def test_agg_cols_explode(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [(agg.explode(
lambda elt: agg.collect(elt + 1).append(0),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32))), [9, 10, 10, 11, 0]),
(agg.explode(
lambda elt: agg.explode(
lambda elt2: agg.collect(elt2 + 1).append(0),
[elt, elt + 1]),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32))),
[9, 10, 10, 11, 10, 11, 11, 12, 0]),
(agg.explode(
lambda elt: agg.filter(elt > 8,
agg.collect(elt + 1).append(0)),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32))), [10, 10, 11, 0]),
(agg.explode(
lambda elt: agg.group_by(elt % 3,
agg.collect(elt + 1).append(0)),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32))), {
0: [10, 10, 0],
1: [11, 0],
2: [9, 0]
})]
for aggregation, expected in tests:
self.assertEqual(
t.select_rows(result=aggregation).result.collect()[0],
expected)
def test_agg_cols_group_by(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [
(agg.group_by(
t.col_idx % 2,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0)), {
0: [1, 3, 5, 7, 9, 0],
1: [2, 4, 6, 8, 10, 0]
}),
(agg.group_by(
t.col_idx % 3,
agg.filter(
t.col_idx > 7,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0))), {
0: [10, 0],
1: [0],
2: [9, 0]
}),
(agg.group_by(
t.col_idx % 3,
agg.explode(
lambda elt: agg.collect(elt + 1).append(0),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32)))), {
0: [10, 11, 0],
1: [0],
2: [9, 10, 0]
}),
]
for aggregation, expected in tests:
self.assertEqual(
t.select_rows(result=aggregation).result.collect()[0],
expected)
def test_aggregate2(self):
schema = hl.tstruct(status=hl.tint32, GT=hl.tcall, qPheno=hl.tint32)
rows = [{'status': 0, 'GT': hl.Call([0, 0]), 'qPheno': 3},
{'status': 0, 'GT': hl.Call([0, 1]), 'qPheno': 13}]
kt = hl.Table.parallelize(rows, schema)
result = convert_struct_to_dict(
kt.group_by(status=kt.status)
.aggregate(
x1=agg.collect(kt.qPheno * 2),
x2=agg.explode(lambda elt: agg.collect(elt), [kt.qPheno, kt.qPheno + 1]),
x3=agg.min(kt.qPheno),
x4=agg.max(kt.qPheno),
x5=agg.sum(kt.qPheno),
x6=agg.product(hl.int64(kt.qPheno)),
x7=agg.count(),
x8=agg.count_where(kt.qPheno == 3),
x9=agg.fraction(kt.qPheno == 1),
x10=agg.stats(hl.float64(kt.qPheno)),
x11=agg.hardy_weinberg_test(kt.GT),
x13=agg.inbreeding(kt.GT, 0.1),
x14=agg.call_stats(kt.GT, ["A", "T"]),
x15=agg.collect(hl.Struct(a=5, b="foo", c=hl.Struct(banana='apple')))[0],
x16=agg.collect(hl.Struct(a=5, b="foo", c=hl.Struct(banana='apple')).c.banana)[0],
x17=agg.explode(lambda elt: agg.collect(elt), hl.null(hl.tarray(hl.tint32))),
x18=agg.explode(lambda elt: agg.collect(elt), hl.null(hl.tset(hl.tint32))),
x19=agg.take(kt.GT, 1, ordering=-kt.qPheno)
).take(1)[0])
expected = {u'status': 0,
u'x13': {u'n_called': 2, u'expected_homs': 1.64, u'f_stat': -1.777777777777777,
u'observed_homs': 1},
u'x14': {u'AC': [3, 1], u'AF': [0.75, 0.25], u'AN': 4, u'homozygote_count': [1, 0]},
u'x15': {u'a': 5, u'c': {u'banana': u'apple'}, u'b': u'foo'},
u'x10': {u'min': 3.0, u'max': 13.0, u'sum': 16.0, u'stdev': 5.0, u'n': 2, u'mean': 8.0},
u'x8': 1, u'x9': 0.0, u'x16': u'apple',
u'x11': {u'het_freq_hwe': 0.5, u'p_value': 0.5},
u'x2': [3, 4, 13, 14], u'x3': 3, u'x1': [6, 26], u'x6': 39, u'x7': 2, u'x4': 13, u'x5': 16,
u'x17': [],
u'x18': [],
u'x19': [hl.Call([0, 1])]}
self.maxDiff = None
self.assertDictEqual(result, expected)
def test_aggregate2(self):
schema = hl.tstruct(status=hl.tint32, GT=hl.tcall, qPheno=hl.tint32)
rows = [{'status': 0, 'GT': hl.Call([0, 0]), 'qPheno': 3},
{'status': 0, 'GT': hl.Call([0, 1]), 'qPheno': 13}]
kt = hl.Table.parallelize(rows, schema)
result = convert_struct_to_dict(
kt.group_by(status=kt.status)
.aggregate(
x1=agg.collect(kt.qPheno * 2),
x2=agg.explode(lambda elt: agg.collect(elt), [kt.qPheno, kt.qPheno + 1]),
x3=agg.min(kt.qPheno),
x4=agg.max(kt.qPheno),
x5=agg.sum(kt.qPheno),
x6=agg.product(hl.int64(kt.qPheno)),
x7=agg.count(),
x8=agg.count_where(kt.qPheno == 3),
x9=agg.fraction(kt.qPheno == 1),
x10=agg.stats(hl.float64(kt.qPheno)),
x11=agg.hardy_weinberg_test(kt.GT),
x13=agg.inbreeding(kt.GT, 0.1),
x14=agg.call_stats(kt.GT, ["A", "T"]),
x15=agg.collect(hl.Struct(a=5, b="foo", c=hl.Struct(banana='apple')))[0],
x16=agg.collect(hl.Struct(a=5, b="foo", c=hl.Struct(banana='apple')).c.banana)[0],
x17=agg.explode(lambda elt: agg.collect(elt), hl.null(hl.tarray(hl.tint32))),
x18=agg.explode(lambda elt: agg.collect(elt), hl.null(hl.tset(hl.tint32))),
x19=agg.take(kt.GT, 1, ordering=-kt.qPheno)
).take(1)[0])
expected = {u'status': 0,
u'x13': {u'n_called': 2, u'expected_homs': 1.64, u'f_stat': -1.777777777777777,
u'observed_homs': 1},
u'x14': {u'AC': [3, 1], u'AF': [0.75, 0.25], u'AN': 4, u'homozygote_count': [1, 0]},
u'x15': {u'a': 5, u'c': {u'banana': u'apple'}, u'b': u'foo'},
u'x10': {u'min': 3.0, u'max': 13.0, u'sum': 16.0, u'stdev': 5.0, u'n': 2, u'mean': 8.0},
u'x8': 1, u'x9': 0.0, u'x16': u'apple',
u'x11': {u'het_freq_hwe': 0.5, u'p_value': 0.5},
u'x2': [3, 4, 13, 14], u'x3': 3, u'x1': [6, 26], u'x6': 39, u'x7': 2, u'x4': 13, u'x5': 16,
u'x17': [],
u'x18': [],
u'x19': [hl.Call([0, 1])]}
self.maxDiff = None
self.assertDictEqual(result, expected)
def test_agg_cols_explode(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [(agg.explode(lambda elt: agg.collect(elt + 1).append(0),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1], hl.empty_array(hl.tint32))),
[9, 10, 10, 11, 0]),
(agg.explode(lambda elt: agg.explode(lambda elt2: agg.collect(elt2 + 1).append(0),
[elt, elt + 1]),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1], hl.empty_array(hl.tint32))),
[9, 10, 10, 11, 10, 11, 11, 12, 0]),
(agg.explode(lambda elt: agg.filter(elt > 8,
agg.collect(elt + 1).append(0)),
hl.cond(t.col_idx > 7, [t.col_idx, t.col_idx + 1], hl.empty_array(hl.tint32))),
[10, 10, 11, 0]),
(agg.explode(lambda elt: agg.group_by(elt % 3,
agg.collect(elt + 1).append(0)),
hl.cond(t.col_idx > 7,
[t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32))),
{0: [10, 10, 0], 1: [11, 0], 2:[9, 0]})
]
for aggregation, expected in tests:
self.assertEqual(t.select_rows(result = aggregation).result.collect()[0], expected)
def test_agg_cols_filter(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [(agg.filter(t.col_idx > 7,
agg.collect(t.col_idx + 1).append(0)),
[9, 10, 0]),
(agg.filter(t.col_idx > 7,
agg.explode(lambda elt: agg.collect(elt + 1).append(0),
[t.col_idx, t.col_idx + 1])),
[9, 10, 10, 11, 0]),
(agg.filter(t.col_idx > 7,
agg.group_by(t.col_idx % 3,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0))),
{0: [10, 0], 2: [9, 0]})
]
for aggregation, expected in tests:
self.assertEqual(t.select_rows(result = aggregation).result.collect()[0], expected)
def test_agg_cols_filter(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [(agg.filter(t.col_idx > 7,
agg.collect(t.col_idx + 1).append(0)),
[9, 10, 0]),
(agg.filter(t.col_idx > 7,
agg.explode(lambda elt: agg.collect(elt + 1).append(0),
[t.col_idx, t.col_idx + 1])),
[9, 10, 10, 11, 0]),
(agg.filter(t.col_idx > 7,
agg.group_by(t.col_idx % 3,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0))),
{0: [10, 0], 2: [9, 0]})
]
for aggregation, expected in tests:
self.assertEqual(t.select_rows(result = aggregation).result.collect()[0], expected)
def test_aggregate1(self):
schema = hl.tstruct(a=hl.tint32,
b=hl.tint32,
c=hl.tint32,
d=hl.tint32,
e=hl.tstr,
f=hl.tarray(hl.tint32))
rows = [{
'a': 4,
'b': 1,
'c': 3,
'd': 5,
'e': "hello",
'f': [1, 2, 3]
}, {
'a': 0,
'b': 5,
'c': 13,
'd': -1,
'e': "cat",
'f': []
}, {
'a': 4,
'b': 2,
'c': 20,
'd': 3,
'e': "dog",
'f': [5, 6, 7]
}]
kt = hl.Table.parallelize(rows, schema)
results = kt.aggregate(
hl.Struct(q1=agg.sum(kt.b),
q2=agg.count(),
q3=agg.collect(kt.e),
q4=agg.filter((kt.d >= 5) | (kt.a == 0),
agg.collect(kt.e)),
q5=agg.explode(lambda elt: agg.mean(elt), kt.f)))
self.assertEqual(results.q1, 8)
self.assertEqual(results.q2, 3)
self.assertEqual(set(results.q3), {"hello", "cat", "dog"})
self.assertEqual(set(results.q4), {"hello", "cat"})
self.assertAlmostEqual(results.q5, 4)
def test_agg_cols_group_by(self):
t = hl.utils.range_matrix_table(1, 10)
tests = [(agg.group_by(t.col_idx % 2,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0)),
{0: [1, 3, 5, 7, 9, 0], 1: [2, 4, 6, 8, 10, 0]}),
(agg.group_by(t.col_idx % 3,
agg.filter(t.col_idx > 7,
hl.array(agg.collect_as_set(t.col_idx + 1)).append(0))),
{0: [10, 0], 1: [0], 2: [9, 0]}),
(agg.group_by(t.col_idx % 3,
agg.explode(lambda elt: agg.collect(elt + 1).append(0),
hl.cond(t.col_idx > 7,
[t.col_idx, t.col_idx + 1],
hl.empty_array(hl.tint32)))),
{0: [10, 11, 0], 1: [0], 2:[9, 10, 0]}),
]
for aggregation, expected in tests:
self.assertEqual(t.select_rows(result = aggregation).result.collect()[0], expected)
def test_aggregate1(self):
schema = hl.tstruct(a=hl.tint32, b=hl.tint32, c=hl.tint32, d=hl.tint32, e=hl.tstr, f=hl.tarray(hl.tint32))
rows = [{'a': 4, 'b': 1, 'c': 3, 'd': 5, 'e': "hello", 'f': [1, 2, 3]},
{'a': 0, 'b': 5, 'c': 13, 'd': -1, 'e': "cat", 'f': []},
{'a': 4, 'b': 2, 'c': 20, 'd': 3, 'e': "dog", 'f': [5, 6, 7]}]
kt = hl.Table.parallelize(rows, schema)
results = kt.aggregate(hl.Struct(q1=agg.sum(kt.b),
q2=agg.count(),
q3=agg.collect(kt.e),
q4=agg.filter((kt.d >= 5) | (kt.a == 0), agg.collect(kt.e)),
q5=agg.explode(lambda elt: agg.mean(elt), kt.f)))
self.assertEqual(results.q1, 8)
self.assertEqual(results.q2, 3)
self.assertEqual(set(results.q3), {"hello", "cat", "dog"})
self.assertEqual(set(results.q4), {"hello", "cat"})
self.assertAlmostEqual(results.q5, 4)
