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DOC: Refactor util docstrings to numpydoc format #23

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81ae6cb
Refactor group.py docstrings to numpydoc format
addisonlynch May 22, 2019
3da010e
Refactor system.py docstrings to numpydoc format
addisonlynch May 22, 2019
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82 changes: 51 additions & 31 deletions fecon236/util/group.py
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Original file line number Diff line number Diff line change
@@ -1,14 +1,19 @@
# Python Module for import Date : 2018-06-17
# vim: set fileencoding=utf-8 ff=unix tw=78 ai syn=python : per PEP 0263
'''
_______________| group.py :: Group utilities
"""Group utilities

CHANGE LOG For LATEST version, see https://git.io/fecon236
2018-06-17 Spin-off groupcotr() to futures.cftc module.
2018-06-16 Move covdiflog() to math.matrix module.
2018-06-14 Spin-off group stuff from top.py.
2018-03-12 fecon235.py, fecon235 v5.18.0312, https://git.io/fecon235
'''
Notes
-----
For LATEST version, see https://git.io/fecon236

Change Log
----------

* 2018-06-17 Spin-off `groupcotr` to `futures.cftc` module.
* 2018-06-16 Move `covdiflog` to `math.matrix` module.
* 2018-06-14 Spin-off group stuff from `top.py`.
* 2018-03-12 `fecon235.py`, fecon235 v5.18.0312, https://git.io/fecon235
"""

from __future__ import absolute_import, print_function, division

Expand Down Expand Up @@ -36,7 +41,7 @@


def groupget(ggdic=group4d, maxi=0):
'''Retrieve and create group dataframe, given group dictionary.'''
"""Retrieve and create group dataframe, given group dictionary."""
# Since dictionaries are unordered, create SORTED list of keys:
keys = [key for key in sorted(ggdic)]
# Download individual dataframes as values into a dictionary:
Expand All @@ -50,11 +55,16 @@ def groupget(ggdic=group4d, maxi=0):


def groupfun(fun, groupdf, *pargs, **kwargs):
'''Use fun(ction) column-wise, then output new group dataframe.'''
# In mathematics, this is known as an "operator":
# a function which takes another function as argument.
# Examples of fun: pcent, normalize, etc. See grouppc() next.
# See groupget() to retrieve and create group dataframe.
"""Use fun(ction) column-wise, then output new group dataframe.

Notes
-----
In mathematics, this is known as an "operator":
a function which takes another function as argument.
Examples of fun: `pcent`, `normalize`, etc. See `grouppc` next.

.. seealso:: `groupget` to retrieve and create group dataframe.
"""
keys = list(groupdf.columns)
# Compute individual columns as dataframes in a list:
out = [tool.todf(fun(tool.todf(groupdf[key]), *pargs, **kwargs))
Expand All @@ -68,24 +78,33 @@ def groupfun(fun, groupdf, *pargs, **kwargs):


def grouppc(groupdf, freq=1):
'''Create overlapping pcent dataframe, given a group dataframe.'''
# See groupget() to retrieve and create group dataframe.
# Very useful to visualize as boxplot, see fred-georeturns.ipynb
"""Create overlapping pcent dataframe, given a group dataframe.

Notes
-----
.. seealso:: `groupget` to retrieve and create group dataframe.

Very useful to visualize as boxplot, see fred-georeturns.ipynb
"""
return groupfun(tool.pcent, groupdf, freq)


def groupdiflog(groupdf, lags=1):
'''Difference between lagged log(data) for columns in group dataframe.'''
# See groupget() to retrieve and create group dataframe.
"""Difference between lagged log(data) for columns in group dataframe.

.. seealso:: See `groupget` to retrieve and create group dataframe.
"""
return groupfun(tool.diflog, groupdf, lags)


def groupgeoret(groupdf, yearly=256, order=True):
'''Geometric mean returns, non-overlapping, for group dataframe.
Argument "yearly" refers to annual frequency, e.g.
256 for daily trading days, 12 for monthly, 4 for quarterly.
ATTN: Use groupgemrat() instead for greater accuracy.
'''
"""Geometric mean returns, non-overlapping, for group dataframe.

Argument `yearly` refers to annual frequency, e.g.
256 for daily trading days, 12 for monthly, 4 for quarterly.

.. note:: Use `groupgemrat` instead for greater accuracy.
"""
keys = list(groupdf.columns)
# Use list comprehension to store lists from georet():
geo = [tool.georet(tool.todf(groupdf[k]), yearly) + [k] for k in keys]
Expand All @@ -97,12 +116,13 @@ def groupgeoret(groupdf, yearly=256, order=True):


def groupgemrat(groupdf, yearly=256, order=False, n=2):
'''Geometric mean rates, non-overlapping, for group dataframe.
Argument "yearly" refers to annual frequency, e.g.
256 for daily trading days, 12 for monthly, 4 for quarterly.
Output is rounded to n-decimal places.
Algorithm takes KURTOSIS into account for greater accuracy.
'''
"""Geometric mean rates, non-overlapping, for group dataframe.

Argument `yearly` refers to annual frequency, e.g.
256 for daily trading days, 12 for monthly, 4 for quarterly.
Output is rounded to n-decimal places.
Algorithm takes KURTOSIS into account for greater accuracy.
"""
keys = list(groupdf.columns)
# Use list comprehension to store lists from gemrat():
gem = [tool.roundit(gemrat(tool.todf(groupdf[k]), yearly), n, echo=False)
Expand All @@ -115,7 +135,7 @@ def groupgemrat(groupdf, yearly=256, order=False, n=2):


def groupholtf(groupdf, h=12, alpha=hw.hw_alpha, beta=hw.hw_beta):
'''Holt-Winters forecasts h-periods ahead from group dataframe.'''
"""Holt-Winters forecasts h-periods ahead from group dataframe."""
forecasts = []
keys = list(groupdf.columns)
for k in keys:
Expand Down
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