Package index
-
validate_submission()
- Validate a submitted model data file.
-
submission_tmpl()
- Create a model output submission file template
Higher level validation functions
Functions combining appropriate check unit test used for higher level validations. All return hub_validations
S3 class objects.
-
validate_model_data()
- Validate the contents of a submitted model data file
-
validate_model_file()
- Valid file level properties of a submitted model output file.
-
validate_model_metadata()
- Valid properties of a metadata file.
-
validate_pr()
- Validate Pull Request
-
validate_submission()
- Validate a submitted model data file.
-
validate_submission_time()
- Validate a submitted model data file submission time.
-
check_for_errors()
- Raise conditions stored in a
hub_validations
S3 object
-
check_config_hub_valid()
- Check hub correctly configured
-
check_file_exists()
- Check file exists at the file path specified
-
check_file_format()
- Check file format is accepted by hub.
-
check_file_location()
- Check file is being submitted to the correct folder
-
check_file_n()
- Check number of files submitted per round does not exceed the allowed number of submissions per team.
-
check_file_name()
- Check a model output file name can be correctly parsed.
-
check_file_read()
- Check file can be read successfully
-
check_for_errors()
- Raise conditions stored in a
hub_validations
S3 object
-
check_metadata_file_exists()
- Check whether a metadata schema file exists
-
check_metadata_file_ext()
- Check file is being submitted to the correct folder
-
check_metadata_file_location()
- Check that the metadata file is being submitted to the correct folder
-
check_metadata_file_name()
- Check whether the file name of a metadata file matches the model_id or combination of team_abbr and model_abbr specified within the metadata file
-
check_metadata_matches_schema()
- Check whether a metadata file matches the schema provided by the hub
-
check_metadata_schema_exists()
- Check whether a metadata schema file exists
-
check_submission_metadata_file_exists()
- Check whether a metadata file for the given model exists
-
check_submission_time()
- Checks submission is within the valid submission window for a given round.
-
check_tbl_col_types()
- Check model data column data types
-
check_tbl_colnames()
- Check column names of model output data
-
check_tbl_match_round_id()
- Check model output data tbl round ID matches submission round ID.
-
check_tbl_rows_unique()
- Check model data rows are all unique
-
check_tbl_spl_compound_taskid_set()
- Check model output data tbl sample compound task id sets for each modeling task match or are coarser than the expected set defined in the config.
-
check_tbl_spl_compound_tid()
- Check model output data tbl samples contain single unique values for each compound task ID within individual samples
-
check_tbl_spl_n()
- Check model output data tbl samples contain the appropriate number of samples for a given compound idx.
-
check_tbl_spl_non_compound_tid()
- Check model output data tbl samples contain single unique combination of non-compound task ID values across all samples
-
check_tbl_unique_round_id()
- Check model output data tbl contains a single unique round ID.
-
check_tbl_value_col()
- Check output type values of model output data against config
-
check_tbl_value_col_ascending()
- Check that
quantile
andcdf
output type values of model output data are non-descending
-
check_tbl_value_col_sum1()
- Check that
pmf
output type values of model output data sum to 1.
-
check_tbl_values()
- Check model output data tbl contains valid value combinations
-
check_tbl_values_required()
- Check all required task ID/output type/output type ID value combinations present in model data.
-
check_valid_round_id()
- Check whether the
round_id
determined for the submission is valid
-
check_valid_round_id_col()
- Check that any round_id_col name provided or extracted from the hub config is valid.
Optional unit validation checks
Optional unit validation checks. All return hub_check
S3 class objects and need to be deployed via validations.yml
file.
-
opt_check_metadata_team_max_model_n()
- Check that submitting team does not exceed maximum number of allowed models per team
-
opt_check_tbl_col_timediff()
- Check time difference between values in two date columns equal a defined period.
-
opt_check_tbl_counts_lt_popn()
- Check that predicted values per location are less than total location population.
-
opt_check_tbl_horizon_timediff()
- Check time difference between values in two date columns equals a defined time period defined by values in a horizon column
Custom unit validation checks
Functions to support creation and deployment of custom unit validation checks
-
create_custom_check()
- Create a custom validation check function template file.
-
capture_check_cnd()
- Capture a condition of the result of validation check.
-
capture_check_info()
- Capture a simple info message condition
-
capture_exec_error()
- Capture an execution error condition
-
capture_exec_warning()
- Capture an execution warning condition
-
is_success()
is_failure()
is_error()
is_info()
not_pass()
is_exec_error()
is_exec_warn()
is_any_error()
- Get status of a hub check
-
parse_file_name()
- Parse model output file metadata from file name
-
read_model_out_file()
- Read a model output file
-
try_check()
- Wrap check expression in try to capture check execution errors
-
expand_model_out_grid()
- Create expanded grid of valid task ID and output type value combinations
-
get_tbl_compound_taskid_set()
- Detect the compound_taskid_set for a tbl for each modeling task in a given round.
-
match_tbl_to_model_task()
- Match model output
tbl
data to their model tasks inconfig_tasks
.
-
print(<hub_validations>)
- Print results of
validate_...()
function as a bullet list
-
print(<pr_hub_validations>)
- Print results of
validate_pr()
function as a bullet list
-
combine()
- Concatenate
hub_validations
S3 class objects
-
new_hub_validations()
as_hub_validations()
- Create new or convert list to
hub_validations
S3 class object