def test_min_max():
# An example generated function wrapper with possible options
data = [4, 5, 6, None, 1]
s = pc.min_max(data)
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.MinMaxOptions())
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.MinMaxOptions(null_handling='skip'))
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.MinMaxOptions(null_handling='emit_null'))
assert s.as_py() == {'min': None, 'max': None}
# Options as dict of kwargs
s = pc.min_max(data, options={'null_handling': 'emit_null'})
assert s.as_py() == {'min': None, 'max': None}
# Options as named functions arguments
s = pc.min_max(data, null_handling='emit_null')
assert s.as_py() == {'min': None, 'max': None}
# Both options and named arguments
with pytest.raises(TypeError):
s = pc.min_max(data,
options=pc.MinMaxOptions(),
null_handling='emit_null')
# Wrong options type
options = pc.TakeOptions()
with pytest.raises(TypeError):
s = pc.min_max(data, options=options)
# Missing argument
with pytest.raises(
TypeError,
match=r"min_max\(\) missing 1 required positional argument"):
s = pc.min_max()
def test_min_max():
# An example generated function wrapper with possible options
data = [4, 5, 6, None, 1]
s = pc.min_max(data)
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions())
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions(skip_nulls=True))
assert s.as_py() == {'min': 1, 'max': 6}
s = pc.min_max(data, options=pc.ScalarAggregateOptions(skip_nulls=False))
assert s.as_py() == {'min': None, 'max': None}
# Options as dict of kwargs
s = pc.min_max(data, options={'skip_nulls': False})
assert s.as_py() == {'min': None, 'max': None}
# Options as named functions arguments
s = pc.min_max(data, skip_nulls=False)
assert s.as_py() == {'min': None, 'max': None}
# Both options and named arguments
with pytest.raises(TypeError):
s = pc.min_max(data,
options=pc.ScalarAggregateOptions(),
skip_nulls=False)
# Wrong options type
options = pc.TakeOptions()
with pytest.raises(TypeError):
s = pc.min_max(data, options=options)
# Missing argument
with pytest.raises(
TypeError,
match=r"min_max\(\) missing 1 required positional argument"):
s = pc.min_max()
def find_min_max_for_numeric_table_columns(
table: pa.Table, ) -> Dict[str, dict]:
"""Determine per-vector min/max values and return as dictionary indexed by vector name"""
ret_dict = {}
for field in table.schema:
if pa.types.is_floating(field.type):
# pylint: disable=no-member
minmax = pc.min_max(table[field.name])
ret_dict[field.name] = {
"min": minmax.get("min").as_py(),
"max": minmax.get("max").as_py(),
}
return ret_dict
def update(self, arr):
self.mean = float(c.mean(arr).as_py())
minmax = c.min_max(arr)
self.min, self.max = float(minmax['min'].as_py()), float(
minmax['max'].as_py())