openest.models.memoizable module

class openest.models.memoizable.MemoizableUnivariate[source]

Bases: object

eval_pval_index(ii, p, threshold=0.001)[source]
get_edges()[source]
class openest.models.memoizable.MemoizedUnivariate(model)[source]

Bases: openest.models.univariate_model.UnivariateModel

copy()[source]
eval_pval(x, p, threshold=0.001)[source]

Inverse CDF Evaluation

Returns the value of $y$ that corresponds to a given p-value: $F^{-1}(p | x)$.

eval_pvals(xs, p, threshold=0.001)[source]
get_eval_pval_spline(p, limits, threshold=0.001, linextrap=False)[source]
get_index(x)[source]
get_indexes(xs)[source]
get_xx()[source]

Listing conditional values

Provide a list of all sampled conditional values.

interpolate_x(newxx)[source]
kind()[source]
reset_cache()[source]
scale_p(a)[source]

Raise the distribution to the power ‘a’ and rescales.

Returns:modifies this model and returns it
Return type:self
scale_y(a)[source]

Rescaling of the Parameter Dimension

Produces a new conditional PDF with the $y$ dimension scaled by a constant: $p(z | x) = p( rac{y}{a} | x)$.

set_x_cache_decimals(decimals)[source]
write(file, delimiter)[source]
write_file(filename, delimiter)[source]