NeuroTools supplies a dependency checker to gracefully disable functionality for which the required dependencies are not installed, without affecting other functionality. If you would like to use these facilities to add a dependency to a non-standard python module, please see the “check_dependency” function or the various modules that use it for examples.
If you are looking to contribute functionality, please provide also tests for said functionality. See the test folder for examples of testing.
The complete NeuroTools test suite can be run as follows:
$ nosetests --with-coverage --cover-package=NeuroTools
The python “nose” unittesting suite is a dependency here. On ubuntu/debian, install it using:
$ sudo apt-get install python-nose python-coverage
Tests for each packages can be run individually, for example for the NeuroTools.stgen sub-package:
$ python test/test_stgen.py
All of NeuroTools in under GPL with the copyright remaining with contributors. In practice, since there maybe many contributions to a given module, we have until now just attributed a global NeuroTools copyright to all contributors equally. It is therefore understood that all copyright holders would need vote to make any licensing changes. Please contact existing core developers if you would like to submit code, but have a problem with submitting code to NeuroTools under these license terms, or if you would like to be added to the list of NeuroTools copyright holders.
Here are described some guidelines for formatting and content of Python “doc strings” in NeuroTools
Here is a template for providing doc strings for functions:
def function(...):
"""
A description of what is the function doing and returning. Few lines
Inputs:
param1 - what is param 1
param2 - what is param 2
....
Examples:
>> One or several examples showing how it can be used
See also:
functions related to, used by the function.
"""
The top level module doc string should inform the user about the structure of the module without having to look at the code The module docstring is the doc you can have if, for example, you do, in ipython (or with help() in python):
>> import numpy
>> ?numpy
>> import scipy.optimize
>> ?scipy.optimize
As you can see, it’s a summary of a module organization, its functions, and so on... It’s a text that should be inserted at the top of the file, and I suggest the following template:
"""
== Name.of.the.module ==
A short text describing how the module is useful, crucial, powerful
Classes
---------
Object1 - The first type of object that can be created with the module
Object2 - One other type of object and what we can do with
Functions
---------
function1 - A key function of the module, and what we can do with
function2 - Same as before...
"""
An example for the stgen module would be as follows:
"""
NeuroTools.stgen
================
A collection of tools for stochastic process generation.
Classes
---------
StGen - Object to generate stochastic processes of various kinds
and return them as SpikeTrain or AnalogSignal objects.
Functions
-----------
shotnoise_fromspikes - Convolves the provided spike train with shot
decaying exponential.
gamma_hazard - Compute the hazard function for a gamma
process with parameters a,b.
"""