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got rid of generated files due to testing frontend
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docs/source/api/dims/math.rst

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import numpy as np
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import pymc as pm
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coords = {"time": np.arange(10), "feature": ["a", "b", "c"]}
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with pm.Model(coords=coords):
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x = pm.Normal("x", mu=0, sigma=1, dims=("time", "feature"))
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# Method-based selection and operations
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x_subset = x.isel(time=slice(0, 5)) # First 5 timesteps
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x_mean = x_subset.mean(dim="feature") # Average across features
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x_subset = x.isel(time=slice(0, 5))
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x_mean = x_subset.mean(dim="feature")
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# Dot product using method syntax
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y = pm.Normal("y", mu=0, sigma=1, dims="feature")
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dot_result = x.dot(y, dim="feature") # Shape: (time,)
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dot_result = x.dot(y, dim="feature")
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For a complete list of available methods, see the :class:`~pytensor.xtensor.type.XTensorVariable` API documentation.

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