batched_convolution

pymc_marketing.mmm.transformers.batched_convolution(x, w, axis=0, mode=ConvMode.After)

Apply a 1D convolution in a vectorized way across multiple batch dimensions.

(Source code, png, hires.png, pdf)

Parameters:

• x – The array to convolve.

• w – The weight of the convolution. The last axis of w determines the number of steps to use in the convolution.

• axis (int) – The axis of x along witch to apply the convolution

• mode (ConvMode, optional) –

  The convolution mode determines how the convolution is applied at the boundaries of the input signal, denoted as “x.” The default mode is ConvMode.Before.

  • ConvMode.After: Applies the convolution with the “Adstock” effect, resulting in a trailing decay effect.

  • ConvMode.Before: Applies the convolution with the “Excitement” effect, creating a leading effect

    similar to the wow factor.

  • ConvMode.Overlap: Applies the convolution with both “Pull-Forward” and “Pull-Backward” effects,

    where the effect overlaps with both preceding and succeeding elements.

Returns:

The result of convolving x with w along the desired axis. The shape of the result will match the shape of x up to broadcasting with w. The convolved axis will show the results of left padding zeros to x while applying the convolutions.

Return type:

y