Documentation update
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docs/build/doctrees/environment.pickle
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pyFTS/tests/transformations.py
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pyFTS/tests/transformations.py
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#!/usr/bin/python
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# -*- coding: utf8 -*-
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import os
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import numpy as np
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import matplotlib.pylab as plt
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import pandas as pd
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from pyFTS.common import Util as cUtil, FuzzySet
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from pyFTS.partitioners import Grid, Entropy, Util as pUtil, Simple
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from pyFTS.benchmarks import benchmarks as bchmk, Measures
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from pyFTS.models import chen, yu, cheng, ismailefendi, hofts, pwfts, tsaur, song, sadaei, ifts
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from pyFTS.models.ensemble import ensemble
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from pyFTS.common import Membership, Util
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from pyFTS.benchmarks import arima, quantreg, BSTS, gaussianproc, knn
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from pyFTS.common import Transformations
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tdiff = Transformations.Differential(1)
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boxcox = Transformations.BoxCox(0)
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from pyFTS.data import Enrollments, AirPassengers
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'''
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data = AirPassengers.get_data()
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roi = Transformations.ROI()
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#plt.plot(data)
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_roi = roi.apply(data)
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#plt.plot(_roi)
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plt.plot(roi.inverse(_roi, data))
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'''
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'''
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data = AirPassengers.get_dataframe()
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data['Month'] = pd.to_datetime(data['Month'], format='%Y-%m')
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trend = Transformations.LinearTrend(data_field='Passengers', index_field='Month',
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index_type='datetime', datetime_mask='%Y-%d')
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trend.train(data)
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plt.plot(data['Passengers'].values)
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plt.plot(trend.trend(data))
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detrend = trend.apply(data)
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plt.plot(trend.inverse(detrend, data, date_offset=pd.DateOffset(months=1)))
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'''
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data = Enrollments.get_dataframe()
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trend = Transformations.LinearTrend(data_field='Enrollments', index_field='Year')
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trend.train(data)
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plt.plot(data['Enrollments'].values)
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plt.plot(trend.trend(data)) #)
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detrend = trend.apply(data)
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plt.plot(trend.inverse(detrend, data))
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plt.show()
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print(data)
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