# Copyright 2019 IBM 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 sklearn.preprocessing
import lale.docstrings
import lale.operators

class PolynomialFeaturesImpl():
    def __init__(self, **hyperparams):
        self._hyperparams = hyperparams
        self._wrapped_model = sklearn.preprocessing.PolynomialFeatures(**self._hyperparams)

    def fit(self, X, y=None):
        self._wrapped_model.fit(X, y)
        return self

    def transform(self, X):
        return self._wrapped_model.transform(X)

_hyperparams_schema = {
    'description': 'Generate polynomial and interaction features.',
    'allOf': [{
        'type': 'object',
        'required': ['include_bias'],
        'relevantToOptimizer': ['degree', 'interaction_only','include_bias'],
        'additionalProperties': False,
        'properties': {
            'degree': {
                'type': 'integer',
                'minimumForOptimizer': 2,
                'maximumForOptimizer': 3,
                'default': 2,
                'description': 'The degree of the polynomial features. Default = 2.'},
            'interaction_only': {
                'type': 'boolean',
                'default': False,
                'description': 'If true, only interaction features are produced: features that are'},
            'include_bias': {
                'type': 'boolean',
                'default': True,
                'description': 'If True (default), then include a bias column, the feature in which'},
        }}],
}

_input_fit_schema = {
    'description': 'Compute number of output features.',
    'type': 'object',
    'required': ['X'],
    'properties': {
        'X': {
            'type': 'array',
            'items': {
                'type': 'array',
                'items': {
                    'type': 'number'},
            },
            'description': 'The data.'},
        'y': {}}}
_input_transform_schema = {
    'description': 'Transform data to polynomial features',
    'type': 'object',
    'required': ['X'],
    'properties': {
        'X': {
            'type': 'array',
            'items': {
                'type': 'array',
                'items': {
                    'type': 'number'},
            },
            'description': 'The data to transform, row by row.'},
    },
}
_output_transform_schema = {
    'description': 'The matrix of features, where NP is the number of polynomial',
    'type': 'array',
    'items': {
        'type': 'array',
        'items': {'type': 'number'}}}

_combined_schemas = {
    '$schema': 'http://json-schema.org/draft-04/schema#',
    'description': """`Polynomial features`_ transformer from scikit-learn.

.. _`Polynomial features`: https://scikit-learn.org/0.20/modules/generated/sklearn.preprocessing.PolynomialFeatures.html#sklearn-preprocessing-polynomialfeatures
""",
    'documentation_url': 'https://lale.readthedocs.io/en/latest/modules/lale.lib.sklearn.polynomial_features.html',
    'import_from': 'sklearn.preprocessing',
    'type': 'object',
    'tags': {
        'pre': [],
        'op': ['transformer'],
        'post': []},
    'properties': {
        'hyperparams': _hyperparams_schema,
        'input_fit': _input_fit_schema,
        'input_transform': _input_transform_schema,
        'output_transform': _output_transform_schema}}

PolynomialFeatures : lale.operators.IndividualOp
PolynomialFeatures = lale.operators.make_operator(PolynomialFeaturesImpl, _combined_schemas)

if sklearn.__version__ >= '0.21':
    # old: https://scikit-learn.org/0.20/modules/generated/sklearn.preprocessing.PolynomialFeatures.html
    # new: https://scikit-learn.org/0.23/modules/generated/sklearn.preprocessing.PolynomialFeatures.html
    from lale.schemas import Enum
    PolynomialFeatures = PolynomialFeatures.customize_schema(
        order=Enum(
            values=['C', 'F'],
            desc="Order of output array in the dense case. 'F' order is faster to compute, but may slow down subsequent estimators.",
            default='C'))

lale.docstrings.set_docstrings(PolynomialFeaturesImpl, PolynomialFeatures._schemas)