Merge branch 'master' of https://github.com/PYFTS/pyFTS
This commit is contained in:
commit
22de024b8f
@ -1,10 +1,9 @@
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from pyFTS.common.transformations.transformation import Transformation
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import numpy as np
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class MovingAverage(Transformation):
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def __init__(self, **kwargs):
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super(MovingAverage, self).__init__()
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super(MovingAverage, self).__init__(**kwargs)
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self.name = 'Moving Average Smoothing'
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self.steps = kwargs.get('steps',2)
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@ -20,8 +19,8 @@ class MovingAverage(Transformation):
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class ExponentialSmoothing(Transformation):
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def __init__(self, **kwargs):
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super(MovingAverage, self).__init__()
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self.name = 'Moving Average Smoothing'
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super(ExponentialSmoothing,self).__init__(**kwargs)
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self.name = 'Exponential Moving Average Smoothing'
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self.steps = kwargs.get('steps',2)
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self.beta = kwargs.get('beta',.5)
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@ -39,3 +38,53 @@ class ExponentialSmoothing(Transformation):
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def inverse(self, data, param=None, **kwargs):
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return data
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class AveragePooling(Transformation):
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def __init__(self, **kwargs):
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super(AveragePooling,self).__init__(**kwargs)
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self.name = 'Exponential Average Smoothing'
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self.kernel = kwargs.get('kernel',5)
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self.stride = kwargs.get('stride',1)
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self.padding = kwargs.get('padding','same')
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def apply(self, data):
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result = []
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if self.padding == 'same':
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for i in range(int(self.kernel/2), len(data)+int(self.kernel/2), self.stride):
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result.append(np.mean(data[np.max([0,i-self.kernel]):np.min([i, len(data)])]))
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elif self.padding == 'valid':
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for i in range(self.kernel, len(data), self.stride):
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result.append(np.mean(data[i-self.kernel:i]))
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else:
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raise ValueError('Invalid padding schema')
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return result
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def inverse(self, data, param=None, **kwargs):
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return data
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class MaxPooling(Transformation):
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def __init__(self, **kwargs):
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super(MaxPooling,self).__init__(**kwargs)
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self.name = 'Exponential Average Smoothing'
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self.kernel = kwargs.get('kernel',5)
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self.stride = kwargs.get('stride',1)
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self.padding = kwargs.get('padding','same')
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def apply(self, data):
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result = []
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if self.padding == 'same':
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for i in range(int(self.kernel/2), len(data)+int(self.kernel/2), self.stride):
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result.append(np.max(data[np.max([0,i-self.kernel]):np.min([i, len(data)])]))
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elif self.padding == 'valid':
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for i in range(self.kernel - 1, len(data), self.stride):
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result.append(np.max(data[i-self.kernel:i]))
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else:
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raise ValueError('Invalid padding schema')
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return result
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def inverse(self, data, param=None, **kwargs):
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return data
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6
setup.py
6
setup.py
@ -5,6 +5,10 @@ import setuptools
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setuptools.setup(
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name='pyFTS',
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install_requires=[
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'matplotlib',
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'numpy',
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'pandas'],
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packages=['pyFTS', 'pyFTS.benchmarks', 'pyFTS.common', 'pyFTS.common.transformations', 'pyFTS.data',
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'pyFTS.models.ensemble', 'pyFTS.models', 'pyFTS.models.seasonal', 'pyFTS.partitioners',
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'pyFTS.probabilistic', 'pyFTS.tests', 'pyFTS.models.nonstationary', 'pyFTS.models.multivariate',
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@ -28,6 +32,6 @@ setuptools.setup(
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'Intended Audience :: Education',
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'Topic :: Scientific/Engineering',
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'Development Status :: 5 - Production/Stable'
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]
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)
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