Source code for example

"""Docstring for the example.py module.

Modules names should have short, all-lowercase names.  The module name may
have underscores if this improves readability.

Every module should have a docstring at the very top of the file.  The
module's docstring may extend over multiple lines.  If your docstring does
extend over multiple lines, the closing three quotation marks must be on
a line by itself, preferably preceded by a blank line.

"""
from __future__ import division, absolute_import, print_function

import os  # standard library imports first

# Do NOT import using *, e.g. from numpy import *
#
# Import the module using
#
#   import numpy
#
# instead or import individual functions as needed, e.g
#
#  from numpy import array, zeros
#
# If you prefer the use of abbreviated module names, we suggest the
# convention used by NumPy itself::

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt

# These abbreviated names are not to be used in docstrings; users must
# be able to paste and execute docstrings after importing only the
# numpy module itself, unabbreviated.


[docs]def foo(var1, var2, *args, long_var_name='hi', **kwargs): r"""Summarize the function in one line. Several sentences providing an extended description. Refer to variables using back-ticks, e.g. `var`. Parameters ---------- var1 : array_like Array_like means all those objects -- lists, nested lists, etc. -- that can be converted to an array. We can also refer to variables like `var1`. var2 : int The type above can either refer to an actual Python type (e.g. ``int``), or describe the type of the variable in more detail, e.g. ``(N,) ndarray`` or ``array_like``. *args : iterable Other arguments. long_var_name : {'hi', 'ho'}, optional Choices in brackets, default first when optional. **kwargs : dict Keyword arguments. Returns ------- type Explanation of anonymous return value of type ``type``. describe : type Explanation of return value named `describe`. out : type Explanation of `out`. type_without_description Other Parameters ---------------- only_seldom_used_keywords : type Explanation. common_parameters_listed_above : type Explanation. Raises ------ BadException Because you shouldn't have done that. See Also -------- numpy.array : Relationship (optional). numpy.ndarray : Relationship (optional), which could be fairly long, in which case the line wraps here. numpy.dot, numpy.linalg.norm, numpy.eye Notes ----- Notes about the implementation algorithm (if needed). This can have multiple paragraphs. You may include some math: .. math:: X(e^{j\omega } ) = x(n)e^{ - j\omega n} And even use a Greek symbol like :math:`\omega` inline. References ---------- Cite the relevant literature, e.g. [1]_. You may also cite these references in the notes section above. .. [1] O. McNoleg, "The integration of GIS, remote sensing, expert systems and adaptive co-kriging for environmental habitat modelling of the Highland Haggis using object-oriented, fuzzy-logic and neural-network techniques," Computers & Geosciences, vol. 22, pp. 585-588, 1996. Examples -------- These are written in doctest format, and should illustrate how to use the function. >>> a = [1, 2, 3] >>> print([x + 3 for x in a]) [4, 5, 6] >>> print("a\nb") a b """ # After closing class docstring, there should be one blank line to # separate following codes (according to PEP257). # But for function, method and module, there should be no blank lines # after closing the docstring. pass