# METHOD_OPTIONS

Type: dict_record

method options for TABLE

Example:-

    METHOD_OPTIONS:
        py_module: table

## py_module

Type: one_of(table)

Python module required to process this script file

Example:-

    py_module: table

# PARALLEL

Type: one_of_record

one of many possible servers

Example:-

    PARALLEL:
        SINGLE: {progress_bar_length: 0}

## SINGLE

Type: dict_record

single process server spec.

Example:-

    SINGLE:
        progress_bar_length: 0

### progress_bar_length

Type: int

Length of progress bar on screen (default=0, off)

Example:-

    progress_bar_length: 0

## MPI_WORKERS

Type: dict_record

MPI local server spec.

Example:-

    MPI_WORKERS:
        n_workers: auto
        cpu_load: 1.0
        progress_bar_length: 0

### n_workers

Type: int / auto

Number of workers to use on this machine, defaults to number of processors, but could be more or fewer.

Example:-

    n_workers: auto

### cpu_load

Type: float

Desired load on CPU as a decimal greater than 0.0 (0%) and less than or equal to 1.0 (100%)

Example:-

    cpu_load: 1.0

### progress_bar_length

Type: int

Length of progress bar on screen (default=0, off)

Example:-

    progress_bar_length: 0

# FILE_PATHS

Type: dict_record

file paths

Example:-

    FILE_PATHS:
        output_folder: auto
        log_folder: auto
        table_file_ext: ['csv']
        delete_old_files_flag: False
        solutions:
            initial_fit_ipred: sol0/solution.pyml
            final_fit_ipred: solN/solution.pyml

## output_folder

Type: output_folder / auto

Output folder - results of computation stored here

Example:-

    output_folder: auto

## log_folder

Type: output_folder / auto

Log folder - log files stored here

Example:-

    log_folder: auto

## table_file_ext

Type: list_of(csv)

Output file extension; determines tabular output file format.

Example:-

    table_file_ext: ['csv']

## delete_old_files_flag

Type: bool

Option to delete any existing files before running.

Example:-

    delete_old_files_flag: False

## solutions

Type: dict

Solutions to compare

Example:-

    solutions:
        initial_fit_ipred: sol0/solution.pyml
        final_fit_ipred: solN/solution.pyml

# DATA_FIELDS

Type: dict_record

data fields for popy.dat.fields object

Example:-

    DATA_FIELDS:
        type_field: TYPE
        id_field: ID
        time_field: TIME

## type_field

Type: str

Field name in data file that contains row type info, e.g. obs/dose etc

Example:-

    type_field: TYPE

## id_field

Type: str

Field name in data file that contains identity string for each data row e.g. obs/dose etc

Example:-

    id_field: ID

## time_field

Type: str

Field name in data file that contains time or event for each data row

Example:-

    time_field: TIME

# PREPROCESS

Type: verbatim

Code that preprocesses the input data. Use this to filter rows and create derived covariates.

Example:-

    PREPROCESS: |

# OUTPUT_TABLES

Type: list_record

List of tables to create.

Example:-

    OUTPUT_TABLES:
        - TABLE:
            input_solution: final_fit_ipred
            output_file: my_table.csv
            cx_columns: "*"
            mx_columns: "*"
            sx_columns: "*"
            px_columns: "*"

## TABLE

Type: dict_record

Table properties.

Example:-

    TABLE:
        input_solution: final_fit_ipred
        output_file: my_table.csv
        cx_columns: "*"
        mx_columns: "*"
        sx_columns: "*"
        px_columns: "*"

### input_solution

Type: str

Label of the solution to parse

Example:-

    input_solution: final_fit_ipred

### output_file

Type: output_file

Destination file for table

Example:-

    output_file: my_table.csv

### cx_columns

Type: list(str) / star

Columns from covariates/observations table to output

Example:-

    cx_columns: "*"

### mx_columns

Type: list(str) / star

Columns from model_params table to output

Example:-

    mx_columns: "*"

### sx_columns

Type: list(str) / star

Columns from states table to output

Example:-

    sx_columns: "*"

### px_columns

Type: list(str) / star

Columns from predictions table to output

Example:-

    px_columns: "*"