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# This is a dummy version of the ACCESS Post Processor.
# Peter Uhe 24 July 2014
# Martin Dix 21 Nov 2014
#
from __future__ import print_function
import numpy as np
import datetime
import cmor
def save(opts, threeD=True):
cmor.setup(inpath=opts['table_path'],
netcdf_file_action=cmor.CMOR_REPLACE_3,
set_verbosity=cmor.CMOR_NORMAL,
exit_control=cmor.CMOR_NORMAL,
logfile=None, create_subdirectories=1)
cmor.dataset_json("Test/CMOR_input_example.json")
# Load the CMIP tables into memory.
tables = []
tables.append(cmor.load_table('CMIP6_grids.json'))
tables.append(cmor.load_table(opts['cmip_table']))
# Create the dimension axes
# Monthly time axis
min_tvals = []
max_tvals = []
cmor_tName = 'time'
tvals = []
axis_ids = []
for year in range(1850, 1851):
for mon in range(1, 13):
tvals.append(datetime.date(year, mon, 15).toordinal() - 1)
# set up time values and bounds
for i, ordinaldate in enumerate(tvals):
model_date = datetime.date.fromordinal(int(ordinaldate) + 1)
# min bound is first day of month
model_date = model_date.replace(day=1)
min_tvals.append(model_date.toordinal() - 1)
# max_bound is first day of next month
tyr = model_date.year + int(model_date.month / 12)
tmon = model_date.month % 12 + 1
model_date = model_date.replace(year=tyr, month=tmon)
max_tvals.append(model_date.toordinal() - 1)
# correct date to middle of month
mid = (max_tvals[i] - min_tvals[i]) / 2.
tvals[i] = min_tvals[i] + mid
tval_bounds = np.column_stack((min_tvals, max_tvals))
cmor.set_table(tables[1])
time_axis_id = cmor.axis(table_entry=cmor_tName,
units='days since 0001-01-01', length=len(tvals),
coord_vals=tvals[:], cell_bounds=tval_bounds[:],
interval=None)
axis_ids.append(time_axis_id)
if not threeD:
# Pressure
plev = np.array([100000, 92500, 85000, 70000, 60000, 50000,
40000, 30000, 25000, 20000, 15000, 10000,
7000, 5000, 3000, 2000, 1000, 500, 100])
plev_bounds = np.array([
[103750, 96250],
[96250, 88750],
[88750, 77500],
[77500, 65000],
[65000, 55000],
[55000, 45000],
[45000, 35000],
[35000, 27500],
[27500, 22500],
[22500, 17500],
[17500, 12500],
[12500, 8500],
[8500, 6000],
[6000, 4000],
[4000, 2500],
[2500, 1500],
[1500, 750],
[750, 300],
[300, 0]])
plev_axis_id = cmor.axis(table_entry='plev19',
units='Pa', length=len(plev),
coord_vals=plev[:], cell_bounds=plev_bounds[:],
interval=None)
axis_ids.append(plev_axis_id)
# 1 degree resolution latitude and longitude
lat = np.linspace(-89.5, 89.5, 180)
lat_bounds = np.column_stack((np.linspace(-90., 89., 180),
np.linspace(-89., 90., 180)))
lat_axis_id = cmor.axis(table_entry='latitude',
units='degrees_north', length=len(lat),
coord_vals=lat[:], cell_bounds=lat_bounds[:],
interval=None)
axis_ids.append(lat_axis_id)
lon = np.linspace(0.5, 359.5, 360)
lon_bounds = np.column_stack((np.linspace(0., 359., 360),
np.linspace(1., 360., 360)))
lon_axis_id = cmor.axis(table_entry='longitude',
units='degrees_north', length=len(lon),
coord_vals=lon[:], cell_bounds=lon_bounds[:],
interval=None)
axis_ids.append(lon_axis_id)
#
# Define the CMOR variable.
#
cmor.set_table(tables[1])
in_missing = float(1.e20)
if threeD:
variable_id = cmor.variable(table_entry='ts', units='K',
axis_ids=axis_ids, data_type='f', missing_value=in_missing)
else:
variable_id = cmor.variable(table_entry='ta', units='K',
axis_ids=axis_ids, data_type='f', missing_value=in_missing)
#
# Write the data
#
if threeD:
data_vals = np.zeros(
(len(tvals), len(lat), len(lon)), np.float32) + 290.
else:
data_vals = np.zeros(
(len(tvals),
len(plev),
len(lat),
len(lon)),
np.float32) + 290.
try:
print('writing...')
cmor.write(variable_id, data_vals[:], ntimes_passed=np.shape(
data_vals)[0]) # assuming time is the first dimension
except Exception as e:
raise Exception("ERROR writing data!")
try:
path = cmor.close(variable_id, file_name=True)
except BaseException:
raise Exception("ERROR closing cmor file!")
print(path)
if __name__ == "__main__":
opts = {'cmip_table': 'CMIP6_Amon.json',
'outpath': 'Test',
'table_path': 'Tables'}
save(opts, threeD=True)
save(opts, threeD=False)
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