SaturationTransformation

class pymc_marketing.mmm.components.saturation.SaturationTransformation(priors=None, prefix=None)

Subclass for all saturation transformations.

In order to use a custom saturation transformation, subclass and define:

• function: function to take x to contributions

• default_priors: default distributions for each parameter in function

By subclassing from this method, lift test integration will come for free!

Examples

Make a non-saturating saturation transformation

from pymc_marketing.mmm import SaturationTransformation
from pymc_marketing.prior import Prior

def infinite_returns(x, b):
    return b * x

class InfiniteReturns(SaturationTransformation):
    lookup_name = "infinite_returns"
    function = infinite_returns
    default_priors = {"b": Prior("HalfNormal")}

Make use of plotting capabilities to understand the transformation and its priors

import matplotlib.pyplot as plt
import numpy as np

saturation = InfiniteReturns()

rng = np.random.default_rng(0)

prior = saturation.sample_prior(random_seed=rng)
curve = saturation.sample_curve(prior)
saturation.plot_curve(curve, sample_kwargs={"rng": rng})
plt.show()

Methods

SaturationTransformation.__init__([priors, ...])
SaturationTransformation.apply(x[, dims])	Call within a model context.
SaturationTransformation.plot_curve(curve[, ...])	Plot curve HDI and samples.
SaturationTransformation.plot_curve_hdi(curve)	Plot the HDI of the curve.
SaturationTransformation.plot_curve_samples(curve)	Plot samples from the curve.
SaturationTransformation.sample_curve([...])	Sample the curve of the saturation transformation given parameters.
SaturationTransformation.sample_prior([coords])	Sample the priors for the transformation.
SaturationTransformation.set_dims_for_all_priors(dims)	Set the dims for all priors.
SaturationTransformation.to_dict()	Convert the transformation to a dictionary.
SaturationTransformation.update_priors(priors)	Update the priors for a function after initialization.

Attributes

combined_dims	Get the combined dims for all the parameters.
function_priors	Get the priors for the function.
model_config	Mapping from variable name to prior for the model.
prefix
variable_mapping	Mapping from parameter name to variable name in the model.
default_priors
function
lookup_name