# -*- coding: utf-8 -*-

#

# Copyright 2017-2025 BigML

#

# Licensed under the Apache License, Version 2.0 (the "License"); you may

# not use this file except in compliance with the License. You may obtain

# a copy of the License at

#

# http://www.apache.org/licenses/LICENSE-2.0

#

# Unless required by applicable law or agreed to in writing, software

# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT

# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the

# License for the specific language governing permissions and limitations

# under the License.

"""Auxiliar class for lists of predictions combination.

"""

import logging

from bigml.util import PRECISION

LOGGER = logging.getLogger('BigML')

class MultiVoteList():

"""A multiple vote prediction in compact format

Uses a number of predictions to generate a combined prediction.

The input should be an ordered list of probability, counts or confidences

for each of the classes in the objective field.

"""

def __init__(self, predictions):

"""Init method, builds a MultiVoteList with a list of predictions

The constuctor expects a list of well formed predictions like:

[0.2, 0.34, 0.48] which might correspond to confidences of

three different classes in the objective field.

"""

if isinstance(predictions, list):

self.predictions = predictions

else:

raise ValueError("Expected a list of values to create a"

"MultiVoteList. Found %s instead" % predictions)

def extend(self, predictions_list):

"""Extending the extend method in lists

"""

if isinstance(predictions_list, MultiVoteList):

predictions_list = predictions_list.predictions

self.predictions.extend(predictions_list)

def append(self, prediction):

"""Extending the append method in lists

"""

self.predictions.append(prediction)

def combine_to_distribution(self, normalize=True):

"""Receives a list of lists. Each element is the list of probabilities

or confidences

associated to each class in the ensemble, as described in the

`class_names` attribute and ordered in the same sequence. Returns the

probability obtained by adding these predictions into a single one

by adding their probabilities and normalizing.

"""

total = 0.0

output = [0.0] * len(self.predictions[0])

for distribution in self.predictions:

for i, vote_value in enumerate(distribution):

output[i] += vote_value

total += vote_value

if not normalize:

total = len(self.predictions)

for i, value in enumerate(output):

output[i] = round(value / total, PRECISION)

return output