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High-level description

The code defines a SizeMatchedModel class that represents a statistical model where parameters vary based on the size of the input data. It provides methods for loading and saving the model, calculating p-values, and determining model means based on input size.

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Code Structure

The SizeMatchedModel class is the central component. It uses a list of bins to partition the input size range and associates a set of parameters with each bin. The distribution attribute holds a statistical distribution object (not defined in this file) used for calculations.

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Symbols

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SizeMatchedModel

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Description

This class represents a statistical model where parameters are determined by the size of the input data. It uses bins to divide the size range and associates a set of parameters with each bin.

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Inputs

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Outputs

N/A - This is a class definition, not a function.

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Internal Logic

The class stores the bins, parameters, distribution, and name. It provides methods for:
  • Loading and saving the model from/to JSON files.
  • Finding the appropriate parameters for a given size using _params_for_size.
  • Calculating p-values using the provided distribution and parameters.
  • Determining the model mean for a given size.

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SizeMatchedModel.from_json

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Description

This class method loads a SizeMatchedModel instance from a JSON file.

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Inputs

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Outputs

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Internal Logic

  • Opens the JSON file and loads the data.
  • Converts string representations of lists and the distribution name to their respective Python objects.
  • Instantiates a new SizeMatchedModel with the loaded data.

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SizeMatchedModel.to_json

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Description

This method saves the SizeMatchedModel instance to a JSON file.

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Inputs

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Outputs

N/A - The method writes data to a file as a side effect.

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Internal Logic

  • Creates a dictionary containing the model’s attributes.
  • Converts lists to JSON-serializable strings.
  • Extracts the distribution’s class name for serialization.
  • Writes the dictionary to the specified JSON file.

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SizeMatchedModel._params_for_size

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Description

This private method retrieves the appropriate parameters for a given size based on the defined bins.

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Inputs

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Outputs

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Internal Logic

  • Uses np.digitize to find the index of the bin corresponding to the input size.
  • Handles cases where the size is outside the defined bins based on strict_bounds.
  • Adjusts the bin index to match the zero-based indexing of the params list.
  • Returns the parameters for the selected bin.

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SizeMatchedModel.pvalue

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Description

This method calculates the p-value of a given value x under the model for a specific size.

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Inputs

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Outputs

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Internal Logic

  • Retrieves the model parameters for the given size using _params_for_size.
  • Calculates the cumulative distribution function (CDF) of x using the model’s distribution and parameters.
  • Inverts the CDF if invert_cdf is True.
  • Returns the calculated p-value.

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SizeMatchedModel.model_mean

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Description

This method calculates the mean of the model for a given size.

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Inputs

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Outputs

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Internal Logic

  • Retrieves the model parameters for the given size using _params_for_size.
  • Calculates the mean of the distribution using the retrieved parameters.
  • Returns the calculated mean.

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TODOs

  • Evaluate distribution in global namespace, so that import is not necessary here