Evaluate a Monte Carlo Model Expression and create an mcmcmodule
Source:R/eval_module.R
eval_module.RdTakes a set of Monte Carlo model expressions and evaluates them and creates an mcmcmodule containing results and metadata.
Usage
eval_module(
exp,
data,
param_names = NULL,
prev_mcmodule = NULL,
summary = FALSE,
mctable = set_mctable(),
data_keys = set_data_keys(),
create_nodes = TRUE
)Arguments
- exp
Model expression or list of expressions to evaluate
- data
Input data frame containing model parameters
- param_names
Named vector for parameter renaming (optional)
- prev_mcmodule
Previous module(s) for dependent calculations
- summary
Logical; whether to calculate summary statistics
- mctable
Monte Carlo configuration table
- data_keys
List of key columns for each dataset
- create_nodes
Logical; whether to create new nodes from data
Examples
# Basic usage with single expression
eval_module(
exp = imports_exp,
data = imports_data,
mctable = imports_mctable,
data_keys = imports_data_keys
)
#>
#> imports evaluated
#>
#> mcmodule created (expressions: )
#> $data
#> $data$imports_data
#> pathogen origin h_prev_min h_prev_max w_prev_min w_prev_max farms_n
#> 1 a nord 0.08 0.10 0.15 0.2 5
#> 2 a south 0.02 0.05 0.15 0.2 10
#> 3 a east 0.10 0.15 0.15 0.2 7
#> 4 b nord 0.50 0.70 0.45 0.6 5
#> 5 b south 0.25 0.30 0.37 0.4 10
#> 6 b east 0.30 0.50 0.45 0.6 7
#> animals_n_mean animals_n_sd test_origin test_sensi_min test_sensi_mode
#> 1 100 6 sometimes 0.89 0.90
#> 2 130 10 sometimes 0.89 0.90
#> 3 140 12 never 0.89 0.90
#> 4 100 2 always 0.80 0.85
#> 5 130 4 sometimes 0.80 0.85
#> 6 140 3 unknown 0.80 0.85
#> test_sensi_max
#> 1 0.91
#> 2 0.91
#> 3 0.91
#> 4 0.90
#> 5 0.90
#> 6 0.90
#>
#>
#> $exp
#> {
#> inf_a <- w_prev
#> false_neg_a <- inf_a * test_origin * (1 - test_sensi)
#> no_test_a <- inf_a * (1 - test_origin)
#> no_detect_a <- false_neg_a + no_test_a
#> }
#>
#> $node_list
#> $node_list$w_prev
#> $node_list$w_prev$type
#> [1] "in_node"
#>
#> $node_list$w_prev$mc_func
#> [1] "runif"
#>
#> $node_list$w_prev$description
#> [1] "Within herd prevalence"
#>
#> $node_list$w_prev$inputs_col
#> [1] "w_prev_min" "w_prev_max"
#>
#> $node_list$w_prev$input_dataset
#> [1] "prevalence_region"
#>
#> $node_list$w_prev$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$w_prev$module
#> [1] "imports"
#>
#> $node_list$w_prev$mc_name
#> [1] "w_prev"
#>
#> $node_list$w_prev$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1001 1 6 1 0.15 0.175 0.175 0.2 0 V each
#> 2 x numeric 1001 1 6 2 0.15 0.176 0.176 0.2 0 V each
#> 3 x numeric 1001 1 6 3 0.15 0.175 0.174 0.2 0 V each
#> 4 x numeric 1001 1 6 4 0.45 0.525 0.526 0.6 0 V each
#> 5 x numeric 1001 1 6 5 0.37 0.385 0.385 0.4 0 V each
#> 6 x numeric 1001 1 6 6 0.45 0.525 0.523 0.6 0 V each
#>
#> $node_list$w_prev$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$test_origin
#> $node_list$test_origin$type
#> [1] "in_node"
#>
#> $node_list$test_origin$description
#> [1] "Probability of the animals being tested in origin"
#>
#> $node_list$test_origin$inputs_col
#> [1] "test_origin"
#>
#> $node_list$test_origin$input_dataset
#> [1] "prevalence_region"
#>
#> $node_list$test_origin$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$test_origin$module
#> [1] "imports"
#>
#> $node_list$test_origin$mc_name
#> [1] "test_origin"
#>
#> $node_list$test_origin$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1 1 6 1 0.5 0.5 0.5 0.5 0 0 each
#> 2 x numeric 1 1 6 2 0.5 0.5 0.5 0.5 0 0 each
#> 3 x numeric 1 1 6 3 0.0 0.0 0.0 0.0 0 0 each
#> 4 x numeric 1 1 6 4 1.0 1.0 1.0 1.0 0 0 each
#> 5 x numeric 1 1 6 5 0.5 0.5 0.5 0.5 0 0 each
#> 6 x numeric 1 1 6 6 0.0 0.0 0.0 0.0 0 0 each
#>
#> $node_list$test_origin$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$test_sensi
#> $node_list$test_sensi$type
#> [1] "in_node"
#>
#> $node_list$test_sensi$mc_func
#> [1] "rpert"
#>
#> $node_list$test_sensi$description
#> [1] "Test sensitivity"
#>
#> $node_list$test_sensi$inputs_col
#> [1] "test_sensi_min" "test_sensi_mode" "test_sensi_max"
#>
#> $node_list$test_sensi$input_dataset
#> [1] "test_sensitivity"
#>
#> $node_list$test_sensi$keys
#> [1] "pathogen"
#>
#> $node_list$test_sensi$module
#> [1] "imports"
#>
#> $node_list$test_sensi$mc_name
#> [1] "test_sensi"
#>
#> $node_list$test_sensi$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1001 1 6 1 0.891 0.900 0.900 0.908 0 V each
#> 2 x numeric 1001 1 6 2 0.891 0.900 0.900 0.909 0 V each
#> 3 x numeric 1001 1 6 3 0.890 0.900 0.900 0.909 0 V each
#> 4 x numeric 1001 1 6 4 0.804 0.850 0.850 0.895 0 V each
#> 5 x numeric 1001 1 6 5 0.803 0.850 0.851 0.894 0 V each
#> 6 x numeric 1001 1 6 6 0.803 0.849 0.849 0.897 0 V each
#>
#> $node_list$test_sensi$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$inf_a
#> $node_list$inf_a$node_exp
#> [1] "w_prev"
#>
#> $node_list$inf_a$type
#> [1] "out_node"
#>
#> $node_list$inf_a$inputs
#> [1] "w_prev"
#>
#> $node_list$inf_a$module
#> [1] "imports"
#>
#> $node_list$inf_a$mc_name
#> [1] "inf_a"
#>
#> $node_list$inf_a$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$inf_a$param
#> [1] "w_prev"
#>
#> $node_list$inf_a$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1001 1 6 1 0.15 0.175 0.175 0.2 0 V each
#> 2 x numeric 1001 1 6 2 0.15 0.176 0.176 0.2 0 V each
#> 3 x numeric 1001 1 6 3 0.15 0.175 0.174 0.2 0 V each
#> 4 x numeric 1001 1 6 4 0.45 0.525 0.526 0.6 0 V each
#> 5 x numeric 1001 1 6 5 0.37 0.385 0.385 0.4 0 V each
#> 6 x numeric 1001 1 6 6 0.45 0.525 0.523 0.6 0 V each
#>
#> $node_list$inf_a$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$false_neg_a
#> $node_list$false_neg_a$node_exp
#> [1] "inf_a * test_origin * (1 - test_sensi)"
#>
#> $node_list$false_neg_a$type
#> [1] "out_node"
#>
#> $node_list$false_neg_a$inputs
#> [1] "inf_a" "test_origin" "test_sensi"
#>
#> $node_list$false_neg_a$module
#> [1] "imports"
#>
#> $node_list$false_neg_a$mc_name
#> [1] "false_neg_a"
#>
#> $node_list$false_neg_a$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$false_neg_a$param
#> [1] "inf_a" "test_origin" "test_sensi"
#>
#> $node_list$false_neg_a$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type
#> 1 x numeric 1001 1 6 1 0.00700 0.00876 0.00876 0.0107 0 V
#> 2 x numeric 1001 1 6 2 0.00702 0.00879 0.00880 0.0107 0 V
#> 3 x numeric 1001 1 6 3 0.00000 0.00000 0.00000 0.0000 0 V
#> 4 x numeric 1001 1 6 4 0.05094 0.07866 0.07829 0.1120 0 V
#> 5 x numeric 1001 1 6 5 0.01979 0.02890 0.02880 0.0387 0 V
#> 6 x numeric 1001 1 6 6 0.00000 0.00000 0.00000 0.0000 0 V
#> outm
#> 1 each
#> 2 each
#> 3 each
#> 4 each
#> 5 each
#> 6 each
#>
#> $node_list$false_neg_a$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$no_test_a
#> $node_list$no_test_a$node_exp
#> [1] "inf_a * (1 - test_origin)"
#>
#> $node_list$no_test_a$type
#> [1] "out_node"
#>
#> $node_list$no_test_a$inputs
#> [1] "inf_a" "test_origin"
#>
#> $node_list$no_test_a$module
#> [1] "imports"
#>
#> $node_list$no_test_a$mc_name
#> [1] "no_test_a"
#>
#> $node_list$no_test_a$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$no_test_a$param
#> [1] "inf_a" "test_origin"
#>
#> $node_list$no_test_a$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1001 1 6 1 0.075 0.0874 0.0876 0.1 0 V each
#> 2 x numeric 1001 1 6 2 0.075 0.0879 0.0881 0.1 0 V each
#> 3 x numeric 1001 1 6 3 0.150 0.1748 0.1741 0.2 0 V each
#> 4 x numeric 1001 1 6 4 0.000 0.0000 0.0000 0.0 0 V each
#> 5 x numeric 1001 1 6 5 0.185 0.1925 0.1924 0.2 0 V each
#> 6 x numeric 1001 1 6 6 0.450 0.5250 0.5228 0.6 0 V each
#>
#> $node_list$no_test_a$data_name
#> [1] "imports_data"
#>
#>
#> $node_list$no_detect_a
#> $node_list$no_detect_a$node_exp
#> [1] "false_neg_a + no_test_a"
#>
#> $node_list$no_detect_a$type
#> [1] "out_node"
#>
#> $node_list$no_detect_a$inputs
#> [1] "false_neg_a" "no_test_a"
#>
#> $node_list$no_detect_a$module
#> [1] "imports"
#>
#> $node_list$no_detect_a$mc_name
#> [1] "no_detect_a"
#>
#> $node_list$no_detect_a$keys
#> [1] "pathogen" "origin"
#>
#> $node_list$no_detect_a$param
#> [1] "false_neg_a" "no_test_a"
#>
#> $node_list$no_detect_a$mcnode
#> node mode nsv nsu nva variate min mean median max Nas type outm
#> 1 x numeric 1001 1 6 1 0.0821 0.0962 0.0963 0.110 0 V each
#> 2 x numeric 1001 1 6 2 0.0823 0.0966 0.0969 0.110 0 V each
#> 3 x numeric 1001 1 6 3 0.1500 0.1748 0.1741 0.200 0 V each
#> 4 x numeric 1001 1 6 4 0.0509 0.0787 0.0783 0.112 0 V each
#> 5 x numeric 1001 1 6 5 0.2056 0.2214 0.2213 0.238 0 V each
#> 6 x numeric 1001 1 6 6 0.4500 0.5250 0.5228 0.600 0 V each
#>
#> $node_list$no_detect_a$data_name
#> [1] "imports_data"
#>
#>
#>
#> $modules
#> [1] "imports"
#>
#> attr(,"class")
#> [1] "mcmodule"