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ChrisJones687ChrisJones687
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update some tests
1 parent 94281be commit 40581c8

36 files changed

+4305
-2409
lines changed

‎R/pops_simulate.R‎

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@@ -90,7 +90,7 @@ pops_simulate <- function(config_rds_file = "") {
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}
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config$competency_table_list <- competency_table_list_creator(config$competency_table)
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config$pest_host_table_list <- pest_host_table_list_creator(config$pest_host_table)
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config$random_seed <- config$random_seed_list[i]
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config$random_seed <- config$random_seed_list[[i]]
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config$random_seeds <- as.matrix(config$random_seeds_list[i, ])[1, ]
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data <- PoPS::pops_model(config)

‎inst/extdata/configs_configuration/test_config.yaml‎

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# File paths for input and output data
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input_path: "C:/Users/cjone/Projects/rpops/inst/extdata" # folder with inputs
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output_path: "C:/Users/cjone/Projects/rpops/inst/extdata/simple20x20/outputs" # folder to write outputs to
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# pest parameters
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starting_infected_files: ["extdata/simple20x20/infected_single.tif"] # GeoTiff File with the locations of initial infections to start the simulation
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parameter_means_file: "extdata/parameter_means_default.csv" # CSV File with the parameter means from the calibration
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parameter_cov_matrix_file: "extdata/parameter_cov_matrix_default.csv" # CSV File with the parameter covariance matrix from the calibration
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pest_host_table: "extdata/pest_host_table_singlehost.csv" # CSV file with the pest host table
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competency_table: "extdata/competency_table_singlehost.csv" # CSV file with the compentency table
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county_level_infection_data: false # is your infection data county level only
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use_initial_condition_uncertainty: false # Are you providing a mean and standard deviation for your starting infection files. This allows for propogating uncertainty through the model.
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start_exposed: false # Should you start with your known infections as exposed. Useful for simulating inoculation experiments.
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latency_period: 0 # what is the lantent period of your pathogen?
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exposed_files: [""] # A list of GeoTiff files with location of exposed infections at start of simulation.
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# host data
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host_files: ["extdata/simple20x20/host.tif"]
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total_populations_file: "extdata/simple20x20/all_plants.tif"
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use_host_uncertainty: false
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# simulation settings
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random_seed: null # no need to set this primarily used for tests to ensure identical random draws.
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start_date: "2024-01-01"
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end_date: "2024-12-31"
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time_step: "week"
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model_type: "SI"
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season_month_start: 1
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season_month_end: 12
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number_of_iterations: 10
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number_of_cores: 2
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output_frequency: "year"
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output_frequency_n: 1
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mask: null
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# weather
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use_lethal_temperature: false
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lethal_temperature_file: ""
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lethal_temperature: -15
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lethal_temperature_month: 1
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use_overwinter_survival: false
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overwinter_survival_rate_month: 3
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overwinter_survival_rate_day: 15
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overwinter_survival_rates_file: ""
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use_temperature: false
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temperature_coefficient_file: ""
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temperature_coefficient_sd_file: ""
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use_precipitation: false
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precipitation_coefficient_file: ""
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precipitation_coefficient_sd_file: ""
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weather_type: "deterministic"
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# mortality
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mortality_frequency: "year"
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mortality_frequency_n: 1
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# treatments
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use_treatment: false
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treatments_file: ""
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treatment_dates: ["2024-12-24"]
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treatment_method: "ratio"
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pesticide_durations: [0]
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pesticide_efficacy: 1.0
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use_quarantine: false
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quarantine_areas_file: ""
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quarantine_directions: ""
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# dispersal
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natural_kernel_type: "cauchy"
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natural_dir: "NONE"
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anthropogenic_kernel_type: "cauchy"
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anthropogenic_dir: "NONE"
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# only used if anthropogenic_kernel_type == "network"
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network_files: [""]
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network_movement_types: ["walk"]
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network_min_distances: [0]
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network_max_distances: [0]
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network_weights: [1]
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# host movement
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use_movements: false # Boolean for moving hosts (used when animals move from farm to farm)
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movements_file: ""
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# stochasticity
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use_multiple_random_seeds: false
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multiple_random_seeds_file: null
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generate_stochasticity: true
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establishment_stochasticity: true
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movement_stochasticity: true
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dispersal_stochasticity: true
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establishment_probability: 0.5
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dispersal_percentage: 0.99
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use_spreadrates: false
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use_overpopulation_movements: false
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overpopulation_percentage: 0.75
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leaving_percentage: 0.5
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leaving_scale_coefficient: 5
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# soil_pests
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use_soils: false
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soil_starting_pest_file: ""
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start_with_soil_populations: false
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dispersers_to_soils_percentage: 0
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# validation and calibration
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infected_val_cal_file: "" # GeoTiff file with the infections in which to compare the validation/calibration results with.
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# calibration only parameters
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perform_calibration: false
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params_to_estimate: [true, true, true, true, false, false] # Position 1 = reproductive rate, 2 =
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prior_means: [0, 0, 0, 0, 0, 0]
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prior_cov_matrix: [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]
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prior_number_of_observations: 0 # observations that have been conducted at the start of the simulation
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number_of_observations: 0 # observations that were conducted during the simulation for validation/calibration (these are samples taken to confirm presence/absence and/or abundance)
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success_metric: "MCC"
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verbose: true
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natural_kappa: 0
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anthropogenic_kappa: 0
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calibration_method: "ABC" # Which method of calibration to use ABC or MCMC. We recommend ABC as it tends to provide more robust and accurate parameter sets.
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# ABC Parameters
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generation_size: 1000
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number_of_generations: 7
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# validation only
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perform_validation: false
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point_file: "" # only if you want to validate to specific point data ()
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use_configuration: false # Use if you want to calculate configuration disagreement. This takes longer to compute simulation statistics and success metrics).
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# Model API only never used unless you are pulling data from an S3 bucket in the cloud
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use_s3: false
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bucket: ""

‎inst/extdata/configs_configuration/test_config_anthropogenic_kernel_error.yml‎

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# File paths for input and output data
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input_path: "C:/Users/cjone/Projects/rpops/inst/extdata" # folder with inputs
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output_path: "C:/Users/cjone/Projects/rpops/inst/extdata/simple20x20/outputs" # folder to write outputs to
4+
5+
# pest parameters
6+
starting_infected_files: ["extdata/simple20x20/infected_single.tif"] # GeoTiff File with the locations of initial infections to start the simulation
7+
parameter_means_file: "extdata/parameter_means_default.csv" # CSV File with the parameter means from the calibration
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parameter_cov_matrix_file: "extdata/parameter_cov_matrix_default.csv" # CSV File with the parameter covariance matrix from the calibration
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pest_host_table: "extdata/pest_host_table_singlehost.csv" # CSV file with the pest host table
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competency_table: "extdata/competency_table_singlehost.csv" # CSV file with the compentency table
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county_level_infection_data: false # is your infection data county level only
12+
use_initial_condition_uncertainty: false # Are you providing a mean and standard deviation for your starting infection files. This allows for propogating uncertainty through the model.
13+
start_exposed: false # Should you start with your known infections as exposed. Useful for simulating inoculation experiments.
14+
latency_period: 0 # what is the lantent period of your pathogen?
15+
exposed_files: [""] # A list of GeoTiff files with location of exposed infections at start of simulation.
16+
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# host data
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host_files: ["extdata/simple20x20/host.tif"]
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total_populations_file: "extdata/simple20x20/all_plants.tif"
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use_host_uncertainty: false
21+
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# simulation settings
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random_seed: null # no need to set this primarily used for tests to ensure identical random draws.
24+
start_date: "2024-01-01"
25+
end_date: "2024-12-31"
26+
time_step: "week"
27+
model_type: "SI"
28+
season_month_start: 1
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season_month_end: 12
30+
number_of_iterations: 10
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number_of_cores: 2
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output_frequency: "year"
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output_frequency_n: 1
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mask: null
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# weather
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use_lethal_temperature: false
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lethal_temperature_file: ""
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lethal_temperature: -15
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lethal_temperature_month: 1
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use_overwinter_survival: false
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overwinter_survival_rate_month: 3
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overwinter_survival_rate_day: 15
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overwinter_survival_rates_file: ""
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use_temperature: false
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temperature_coefficient_file: ""
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temperature_coefficient_sd_file: ""
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use_precipitation: false
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precipitation_coefficient_file: ""
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precipitation_coefficient_sd_file: ""
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weather_type: "deterministic"
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# mortality
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mortality_frequency: "year"
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mortality_frequency_n: 1
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# treatments
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use_treatment: false
59+
treatments_file: ""
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treatment_dates: ["2024-12-24"]
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treatment_method: "ratio"
62+
pesticide_durations: [0]
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pesticide_efficacy: 1.0
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use_quarantine: false
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quarantine_areas_file: ""
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quarantine_directions: ""
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# dispersal
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natural_kernel_type: "cauchy"
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natural_dir: "NONE"
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anthropogenic_kernel_type: "goodbye"
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anthropogenic_dir: "NONE"
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# only used if anthropogenic_kernel_type == "network"
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network_files: [""]
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network_movement_types: ["walk"]
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network_min_distances: [0]
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network_max_distances: [0]
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network_weights: [1]
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# host movement
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use_movements: false # Boolean for moving hosts (used when animals move from farm to farm)
82+
movements_file: ""
83+
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# stochasticity
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use_multiple_random_seeds: false
86+
multiple_random_seeds_file: null
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generate_stochasticity: true
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establishment_stochasticity: true
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movement_stochasticity: true
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dispersal_stochasticity: true
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establishment_probability: 0.5
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dispersal_percentage: 0.99
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use_spreadrates: false
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use_overpopulation_movements: false
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overpopulation_percentage: 0.75
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leaving_percentage: 0.5
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leaving_scale_coefficient: 5
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# soil_pests
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use_soils: false
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soil_starting_pest_file: ""
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start_with_soil_populations: false
103+
dispersers_to_soils_percentage: 0
104+
105+
# validation and calibration
106+
infected_val_cal_file: "" # GeoTiff file with the infections in which to compare the validation/calibration results with.
107+
108+
# calibration only parameters
109+
perform_calibration: false
110+
params_to_estimate: [true, true, true, true, false, false] # Position 1 = reproductive rate, 2 =
111+
prior_means: [0, 0, 0, 0, 0, 0]
112+
prior_cov_matrix: [[0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0]]
113+
prior_number_of_observations: 0 # observations that have been conducted at the start of the simulation
114+
number_of_observations: 0 # observations that were conducted during the simulation for validation/calibration (these are samples taken to confirm presence/absence and/or abundance)
115+
success_metric: "MCC"
116+
verbose: true
117+
natural_kappa: 0
118+
anthropogenic_kappa: 0
119+
calibration_method: "ABC" # Which method of calibration to use ABC or MCMC. We recommend ABC as it tends to provide more robust and accurate parameter sets.
120+
# ABC Parameters
121+
generation_size: 1000
122+
number_of_generations: 7
123+
124+
# validation only
125+
perform_validation: false
126+
point_file: "" # only if you want to validate to specific point data ()
127+
use_configuration: false # Use if you want to calculate configuration disagreement. This takes longer to compute simulation statistics and success metrics).
128+
129+
# Model API only never used unless you are pulling data from an S3 bucket in the cloud
130+
use_s3: false
131+
bucket: ""

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