mirror of
https://github.com/webclinic017/drift.git
synced 2026-08-04 22:57:46 +00:00
Mark Aron Szulyovszky
54 lines
1.2 KiB
Python
54 lines
1.2 KiB
Python
import numpy as np
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import pandas as pd
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from training.walk_forward import walk_forward_train_test
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from sklearn.base import BaseEstimator
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no_of_rows = 100
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def __generate_test_data(no_of_rows):
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no_columns = 6
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X = [[row] * no_columns for row in range(no_of_rows)]
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assert X[0][0] == 0
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assert X[1][0] == 1
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assert X[2][0] == 2
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assert X[3][0] == 3
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X = pd.DataFrame(X)
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y = [row+1 for row in range(no_of_rows)]
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assert y[0] == 1
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assert y[1] == 2
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assert y[2] == 3
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y = pd.Series(y)
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return X, y
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def test_walk_forward_train_test():
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X, y = __generate_test_data(no_of_rows)
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window_length = 10
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class StubModel(BaseEstimator):
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def fit(self, X, y):
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assert len(X) == window_length
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for i in range(len(X)):
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assert X[i][0] + 1 == y[i]
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def predict(self, X):
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return np.array([X[0][0] + 1])
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model = StubModel()
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scaler = None
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models, predictions = walk_forward_train_test(
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model_name='test',
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model=model,
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X=X,
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y=y,
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target_returns=y,
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window_size=window_length,
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retrain_every=10,
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scaler=scaler)
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for i in range(window_length, no_of_rows):
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predictions[i] == y[i]
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