projektAI/venv/Lib/site-packages/mlxtend/preprocessing/copy_transformer.py

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2021-06-06 22:13:05 +02:00
# Sebastian Raschka 2014-2020
# mlxtend Machine Learning Library Extensions
#
# A Class that returns a copy of a dataset in a scikit-learn pipeline.
# Author: Sebastian Raschka <sebastianraschka.com>
#
# License: BSD 3 clause
import numpy as np
from sklearn.base import BaseEstimator
from scipy.sparse import issparse
class CopyTransformer(BaseEstimator):
"""Transformer that returns a copy of the input array
For usage examples, please see
http://rasbt.github.io/mlxtend/user_guide/preprocessing/CopyTransformer/
"""
def __init__(self):
pass
def transform(self, X, y=None):
""" Return a copy of the input array.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape = [n_samples] (default: None)
Returns
---------
X_copy : copy of the input X array.
"""
if isinstance(X, list):
return np.asarray(X)
elif isinstance(X, np.ndarray) or issparse(X):
return X.copy()
else:
raise ValueError('X must be a list or NumPy array'
' or SciPy sparse array. Found %s'
% type(X))
def fit_transform(self, X, y=None):
""" Return a copy of the input array.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape = [n_samples] (default: None)
Returns
---------
X_copy : copy of the input X array.
"""
return self.transform(X)
def fit(self, X, y=None):
""" Mock method. Does nothing.
Parameters
----------
X : {array-like, sparse matrix}, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples and
n_features is the number of features.
y : array-like, shape = [n_samples] (default: None)
Returns
---------
self
"""
return self