#!/usr/bin/env python
# -*- coding: utf-8 -*-
#--------------------------------------------------------------------------------------------------
# Program Name: vis
# Program Description: Helps analyze music with computers.
#
# Filename: controllers/experimenters/aggregator.py
# Purpose: Aggregating experimenters.
#
# Copyright (C) 2013 Christopher Antila
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Affero General Public License as
# published by the Free Software Foundation, either version 3 of the
# License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Affero General Public License for more details.
#
# You should have received a copy of the GNU Affero General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#--------------------------------------------------------------------------------------------------
"""
.. codeauthor:: Christopher Antila <crantila@fedoraproject.org>
Aggregating experimenters.
"""
import pandas
from vis.analyzers import experimenter
[docs]class ColumnAggregator(experimenter.Experimenter):
"""
Experiment that aggregates data from all columns of a :class:`DataFrame`, a list of \
:class:`DataFrame` objects, or a list of :class:`Series`, into a single :class:`Series`. \
Aggregation is done through addition. If a :class:`DataFrame` has a column with the name \
:obj:`u'all'`, it will *not* be included in the aggregation.
"""
def __init__(self, index, settings=None):
"""
:param index: The data to aggregate. You should ensure the row index of each pandas object \
can be sensibly combined. The data should be numbers.
:type index: :class:`pandas.DataFrame` or :obj:`list` of :class:`pandas.DataFrame` or of \
:class:`pandas.Series`
:param settings: This indexer uses no settings, so this is ignored.
:type settings: :obj:`dict` or :obj:`None`
"""
super(ColumnAggregator, self).__init__(index, None)
[docs] def run(self):
"""
Run the :class:`ColumnAggregator` experiment.
:returns: A :class:`Series` with an index that is the combination of all indices of the \
provided pandas objects, and the value is the sum of all values in the pandas objects.
:rtype: :class:`pandas.Series`
"""
# make sure we have a single DataFrame
if isinstance(self._index, list):
if isinstance(self._index[0], pandas.DataFrame):
self._index = [ColumnAggregator(x).run() for x in self._index]
# combine the list-of-Series into a DataFrame
self._index = pandas.DataFrame(dict([(i, x) for i, x in enumerate(self._index)]))
# make the sum aggregation
return self._index.select(lambda x: x != u'all', axis=1).sum(axis=1, skipna=True)