Configuring the new tag for pyPI release
This commit is contained in:
parent
3297753129
commit
967d07e5bb
94
MANIFEST
94
MANIFEST
@ -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
|
@ -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
|
||||
|
||||
|
@ -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
|
||||
|
@ -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
|
||||
|
@ -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
|
||||
|
||||
|
@ -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
|
||||
|
||||
|
@ -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
|
||||
|
||||
|
@ -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
|
||||
|
||||
|
@ -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
|
||||
|
||||
|
@ -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
10
setup.py
@ -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'
|
||||
#]
|
||||
)
|
||||
|
Loading…
Reference in New Issue
Block a user