# This software is open source software available under the BSD-3 license.
#
# Copyright (c) 2022 Triad National Security, LLC. All rights reserved.
# Copyright (c) 2022 Lawrence Livermore National Security, LLC. All rights
# reserved.
# Copyright (c) 2022 UT-Battelle, LLC. All rights reserved.
#
# Additional copyright and license information can be found in the LICENSE file
# distributed with this code, or at
# https://raw.githubusercontent.com/MPAS-Dev/MPAS-Analysis/main/LICENSE
"""
Utility functions for reading a single MPAS file into xarray and for removing
all but a given list of variables from a data set.
"""
# Authors
# -------
# Xylar Asay-Davis
import xarray
from mpas_analysis.shared.timekeeping.utility import \
string_to_days_since_date, days_to_datetime
[docs]
def open_mpas_dataset(fileName, calendar,
timeVariableNames=['xtime_startMonthly',
'xtime_endMonthly'],
variableList=None, startDate=None, endDate=None):
"""
Opens and returns an xarray data set given file name(s) and the MPAS
calendar name.
Parameters
----------
fileName : str
File path to read
calendar : {``'gregorian'``, ``'noleap'``}, optional
The name of one of the calendars supported by MPAS cores
timeVariableNames : str or list of 2 str, optional
The name of the time variable (typically ``'xtime'``
or ``['xtime_startMonthly', 'xtime_endMonthly']``), or ``None`` if
time does not need to be parsed (and is already in the ``Time``
variable)
variableList : list of strings, optional
If present, a list of variables to be included in the data set
startDate, endDate : string or datetime.datetime, optional
If present, the first and last dates to be used in the data set. The
time variable is sliced to only include dates within this range.
Returns
-------
ds : ``xarray.Dataset``
Raises
------
TypeError
If the time variable has an unsupported type (not a date string).
ValueError
If the time variable is not found in the data set
"""
# Authors
# -------
# Xylar Asay-Davis
ds = xarray.open_dataset(fileName, decode_cf=True, decode_times=False,
lock=False)
if timeVariableNames is not None:
ds = _parse_dataset_time(ds, timeVariableNames, calendar)
if startDate is not None and endDate is not None:
if isinstance(startDate, str):
startDate = string_to_days_since_date(dateString=startDate,
calendar=calendar)
if isinstance(endDate, str):
endDate = string_to_days_since_date(dateString=endDate,
calendar=calendar)
# select only the data in the specified range of dates
ds = ds.sel(Time=slice(startDate, endDate))
if ds.sizes['Time'] == 0:
raise ValueError('The data set contains no Time entries between '
'dates {} and {}.'.format(
days_to_datetime(startDate, calendar=calendar),
days_to_datetime(endDate, calendar=calendar)))
if variableList is not None:
ds = ds[variableList]
return ds
def _parse_dataset_time(ds, inTimeVariableName, calendar,
outTimeVariableName='Time',
referenceDate='0001-01-01'):
"""
A helper function for computing a time coordinate from an MPAS time
variable. Given a data set and a time variable name (or list of 2
time names), returns a new data set with time coordinate
`outTimeVariableName` filled with days since `referenceDate`
Parameters
----------
ds : ``xarray.DataSet``
The data set containing an MPAS time variable to be used to build
an xarray time coordinate.
inTimeVariableName : str or tuple or list of str
The name of the time variable in the MPAS data set that will be
used to build the 'Time' coordinate. The array(s) named by
inTimeVariableName should contain date strings. Typically,
inTimeVariableName is ``'xtime'``. If a list of two variable
names is provided, times from the two are averaged together to
determine the value of the time coordinate. In such cases,
inTimeVariableName is typically
``['xtime_startMonthly', 'xtime_endMonthly']``.
calendar : {'gregorian', 'noleap'}
The name of one of the calendars supported by MPAS cores
outTimeVariableName : str
The name of the coordinate to assign times to, typically 'Time'.
referenceDate : str, optional
The reference date for the time variable, typically '0001-01-01',
taking one of the following forms::
0001-01-01
0001-01-01 00:00:00
Returns
-------
dsOut : ``xarray.DataSet``
A copy of the input data set with the `outTimeVariableName`
coordinate containing the time coordinate parsed from
`inTimeVariableName`.
Raises
------
TypeError
If the time variable has an unsupported type (not a date string
or a floating-pont number of days since the start of the simulatio).
"""
# Authors
# -------
# Xylar Asay-Davis
if isinstance(inTimeVariableName, (tuple, list)):
# we want to average the two
assert(len(inTimeVariableName) == 2)
dsStart = _parse_dataset_time(
ds=ds,
inTimeVariableName=inTimeVariableName[0],
calendar=calendar,
outTimeVariableName=outTimeVariableName,
referenceDate=referenceDate)
dsEnd = _parse_dataset_time(
ds=ds,
inTimeVariableName=inTimeVariableName[1],
calendar=calendar,
outTimeVariableName=outTimeVariableName,
referenceDate=referenceDate)
starts = dsStart[outTimeVariableName].values
ends = dsEnd[outTimeVariableName].values
# replace the time in starts with the mean of starts and ends
dsOut = dsStart.copy()
dsOut.coords['startTime'] = (outTimeVariableName, starts)
dsOut.coords['endTime'] = (outTimeVariableName, ends)
dsOut.coords[outTimeVariableName] = (outTimeVariableName,
[starts[i] +
(ends[i] - starts[i]) / 2
for i in range(len(starts))])
else:
# there is just one time variable (either because we're recursively
# calling the function or because we're not averaging).
timeVar = ds[inTimeVariableName]
if timeVar.dtype != '|S64':
raise TypeError("timeVar of unsupported type {}. String variable "
"expected.".format(timeVar.dtype))
# this is an array of date strings like 'xtime'
# convert to string
timeStrings = [''.join(xtime.astype('U')).strip()
for xtime in timeVar.values]
days = string_to_days_since_date(dateString=timeStrings,
referenceDate=referenceDate,
calendar=calendar)
dsOut = ds.copy()
dsOut.coords[outTimeVariableName] = (outTimeVariableName, days)
return dsOut
# vim: ai ts=4 sts=4 et sw=4 ft=python