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test_matrix_table.py
1229 lines (1000 loc) · 53 KB
/
test_matrix_table.py
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import math
import operator
import random
import unittest
import hail as hl
import hail.expr.aggregators as agg
from hail.utils.java import Env
from hail.utils.misc import new_temp_file
from ..helpers import *
setUpModule = startTestHailContext
tearDownModule = stopTestHailContext
class Tests(unittest.TestCase):
def get_vds(self, min_partitions=None) -> hl.MatrixTable:
return hl.import_vcf(resource("sample.vcf"), min_partitions=min_partitions)
def test_range_count(self):
self.assertEqual(hl.utils.range_matrix_table(7, 13).count(), (7, 13))
def test_row_key_field_show_runs(self):
ds = self.get_vds()
ds.locus.show()
def test_update(self):
vds = self.get_vds()
vds = vds.select_entries(dp=vds.DP, gq=vds.GQ)
self.assertTrue(schema_eq(vds.entry.dtype, hl.tstruct(dp=hl.tint32, gq=hl.tint32)))
def test_annotate(self):
vds = self.get_vds()
vds = vds.annotate_globals(foo=5)
self.assertEqual(vds.globals.dtype, hl.tstruct(foo=hl.tint32))
vds = vds.annotate_rows(x1=agg.count(),
x2=agg.fraction(False),
x3=agg.count_where(True),
x4=vds.info.AC + vds.foo)
vds = vds.annotate_cols(apple=6)
vds = vds.annotate_cols(y1=agg.count(),
y2=agg.fraction(False),
y3=agg.count_where(True),
y4=vds.foo + vds.apple)
expected_schema = hl.tstruct(s=hl.tstr, apple=hl.tint32, y1=hl.tint64, y2=hl.tfloat64, y3=hl.tint64,
y4=hl.tint32)
self.assertTrue(schema_eq(vds.col.dtype, expected_schema),
"expected: " + str(vds.col.dtype) + "\nactual: " + str(expected_schema))
vds = vds.select_entries(z1=vds.x1 + vds.foo,
z2=vds.x1 + vds.y1 + vds.foo)
self.assertTrue(schema_eq(vds.entry.dtype, hl.tstruct(z1=hl.tint64, z2=hl.tint64)))
def test_annotate_globals(self):
mt = hl.utils.range_matrix_table(1, 1)
ht = hl.utils.range_table(1, 1)
data = [
(5, hl.tint, operator.eq),
(float('nan'), hl.tfloat32, lambda x, y: str(x) == str(y)),
(float('inf'), hl.tfloat64, lambda x, y: str(x) == str(y)),
(float('-inf'), hl.tfloat64, lambda x, y: str(x) == str(y)),
(1.111, hl.tfloat64, operator.eq),
([hl.Struct(**{'a': None, 'b': 5}),
hl.Struct(**{'a': 'hello', 'b': 10})], hl.tarray(hl.tstruct(a=hl.tstr, b=hl.tint)), operator.eq)
]
for x, t, f in data:
self.assertTrue(f(hl.eval(mt.annotate_globals(foo=hl.literal(x, t)).foo), x), f"{x}, {t}")
self.assertTrue(f(hl.eval(ht.annotate_globals(foo=hl.literal(x, t)).foo), x), f"{x}, {t}")
def test_head(self):
# no empty partitions
mt1 = hl.utils.range_matrix_table(10, 10)
# empty partitions at front
mt2 = hl.utils.range_matrix_table(20, 10, 20)
mt2 = mt2.filter_rows(mt2.row_idx > 9)
mts = [mt1, mt2]
for mt in mts:
tmp_file = new_temp_file(suffix='mt')
mt.write(tmp_file)
mt_readback = hl.read_matrix_table(tmp_file)
for mt_ in [mt, mt_readback]:
assert mt_.head(1).count_rows() == 1
assert mt_.head(1)._force_count_rows() == 1
assert mt_.head(100).count_rows() == 10
assert mt_.head(100)._force_count_rows() == 10
def test_head_cols(self):
mt1 = hl.utils.range_matrix_table(10, 10)
assert mt1.head(1, 2).count() == (1, 2)
assert mt1.head(1, None).count() == (1, 10)
assert mt1.head(None, 1).count() == (10, 1)
def test_filter(self):
vds = self.get_vds()
vds = vds.annotate_globals(foo=5)
vds = vds.annotate_rows(x1=agg.count())
vds = vds.annotate_cols(y1=agg.count())
vds = vds.annotate_entries(z1=vds.DP)
vds = vds.filter_rows((vds.x1 == 5) & (agg.count() == 3) & (vds.foo == 2))
vds = vds.filter_cols((vds.y1 == 5) & (agg.count() == 3) & (vds.foo == 2))
vds = vds.filter_entries((vds.z1 < 5) & (vds.y1 == 3) & (vds.x1 == 5) & (vds.foo == 2))
vds.count_rows()
def test_aggregate(self):
vds = self.get_vds()
vds = vds.annotate_globals(foo=5)
vds = vds.annotate_rows(x1=agg.count())
vds = vds.annotate_cols(y1=agg.count())
vds = vds.annotate_entries(z1=vds.DP)
qv = vds.aggregate_rows(agg.count())
qs = vds.aggregate_cols(agg.count())
qg = vds.aggregate_entries(agg.count())
self.assertIsNotNone(vds.aggregate_entries(hl.agg.take(vds.s, 1)[0]))
self.assertEqual(qv, 346)
self.assertEqual(qs, 100)
self.assertEqual(qg, qv * qs)
qvs = vds.aggregate_rows(hl.Struct(x=agg.collect(vds.locus.contig),
y=agg.collect(vds.x1)))
qss = vds.aggregate_cols(hl.Struct(x=agg.collect(vds.s),
y=agg.collect(vds.y1)))
qgs = vds.aggregate_entries(hl.Struct(x=agg.filter(False, agg.collect(vds.y1)),
y=agg.filter(hl.rand_bool(0.1), agg.collect(vds.GT))))
def test_aggregate_ir(self):
ds = (hl.utils.range_matrix_table(5, 5)
.annotate_globals(g1=5)
.annotate_entries(e1=3))
x = [("col_idx", lambda e: ds.aggregate_cols(e)),
("row_idx", lambda e: ds.aggregate_rows(e))]
for name, f in x:
r = f(hl.struct(x=agg.sum(ds[name]) + ds.g1,
y=agg.filter(ds[name] % 2 != 0, agg.sum(ds[name] + 2)) + ds.g1,
z=agg.sum(ds.g1 + ds[name]) + ds.g1,
mean=agg.mean(ds[name])))
self.assertEqual(convert_struct_to_dict(r), {u'x': 15, u'y': 13, u'z': 40, u'mean': 2.0})
r = f(5)
self.assertEqual(r, 5)
r = f(hl.null(hl.tint32))
self.assertEqual(r, None)
r = f(agg.filter(ds[name] % 2 != 0, agg.sum(ds[name] + 2)) + ds.g1)
self.assertEqual(r, 13)
r = ds.aggregate_entries(agg.filter((ds.row_idx % 2 != 0) & (ds.col_idx % 2 != 0),
agg.sum(ds.e1 + ds.g1 + ds.row_idx + ds.col_idx)) + ds.g1)
self.assertTrue(r, 48)
def test_select_entries(self):
mt = hl.utils.range_matrix_table(10, 10, n_partitions=4)
mt = mt.annotate_entries(a=hl.struct(b=mt.row_idx, c=mt.col_idx), foo=mt.row_idx * 10 + mt.col_idx)
mt = mt.select_entries(mt.a.b, mt.a.c, mt.foo)
mt = mt.annotate_entries(bc=mt.b * 10 + mt.c)
mt_entries = mt.entries()
assert (mt_entries.all(mt_entries.bc == mt_entries.foo))
def test_select_cols(self):
mt = hl.utils.range_matrix_table(3, 5, n_partitions=4)
mt = mt.annotate_entries(e=mt.col_idx * mt.row_idx)
mt = mt.annotate_globals(g=1)
mt = mt.annotate_cols(sum=agg.sum(mt.e + mt.col_idx + mt.row_idx + mt.g) + mt.col_idx + mt.g,
count=agg.count_where(mt.e % 2 == 0),
foo=agg.count())
result = convert_struct_to_dict(mt.cols().collect()[-2])
self.assertEqual(result, {'col_idx': 3, 'sum': 28, 'count': 2, 'foo': 3})
def test_drop(self):
vds = self.get_vds()
vds = vds.annotate_globals(foo=5)
vds = vds.annotate_cols(bar=5)
vds1 = vds.drop('GT', 'info', 'foo', 'bar')
self.assertTrue('foo' not in vds1.globals)
self.assertTrue('info' not in vds1.row)
self.assertTrue('bar' not in vds1.col)
self.assertTrue('GT' not in vds1.entry)
vds1._force_count_rows()
vds2 = vds.drop(vds.GT, vds.info, vds.foo, vds.bar)
self.assertTrue('foo' not in vds2.globals)
self.assertTrue('info' not in vds2.row)
self.assertTrue('bar' not in vds2.col)
self.assertTrue('GT' not in vds2.entry)
vds2._force_count_rows()
def test_explode_rows(self):
mt = hl.utils.range_matrix_table(4, 4)
mt = mt.annotate_entries(e=mt.row_idx * 10 + mt.col_idx)
self.assertTrue(mt.annotate_rows(x=[1]).explode_rows('x').drop('x')._same(mt))
self.assertEqual(mt.annotate_rows(x=hl.empty_array('int')).explode_rows('x').count_rows(), 0)
self.assertEqual(mt.annotate_rows(x=hl.null('array<int>')).explode_rows('x').count_rows(), 0)
self.assertEqual(mt.annotate_rows(x=hl.range(0, mt.row_idx)).explode_rows('x').count_rows(), 6)
mt = mt.annotate_rows(x=hl.struct(y=hl.range(0, mt.row_idx)))
self.assertEqual(mt.explode_rows(mt.x.y).count_rows(), 6)
def test_explode_cols(self):
mt = hl.utils.range_matrix_table(4, 4)
mt = mt.annotate_entries(e=mt.row_idx * 10 + mt.col_idx)
self.assertTrue(mt.annotate_cols(x=[1]).explode_cols('x').drop('x')._same(mt))
self.assertEqual(mt.annotate_cols(x=hl.empty_array('int')).explode_cols('x').count_cols(), 0)
self.assertEqual(mt.annotate_cols(x=hl.null('array<int>')).explode_cols('x').count_cols(), 0)
self.assertEqual(mt.annotate_cols(x=hl.range(0, mt.col_idx)).explode_cols('x').count_cols(), 6)
def test_explode_key_errors(self):
mt = hl.utils.range_matrix_table(1, 1).key_cols_by(a=[1]).key_rows_by(b=[1])
with self.assertRaises(ValueError):
mt.explode_cols('a')
with self.assertRaises(ValueError):
mt.explode_rows('b')
def test_group_by_field_lifetimes(self):
mt = hl.utils.range_matrix_table(3, 3)
mt2 = (mt.group_rows_by(row_idx='100')
.aggregate(x=hl.agg.collect_as_set(mt.row_idx + 5)))
assert mt2.aggregate_entries(hl.agg.all(mt2.x == hl.set({5, 6, 7})))
mt3 = (mt.group_cols_by(col_idx='100')
.aggregate(x=hl.agg.collect_as_set(mt.col_idx + 5)))
assert mt3.aggregate_entries(hl.agg.all(mt3.x == hl.set({5, 6, 7})))
def test_aggregate_cols_by(self):
mt = hl.utils.range_matrix_table(2, 4)
mt = (mt.annotate_cols(group=mt.col_idx < 2)
.annotate_globals(glob=5))
grouped = mt.group_cols_by(mt.group)
result = grouped.aggregate(sum=hl.agg.sum(mt.row_idx * 2 + mt.col_idx + mt.glob) + 3)
expected = (hl.Table.parallelize([
{'row_idx': 0, 'group': True, 'sum': 14},
{'row_idx': 0, 'group': False, 'sum': 18},
{'row_idx': 1, 'group': True, 'sum': 18},
{'row_idx': 1, 'group': False, 'sum': 22}
], hl.tstruct(row_idx=hl.tint, group=hl.tbool, sum=hl.tint64))
.annotate_globals(glob=5)
.key_by('row_idx', 'group'))
self.assertTrue(result.entries()._same(expected))
def test_aggregate_cols_by_init_op(self):
mt = hl.import_vcf(resource('sample.vcf'))
cs = mt.group_cols_by(mt.s).aggregate(cs = hl.agg.call_stats(mt.GT, mt.alleles))
cs._force_count_rows() # should run without error
def test_aggregate_rows_by(self):
mt = hl.utils.range_matrix_table(4, 2)
mt = (mt.annotate_rows(group=mt.row_idx < 2)
.annotate_globals(glob=5))
grouped = mt.group_rows_by(mt.group)
result = grouped.aggregate(sum=hl.agg.sum(mt.col_idx * 2 + mt.row_idx + mt.glob) + 3)
expected = (hl.Table.parallelize([
{'col_idx': 0, 'group': True, 'sum': 14},
{'col_idx': 1, 'group': True, 'sum': 18},
{'col_idx': 0, 'group': False, 'sum': 18},
{'col_idx': 1, 'group': False, 'sum': 22}
], hl.tstruct(group=hl.tbool, col_idx=hl.tint, sum=hl.tint64))
.annotate_globals(glob=5)
.key_by('group', 'col_idx'))
self.assertTrue(result.entries()._same(expected))
def test_collect_cols_by_key(self):
mt = hl.utils.range_matrix_table(3, 3)
col_dict = hl.literal({0: [1], 1: [2, 3], 2: [4, 5, 6]})
mt = mt.annotate_cols(foo=col_dict.get(mt.col_idx)) \
.explode_cols('foo')
mt = mt.annotate_entries(bar=mt.row_idx * mt.foo)
grouped = mt.collect_cols_by_key()
self.assertListEqual(grouped.cols().order_by('col_idx').collect(),
[hl.Struct(col_idx=0, foo=[1]),
hl.Struct(col_idx=1, foo=[2, 3]),
hl.Struct(col_idx=2, foo=[4, 5, 6])])
self.assertListEqual(
grouped.entries().select('bar')
.order_by('row_idx', 'col_idx').collect(),
[hl.Struct(row_idx=0, col_idx=0, bar=[0]),
hl.Struct(row_idx=0, col_idx=1, bar=[0, 0]),
hl.Struct(row_idx=0, col_idx=2, bar=[0, 0, 0]),
hl.Struct(row_idx=1, col_idx=0, bar=[1]),
hl.Struct(row_idx=1, col_idx=1, bar=[2, 3]),
hl.Struct(row_idx=1, col_idx=2, bar=[4, 5, 6]),
hl.Struct(row_idx=2, col_idx=0, bar=[2]),
hl.Struct(row_idx=2, col_idx=1, bar=[4, 6]),
hl.Struct(row_idx=2, col_idx=2, bar=[8, 10, 12])])
def test_weird_names(self):
ds = self.get_vds()
exprs = {'a': 5, ' a ': 5, r'\%!^!@#&#&$%#$%': [5], '$': 5, 'ß': 5}
ds.annotate_globals(**exprs)
ds.select_globals(**exprs)
ds.annotate_cols(**exprs)
ds1 = ds.select_cols(**exprs)
ds.annotate_rows(**exprs)
ds2 = ds.select_rows(**exprs)
ds.annotate_entries(**exprs)
ds.select_entries(**exprs)
ds1.explode_cols('\%!^!@#&#&$%#$%')
ds1.explode_cols(ds1['\%!^!@#&#&$%#$%'])
ds1.group_cols_by(ds1.a).aggregate(**{'*``81': agg.count()})
ds1.drop('\%!^!@#&#&$%#$%')
ds1.drop(ds1['\%!^!@#&#&$%#$%'])
ds2.explode_rows('\%!^!@#&#&$%#$%')
ds2.explode_rows(ds2['\%!^!@#&#&$%#$%'])
ds2.group_rows_by(ds2.a).aggregate(**{'*``81': agg.count()})
def test_semi_anti_join_rows(self):
mt = hl.utils.range_matrix_table(10, 3)
ht = hl.utils.range_table(3)
assert mt.semi_join_rows(ht).count() == (3, 3)
assert mt.anti_join_rows(ht).count() == (7, 3)
def test_semi_anti_join_cols(self):
mt = hl.utils.range_matrix_table(3, 10)
ht = hl.utils.range_table(3)
assert mt.semi_join_cols(ht).count() == (3, 3)
assert mt.anti_join_cols(ht).count() == (3, 7)
def test_joins(self):
vds = self.get_vds().select_rows(x1=1, y1=1)
vds2 = vds.select_rows(x2=1, y2=2)
vds2 = vds2.select_cols(c1=1, c2=2)
vds = vds.annotate_rows(y2=vds2.index_rows(vds.row_key).y2)
vds = vds.annotate_cols(c2=vds2.index_cols(vds.s).c2)
vds = vds.annotate_cols(c2=vds2.index_cols(hl.str(vds.s)).c2)
rt = vds.rows()
ct = vds.cols()
vds.annotate_rows(**rt[vds.locus, vds.alleles])
self.assertTrue(rt.all(rt.y2 == 2))
self.assertTrue(ct.all(ct.c2 == 2))
def test_joins_with_key_structs(self):
mt = self.get_vds()
rows = mt.rows()
cols = mt.cols()
self.assertEqual(rows[mt.locus, mt.alleles].take(1), rows[mt.row_key].take(1))
self.assertEqual(cols[mt.s].take(1), cols[mt.col_key].take(1))
self.assertEqual(mt.index_rows(mt.row_key).take(1), mt.index_rows(mt.locus, mt.alleles).take(1))
self.assertEqual(mt.index_cols(mt.col_key).take(1), mt.index_cols(mt.s).take(1))
self.assertEqual(mt[mt.row_key, mt.col_key].take(1), mt[(mt.locus, mt.alleles), mt.s].take(1))
def test_table_join(self):
ds = self.get_vds()
# test different row schemas
self.assertTrue(ds.union_cols(ds.drop(ds.info))
.count_rows(), 346)
def test_table_product_join(self):
left = hl.utils.range_matrix_table(5, 1)
right = hl.utils.range_table(5)
right = right.annotate(i=hl.range(right.idx + 1, 5)).explode('i').key_by('i')
left = left.annotate_rows(matches=right.index(left.row_key, all_matches=True))
rows = left.rows()
self.assertTrue(rows.all(rows.matches.map(lambda x: x.idx) == hl.range(0, rows.row_idx)))
def test_naive_coalesce(self):
vds = self.get_vds(min_partitions=8)
self.assertEqual(vds.n_partitions(), 8)
repart = vds.naive_coalesce(2)
self.assertTrue(vds._same(repart))
def test_coalesce_with_no_rows(self):
mt = self.get_vds().filter_rows(False)
self.assertEqual(mt.repartition(1).count_rows(), 0)
def test_literals_rebuild(self):
mt = hl.utils.range_matrix_table(1, 1)
mt = mt.annotate_rows(x = hl.cond(hl.len(hl.literal([1,2,3])) < hl.rand_unif(10, 11), mt.globals, hl.struct()))
mt._force_count_rows()
def test_unions(self):
dataset = hl.import_vcf(resource('sample2.vcf'))
# test union_rows
ds1 = dataset.filter_rows(dataset.locus.position % 2 == 1)
ds2 = dataset.filter_rows(dataset.locus.position % 2 == 0)
datasets = [ds1, ds2]
r1 = ds1.union_rows(ds2)
r2 = hl.MatrixTable.union_rows(*datasets)
self.assertTrue(r1._same(r2))
with self.assertRaises(ValueError):
ds1.filter_cols(ds1.s.endswith('5')).union_rows(ds2)
# test union_cols
ds = dataset.union_cols(dataset).union_cols(dataset)
for s, count in ds.aggregate_cols(agg.counter(ds.s)).items():
self.assertEqual(count, 3)
def test_union_cols_example(self):
joined = hl.import_vcf(resource('joined.vcf'))
left = hl.import_vcf(resource('joinleft.vcf'))
right = hl.import_vcf(resource('joinright.vcf'))
self.assertTrue(left.union_cols(right)._same(joined))
def test_index(self):
ds = self.get_vds(min_partitions=8)
self.assertEqual(ds.n_partitions(), 8)
ds = ds.add_row_index('rowidx').add_col_index('colidx')
for i, struct in enumerate(ds.cols().select('colidx').collect()):
self.assertEqual(i, struct.colidx)
for i, struct in enumerate(ds.rows().select('rowidx').collect()):
self.assertEqual(i, struct.rowidx)
def test_choose_cols(self):
ds = self.get_vds()
indices = list(range(ds.count_cols()))
random.shuffle(indices)
old_order = ds.key_cols_by()['s'].collect()
self.assertEqual(ds.choose_cols(indices).key_cols_by()['s'].collect(),
[old_order[i] for i in indices])
self.assertEqual(ds.choose_cols(list(range(10))).s.collect(),
old_order[:10])
def test_choose_cols_vs_explode(self):
ds = self.get_vds()
ds2 = ds.annotate_cols(foo=[0, 0]).explode_cols('foo').drop('foo')
self.assertTrue(ds.choose_cols(sorted(list(range(ds.count_cols())) * 2))._same(ds2))
def test_distinct_by_row(self):
orig_mt = hl.utils.range_matrix_table(10, 10)
mt = orig_mt.key_rows_by(row_idx=orig_mt.row_idx // 2)
self.assertTrue(mt.distinct_by_row().count_rows() == 5)
self.assertTrue(orig_mt.union_rows(orig_mt).distinct_by_row()._same(orig_mt))
def test_distinct_by_col(self):
orig_mt = hl.utils.range_matrix_table(10, 10)
mt = orig_mt.key_cols_by(col_idx=orig_mt.col_idx // 2)
self.assertTrue(mt.distinct_by_col().count_cols() == 5)
self.assertTrue(orig_mt.union_cols(orig_mt).distinct_by_col()._same(orig_mt))
def test_aggregation_with_no_aggregators(self):
mt = hl.utils.range_matrix_table(3, 3)
self.assertEqual(mt.group_rows_by(mt.row_idx).aggregate().count_rows(), 3)
self.assertEqual(mt.group_cols_by(mt.col_idx).aggregate().count_cols(), 3)
def test_computed_key_join_1(self):
ds = self.get_vds()
kt = hl.Table.parallelize(
[{'key': 0, 'value': True},
{'key': 1, 'value': False}],
hl.tstruct(key=hl.tint32, value=hl.tbool),
key=['key'])
ds = ds.annotate_rows(key=ds.locus.position % 2)
ds = ds.annotate_rows(value=kt[ds['key']]['value'])
rt = ds.rows()
self.assertTrue(
rt.all(((rt.locus.position % 2) == 0) == rt['value']))
def test_computed_key_join_2(self):
# multiple keys
ds = self.get_vds()
kt = hl.Table.parallelize(
[{'key1': 0, 'key2': 0, 'value': 0},
{'key1': 1, 'key2': 0, 'value': 1},
{'key1': 0, 'key2': 1, 'value': -2},
{'key1': 1, 'key2': 1, 'value': -1}],
hl.tstruct(key1=hl.tint32, key2=hl.tint32, value=hl.tint32),
key=['key1', 'key2'])
ds = ds.annotate_rows(key1=ds.locus.position % 2, key2=ds.info.DP % 2)
ds = ds.annotate_rows(value=kt[ds.key1, ds.key2]['value'])
rt = ds.rows()
self.assertTrue(
rt.all((rt.locus.position % 2) - 2 * (rt.info.DP % 2) == rt['value']))
def test_computed_key_join_3(self):
# duplicate row keys
ds = self.get_vds()
kt = hl.Table.parallelize(
[{'culprit': 'InbreedingCoeff', 'foo': 'bar', 'value': 'IB'}],
hl.tstruct(culprit=hl.tstr, foo=hl.tstr, value=hl.tstr),
key=['culprit', 'foo'])
ds = ds.annotate_rows(
dsfoo='bar',
info=ds.info.annotate(culprit=[ds.info.culprit, "foo"]))
ds = ds.explode_rows(ds.info.culprit)
ds = ds.annotate_rows(value=kt[ds.info.culprit, ds.dsfoo]['value'])
rt = ds.rows()
self.assertTrue(
rt.all(hl.cond(
rt.info.culprit == "InbreedingCoeff",
rt['value'] == "IB",
hl.is_missing(rt['value']))))
def test_interval_join(self):
left = hl.utils.range_matrix_table(50, 1, n_partitions=10)
intervals = hl.utils.range_table(4)
intervals = intervals.key_by(interval=hl.interval(intervals.idx * 10, intervals.idx * 10 + 5))
left = left.annotate_rows(interval_matches=intervals.index(left.row_key))
rows = left.rows()
self.assertTrue(rows.all(hl.case()
.when(rows.row_idx % 10 < 5, rows.interval_matches.idx == rows.row_idx // 10)
.default(hl.is_missing(rows.interval_matches))))
def test_interval_product_join(self):
left = hl.utils.range_matrix_table(50, 1, n_partitions=8)
intervals = hl.utils.range_table(25)
intervals = intervals.key_by(interval=hl.interval(
1 + (intervals.idx // 5) * 10 + (intervals.idx % 5),
(1 + intervals.idx // 5) * 10 - (intervals.idx % 5)))
intervals = intervals.annotate(i=intervals.idx % 5)
left = left.annotate_rows(interval_matches=intervals.index(left.row_key, all_matches=True))
rows = left.rows()
self.assertTrue(rows.all(hl.sorted(rows.interval_matches.map(lambda x: x.i))
== hl.range(0, hl.min(rows.row_idx % 10, 10 - rows.row_idx % 10))))
def test_entry_join_self(self):
mt1 = hl.utils.range_matrix_table(10, 10, n_partitions=4).choose_cols([9, 8, 7, 6, 5, 4, 3, 2, 1, 0])
mt1 = mt1.annotate_entries(x=10 * mt1.row_idx + mt1.col_idx)
self.assertEqual(mt1[mt1.row_idx, mt1.col_idx].dtype, mt1.entry.dtype)
mt_join = mt1.annotate_entries(x2=mt1[mt1.row_idx, mt1.col_idx].x)
mt_join_entries = mt_join.entries()
self.assertTrue(mt_join_entries.all(mt_join_entries.x == mt_join_entries.x2))
def test_entry_join_const(self):
mt1 = hl.utils.range_matrix_table(10, 10, n_partitions=4)
mt1 = mt1.annotate_entries(x=mt1.row_idx + mt1.col_idx)
mt2 = hl.utils.range_matrix_table(1, 1, n_partitions=1)
mt2 = mt2.annotate_entries(foo=10101)
mt_join = mt1.annotate_entries(**mt2[mt1.row_idx // 100, mt1.col_idx // 100])
mt_join_entries = mt_join.entries()
self.assertTrue(mt_join_entries.all(mt_join_entries['foo'] == 10101))
def test_entry_join_missingness(self):
mt1 = hl.utils.range_matrix_table(10, 10, n_partitions=4)
mt1 = mt1.annotate_entries(x=mt1.row_idx + mt1.col_idx)
mt2 = mt1.filter_cols(mt1.col_idx % 2 == 0)
mt2 = mt2.filter_rows(mt2.row_idx % 2 == 0)
mt_join = mt1.annotate_entries(x2=mt2[mt1.row_idx, mt1.col_idx].x * 10)
mt_join_entries = mt_join.entries()
kept = mt_join_entries.filter((mt_join_entries.row_idx % 2 == 0) & (mt_join_entries.col_idx % 2 == 0))
removed = mt_join_entries.filter(~((mt_join_entries.row_idx % 2 == 0) & (mt_join_entries.col_idx % 2 == 0)))
self.assertTrue(kept.all(hl.is_defined(kept.x2) & (kept.x2 == kept.x * 10)))
self.assertTrue(removed.all(hl.is_missing(removed.x2)))
def test_entries_table_length_and_fields(self):
mt = hl.utils.range_matrix_table(10, 10, n_partitions=4)
mt = mt.annotate_entries(x=mt.col_idx + mt.row_idx)
et = mt.entries()
self.assertEqual(et.count(), 100)
self.assertTrue(et.all(et.x == et.col_idx + et.row_idx))
def test_entries_table_no_keys(self):
mt = hl.utils.range_matrix_table(2, 2)
mt = mt.annotate_entries(x = (mt.row_idx, mt.col_idx))
original_order = [
hl.utils.Struct(row_idx=0, col_idx=0, x=(0, 0)),
hl.utils.Struct(row_idx=0, col_idx=1, x=(0, 1)),
hl.utils.Struct(row_idx=1, col_idx=0, x=(1, 0)),
hl.utils.Struct(row_idx=1, col_idx=1, x=(1, 1)),
]
assert mt.entries().collect() == original_order
assert mt.key_cols_by().entries().collect() == original_order
assert mt.key_rows_by().key_cols_by().entries().collect() == original_order
assert mt.key_rows_by().entries().collect() == sorted(original_order, key=lambda x: x.col_idx)
def test_filter_cols_required_entries(self):
mt1 = hl.utils.range_matrix_table(10, 10, n_partitions=4)
mt1 = mt1.filter_cols(mt1.col_idx < 3)
self.assertEqual(len(mt1.entries().collect()), 30)
def test_filter_cols_with_global_references(self):
mt = hl.utils.range_matrix_table(10, 10)
s = hl.literal({1, 3, 5, 7})
self.assertEqual(mt.filter_cols(s.contains(mt.col_idx)).count_cols(), 4)
def test_vcf_regression(self):
ds = hl.import_vcf(resource('33alleles.vcf'))
self.assertEqual(
ds.filter_rows(ds.alleles.length() == 2).count_rows(), 0)
def test_field_groups(self):
ds = self.get_vds()
df = ds.annotate_rows(row_struct=ds.row).rows()
self.assertTrue(df.all((df.info == df.row_struct.info) & (df.qual == df.row_struct.qual)))
ds2 = ds.add_col_index()
df = ds2.annotate_cols(col_struct=ds2.col).cols()
self.assertTrue(df.all((df.col_idx == df.col_struct.col_idx)))
df = ds.annotate_entries(entry_struct=ds.entry).entries()
self.assertTrue(df.all(
((hl.is_missing(df.GT) |
(df.GT == df.entry_struct.GT)) &
(df.AD == df.entry_struct.AD))))
def test_filter_partitions(self):
ds = self.get_vds(min_partitions=8)
self.assertEqual(ds.n_partitions(), 8)
self.assertEqual(ds._filter_partitions([0, 1, 4]).n_partitions(), 3)
self.assertEqual(ds._filter_partitions(range(3)).n_partitions(), 3)
self.assertEqual(ds._filter_partitions([4, 5, 7], keep=False).n_partitions(), 5)
self.assertTrue(
ds._same(hl.MatrixTable.union_rows(
ds._filter_partitions([0, 3, 7]),
ds._filter_partitions([0, 3, 7], keep=False))))
def test_from_rows_table(self):
mt = hl.import_vcf(resource('sample.vcf'))
mt = mt.annotate_globals(foo='bar')
rt = mt.rows()
rm = hl.MatrixTable.from_rows_table(rt)
self.assertTrue(rm._same(mt.filter_cols(False).select_entries().key_cols_by().select_cols()))
def test_sample_rows(self):
ds = self.get_vds()
ds_small = ds.sample_rows(0.01)
self.assertTrue(ds_small.count_rows() < ds.count_rows())
def test_read_stored_cols(self):
ds = self.get_vds()
ds = ds.annotate_globals(x='foo')
f = new_temp_file(suffix='vds')
ds.write(f)
t = hl.read_table(f + '/cols')
self.assertTrue(ds.cols()._same(t))
def test_read_stored_rows(self):
ds = self.get_vds()
ds = ds.annotate_globals(x='foo')
f = new_temp_file(suffix='vds')
ds.write(f)
t = hl.read_table(f + '/rows')
self.assertTrue(ds.rows()._same(t))
def test_read_stored_globals(self):
ds = self.get_vds()
ds = ds.annotate_globals(x=5, baz='foo')
f = new_temp_file(suffix='vds')
ds.write(f)
t = hl.read_table(f + '/globals')
self.assertTrue(ds.globals_table()._same(t))
def test_codecs_matrix(self):
from hail.utils.java import 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 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_fix3307_read_mt_wrong(self):
mt = hl.import_vcf(resource('sample2.vcf'))
mt = hl.split_multi_hts(mt)
mt.write('/tmp/foo.mt', overwrite=True)
mt2 = hl.read_matrix_table('/tmp/foo.mt')
t = hl.read_table('/tmp/foo.mt/rows')
self.assertTrue(mt.rows()._same(t))
self.assertTrue(mt2.rows()._same(t))
self.assertTrue(mt._same(mt2))
def test_rename(self):
dataset = self.get_vds()
renamed1 = dataset.rename({'locus': 'locus2', 'info': 'info2', 's': 'info'})
self.assertEqual(renamed1['locus2']._type, dataset['locus']._type)
self.assertEqual(renamed1['info2']._type, dataset['info']._type)
self.assertEqual(renamed1['info']._type, dataset['s']._type)
self.assertEqual(renamed1['info']._indices, renamed1._col_indices)
self.assertFalse('locus' in renamed1._fields)
self.assertFalse('s' in renamed1._fields)
with self.assertRaises(ValueError):
dataset.rename({'locus': 'info'})
with self.assertRaises(ValueError):
dataset.rename({'locus': 'a', 's': 'a'})
with self.assertRaises(LookupError):
dataset.rename({'foo': 'a'})
def test_range(self):
ds = hl.utils.range_matrix_table(100, 10)
self.assertEqual(ds.count_rows(), 100)
self.assertEqual(ds.count_cols(), 10)
et = ds.annotate_entries(entry_idx=10 * ds.row_idx + ds.col_idx).entries().add_index()
self.assertTrue(et.all(et.idx == et.entry_idx))
def test_filter_entries(self):
ds = hl.utils.range_matrix_table(100, 10)
ds = ds.annotate_rows(foo=5) # triggered a RV bug
ds = ds.annotate_cols(bar=5)
ds = ds.filter_entries((ds.col_idx * ds.row_idx) % 4 == 0)
entries = ds.entries()
self.assertTrue(entries.all((entries.col_idx * entries.row_idx) % 4 == 0))
def test_filter_na(self):
mt = hl.utils.range_matrix_table(1, 1)
self.assertEqual(mt.filter_rows(hl.null(hl.tbool)).count_rows(), 0)
self.assertEqual(mt.filter_cols(hl.null(hl.tbool)).count_cols(), 0)
self.assertEqual(mt.filter_entries(hl.null(hl.tbool)).entries().count(), 0)
def test_to_table_on_various_fields(self):
mt = hl.utils.range_matrix_table(3, 4)
sample_ids = ['Bob', 'Alice', 'David', 'Carol']
entries = [1, 0, 3, 2]
rows = ['1:3:A:G', '1:2:A:G', '1:0:A:G']
mt = mt.annotate_cols(s=hl.array(sample_ids)[mt.col_idx]).key_cols_by('s')
mt = mt.annotate_entries(e=hl.array(entries)[mt.col_idx])
mt = mt.annotate_rows(r=hl.array(rows)[mt.row_idx]).key_rows_by('r')
self.assertEqual(mt.s.collect(), sample_ids)
self.assertEqual(mt.s.take(1), [sample_ids[0]])
self.assertEqual(mt.e.collect(), entries * 3)
self.assertEqual(mt.e.take(1), [entries[0]])
self.assertEqual(mt.row_idx.collect(), [2, 1, 0])
self.assertEqual(mt.r.collect(), sorted(rows))
self.assertEqual(mt.r.take(1), [sorted(rows)[0]])
self.assertEqual(mt.cols().s.collect(), sorted(sample_ids))
self.assertEqual(mt.cols().s.take(1), [sorted(sample_ids)[0]])
self.assertEqual(mt.entries().e.collect(), sorted(entries) * 3)
self.assertEqual(mt.entries().e.take(1), [sorted(entries)[0]])
self.assertEqual(mt.rows().row_idx.collect(), [2, 1, 0])
self.assertEqual(mt.rows().r.collect(), sorted(rows))
self.assertEqual(mt.rows().r.take(1), [sorted(rows)[0]])
def test_order_by(self):
ht = hl.utils.range_table(10)
self.assertEqual(ht.order_by('idx').idx.collect(), list(range(10)))
self.assertEqual(ht.order_by(hl.asc('idx')).idx.collect(), list(range(10)))
self.assertEqual(ht.order_by(hl.desc('idx')).idx.collect(), list(range(10))[::-1])
def test_order_by_complex_exprs(self):
ht = hl.utils.range_table(10)
assert ht.order_by(-ht.idx).idx.collect() == list(range(10))[::-1]
def test_order_by_intervals(self):
intervals = {0: hl.Interval(0, 3, includes_start=True, includes_end=False),
1: hl.Interval(0, 4, includes_start=True, includes_end=True),
2: hl.Interval(1, 4, includes_start=True, includes_end=False),
3: hl.Interval(0, 4, includes_start=False, includes_end=False),
4: hl.Interval(0, 4, includes_start=True, includes_end=False)}
ht = hl.utils.range_table(5)
ht = ht.annotate_globals(ilist=intervals)
ht = ht.annotate(interval=ht['ilist'][ht['idx']])
ht = ht.order_by(ht['interval'])
ordered = ht['interval'].collect()
expected = [intervals[i] for i in [0, 4, 1, 3, 2]]
self.assertEqual(ordered, expected)
def test_range_matrix_table(self):
mt = hl.utils.range_matrix_table(13, 7, n_partitions=5)
self.assertEqual(mt.globals.dtype, hl.tstruct())
self.assertEqual(mt.row.dtype, hl.tstruct(row_idx=hl.tint32))
self.assertEqual(mt.col.dtype, hl.tstruct(col_idx=hl.tint32))
self.assertEqual(mt.entry.dtype, hl.tstruct())
self.assertEqual(list(mt.row_key), ['row_idx'])
self.assertEqual(list(mt.col_key), ['col_idx'])
self.assertEqual([r.row_idx for r in mt.rows().collect()], list(range(13)))
self.assertEqual([r.col_idx for r in mt.cols().collect()], list(range(7)))
def test_make_table(self):
mt = hl.utils.range_matrix_table(3, 2)
mt = mt.select_entries(x=mt.row_idx * mt.col_idx)
mt = mt.key_cols_by(col_idx=hl.str(mt.col_idx))
t = hl.Table.parallelize(
[{'row_idx': 0, '0.x': 0, '1.x': 0},
{'row_idx': 1, '0.x': 0, '1.x': 1},
{'row_idx': 2, '0.x': 0, '1.x': 2}],
hl.tstruct(**{'row_idx': hl.tint32, '0.x': hl.tint32, '1.x': hl.tint32}),
key='row_idx')
self.assertTrue(mt.make_table()._same(t))
def test_make_table_empty_entry_field(self):
mt = hl.utils.range_matrix_table(3, 2)
mt = mt.select_entries(**{'': mt.row_idx * mt.col_idx})
mt = mt.key_cols_by(col_idx=hl.str(mt.col_idx))
t = mt.make_table()
self.assertEqual(
t.row.dtype,
hl.tstruct(**{'row_idx': hl.tint32, '0': hl.tint32, '1': hl.tint32}))
def test_make_table_sep(self):
mt = hl.utils.range_matrix_table(3, 2)
mt = mt.select_entries(x=mt.row_idx * mt.col_idx)
mt = mt.key_cols_by(col_idx=hl.str(mt.col_idx))
t = mt.make_table()
assert list(t.row) == ['row_idx', '0.x', '1.x']
t = mt.make_table(separator='__')
assert list(t.row) == ['row_idx', '0__x', '1__x']
def test_make_table_row_equivalence(self):
mt = hl.utils.range_matrix_table(3, 3)
mt = mt.annotate_rows(r1 = hl.rand_norm(), r2 = hl.rand_norm())
mt = mt.annotate_entries(e1 = hl.rand_norm(), e2 = hl.rand_norm())
mt = mt.key_cols_by(col_idx=hl.str(mt.col_idx))
assert mt.make_table().select(*mt.row_value)._same(mt.rows())
def test_transmute(self):
mt = (
hl.utils.range_matrix_table(1, 1)
.annotate_globals(g1=0, g2=0)
.annotate_cols(c1=0, c2=0)
.annotate_rows(r1=0, r2=0)
.annotate_entries(e1=0, e2=0))
self.assertEqual(mt.transmute_globals(g3=mt.g2 + 1).globals.dtype, hl.tstruct(g1=hl.tint, g3=hl.tint))
self.assertEqual(mt.transmute_rows(r3=mt.r2 + 1).row_value.dtype, hl.tstruct(r1=hl.tint, r3=hl.tint))
self.assertEqual(mt.transmute_cols(c3=mt.c2 + 1).col_value.dtype, hl.tstruct(c1=hl.tint, c3=hl.tint))
self.assertEqual(mt.transmute_entries(e3=mt.e2 + 1).entry.dtype, hl.tstruct(e1=hl.tint, e3=hl.tint))
def test_transmute_agg(self):
mt = hl.utils.range_matrix_table(1, 1).annotate_entries(x=5)
mt = mt.transmute_rows(y = hl.agg.mean(mt.x))
def test_agg_explode(self):
t = hl.Table.parallelize([
hl.struct(a=[1, 2]),
hl.struct(a=hl.empty_array(hl.tint32)),
hl.struct(a=hl.null(hl.tarray(hl.tint32))),
hl.struct(a=[3]),
hl.struct(a=[hl.null(hl.tint32)])
])
self.assertCountEqual(t.aggregate(hl.agg.explode(lambda elt: hl.agg.collect(elt), t.a)),
[1, 2, None, 3])
def test_agg_call_stats(self):
t = hl.Table.parallelize([
hl.struct(c=hl.call(0, 0)),
hl.struct(c=hl.call(0, 1)),
hl.struct(c=hl.call(0, 2, phased=True)),
hl.struct(c=hl.call(1)),
hl.struct(c=hl.call(0)),
hl.struct(c=hl.call())
])
actual = t.aggregate(hl.agg.call_stats(t.c, ['A', 'T', 'G']))
expected = hl.struct(AC=[5, 2, 1],
AF=[5.0 / 8.0, 2.0 / 8.0, 1.0 / 8.0],
AN=8,
homozygote_count=[1, 0, 0])
self.assertTrue(hl.Table.parallelize([actual]),
hl.Table.parallelize([expected]))
def test_hardy_weinberg_test(self):
mt = hl.import_vcf(resource('HWE_test.vcf'))
mt = mt.select_rows(**hl.agg.hardy_weinberg_test(mt.GT))
rt = mt.rows()
expected = hl.Table.parallelize([
hl.struct(
locus=hl.locus('20', pos),
alleles=alleles,
het_freq_hwe=r,
p_value=p)
for (pos, alleles, r, p) in [
(1, ['A', 'G'], 0.0, 0.5),
(2, ['A', 'G'], 0.25, 0.5),
(3, ['T', 'C'], 0.5357142857142857, 0.21428571428571427),
(4, ['T', 'A'], 0.5714285714285714, 0.6571428571428573),
(5, ['G', 'A'], 0.3333333333333333, 0.5)]],
key=['locus', 'alleles'])
self.assertTrue(rt.filter(rt.locus.position != 6)._same(expected))
rt6 = rt.filter(rt.locus.position == 6).collect()[0]
self.assertEqual(rt6['p_value'], 0.5)
self.assertTrue(math.isnan(rt6['het_freq_hwe']))
def test_hw_func_and_agg_agree(self):
mt = hl.import_vcf(resource('sample.vcf'))
mt = mt.annotate_rows(
stats=hl.agg.call_stats(mt.GT, mt.alleles),
hw=hl.agg.hardy_weinberg_test(mt.GT))
mt = mt.annotate_rows(
hw2=hl.hardy_weinberg_test(mt.stats.homozygote_count[0],
mt.stats.AC[1] - 2 * mt.stats.homozygote_count[1],
mt.stats.homozygote_count[1]))
rt = mt.rows()
self.assertTrue(rt.all(rt.hw == rt.hw2))
def test_write_stage_locally(self):
mt = self.get_vds()
f = new_temp_file(suffix='mt')
mt.write(f, stage_locally=True)
mt2 = hl.read_matrix_table(f)
self.assertTrue(mt._same(mt2))
def test_nulls_in_distinct_joins(self):
# MatrixAnnotateRowsTable uses left distinct join
mr = hl.utils.range_matrix_table(7, 3, 4)
matrix1 = mr.key_rows_by(new_key=hl.cond((mr.row_idx == 3) | (mr.row_idx == 5),
hl.null(hl.tint32), mr.row_idx))
matrix2 = mr.key_rows_by(new_key=hl.cond((mr.row_idx == 4) | (mr.row_idx == 6),
hl.null(hl.tint32), mr.row_idx))
joined = matrix1.select_rows(idx1=matrix1.row_idx,
idx2=matrix2.rows()[matrix1.new_key].row_idx)
def row(new_key, idx1, idx2):
return hl.Struct(new_key=new_key, idx1=idx1, idx2=idx2)
expected = [row(0, 0, 0),
row(1, 1, 1),
row(2, 2, 2),
row(4, 4, None),
row(6, 6, None),
row(None, 3, None),
row(None, 5, None)]
self.assertEqual(joined.rows().collect(), expected)
# union_cols uses inner distinct join
matrix1 = matrix1.annotate_entries(ridx=matrix1.row_idx,
cidx=matrix1.col_idx)
matrix2 = matrix2.annotate_entries(ridx=matrix2.row_idx,
cidx=matrix2.col_idx)