gemseo / algos / doe

doe_quality module

DOE assessor.

class gemseo.algos.doe.doe_quality.DOEMeasures(discrepancy, mindist, phip)

Bases: tuple

The quality measures of a DOE.

Namely \(\phi^p\), minimum-distance and discrepancy measures, accessible with the attributes discrepancy, mindist and phip.

The smaller the quality measures, the better, except for the minimum-distance criterion for which the larger it is the better.

count(value, /)

Return number of occurrences of value.

index(value, start=0, stop=9223372036854775807, /)

Return first index of value.

Raises ValueError if the value is not present.

discrepancy

Alias for field number 0

mindist

Alias for field number 1

phip

Alias for field number 2

class gemseo.algos.doe.doe_quality.DOEQuality(samples, power=50, discrepancy_type_name='CD', **discrepancy_options)[source]

Bases: object

The quality of a DOE.

Parameters:

  • samples (ndarray) – The input samples of the DOE.

  • power (int) –

    The power \(p\) of the \(\phi^p\) criterion.

    By default it is set to 50.

  • discrepancy_type_name (DiscrepancyTypeNameType) –

    The type of discrepancy.

    By default it is set to “CD”.

  • **discrepancy_options (Any) – The options passed to scipy.stats.qmc.discrepancy.

measures: DOEMeasures

The quality measures of the DOE.

gemseo.algos.doe.doe_quality.compute_discrepancy(samples, type_name='CD', **options)[source]

Compute the discrepancy of a sample set (the smaller, the better).

Parameters:
Returns:

The discrepancy.

Return type:

float

gemseo.algos.doe.doe_quality.compute_mindist_criterion(samples)[source]

Compute the minimum-distance criterion of a sample set (the higher, the better).

This criterion is also called mindist.

Parameters:

samples (ndarray) – The data samples.

Returns:

The minimum-distance criterion.

Return type:

float

gemseo.algos.doe.doe_quality.compute_phip_criterion(samples, power=50)[source]

Compute the math:phi^p criterion of a sample set (the smaller, the better).

See [MM95].

Parameters:

  • samples (ndarray) – The data samples.

  • power (float) –

    The power \(p\) of the \(\phi^p\) criterion.

    By default it is set to 50.

Returns:

phi^p criterion.

Return type:

The math