pymc_forecast.features#

Seasonal feature builders: Fourier design matrices and periodic tiling.

pymc_forecast.features.fourier_features(time, *, period, num_terms)[source]#

Build a labeled Fourier seasonality design matrix.

Parameters:

  • time (int or array_like) – Either a Python int duration (phases 0..duration-1) or an array of numeric time positions (e.g. np.arange(len(index)) or fractional day-of-week positions). Only a built-in int takes the duration branch; anything else (including a NumPy integer scalar) is converted with np.asarray(time, dtype=float). The positions set the phase; the returned "time" coord carries them.

  • period (float) – Seasonal period, in the same units as time.

  • num_terms (int) – Number of harmonics; the output has 2 * num_terms columns.

Returns:

xarray.DataArray – Dims ("time", "fourier") with shape (n, 2 * num_terms). The "time" coord holds the positions (not the data’s time coords) and the "fourier" coord labels each harmonic (sin_1 .. sin_k, cos_1 .. cos_k).

Raises:

ValueError – If num_terms < 1.

pymc_forecast.features.periodic_repeat(pattern, duration, *, axis=0, period=None)[source]#

Tile a seasonal pattern to cover duration time steps.

Works on numpy arrays and on PyTensor variables (e.g. a sampled seasonal latent inside a model). For PyTensor variables the length along axis is always symbolic, so period must be passed explicitly.

Parameters:

  • pattern (numpy.ndarray or pytensor.tensor.TensorVariable) – The seasonal pattern; its length along axis is the period unless period is given.

  • duration (int) – Target length along axis.

  • axis (int, default 0) – Axis to repeat along.

  • period (int, optional) – Explicit period; only the first period entries of pattern along axis are repeated. None reads it from a NumPy pattern’s shape; it is required for every PyTensor pattern.

Returns:

numpy.ndarray or pytensor.tensor.TensorVariable – The tiled pattern with length duration along axis: a NumPy array for a NumPy pattern, otherwise a symbolic tensor.

Raises:

ValueError – If period is None and the length of pattern along axis is symbolic (any PyTensor pattern).