umami.tests.integration package#

Submodules#

umami.tests.integration.test_examples module#

Integration tests for the scripts located in the examples directory.

umami.tests.integration.test_examples.test_example_plots(command, expected_result)#

Check the plotting of the example plots

Parameters:

command (str) – file containing the test to be run
expected_result (int) – expected test result

umami.tests.integration.test_input_vars_plot module#

Integration tests for variable plotting.

class umami.tests.integration.test_input_vars_plot.TestInputVarsPlotting(methodName='runTest')#

Bases: TestCase

Integration tests for variable plotting.

setUp()#: Download test files for input var plots.

test_plot_input_vars()#: Integration test of plot_input_vars.py script.

umami.tests.integration.test_input_vars_plot.get_configuration() → object#

Load yaml file with settings for integration test of the input vars plotting.

Returns:: Loaded configuration file.
Return type:: object
Raises:: YAMLError – If a needed key is not in file.

umami.tests.integration.test_input_vars_plot.run_plot_input_vars(config: str) → bool#

Call plot_input_vars.py.

Parameters:: config (str) – Path to config file.
Returns:: True if tests pass, False if tests fail.
Return type:: bool

umami.tests.integration.test_plotting_umami module#

This script integration tests the plotting of the training results of the different models.

class umami.tests.integration.test_plotting_umami.TestPlottingUmami(methodName='runTest')#

Bases: TestCase

Integration test class for the plotting of the training results.

This class creates a test folder and downloads all important files.

setUp()#: Download test files for running the dips training.

test_plotting_umami_dips()#: Testing the plotting of the DIPS trainings.

test_plotting_umami_dl1r()#: Testing the plotting of the DL1r trainings.

test_plotting_umami_umami()#: Testing the plotting of the Umami trainings.

umami.tests.integration.test_plotting_umami.get_configuration()#

Load yaml file with settings for integration test of dips training.

Returns:: Loaded configuration file.
Return type:: object
Raises:: YAMLError – If a needed key is not in file.

umami.tests.integration.test_plotting_umami.run_plotting(config, tagger)#

Call plotting_umami.py and try to plot the results of the previous tests. Return value True if training succeeded, False if one step did not succeed.

Parameters:

config (dict) – Dict with the needed configurations for the plotting.
tagger (str) – Name of the tagger which is to be plotted.

Raises:

AssertionError – If the plotting step fails.

Returns:

isSuccess – Preprocessing succeeded or not.

Return type:

bool

umami.tests.integration.test_preprocessing module#

This script integration tests the preprocessing methods.

class umami.tests.integration.test_preprocessing.TestPreprocessing(methodName='runTest')#

Bases: TestCase

Test class for the preprocessing.

This class sets up the needed configs for testing the preprocessing of Umami.

setUp()#: Download test files for running the preprocessing and dress preprocessing config file.

test_preprocessing_additional_jet_labels()#: Integration test of preprocessing.py script using GN1 variables, and allowing for additional jet labels

test_preprocessing_dips_count()#: Integration test of preprocessing.py script using DIPS variables.

test_preprocessing_dips_four_classes_pdf()#: Integration test of preprocessing.py script using DIPS variables and four classes.

test_preprocessing_dips_hits_count()#: Integration test of preprocessing.py script using DIPS with hits variables.

test_preprocessing_dips_pdf()#: Integration test of preprocessing.py script using DIPS variables.

test_preprocessing_dips_weighting()#: Integration test of preprocessing.py script using DIPS variables.

test_preprocessing_dl1r_count()#: Integration test of preprocessing.py script using DL1r variables.

test_preprocessing_dl1r_pdf()#: Integration test of preprocessing.py script using DL1r variables.

test_preprocessing_dl1r_weighting()#: Integration test of preprocessing.py script using DL1r variables.

test_preprocessing_umami_count()#: Integration test of preprocessing.py script using Umami variables.

test_preprocessing_umami_importance_no_replace()#: Integration test of preprocessing.py script using DL1r variables.

test_preprocessing_umami_pdf()#: Integration test of preprocessing.py script using Umami variables.

test_preprocessing_umami_weighting()#: Integration test of preprocessing.py script using Umami variables.

umami.tests.integration.test_preprocessing.get_configuration()#

Load yaml file with settings for integration test of preprocessing.

Returns:: Loaded configuration file.
Return type:: object
Raises:: YAMLError – If a needed key is not in file.

umami.tests.integration.test_preprocessing.run_preprocessing(config: dict, tagger: str, method: str, string_id: str, test_dir: str, flavours_to_process: list | None = None, sample_type_list: list | None = None, sample_usecase_list: list | None = None) → bool#

Call all steps of the preprocessing for a certain configuration and variable dict input. Return value True if all steps succeeded.

Parameters:

config (dict) – Dict with the needed configurations for the preprocessing.
tagger (str) – Name of the tagger which the preprocessing should be done for. The difference is in saving tracks or not.
method (str) – Define which sampling method is used.
string_id (str) – Unique identifier to further specify which preprocessing was done.
test_dir (str) – Path to the directory where all the files are downloaded to etc.
flavours_to_process (list, optional) – List with the flavours that are to be processed. By default None
sample_type_list (list, optional) – List with the sample types to prepare. By default this will be [‘ttbar’, ‘zpext’]. By default None
sample_usecase_list (list, optional) – List with the sample usecases to prepare. By default this will be [‘training’, ‘validation’] for DL1r and [“training”] for all other taggers. By default None

Raises:

AssertionError – If the prepare step fails.
AssertionError – If the resampling step fails.
AssertionError – If the scaling step fails.
AssertionError – If the apply scaling step fails.
AssertionError – If the write step fails.
AssertionError – If the to records step fails.
KeyError – If the resampling method is not supported by the test.

Returns:

isSuccess – Preprocessing succeeded or not.

Return type:

bool

umami.tests.integration.test_preprocessing_upp module#

This script integration tests the preprocessing methods.

class umami.tests.integration.test_preprocessing_upp.TestPreprocessingUPP(methodName='runTest')#

Bases: TestCase

Test class for the preprocessing with UPP.

This class sets up the needed configs for testing the preprocessing of UPP.

setUp()#: Download test files for running the preprocessing and dress preprocessing config file.

test_preprocessing_dips_upp_countup()#: Integration test of preprocessing.py with UPP preprocessing.

test_preprocessing_dips_upp_pdf()#: Integration test of preprocessing.py with UPP preprocessing.

test_preprocessing_upp_flags()#: Integration test of preprocessing.py with UPP flags.

umami.tests.integration.test_preprocessing_upp.get_configuration()#

Load yaml file with settings for integration test of preprocessing.

Returns:: Loaded configuration file.
Return type:: object

umami.tests.integration.test_preprocessing_upp.run_preprocessing(config: dict, tagger: str, method: str, string_id: str, test_dir: str) → bool#

Call all steps of the preprocessing for a certain configuration and variable dict input. Return value True if all steps succeeded.

Parameters:

config (dict) – Dict with the needed configurations for the preprocessing.
tagger (str) – Name of the tagger which the preprocessing should be done for. The difference is in saving tracks or not.
method (str) – Define which sampling method is used.
string_id (str) – Unique identifier to further specify which preprocessing was done.
test_dir (str) – Path to the directory where all the files are downloaded to etc.

Returns:

isSuccess – Preprocessing succeeded or not.

Return type:

bool

umami.tests.integration.test_train module#

This script integration tests the training of the different models.

class umami.tests.integration.test_train.TestTraining(methodName='runTest')#

Bases: TestCase

Integration test class for the training.

This class creates a test folder and downloads all important files.

setUp()#: Download test files for running the dips training.

test_evaluate_tagger_in_files()#: Integration test the evaluation of only the taggers available in the files.

test_train_cads()#: Integration test of train.py for CADS script.

test_train_cond_att_umami()#: Integration test of train.py for UMAMI Cond Att script.

test_train_dips_four_classes()#: Integration test of train.py for DIPS script with four classes.

test_train_dips_no_attention()#: Integration test of train.py for DIPS script.

test_train_dl1r()#: Integration test of train.py for DL1r script.

test_train_tfrecords_cads()#: Integration test of train.py for CADS script with TFRecords.

test_train_tfrecords_cond_att_umami()#: Integration test of train.py for UMAMI Cond Att script with TFRecords.

test_train_tfrecords_dips()#: Integration test of train.py for DIPS script with TFRecords.

test_train_tfrecords_dl1r()#: Integration test of train.py for DL1r script with TFRecords.

test_train_tfrecords_umami()#: Integration test of train.py for UMAMI script with TFRecords.

test_train_umami()#: Integration test of train.py for UMAMI script.

umami.tests.integration.test_train.get_configuration()#

Load yaml file with settings for integration test of dips training.

Returns:: Loaded configuration file.
Return type:: object
Raises:: YAMLError – If a needed key is not in file.

umami.tests.integration.test_train.prepare_config(tagger: str, test_dir: str, var_file_from: str | None = None, preprocess_files_from: str | None = None, four_classes_case: bool = False, use_tf_records: bool = False) → dict#

Prepare the train config for the given tagger and save it.

Parameters:

tagger (str) – Name of the tagger for which the config is to be prepared.
test_dir (str) – Path to the test directory where the config file is to be saved.
var_file_from (str, optional) – Name of the tagger from which the variable file is used. Possible options are dips, umami, dl1r. If None is given, the value of tagger is used. By default None
preprocess_files_from (str) – Name of the preprocessing files that should be used. If not given, the preprocessing files from the tagger will be tried to use.
four_classes_case (bool) – Decide, if you want to run the test with four classes (light, c-, b- and tau)
use_tf_records (bool) – Decide, if the TFRecords files are used for training or not.

Returns:

config – Path to the created config that is to be used for the test.

Return type:

str

umami.tests.integration.test_train.run_training(config: dict, tagger: str) → bool#

Call train.py for the given tagger. Return value True if training succeeded, False if one step did not succees.

Parameters:

config (dict) – Dict with the needed configurations for training.
tagger (str) – Name of the tagger that is to be trained.

Raises:

AssertionError – If train.py fails for the given tagger.
AssertionError – If plotting_epoch_performance.py fails for the given tagger.
AssertionError – If evaluate_model.py fails for the given tagger.

Returns:

isSuccess – Training succeeded or not.

Return type:

bool

umami.tests.integration package#

Submodules#

umami.tests.integration.test_examples module#

umami.tests.integration.test_input_vars_plot module#

umami.tests.integration.test_plotting_umami module#

umami.tests.integration.test_preprocessing module#

umami.tests.integration.test_preprocessing_upp module#

umami.tests.integration.test_train module#

Module contents#