meridian.model.context.ModelContext

    Model context for Meridian.

      meridian 
 . 
 model 
 . 
 context 
 . 
 ModelContext 
 ( 
 input_data 
 : 
   meridian 
 . 
 data 
 . 
 input_data 
 . 
 InputData 
 
 
 , 
 model_spec 
 : 
   meridian 
 . 
 model 
 . 
 spec 
 . 
 ModelSpec 
 
 
 )

    This class contains all model parameters that do not change between the runs of Meridian.

    adstock_decay_spec
    Returns AdstockDecaySpec object with correctly mapped channels.
    baseline_geo_idx
    Returns the index of the baseline geo.
    controls

    controls_scaled

    controls_transformer
    Returns a CenteringAndScalingTransformer for controls, if it exists.
    holdout_id

    input_data

    is_national

    knot_info

    kpi

    kpi_scaled

    kpi_transformer

    media_effects_dist

    media_tensors

    model_spec

    n_controls

    n_geos

    n_media_channels

    n_media_times

    n_non_media_channels

    n_organic_media_channels

    n_organic_rf_channels

    n_rf_channels

    n_times

    non_media_transformer
    Returns a CenteringAndScalingTransformer for non-media treatments.
    non_media_treatments

    non_media_treatments_normalized
    Normalized non-media treatments.

    The non-media treatments values are scaled by population (for channels where non_media_population_scaling_id is True ) and normalized by centering and scaling with means and standard deviations.

    organic_media_tensors

    organic_rf_tensors

    population

    prior_broadcast
    Returns broadcasted PriorDistribution object.
    revenue_per_kpi

    rf_tensors

    total_outcome

    total_spend

    unique_sigma_for_each_geo

    Methods

    create_inference_data_coords

    View source 

      create_inference_data_coords 
 ( 
 n_chains 
 : 
 int 
 , 
 n_draws 
 : 
 int 
 ) 
 -> 
 Mapping 
 [ 
 str 
 , 
 np 
 . 
 ndarray 
 | 
 Sequence 
 [ 
 str 
 ]]

    Creates data coordinates for inference data.

    create_inference_data_dims

    View source 

      create_inference_data_dims 
 () 
 -> 
 Mapping 
 [ 
 str 
 , 
 Sequence 
 [ 
 str 
 ]]

    Creates data dimensions for inference data.

    expand_selected_time_dims

    View source 

      expand_selected_time_dims 
 ( 
 start_date 
 : 
   meridian 
 . 
 data 
 . 
 time_coordinates 
 . 
 Date 
 
 
 = 
 None 
 , 
 end_date 
 : 
   meridian 
 . 
 data 
 . 
 time_coordinates 
 . 
 Date 
 
 
 = 
 None 
 ) 
 -> 
 ( 
 list 
 [ 
 str 
 ] 
 | 
 None 
 )

    Validates and returns time dimension values based on the selected times.

    If both start_date and end_date are None, returns None. If specified, both start_date and end_date are inclusive, and must be present in the time coordinates of the input data.

    Args

    start_date
    Start date of the selected time period. If None, implies the earliest time dimension value in the input data.
    end_date
    End date of the selected time period. If None, implies the latest time dimension value in the input data.

    Returns
    A list of time dimension values (as Meridian-formatted strings) in the input data within the selected time period, or do nothing and pass through None if both arguments are Nones, or if start_date and end_date correspond to the entire time range in the input data.

    Raises
    ValueError if start_date or end_date is not in the input data time dimensions.

    populate_cached_properties

    View source 

      populate_cached_properties 
 ()

    Eagerly activates all cached properties.

    This is useful for creating a tf.function computation graph with this Meridian object as part of a captured closure. Within the computation graph, internal state mutations are problematic, and so this method freezes the object's states before the computation graph is created.
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