#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Apr 19 14:22:34 2018
@author: jonasg
"""
from pyaerocom.helpers import cftime_to_datetime64
from pyaerocom.io.testfiles import get
from pyaerocom import GriddedData
if __name__ == "__main__":
times = GriddedData(get()["models"]["ecmwf_osuite"],
var_name="od550aer").time
for k in range(1000):
ts = cftime_to_datetime64(times.points, times.units)
def check_time_coord(cube, ts_type, year):
"""Method that checks the time coordinate of an iris Cube
This method checks if the time dimension of a cube is accessible and
according to the standard (i.e. fully usable). It only checks, and does not
correct. For the latter, please see :func:`correct_time_coord`.
Parameters
----------
cube : Cube
cube containing data
ts_type : str
temporal resolution of data (e.g. "hourly", "daily"). This information
is e.g. encrypted in the filename of a NetCDF file and may be
accessed using :class:`pyaerocom.io.FileConventionRead`
year : int
interger specifying year of observation, e.g. 2017
Returns
-------
bool
True, if time dimension is ok, False if not
"""
ok = True
test_idx = [0,1,2,7] #7, since last accessible index in a 3hourly dataset of one day is 7
try:
try:
t = cube.coord("time")
except:
raise AttributeError("Cube does not contain time dimension")
if not isinstance(t, iris.coords.DimCoord):
raise AttributeError("Time is not a DimCoord instance")
try:
cftime_to_datetime64(0, cfunit=t.units)
except:
raise ValueError("Could not convert time unit string")
tres_np = TSTR_TO_NP_TD[ts_type]
conv = TSTR_TO_NP_DT[ts_type]
base = datetime64("%s-01-01 00:00:00" %year).astype(conv)
test_datenums = asarray(test_idx)
ts_nominal = base + test_datenums.astype(tres_np)
dts_nominal = ts_nominal[1:] - ts_nominal[:-1]
ts_values = cftime_to_datetime64(t[test_idx].points, cfunit=t.units).astype(conv)
dts_values = ts_values[1:] - ts_values[:-1]
if not all(ts_values == ts_nominal):
raise ValueError("Time match error, nominal dates for test array"
"%s (unit=%s): %s\nReceived values after "
"conversion: %s"
%(test_datenums, t.units.origin,
ts_nominal, ts_values))
elif not all(dts_values == dts_nominal):
raise ValueError("Time match error, time steps for test array"
"%s (unit=%s): %s\nReceived values after "
"conversion: %s"
%(test_datenums, t.units.origin,
dts_nominal, dts_values))
except Exception as e:
logger.warning("Invalid time dimension.\n"
"Error message: {}".format(repr(e)))
ok = False
return ok
def check_time_coord(cube, ts_type, year):
"""Method that checks the time coordinate of an iris Cube
This method checks if the time dimension of a cube is accessible and
according to the standard (i.e. fully usable). It only checks, and does not
correct. For the latter, please see :func:`correct_time_coord`.
Parameters
----------
cube : Cube
cube containing data
ts_type : str
pyaerocom ts_type
year :
year of data
Returns
-------
bool
True, if time dimension is ok, False if not
"""
try:
t = cube.coord("time")
except:
raise AttributeError("Cube does not contain time dimension")
if not isinstance(t, iris.coords.DimCoord):
raise AttributeError("Time is not a DimCoord instance")
try:
cftime_to_datetime64(0, cfunit=t.units)
except:
raise ValueError("Could not convert time unit string")
tidx = make_datetimeindex(ts_type, year)
num_per = len(tidx)
num = len(t.points)
if not num == num_per:
if tidx[0].is_leap_year:
if not _check_leap_year(num, num_per, ts_type):
raise UnresolvableTimeDefinitionError(
'Expected {} timestamps but '
'data has {}'.format(len(tidx), num))
else:
raise UnresolvableTimeDefinitionError('Expected {} timestamps but '
'data has {}'.format(
len(tidx), num))
pstr = TS_TYPE_TO_PANDAS_FREQ[ts_type]
# ToDo: check why MS is not working for period conversion
if pstr == 'MS':
pstr = 'M'
# convert first and last timestamps of index array into periods
# (e.g. January and December for monthly data)
per0 = tidx[0].to_period(pstr)
per1 = tidx[-1].to_period(pstr)
# first and last timestamp in data
t0, t1 = cftime_to_datetime64([t.points[0], t.points[-1]], cfunit=t.units)
if not per0.start_time <= t0 <= per0.end_time:
raise ValueError('First timestamp of data {} does not lie in first '
'period: {}'.format(t0, per0))
elif not per1.start_time <= t1 <= per1.end_time:
raise ValueError('Last timestamp of data {} does not lie in last '
'period: {}'.format(t1, per1))