mpas_analysis.ocean.compute_anomaly_subtask.ComputeAnomalySubtask

class mpas_analysis.ocean.compute_anomaly_subtask.ComputeAnomalySubtask(parentTask, mpasTimeSeriesTask, outFileName, variableList, movingAveragePoints, subtaskName='computeAnomaly', alter_dataset=None)[source]

A subtask for computing anomalies of moving averages and writing them out.

Attributes:
mpasTimeSeriesTask : MpasTimeSeriesTask

The task that extracts the time series from MPAS monthly output

outFileName : str

The file name (usually without full path) where the resulting data set should be written

variableList : list of str

Variables to be included in the data set

movingAveragePoints : int

The number of points (months) used in the moving average used to smooth the data set

alter_dataset : function

A function that takes an xarray.Dataset and returns an xarray.Dataset for manipulating the data set (e.g. adding a new variable computed from others). This operation is performed before computing moving averages and anomalies, so that these operations are also performed on any new variables added to the data set.

__init__(parentTask, mpasTimeSeriesTask, outFileName, variableList, movingAveragePoints, subtaskName='computeAnomaly', alter_dataset=None)[source]

Construct the analysis task.

Parameters:
parentTask : AnalysisTask

The parent task of which this is a subtask

mpasTimeSeriesTask : MpasTimeSeriesTask

The task that extracts the time series from MPAS monthly output

outFileName : str

The file name (usually without full path) where the resulting data set should be written

variableList : list of str

Variables to be included in the data set

movingAveragePoints : int

The number of points (months) used in the moving average used to smooth the data set

subtaskName : str, optional

The name of the subtask

alter_dataset : function

A function that takes an xarray.Dataset and returns an xarray.Dataset for manipulating the data set (e.g. adding a new variable computed from others). This operation is performed before computing moving averages and anomalies, so that these operations are also performed on any new variables added to the data set.

Methods

__init__(parentTask, mpasTimeSeriesTask, …) Construct the analysis task.
add_subtask(subtask) Add a subtask to this tasks.
check_analysis_enabled(analysisOptionName[, …]) Check to make sure a given analysis is turned on, issuing a warning or raising an exception if not.
check_generate() Determines if this analysis should be generated, based on the generate config option and taskName, componentName and tags.
is_alive() Return whether process is alive
join([timeout]) Wait until child process terminates
run([writeLogFile]) Sets up logging and then runs the analysis task.
run_after(task) Only run this task after the given task has completed.
run_task() Performs analysis of ocean heat content (OHC) from time-series output.
set_start_end_date(section) Set the start and end dates in the config correspond to the start and end years in a given category of analysis
setup_and_check() Perform steps to set up the analysis and check for errors in the setup.
start() Start child process
terminate() Terminate process; sends SIGTERM signal or uses TerminateProcess()

Attributes

BLOCKED
FAIL
READY
RUNNING
SUCCESS
UNSET
authkey
daemon Return whether process is a daemon
exitcode Return exit code of process or None if it has yet to stop
ident Return identifier (PID) of process or None if it has yet to start
name
pid Return identifier (PID) of process or None if it has yet to start
sentinel Return a file descriptor (Unix) or handle (Windows) suitable for waiting for process termination.