KaneAI - World’s First E2E Software Testing Agent.Book a Demo Join TestMu Conference

How to use _wrapper method in assertpy

Best Python code snippet using assertpy_python

Main2.py

...74            f1_micro[algorithm + '_wrapper'] = np.zeros((9, 10))75            train_time[algorithm + '_wrapper'] = np.zeros((9, 10))76            test_time[algorithm + '_wrapper'] = np.zeros((9, 10))77            for percent in range(1, 10):78                a, b, c, d, e = wrapper.cross_validation_wrapper(79                    data_name=data_set_name, mlc_type=mlc, compare_with=algorithm, feature_threshold=(percent * 0.1),80                    need_normalize=need_normalize, need_sampling=need_sampling, need_contaminate=need_contaminate)81                hamming_loss[algorithm + '_wrapper'][percent-1, :], f1_macro[algorithm + '_wrapper'][percent-1, :],\82                f1_micro[algorithm + '_wrapper'][percent-1, :], train_time[algorithm + '_wrapper'][percent-1, :],\83                test_time[algorithm + '_wrapper'][percent-1, :] = a[percent-1, :], b[percent-1, :], c[percent-1, :],\84                                                                  d[percent-1, :], e[percent-1, :]85            np.save(dir_name + '/hamming_loss_' + algorithm + '_wrapper', hamming_loss[algorithm + '_wrapper'])86            np.save(dir_name + '/f1_macro_' + algorithm + '_wrapper', f1_macro[algorithm + '_wrapper'])87            np.save(dir_name + '/f1_micro_' + algorithm + '_wrapper', f1_micro[algorithm + '_wrapper'])88            np.save(dir_name + '/train_time_' + algorithm + '_wrapper', train_time[algorithm + '_wrapper'])89            np.save(dir_name + '/test_time_' + algorithm + '_wrapper', test_time[algorithm + '_wrapper'])90        else:91            ranking_loss[algorithm + '_wrapper'] = np.zeros((9, 10))92            average_precision[algorithm + '_wrapper'] = np.zeros((9, 10))93            train_time[algorithm + '_wrapper'] = np.zeros((9, 10))94            test_time[algorithm + '_wrapper'] = np.zeros((9, 10))95            for percent in range(1, 10):96                a, b, c, d = wrapper.cross_validation_wrapper(97                    data_name=data_set_name, mlc_type=mlc, compare_with=algorithm, feature_threshold=(percent * 0.1),98                    need_normalize=need_normalize, need_sampling=need_sampling, need_contaminate=need_contaminate)99                ranking_loss[algorithm + '_wrapper'][percent-1, :],\100                average_precision[algorithm + '_wrapper'][percent-1, :],\101                train_time[algorithm + '_wrapper'][percent-1, :],\102                test_time[algorithm + '_wrapper'][percent-1, :] = a[percent-1, :], b[percent-1, :], c[percent-1, :],\103                                                                  d[percent-1, :]104            np.save(dir_name + '/ranking_loss_' + algorithm + '_wrapper', ranking_loss[algorithm + '_wrapper'])105            np.save(dir_name + '/average_precision_' + algorithm + '_wrapper', average_precision[algorithm + '_wrapper'])106            np.save(dir_name + '/train_time_' + algorithm + '_wrapper', train_time[algorithm + '_wrapper'])107            np.save(dir_name + '/test_time_' + algorithm + '_wrapper', test_time[algorithm + '_wrapper'])108    return load_results(data_set_name, mlc, test_name, algorithm_list_filter, algorithm_list_wrapper)109    #  return hamming_loss, f1_macro, f1_micro, ranking_loss, average_precision, train_time, test_time110def load_results(data_set_name, mlc, test_name, algorithm_list_filter=[], algorithm_list_wrapper=[]):...

Main.py

Source: Main.py

...72            np.save(dir_name + '/test_time_' + algorithm, test_time[algorithm])73    for algorithm in algorithm_list_wrapper:74        if mlc != 'CLR':75            hamming_loss[algorithm + '_wrapper'], f1_macro[algorithm + '_wrapper'], f1_micro[algorithm + '_wrapper'],\76             train_time[algorithm + '_wrapper'], test_time[algorithm + '_wrapper'] = wrapper.cross_validation_wrapper(77                    data_name=data_set_name, mlc_type=mlc, compare_with=algorithm, feature_threshold=0,78                    need_normalize=need_normalize, need_sampling=need_sampling, need_contaminate=need_contaminate,79                    need_shuffling=need_shuffling)80            np.save(dir_name + '/hamming_loss_' + algorithm + '_wrapper', hamming_loss[algorithm + '_wrapper'])81            np.save(dir_name + '/f1_macro_' + algorithm + '_wrapper', f1_macro[algorithm + '_wrapper'])82            np.save(dir_name + '/f1_micro_' + algorithm + '_wrapper', f1_micro[algorithm + '_wrapper'])83            np.save(dir_name + '/train_time_' + algorithm + '_wrapper', train_time[algorithm + '_wrapper'])84            np.save(dir_name + '/test_time_' + algorithm + '_wrapper', test_time[algorithm + '_wrapper'])85        else:86            ranking_loss[algorithm + '_wrapper'], average_precision[algorithm + '_wrapper'], \87             train_time[algorithm + '_wrapper'], test_time[algorithm + '_wrapper'] =\88             wrapper.cross_validation_wrapper(89                    data_name=data_set_name, mlc_type=mlc, compare_with=algorithm, feature_threshold=0,90                    need_normalize=need_normalize, need_sampling=need_sampling, need_contaminate=need_contaminate,91                    need_shuffling=need_shuffling)92            np.save(dir_name + '/ranking_loss_' + algorithm + '_wrapper', ranking_loss[algorithm + '_wrapper'])93            np.save(dir_name + '/average_precision_' + algorithm + '_wrapper', average_precision[algorithm + '_wrapper'])94            np.save(dir_name + '/train_time_' + algorithm + '_wrapper', train_time[algorithm + '_wrapper'])95            np.save(dir_name + '/test_time_' + algorithm + '_wrapper', test_time[algorithm + '_wrapper'])96    return load_results(data_set_name, mlc, test_name, algorithm_list_filter, algorithm_list_wrapper )97    #  return hamming_loss, f1_macro, f1_micro, ranking_loss, average_precision, train_time, test_time98def load_results(data_set_name, mlc, test_name, algorithm_list_filter=[], algorithm_list_wrapper=[]):99    # loading results from test() and show the plot100    hamming_loss = dict()101    f1_macro = dict()102    f1_micro = dict()...

yaxmlplus.py

Source: yaxmlplus.py

...126            for image in images:127                etree.SubElement(offer, "image").text = image            128        etree.SubElement(offer, "description").text = self._wrapper.description()129        if not is_stead:130            self.unit_wrapper(etree, etree.SubElement(offer, "area"), self._wrapper.area())131            if self._wrapper.living_space():132                self.unit_wrapper(etree, etree.SubElement(offer, "living-space"), self._wrapper.living_space())133            if self._wrapper.kitchen_space():134                self.unit_wrapper(etree, etree.SubElement(offer, "kitchen-space"), self._wrapper.kitchen_space())135            for room_space in self._wrapper.rooms_space():136                self.unit_wrapper(etree, etree.SubElement(offer, "room-space"), room_space)137            if self._wrapper.rooms_type():138                etree.SubElement(offer, "rooms-type").text = self._wrapper.rooms_type()            139            self.add_bool_element(etree, offer, 'kitchen-furniture', self._wrapper.kitchen_furniture())140            self.add_bool_element(etree, offer, 'room-furniture', self._wrapper.room_furniture())141            self.add_bool_element(etree, offer, 'television', self._wrapper.television())142            self.add_bool_element(etree, offer, 'washing-machine', self._wrapper.washing_machine())143            self.add_bool_element(etree, offer, 'refrigerator', self._wrapper.refrigerator())144            self.add_bool_element(etree, offer, 'alarm', self._wrapper.alarm())145        else:146            etree.SubElement(offer, "lot-type").text = self._wrapper.lot_type()            147        if has_stead: 148            self.unit_wrapper(etree, etree.SubElement(offer, "lot-area"), self._wrapper.lot_area(), u'ÑÐ¾Ñ')149        self.add_bool_element(etree, offer, 'new-flat', self._wrapper.new_flat())     150        if self._wrapper.rooms():151            etree.SubElement(offer, "rooms").text = self._wrapper.rooms()        152        if self._wrapper.rooms_offered():153            etree.SubElement(offer, "rooms-offered").text = self._wrapper.rooms_offered()154        155        if self._wrapper.is_studio():156            self.add_bool_element(etree, offer, 'open-plan', self._wrapper.is_studio())157                        158        self.add_bool_element(etree, offer, 'phone', self._wrapper.phone())        159        self.add_bool_element(etree, offer, 'internet', self._wrapper.internet())160        self.add_bool_element(etree, offer, 'mortgage', self._wrapper.mortgage())161        162        if self._wrapper.renovation():...

Blogs

Check out the latest blogs from LambdaTest on this topic:

What is coaching leadership

Coaching is a term that is now being mentioned a lot more in the leadership space. Having grown successful teams I thought that I was well acquainted with this subject.

Best 13 Tools To Test JavaScript Code

Unit and functional testing are the prime ways of verifying the JavaScript code quality. However, a host of tools are available that can also check code before or during its execution in order to test its quality and adherence to coding standards. With each tool having its unique features and advantages contributing to its testing capabilities, you can use the tool that best suits your need for performing JavaScript testing.

Six Agile Team Behaviors to Consider

Are members of agile teams different from members of other teams? Both yes and no. Yes, because some of the behaviors we observe in agile teams are more distinct than in non-agile teams. And no, because we are talking about individuals!

Agile Testing is different – Here is what you need to know

Agile Testing is different- Here is what you need to know.og

Guide To Find Index Of Element In List with Python Selenium

In an ideal world, you can test your web application in the same test environment and return the same results every time. The reality can be difficult sometimes when you have flaky tests, which may be due to the complexity of the web elements you are trying to perform an action on your test case.

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.