def reference_remove_sequence():
try:
data = flask.request.json
scala_object(Env.hail().variant,
'ReferenceGenome').removeSequence(data['name'])
return '', 204
except FatalError as e:
return flask.jsonify({'message': e.args[0]}), 400
def _convert_to_j(self, annotation):
if annotation is not None:
return scala_object(Env.hail().annotations, 'Annotation').fromSeq(
Env.jutils().arrayListToISeq(
[t._convert_to_j(annotation.get(f)) for f, t in self.items()]))
else:
return None
def create_backward_compatibility_files():
import os
all_values_table, all_values_matrix_table = create_all_values_datasets()
file_version = Env.hail().expr.ir.FileFormat.version().toString()
supported_codecs = scala_object(Env.hail().io, 'BufferSpec').specs()
table_dir = resource(
os.path.join('backward_compatability', str(file_version), 'table'))
if not os.path.exists(table_dir):
os.makedirs(table_dir)
matrix_table_dir = resource(
os.path.join('backward_compatability', str(file_version),
'matrix_table'))
if not os.path.exists(matrix_table_dir):
os.makedirs(matrix_table_dir)
i = 0
for codec in supported_codecs:
all_values_table.write(os.path.join(table_dir, f'{i}.ht'),
overwrite=True,
_codec_spec=codec.toString())
all_values_matrix_table.write(os.path.join(matrix_table_dir,
f'{i}.hmt'),
overwrite=True,
_codec_spec=codec.toString())
i += 1
def __init__(self, key_type, value_type, required=False):
jtype = scala_object(Env.hail().expr,
'TDict').apply(key_type._jtype, value_type._jtype,
required)
self.key_type = key_type
self.value_type = value_type
super(TDict, self).__init__(jtype)
def _convert_to_j(self, annotation):
if annotation is not None:
return scala_object(Env.hail().annotations, 'Annotation').fromSeq(
Env.jutils().arrayListToISeq(
[t._convert_to_j(annotation.get(f)) for f, t in self.items()]))
else:
return None
def random(rows, cols, block_size):
hc = Env.hc()
return BlockMatrix(
hc,
scala_object(Env.hail().distributedmatrix,
'BlockMatrix').random(hc._jhc, rows, cols,
block_size))
def __init__(self, element_type, required=False):
"""
:param :class:`.Type` element_type: Hail type of set element
"""
jtype = scala_object(Env.hail().expr,
'TSet').apply(element_type._jtype, required)
self.element_type = element_type
super(TSet, self).__init__(jtype)
def _convert_to_j(self, annotation):
if annotation is not None:
return scala_object(Env.hail().annotations, 'Annotation').fromSeq(
Env.jutils().arrayListToISeq([
f.typ._convert_to_j(annotation.get(f.name))
for f in self.fields
]))
else:
return None
def test_codecs_table(self):
from hail.utils.java import Env, scala_object
codecs = scala_object(Env.hail().io, 'CodecSpec').codecSpecs()
rt = self.get_vds().rows()
temp = new_temp_file(suffix='ht')
for codec in codecs:
rt.write(temp, overwrite=True, _codec_spec=codec.toString())
rt2 = hl.read_table(temp)
self.assertTrue(rt._same(rt2))
def test_codecs_table(self):
from hail.utils.java import scala_object
codecs = scala_object(Env.hail().io, 'CodecSpec').codecSpecs()
rt = self.get_vds().rows()
temp = new_temp_file(suffix='ht')
for codec in codecs:
rt.write(temp, overwrite=True, _codec_spec=codec.toString())
rt2 = hl.read_table(temp)
self.assertTrue(rt._same(rt2))
def test_codecs_matrix(self):
from hail.utils.java import Env, scala_object
codecs = scala_object(Env.hail().io, 'CodecSpec').codecSpecs()
ds = self.get_vds()
temp = new_temp_file(suffix='hmt')
for codec in codecs:
ds.write(temp, overwrite=True, _codec_spec=codec.toString())
ds2 = hl.read_matrix_table(temp)
self.assertTrue(ds._same(ds2))
def __init__(self, **field_types):
self._field_types = field_types
self._fields = tuple(field_types)
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TStruct').apply(
list(self._fields),
[t._jtype for f, t in self._field_types.items()],
False)
super(tstruct, self).__init__()
def __init__(self, **field_types):
self._field_types = field_types
self._fields = tuple(field_types)
self._get_jtype = lambda: scala_object(Env.hail(
).expr.types, 'TStruct').apply(list(
self._fields), [t._jtype
for f, t in self._field_types.items()], False)
super(tstruct, self).__init__()
def __init__(self, contig, position, reference_genome=None):
if isinstance(contig, int):
contig = str(contig)
jrep = scala_object(Env.hail().variant,
'Locus').apply(contig, position)
self._init_from_java(jrep)
self._contig = contig
self._position = position
self._rg = reference_genome if reference_genome else Env.hc(
).default_reference
def __init__(self, contig, position, reference_genome='default'):
if isinstance(contig, int):
contig = str(contig)
self._rg = reference_genome
jrep = scala_object(Env.hail().variant, 'Locus').apply(contig, position, self._rg._jrep)
self._init_from_java(jrep)
self._contig = contig
self._position = position
def __init__(self, contig, start, ref, alts, reference_genome=None):
if isinstance(contig, int):
contig = str(contig)
jrep = scala_object(Env.hail().variant,
'Variant').apply(contig, start, ref, alts)
self._init_from_java(jrep)
self._contig = contig
self._start = start
self._ref = ref
self._rg = reference_genome if reference_genome else Env.hc(
).default_reference
def __init__(self, contig, position, reference_genome='default'):
if isinstance(contig, int):
contig = str(contig)
self._rg = reference_genome
jrep = scala_object(Env.hail().variant,
'Locus').apply(contig, position, self._rg._jrep)
self._init_from_java(jrep)
self._contig = contig
self._position = position
def __init__(self, names, types, required=False):
if len(names) != len(types):
raise ValueError('length of names and types not equal: %d and %d' %
(len(names), len(types)))
jtype = scala_object(Env.hail().expr,
'TStruct').apply(names,
map(lambda t: t._jtype, types),
required)
self.fields = [Field(names[i], types[i]) for i in range(len(names))]
super(TStruct, self).__init__(jtype)
def from_fields(cls, fields, required=False):
"""Creates a new TStruct from field objects.
:param fields: The TStruct fields.
:type fields: list of :class:`.Field`
:param bool required: Flag for whether the struct can be missing.
:return: TStruct from input fields
:rtype: :class:`.TStruct`
"""
struct = TStruct.__new__(cls)
struct.fields = fields
jfields = [
scala_object(Env.hail().expr,
'Field').apply(f.name, f.typ._jtype, i)
for i, f in enumerate(fields)
]
jtype = scala_object(Env.hail().expr,
'TStruct').apply(jindexed_seq(jfields), required)
return TStruct._from_java(jtype)
def parse(cls, string, reference_genome='default'):
"""Parses a locus object from a CHR:POS string.
**Examples**
>>> l1 = hl.Locus.parse('1:101230')
>>> l2 = hl.Locus.parse('X:4201230')
:param str string: String to parse.
:param reference_genome: Reference genome to use. Default is :func:`~hail.default_reference`.
:type reference_genome: :obj:`str` or :class:`.ReferenceGenome`
:rtype: :class:`.Locus`
"""
return Locus._from_java(scala_object(Env.hail().variant, 'Locus').parse(string, reference_genome._jrep), reference_genome)
def parse(cls, string, reference_genome=None):
"""Parses a locus object from a CHR:POS string.
**Examples**
>>> l1 = Locus.parse('1:101230')
>>> l2 = Locus.parse('X:4201230')
:param str string: String to parse.
:param reference_genome: Reference genome to use. Default is :py:meth:`hail.api1.HailContext.default_reference`.
:type reference_genome: :class:`.GenomeReference`
:rtype: :class:`.Locus`
"""
rg = reference_genome if reference_genome else Env.hc(
).default_reference
return Locus._from_java(
scala_object(Env.hail().variant, 'Locus').parse(string), rg)
def parse(cls, string, reference_genome='default'):
"""Parses a locus object from a CHR:POS string.
**Examples**
>>> l1 = hl.Locus.parse('1:101230')
>>> l2 = hl.Locus.parse('X:4201230')
:param str string: String to parse.
:param reference_genome: Reference genome to use. Default is :func:`~hail.default_reference`.
:type reference_genome: :obj:`str` or :class:`.ReferenceGenome`
:rtype: :class:`.Locus`
"""
return Locus._from_java(
scala_object(Env.hail().variant,
'Locus').parse(string, reference_genome._jrep),
reference_genome)
def parse(cls, string, reference_genome=None):
"""Parses a variant object from a string.
There are two acceptable formats: CHR:POS:REF:ALT, and
CHR:POS:REF:ALT1,ALT2,...ALTN. Below is an example of
each:
>>> v_biallelic = Variant.parse('16:20012:A:TT')
>>> v_multiallelic = Variant.parse('16:12311:T:C,TTT,A')
:param str string: String to parse.
:param reference_genome: Reference genome to use. Default is :py:meth:`hail.api1.HailContext.default_reference`.
:type reference_genome: :class:`.GenomeReference`
:rtype: :class:`.Variant`
"""
rg = reference_genome if reference_genome else Env.hc(
).default_reference
jrep = scala_object(Env.hail().variant, 'Variant').parse(string)
return Variant._from_java(jrep, rg)
def create_backward_compatibility_files():
import os
all_values_table, all_values_matrix_table = create_all_values_datasets()
file_version = Env.hail().variant.FileFormat.version().toString()
supported_codecs = scala_object(Env.hail().io, 'CodecSpec').supportedCodecSpecs()
table_dir = 'backward_compatability/{}/table'.format(file_version)
if not os.path.exists(table_dir):
os.makedirs(table_dir)
matrix_table_dir = 'backward_compatability/{}/matrix_table'.format(file_version)
if not os.path.exists(matrix_table_dir):
os.makedirs(matrix_table_dir)
i = 0
for codec in supported_codecs:
all_values_table.write('{}/{}.ht'.format(table_dir, i), overwrite=True, _codec_spec=codec.toString())
all_values_matrix_table.write('{}/{}.hmt'.format(matrix_table_dir, i), overwrite=True, _codec_spec=codec.toString())
i += 1
def create_backward_compatibility_files():
import os
all_values_table, all_values_matrix_table = create_all_values_datasets()
file_version = Env.hail().variant.FileFormat.version().toString()
supported_codecs = scala_object(Env.hail().io, 'CodecSpec').supportedCodecSpecs()
table_dir = resource(os.path.join('backward_compatability', str(file_version), 'table'))
if not os.path.exists(table_dir):
os.makedirs(table_dir)
matrix_table_dir = resource(os.path.join('backward_compatability', str(file_version), 'matrix_table'))
if not os.path.exists(matrix_table_dir):
os.makedirs(matrix_table_dir)
i = 0
for codec in supported_codecs:
all_values_table.write(os.path.join(table_dir, f'{i}.ht'), overwrite=True, _codec_spec=codec.toString())
all_values_matrix_table.write(os.path.join(matrix_table_dir, f'{i}.hmt'), overwrite=True,
_codec_spec=codec.toString())
i += 1
def __init__(self, reference_genome=None, required=False):
self._rg = reference_genome if reference_genome else Env.hc(
).default_reference
jtype = scala_object(Env.hail().expr,
'TInterval').apply(self._rg._jrep, required)
super(TInterval, self).__init__(jtype)
def __init__(self, ref, alt):
jaa = scala_object(Env.hail().variant, 'AltAllele').apply(ref, alt)
self._init_from_java(jaa)
self._ref = ref
self._alt = alt
def __init__(self, required=False):
super(TCall, self).__init__(
scala_object(Env.hail().expr, 'TCall').apply(required))
def remove_sequence(self, name):
scala_object(Env.hail().variant,
'ReferenceGenome').removeSequence(name)
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TInt32Optional')
super(_tint32, self).__init__()
def __init__(self, element_type):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TArray').apply(element_type._jtype, False)
self._element_type = element_type
super(tarray, self).__init__()
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TStringOptional')
super(_tstr, self).__init__()
def __init__(self, required=False):
super(TInt64, self).__init__(
scala_object(Env.hail().expr, 'TInt64').apply(required))
self.required = required
def __init__(self, key_type, value_type):
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TDict').apply(
key_type._jtype, value_type._jtype, False)
self._key_type = key_type
self._value_type = value_type
super(tdict, self).__init__()
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TCallOptional')
super(_tcall, self).__init__()
def __init__(self, *types):
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TTuple').apply(map(lambda t: t._jtype, types),
False)
self._types = types
super(ttuple, self).__init__()
def __init__(self, key_type, value_type):
self._get_jtype = lambda: scala_object(Env.hail(
).expr.types, 'TDict').apply(key_type._jtype, value_type._jtype, False)
self._key_type = key_type
self._value_type = value_type
super(tdict, self).__init__()
def __init__(self, *types):
self._get_jtype = lambda: scala_object(Env.hail(
).expr.types, 'TTuple').apply(map(lambda t: t._jtype, types), False)
self._types = types
super(ttuple, self).__init__()
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types,
'TCallOptional')
super(_tcall, self).__init__()
def remove_sequence(self, name):
scala_object(self._hail_package.variant,
'ReferenceGenome').removeSequence(name)
def __init__(self, element_type):
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TSet').apply(element_type._jtype, False)
self._element_type = element_type
super(tset, self).__init__()
def remove_liftover(self, name, dest_reference_genome):
scala_object(self._hail_package.variant,
'ReferenceGenome').referenceRemoveLiftover(
name, dest_reference_genome)
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TVoid')
super(_tvoid, self).__init__()
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TBooleanOptional')
super(_tbool, self).__init__()
def __init__(self, point_type):
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TInterval').apply(self.point_type._jtype, False)
self._point_type = point_type
super(tinterval, self).__init__()
def __init__(self):
self._get_jtype = lambda: scala_object(Env.hail().expr.types, 'TFloat64Optional')
super(_tfloat64, self).__init__()
def __init__(self, reference_genome='default'):
self._rg = reference_genome
self._get_jtype = lambda: scala_object(Env.hail().expr.types.virtual, 'TLocus').apply(self._rg._jrep,
False)
super(tlocus, self).__init__()
def remove_liftover(self, name, dest_reference_genome):
scala_object(Env.hail().variant,
'ReferenceGenome').referenceRemoveLiftover(
name, dest_reference_genome)
def __init__(self, required=False):
super(TAltAllele, self).__init__(
scala_object(Env.hail().expr, 'TAltAllele').apply(required))
def blocking_reference_add_sequence(data):
scala_object(Env.hail().variant, 'ReferenceGenome').addSequence(
data['name'], data['fasta_file'], data['index_file'])
def blocking_reference_remove_sequence(data):
scala_object(
Env.hail().variant, 'ReferenceGenome').removeSequence(data['name'])
