Package 'leapfrog'

Beers Ordinary Graduation with Open-Ended Age Group

Description

Graduates vector from 5-year to single-year age, assuming the final value is an open-ended age group rather than an additional 5-year age group to be graduated.

Usage

beers_open_ended(x)

Arguments

x	vector of length at least 6

---

Get the state space dimensions for a particular model configuration

Description

Get the state space dimensions for a particular model configuration

Usage

get_leapfrog_ss(configuration)

Arguments

configuration

The configuration to get state space for, see list_model_configurations.

Value

State space as a named list

---

Run leapfrog model fit

Description

Run leapfrog model fit

Usage

get_state_space(configuration = "HivFullAgeStratification")

Arguments

configuration

The model configuration to run, see list_model_configurations() for available configurations

Value

The state space for this model configuration.

Examples

s <- get_state_space("HivCoarseAgeStratification")

---

Slice a single year from model state

Description

Slice a single year from model state

Usage

get_time_slice(state, index)

Arguments

state	The model state with time dimension
index	The index of the time step you want to extract

Value

List of model outputs for the specified time step. Can be used as input state for run_model_from_state() and run_model_single_year(). All outputs will have 1 fewer dimension than input state.

---

List the avaialble model configurations

Description

List the avaialble model configurations

Usage

list_model_configurations()

Value

List of available model configurations

---

Process parameters and convert from 1 based indexing in R to 0 based indexing in C++. Also add in any defaults/extra parameters, e.g. h_art_stage_dur.

Description

Process parameters and convert from 1 based indexing in R to 0 based indexing in C++. Also add in any defaults/extra parameters, e.g. h_art_stage_dur.

Usage

process_parameters_to_cpp(parameters)

Arguments

parameters

The list of parameters to feed into the model.

Value

List of parameters with 0 based indexing and defaults.

---

Process parameters and convert from 0 based indexing for C++ to 1 based indexing in R.

Description

Process parameters and convert from 0 based indexing for C++ to 1 based indexing in R.

Usage

process_parameters_to_r(parameters)

Arguments

parameters

List of parameters.

Value

List of parameters with 1 based indexing.

---

Prepare inputs from Spectrum PJNZ

Description

Prepare inputs from Spectrum PJNZ

Usage

process_pjnz(
  pjnz,
  use_coarse_age_groups = FALSE,
  extract_child_params = FALSE,
  bypass_adult = FALSE
)

Arguments

pjnz	path to PJNZ file
use_coarse_age_groups	use the coarse age stratification
extract_child_params	If TRUE, then child parameters required to run the child model will be extracted. If FALSE, only adult parameters will be extracted from the PJNZ.
bypass_adult	produce parameters that will bypass the adult model when running the child model variant

Value

list of input parameters

Examples

pjnz <- system.file(
  "pjnz/bwa_aim-adult-art-no-special-elig_v6.13_2022-04-18.PJNZ",
  package = "leapfrog")
parameters <- process_pjnz(pjnz)

---

Read parameters from HDF5 file format. This implicitly processes the parameters from C++ 0 based indexing to R 1 based indexing.

Description

Read parameters from HDF5 file format. This implicitly processes the parameters from C++ 0 based indexing to R 1 based indexing.

Usage

read_parameters(file_path)

Arguments

file_path

HDF5 file to read

---

Run leapfrog model fit

Description

Run leapfrog model fit

Usage

run_model(
  parameters,
  configuration = "HivFullAgeStratification",
  output_years = seq(1970, 2030)
)

Arguments

parameters	Projection parameters
configuration	The model configuration to run, see list_model_configurations() for available configurations
output_years	Which years of the model to return from the simulation, defaults to all years from 1970 to 2030. Also used to control what years the simulation is run for. If output only 2030, simulation will be run from projection_start_year passed in the parameters list.

Value

List of model outputs, where the last dimension of each element is time, e.g. p_totpop state variable has dimensions 81 x 2. If output_years specified has length 61 then the p_totpop output will have dimensions 81 x 2 x 61.

Examples

pjnz <- system.file(
  "pjnz/bwa_aim-adult-art-no-special-elig_v6.13_2022-04-18.PJNZ",
  package = "leapfrog", mustWork = TRUE)
parameters <- process_pjnz(pjnz, use_coarse_age_groups = TRUE)
out <- run_model(parameters, "HivCoarseAgeStratification", 1970:2030)

---

Run leapfrog model fit from initial state

Description

Run leapfrog model fit from initial state

Usage

run_model_from_state(
  parameters,
  configuration,
  initial_state,
  simulation_start_year,
  output_years = seq(1970, 2030)
)

Arguments

parameters	Projection parameters
configuration	The model configuration to run, see list_model_configurations() for available configurations
initial_state	The model will run from this initial state
simulation_start_year	Start the model simulation from a particular year
output_years	Which years of the model to return from the simulation, defaults to all years from 1970 to 2030. Also used to control what years the simulation is run for. If output only 2030, simulation will be run from projection_start_year passed in the parameters list.

Value

List of model outputs, where the last dimension of each element is time, e.g. p_totpop state variable has dimensions 81 x 2. If output_years specified has length 61 then the p_totpop output will have dimensions 81 x 2 x 61.

Examples

pjnz <- system.file(
  "pjnz/bwa_aim-adult-art-no-special-elig_v6.13_2022-04-18.PJNZ",
  package = "leapfrog", mustWork = TRUE)
parameters <- process_pjnz(pjnz, use_coarse_age_groups = TRUE)
out_first_half_years <- run_model(parameters, "HivCoarseAgeStratification", 1970:2000)
out_second_half_years <- run_model_from_state(
  parameters,
  "HivCoarseAgeStratification",
  get_time_slice(out_first_half_years, 31),
  2000,
  2001:2030)

---

Run leapfrog model fit for a single year

Description

Run leapfrog model fit for a single year

Usage

run_model_single_year(
  parameters,
  configuration,
  initial_state,
  simulation_start_year
)

Arguments

parameters	Projection parameters
configuration	The model configuration to run, see list_model_configurations() for available configurations
initial_state	The model will run from this initial state
simulation_start_year	Start the model simulation from this year

Value

List of model outputs without the last time dimension. This is different from run_model_from_state() and run_model() that do include the last time dimension. Since only the next time step is returned, dropping the time dimensions makes it easier to feed the returned list into the next single year model run. In contrast to run_model_from_state() the p_totpop output will have dimensions 81 x 2 not 81 x 2 x 61.

Examples

pjnz <- system.file(
  "pjnz/bwa_aim-adult-art-no-special-elig_v6.13_2022-04-18.PJNZ",
  package = "leapfrog", mustWork = TRUE)
parameters <- process_pjnz(pjnz, use_coarse_age_groups = TRUE)
out_first_half_years <- run_model(parameters, "HivCoarseAgeStratification", 1970:2000)
prev_state <- get_time_slice(out_first_half_years, 31)
for (i in 2001:2029) {
  new_state <- run_model_single_year(parameters, "HivCoarseAgeStratification", prev_state, i)
  # Do things with new state, other processes, saving output etc.
  prev_state <- new_state
}

---

Save parameters to HDF5 file format. This implicitly processes the parameters to C++ 0 based indexing.

Description

Save parameters to HDF5 file format. This implicitly processes the parameters to C++ 0 based indexing.

Usage

save_parameters(df, file_path)

Arguments

df	list/dataframe to serialize
file_path	where to save the HDF5 file

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