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Configuring the new tag for pyPI release

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Petrônio Cândido 2018-03-06 16:08:14 -03:00
parent 3297753129
commit 967d07e5bb
11 changed files with 166 additions and 72 deletions
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94
MANIFEST
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@ -0,0 +1,94 @@
# file GENERATED by distutils, do NOT edit
setup.cfg
setup.py
pyFTS/__init__.py
pyFTS/benchmarks/Measures.py
pyFTS/benchmarks/ResidualAnalysis.py
pyFTS/benchmarks/Util.py
pyFTS/benchmarks/__init__.py
pyFTS/benchmarks/arima.py
pyFTS/benchmarks/benchmarks.py
pyFTS/benchmarks/distributed_benchmarks.py
pyFTS/benchmarks/naive.py
pyFTS/benchmarks/parallel_benchmarks.py
pyFTS/benchmarks/quantreg.py
pyFTS/common/Composite.py
pyFTS/common/FLR.py
pyFTS/common/FuzzySet.py
pyFTS/common/Membership.py
pyFTS/common/SortedCollection.py
pyFTS/common/Transformations.py
pyFTS/common/Util.py
pyFTS/common/__init__.py
pyFTS/common/flrg.py
pyFTS/common/fts.py
pyFTS/common/tree.py
pyFTS/data/AirPassengers.py
pyFTS/data/Enrollments.py
pyFTS/data/INMET.py
pyFTS/data/NASDAQ.py
pyFTS/data/SONDA.py
pyFTS/data/SP500.py
pyFTS/data/TAIEX.py
pyFTS/data/__init__.py
pyFTS/data/artificial.py
pyFTS/data/common.py
pyFTS/data/sunspots.py
pyFTS/models/__init__.py
pyFTS/models/chen.py
pyFTS/models/cheng.py
pyFTS/models/hofts.py
pyFTS/models/hwang.py
pyFTS/models/ifts.py
pyFTS/models/ismailefendi.py
pyFTS/models/pwfts.py
pyFTS/models/sadaei.py
pyFTS/models/song.py
pyFTS/models/yu.py
pyFTS/models/ensemble/__init__.py
pyFTS/models/ensemble/ensemble.py
pyFTS/models/ensemble/multiseasonal.py
pyFTS/models/multivariate/FLR.py
pyFTS/models/multivariate/__init__.py
pyFTS/models/multivariate/common.py
pyFTS/models/multivariate/flrg.py
pyFTS/models/multivariate/mvfts.py
pyFTS/models/multivariate/variable.py
pyFTS/models/nonstationary/__init__.py
pyFTS/models/nonstationary/common.py
pyFTS/models/nonstationary/cvfts.py
pyFTS/models/nonstationary/flrg.py
pyFTS/models/nonstationary/honsfts.py
pyFTS/models/nonstationary/nsfts.py
pyFTS/models/nonstationary/partitioners.py
pyFTS/models/nonstationary/perturbation.py
pyFTS/models/nonstationary/util.py
pyFTS/models/seasonal/SeasonalIndexer.py
pyFTS/models/seasonal/__init__.py
pyFTS/models/seasonal/cmsfts.py
pyFTS/models/seasonal/common.py
pyFTS/models/seasonal/msfts.py
pyFTS/models/seasonal/partitioner.py
pyFTS/models/seasonal/sfts.py
pyFTS/partitioners/CMeans.py
pyFTS/partitioners/Entropy.py
pyFTS/partitioners/FCM.py
pyFTS/partitioners/Grid.py
pyFTS/partitioners/Huarng.py
pyFTS/partitioners/Util.py
pyFTS/partitioners/__init__.py
pyFTS/partitioners/parallel_util.py
pyFTS/partitioners/partitioner.py
pyFTS/probabilistic/ProbabilityDistribution.py
pyFTS/probabilistic/__init__.py
pyFTS/probabilistic/kde.py
pyFTS/tests/__init__.py
pyFTS/tests/cmsfts.py
pyFTS/tests/distributed.py
pyFTS/tests/ensemble.py
pyFTS/tests/general.py
pyFTS/tests/multivariate.py
pyFTS/tests/nonstationary.py
pyFTS/tests/pwfts.py
pyFTS/tests/seasonal.py
pyFTS/tests/sfts.py

16
pyFTS/data/AirPassengers.py
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@ -1,10 +1,16 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/AirPassengers.csv')
passengers = pd.read_csv(filename, sep=",")
passengers = np.array(passengers["Passengers"])
return passengers
dat = get_dataframe()
dat = np.array(dat["Passengers"])
return dat
def get_dataframe():
dat = common.get_dataframe('data/AirPassengers.csv',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/AirPassengers.csv',
sep=",")
return dat

17
pyFTS/data/Enrollments.py
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@ -1,11 +1,16 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/Enrollments.csv')
enrollments = pd.read_csv(filename, sep=";")
enrollments = np.array(enrollments["Enrollments"])
return enrollments
dat = get_dataframe()
dat = np.array(dat["Enrollments"])
return dat
def get_dataframe():
dat = common.get_dataframe('data/Enrollments.csv',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/Enrollments.csv',
sep=";")
return dat

5
pyFTS/data/INMET.py
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@ -16,7 +16,10 @@
from pyFTS.data import common
import pandas as pd
def get_dataframe():
dat = common.get_dataframe('data/INMET.csv.bz2',sep=";", compression='bz2')
dat = common.get_dataframe('data/INMET.csv.bz2',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/INMET.csv.bz2',
sep=";", compression='bz2')
dat["DataHora"] = pd.to_datetime(dat["DataHora"], format='%d/%m/%Y %H:%M')
return dat

18
pyFTS/data/NASDAQ.py
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@ -1,11 +1,17 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/NASDAQ.csv.bz2')
dat = pd.read_csv(filename, sep=";", compression='bz2')
dat = np.array(dat["avg"])
def get_data(field):
dat = get_dataframe()
dat = np.array(dat[field])
return dat
def get_dataframe():
dat = common.get_dataframe('data/NASDAQ.csv.bz2',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/data/NASDAQ.csv.bz2',
sep=";", compression='bz2')
return dat

12
pyFTS/data/SONDA.py
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@ -1,18 +1,18 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data(field):
filename = pkg_resources.resource_filename('pyFTS', 'data/SONDA_BSB.csv.bz2')
dat = pd.read_csv(filename, sep=";", compression='bz2')
dat = get_dataframe()
dat = np.array(dat[field])
return dat
def get_dataframe():
filename = pkg_resources.resource_filename('pyFTS', 'data/SONDA_BSB.csv.bz2')
dat = pd.read_csv(filename, sep=";", compression='bz2')
dat = common.get_dataframe('data/SONDA_BSB.csv.bz2',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/SONDA_BSB.csv.bz2',
sep=";", compression='bz2')
dat["datahora"] = pd.to_datetime(dat["datahora"], format='%Y-%m-%d %H:%M:%S')
return dat

11
pyFTS/data/SP500.py
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@ -1,11 +1,12 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/SP500.csv.bz2')
dat = pd.read_csv(filename, sep=",", compression='bz2')
def get_dataframe():
dat = common.get_dataframe('data/SP500.csv.bz2',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/SP500.csv.bz2',
sep=",", compression='bz2')
dat = np.array(dat["Avg"])
return dat

12
pyFTS/data/TAIEX.py
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@ -1,18 +1,18 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/TAIEX.csv.bz2')
dat = pd.read_csv(filename, sep=",", compression='bz2')
dat = get_dataframe()
dat = np.array(dat["avg"])
return dat
def get_dataframe():
filename = pkg_resources.resource_filename('pyFTS', 'data/TAIEX.csv.bz2')
dat = pd.read_csv(filename, sep=",", compression='bz2')
dat = common.get_dataframe('data/TAIEX.csv.bz2',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/TAIEX.csv.bz2',
sep=";", compression='bz2')
dat["Date"] = pd.to_datetime(dat["Date"])
return dat

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pyFTS/data/sunspots.py
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@ -1,11 +1,15 @@
from pyFTS.data import common
import pandas as pd
import numpy as np
import os
import pkg_resources
def get_data():
filename = pkg_resources.resource_filename('pyFTS', 'data/sunspots.csv')
dat = pd.read_csv(filename, sep=",")
dat = get_dataframe()
dat = np.array(dat["SUNACTIVITY"])
return dat
def get_dataframe():
dat = common.get_dataframe('data/sunspots.csv',
'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/sunspots.csv',
sep=",")
return dat

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pyFTS/tests/general.py
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@ -9,31 +9,6 @@ import numpy as np
import pandas as pd
from pyFTS.common import Transformations
from pyFTS.benchmarks import benchmarks as bchmk
from pyFTS.data import INMET
bc = Transformations.BoxCox(0)
diff = Transformations.Differential(1)
#ix = SeasonalIndexer.LinearSeasonalIndexer([12, 24], [720, 1],[False, False])
"""
DATASETS
"""
from pyFTS.data import Enrollments
data = Enrollments.get_data()
from pyFTS.partitioners import Grid
from pyFTS.models import song, chen, yu, sadaei, ismailefendi, cheng, hofts
train = data
test = data
fs = Grid.GridPartitioner(train, 10) #, transformation=bc)
#tmp = bchmk.simpleSearch_RMSE(train, test, hofts.HighOrderFTS, range(4,12), [2], tam=[10, 5])
model = hofts.HighOrderFTS("", partitioner=fs)
model.fit(train, order=3)
print(model)
print(INMET.get_dataframe())

10
setup.py
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@ -6,9 +6,9 @@ setup(
'pyFTS.models', 'pyFTS.models.seasonal', 'pyFTS.partitioners', 'pyFTS.probabilistic',
'pyFTS.tests', 'pyFTS.models.nonstationary', 'pyFTS.models.multivariate'],
#package_dir={}
package_data={'pyFTS.data': ['*.csv','*.csv.bz2']},
#package_data={'pyFTS.data': ['*.csv','*.csv.bz2']},
#data_files=[('data', ['pyFTS/data/Enrollments.csv', 'pyFTS/data/AirPassengers.csv'])],
include_package_data=True,
#include_package_data=True,
version='1.2.3',
description='Fuzzy Time Series for Python',
author='Petronio Candido L. e Silva',
@ -22,7 +22,7 @@ setup(
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
],
install_requires=[
'numpy','pandas','matplotlib','dill','copy','dispy','multiprocessing','joblib','statsmodels'
]
#install_requires=[
# 'numpy','pandas','matplotlib','dill','copy','dispy','multiprocessing','joblib','statsmodels'
#]
)