# -*- coding: utf-8 -*-
#!/usr/bin/env python
#
# Copyright 2015-2021 BigML
#
# 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.


""" Testing Multi-label predictions

"""



from bigmler.tests.world import (world, common_setup_module,
                                 common_teardown_module, teardown_class)

import bigmler.tests.basic_tst_prediction_steps as test_pred
import bigmler.tests.ml_tst_prediction_steps as ml_pred
import bigmler.tests.ml_tst_evaluation_steps as ml_eval
import bigmler.tests.evaluation_steps as evaluation



def setup_module():
    """Setup for the module

    """
    common_setup_module()
    test = TestML()
    test.setup_scenario1()


def teardown_module():
    """Teardown for the module

    """
    common_teardown_module()

class TestML(object):

    def teardown(self):
        """Calling generic teardown for every method

        """
        print("\nEnd of tests in: %s\n-------------------\n" % __name__)
        teardown_class()

    def setup(self):
        """
            Debug information
        """
        print("\n-------------------\nTests in: %s\n" % __name__)

    def setup_scenario1(self):
        """
            Scenario: Successfully building multi-label test predictions from start:
                Given I create BigML multi-label resources tagged as "<tag>" with "<label_separator>" label separator and <number_of_labels> labels uploading train "<data>" file with "<training_separator>" field separator to test "<test>" and log predictions in "<output>"
                And I check that the source has been created
                And I check that the dataset has been created
                And I check that the models have been created
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |tag |label_separator |number_of_labels | data                   |training_separator | test                        | output                          |predictions_file           |
                |my_multilabel_1|:|7| ../data/multilabel.csv |,| ../data/test_multilabel.csv | ./scenario_ml_1/predictions.csv | ./check_files/predictions_ml.csv |
        """
        print(self.setup_scenario1.__doc__)
        examples = [
            ['my_multilabel_1', ':', '7', 'data/multilabel.csv', ',', 'data/test_multilabel.csv', 'scenario_ml_1/predictions.csv', 'check_files/predictions_ml.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            ml_pred.i_create_all_ml_resources(self, tag=example[0], label_separator=example[1], number_of_labels=example[2], data=example[3], training_separator=example[4], test=example[5], output=example[6])
            test_pred.i_check_create_source(self)
            test_pred.i_check_create_dataset(self)
            test_pred.i_check_create_models(self)
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[7])

    def test_scenario2(self):
        """
            Scenario: Successfully building test predictions from source
                Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
                And I create BigML multi-label resources using source to test "<test>" and log predictions in "<output>"
                And I check that the dataset has been created
                And I check that the models have been created
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |scenario    | kwargs                                                  | test                    | output                        |predictions_file           |
                | scenario_ml_1| {"tag": "my_multilabel_1", "data": "../data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "./scenario_ml_1/predictions.csv", "test": "../data/test_multilabel.csv"}   | ../data/test_multilabel.csv   | ./scenario_ml_2/predictions.csv   | ./check_files/predictions_ml_comma.csv   |
        """
        print(self.test_scenario2.__doc__)
        examples = [
            ['scenario_ml_1', '{"tag": "my_multilabel_1", "data": "data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "scenario_ml_1/predictions.csv", "test": "data/test_multilabel.csv"}', 'data/test_multilabel.csv', 'scenario_ml_2/predictions.csv', 'check_files/predictions_ml_comma.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            test_pred.i_create_resources_from_source(self, multi_label='multi-label', test=example[2], output=example[3])
            test_pred.i_check_create_dataset(self)
            test_pred.i_check_create_models(self)
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[4])

    def test_scenario3(self):
        """
            Scenario: Successfully building test predictions from dataset
                Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
                And I create BigML multi-label resources using dataset to test "<test>" and log predictions in "<output>"
                And I check that the models have been created
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |scenario    | kwargs                                                  | test                    | output                        |predictions_file           |
                | scenario_ml_1| {"tag": "my_multilabel_1", "data": "../data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "./scenario_ml_1/predictions.csv", "test": "../data/test_multilabel.csv"}    | ../data/test_multilabel.csv   | ./scenario_ml_3/predictions.csv   | ./check_files/predictions_ml_comma.csv   |

        """
        print(self.test_scenario3.__doc__)
        examples = [
            ['scenario_ml_1', '{"tag": "my_multilabel_1", "data": "data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "scenario_ml_1/predictions.csv", "test": "data/test_multilabel.csv"}', 'data/test_multilabel.csv', 'scenario_ml_3/predictions.csv', 'check_files/predictions_ml_comma.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            test_pred.i_create_resources_from_dataset(self, multi_label='multi-label', test=example[2], output=example[3])
            test_pred.i_check_create_models(self)
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[4])

    def test_scenario4(self):
        """
            Scenario: Successfully building test predictions from models file
                Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
                And I create BigML multi-label resources using models in file "<models_file>" to test "<test>" and log predictions in "<output>"
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |scenario    | kwargs                                                  | models_file        | test                  | output                      |predictions_file                    |
                | scenario_ml_1| {"tag": "my_multilabel_1", "data": "../data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "./scenario_ml_1/predictions.csv", "test": "../data/test_multilabel.csv"}   | ./scenario_ml_1/models | ../data/test_multilabel.csv | ./scenario_ml_4/predictions.csv | ./check_files/predictions_ml_comma.csv |

        """
        print(self.test_scenario4.__doc__)
        examples = [
            ['scenario_ml_1', '{"tag": "my_multilabel_1", "data": "data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "scenario_ml_1/predictions.csv", "test": "data/test_multilabel.csv"}', 'scenario_ml_1/models', 'data/test_multilabel.csv', 'scenario_ml_4/predictions.csv', 'check_files/predictions_ml_comma.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            test_pred.i_create_resources_from_models_file(self, multi_label='multi-label', models_file=example[2], test=example[3], output=example[4])
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[5])

    def test_scenario5(self):
        """
            Scenario: Successfully building test predictions from models retrieved by tag
                Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
                And I create BigML multi-label resources using models tagged as "<tag>" to test "<test>" and log predictions in "<output>"
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |scenario    | kwargs                                                  | tag       | test                  | output                      |predictions_file                    |
                | scenario_ml_6| {"tag": "my_multilabel_5", "data": "../data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "./scenario_ml_6/predictions.csv", "test": "../data/test_multilabel.csv"}    | my_multilabel_5 | ../data/test_multilabel.csv | ./scenario_ml_5/predictions.csv | ./check_files/predictions_ml_comma.csv |

        """
        print(self.test_scenario5.__doc__)
        examples = [
            ['scenario_ml_6', '{"tag": "my_multilabel_5", "data": "data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "scenario_ml_6/predictions.csv", "test": "data/test_multilabel.csv"}', 'my_multilabel_5', 'data/test_multilabel.csv', 'scenario_ml_5/predictions.csv', 'check_files/predictions_ml_comma.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            ml_pred.i_predict_ml_from_model_tag(self, tag=example[2], test=example[3], output=example[4])
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[5])

    def test_scenario6(self):
        """
            Scenario: Successfully building test predictions from models retrieved by tag
                Given I have previously executed "<scenario>" or reproduce it with arguments <kwargs>
                And I create BigML multi-label resources with labels "<labels>" using models tagged as "<tag>" to test "<test>" and log predictions in "<output>"
                And I check that the predictions are ready
                Then the local prediction file is like "<predictions_file>"

                Examples:
                |scenario    | kwargs                                                  |labels      | tag       | test                  | output                      |predictions_file                    |
                | scenario_ml_6| {"tag": "my_multilabel_5", "data": "../data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "./scenario_ml_6/predictions.csv", "test": "../data/test_multilabel.csv"}    | Adult,Student | my_multilabel_5 | ../data/test_multilabel.csv | ./scenario_ml_7/predictions.csv | ./check_files/predictions_ml_labels.csv |

        """
        print(self.test_scenario6.__doc__)
        examples = [
            ['scenario_ml_6', '{"tag": "my_multilabel_5", "data": "data/multilabel.csv", "label_separator": ":", "number_of_labels": 7, "training_separator": ",", "output": "scenario_ml_6/predictions.csv", "test": "data/test_multilabel.csv"}', 'Adult,Student', 'my_multilabel_5', 'data/test_multilabel.csv', 'scenario_ml_7/predictions.csv', 'check_files/predictions_ml_labels.csv']]
        for example in examples:
            print("\nTesting with:\n", example)
            test_pred.i_have_previous_scenario_or_reproduce_it(self, example[0], example[1])
            ml_pred.i_predict_ml_from_model_tag_with_labels(self, labels=example[2], tag=example[3], test=example[4], output=example[5])
            test_pred.i_check_create_predictions(self)
            test_pred.i_check_predictions(self, example[6])
