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all.py
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all.py
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# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import pandas as pd
from ... import opcodes as OperandDef
from ...config import options
from ...core import OutputType
from .core import (
DataFrameReductionOperand,
DataFrameReductionMixin,
recursive_tile,
DATAFRAME_TYPE,
)
class DataFrameAll(DataFrameReductionOperand, DataFrameReductionMixin):
_op_type_ = OperandDef.ALL
_func_name = "all"
@property
def is_atomic(self):
return True
@classmethod
def tile(cls, op):
in_df = op.inputs[0]
out_df = op.outputs[0]
if op.axis is None and isinstance(in_df, DATAFRAME_TYPE):
dtypes = pd.Series([out_df.dtype])
index = in_df.dtypes.index
out_df = yield from recursive_tile(
in_df.agg(
cls.get_reduction_callable(op),
axis=0,
_numeric_only=op.numeric_only,
_bool_only=op.bool_only,
_combine_size=op.combine_size,
_output_type=OutputType.series,
_dtypes=dtypes,
_index=index,
)
)
out_df = yield from recursive_tile(
out_df.agg(
cls.get_reduction_callable(op),
axis=0,
_numeric_only=op.numeric_only,
_bool_only=op.bool_only,
_combine_size=op.combine_size,
_output_type=OutputType.scalar,
_dtypes=out_df.dtype,
_index=None,
)
)
return [out_df]
else:
return (yield from super().tile(op))
def __call__(self, df):
if self.axis is None and isinstance(df, DATAFRAME_TYPE):
return self.new_scalar([df], np.dtype("bool"))
else:
return super().__call__(df)
def all_series(
series,
axis=0,
bool_only=None,
skipna=True,
level=None,
combine_size=None,
method=None,
):
use_inf_as_na = options.dataframe.mode.use_inf_as_na
op = DataFrameAll(
axis=axis,
skipna=skipna,
level=level,
bool_only=bool_only,
combine_size=combine_size,
output_types=[OutputType.scalar],
use_inf_as_na=use_inf_as_na,
method=method,
)
return op(series)
def all_dataframe(
df,
axis=0,
bool_only=None,
skipna=True,
level=None,
combine_size=None,
method=None,
):
use_inf_as_na = options.dataframe.mode.use_inf_as_na
output_types = [OutputType.series] if axis is not None else [OutputType.scalar]
op = DataFrameAll(
axis=axis,
skipna=skipna,
level=level,
bool_only=bool_only,
combine_size=combine_size,
output_types=output_types,
use_inf_as_na=use_inf_as_na,
method=method,
)
return op(df)
def all_index(idx):
use_inf_as_na = options.dataframe.mode.use_inf_as_na
op = DataFrameAll(output_types=[OutputType.scalar], use_inf_as_na=use_inf_as_na)
return op(idx)