prfmodel.scaling.Baseline

class prfmodel.scaling.Baseline

Additive baseline scaling model.

Transforms a temporal response by adding a baseline.

Examples

>>> import numpy as np
>>> import pandas as pd
>>> params = pd.DataFrame({
...     "baseline": [5.0, 10.0, -3.0],
... })
>>> num_frames = 10
>>> inputs = np.ones((params.shape[0], num_frames))
>>> model = Baseline()
>>> resp = model(inputs, params)
>>> print(resp.shape)  # (num_units, num_frames)
(3, 10)
__call__(inputs: prfmodel.typing.Tensor, parameters: pandas.DataFrame, dtype: str | None = None) → prfmodel.typing.Tensor

Predict the model response.

Parameters:

  • inputs (prfmodel.typing.Tensor) – Input tensor with temporal response and shape (num_units, num_frames).

  • parameters (pandas.DataFrame) – Dataframe with columns containing different model parameters and rows containing parameter values for different units.

  • dtype (str, optional) – The dtype of the prediction result. If None (the default), uses the dtype from prfmodel.utils.get_dtype().

Returns:

The predicted model response with shape (num_units, num_frames) and dtype dtype.

Return type:

Tensor

property parameter_names: list[str]

Names of parameters used by the model.

Parameter names are: baseline.