some refactorings and rst-compliant readme

README.md

@@ -1,4 +1,17 @@
-Note: The old braindecode repository has been moved to https://github.com/robintibor/braindevel.
+Note: The old braindecode repository has been moved to
+https://github.com/robintibor/braindevel.
+
+Braindecode
+===========
 
-# Braindecode
 A deep learning for raw time-domain EEG decoding toolbox.
+
+Installation
+============
+
+Install pytorch from http://pytorch.org/.
+
+Documentation
+=============
+
+Documentation is online under http://braindecode.readthedocs.io/

braindecode/datasets/signal_target.py

@@ -0,0 +1,20 @@
+class SignalAndTarget(object):
+    def __init__(self, X, y):
+        assert len(X) == len(y)
+        self.X = X
+        self.y = y
+
+
+def apply_to_X_y(fn, *sets):
+    X = fn(*[s.X for s in sets])
+    y = fn(*[s.y for s in sets])
+    return SignalAndTarget(X,y)
+
+
+def split_into_two_sets(dataset, fraction=None, n_boundary=None):
+    assert fraction is not None or n_boundary is not None
+    if n_boundary is None:
+        n_boundary = int(round(len(dataset.X) * fraction))
+    first_set = apply_to_X_y(lambda a: a[:n_boundary], dataset)
+    second_set = apply_to_X_y(lambda a: a[n_boundary:], dataset)
+    return first_set, second_set

braindecode/iterators.py

@@ -1,6 +1,7 @@
 import numpy as np
 from numpy.random import RandomState
 
+
 def get_balanced_batches(n_trials, rng, shuffle, n_batches=None,
                          batch_size=None):
     """Create indices for batches balanced in size (batches will have maximum size difference of 1).

braindecode/models/shallow_fbcsp.py

@@ -2,7 +2,7 @@
 from torch import nn
 from torch.nn import init
 
-from braindecode.modules.expression import Expression
+from braindecode.torchext.modules import Expression
 from braindecode.torchext.functions import safe_log, square
 from braindecode.torchext.util import np_to_var
 

setup.py

@@ -0,0 +1,61 @@
+from setuptools import setup  # Always prefer setuptools over distutils
+from codecs import open  # To use a consistent encoding
+from os import path
+
+here = path.abspath(path.dirname(__file__))
+
+# Get the long description from the relevant file
+with open(path.join(here, 'README.md'), encoding='utf-8') as f:
+    long_description = f.read()
+
+
+setup(
+    name='Braindecode',
+
+    # Versions should comply with PEP440.  For a discussion on single-sourcing
+    # the version across setup.py and the project code, see
+    # http://packaging.python.org/en/latest/tutorial.html#version
+    version='0.1.1',
+
+    description='A deep learning for raw time-domain EEG decoding toolbox.',
+    long_description=long_description,  #this is the
+
+    # The project's main homepage.
+    url='https://github.com/robintibor/braindecode',
+
+    # Author details
+    author='Robin Tibor Schirrmeister',
+    author_email='[email protected]',
+
+    # Choose your license
+    license='BSD 3-Clause',
+
+    install_requires=['numpy','mne'],
+    #tests_require = [...]
+
+    # See https://PyPI.python.org/PyPI?%3Aaction=list_classifiers
+    classifiers=[
+        'Development Status :: 3 - Alpha',
+
+        # Indicate who your project is intended for
+        "Intended Audience :: Developers",
+        "Intended Audience :: Science/Research",
+        'Topic :: Software Development :: Build Tools',
+
+        "Topic :: Scientific/Engineering :: Artificial Intelligence",
+
+        # Pick your license as you wish (should match "license" above)
+        'License :: OSI Approved :: BSD License',
+
+        # Specify the Python versions you support here. In particular, ensure
+        # that you indicate whether you support Python 2, Python 3 or both.
+        'Programming Language :: Python :: 2.7',
+        'Programming Language :: Python :: 3.5',
+    ],
+
+    # What does your project relate to?
+    keywords='eeg deep-learning brain-state-decoding',
+
+    packages=['braindecode'],
+
+)