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Bugfix in models.nonstationary.util.plot_sets_conditional

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Petrônio Cândido 2018-08-07 16:31:32 -03:00
parent 2055b512ca
commit 39e0c6aa88
2 changed files with 33 additions and 2 deletions
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2
pyFTS/models/nonstationary/util.py
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@ -63,7 +63,7 @@ def plot_sets_conditional(model, data, step=1, size=[5, 5], colors=None,
for t in range: for t in range:
model.forecast([data[t]]) model.forecast([data[t]])
perturb = model.perturbation_factors(data[t]) perturb = model.conditional_perturbation_factors(data[t])
for ct, key in enumerate(model.partitioner.ordered_sets): for ct, key in enumerate(model.partitioner.ordered_sets):
set = model.partitioner.sets[key] set = model.partitioner.sets[key]

33
pyFTS/tests/nonstationary.py
View File

@ -11,7 +11,7 @@ import pandas as pd
from pyFTS.data import TAIEX, NASDAQ, SP500, artificial, mackey_glass from pyFTS.data import TAIEX, NASDAQ, SP500, artificial, mackey_glass
mackey_glass.get_data() mackey_glass.get_data()
'''
datasets = { datasets = {
"TAIEX": TAIEX.get_data()[:4000], "TAIEX": TAIEX.get_data()[:4000],
"SP500": SP500.get_data()[10000:14000], "SP500": SP500.get_data()[10000:14000],
@ -53,7 +53,38 @@ partitions = {'CMIV': {'BoxCox(0)': 36, 'Differential(1)': 11, 'None': 8},
'SP500': {'BoxCox(0)': 33, 'Differential(1)': 7, 'None': 33}, 'SP500': {'BoxCox(0)': 33, 'Differential(1)': 7, 'None': 33},
'TAIEX': {'BoxCox(0)': 39, 'Differential(1)': 31, 'None': 33}} 'TAIEX': {'BoxCox(0)': 39, 'Differential(1)': 31, 'None': 33}}
from pyFTS.models.nonstationary import partitioners as nspart, cvfts, util as nsUtil
def model_details(ds, tf, train_split, test_split):
data = datasets[ds]
train = data[:train_split]
test = data[train_split:test_split]
transformation = transformations[tf]
fs = nspart.simplenonstationary_gridpartitioner_builder(data=train, npart=partitions[ds][tf],
transformation=transformation)
model = nsfts.NonStationaryFTS(partitioner=fs)
model.fit(train)
print(model)
forecasts = model.predict(test)
residuals = np.array(test[1:]) - np.array(forecasts[:-1])
fig, axes = plt.subplots(nrows=2, ncols=1, figsize=[15, 10])
axes[0].plot(test[1:], label="Original")
axes[0].plot(forecasts[:-1], label="Forecasts")
axes[1].set_title("Residuals")
axes[1].plot(residuals)
handles0, labels0 = axes[0].get_legend_handles_labels()
lgd = axes[0].legend(handles0, labels0, loc=2)
nsUtil.plot_sets_conditional(model, test, step=10, size=[12, 5])
model_details('NASDAQ','None',200,2000)
'''
tag = 'benchmarks' tag = 'benchmarks'