Documentation update

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Petrônio Cândido 2020-01-24 00:45:40 -03:00
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#!/usr/bin/python
# -*- coding: utf8 -*-
import os
import numpy as np
import matplotlib.pylab as plt
import pandas as pd
from pyFTS.common import Util as cUtil, FuzzySet
from pyFTS.partitioners import Grid, Entropy, Util as pUtil, Simple
from pyFTS.benchmarks import benchmarks as bchmk, Measures
from pyFTS.models import chen, yu, cheng, ismailefendi, hofts, pwfts, tsaur, song, sadaei, ifts
from pyFTS.models.ensemble import ensemble
from pyFTS.common import Membership, Util
from pyFTS.benchmarks import arima, quantreg, BSTS, gaussianproc, knn
from pyFTS.common import Transformations
tdiff = Transformations.Differential(1)
boxcox = Transformations.BoxCox(0)
from pyFTS.data import Enrollments, AirPassengers
'''
data = AirPassengers.get_data()
roi = Transformations.ROI()
#plt.plot(data)
_roi = roi.apply(data)
#plt.plot(_roi)
plt.plot(roi.inverse(_roi, data))
'''
'''
data = AirPassengers.get_dataframe()
data['Month'] = pd.to_datetime(data['Month'], format='%Y-%m')
trend = Transformations.LinearTrend(data_field='Passengers', index_field='Month',
index_type='datetime', datetime_mask='%Y-%d')
trend.train(data)
plt.plot(data['Passengers'].values)
plt.plot(trend.trend(data))
detrend = trend.apply(data)
plt.plot(trend.inverse(detrend, data, date_offset=pd.DateOffset(months=1)))
'''
data = Enrollments.get_dataframe()
trend = Transformations.LinearTrend(data_field='Enrollments', index_field='Year')
trend.train(data)
plt.plot(data['Enrollments'].values)
plt.plot(trend.trend(data)) #)
detrend = trend.apply(data)
plt.plot(trend.inverse(detrend, data))
plt.show()
print(data)