Package: slacgs
SLACGSA Simulator for Loss Analysis of Linear Classifiers on Gaussian Samples in order to evaluate Trade Off Between Samples and Features sizes in Classification Problems on gaussian Samples.Documentation:https://slacgs.netlify.app/Reports with results will be stored in a Google Spreadsheet for each:  Experiment Scenario, Custom Experiment Scenario	and another one for the Custom Simulations.The Spreadsheets are stored in a Google Drive folder named 'slacgs.demo.<user_email>'	owned by slacgs' google service	account and shared with the user's Google Drive account.Also, images with data visualization will be exported to a local folder inside user's local folder (/slacgs/images/ or /content/slacgs/images (for G-colab) )Reports Exported:Loss Report: Contains mainly results focused on Loss Functions evaluations for each dimensionality of the model.Compare Resport: Contains mainly results focused on comparing the performance of the Model using 2 features and 3 features.Home Report (Scenario): Contains results from all simulations in a Scenario and links to the other reports. (available only for comparison between 2D and 3D)Images Exported (<user_home>/slacgs/images/ or /content/slacgs/images [for G-colab] ):Scenario Data plots .gif: Contains a gif with all plots with the data points (n = 1024, dims=[2,3] ) generated for all Models in an Experiment Scenario.Simulation Data plot .png: Contains a plot with the data points (n = 1024, dims=[2,3] ) generated for a Model in a Simulation.Simulation Loss plot .png: Contains a plot with the loss values (Theoretical, Empirical with Train Data, Empirical with Test data) generated for a Model in a Simulation.Loss Functions:Theoretical Loss: estimated using probability theoryEmpirical Loss with Train Data: estimated using empirical approach with train dataEmpirical Loss with Test Data: estimated using empirical approach with test dataExperimentDownload Experiment PDFDemoDownload and InstallSet/Start Report ServiceExperiment ScenariosDemo Functions:Run an Experiment Simulationrun a simulation for one of the experiment scenarios and return True if there are still parameters to be simulated and False otherwiseAdd a Simulation to an Experiment Scenarioadd simulation results to one of the experiment scenario spreadsheetsRun a Custom Scenariorun a custom scenario and write the results to a Google Spreadsheet shared with the userAdd a Simulation to a Custom Scenarioadd a simulation to a custom scenario spreadsheetRun a Custom Simulationrun a custom simulation for any dimensionality and cardinalityRun All Experiment Simulationsrun all simulations in all experiment scenarios1. Download And Installpipinstallslacgs2. Set Report Servicefromslacgs.demoimport*## opt-1: set report service configuration with your own google cloud service account key filepath_to_google_cloud_service_account_api_key='path/to/key.json'set_report_service_conf(path_to_google_cloud_service_account_api_key)# opt-2 set report service configuration to use slacgs' server if you have the access passwordset_report_service_conf()3. Experiment Scenariosfromslacgs.demoimportprint_experiment_scenariosprint_experiment_scenarios()4 Demo Functionsfromslacgs.demoimport*## 1. Run an Experiment Simulation ##run_experiment_simulation()## 2. Add a Simulation to an Experiment Scenario Spreadsheet ##### Scenario 1scenario_number=1params=[1,1,2.1,0,0,0]add_simulation_to_experiment_scenario_spreadsheet(params,scenario_number)### Scenario 2scenario_number=2params=[1,1,2,-0.15,0,0]add_simulation_to_experiment_scenario_spreadsheet(params,scenario_number)### Scenario 3scenario_number=3params=[1,1,2,0,0.15,0.15]add_simulation_to_experiment_scenario_spreadsheet(params,scenario_number)### Scenario 4scenario_number=4params=[1,1,2,-0.1,0.15,0.15]add_simulation_to_experiment_scenario_spreadsheet(params,scenario_number)## 3. Run a Custom Scenario ##scenario_list=[[1,1,3,round(0.1*rho,1),0,0]forrhoinrange(-5,6)]scenario_number=5run_custom_scenario(scenario_list,scenario_number)## 4. Add a Simulation to a Custom Scenario Spreadsheet ##params=(1,1,3,-0.7,0,0)scenario_number=5add_simulation_to_custom_scenario_spreadsheet(params,scenario_number)## 5. Run a Custom Simulation ##### 2 featuresparams=[1,2,0.4]run_custom_simulation(params)### 3 featuresparams=[1,1,4,-0.2,0.1,0.1]run_custom_simulation(params)### 4 featuresparams=[1,1,1,2,0,0,0,0,0,0]run_custom_simulation(params)### 5 featuresparams=[1,1,2,2,2,-0.3,-0.2,-0.1,0,0.1,0.2,0.2,0,0,0]dims_to_compare=(2,5)run_custom_simulation(params,dims_to_compare)### 6 featuresparams=[1,2,3,4,5,6,-0.3,-0.3,-0.2,-0.2,-0.1,-0.1,0,0,0.1,0.1,0.2,0.2,0.3,0.3,0.4]run_custom_simulation(params)## 6. Run All Experiment Simulations ##run_experiment()4.1 Demo Test Functions (simulations running at 1% of its default number of iterations)fromslacgs.demoimport*## 1. Run an Experiment Simulation ##run_experiment_simulation_test()## 2. Add a Simulation to an Experiment Scenario Spreadsheet ##### scenario 1scenario_number=1params=[1,1,2.1,0,0,0]add_simulation_to_experiment_scenario_spreadsheet_test(params,scenario_number)### scenario 2scenario_number=2params=[1,1,2,-0.15,0,0]add_simulation_to_experiment_scenario_spreadsheet_test(params,scenario_number)### scenario 3scenario_number=3params=[1,1,2,0,0.15,0.15]add_simulation_to_experiment_scenario_spreadsheet_test(params,scenario_number)### scenario 4scenario_number=4params=[1,1,2,-0.1,0.15,0.15]add_simulation_to_experiment_scenario_spreadsheet_test(params,scenario_number)## 3. Run a Custom Scenario ##scenario_list=[[1,1,3,round(0.1*rho,1),0,0]forrhoinrange(-5,6)]scenario_number=5run_custom_scenario_test(scenario_list,scenario_number)## 4. Add a Simulation to a Custom Scenario Spreadsheet ##params=(1,1,3,-0.7,0,0)scenario_number=5add_simulation_to_custom_scenario_spreadsheet_test(params,scenario_number)## 5. Run a Custom Simulation ##### 2 featuresparams=[1,2,0.4]run_custom_simulation_test(params)### 3 featuresparams=[1,1,4,-0.2,0.1,0.1]run_custom_simulation_test(params)### 4 featuresparams=[1,1,1,2,0,0,0,0,0,0]run_custom_simulation_test(params)### 5 featuresparams=[1,1,2,2,2,-0.3,-0.2,-0.1,0,0.1,0.2,0.2,0,0,0]dims_to_compare=_test(2,5)run_custom_simulation_test(params,dims_to_compare)### 6 featuresparams=[1,2,3,4,5,6,-0.3,-0.3,-0.2,-0.2,-0.1,-0.1,0,0,0.1,0.1,0.2,0.2,0.3,0.3,0.4]run_custom_simulation_test(params)## 6. Run All Experiment Simulations ##run_experiment_test()