I do a lot of work entirely in an IPython notebook and it can be annoying to switch back and forth from a browser to the command line to look up function usage. I therefore wrote this little utility. Given a numpy function name, it will look up the function's source on GitHub, and parse the usage comment at the top of the function.
This code requires the BeautifulSoup 4 library, which is readily pip'd.
Here's an example:
>> import npdoc
>> npd('meshgrid')
>> Return coordinate matrices from coordinate vectors.
Make N-D coordinate arrays for vectorized evaluations of
N-D scalar/vector fields over N-D grids, given
one-dimensional coordinate arrays x1, x2,..., xn.
.. versionchanged:: 1.9
1-D and 0-D cases are allowed.
...
(Not showing the full output because there's a lot)
You can also specify to only see the first or last lines with the nl argument. A positive argument gives the first N lines:
>> import npdoc
>> npd('meshgrid', nl = 4)
>> Return coordinate matrices from coordinate vectors.
Make N-D coordinate arrays for vectorized evaluations of
N-D scalar/vector fields over N-D grids, given
And a negative argument gives the last N lines:
>> import npdoc
>> npd('meshgrid', nl = -4)
>> >>> y = np.arange(-5, 5, 0.1)
>>> xx, yy = np.meshgrid(x, y, sparse=True)
>>> z = np.sin(xx**2 + yy**2) / (xx**2 + yy**2)
>>> h = plt.contourf(x,y,z)
Note: in the case of the base NumPy functions, like np.array, the source is more difficult to get to and to parse (those functions are written in C, too), so in that case, npd() will just open a browser with the formatted webpage. If you just want to go straight to the formatted webpage anyway, just do npd('meshgrid', browser = True).