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# Copyright (C) 2023-present The Project Contributors
#
# 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.
from typing import List
from typing import Optional
import pandas as pd
from sklearn.metrics import confusion_matrix
class MatrixUtil:
@staticmethod
def create_confusion_matrix(data: pd.DataFrame, true_column_name: str, predicted_column_name: str) -> pd.DataFrame:
categories = data[true_column_name].unique().tolist()
data_confusion_matrix = confusion_matrix(
y_true=data[true_column_name], y_pred=data[predicted_column_name], labels=categories
)
result = pd.DataFrame(data_confusion_matrix, index=categories, columns=categories)
return result
@staticmethod
def convert_confusion_matrix_to_percent(data: pd.DataFrame) -> pd.DataFrame:
# convert to percents row-wise
result = data / data.values.sum(axis=1) * 100
return result
@staticmethod
def create_confusion_matrix_labels(data: pd.DataFrame, in_percent: Optional[bool] = False) -> List[List[str]]:
# str of each non-zero element of data for annotations
if in_percent:
data_percent = data.values / data.values.sum(axis=1) * 100
annotation_text = [[f"{y:.2f}%" if y != 0 else "" for y in x] for x in data_percent]
else:
annotation_text = [[str(y) if y != 0 else "" for y in x] for x in data.values]
return annotation_text
