36 lines
745 B
Python
36 lines
745 B
Python
import numpy as np
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import theano
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from theano import tensor as T
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theano.config.profile_memory = True
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theano.config.profile = True
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SLOPE = 3.1
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INTERCEPT = -1.2
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def residual_stats_theano(x, y):
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expected = SLOPE * x + INTERCEPT
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residuals = y - expected
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return residuals.mean(), residuals.std()
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x_var = T.vector()
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y_var = T.vector()
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residual_stats = theano.function(
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inputs=[x_var, y_var],
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outputs=residual_stats_theano(x_var, y_var),
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allow_input_downcast=True,
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profile=True,
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)
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if __name__ == '__main__':
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x = np.linspace(-10, 10, 1000)
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y = SLOPE * x + INTERCEPT
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y += np.random.normal(loc=0.1, scale=0.5, size=x.shape)
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mn, std = residual_stats(x, y)
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print('Residual mean=', mn, ', std=', std)
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