Source code for nvtabular.ops.logop

#
# Copyright (c) 2021, NVIDIA CORPORATION.
#
# 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

from nvtabular.dispatch import (
    DataFrameType,
    _encode_list_column,
    _flatten_list_column_values,
    _is_list_dtype,
    annotate,
)

from ..tags import Tags
from .operator import ColumnSelector, Operator


class LogOp(Operator):
    """
    This operator calculates the log of continuous columns. Note that
    to handle the common case of zerofilling null values, this
    calculates ``log(1+x)`` instead of just ``log(x)``.

    Example usage::

        # Use LogOp to define NVTabular workflow
        cont_features = cont_names >> nvt.ops.LogOp() >> ...
        processor = nvt.Workflow(cont_features)
    """

    @annotate("LogOp_op", color="darkgreen", domain="nvt_python")
    def transform(self, col_selector: ColumnSelector, df: DataFrameType) -> DataFrameType:
        for name in col_selector.names:
            column = df[name]
            if _is_list_dtype(column):
                transformed = np.log(_flatten_list_column_values(column).astype(np.float32) + 1)
                df[name] = _encode_list_column(column, transformed)
            else:
                df[name] = np.log(column.astype(np.float32) + 1)
        return df

    def output_tags(self):
        return [Tags.CONTINUOUS]

    def output_dtype(self):
        return np.float

    transform.__doc__ = Operator.transform.__doc__