PhasedHaplotypeMatrix#
- class pybrops.popgen.gmat.PhasedHaplotypeMatrix.PhasedHaplotypeMatrix[source]#
Bases:
HaplotypeMatrix
,PhasedTaxaVariantMatrix
An abstract class for phased genoypte matrix objects.
- The purpose of this abstract class is to merge the following interfaces:
HaplotypeMatrix
PhasedTaxaVariantMatrix
Methods
Add additional elements to the end of the Matrix along an axis.
Add additional elements to the end of the PhasedMatrix along the phase axis.
Add additional elements to the end of the Matrix along the taxa axis.
Add additional elements to the end of the VariantMatrix along the variant axis.
Append values to the Matrix.
Append values to the Matrix along the phase axis.
Append values to the Matrix along the taxa axis.
Append values to the VariantMatrix along the variant axis.
Concatenate matrices together along an axis.
Concatenate list of Matrix together along the phase axis.
Concatenate list of Matrix together along the taxa axis.
Concatenate list of VariantMatrix together along the variant axis.
Make a shallow copy of the Matrix.
Make a deep copy of the Matrix.
Delete sub-arrays along an axis.
Delete sub-arrays along the phase axis.
Delete sub-arrays along the taxa axis.
Delete sub-arrays along the variant axis.
Read an object from an HDF5 file.
Sort the GroupableMatrix along an axis, then populate grouping indices.
Sort the Matrix along the taxa axis, then populate grouping indices for the taxa axis.
Sort the VariantMatrix along the variant axis, then populate grouping indices for the variant axis.
Gather haplotype counts across for homozygous major, heterozygous, homozygous minor all individuals.
Gather haplotype frequencies for homozygous major, heterozygous, homozygous minor across all individuals.
Haplotype count of the non-zero haplotype across all taxa.
Haplotype frequency of the non-zero haplotype across all taxa.
Incorporate values along the given axis before the given indices.
Incorporate values along the phase axis before the given indices.
Incorporate values along the taxa axis before the given indices.
Incorporate values along the variant axis before the given indices.
Insert values along the given axis before the given indices.
Insert values along the phase axis before the given indices.
Insert values along the taxa axis before the given indices.
Insert values along the variant axis before the given indices.
Determine whether the Matrix has been sorted and grouped.
Determine whether the Matrix has been sorted and grouped along the taxa axis.
Determine whether the Matrix has been sorted and grouped along the variant axis.
Perform an indirect stable sort using a sequence of keys.
Perform an indirect stable sort using a sequence of keys along the taxa axis.
Perform an indirect stable sort using a sequence of keys along the variant axis.
Mean expected heterozygosity across all taxa.
Minor haplotype frequency across all taxa.
Remove sub-arrays along an axis.
Remove sub-arrays along the phase axis.
Remove sub-arrays along the taxa axis.
Remove sub-arrays along the variant axis.
Reorder elements of the Matrix using an array of indices.
Reorder elements of the Matrix along the taxa axis using an array of indices.
Reorder elements of the Matrix along the variant axis using an array of indices.
Select certain values from the matrix.
Select certain values from the Matrix along the phase axis.
Select certain values from the Matrix along the taxa axis.
Select certain values from the VariantMatrix along the variant axis.
Sort slements of the Matrix using a sequence of keys.
Sort slements of the Matrix along the taxa axis using a sequence of keys.
Sort slements of the Matrix along the variant axis using a sequence of keys.
Haplotype count of the non-zero haplotype within each taxon.
Haplotype frequency of the non-zero haplotype within each taxon.
Write an object to an HDF5 file.
Ungroup the GroupableMatrix along an axis by removing grouping metadata.
Ungroup the TaxaMatrix along the taxa axis by removing taxa group metadata.
Ungroup the VariantMatrix along the variant axis by removing variant group metadata.
Attributes
Pointer to raw matrix object.
Matrix representation format.
Number of dimensions of the raw matrix.
Shape of the raw matrix.
The number of phases represented by the haplotype matrix.
Number of taxa.
Number of variants.
Axis along which phases are stored.
The ploidy level represented by the haplotype matrix.
Taxa label.
Axis along which taxa are stored.
Taxa group label.
Taxa group length.
Taxa group name.
Taxa group stop index.
Taxa group start index.
Axis along which variants are stored.
Variant chromosome group label.
Variant chromosome group length.
Variant chromosome group names.
Variant chromosome group stop indices.
Variant chromosome group start indices.
Variant genetic position.
Variant haplotype sequence.
Variant haplotype group label.
Variant reference haplotype sequence.
Variant mask.
Variant name.
Variant physical position.
Variant crossover sequential probability.
- abstract __add__(value)#
Elementwise add matrices
- Parameters:
value (object) – Object which to add.
- Returns:
out – An object resulting from the addition.
- Return type:
object
- abstract __mul__(value)#
Elementwise multiply matrices
- Parameters:
value (object) – Object which to multiply.
- Returns:
out – An object resulting from the multiplication.
- Return type:
object
- abstract adjoin(values, axis, **kwargs)#
Add additional elements to the end of the Matrix along an axis.
- Parameters:
values (Matrix or numpy.ndarray) – Values are appended to append to the Matrix.
axis (int) – The axis along which values are adjoined.
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:
- abstract adjoin_phase(values, **kwargs)#
Add additional elements to the end of the PhasedMatrix along the phase axis.
- Parameters:
values (Matrix, numpy.ndarray) – Values are appended 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 PhasedMatrix is allocated and filled.
- Return type:
- abstract adjoin_taxa(values, taxa, taxa_grp, **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.
taxa_grp (numpy.ndarray) – Taxa groups to adjoin to the Matrix.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – A copy of TaxaMatrix with values appended to axis. Note that adjoin does not occur in-place: a new TaxaMatrix is allocated and filled.
- Return type:
- abstract adjoin_vrnt(values, vrnt_chrgrp, vrnt_phypos, vrnt_name, vrnt_genpos, vrnt_xoprob, vrnt_hapgrp, vrnt_mask, **kwargs)#
Add additional elements to the end of the VariantMatrix 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_mask (numpy.ndarray) – Variant mask to adjoin to the Matrix.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – A copy of the VariantMatrix with values appended to axis. Note that adjoin does not occur in-place: a new VariantMatrix is allocated and filled.
- Return type:
- abstract append(values, axis, **kwargs)#
Append values to the Matrix.
- Parameters:
values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.
axis (int) – The axis along which values are appended.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract append_phase(values, **kwargs)#
Append values to the Matrix along the phase axis.
- Parameters:
values (Matrix, numpy.ndarray) – Values are appended to append to the matrix.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract append_taxa(values, taxa, taxa_grp, **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
- abstract append_vrnt(values, vrnt_chrgrp, vrnt_phypos, vrnt_name, vrnt_genpos, vrnt_xoprob, vrnt_hapgrp, vrnt_mask, **kwargs)#
Append values to the VariantMatrix along the variant axis.
- Parameters:
values (Matrix, numpy.ndarray) – Values are appended to append to the VariantMatrix.
vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to append to the VariantMatrix.
vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to append to the VariantMatrix.
vrnt_name (numpy.ndarray) – Variant names to append to the VariantMatrix.
vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to append to the VariantMatrix.
vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to append to the VariantMatrix.
vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to append to the VariantMatrix.
vrnt_mask (numpy.ndarray) – Variant mask to append to the VariantMatrix.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract classmethod concat(mats, axis, **kwargs)#
Concatenate matrices together along an 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.
axis (int) – The axis along which the arrays will be joined.
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:
- abstract classmethod concat_phase(mats, **kwargs)#
Concatenate list of Matrix together along the phase axis.
- Parameters:
mats (Sequence of Matrix) – List of PhasedMatrix 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 PhasedMatrix. Note that concat does not occur in-place: a new PhasedMatrix is allocated and filled.
- Return type:
- abstract 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 TaxaMatrix. Note that concat does not occur in-place: a new TaxaMatrix is allocated and filled.
- Return type:
- abstract classmethod concat_vrnt(mats, **kwargs)#
Concatenate list of VariantMatrix together along the variant axis.
- Parameters:
mats (Sequence of VariantMatrix) – List of VariantMatrix 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 VariantMatrix is allocated and filled.
- Return type:
- abstract copy()#
Make a shallow copy of the Matrix.
- Returns:
out – A shallow copy of the original Matrix.
- Return type:
- abstract deepcopy(memo)#
Make a deep copy of the Matrix.
- Parameters:
memo (dict) – Dictionary of memo metadata.
- Returns:
out – A deep copy of the original Matrix.
- Return type:
- abstract delete(obj, axis, **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 Matrix with deleted elements. Note that concat does not occur in-place: a new Matrix is allocated and filled.
- Return type:
- abstract delete_phase(obj, **kwargs)#
Delete sub-arrays along the phase 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 PhasedMatrix with deleted elements. Note that concat does not occur in-place: a new PhasedMatrix is allocated and filled.
- Return type:
- abstract 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 TaxaMatrix with deleted elements. Note that concat does not occur in-place: a new TaxaMatrix is allocated and filled.
- Return type:
- abstract 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 VariantMatrix with deleted elements. Note that delete does not occur in-place: a new VariantMatrix is allocated and filled.
- Return type:
- abstract classmethod from_hdf5(filename, groupname)#
Read an object from an HDF5 file.
- Parameters:
filename (str, Path, h5py.File) – If
str
, an HDF5 file name from which to read. IfPath
, an HDF5 file name from which to read. Ifh5py.File
, an opened HDF5 file from which to read.groupname (str, None) – If
str
, an HDF5 group name under which object data is stored. IfNone
, object is read from base HDF5 group.
- Returns:
out – An object read from an HDF5 file.
- Return type:
- abstract group(axis, **kwargs)#
Sort the GroupableMatrix 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
- abstract 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
- abstract group_vrnt(**kwargs)#
Sort the VariantMatrix along the variant axis, then populate grouping indices for the variant axis.
- Parameters:
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract gtcount(dtype)#
Gather haplotype counts across for homozygous major, heterozygous, homozygous minor all individuals.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – An int64 array of shape
(3,h)
containing haplotype counts across allh
haplotypes.Where:
out[0]
is the count of0
genotype across all lociout[1]
is the count of1
genotype across all lociout[2]
is the count of2
genotype across all loci
- Return type:
numpy.ndarray
- abstract gtfreq(dtype)#
Gather haplotype frequencies for homozygous major, heterozygous, homozygous minor across all individuals.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – An float64 array of shape
(3,h)
containing haplotype counts across allh
haplotypes.Where:
out[0]
is the frequency of0
genotype across all lociout[1]
is the frequency of1
genotype across all lociout[2]
is the frequency of2
genotype across all loci
- Return type:
numpy.ndarray
- abstract hcount(dtype)#
Haplotype count of the non-zero haplotype across all taxa.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – A numpy.ndarray of shape (h,) containing haplotype counts of the haplotype coded as 1 for all ‘h’ haplotypes.
- Return type:
numpy.ndarray
- abstract hfreq(dtype)#
Haplotype frequency of the non-zero haplotype across all taxa.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – A numpy.ndarray of shape (h,) containing haplotype frequencies of the haplotype coded as 1 for all ‘h’ haplotypes.
- Return type:
numpy.ndarray
- abstract incorp(obj, values, axis, **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 (numpy.ndarray) – Values to incorporate into the matrix.
axis (int) – The axis along which values are incorporated.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract incorp_phase(obj, values, **kwargs)#
Incorporate values along the phase 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.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract incorp_taxa(obj, values, taxa, taxa_grp, **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
- abstract incorp_vrnt(obj, values, vrnt_chrgrp, vrnt_phypos, vrnt_name, vrnt_genpos, vrnt_xoprob, vrnt_hapgrp, vrnt_mask, **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 VariantMatrix.
vrnt_chrgrp (numpy.ndarray) – Variant chromosome groups to incorporate into the VariantMatrix.
vrnt_phypos (numpy.ndarray) – Variant chromosome physical positions to incorporate into the VariantMatrix.
vrnt_name (numpy.ndarray) – Variant names to incorporate into the VariantMatrix.
vrnt_genpos (numpy.ndarray) – Variant chromosome genetic positions to incorporate into the VariantMatrix.
vrnt_xoprob (numpy.ndarray) – Sequential variant crossover probabilities to incorporate into the VariantMatrix.
vrnt_hapgrp (numpy.ndarray) – Variant haplotype labels to incorporate into the VariantMatrix.
vrnt_mask (numpy.ndarray) – Variant mask to incorporate into the VariantMatrix.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract insert(obj, values, axis, **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 (ArrayLike) – Values to insert into the matrix.
axis (int) – The axis along which values are inserted.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – A Matrix with values inserted. Note that insert does not occur in-place: a new Matrix is allocated and filled.
- Return type:
- abstract insert_phase(obj, values, **kwargs)#
Insert values along the phase 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.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – A PhasedMatrix with values inserted. Note that insert does not occur in-place: a new PhasedMatrix is allocated and filled.
- Return type:
- abstract insert_taxa(obj, values, taxa, taxa_grp, **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 TaxaMatrix with values inserted. Note that insert does not occur in-place: a new TaxaMatrix is allocated and filled.
- Return type:
- abstract insert_vrnt(obj, values, vrnt_chrgrp, vrnt_phypos, vrnt_name, vrnt_genpos, vrnt_xoprob, vrnt_hapgrp, vrnt_mask, **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_mask (numpy.ndarray) – Variant mask to insert into the Matrix.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – A VariantMatrix with values inserted. Note that insert does not occur in-place: a new VariantMatrix is allocated and filled.
- Return type:
- abstract is_grouped(axis, **kwargs)#
Determine whether the Matrix has been sorted and grouped.
- Parameters:
axis (int) – Axis along which to determine whether elements have been sorted and grouped.
kwargs (dict) – Additional keyword arguments.
- Returns:
grouped – True or False indicating whether the Matrix has been sorted and grouped.
- Return type:
bool
- abstract 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
- abstract 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
- abstract lexsort(keys, axis, **kwargs)#
Perform an indirect stable sort using a sequence of keys.
- 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.
axis (int) – Axis to be indirectly sorted.
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
- abstract lexsort_taxa(keys, **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
- abstract lexsort_vrnt(keys, **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
- abstract property mat: object#
Pointer to raw matrix object.
- abstract property mat_format: str#
Matrix representation format.
- abstract property mat_ndim: int#
Number of dimensions of the raw matrix.
- abstract property mat_shape: tuple#
Shape of the raw matrix.
- abstract meh(dtype)#
Mean expected heterozygosity across all taxa.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
meh – A 64-bit floating point representing the mean expected heterozygosity.
- Return type:
numpy.float64
- abstract mhf(dtype)#
Minor haplotype frequency across all taxa.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – A numpy.ndarray of shape (h,) containing haplotype frequencies for the minor haplotype.
- Return type:
numpy.ndarray
- abstract property nphase: int#
The number of phases represented by the haplotype matrix.
- abstract property ntaxa: int#
Number of taxa.
- abstract property nvrnt: int#
Number of variants.
- abstract property phase_axis: int#
Axis along which phases are stored.
- abstract property ploidy: int#
The ploidy level represented by the haplotype matrix.
- abstract remove(obj, axis, **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
- abstract remove_phase(obj, **kwargs)#
Remove sub-arrays along the phase 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
- abstract 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
- abstract 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
- abstract reorder(indices, axis, **kwargs)#
Reorder elements of the Matrix using an array of indices. Note this modifies the Matrix in-place.
- Parameters:
indices (A (N,) ndarray of ints, Sequence of ints) – Array of indices that reorder the matrix along the specified axis.
axis (int) – Axis to be reordered.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract 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
- abstract 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, Sequence of ints) – Array of indices that reorder the matrix along the specified axis.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract select(indices, axis, **kwargs)#
Select certain values from the matrix.
- Parameters:
indices (ArrayLike (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 matrix with values selected. Note that select does not occur in-place: a new Matrix is allocated and filled.
- Return type:
- abstract select_phase(indices, **kwargs)#
Select certain values from the Matrix along the phase axis.
- Parameters:
indices (ArrayLike (Nj, ...)) – The indices of the values to select.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – The output PhasedMatrix with values selected. Note that select does not occur in-place: a new PhasedMatrix is allocated and filled.
- Return type:
- abstract 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 TaxaMatrix with values selected. Note that select does not occur in-place: a new TaxaMatrix is allocated and filled.
- Return type:
- abstract select_vrnt(indices, **kwargs)#
Select certain values from the VariantMatrix along the variant axis.
- Parameters:
indices (ArrayLike (Nj, ...)) – The indices of the values to select.
kwargs (dict) – Additional keyword arguments.
- Returns:
out – The output VariantMatrix with values selected. Note that select does not occur in-place: a new VariantMatrix is allocated and filled.
- Return type:
- abstract sort(keys, axis, **kwargs)#
Sort slements of the Matrix 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.
axis (int) – Axis to be indirectly sorted.
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract sort_taxa(keys, **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
- abstract sort_vrnt(keys, **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
- abstract property taxa: object#
Taxa label.
- abstract property taxa_axis: int#
Axis along which taxa are stored.
- abstract property taxa_grp: object#
Taxa group label.
- abstract property taxa_grp_len: object#
Taxa group length.
- abstract property taxa_grp_name: object#
Taxa group name.
- abstract property taxa_grp_spix: object#
Taxa group stop index.
- abstract property taxa_grp_stix: object#
Taxa group start index.
- abstract thcount(dtype)#
Haplotype count of the non-zero haplotype within each taxon.
- Parameters:
dtype (dtype, optional) – The type of the returned array. If None, return native dtype.
- Returns:
out – A numpy.ndarray of shape (n, h) containing haplotype counts of the haplotype coded as 1 for all ‘n’ individuals, for all ‘h’ haplotypes.
- Return type:
numpy.ndarray
- abstract thfreq(dtype)#
Haplotype frequency of the non-zero haplotype within each taxon.
- Parameters:
dtype (dtype, optional) – The type of the returned array and of the accumulator in which the elements are summed.
- Returns:
out – A numpy.ndarray of shape (n, h) containing haplotype frequencies of the haplotype coded as 1 for all ‘n’ individuals, for all ‘h’ haplotypes.
- Return type:
numpy.ndarray
- abstract to_hdf5(filename, groupname, overwrite)#
Write an object to an HDF5 file.
- Parameters:
filename (str, Path, h5py.File) – If
str
, an HDF5 file name to which to write. IfPath
, an HDF5 file path to which to write. Ifh5py.File
, an opened HDF5 file to which to write.groupname (str, None) – If
str
, an HDF5 group name under which object data is stored. IfNone
, object 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
- abstract ungroup(axis, **kwargs)#
Ungroup the GroupableMatrix 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
- abstract ungroup_taxa(**kwargs)#
Ungroup the TaxaMatrix along the taxa axis by removing taxa group metadata.
- Parameters:
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract ungroup_vrnt(**kwargs)#
Ungroup the VariantMatrix along the variant axis by removing variant group metadata.
- Parameters:
kwargs (dict) – Additional keyword arguments.
- Return type:
None
- abstract property vrnt_axis: int#
Axis along which variants are stored.
- abstract property vrnt_chrgrp: object#
Variant chromosome group label.
- abstract property vrnt_chrgrp_len: object#
Variant chromosome group length.
- abstract property vrnt_chrgrp_name: object#
Variant chromosome group names.
- abstract property vrnt_chrgrp_spix: object#
Variant chromosome group stop indices.
- abstract property vrnt_chrgrp_stix: object#
Variant chromosome group start indices.
- abstract property vrnt_genpos: object#
Variant genetic position.
- abstract property vrnt_hapalt: object#
Variant haplotype sequence.
- abstract property vrnt_hapgrp: object#
Variant haplotype group label.
- abstract property vrnt_hapref: object#
Variant reference haplotype sequence.
- abstract property vrnt_mask: object#
Variant mask.
- abstract property vrnt_name: object#
Variant name.
- abstract property vrnt_phypos: object#
Variant physical position.
- abstract property vrnt_xoprob: object#
Variant crossover sequential probability.