Simulation Parameter Analysis R Toolkit ApplicatioN: 'spartan'


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Documentation for package ‘spartan’ version 3.0.2

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A B C D E F G I K L M N O P R S T U V W

-- A --

aa_getATestResults Calculates the A-Test scores observed for all sets, for each sample size
aa_getATestResults_overTime Get A-Test results for multiple simulation timepoints
aa_graphATestsForSampleSize Produce a plot for each sample size, showing the A-Test scores for each set of that size
aa_graphSampleSizeSummary Plots a comparison of the maximum A-Test score for each sample size
aa_sampleSizeSummary Determines the median and maximum A-Test score observed for each sample size
aa_sampleSizeSummary_overTime Determines median and maximum A-Test score for each sample size over time
aa_summariseReplicateRuns Summarise results in set folder structure into one single CSV file
aa_summariseReplicateRuns_overTime Calculate summary responses for consistency analysis simulations at multiple timepoints
add_parameter_value_to_file Iterates through the parameters, adding their sampled value to the netlogo experiment file
analysenetwork_structures Analyse each network structure provided as a potential NN structure
append_time_to_argument Appends the time to an argument if processing timepoints
atest Calculates the A-test score for two distributions
a_test_results Analysed results from tutorial_consistency_set: a-test scores when sets compared

-- B --

build_curve_results_from_r_object When developing spartanDB, it became clear curve results may not be in separate files but in one R object. This takes an R object containing curve summaries and builds these into the format spartan requires to perform the analysis

-- C --

calculate_atest_score Calculate the A-Test score for a parameter set in comparison with baseline
calculate_fold_MSE Calculate the mean squared error for this fold in k-fold cross validation
calculate_medians_for_all_measures Calculate medians for all measures for a simulation parameter result
calculate_prccs_all_parameters Calculate PRCC values for all parameter-measure pairs
calculate_prcc_for_all_measures For all measures, calculate the prcc for each parameter
calculate_weights_for_ensemble_model Internal function to calculate the weights for all emulators in the ensemble
check_argument_positive_int Check that an argument that should be a positive integer has been specified correctly
check_boolean Check that an argument that should be a boolean has been specified correctly
check_column_ranges For aleatory analysis, checks the analysis start and end columns are sensible
check_confidence_interval Check that a confidence interval is within a specified range
check_consistency_result_type Check that the user has declared either a file name or an R object
check_double_value_in_range Check that a double argument is within a specified range
check_filepath_exists Check that the filepath of required data or output exists
check_file_exist Checks for the existence of a file
check_file_exists Check whether a file exists
check_function_dependent_paramvals Call the correct paramvals check for the calling function, as netlogo & robustness differ
check_global_param_sampling_args Checks the input values for global parameter sampling techniques
check_graph_output_type Check the requested graph types are correct (PDF, PNG, TIFF, BMP)
check_input_args Wrapper function called by all spartan methods to check input pre-execution
check_lengths_parameters_ranges Check that the lengths of the parameters, minimum values, and maximum values, are equal
check_lhs_algorithm Check that the chosen lhc sampling algorithm is either normal or optimal.
check_list_all_integers Check that all objects of a list are integers
check_nested_filepaths Check that result filepaths under the root directory exist
check_netlogo_parameters_and_values Checks the netlogo parameters and values are formatted correctly
check_numeric_list_values Check that two lists are numeric, and the values of one are less than the other
check_package_installed Check that a required package has been installed
check_parameters_and_ranges Pre-Check of the parameters and ranges specified for sampling parameter space
check_paramvals_length_equals_parameter_length Where used in robustness analysis, check that the length of PARAMVALS equals
check_robustness_parameter_and_ranges_lengths Where used, checks that PARAMETERS, PMIN, PMAX, PINC, and BASELINE are all the same length
check_robustness_paramvals_contains_baseline Checks that the parameter values specified in PARAMVALS contain the BASELINE
check_robustness_range_contains_baseline Checks that the range specified by PMIN and PMAX contains the BASELINE
check_robustness_range_or_values For robustness, check whether using PMIN/PMAX/PINC entry or PARAMVALS
check_robustness_sampling_args Pre-execution checks to perform before the spartan robustness samplng technique is executed. Checks all parameter input
check_text Check that an argument that should be a text label has been specified correctly
check_text_list Check that an arguments of a list that should be a text label has been specified correctly
close_and_write_netlogo_file Close the current netlogo sample file and write out
compare_all_values_of_parameter_to_baseline For one parameter, compare responses for all values with those at baseline
construct_result_filename Appends the time to an eFAST argument, if processing multiple timepoints
createAndEvaluateFolds Create and evaluate folds within k-fold cross validation
createtest_fold Create test data fold for k-fold cross validation
createTrainingFold Create training data fold for k-fold cross validation
create_abc_settings_object Creates ensemble-specific parameters for ABC analysis
create_ensemble Internal function to create the ensemble
create_neural_network Create neural network emulator, using neuralnet package

-- D --

dataset_precheck Before partitioning data, removes any columns where the value is all equal, or all NA
determine_optimal_neural_network_structure Determine the optimal hidden layer structure from those provided

-- E --

efast_generate_medians_for_all_parameter_subsets Generates summary file for stochastic simulations stored in multiple files
efast_generate_medians_for_all_parameter_subsets_overTime Pre-process analysis settings if multiple timepoints are being considered
efast_generate_sample Generates parameter sets for variance-based eFAST Sensitivity Analysis
efast_generate_sample_netlogo Prepares Netlogo experiment files for a variance-based sensitivity analysis, using eFAST
efast_get_overall_medians Calculates the summary stats for each parameter set (median of any replicates)
efast_get_overall_medians_overTime Pre-process analysis settings if multiple timepoints are being considered
efast_graph_Results Plot the parition of variance in a simulation response for each measure
efast_netlogo_get_overall_medians Deprecated: Use 'efast_netlogo_get_overall_medians'
efast_netlogo_run_Analysis Deprecated: Use 'efast_run_Analysis'
efast_process_netlogo_result Analyses Netlogo simulation data for parameter sets generated for eFAST
efast_run_Analysis Runs the eFAST Analysis for the pre-generated summary file
efast_run_Analysis_from_DB Runs the eFAST Analysis for a set of results stored in a database
efast_run_Analysis_overTime Pre-process analysis settings if multiple timepoints are being considered
emulated_lhc_values Latin-hypercube value set use to demonstrate emulated sensitivity analysis
emulate_efast_sampled_parameters Emulate simulations for a set of eFAST generated parameter values
emulate_lhc_sampled_parameters Emulate simulations for a set of latin-hypercube generated parameter values
emulation_algorithm_settings Initialise machine-learning algorithms settings for emulation creation
emulator_parameter_evolution Evolve parameter sets that meet a desired ensemble outcome
emulator_predictions Used to generate predictions from an emulator, normalising data if required
ensemble_abc_wrapper Wrapper to allow EasyABC functions to run using Ensemble
execute_checks Executes the list of check functions compiled for the calling function
exemplar_sim_output Example of a dataset output from an agent-based simulation, used in package testing

-- F --

format_efast_result_for_output Joins the various results objects into an output ready format

-- G --

generate_a_test_results_header Generates the CSV file header for the A-Test results file
generate_a_test_score Take the first set and compare it to a distribution from another set using the A-Test
generate_efast_parameter_sets Use the eFAST approach to generate parameter sets
generate_emulators_and_ensemble Generate a set of emulators and combine into an ensemble
generate_ensemble_from_existing_emulations Generate an ensemble from previously created spartan emulation objects
generate_ensemble_training_set Internal function used to combine test set predictions from emulators to form the ensemble training set
generate_headers_for_atest_file Generates headers for the A-Test summary CSV and R Object
generate_list_of_checks Defines which functions to call to check an input argument.
generate_medians_for_param_set Generate the median responses for a set of parameter values
generate_parameter_table Takes the value list and generates the sample that is output to csv file
generate_prcc_results_header Generates the CSV file header for the prcc results file
generate_requested_emulations Generate emulators for specified machine learning techniques with provided data
generate_sensitivity_indices Generate eFAST Sensitivity Indices
generate_summary_stats_for_all_param_sets Generate summary statistics for each value of all parameters in this analysis
get_argument_correct_case Tries upper and lower case names for input arguments
get_correct_file_path_for_function Gets the correct filepath for the column range input checker
get_file_and_object_argument_names Gets the correct file and R object argument names for the input checker
get_max_and_median_atest_scores Return the max and median A-Test score for all measures for a sample size
get_medians_for_size_subsets For a given sample size, get the median results to summarise results for all sets
get_median_results_for_all_measures For a model result, calculate the medians of the desired measures
graph_Posteriors_All_Parameters Graph posterior distributions generated for all parameters, to PDF file
graph_sample_size_results Graph the A-Test results for a sample size

-- I --

import_model_result Import a model result from either a CSV or XML file
initialise_netlogo_xml_file Initialises the Netlogo setup file for this experiment

-- K --

kfoldCrossValidation Perform k-fold cross validation for assessing neural network structure performance

-- L --

lhc_calculatePRCCForMultipleTimepoints Calculates the PRCC for each parameter at each timepoint, storeing PRCC and P-Value in two different files to make the plot function easier
lhc_generateLHCSummary Summarises simulation behaviour for each parameter set, by median of distribution of replicate runs
lhc_generateLHCSummary_overTime Pre-process analysis settings if multiple timepoints are being considered
lhc_generatePRCoEffs Generate Partial Rank Correlation Coefficients for parameter/response pairs
lhc_generatePRCoEffs_db_link Generate Partial Rank Correlation Coefficients for parameter/response pairs for results in database
lhc_generatePRCoEffs_overTime Pre-process analysis settings if multiple timepoints are being considered
lhc_generateTimepointFiles Generates spartan-compatible timepoint files if simulation results over time are in one file
lhc_generate_lhc_sample Generates sets of simulation parameters using latin-hypercube sampling
lhc_generate_lhc_sample_netlogo Prepares Netlogo experiment files for a sampling-based sensitivity analysis, using latin-hypercube sampling
lhc_generate_netlogo_PRCoEffs Deprecated. Use 'lhc_generatePRCoEffs' instead
lhc_graphMeasuresForParameterChange Generates parameter/measure plot for each pairing in the analysis
lhc_graphMeasuresForParameterChange_from_db Generates parameter/measure plot for each pairing in the analysis, from results stored in a database
lhc_graphMeasuresForParameterChange_overTime Wrapper for graphing LHC results for multiple timepoints
lhc_netlogo_graphMeasuresForParameterChange Deprecated. Use 'lhc_graphMeasuresForParameterChange' instead
lhc_plotCoEfficients Plots the PRCC coefficients against each other for ease of comparison
lhc_polarplot Creates a polar plot for each response, showing PRCC for each parameter
lhc_process_netlogo_result Analyses Netlogo simulations generated for a latin-hypercube based sensitivity analysis
lhc_process_sample_run_subsets Summarises results of runs for parameter sets generated by a latin-hypercube
lhc_process_sample_run_subsets_overTime Pre-process analysis settings if multiple timepoints are being considered

-- M --

make_graph_title Make graph title, sub title, and file name
make_lhc_plot Make the LHC output plot

-- N --

normaliseATest Normalises the A-Test such that it is above 0.5
normalise_dataset Normalise a dataset such that all values are between 0 and 1
nsga2_set_user_params Initialise analysis specific parameters for NSGA-2
num.decimals Diagnostic function used to determine number of decimal places

-- O --

oat_csv_result_file_analysis Performs a robustness analysis for supplied simulation data, comparing simulation behaviour at different parameter values
oat_csv_result_file_analysis_from_DB Performs a robustness analysis for simulation results stored in a database, comparing simulation behaviour at different parameter values
oat_csv_result_file_analysis_overTime Pre-process analysis settings if multiple timepoints are being considered
oat_generate_netlogo_behaviour_space_XML Creates a Netlogo compatible behaviour space experiment for robustness analysis
oat_graphATestsForSampleSize Takes each parameter in turn and creates a plot showing A-Test score against parameter value.
oat_parameter_sampling Create parameter samples for robustness (local) analysis
oat_plotResultDistribution For stochastic simulations plots the distribution of results for each parameter value
oat_processParamSubsets Summarises stochastic, repeated, simulations for all robustness parameter sets into a single file.
oat_processParamSubsets_overTime Summarises stochastic, repeated, simulations for all robustness parameter sets into a single file, for multiple timepoints
oat_process_netlogo_result Takes a Netlogo behaviour space file and performs a robustness analysis from that simulation data
output_ggplot_graph Output a ggplot graph in the requested formats
output_param_sets_per_curve Output the generated parameter sets for each curve

-- P --

partition_dataset Partition latin-hypercube summary file to training, testing, and validation
perform_aTest_for_all_sim_measures Performs A-Test to compare all simulation measures
plotATestsFromTimepointFiles Plots the A-Tests for all timepoints being examined
ploteFASTSiFromTimepointFiles Plot the Si value for all parameters for multiple simulation timepoints
plotPRCCSFromTimepointFiles Plots Graphs for Partial Rank Correlation Coefficients Over Time
plot_compare_sim_observed_to_model_prediction Internal function used to create accuracy plots of the emulation against observed data
process_netlogo_parameter_range_info Processes netlogo parameter information to generate names of those of interest to this analysis
process_parameter_value_if_exists Process parameter value set if results exist
produce_accuracy_plots_all_measures Internal function used to create accuracy plots of the emulation against observed data, for all measures
produce_accuracy_plots_single_measure Internal function used to create accuracy plots of the emulation against observed data
produce_atest_score_summary Generates A-Test score summary for all sample sizes
produce_summary_for_all_values_of_parameter For one parameter, evaluate the results of all values that parameter can take

-- R --

read_all_curve_results Reads results from each curve into a multi-dimensional array
read_from_csv To save retyping all options, function to read CSV data
read_model_result_file Reads a model result file, either CSV or XML
read_simulation_results Read in the simulation results either from a file, or R object The existance of these results was checked in pre-execution checks
retrieve_results_for_comparison_result_set Get the first result set, to which all others are compared

-- S --

sample_parameter_space Generate the LHC design for the chosen algorithm
scale_lhc_sample Scale the LHC design to be the range explored for each parameter
screen_nsga2_parameters Screens NSGA-2 related parameters, guiding which to select for evolving parameter sets
selectSuitableStructure Selects the most suitable neural network structure from the potentials made
set.nsga_sensitivity_params Set parameters for NSGA-2 sensitivity analysis
sim_data_for_emulation Set of parameter and response pairs for training an emulator of a simulation
summarise_lhc_sweep_responses Processes an LHC sample, returning summary stats for all parameter sets
summarise_replicate_runs Summarises replicate runs of a parameter set. Used by LHC and eFAST

-- T --

tutorial_consistency_set Example dataset showing the structure for consistency analysis data

-- U --

updateErrorForStructure Add the MSE for a newly examined structure to the list of those already seen
use_ensemble_to_generate_predictions Predict simulation responses for a parameter set using an ensemble

-- V --

visualise_data_distribution Used to diagnose skew in a training dataset before use in emulation

-- W --

weight_emulator_predictions_by_ensemble Internal function to weight emulator predictions by that calculated for the ensemble
write_data_to_csv Shortcut function for writing data to CSV file