def test_int_index(self):
from pandas.core.series import Series
arr = np.random.randn(100, 4)
result = lib.reduce(arr, np.sum, labels=Index(np.arange(4)))
expected = arr.sum(0)
assert_almost_equal(result, expected)
result = lib.reduce(arr, np.sum, axis=1, labels=Index(np.arange(100)))
expected = arr.sum(1)
assert_almost_equal(result, expected)
dummy = Series(0., index=np.arange(100))
result = lib.reduce(arr, np.sum, dummy=dummy,
labels=Index(np.arange(4)))
expected = arr.sum(0)
assert_almost_equal(result, expected)
dummy = Series(0., index=np.arange(4))
result = lib.reduce(arr, np.sum, axis=1, dummy=dummy,
labels=Index(np.arange(100)))
expected = arr.sum(1)
assert_almost_equal(result, expected)
result = lib.reduce(arr, np.sum, axis=1, dummy=dummy,
labels=Index(np.arange(100)))
assert_almost_equal(result, expected)
def test_int_index(self):
from pandas.core.series import Series
arr = np.random.randn(100, 4)
result = lib.reduce(arr, np.sum, labels=Index(np.arange(4)))
expected = arr.sum(0)
assert_almost_equal(result, expected)
result = lib.reduce(arr, np.sum, axis=1, labels=Index(np.arange(100)))
expected = arr.sum(1)
assert_almost_equal(result, expected)
dummy = Series(0., index=np.arange(100))
result = lib.reduce(arr, np.sum, dummy=dummy,
labels=Index(np.arange(4)))
expected = arr.sum(0)
assert_almost_equal(result, expected)
dummy = Series(0., index=np.arange(4))
result = lib.reduce(arr, np.sum, axis=1, dummy=dummy,
labels=Index(np.arange(100)))
expected = arr.sum(1)
assert_almost_equal(result, expected)
result = lib.reduce(arr, np.sum, axis=1, dummy=dummy,
labels=Index(np.arange(100)))
assert_almost_equal(result, expected)
def apply_raw(self):
try:
result = lib.reduce(self.values, self.f, axis=self.axis)
except Exception:
result = np.apply_along_axis(self.f, self.axis, self.values)
# TODO: mixed type case
from pandas import DataFrame, Series
if result.ndim == 2:
return DataFrame(result, index=self.index, columns=self.columns)
else:
return Series(result, index=self.agg_axis)
def apply_raw(self):
try:
result = lib.reduce(self.values, self.f, axis=self.axis)
except Exception:
result = np.apply_along_axis(self.f, self.axis, self.values)
# TODO: mixed type case
from pandas import DataFrame, Series
if result.ndim == 2:
return DataFrame(result, index=self.index, columns=self.columns)
else:
return Series(result, index=self.agg_axis)
def apply_standard(self):
from pandas import Series
reduce = self.reduce
if reduce is None:
reduce = True
# try to reduce first (by default)
# this only matters if the reduction in values is of different dtype
# e.g. if we want to apply to a SparseFrame, then can't directly reduce
if reduce:
values = self.values
# we cannot reduce using non-numpy dtypes,
# as demonstrated in gh-12244
if not is_extension_type(values):
# Create a dummy Series from an empty array
index = self.obj._get_axis(self.axis)
empty_arr = np.empty(len(index), dtype=values.dtype)
dummy = Series(empty_arr, index=index, dtype=values.dtype)
try:
labels = self.agg_axis
result = lib.reduce(values,
self.f,
axis=self.axis,
dummy=dummy,
labels=labels)
return Series(result, index=labels)
except Exception:
pass
# compute the result using the series generator
results, res_index, res_columns = self._apply_series_generator()
# wrap results
return self.wrap_results(results, res_index, res_columns)
def apply_standard(self):
from pandas import Series
reduce = self.reduce
if reduce is None:
reduce = True
# try to reduce first (by default)
# this only matters if the reduction in values is of different dtype
# e.g. if we want to apply to a SparseFrame, then can't directly reduce
if reduce:
values = self.values
# we cannot reduce using non-numpy dtypes,
# as demonstrated in gh-12244
if not is_extension_type(values):
# Create a dummy Series from an empty array
index = self.obj._get_axis(self.axis)
empty_arr = np.empty(len(index), dtype=values.dtype)
dummy = Series(empty_arr, index=index, dtype=values.dtype)
try:
labels = self.agg_axis
result = lib.reduce(values, self.f,
axis=self.axis,
dummy=dummy,
labels=labels)
return Series(result, index=labels)
except Exception:
pass
# compute the result using the series generator
results, res_index, res_columns = self._apply_series_generator()
# wrap results
return self.wrap_results(results, res_index, res_columns)