DenseGenotypeMatrix

class pybrops.popgen.gmat.DenseGenotypeMatrix.DenseGenotypeMatrix(mat, taxa=None, taxa_grp=None, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, ploidy=2, **kwargs)

Bases: DenseTaxaVariantMatrix, DenseGeneticMappableMatrix, GenotypeMatrix

A concrete class for unphased genoypte matrix objects.

The purpose of this concrete class is to implement functionality for:

1. Genotype matrix ploidy and phase metadata.

2. Genotype matrix format conversion.

3. Genotype matrix allele counting routines.

4. Genotype matrix genotype counting routines.

5. Loading genotype matrices from VCF and HDF5.

Parameters:

• mat (numpy.ndarray) – An int8 haplotype matrix. Must be {0,1,2} format.

• taxa (numpy.ndarray, None) –

  A numpy.ndarray of shape (n,) containing taxa names. If None, do not store any taxa name information.

  Where:

  • n is the number of taxa.

• taxa_grp (numpy.ndarray, None) –

  A numpy.ndarray of shape (n,) containing taxa groupings. If None, do not store any taxa group information.

  Where:

  • n is the number of taxa.

• vrnt_chrgrp (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant chromosome group labels. If None, do not store any variant chromosome group label information.

  Where:

  • p is the number of variants.

• vrnt_phypos (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant chromosome physical positions. If None, do not store any variant chromosome physical position information.

  Where:

  • p is the number of variants.

• vrnt_name (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant names. If None, do not store any variant names.

  Where:

  • p is the number of variants.

• vrnt_genpos (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant chromosome genetic positions. If None, do not store any variant chromosome genetic position information.

  Where:

  • p is the number of variants.

• vrnt_xoprob (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant crossover probabilities. If None, do not store any variant crossover probabilities.

  Where:

  • p is the number of variants.

• vrnt_hapgrp (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant haplotype group labels. If None, do not store any variant haplotype group label information.

  Where:

  • p is the number of variants.

• vrnt_hapalt (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant alternative alleles. If None, do not store any variant alternative allele information.

  Where:

  • p is the number of variants.

• vrnt_hapref (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing variant reference alleles. If None, do not store any variant reference allele information.

  Where:

  • p is the number of variants.

• vrnt_mask (numpy.ndarray, None) –

  A numpy.ndarray of shape (p,) containing a variant mask. If None, do not store any variant mask information.

  Where:

  • p is the number of variants.

• ploidy (int) – The ploidy represented by the genotype matrix. This only represents ploidy of the reproductive habit. If the organism represented is an allopolyploid (e.g. hexaploid wheat), the ploidy is 2 since it reproduces in a diploid manner.

• kwargs (dict) – Additional keyword arguments.

Methods

acount	Allele count of the non-zero allele across all taxa.
adjoin	Add additional elements to the end of the Matrix along an axis.
adjoin_taxa	Add additional elements to the end of the Matrix along the taxa axis.
adjoin_vrnt	Add additional elements to the end of the Matrix along the variant axis.
afixed	Determine allele fixation for loci across all taxa.
afreq	Allele frequency of the non-zero allele across all taxa.
apoly	Allele polymorphism presence or absense across all loci.
append	Append values to the matrix.
append_taxa	Append values to the Matrix along the taxa axis.
append_vrnt	Append values to the Matrix along the variant axis.
concat	Concatenate matrices together along an axis.
concat_taxa	Concatenate list of Matrix together along the taxa axis.
concat_vrnt	Concatenate list of Matrix together along the variant axis.
copy	Make a shallow copy of the DenseGenotypeMatrix.
deepcopy	Make a deep copy of the DenseGenotypeMatrix.
delete	Delete sub-arrays along an axis.
delete_taxa	Delete sub-arrays along the taxa axis.
delete_vrnt	Delete sub-arrays along the variant axis.
from_hdf5	Read GenotypeMatrix from an HDF5 file.
from_vcf	Create a DenseGenotypeMatrix from a VCF file.
group	Sort the DenseTaxaVariantMatrix along an axis, then populate grouping indices.
group_taxa	Sort the Matrix along the taxa axis, then populate grouping indices for the taxa axis.
group_vrnt	Sort the Matrix along the variant axis, then populate grouping indices for the variant axis.
gtcount	Gather genotype counts for homozygous major, heterozygous, homozygous minor for all individuals.
gtfreq	Gather genotype frequencies for homozygous major, heterozygous, homozygous minor across all individuals.
incorp	Incorporate values along the given axis before the given indices.
incorp_taxa	Incorporate values along the taxa axis before the given indices.
incorp_vrnt	Incorporate values along the variant axis before the given indices.
insert	Insert values along the given axis before the given indices.
insert_taxa	Insert values along the taxa axis before the given indices.
insert_vrnt	Insert values along the variant axis before the given indices.
interp_genpos	Interpolate genetic map postions for variants using a GeneticMap
interp_xoprob	Interpolate genetic map positions AND crossover probabilities between sequential markers using a GeneticMap and a GeneticMapFunction.
is_grouped	Determine whether the Matrix has been sorted and grouped.
is_grouped_taxa	Determine whether the Matrix has been sorted and grouped along the taxa axis.
is_grouped_vrnt	Determine whether the Matrix has been sorted and grouped along the variant axis.
lexsort	Perform an indirect stable sort using a tuple of keys.
lexsort_taxa	Perform an indirect stable sort using a sequence of keys along the taxa axis.
lexsort_vrnt	Perform an indirect stable sort using a sequence of keys along the variant axis.
maf	Minor allele frequency across all taxa.
mat_asformat	Get mat in a specific format type.
meh	Mean expected heterozygosity across all taxa.
remove	Remove sub-arrays along an axis.
remove_taxa	Remove sub-arrays along the taxa axis.
remove_vrnt	Remove sub-arrays along the variant axis.
reorder	Reorder the VariantMatrix.
reorder_taxa	Reorder elements of the Matrix along the taxa axis using an array of indices.
reorder_vrnt	Reorder elements of the Matrix along the variant axis using an array of indices.
select	Select certain values from the matrix.
select_taxa	Select certain values from the Matrix along the taxa axis.
select_vrnt	Select certain values from the Matrix along the variant axis.
sort	Reset metadata for corresponding axis: name, stix, spix, len.
sort_taxa	Sort slements of the Matrix along the taxa axis using a sequence of keys.
sort_vrnt	Sort slements of the Matrix along the variant axis using a sequence of keys.
tacount	Allele count of the non-zero allele within each taxon.
tafreq	Allele frequency of the non-zero allele within each taxon.
to_hdf5	Write GenotypeMatrix to an HDF5 file.
ungroup	Ungroup the DenseTaxaVariantMatrix along an axis by removing grouping metadata.
ungroup_taxa	Ungroup the DenseTaxaMatrix along the taxa axis by removing taxa group metadata.
ungroup_vrnt	Ungroup the DenseVariantMatrix along the variant axis by removing variant group metadata.

Attributes

mat	Pointer to raw numpy.ndarray object.
mat_format	Matrix representation format.
mat_ndim	Number of dimensions of the raw numpy.ndarray.
mat_shape	Shape of the raw numpy.ndarray.
nphase	Number of chromosome phases represented by the matrix.
ntaxa	Number of taxa
nvrnt	Number of variants.
ploidy	Genome ploidy number represented by matrix.
taxa	Taxa label array
taxa_axis	Get taxa axis number
taxa_grp	Taxa group label.
taxa_grp_len	Taxa group length.
taxa_grp_name	Taxa group name.
taxa_grp_spix	Taxa group stop index.
taxa_grp_stix	Taxa group start index.
vrnt_axis	Get variant axis
vrnt_chrgrp	Variant chromosome group label.
vrnt_chrgrp_len	Variant chromosome group length.
vrnt_chrgrp_name	Variant chromosome group names.
vrnt_chrgrp_spix	Variant chromosome group stop indices.
vrnt_chrgrp_stix	Variant chromosome group start indices.
vrnt_genpos	Variant genetic position.
vrnt_hapalt	Variant haplotype sequence.
vrnt_hapgrp	Variant haplotype group label.
vrnt_hapref	Variant reference haplotype sequence.
vrnt_mask	Variant mask.
vrnt_name	Variant name.
vrnt_phypos	Variant physical position.
vrnt_xoprob	Variant crossover sequential probability.

__add__(value)

Elementwise add matrices

Parameters:

value (object) – Object which to add.

Returns:

out – An object resulting from the addition.

Return type:

object

__mul__(value)

Elementwise multiply matrices

Parameters:

value (object) – Object which to multiply.

Returns:

out – An object resulting from the multiplication.

Return type:

object

acount(dtype=None)

Allele count of the non-zero allele across all taxa.

Parameters:

dtype (dtype, None) – The data type of the accumulator and returned array. If None, use the native integer type.

Returns:

out – A numpy.ndarray of shape (p,) containing allele counts of the allele coded as 1 for all p loci.

Return type:

numpy.ndarray

adjoin(values, axis=-1, taxa=None, taxa_grp=None, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Add additional elements to the end of the Matrix along an axis.

Parameters:

• values (DensePhasedGenotypeMatrix, numpy.ndarray) – Values are appended to append to the Matrix.

• axis (int) – The axis along which values are adjoined.

• taxa (numpy.ndarray) – Taxa names to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None taxa field, providing this argument overwrites the field.

• taxa_grp (numpy.ndarray) – Taxa groups to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None taxa_grp field, providing this argument overwrites the field.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to adjoin to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to adjoin to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A copy of DenseTaxaVariantMatrix with values appended to axis. Note that adjoin does not occur in-place: a new DenseTaxaVariantMatrix is allocated and filled.

Return type:

DenseTaxaVariantMatrix

adjoin_taxa(values, taxa=None, taxa_grp=None, **kwargs)

Add additional elements to the end of the Matrix along the taxa axis.

Parameters:

• values (Matrix, numpy.ndarray) – Values are appended to adjoin to the Matrix.

• taxa (numpy.ndarray) – Taxa names to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None taxa field, providing this argument overwrites the field.

• taxa_grp (numpy.ndarray) – Taxa groups to adjoin to the Matrix. If values is a DenseHaplotypeMatrix that has a non-None taxa_grp field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A copy of mat with values appended to axis. Note that adjoin does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

adjoin_vrnt(values, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Add additional elements to the end of the Matrix along the variant axis.

Parameters:

• values (Matrix, numpy.ndarray) – Values are appended to adjoin to the Matrix.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to adjoin to the Matrix.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to adjoin to the Matrix.

• vrnt_name (numpy.ndarray) – Variant names to adjoin to the Matrix.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to adjoin to the Matrix.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to adjoin to the Matrix.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to adjoin to the Matrix.

• vrnt_hapalt (numpy.ndarray) – Variant haplotype sequence.

• vrnt_hapref (numpy.ndarray) – Variant haplotype reference sequence.

• vrnt_mask (numpy.ndarray) – Variant mask to adjoin to the Matrix.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A copy of mat with values appended to axis. Note that adjoin does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

afixed(dtype=None)

Determine allele fixation for loci across all taxa.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray of shape (p,) containing indicator variables for whether a locus is fixed at a particular locus.

Return type:

numpy.ndarray

afreq(dtype=None)

Allele frequency of the non-zero allele across all taxa.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray of shape (p,) containing allele frequencies of the allele coded as 1 for all p loci.

Return type:

numpy.ndarray

apoly(dtype=None)

Allele polymorphism presence or absense across all loci.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray of shape (p,) containing indicator variables for whether the locus is polymorphic.

Return type:

numpy.ndarray

append(values, axis=-1, taxa=None, taxa_grp=None, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Append values to the matrix.

Parameters:

• values (DenseHaplotypeMatrix, numpy.ndarray) – Values are appended to append to the matrix. Must be of type int8. Must be of shape (m, n, p)

• axis (int) – The axis along which values are appended.

• taxa (numpy.ndarray) – Taxa names to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa field, providing this argument overwrites the field.

• taxa_grp (numpy.ndarray) – Taxa groups to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa_grp field, providing this argument overwrites the field.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to append to the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

append_taxa(values, taxa=None, taxa_grp=None, **kwargs)

Append values to the Matrix along the taxa axis.

Parameters:

• values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.

• taxa (numpy.ndarray) – Taxa names to append to the Matrix.

• taxa_grp (numpy.ndarray) – Taxa groups to append to the Matrix.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

append_vrnt(values, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Append values to the Matrix along the variant axis.

Parameters:

• values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to append to the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

classmethod concat(mats, axis=-1, **kwargs)

Concatenate matrices together along an axis.

Parameters:

• mats (Sequence of matrices) – List of Matrix to concatenate. The matrices must have the same shape, except in the dimension corresponding to axis.

• axis (int) – The axis along which the arrays will be joined.

• kwargs (dict) – Additional keyword arguments

Returns:

out – The concatenated DenseTaxaVariantMatrix. Note that concat does not occur in-place: a new DenseTaxaVariantMatrix is allocated and filled.

Return type:

DenseTaxaVariantMatrix

classmethod concat_taxa(mats, **kwargs)

Concatenate list of Matrix together along the taxa axis.

Parameters:

• mats (Sequence of Matrix) – List of Matrix to concatenate. The matrices must have the same shape, except in the dimension corresponding to axis.

• kwargs (dict) – Additional keyword arguments

Returns:

out – The concatenated DenseGenotypeMatrix. Note that concat does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

classmethod concat_vrnt(mats, **kwargs)

Concatenate list of Matrix together along the variant axis.

Parameters:

• mats (Sequence of Matrix) – List of Matrix to concatenate. The matrices must have the same shape, except in the dimension corresponding to axis.

• kwargs (dict) – Additional keyword arguments

Returns:

out – The concatenated matrix. Note that concat does not occur in-place: a new Matrix is allocated and filled.

Return type:

Matrix

copy()

Make a shallow copy of the DenseGenotypeMatrix.

Returns:

out – A shallow copy of the original DenseGenotypeMatrix.

Return type:

DenseGenotypeMatrix

deepcopy(memo=None)

Make a deep copy of the DenseGenotypeMatrix.

Parameters:

memo (dict) – Dictionary of memo metadata.

Returns:

out – A deep copy of the original DenseGenotypeMatrix.

Return type:

DenseGenotypeMatrix

delete(obj, axis=-1, **kwargs)

Delete sub-arrays along an axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• axis (int) – The axis along which to delete the subarray defined by obj.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseTaxaVariantMatrix with deleted elements. Note that concat does not occur in-place: a new DenseTaxaVariantMatrix is allocated and filled.

Return type:

DenseTaxaVariantMatrix

delete_taxa(obj, **kwargs)

Delete sub-arrays along the taxa axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseGenotypeMatrix with deleted elements. Note that concat does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

delete_vrnt(obj, **kwargs)

Delete sub-arrays along the variant axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseGenotypeMatrix with deleted elements. Note that concat does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

classmethod from_hdf5(filename, groupname=None)

Read GenotypeMatrix from an HDF5 file.

Parameters:

• filename (str, Path, h5py.File) – If str or Path, an HDF5 file name from which to read. File is closed after reading. If h5py.File, an opened HDF5 file from which to read. File is not closed after reading.

• groupname (str, None) – If str, an HDF5 group name under which GenotypeMatrix data is stored. If None, GenotypeMatrix is read from base HDF5 group.

Returns:

gmat – A genotype matrix read from file.

Return type:

GenotypeMatrix

classmethod from_vcf(filename, auto_group_vrnt=True)

Create a DenseGenotypeMatrix from a VCF file.

Parameters:

• filename (str) – Path to VCF file.

• auto_group_vrnt (bool) – Whether to group variants in returned genotype matrix.

Returns:

out – An unphased genotype matrix with associated metadata from VCF file.

Return type:

DenseGenotypeMatrix

group(axis=-1, **kwargs)

Sort the DenseTaxaVariantMatrix along an axis, then populate grouping indices.

Parameters:

• axis (int) – The axis along which values are grouped.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

group_taxa(**kwargs)

Sort the Matrix along the taxa axis, then populate grouping indices for the taxa axis.

Parameters:

kwargs (dict) – Additional keyword arguments.

Return type:

None

group_vrnt(**kwargs)

Sort the Matrix along the variant axis, then populate grouping indices for the variant axis.

Parameters:

kwargs (dict) – Additional keyword arguments.

Return type:

None

gtcount(dtype=None)

Gather genotype counts for homozygous major, heterozygous, homozygous minor for all individuals.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray array of shape (g,p) containing allele counts across all p loci for each of g genotype combinations.

Where:

• out[0] is the count of 0 genotype across all loci

• out[1] is the count of 1 genotype across all loci

• out[2] is the count of 2 genotype across all loci

• ...

• out[g-1] is the count of g-1 genotype across all loci

Return type:

numpy.ndarray

gtfreq(dtype=None)

Gather genotype frequencies for homozygous major, heterozygous, homozygous minor across all individuals.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray array of shape (g,p) containing haplotype counts across all p loci for all g genotype combinations.

Where:

• out[0] is the frequency of 0 genotype across all loci

• out[1] is the frequency of 1 genotype across all loci

• out[2] is the frequency of 2 genotype across all loci

• ...

• out[g-1] is the frequency of g-1 genotype across all loci

Return type:

numpy.ndarray

incorp(obj, values, axis=-1, taxa=None, taxa_grp=None, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Incorporate values along the given axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is incorporated.

• values (array_like) – Values to incorporate into the matrix.

• axis (int) – The axis along which values are incorporated.

• taxa (numpy.ndarray) – Taxa names to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa field, providing this argument overwrites the field.

• taxa_grp (numpy.ndarray) – Taxa groups to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa_grp field, providing this argument overwrites the field.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to incorporate into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

incorp_taxa(obj, values, taxa=None, taxa_grp=None, **kwargs)

Incorporate values along the taxa axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is incorporated.

• values (Matrix, numpy.ndarray) – Values to incorporate into the matrix.

• taxa (numpy.ndarray) – Taxa names to incorporate into the Matrix.

• taxa_grp (numpy.ndarray) – Taxa groups to incorporate into the Matrix.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

incorp_vrnt(obj, values, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Incorporate values along the variant axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is incorporated.

• values (Matrix, numpy.ndarray) – Values to incorporate into the matrix.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to incorporate into the Matrix. If values is a DenseVariantMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

insert(obj, values, axis=-1, taxa=None, taxa_grp=None, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Insert values along the given axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is inserted.

• values (Matrix, numpy.ndarray) – Values to insert into the matrix.

• axis (int) – The axis along which values are inserted.

• taxa (numpy.ndarray) – Taxa names to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa field, providing this argument overwrites the field.

• taxa_grp (numpy.ndarray) – Taxa groups to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None taxa_grp field, providing this argument overwrites the field.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_chrgrp field, providing this argument overwrites the field.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_phypos field, providing this argument overwrites the field.

• vrnt_name (numpy.ndarray) – Variant names to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_name field, providing this argument overwrites the field.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_genpos field, providing this argument overwrites the field.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_xoprob field, providing this argument overwrites the field.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_hapgrp field, providing this argument overwrites the field.

• vrnt_mask (numpy.ndarray) – Variant mask to insert into the Matrix. If values is a DenseTaxaVariantMatrix that has a non-None vrnt_mask field, providing this argument overwrites the field.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseTaxaVariantMatrix with values inserted. Note that insert does not occur in-place: a new DenseTaxaVariantMatrix is allocated and filled.

Return type:

DenseTaxaVariantMatrix

insert_taxa(obj, values, taxa=None, taxa_grp=None, **kwargs)

Insert values along the taxa axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is inserted.

• values (Matrix, numpy.ndarray) – Values to insert into the matrix.

• taxa (numpy.ndarray) – Taxa names to insert into the Matrix.

• taxa_grp (numpy.ndarray) – Taxa groups to insert into the Matrix.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseGenotypeMatrix with values inserted. Note that insert does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

insert_vrnt(obj, values, vrnt_chrgrp=None, vrnt_phypos=None, vrnt_name=None, vrnt_genpos=None, vrnt_xoprob=None, vrnt_hapgrp=None, vrnt_hapalt=None, vrnt_hapref=None, vrnt_mask=None, **kwargs)

Insert values along the variant axis before the given indices.

Parameters:

• obj (int, slice, or Sequence of ints) – Object that defines the index or indices before which values is inserted.

• values (array_like) – Values to insert into the matrix.

• vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to insert into the Matrix.

• vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to insert into the Matrix.

• vrnt_name (numpy.ndarray) – Variant names to insert into the Matrix.

• vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to insert into the Matrix.

• vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to insert into the Matrix.

• vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to insert into the Matrix.

• vrnt_hapalt (numpy.ndarray) – Variant alternative haplotype labels to insert into the Matrix.

• vrnt_hapref (numpy.ndarray) – Variant reference haplotype labels to insert into the Matrix.

• vrnt_mask (numpy.ndarray) – Variant mask to insert into the Matrix.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – A DenseGenotypeMatrix with values inserted. Note that insert does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

interp_genpos(gmap, **kwargs)

Interpolate genetic map postions for variants using a GeneticMap

Parameters:

gmap (GeneticMap) – A genetic map from which to interopolate genetic map postions for loci within the VariantMatrix.

Return type:

None

interp_xoprob(gmap, gmapfn, **kwargs)

Interpolate genetic map positions AND crossover probabilities between sequential markers using a GeneticMap and a GeneticMapFunction.

Parameters:

• gmap (GeneticMap) – A genetic map from which to interopolate genetic map postions for loci within the VariantMatrix.

• gmapfn (GeneticMapFunction) – A genetic map function from which to interpolate crossover probabilities for loci within the VariantMatrix.

Return type:

None

is_grouped(axis=-1, **kwargs)

Determine whether the Matrix has been sorted and grouped.

Parameters:

• axis (int) – Axis along which to determine if is grouped.

• kwargs (dict) – Additional keyword arguments.

Returns:

grouped – True or False indicating whether the GeneticMap has been sorted and grouped.

Return type:

bool

is_grouped_taxa(**kwargs)

Determine whether the Matrix has been sorted and grouped along the taxa axis.

Parameters:

kwargs (dict) – Additional keyword arguments.

Returns:

grouped – True or False indicating whether the Matrix has been sorted and grouped.

Return type:

bool

is_grouped_vrnt(**kwargs)

Determine whether the Matrix has been sorted and grouped along the variant axis.

Parameters:

kwargs (dict) – Additional keyword arguments.

Returns:

grouped – True or False indicating whether the Matrix has been sorted and grouped.

Return type:

bool

lexsort(keys=None, axis=-1, **kwargs)

Perform an indirect stable sort using a tuple of keys.

Parameters:

• keys (tuple, None) – A tuple of columns to be sorted. The last column is the primary sort key. If None, sort using vrnt_chrgrp as primary key, and vrnt_phypos as secondary key.

• axis (int) – The axis of the Matrix over which to sort values.

• kwargs (dict) – Additional keyword arguments.

Returns:

indices – Array of indices that sort the keys.

Return type:

numpy.ndarray

lexsort_taxa(keys=None, **kwargs)

Perform an indirect stable sort using a sequence of keys along the taxa axis.

Parameters:

• keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.

• kwargs (dict) – Additional keyword arguments.

Returns:

indices – Array of indices that sort the keys along the specified axis.

Return type:

A (N,) ndarray of ints

lexsort_vrnt(keys=None, **kwargs)

Perform an indirect stable sort using a sequence of keys along the variant axis.

Parameters:

• keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.

• kwargs (dict) – Additional keyword arguments.

Returns:

indices – Array of indices that sort the keys along the specified axis.

Return type:

A (N,) ndarray of ints

maf(dtype=None)

Minor allele frequency across all taxa.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray of shape (p,) containing allele frequencies for the minor allele.

Return type:

numpy.ndarray

property mat: ndarray

Pointer to raw numpy.ndarray object.

mat_asformat(format)

Get mat in a specific format type.

Parameters:

format (str) – Desired output format. Options are “{0,1,2}”, “{-1,0,1}”, “{-1,m,1}”.

Returns:

out – Matrix in the desired output format.

Return type:

numpy.ndarray

property mat_format: str

Matrix representation format.

property mat_ndim: int

Number of dimensions of the raw numpy.ndarray.

property mat_shape: tuple

Shape of the raw numpy.ndarray.

meh(dtype=None)

Mean expected heterozygosity across all taxa.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A number representing the mean expected heterozygous. If dtype is None, then a native 64-bit floating point is returned. Otherwise, of type specified by dtype.

Return type:

Real

property nphase: int

Number of chromosome phases represented by the matrix.

property ntaxa: int

Number of taxa

property nvrnt: int

Number of variants.

property ploidy: int

Genome ploidy number represented by matrix.

remove(obj, axis=-1, **kwargs)

Remove sub-arrays along an axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• axis (int) – The axis along which to remove the subarray defined by obj.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

remove_taxa(obj, **kwargs)

Remove sub-arrays along the taxa axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

remove_vrnt(obj, **kwargs)

Remove sub-arrays along the variant axis.

Parameters:

• obj (int, slice, or Sequence of ints) – Indicate indices of sub-arrays to remove along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

reorder(indices, axis=-1, **kwargs)

Reorder the VariantMatrix.

Parameters:

• indices (numpy.ndarray) – Indices of where to place elements.

• axis (int) – The axis over which to reorder values.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

reorder_taxa(indices, **kwargs)

Reorder elements of the Matrix along the taxa axis using an array of indices. Note this modifies the Matrix in-place.

Parameters:

• indices (A (N,) ndarray of ints) – Array of indices that reorder the matrix along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

reorder_vrnt(indices, **kwargs)

Reorder elements of the Matrix along the variant axis using an array of indices. Note this modifies the Matrix in-place.

Parameters:

• indices (A (N,) ndarray of ints) – Array of indices that reorder the matrix along the specified axis.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

select(indices, axis=-1, **kwargs)

Select certain values from the matrix.

Parameters:

• indices (array_like (Nj, ...)) – The indices of the values to select.

• axis (int) – The axis along which values are selected.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – The output DenseTaxaVariantMatrix with values selected. Note that select does not occur in-place: a new DenseTaxaVariantMatrix is allocated and filled.

Return type:

DenseTaxaVariantMatrix

select_taxa(indices, **kwargs)

Select certain values from the Matrix along the taxa axis.

Parameters:

• indices (array_like (Nj, ...)) – The indices of the values to select.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – The output DenseGenotypeMatrix with values selected. Note that select does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

select_vrnt(indices, **kwargs)

Select certain values from the Matrix along the variant axis.

Parameters:

• indices (array_like (Nj, ...)) – The indices of the values to select.

• kwargs (dict) – Additional keyword arguments.

Returns:

out – The output DenseGenotypeMatrix with values selected. Note that select does not occur in-place: a new DenseGenotypeMatrix is allocated and filled.

Return type:

DenseGenotypeMatrix

sort(keys=None, axis=-1, **kwargs)

Reset metadata for corresponding axis: name, stix, spix, len. Sort the VariantMatrix using a tuple of keys.

Parameters:

• keys (tuple, None) – A tuple of columns to be sorted. The last column is the primary sort key. If None, sort using vrnt_chrgrp as primary key, and vrnt_phypos as secondary key.

• axis (int) – The axis over which to sort values.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

sort_taxa(keys=None, **kwargs)

Sort slements of the Matrix along the taxa axis using a sequence of keys. Note this modifies the Matrix in-place.

Parameters:

• keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

sort_vrnt(keys=None, **kwargs)

Sort slements of the Matrix along the variant axis using a sequence of keys. Note this modifies the Matrix in-place.

Parameters:

• keys (A (k, N) array or tuple containing k (N,)-shaped sequences) – The k different columns to be sorted. The last column (or row if keys is a 2D array) is the primary sort key.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

tacount(dtype=None)

Allele count of the non-zero allele within each taxon.

Parameters:

dtype (dtype, None) – The data type of the accumulator and returned array. If None, use the native accumulator type (int or float).

Returns:

out – A numpy.ndarray of shape (n,p) containing allele counts of the allele coded as 1 for all n individuals, for all p loci.

Return type:

numpy.ndarray

tafreq(dtype=None)

Allele frequency of the non-zero allele within each taxon.

Parameters:

dtype (dtype, None) – The data type of the returned array. If None, use the native type.

Returns:

out – A numpy.ndarray of shape (n,p) containing allele frequencies of the allele coded as 1 for all n individuals, for all p loci.

Return type:

numpy.ndarray

property taxa: ndarray | None

Taxa label array

property taxa_axis: int

Get taxa axis number

property taxa_grp: ndarray | None

Taxa group label.

property taxa_grp_len: ndarray | None

Taxa group length.

property taxa_grp_name: ndarray | None

Taxa group name.

property taxa_grp_spix: ndarray | None

Taxa group stop index.

property taxa_grp_stix: ndarray | None

Taxa group start index.

to_hdf5(filename, groupname=None, overwrite=True)

Write GenotypeMatrix to an HDF5 file.

Parameters:

• filename (str, Path, h5py.File) – If str, an HDF5 file name to which to write. File is closed after writing. If h5py.File, an opened HDF5 file to which to write. File is not closed after writing.

• groupname (str, None) – If str, an HDF5 group name under which GenotypeMatrix data is stored. If None, GenotypeMatrix is written to the base HDF5 group.

• overwrite (bool) – Whether to overwrite values in an HDF5 file if a field already exists.

Return type:

None

ungroup(axis=-1, **kwargs)

Ungroup the DenseTaxaVariantMatrix along an axis by removing grouping metadata.

Parameters:

• axis (int) – The axis along which values should be ungrouped.

• kwargs (dict) – Additional keyword arguments.

Return type:

None

ungroup_taxa(**kwargs)

Ungroup the DenseTaxaMatrix along the taxa axis by removing taxa group metadata.

Parameters:

kwargs (dict) – Additional keyword arguments.

Return type:

None

ungroup_vrnt(**kwargs)

Ungroup the DenseVariantMatrix along the variant axis by removing variant group metadata.

Parameters:

kwargs (dict) – Additional keyword arguments.

Return type:

None

property vrnt_axis: int

Get variant axis

property vrnt_chrgrp: ndarray | None

Variant chromosome group label.

property vrnt_chrgrp_len: ndarray | None

Variant chromosome group length.

property vrnt_chrgrp_name: ndarray | None

Variant chromosome group names.

property vrnt_chrgrp_spix: ndarray | None

Variant chromosome group stop indices.

property vrnt_chrgrp_stix: ndarray | None

Variant chromosome group start indices.

property vrnt_genpos: ndarray | None

Variant genetic position.

property vrnt_hapalt: ndarray | None

Variant haplotype sequence.

property vrnt_hapgrp: ndarray | None

Variant haplotype group label.

property vrnt_hapref: ndarray | None

Variant reference haplotype sequence.

property vrnt_mask: ndarray | None

Variant mask.

property vrnt_name: ndarray | None

Variant name.

property vrnt_phypos: ndarray | None

Variant physical position.

property vrnt_xoprob: ndarray | None

Variant crossover sequential probability.