polaris.ocean.tasks.sphere_transport.analysis.Analysis

class polaris.ocean.tasks.sphere_transport.analysis.Analysis(component, subdir, case_name, dependencies, refinement='both')

A step for analyzing the output from sphere transport test cases

Variables:

• resolutions (list of float) – The resolutions of the meshes that have been run

• case_name (str) – The name of the test case

__init__(component, subdir, case_name, dependencies, refinement='both')

Create the step

Parameters:

• component (polaris.Component) – The component the step belongs to

• subdir (str) – The subdirectory that the step resides in

• case_name (str) – The name of the test case

• dependencies (dict of dict of polaris.Steps) – The dependencies of this step

• refinement (str, optional) – Refinement type. One of ‘space’, ‘time’ or ‘both’ indicating both space and time

Methods

__init__(component, subdir, case_name, ...)	Create the step
add_dependency(step[, name])	Add step as a dependency of this step (i.e. this step can't run until the dependency has finished).
add_input_file([filename, target, database, ...])	Add an input file to the step (but not necessarily to the MPAS model).
add_output_file(filename[, validate_vars])	Add the output file that must be produced by this step and may be made available as an input to steps, perhaps in other tasks.
compute_error(refinement_factor, variable_name)	Compute the error for a given resolution
constrain_resources(available_resources)	Constrain cpus_per_task and ntasks based on the number of cores available to this step
convergence_parameters([field_name])	Get convergence parameters
exact_solution(refinement_factor, ...[, zidx])	Get the exact solution
get_output_field(refinement_factor, ...[, zidx])	Get the model output field at the given time and z index
map_from_native_model_vars(ds)	If the model is Omega, rename dimensions and variables in a dataset from their Omega names to the MPAS-Ocean equivalent (appropriate for datasets that are output from the model)
map_to_native_model_vars(ds)	If the model is Omega, rename dimensions and variables in a dataset from their MPAS-Ocean names to the Omega equivalent (appropriate for input datasets like an initial condition)
open_model_dataset(filename, **kwargs)	Open the given dataset, mapping variable and dimension names from Omega to MPAS-Ocean names if appropriate
plot_convergence(variable_name, title, zidx)	Compute the error norm for each resolution and produce a convergence plot
process_inputs_and_outputs()	Process the inputs to and outputs from a step added with polaris.Step.add_input_file() and polaris.Step.add_output_file().
run()	Run this step of the test case
runtime_setup()	Update attributes of the step at runtime before calling the run() method.
set_resources([cpus_per_task, ...])	Update the resources for the subtask.
set_shared_config(config[, link])	Replace the step's config parser with the shared config parser
setup()	Add input files based on resolutions, which may have been changed by user config options
validate_baselines()	Compare variables between output files in this step and in the same step from a baseline run if one was provided.
write_model_dataset(ds, filename)	Write out the given dataset, mapping dimension and variable names from MPAS-Ocean to Omega names if appropriate