DenseTwoWayDHAdditiveGeneticVarianceMatrixFactory#

class pybrops.model.vmat.fcty.DenseTwoWayDHAdditiveGeneticVarianceMatrixFactory.DenseTwoWayDHAdditiveGeneticVarianceMatrixFactory(**kwargs)[source]#

Bases: AdditiveGeneticVarianceMatrixFactory

docstring for DenseTwoWayDHAdditiveGeneticVarianceMatrixFactory.

Constructor for DenseTwoWayDHAdditiveGeneticVarianceMatrixFactory.

Parameters:: kwargs (dict) – Additional keyword arguments used for cooperative inheritance.

Methods

`from_algmod`	Estimate genetic variances from a GenomicModel.
`from_gmod`	Estimate genetic variances from a GenomicModel and PhasedGenotypeMatrix.

from_algmod(algmod, pgmat, ncross, nprogeny, nself, gmapfn, mem=1024, **kwargs)[source]#

Estimate genetic variances from a GenomicModel.

Parameters:

algmod (AdditiveLinearGenomicModel) – AdditiveLinearGenomicModel with which to estimate genetic variances.
pgmat (PhasedGenotypeMatrix) – Input genomes to use to estimate genetic variances.
ncross (int) – Number of cross patterns to simulate for genetic variance estimation.
nprogeny (int) – Number of progeny to simulate per cross to estimate genetic variance.
nself (int) – Number of selfing generations post-cross pattern before ‘nprogeny’ individuals are simulated.
gmapfn (GeneticMapFunction) – GeneticMapFunction to use to estimate covariance induced by recombination.
mem (int) – Memory chunk size to use during matrix operations.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A matrix of additive genetic variance estimations.

Return type:

DenseTwoWayDHAdditiveGeneticVarianceMatrix

from_gmod(gmod, pgmat, ncross, nprogeny, nself, gmapfn, **kwargs)[source]#

Estimate genetic variances from a GenomicModel and PhasedGenotypeMatrix.

Parameters:

gmod (GenomicModel) – GenomicModel with which to estimate genetic variances.
pgmat (PhasedGenotypeMatrix) – Input genomes to use to estimate genetic variances.
ncross (int) – Number of cross patterns to simulate for genetic variance estimation.
nprogeny (int) – Number of progeny to simulate per cross to estimate genetic variance.
nself (int) – Number of selfing generations post-cross pattern before ‘nprogeny’ individuals are simulated.
gmapfn (GeneticMapFunction) – Genetic map function with which to calculate recombination probabilities.
kwargs (dict) – Additional keyword arguments.

Returns:

out – A matrix of genetic variance estimations.

Return type:

DenseTwoWayDHAdditiveGeneticVarianceMatrix