fix documentation (#681)

doc/source/conf.py

@@ -71,12 +71,12 @@ def __getattr__(cls, name):
 # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
+    'sphinx_autorun',
     'sphinx.ext.autodoc',
     'sphinx.ext.autosummary',
     'sphinx.ext.todo',
     'sphinx.ext.viewcode',
     'sphinxcontrib.napoleon',
-    'sphinxcontrib.autorun',
 ]
 
 # Add any paths that contain templates here, relative to this directory.

neurom/check/neuron_checks.py

@@ -103,7 +103,7 @@ def has_no_flat_neurites(neuron, tol=0.1, method='ratio'):
     Arguments:
         neuron(Neuron): The neuron object to test
         tol(float): tolerance
-        method(string): way of determining flatness, 'tolerance', 'ratio'
+        method(string): way of determining flatness, 'tolerance', 'ratio' \
         as described in :meth:`neurom.check.morphtree.get_flat_neurites`
 
     Returns:
@@ -226,7 +226,7 @@ def has_no_jumps(neuron, max_distance=30.0, axis='z'):
 def has_no_fat_ends(neuron, multiple_of_mean=2.0, final_point_count=5):
     '''Check if leaf points are too large
 
-    Arguments
+    Arguments:
         neuron(Neuron): The neuron object to test
         multiple_of_mean(float): how many times larger the final radius
         has to be compared to the mean of the final points
@@ -253,18 +253,23 @@ def has_no_fat_ends(neuron, multiple_of_mean=2.0, final_point_count=5):
 def has_no_narrow_start(neuron, frac=0.9):
     '''Check if neurites have a narrow start
 
+    Arguments:
+        neuron(Neuron): The neuron object to test
+        frac(float): Ratio that the second point must be smaller than the first
+
     Returns:
         CheckResult with a list of all first segments of neurites with a narrow start
     '''
-    bad_ids = [(neurite.root_node.id, [neurite.root_node.points[1]]) for neurite in neuron.neurites
+    bad_ids = [(neurite.root_node.id, [neurite.root_node.points[1]])
+               for neurite in neuron.neurites
                if neurite.root_node.points[1][COLS.R] < frac * neurite.root_node.points[2][COLS.R]]
     return CheckResult(len(bad_ids) == 0, bad_ids)
 
 
-def has_no_dangling_branch(n):
+def has_no_dangling_branch(neuron):
     '''Check if the neuron has dangling neurites'''
-    soma_center = n.soma.points[:, COLS.XYZ].mean(axis=0)
-    recentered_soma = n.soma.points[:, COLS.XYZ] - soma_center
+    soma_center = neuron.soma.points[:, COLS.XYZ].mean(axis=0)
+    recentered_soma = neuron.soma.points[:, COLS.XYZ] - soma_center
     radius = np.linalg.norm(recentered_soma, axis=1)
     soma_max_radius = radius.max()
 
@@ -278,14 +283,15 @@ def is_dangling(neurite):
         if neurite.type != NeuriteType.axon:
             return True
 
-        all_points = list(chain.from_iterable(_neurite.points[1:] for _neurite in iter_neurites(n)
-                                              if _neurite.type != NeuriteType.axon))
+        all_points = list(chain.from_iterable(n.points[1:]
+                                              for n in iter_neurites(neurite)
+                                              if n.type != NeuriteType.axon))
         res = [np.linalg.norm(starting_point - p[COLS.XYZ]) >= 2 * p[COLS.R] + 2
                for p in all_points]
         return all(res)
 
-    bad_ids = [(neurite.root_node.id, [neurite.root_node.points[1]])
-               for neurite in iter_neurites(n) if is_dangling(neurite)]
+    bad_ids = [(n.root_node.id, [n.root_node.points[1]])
+               for n in iter_neurites(neuron) if is_dangling(n)]
     return CheckResult(len(bad_ids) == 0, bad_ids)
 
 
@@ -294,7 +300,14 @@ def has_no_narrow_neurite_section(neuron,
                                   radius_threshold=0.05,
                                   considered_section_min_length=50):
     '''Check if the neuron has dendrites with narrow sections
-        sections below 'considered_section_min_length' are not taken into account
+
+    Arguments:
+        neuron(Neuron): The neuron object to test
+        neurite_filter(callable): filter the neurites by this callable
+        radius_threshold(float): radii below this are considered narro
+        considered_section_min_length(float): sections with length below
+        this are not taken into account
+
     Returns:
         CheckResult with result. result.info contains the narrow section ids and their
         first point

requirements_dev.txt

@@ -36,4 +36,6 @@ nosexcover>=1.0.8
 sphinx>=1.3.0
 sphinxcontrib-napoleon>=0.3.0
 sphinx_rtd_theme>=0.1.0
-sphinxcontrib-autorun
+sphinx-autorun
+pyyaml>=3.10
+future>=0.16.0

setup.py

@@ -29,7 +29,6 @@
 """ Distribution configuration for neurom
 """
 # pylint: disable=R0801
-import os
 from setuptools import setup
 from setuptools import find_packages
 
@@ -45,13 +44,9 @@
         'pyyaml>=3.10',
         'scipy>=0.13.3',
         'tqdm>=4.8.4',
+        'future>=0.16.0',
         ]
 
-# Hack to avoid installation of modules with C extensions
-# in readthedocs documentation building environment.
-if os.environ.get('READTHEDOCS') == 'True':
-    REQS = []
-
 config = {
     'description': 'NeuroM: a light-weight neuron morphology analysis package',
     'author': 'BBP Algorithm Development Team',