +47,7 @@ def __new__(cls, array_radius, array_type, transducer_type, scatter_radius=None,
         return self
 
     def __repr__(self):
-        return 'ArrayConfiguration(\n' + ',\n'.join(
-            '    {0} = {1}'.format(name, repr(data).replace('\n', '\n      '))
-            for name, data in
-            zip(['array_radius', 'array_type', 'transducer_type', 'scatter_radius', 'dual_radius'], self)) + ')'
+        return utils.get_named_tuple__repr__(self)
 
 
 class TimeSignal(namedtuple('TimeSignal', 'signal fs delay')):
@@ -84,9 +80,7 @@ def __new__(cls, signal, fs, delay=None):
         return self
 
     def __repr__(self):
-        return 'TimeSignal(\n' + ',\n'.join(
-            '    {0} = {1}'.format(name, repr(data).replace('\n', '\n      '))
-            for name, data in zip(['signal', 'fs', 'delay'], self)) + ')'
+        return utils.get_named_tuple__repr__(self)
 
 
 class SphericalGrid(namedtuple('SphericalGrid', 'azimuth colatitude radius weight')):
@@ -120,9 +114,7 @@ def __new__(cls, azimuth, colatitude, radius=None, weight=None):
         return self
 
     def __repr__(self):
-        return 'SphericalGrid(\n' + ',\n'.join(
-            '    {0} = {1}'.format(name, repr(data).replace('\n', '\n      '))
-            for name, data in zip(['azimuth', 'colatitude', 'radius', 'weight'], self)) + ')'
+        return utils.get_named_tuple__repr__(self)
 
 
 class ArraySignal(namedtuple('ArraySignal', 'signal grid center_signal configuration temperature')):
@@ -154,9 +146,7 @@ def __new__(cls, signal, grid, center_signal=None, configuration=None, temperatu
         return self
 
     def __repr__(self):
-        return 'ArraySignal(\n' + ',\n'.join(
-            '    {0} = {1}'.format(name, repr(data).replace('\n', '\n      '))
-            for name, data in zip(['signal', 'grid', 'center_signal', 'configuration', 'temperature'], self)) + ')'
+        return utils.get_named_tuple__repr__(self)
 
 
 class HrirSignal(namedtuple('HrirSignal', 'l r grid center_signal')):
@@ -188,9 +178,7 @@ def __new__(cls, l, r, grid, center_signal=None):
         return self
 
     def __repr__(self):
-        return 'HrirSignal(\n' + ',\n'.join(
-            '    {0} = {1}'.format(name, repr(data).replace('\n', '\n      '))
-            for name, data in zip(['l', 'r', 'grid', 'center_signal'], self)) + ')'
+        return utils.get_named_tuple__repr__(self)
 
 
 def read_miro_struct(file_name, channel='irChOne', transducer_type='omni', scatter_radius=None,
@@ -236,7 +224,7 @@ def read_miro_struct(file_name, channel='irChOne', transducer_type='omni', scatt
             center_signal = TimeSignal(signal=_np.squeeze(current_data['irCenter']).T,
                                        fs=_np.squeeze(current_data['fs']))
         except KeyError:
-            print('WARNING: Center signal not included in miro struct, use extended miro_to_struct.m!')
+            print('WARNING: Center signal not included in miro struct, use extended miro_to_struct.m!', file=sys.stderr)
             center_signal = None
 
     mic_grid = SphericalGrid(azimuth=_np.squeeze(current_data['azimuth']),
@@ -245,8 +233,8 @@ def read_miro_struct(file_name, channel='irChOne', transducer_type='omni', scatt
                              weight=_np.squeeze(current_data['quadWeight']))
 
     if (mic_grid.colatitude < 0).any():
-        print("WARNING: The 'colatitude' data contains negative values, which is an indication that it is actually "
-              "elevation")
+        print('WARNING: The "colatitude" data contains negative values, which is an indication that it is actually '
+              'elevation', file=sys.stderr)
 
     if _np.squeeze(current_data['scatterer']):
         sphere_config = 'rigid'
@@ -383,7 +371,7 @@ def empty_time_signal(no_of_signals, signal_length):
        .air_temperature  Average temperature in [C]
     """
     return _np.rec.array(_np.zeros(no_of_signals,
-                                   dtype=[('signal', str(signal_length) + 'f8'),
+                                   dtype=[('signal', f'{signal_length}f8'),
                                           ('fs', 'f8'),
                                           ('azimuth', 'f8'),
                                           ('colatitude', 'f8'),
@@ -447,8 +435,6 @@ def write_SSR_IRs(filename, time_data_l, time_data_r, wavformat='float32'):
     ValueError
         in case integer format should be exported and amplitude exceeds 1.0
     """
-    import sys
-
     # make lower case and remove spaces
     wavformat = wavformat.lower().strip()
 

sound_field_analysis/lebedev.py

@@ -1,4 +1,5 @@
-"""Generate Lebedev grid and coefficients
+"""
+Generate Lebedev grid and coefficients
 This module only exposes the function  `lebGrid = lebedev.genGrid(degree)`.
 
 lebGrid is a named tuple containing the coordinates .x, .y, .z and the weights .w
@@ -211,4 +212,4 @@ def genGrid(n):
         lebGrid.w = leb[:, 3]
         return lebGrid
     except KeyError:
-        raise ValueError('No grid available for degree', n)
+        raise ValueError(f'No grid available for degree {n}')