def prep_cmor():
cmor.setup(inpath=ipth,set_verbosity=cmor.CMOR_QUIET, netcdf_file_action = cmor.CMOR_REPLACE, exit_control = cmor.CMOR_EXIT_ON_MAJOR);
cmor.dataset(
outpath = opth,
experiment_id = "lgm",
institution = "GICC (Generic International Climate Center, Geneva, Switzerland)",
source = "GICCM1 (2002): atmosphere: GICAM3 (gicam_0_brnchT_itea_2, T63L32); ocean: MOM (mom3_ver_3.5.2, 2x3L15); sea ice: GISIM4; land: GILSM2.5",
calendar = "standard",
realization = 1,
contact = "Rusty Koder (koder@middle_earth.net)",
history = "Output from archive/giccm_03_std_2xCO2_2256.",
comment = "Equilibrium reached after 30-year spin-up after which data were output starting with nominal date of January 2030",
references = "Model described by Koder and Tolkien (J. Geophys. Res., 2001, 576-591). Also see http://www.GICC.su/giccm/doc/index.html 2XCO2 simulation described in Dorkey et al. '(Clim. Dyn., 2003, 323-357.)",
leap_year=0,
leap_month=0,
institute_id="PCMDI",
month_lengths=None,model_id="GICCM1",forcing="Nat",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0.)
tables=[]
a = cmor.load_table("Tables/CMIP5_Omon")
tables.append(a)
tables.append(cmor.load_table("Tables/CMIP5_Amon"))
return
def path_test():
cmor.setup(inpath='Test',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('mytest2010030812', 'ukmo', 'HadCM3', '360_day',
institute_id="PCMDI",
model_id='HadCM3',forcing='co2')
table='CMIP5_Amon_YYYYMMDDHH'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
'coord_vals': [15],
'cell_bounds': [0, 30]
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids)
cmor.write(varid, [273])
path=cmor.close(varid, file_name=True)
print "Saved file: ",path
def main():
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE)
cmor.dataset('pre-industrial control', 'mohc', 'HadGEM2: source',
'360_day',
institute_id = 'ukmo',
model_id = 'HadGEM2',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0.,
contact = 'bob')
table = 'CMIP5_6hrLev'
cmor.load_table(table)
axes = [ {'table_entry': 'time1',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
{'table_entry': 'hybrid_height',
'coord_vals': [0, 1],
'cell_bounds': [[0., 0.5], [0.5, 1.]],
'units': 'm',
},
]
values = numpy.array([1.2,1.2], numpy.float32)
numpy.reshape(values, (2,1,1,1))
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
print 'cmor.axis calls complete'
cmor.zfactor(axis_ids[3], 'b', '', axis_ids[3:4], 'd', [0., 0.5], [[0., 0.25], [0.25, 1.]])
cmor.zfactor(axis_ids[3], 'orog', 'm', axis_ids[1:3], 'd', [[0.]])
print 'cmor.zfactor calls complete'
varid = cmor.variable('ua',
'm s-1',
axis_ids,
missing_value = -99
)
print 'cmor.variable call complete'
cmor.write(varid, values, time_vals = [6.0])
print 'cmor.write call complete'
cmor.close()
def test_mode(mode):
cmor.setup(inpath="Tables", netcdf_file_action=mode)
cmor.dataset(
"pre-industrial control",
"ukmo",
"HadCM3",
"360_day",
institute_id="ukmo",
model_id="HadCM3",
forcing="TO",
contact="Derek Jeter",
history="some global history",
parent_experiment_id="lgm",
parent_experiment_rip="r1i1p1",
branch_time=0,
)
table = "CMIP5_fx"
cmor.load_table(table)
axes = [
{"table_entry": "latitude", "units": "degrees_north", "coord_vals": [0], "cell_bounds": [-1, 1]},
{"table_entry": "longitude", "units": "degrees_east", "coord_vals": [90], "cell_bounds": [89, 91]},
]
values = numpy.array([5000], numpy.float32)
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units in (("deptho", "m"),):
varid = cmor.variable(var, units, axis_ids, history="variable history")
cmor.write(varid, values)
fnm = cmor.close(varid, file_name=True)
cmor.close()
return fnm
def prep_cmor():
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_QUIET,
netcdf_file_action=cmor.CMOR_REPLACE,
exit_control=cmor.CMOR_EXIT_ON_MAJOR)
cmor.dataset(
outpath=opth,
experiment_id="lgm",
institution=
"GICC (Generic International Climate Center, Geneva, Switzerland)",
source=
"GICCM1 (2002): atmosphere: GICAM3 (gicam_0_brnchT_itea_2, T63L32); ocean: MOM (mom3_ver_3.5.2, 2x3L15); sea ice: GISIM4; land: GILSM2.5",
calendar="standard",
realization=1,
contact="Rusty Koder (koder@middle_earth.net)",
history="Output from archive/giccm_03_std_2xCO2_2256.",
comment=
"Equilibrium reached after 30-year spin-up after which data were output starting with nominal date of January 2030",
references=
"Model described by Koder and Tolkien (J. Geophys. Res., 2001, 576-591). Also see http://www.GICC.su/giccm/doc/index.html 2XCO2 simulation described in Dorkey et al. '(Clim. Dyn., 2003, 323-357.)",
leap_year=0,
leap_month=0,
institute_id="PCMDI",
month_lengths=None,
model_id="GICCM1",
forcing="Nat",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0.)
tables = []
a = cmor.load_table("Tables/CMIP5_Omon")
tables.append(a)
tables.append(cmor.load_table("Tables/CMIP5_Amon"))
return
def main():
cmor.setup(inpath='Tables', netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0.,
contact='bob')
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [
{
'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
values = numpy.array([1.], numpy.float32) + 200
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, positive in (
('ts', 'K', ''),
('rsut', 'W m-2', 'up'),
('rlut', 'W m-2', 'down'),
):
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99,
positive=positive)
cmor.write(varid, values, time_vals=[15], time_bnds=[[0, 30]])
cmor.close()
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action = cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0,
contact = 'brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [ {'table_entry': 'time2',
'units': 'days since 1850-01-01 00:00:00',
'coord_vals' : [15.5, 45,],
'cell_bounds':[[0,396],[31,424]]
},
{'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [5000., 3000., 2000., 1000.],
'cell_bounds': [ 5000., 3000., 2000., 1000.,0]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
print 'doing:',axis
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('difvso', 'm2 s-1', 274.),):
values = numpy.ones(map(lambda x: len(x["coord_vals"]),axes))*value
values=values.astype("f")
varid = cmor.variable(var,
units,
axis_ids,
history = 'variable history',
missing_value = -99
)
cmor.write(varid, values)
cmor.close()
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [{'table_entry': 'time2',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [500, 1000.],
'cell_bounds': [0., 750., 1200.]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
print('doing:', axis)
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('tnpeot', 'W m-2', 274),):
values = numpy.array([value, ] *
len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99
)
for i in range(12):
cmor.write(varid, values, time_vals=[
30 * i + 15], time_bnds=[[30 * i, 360 + 30 * (i + 1)]])
cmor.close()
def main():
cmor.setup(inpath='Tables', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
forcing='SO',
model_id='HadCM3',
contact="Dusty Baker (even though he was a Dodgers",
parent_experiment_rip="r1i3p2",
parent_experiment_id="lgm",
branch_time=0)
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [
{
'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, val in (('ts', 'K', 278), ('ps', 'hPa', 974.2)):
varid = cmor.variable(
var,
units,
axis_ids,
)
values = numpy.array([val], numpy.float32)
cmor.write(varid, values, time_vals=[15], time_bnds=[[0, 30]])
cmor.close()
def cmor_ini():
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE)
cmor.dataset('pre-industrial control', 'mohc', 'HadGEM2: source',
'360_day',
institute_id = 'ukmo',
model_id = 'HadGEM2',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0.,
contact = 'bob')
def main():
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0,
contact = 'brian clough')
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'plevs',
'units': 'Pa',
'coord_vals': [100000., 92500., 85000., 70000., 60000., 50000., 40000., 30000., 25000., 20000., 15000., 10000., 7000., 5000., 3000., 2000., 1000.]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
print 'doing:',axis
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('ta', 'K', 274), ('ua', 'm s-1', 10)):
values = numpy.array([value,]*len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history = 'variable history',
missing_value = -99
)
cmor.set_variable_attribute(varid, 'cell_measures', 'BLABLABLA')
cmor.write(varid, values, time_vals = [15], time_bnds = [ [0,30] ])
cmor.close()
def cmor_initialisation():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3,
create_subdirectories=0)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0.,
contact='bob',
outpath='./out')
def cmor_initialisation():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action = cmor.CMOR_REPLACE_3,
create_subdirectories = 0)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0.,
contact = 'bob',
outpath = 'test_ltd')
def cmor_ini():
cmor.setup(inpath='Tables', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('pre-industrial control',
'mohc',
'HadGEM2: source',
'360_day',
institute_id='ukmo',
model_id='HadGEM2',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0.,
contact='bob')
def setup_cmor() :
#---------------------------------------------------------------------------------------------------
# Initialise CMOR library
cmor.setup(inpath=MIP_TABLE_DIR, netcdf_file_action=cmor.CMOR_REPLACE_3,
set_verbosity=cmor.CMOR_NORMAL, create_subdirectories=0)
# Create CMOR dataset
cmor.dataset(outpath='Test', institution='Met Office Hadley Centre', institute_id="MOHC",
experiment_id='amip', model_id="HadGEM2-A", source='HadGEM2-A 2009',
calendar='360_day', contact='*****@*****.**',
realization=1, initialization_method=1, physics_version=1,
history='history', comment='CMIP5 site axis test',
references='references', forcing="GHG, TO (yeah or some think)",
parent_experiment_id='N/A', parent_experiment_rip='N/A', branch_time=0
)
def main():
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
history = 'some global history',
forcing = 'N/A',
parent_experiment_id = 'N/A',
parent_experiment_rip = 'N/A',
branch_time = 0.,
contact = 'bob')
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
values = numpy.array([1.], numpy.float32)+200
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, positive in (('ts', 'K', ''),
('rsut', 'W m-2', 'up'),
('rlut', 'W m-2', 'down'),):
varid = cmor.variable(var,
units,
axis_ids,
history = 'variable history',
missing_value = -99,
positive = positive
)
cmor.write(varid, values, time_vals = [15], time_bnds = [ [0,30] ])
cmor.close()
def main():
missing = -99.
cmor.setup(inpath='Tables', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
forcing='Nat',
model_id='HadCM3',
contact="Bleachers 140",
parent_experiment_rip="r1i3p2",
parent_experiment_id="lgm",
branch_time=0.)
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [
{
'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
values = numpy.array([missing], numpy.float32)
myma = numpy.ma.masked_values(values, missing)
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids, missing_value=myma.fill_value)
cmor.write(varid, myma, time_vals=[15], time_bnds=[[0, 30]])
cmor.close(varid)
def path_test():
cmor.setup(inpath='TestTables', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical',
'ukmo',
'HadCM3',
'360_day',
model_id='HadCM3',
forcing='Nat',
contact="J.T. Snow",
institute_id="PCMDI",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0)
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [
{
'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
'coord_vals': [15],
'cell_bounds': [0, 30]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids)
cmor.write(varid, [275])
path = cmor.close(varid, file_name=True)
print path
def cmor_initialisation():
cmor.setup(inpath="/git/cmip5-cmor-tables/Tables", netcdf_file_action=cmor.CMOR_REPLACE_3, create_subdirectories=0)
cmor.dataset(
"pre-industrial control",
"ukmo",
"HadCM3",
"360_day",
institute_id="ukmo",
model_id="HadCM3",
history="some global history",
forcing="N/A",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0.0,
contact="bob",
outpath="hadju/test",
)
def path_test():
cmor.setup(inpath='TestTables',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', '360_day',model_id='HadCM3',forcing='Nat',
contact="J.T. Snow",
institute_id="PCMDI",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0)
table='CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time2',
'units': 'months since 2000-01-01 00:00:00',
'coord_vals': times,
'cell_bounds': times_bnds,
},
{'table_entry': 'plevs',
'units': 'Pa',
'coord_vals': [100000., 92500., 85000., 70000., 60000., 50000.,
40000., 30000., 25000., 20000., 15000.,
10000., 7000., 5000., 3000., 2000., 1000.]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('co2Clim', '1.e-6', axis_ids)
import numpy
data =numpy.array([3,4,5])
data.resize((3,17,1,1))
cmor.write(varid, data)
path=cmor.close(varid, file_name=True)
print path
def test_mode(mode):
cmor.setup(inpath='Tables', netcdf_file_action=mode)
cmor.dataset('pre-industrial control',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
model_id='HadCM3',
forcing="TO",
contact="Derek Jeter",
history='some global history',
parent_experiment_id="lgm",
parent_experiment_rip="r1i1p1",
branch_time=0)
table = 'CMIP5_fx'
cmor.load_table(table)
axes = [
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
values = numpy.array([5000], numpy.float32)
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units in (('deptho', 'm'), ):
varid = cmor.variable(var, units, axis_ids, history='variable history')
cmor.write(varid, values)
fnm = cmor.close(varid, file_name=True)
cmor.close()
return fnm
def path_test():
cmor.setup(inpath='Test', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('mytest2010030812',
'ukmo',
'HadCM3',
'360_day',
institute_id="PCMDI",
model_id='HadCM3',
forcing='co2')
table = 'CMIP5_Amon_YYYYMMDDHH'
cmor.load_table(table)
axes = [
{
'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
'coord_vals': [15],
'cell_bounds': [0, 30]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids)
cmor.write(varid, [273])
path = cmor.close(varid, file_name=True)
print "Saved file: ", path
def main():
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
forcing = 'SO',
model_id = 'HadCM3',contact="Dusty Baker (even though he was a Dodgers",
parent_experiment_rip="r1i3p2",
parent_experiment_id="lgm",branch_time=0)
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, val in (('ts', 'K',278), ('ps', 'hPa',974.2)):
varid = cmor.variable(var,
units,
axis_ids,
)
values = numpy.array([val], numpy.float32)
cmor.write(varid, values, time_vals = [15], time_bnds = [ [0,30] ])
cmor.close()
def multi_call_test():
cmor.setup(inpath='Tables',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', '360_day',
institute_id="PCMDI",
model_id='HadCM3',contact="Ron Nen",forcing='SO',
parent_experiment_id="lgm",
parent_experiment_rip="r1i3p2",
branch_time=0.)
table='CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids)
cmor.write(varid, [275], time_vals = [15], time_bnds = [ [0,30] ])
print 'First write worked as expected'
try:
cmor.write(varid, [275], time_vals = [15], time_bnds = [ [0], [30] ])
raise Exception,"We shouldn't be getting in here"
except:
print 'Second write that should have failed did fail, good!'
pass
cmor.close(varid)
print 'Success'
def main():
missing = -99.
cmor.setup(inpath='Tables',
netcdf_file_action = cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
forcing = 'Nat',
model_id = 'HadCM3',
contact="Bleachers 140",
parent_experiment_rip="r1i3p2",
parent_experiment_id="lgm",branch_time=0.)
table = 'CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
values = numpy.array([missing], numpy.float32)
myma = numpy.ma.masked_values(values, missing)
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids, missing_value = myma.fill_value)
cmor.write(varid, myma, time_vals = [15], time_bnds = [ [0,30] ])
cmor.close(varid)
def path_test():
cmor.setup(inpath='TestTables',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', '360_day',model_id='HadCM3',forcing='Nat',
contact="J.T. Snow",
institute_id="PCMDI",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0)
table='CMIP5_Amon'
cmor.load_table(table)
axes = [ {'table_entry': 'time',
'units': 'days since 2000-01-01 00:00:00',
'coord_vals': [15],
'cell_bounds': [0, 30]
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('ts', 'K', axis_ids)
cmor.write(varid, [275])
path=cmor.close(varid, file_name=True)
print path
def prep(mode):
error_flag = cmor.setup(inpath='Test', netcdf_file_action=mode )
error_flag = cmor.dataset(
outpath='Test',
experiment_id='noVolc2000',
institution= 'GICC (Generic International Climate Center, Geneva, Switzerland)',
source='GICCM1 (2002): ',
calendar='standard',
realization=1,
contact = 'Rusty Koder (koder@middle_earth.net) ',
history='Output from archivcl_A1.nce/giccm_03_std_2xCO2_2256.',
comment='Equilibrium reached after 30-year spin-up ',
references='Model described by Koder and Tolkien ',
institute_id="PCMDI",
model_id="GICCM1",
forcing="TO, SO, Nat",
## month_lengths=[30,28,30,30,30,30,30,31,30,31,30,30],
## leap_year=3,
## leap_month=1,
parent_experiment_rip="r1i3p2",
parent_experiment_id="N/A",branch_time=1)
def prep(mode):
error_flag = cmor.setup(inpath='Test', netcdf_file_action=mode)
error_flag = cmor.dataset(
outpath='Test',
experiment_id='noVolc2000',
institution=
'GICC (Generic International Climate Center, Geneva, Switzerland)',
source='GICCM1 (2002): ',
calendar='standard',
realization=1,
contact='Rusty Koder (koder@middle_earth.net) ',
history='Output from archivcl_A1.nce/giccm_03_std_2xCO2_2256.',
comment='Equilibrium reached after 30-year spin-up ',
references='Model described by Koder and Tolkien ',
institute_id="PCMDI",
model_id="GICCM1",
forcing="TO, SO, Nat",
## month_lengths=[30,28,30,30,30,30,30,31,30,31,30,30],
## leap_year=3,
## leap_month=1,
parent_experiment_rip="r1i3p2",
parent_experiment_id="N/A",
branch_time=1)
def test_mode(mode,i,suffix=''):
cmor.setup(inpath='Tables',
netcdf_file_action = mode)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
forcing="TO",
contact="Derek Jeter",
history = 'some global history',
parent_experiment_rip="r1i3p2",
parent_experiment_id="lgm",branch_time=0)
table = 'CMIP5_Amon'
cmor.load_table(table)
levels = [100000.,
92500.,
85000.,
70000.,
60000.,
50000.,
40000.,
30000.,
25000.,
20000.,
15000.,
10000.,
7000.,
5000.,
3000.,
2000.,
1000.,
999,
998,
997,
996,
995,
994]
axes = [ {'table_entry': 'time',
'units': 'months since 2000-01-01 00:00:00',
},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
{'table_entry': 'plevs',
'units': 'Pa',
'coord_vals': levels},
]
values = numpy.array(range(len(levels)), numpy.float32)+195
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units in (('ta', 'K'),):
varid = cmor.variable(var,
units,
axis_ids,
history = 'variable history',
missing_value = -99
)
print 'suffix is:',suffix
print "Sending time bounds:",[[i,i+1]]
cmor.write(varid, values, time_vals = [i], time_bnds = [ [i,i+1] ],file_suffix=suffix)
fnm = cmor.close(varid,file_name=True)
cmor.close()
return fnm
dlon = 360./nlon
nlev = 24
dlev = 1000./nlev
ntimes = 1
lats = numpy.arange(-90+dlat/2.,90,dlat)
blats = numpy.arange(-90,90+dlat,dlat)
lons = numpy.arange(0+dlon/2.,360.,dlon)
blons = numpy.arange(0,360.+dlon,dlon)
levs = numpy.array([1000.,925,900,850,800,700,600,500,400,300,250,200,150,100,75,70,50,30,20,10,7.5,5,2.5,1])
alllevs = numpy.arange(1000,0,-dlev).tolist()
print len(alllevs)
cmor.setup(inpath='.',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'pcmdi-10b HadCM3', 'gregorian',model_id='pcmdi-10b',outpath='Test',forcing='N/A', parent_experiment_id="lgm", parent_experiment_rip="r1i1p1",contact="Bruce Bochy",branch_time=0,institute_id="yep")
table='Tables/CMIP5_Amon'
cmor.load_table(table)
ilat = cmor.axis(table_entry='latitude',coord_vals=lats,cell_bounds=blats,units='degrees_north')
ilon = cmor.axis(table_entry='longitude',coord_vals=lons,cell_bounds=blons,units='degrees_east')
itim = cmor.axis(table_entry='time',units='months since 2010')#,coord_vals=numpy.arange(ntimes,dtype=numpy.float),cell_bounds=numpy.arange(ntimes+1,dtype=float),units='months since 2000')
ilev = cmor.axis(table_entry='plevs',coord_vals=levs,units='hPa')
axes=[itim,ilev,ilat,ilon]
var = cmor.variable(table_entry='ta',units='K',axis_ids=axes)
print "allocating mem for data"
data = numpy.random.random((nlev,nlat,nlon))*30+273.15
import cmor, numpy
ipth = "Test"
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action=cmor.CMOR_REPLACE,
logfile=None)
cmor.dataset(outpath=ipth,
experiment_id="lgm",
institution="PCMDI",
source="GICCM1 2002",
institute_id="PCMDI",
calendar="standard",
contact="Bengie Molina",
model_id="GICCM1",
forcing="SO",
parent_experiment_id="historical",
parent_experiment_rip="r3i8p1",
branch_time=0.)
cmor.load_table("Tables/CMIP5_Amon")
nlat = 90
dlat = 180 / nlat
nlon = 180
dlon = 360. / nlon
lats = numpy.arange(-90 + dlat / 2., 90, dlat)
blats = numpy.arange(-90, 90 + dlat, dlat)
lons = numpy.arange(0 + dlon / 2., 360., dlon)
def mywrite(data=None, time_vals=None, append_to=None, cell_bounds=None):
breq = "100000. 80000. 80000. 68000. 68000. 56000. 56000. 44000. 44000. 31000. 31000. 18000. 18000. 0.".split(
)
bnds_req = []
for b in breq:
bnds_req.append(float(b))
bnds_req = numpy.array(bnds_req)
bnds_req.shape = (7, 2)
print bnds_req[-2], bnds_req.shape
levs = []
for b in bnds_req:
levs.append((b[0] + b[1]) / 2.)
levs = numpy.array(levs)
print levs
ipth = "Test"
if append_to is None:
mode = cmor.CMOR_REPLACE
else:
mode = cmor.CMOR_APPEND
print 'Mode in python:', mode
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action=mode,
logfile=None)
cmor.dataset(outpath=ipth,
experiment_id="lgm",
institution="PCMDI",
source="GICCM1 2002",
institute_id="PCMDI",
calendar="standard",
contact="Pablo Sandoval",
model_id="GICCM1",
forcing="Nat",
parent_experiment_id="historical",
parent_experiment_rip="r1i3p2",
branch_time=3.14159)
cmor.load_table("Tables/CMIP5_Amon")
dlat = 180 / nlat
dlon = 360. / nlon
lats = numpy.arange(-90 + dlat / 2., 90, dlat)
bnds_lat = numpy.arange(-90, 90 + dlat, dlat)
lons = numpy.arange(0 + dlon / 2., 360., dlon) - 180.
bnds_lon = numpy.arange(0, 360. + dlon, dlon) - 180.
plevs = numpy.array([
100000., 92500., 85000., 70000., 60000., 50000., 40000., 30000.,
25000., 20000., 15000., 10000., 7000., 5000., 3000., 2000., 1000.
])
itim = cmor.axis(table_entry='time', units='month since 2008')
#itim = cmor.axis(table_entry='time',units='month since 2008',coord_vals=numpy.arange(0,12,1))
ilat = cmor.axis(table_entry='latitude',
coord_vals=lats,
units='degrees_north',
cell_bounds=bnds_lat)
ilon = cmor.axis(table_entry='longitude',
coord_vals=lons,
units='degrees_east',
cell_bounds=bnds_lon)
print 'so far', itim, ilat, ilon
ilev = cmor.axis(table_entry="plevs", coord_vals=plevs, units="Pa")
iv = cmor.variable(table_entry='ta',
axis_ids=numpy.array((itim, ilev, ilat, ilon)),
units='K')
#cmor.write(iv,data)
if append_to is None:
print 'time:', time_vals
print 'bnds:', cell_bounds
cmor.write(iv, data, time_vals=time_vals,
time_bnds=cell_bounds) #,file_suffix="with-appending")
else:
print 'Ok writing with a suffix', append_to
cmor.write(iv,
data,
time_vals=time_vals,
file_suffix=append_to,
time_bnds=cell_bounds)
print 'and back'
file = cmor.close(iv, file_name=True)
print 'Ok dumped to:', file
cmor.close()
return file
lat = lat() # import cmor module import cmor contact = 'cmbe: Renata McCoy, [email protected], ARM Archive user services: [email protected]' model = 'cmbe' #+ site_location[site_fac] # setup cmor before doing anything else with cmor error_flag = cmor.setup(netcdf_file_action=cmor.CMOR_REPLACE, create_subdirectories=0) # define dataset for all variables from one site cmor.dataset( experiment_id='obs', institution='ARM', institute_id="ARM", source= 'CMBE (Climate Modeling Best Estimate), ARM (Atmospheric Radiation Measurement Program)', calendar='proleptic_gregorian', model_id=model, contact=contact, outpath=out_path) # add those additional global attributes to the output file # --- this did not work------, neede to put contact info in cmor.dataset setup #contact = "cmbe: Renata McCoy, [email protected], ARM Archive user services: [email protected]" #cmor.set_cur_dataset_attribute('contact',contact) # copy some global attributes from the original cmbe files # read some global attributes and put into the cmor created netcdf file title = fid.title description = fid.description project = fid.project
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', 'noleap',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [{'table_entry': 'time2',
'units': 'days since 1861',
},
{'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [500, 1000.],
'cell_bounds': [0., 750., 1200.]},
{'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]},
{'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]},
]
axes2 = {'coord_vals': [48925.5, 48955, 48984.5, 49015, 49045.5, 49076, 49106.5, 49137.5, 49168, 49198.5, 49229, 49259.5],
'cell_bounds': [[45625, 52591],
[45656, 52619, ],
[45684, 52650, ],
[45715, 52680, ],
[45745, 52711, ],
[45776, 52741, ],
[45806, 52772, ],
[45837, 52803, ],
[45868, 52833, ],
[45898, 52864, ],
[45929, 52894, ],
[45959, 52925]], }
axis_ids = list()
for axis in axes:
print('doing:', axis)
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('tnpeot', 'W m-2', 274),):
values = numpy.array([value, ] *
len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99
)
for i in range(12):
cmor.write(
varid,
values,
time_vals=axes2["coord_vals"][i],
time_bnds=axes2["cell_bounds"][i])
cmor.close()
pass
cal = data.getTime().getCalendar() # cmor understand cdms calendars
if A.verbose:
cmor_verbose = cmor.CMOR_NORMAL
else:
cmor_verbose = cmor.CMOR_QUIET
error_flag = cmor.setup(
inpath='.',
netcdf_file_action=cmor.CMOR_REPLACE,
set_verbosity=cmor_verbose,
exit_control=cmor.CMOR_NORMAL,
# logfile='logfile',
create_subdirectories=int(A.drs))
error_flag = cmor.dataset(experiment_id=exp,
outpath=A.output_directory,
institution=inst,
source=src,
calendar=cal,
**xtra)
if not os.path.exists(A.tables):
raise RuntimeError("No such file or directory for tables: %s" %
A.tables)
if os.path.isdir(A.tables):
table = os.path.join(A.tables, "pcmdi_metrics_table")
else:
table = A.tables
table = cmor.load_table(table)
# Ok CMOR is ready let's create axes
cmor_axes = []
for ax in s.getAxisList():
if ax.isLatitude():
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control',
'ukmo',
'HadCM3',
'noleap',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [
{
'table_entry':
'time2',
'units':
'days since 1861',
'coord_vals': [
48925.5, 48955, 48984.5, 49015, 49045.5, 49076, 49106.5,
49137.5, 49168, 49198.5, 49229, 49259.5
],
'cell_bounds': [[45625, 52591], [
45656,
52619,
], [
45684,
52650,
], [
45715,
52680,
], [
45745,
52711,
], [
45776,
52741,
], [
45806,
52772,
], [
45837,
52803,
], [
45868,
52833,
], [
45898,
52864,
], [
45929,
52894,
], [45959, 52925]],
},
{
'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [500, 1000.],
'cell_bounds': [0., 750., 1200.]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
print('doing:', axis)
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('tnpeot', 'W m-2', 274), ):
values = numpy.array([
value,
] * len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99)
for i in range(12):
cmor.write(varid, values, ntimes_passed=1)
cmor.close()
dt = (bounds[1] - bounds[0])
bounds.append(bounds[-1] + dt)
bounds = np.array([ to_udunits(v, TIME) for v in bounds ])
time = (bounds[:-1] + bounds[1:])/2.
# now save data
start_for_variable = datetime.datetime.now()
for variable in config['variables'].values():
start_this_variable = datetime.datetime.now()
if variable['realm'] in ['atmos', 'land']:
data = np.concatenate(vars[ variable['output variable name'] ], axis=0)
print variable['output variable name']
# setup output file
cmor.setup(inpath=TABLES, netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset( **config['description'] )
cmor.load_table( variable['table'] )
cell_methods = variable['cell_methods'] or ''
if re.search('3hr', variable['table']):
#if not re.match('time:\s*mean', cell_methods):
# bounds = None
time_ = time
bounds_ = bounds
elif re.search('6hr', variable['table']):
if re.match('time:\s*mean', cell_methods):
data = average_data(data, 2)
time_ = average_data(time, 2)
bounds_ = bounds[::2]
else:
data = data[::2] # sample every 6hr
def path_test():
cmor.setup(inpath='TestTables', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical',
'ukmo',
'HadCM3',
'360_day',
model_id='HadCM3',
forcing='Nat',
contact="J.T. Snow",
institute_id="PCMDI",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0)
table = 'CMIP6_Amon.json'
cmor.load_table(table)
axes = [
{
'table_entry': 'time2',
'units': 'months since 2000-01-01 00:00:00',
'coord_vals': times,
'cell_bounds': times_bnds,
},
{
'table_entry':
'plevs',
'units':
'Pa',
'coord_vals': [
100000., 92500., 85000., 70000., 60000., 50000., 40000.,
30000., 25000., 20000., 15000., 10000., 7000., 5000., 3000.,
2000., 1000.
]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
varid = cmor.variable('co2Clim', '1.e-6', axis_ids)
import numpy
data = numpy.array([3, 4, 5])
data.resize((3, 17, 1, 1))
cmor.write(varid, data)
path = cmor.close(varid, file_name=True)
print path
tables = """CMIP5_3hr CMIP5_6hrPlev CMIP5_LImon CMIP5_OImon CMIP5_Omon CMIP5_aero CMIP5_cfDay CMIP5_cfOff CMIP5_day CMIP5_grids CMIP5_6hrLev CMIP5_Amon CMIP5_Lmon CMIP5_Oclim CMIP5_Oyr CMIP5_cf3hr CMIP5_cfMon CMIP5_cfSites CMIP5_fx"""
tables = """CMIP5_3hr CMIP5_6hrPlev CMIP5_LImon CMIP5_OImon CMIP5_Omon CMIP5_aero CMIP5_cfDay CMIP5_cfOff CMIP5_day CMIP5_6hrLev CMIP5_Amon CMIP5_Lmon CMIP5_Oclim CMIP5_Oyr CMIP5_cfMon CMIP5_fx"""
for t in tables.split():
print 'Table:',t
tnm = "Tables/%s" % t
tbl = readTable(tnm)
vr = tbl['variable']
ax = tbl['axis']
g = tbl['general']
cmor.setup(inpath='Tables',set_verbosity=cmor.CMOR_QUIET,
netcdf_file_action = cmor.CMOR_REPLACE,exit_control=cmor.CMOR_EXIT_ON_MAJOR)
cmor.dataset('pre-industrial control', 'ukmo', 'HadCM3', '360_day',
institute_id = 'ukmo',
model_id = 'HadCM3',
forcing="TO",
contact="Derek Jeter",
history = 'some global history',
parent_experiment_id="lgm",branch_time=0)
cmor.load_table(tnm)
dims={}
print '\tDimensions:'
for a in ax:
A=ax[a]
print '\t\t',a,A.get('type','notype')
mn = float(A.get("valid_min",-1.e20))
mx = float(A.get("valid_max",1.e20))
val = (mn+mx)/2.
try:
val = numpy.array([float(A.get("value",val)),])
except:
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(
outpath=opts["outpath"],
experiment_id="historical",
institution="CMOR-test",
source="CMOR-test",
calendar="gregorian",
realization=1,
contact="dummy",
history="dummy",
model_id="CMOR-test",
forcing="GHG",
institute_id="CMOR-test",
parent_experiment_id="piControl",
branch_time=109207.0,
parent_experiment_rip="r1i1p1",
)
# Load the CMIP tables into memory.
tables = []
tables.append(cmor.load_table("CMIP5_grids"))
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 + 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]) / 2.0
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,
]
)
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, 500],
]
)
plev_axis_id = cmor.axis(
table_entry="plevs",
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(-90.0, 89.0, 180.0), np.linspace(-89.0, 90.0, 180.0)))
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(0.0, 359.0, 360.0), np.linspace(1.0, 360.0, 360.0)))
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(1.0e20)
if threeD:
variable_id = cmor.variable(table_entry="ts", units="K", axis_ids=axis_ids, type="f", missing_value=in_missing)
else:
variable_id = cmor.variable(table_entry="ta", units="K", axis_ids=axis_ids, type="f", missing_value=in_missing)
#
# Write the data
#
if threeD:
data_vals = np.zeros((len(tvals), len(lat), len(lon)), np.float32) + 290.0
else:
data_vals = np.zeros((len(tvals), len(plev), len(lat), len(lon)), np.float32) + 290.0
try:
print "writing..."
cmor.write(
variable_id, data_vals[:], ntimes_passed=np.shape(data_vals)[0]
) # assuming time is the first dimension
except Exception, e:
raise Exception("ERROR writing data!")
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [
{
'table_entry': 'time2',
'units': 'days since 2000-01-01 00:00:00',
},
{
'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [500, 1000.],
'cell_bounds': [0., 750., 1200.]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
print 'doing:', axis
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('tnpeot', 'W m-2', 274), ):
values = numpy.array([
value,
] * len(axes[1]['coord_vals']), numpy.float32)
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99)
for i in range(12):
cmor.write(varid,
values,
time_vals=[30 * i + 15],
time_bnds=[[30 * i, 360 + 30 * (i + 1)]])
cmor.close()
nlat = 360
dlat = 180./nlat
nlon = 720
dlon = 360./nlon
nlev = 17
ntimes = 12
lats = numpy.arange(-90+dlat/2.,90,dlat)
blats = numpy.arange(-90,90+dlat,dlat)
lons = numpy.arange(0+dlon/2.,360.,dlon)
blons = numpy.arange(0,360.+dlon,dlon)
cmor.setup(inpath='.',netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical', 'ukmo', 'HadCM3', 'gregorian',model_id='HadCM3',outpath='Test',forcing='N/A', parent_experiment_id="lgm", parent_experiment_rip="r1i1p1",branch_time=0,contact="Juan Uribe",institute_id="myinst")
table='Tables/CMIP5_Amon'
cmor.load_table(table)
ilat = cmor.axis(table_entry='latitude',coord_vals=lats,cell_bounds=blats,units='degrees_north')
ilon = cmor.axis(table_entry='longitude',coord_vals=lons,cell_bounds=blons,units='degrees_east')
itim = cmor.axis(table_entry='time',units='months since 2010')#,coord_vals=numpy.arange(ntimes,dtype=numpy.float),cell_bounds=numpy.arange(ntimes+1,dtype=float),units='months since 2000')
ilev = cmor.axis(table_entry='plevs',coord_vals=numpy.array([1000.,925,850,700,600,500,400,300,250,200,150,100,70,50,30,20,10]),units='hPa')
axes=[itim,ilev,ilat,ilon]
var = cmor.variable(table_entry='ta',units='K',axis_ids=axes)
ntimes=250
data = numpy.random.random((nlev,nlat,nlon))*30+273.15
f = cdms2.open("Test/GR30s_halo.nc")
nlon = f['grid_center_lat'].shape[1]
nlat = f['grid_center_lat'].shape[0]
error_flag = cmor.setup(inpath='Test', netcdf_file_action=cmor.CMOR_APPEND)
error_flag = cmor.dataset(
outpath='Joerg',
experiment_id='DcppC2',
institution='GICC (Generic International Climate Center, Geneva, Switzerland)',
institute_id="GICC",
source='GICCM1 (2002): ',
calendar='360_day',
realization=1,
contact='Rusty Koder (koder@middle_earth.net) ',
history='Output from archivcl_A1.nce/giccm_03_std_2xCO2_2256.',
comment='Equilibrium reached after 30-year spin-up ',
references='Model described by Koder and Tolkien ',
model_id="GICCM1",
forcing="Ant",
parent_experiment_id="lgm", branch_time=0)
ntables = [cmor.load_table("Tables/CMIP6_grids")]
ntables.append(cmor.load_table("Tables/CMIP5_OImon"))
cmor.set_table(ntables[0])
axes = numpy.zeros(2, numpy.int32)
levs.append((b[0]+b[1])/2.)
levs=numpy.array(levs)
print levs
ipth="Test"
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action = cmor.CMOR_REPLACE,
logfile = None)
cmor.dataset(
outpath = ipth,
experiment_id = "present-day control experiment",
institution = "PCMDI",
source = "PCMDI",
calendar = "standard",
model_id="pcmdi-09a",forcing="forcing")
cmor.load_table("python_test_table_A")
nlat = 90
dlat = 180/nlat
nlon = 180
dlon = 360./nlon
lats = numpy.arange(-90+dlat/2.,90,dlat)
lons = numpy.arange(0,360.,dlon)
ntime = 12
myaxes=numpy.zeros(9,dtype='i')
myaxes2=numpy.zeros(9,dtype='i')
myvars=numpy.zeros(9,dtype='i')
cmor.setup(inpath=ipth,set_verbosity=cmor.CMOR_NORMAL, netcdf_file_action = cmor.CMOR_REPLACE, exit_control = cmor.CMOR_EXIT_ON_MAJOR);
cmor.dataset(
outpath = opth,
experiment_id = "historical",
institution = "GICC (Generic International Climate Center, Geneva, Switzerland)",
source = "GICCM1 2002: atmosphere: GICAM3 (gicam_0_brnchT_itea_2, T63L32); ocean: MOM (mom3_ver_3.5.2, 2x3L15); sea ice: GISIM4; land: GILSM2.5",
calendar = "standard",
realization = 1,
contact = "Tim Lincecum",
history = "Testing noncartesian grid and ocn sigma",
comment = "trying to see if it core dumps",
references = "ref",
leap_year=0,
leap_month=0,
month_lengths=None,
model_id="GICCM1",
forcing="Ant, Nat",
institute_id="pcmdi",
parent_experiment_id="piControl",
parent_experiment_rip="r1i2p3",
branch_time=18336.33)
tables=[]
a = cmor.load_table("Tables/CMIP5_grids")
tables.append(a)
tables.append(cmor.load_table("Tables/CMIP5_Omon"))
print 'Tables ids:',tables
filename = sys.argv[1]
config = load(open(filename).read())
if not os.path.exists('cmip5'):
os.mkdir('cmip5')
start_for_variable = datetime.datetime.now()
for variable in config['variables'].values():
start_this_variable = datetime.datetime.now()
if variable['realm'] in ['atmos', 'land', 'landIce land']:
# setup output file
cmor_setup_start = datetime.datetime.now()
cmor.setup(inpath=TABLES, netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset(**config['description'])
cmor.load_table(variable['table'])
print "####prof cmor setup", datetime.datetime.now() - cmor_setup_start
# read ctls
files = glob.glob('*.ctl')
n = len(files)
bounds = []
data = []
for i, filename in enumerate(files):
f = ctler.CTLReader(filename)
values = f.variables[variable['name in BMGCS'].upper()][:]
data.append(values * adjust_units(variable['units in BMGCS'],
variable['desired units']))
bounds.append(f.variables['time'][0])
data = np.concatenate(data, axis=0)
def process(rc):
'''
Convert netcdf/matlab/grads files into CMIP5 format.
'''
pdb.set_trace()
# ----------------------------
# Loop yearly on file list.
# ----------------------------
file_template = rc['file_template'].split(",")
if (len(file_template) == 2):
template_parameter = file_template[1]
rc['file_template'] = file_template[0]
else:
template_parameter = 'years'
for year in rc[template_parameter].split(","):
if (year == ''):
files = os.popen("ls " + rc['file_template']).readlines()
else:
# ------------------------------------------------
# Use string formating for path with same argument
# ------------------------------------------------
try:
tmplFile = rc['file_template'] % (year)
except:
tmplFile = rc['file_template'].format(year)
if (not os.path.isfile(tmplFile)):
print "**** Warning %s not found\n" % (tmplFile)
continue
files = os.popen("ls " + tmplFile).readlines()
if (files == []):
print "No file found: Check your resource file"
return -1
# ------------------------------------------------
# Get the right handler to manage this file format
# ------------------------------------------------
Handler = factory.HandlerFormats(files[0].strip())
# -----------------------------------
# Take care of cmor initialization.
# -----------------------------------
cmor.setup(inpath=rc['inpath'], netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset(experiment_id=rc['experiment_id'],
institution=rc['institution'],
calendar=rc['calendar'],
institute_id=rc['institute_id'],
model_id=rc['model_id'],
source=rc['source'],
contact=rc['contact'],
references=rc['references'])
# -----------------------------------------
# add extra Global Attributes for obs4MIPs.
# -----------------------------------------
cmor.set_cur_dataset_attribute('instrument', rc['instrument'])
cmor.set_cur_dataset_attribute('mip_specs', rc['mip_specs'])
cmor.set_cur_dataset_attribute('data_structure', rc['data_structure'])
cmor.set_cur_dataset_attribute('source_type', rc['source_type'])
cmor.set_cur_dataset_attribute('source_id', rc['source_id'])
cmor.set_cur_dataset_attribute('realm', rc['realm'])
cmor.set_cur_dataset_attribute('obs_project', rc['obs_project'])
cmor.set_cur_dataset_attribute('processing_version',
rc['processing_version'])
cmor.set_cur_dataset_attribute('processing_level',
rc['processing_level'])
cmor.load_table(rc['table'])
# ---------------------------------------------------------------------
# We loop on each file found, a new cmor file will be create on each
# iteration. If you want to aggregate, you need to use Grads ctl file
# or NeCDF list of file.
# ---------------------------------------------------------------------
for file in files:
fnm = file.strip() # Get rid of \n
aVariable = eval(rc['original_var'])
nbVariable = len(aVariable)
# -----------------------------------------------------
# ECMWF needs synoptic time 00z and 12z in he filename.
# We extract it from the first file in the list.
# -----------------------------------------------------
if (rc['source_fn'] == 'SYNOPTIC'):
index = fnm.find('z.')
rc['SYNOPTIC'] = fnm[index - 2:index]
# -----------------------
# Work on all variables
# -------------------------
for j in arange(nbVariable):
# ----------------------------------------------------
# Fetch the variable directly or excute equation.
# ----------------------------------------------------
try:
variable = aVariable[j]
Handler.open(fnm, variable=variable)
rc['cvrt_original_var'] = aVariable[j]
print "Working on variable %s " % variable
except:
if (aVariable[j] != 'equation'):
print "Variable %s can't open" % variable
continue
else:
print "Executing %s " % eval(rc['equation'])[j]
# pdb.set_trace()
rc['cvrt_original_units'] = eval(rc['original_units'])[j]
rc['cvrt_cmor_var'] = eval(rc['cmor_var'])[j]
rc['cvrt_equation'] = eval(rc['equation'])[j]
rc['cvrt_level'] = eval(rc['level'])[j]
data = Handler.getData()
# ----------------------------------------------------------
# Evaluate equation if needed. Usually used to change units
# ----------------------------------------------------------
if (rc['cvrt_equation'][0] == '@'):
fncName = rc['cvrt_equation'][1:]
fnc = import_equation("equations.%s" % fncName)
data[:] = fnc(Handler)
else:
data[:] = eval(rc['cvrt_equation'])
# -------------------------------------------------------------
# Save filled value in case data type is changed in createAxes
# -------------------------------------------------------------
fill_value = data.fill_value
# ---------------------------------------------
# Extract latitude/longitude
# ---------------------------------------------
lonvals = Handler.getLongitude()
latvals = Handler.getLatitude()
# ---------------------
# Create cmor time axis
# ----------------------
(rel_time, rel_time_bnds) = createTime(Handler, rc)
# ---------------------------------------------------
# Create cmor axes and add an axis to data if needed
# ---------------------------------------------------
(axes, data) = createAxes(rc, latvals, lonvals, data)
axis_ids = list()
for axis in axes:
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
# ----------------------------------------------------------
# Create cmor variable
# Note: since this is in the loop, a new cmor file will be
# create for each cmor write command.
# ----------------------------------------------------------
varid = cmor.variable(table_entry=rc['cvrt_cmor_var'],
axis_ids=axis_ids,
history='',
missing_value=fill_value,
original_name=rc['cvrt_original_var'],
units=rc['cvrt_original_units'])
# -------------------------------
# Write data for this time frame.
# -------------------------------
cmor.write(varid,data,\
time_vals=rel_time,time_bnds=rel_time_bnds)
cmor.close(varid, file_name=True)
# ---------------------------------------
# Rename cmor files according to project.
# ---------------------------------------
if (movefiles(rc)):
return -2
cmor.close()
return 0
cmor.setup(inpath="Test",
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action=cmor.CMOR_REPLACE,
exit_control=cmor.CMOR_EXIT_ON_MAJOR)
cmor.dataset(
outpath="Test",
experiment_id="historical",
institution=
"GICC (Generic International Climate Center, Geneva, Switzerland)",
source=
"GICCM1 (2002): atmosphere: GICAM3 (gicam_0_brnchT_itea_2, T63L32); ocean: MOM (mom3_ver_3.5.2, 2x3L15); sea ice: GISIM4; land: GILSM2.5",
calendar="standard",
realization=1,
contact="Charles Doutriaux ([email protected])",
history="Test for speed and compression.",
comment="NetCDF4 vs NetCDF3 testing",
references="http://cdat.sf.net",
leap_year=0,
leap_month=0,
institute_id="PCMDI",
month_lengths=None,
model_id="GICCM1",
forcing="SO",
parent_experiment_id="lgm",
branch_time=4.)
tables = []
tables.append(cmor.load_table("mytable"))
print 'Tables ids:', tables
ntimes = 1
lats = numpy.arange(90 - dlat / 2., -90, -dlat)
blats = numpy.arange(90, -90 - dlat, -dlat)
lats2 = numpy.arange(-90 + dlat / 2., 90, dlat)
blats2 = numpy.arange(-90, 90 + dlat, dlat)
lons = numpy.arange(0 + dlon / 2., 360., dlon)
blons = numpy.arange(0, 360. + dlon, dlon)
cmor.setup(inpath='.', netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset('historical',
'ukmo',
'HadCM3',
'gregorian',
model_id='HadCM3',
outpath='Test',
forcing='TO, Nat',
contact="Jonathan sanchez",
parent_experiment_id="lgm",
parent_experiment_rip="r1i1p1",
branch_time=0,
institute_id='pcmdi')
table = 'Tables/CMIP5_Amon'
cmor.load_table(table)
data = lats[:, numpy.newaxis] * lons[numpy.newaxis, :]
data = (data + 29000) / 750. + 233.2
ilat = cmor.axis(table_entry='latitude',
coord_vals=lats,
cell_bounds=blats,
filename = sys.argv[1]
config = load(open(filename).read())
if not os.path.exists("cmip5"):
os.mkdir("cmip5")
start_for_variable = datetime.datetime.now()
for variable in config["variables"].values():
start_this_variable = datetime.datetime.now()
if variable["realm"] in ["atmos", "land", "landIce land"]:
# setup output file
cmor_setup_start = datetime.datetime.now()
cmor.setup(inpath=TABLES, netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset(**config["description"])
cmor.load_table(variable["table"])
print "####prof cmor setup", datetime.datetime.now() - cmor_setup_start
# read ctls
files = glob.glob("*.ctl")
n = len(files)
bounds = []
data = []
for i, filename in enumerate(files):
f = ctler.CTLReader(filename)
values = f.variables[variable["name in BMGCS"].upper()][:]
data.append(values * adjust_units(variable["units in BMGCS"], variable["desired units"]))
bounds.append(f.variables["time"][0])
data = np.concatenate(data, axis=0)
dt = bounds[1] - bounds[0]
def main():
cmor.setup(inpath='/git/cmip5-cmor-tables/Tables',
netcdf_file_action=cmor.CMOR_REPLACE_3)
cmor.dataset('pre-industrial control',
'ukmo',
'HadCM3',
'360_day',
institute_id='ukmo',
model_id='HadCM3',
history='some global history',
forcing='N/A',
parent_experiment_id='N/A',
parent_experiment_rip='N/A',
branch_time=0,
contact='brian clough')
table = 'CMIP5_Oclim'
cmor.load_table(table)
axes = [
{
'table_entry': 'time2',
'units': 'days since 1850-01-01 00:00:00',
'coord_vals': [
15.5,
45,
],
'cell_bounds': [[0, 396], [31, 424]]
},
{
'table_entry': 'depth_coord',
'units': 'm',
'coord_vals': [5000., 3000., 2000., 1000.],
'cell_bounds': [5000., 3000., 2000., 1000., 0]
},
{
'table_entry': 'latitude',
'units': 'degrees_north',
'coord_vals': [0],
'cell_bounds': [-1, 1]
},
{
'table_entry': 'longitude',
'units': 'degrees_east',
'coord_vals': [90],
'cell_bounds': [89, 91]
},
]
axis_ids = list()
for axis in axes:
print 'doing:', axis
axis_id = cmor.axis(**axis)
axis_ids.append(axis_id)
for var, units, value in (('difvso', 'm2 s-1', 274.), ):
values = numpy.ones(map(lambda x: len(x["coord_vals"]), axes)) * value
values = values.astype("f")
varid = cmor.variable(var,
units,
axis_ids,
history='variable history',
missing_value=-99)
cmor.write(varid, values)
cmor.close()
s=s.replace("${DEFLATE_LEVEL}",str(level))
s=s.replace("${DEFLATE}",str(deflate))
s=s.replace("${SHUFFLE}",str(shuffle))
f=open("mytable","w")
f.write(s)
f.close()
cmor.setup(inpath="Test",set_verbosity=cmor.CMOR_NORMAL, netcdf_file_action = cmor.CMOR_REPLACE, exit_control = cmor.CMOR_EXIT_ON_MAJOR);
cmor.dataset(
outpath = "Test",
experiment_id = "lgm",
institution = "GICC (Generic International Climate Center, Geneva, Switzerland)",
source = "GICCM1 (2002): atmosphere: GICAM3 (gicam_0_brnchT_itea_2, T63L32); ocean: MOM (mom3_ver_3.5.2, 2x3L15); sea ice: GISIM4; land: GILSM2.5",
calendar = "standard",
realization = 1,
contact = "Charles Doutriaux ([email protected])",
history = "Test for speed and compression.",
comment = "NetCDF4 vs NetCDF3 testing",
references = "http://cdat.sf.net",
leap_year=0,
leap_month=0,
institute_id="PCMDI",
month_lengths=None,model_id="GICCM1",forcing="SO",parent_experiment_id="N/A",branch_time=0.)
tables=[]
tables.append(cmor.load_table("mytable"))
print 'Tables ids:',tables
## read in data, just one slice
f=cdms2.open(cdat_info.get_prefix()+'/sample_data/tas_ccsr-95a.xml')
pth = os.path.split(os.path.realpath(os.curdir))
if pth[-1] == 'Test':
ipth = opth = '.'
else:
ipth = opth = 'Test'
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action=cmor.CMOR_REPLACE)
cmor.dataset(outpath=opth,
experiment_id="historical",
institution="PCMDI",
source="GICCM1 2002",
calendar="standard",
contact="Tim Lincecum",
institute_id="PCMDI",
model_id="GICCM1",
forcing="Nat",
parent_experiment_id="N/A",
parent_experiment_rip="N/A",
branch_time=0.)
cmor.load_table("Tables/CMIP5_Amon")
s = f("clt", slice(14))
Saxes = s.getAxisList()
axes = []
for ax in Saxes[1:]:
tmp = cmor.axis(ax.id,
coord_vals=ax[:],
import cmor
import numpy
ipth = "Test"
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action=cmor.CMOR_REPLACE,
logfile=None)
cmor.dataset(outpath=ipth,
experiment_id="lgm",
institution="PCMDI",
source="PCMDI",
calendar="standard",
model_id="pcmdi-09a",
forcing="forcing")
cmor.load_table("Tables/CMIP6_Omon.json")
nlat = 90
dlat = 180 / nlat
nlon = 180
dlon = 360. / nlon
nlev = 5
lats = numpy.arange(-90 + dlat / 2., 90, dlat)
blats = numpy.arange(-90, 90 + dlat, dlat)
lons = numpy.arange(0 + dlon / 2., 360., dlon)
blons = numpy.arange(0, 360. + dlon, dlon)
ntime = 12
def mywrite(data = None, time_vals = None, append_to = None,cell_bounds=None):
breq = "100000. 80000. 80000. 68000. 68000. 56000. 56000. 44000. 44000. 31000. 31000. 18000. 18000. 0.".split()
bnds_req = []
for b in breq:
bnds_req.append(float(b))
bnds_req=numpy.array(bnds_req)
bnds_req.shape=(7,2)
print bnds_req[-2], bnds_req.shape
levs=[]
for b in bnds_req:
levs.append((b[0]+b[1])/2.)
levs=numpy.array(levs)
print levs
ipth="Test"
if append_to is None:
mode = cmor.CMOR_REPLACE
else:
mode = cmor.CMOR_APPEND
print 'Mode in python:',mode
cmor.setup(inpath=ipth,
set_verbosity=cmor.CMOR_NORMAL,
netcdf_file_action = mode,
logfile = None)
cmor.dataset(
outpath = ipth,
experiment_id = "lgm",
institution = "PCMDI",
source = "GICCM1 2002",
institute_id="PCMDI",
calendar = "standard",
contact="Pablo Sandoval",
model_id="GICCM1",forcing="Nat",
parent_experiment_id="historical",
parent_experiment_rip="r1i3p2",
branch_time=3.14159)
cmor.load_table("Tables/CMIP5_Amon")
dlat = 180/nlat
dlon = 360./nlon
lats = numpy.arange(-90+dlat/2.,90,dlat)
bnds_lat = numpy.arange(-90,90+dlat,dlat)
lons = numpy.arange(0+dlon/2.,360.,dlon)-180.
bnds_lon = numpy.arange(0,360.+dlon,dlon)-180.
plevs = numpy.array([100000., 92500., 85000., 70000.,
60000., 50000., 40000., 30000., 25000., 20000.,
15000., 10000., 7000., 5000., 3000., 2000., 1000.])
itim = cmor.axis(table_entry='time',units='month since 2008')
#itim = cmor.axis(table_entry='time',units='month since 2008',coord_vals=numpy.arange(0,12,1))
ilat = cmor.axis(table_entry='latitude',coord_vals=lats,units='degrees_north',cell_bounds=bnds_lat)
ilon = cmor.axis(table_entry='longitude',coord_vals=lons,units='degrees_east',cell_bounds=bnds_lon)
print 'so far',itim,ilat,ilon
ilev = cmor.axis(table_entry="plevs",coord_vals=plevs,units="Pa")
iv = cmor.variable(table_entry='ta',axis_ids=numpy.array((itim,ilev,ilat,ilon)),units='K')
#cmor.write(iv,data)
if append_to is None:
print 'time:',time_vals
print 'bnds:',cell_bounds
cmor.write(iv,data,time_vals=time_vals,time_bnds=cell_bounds)#,file_suffix="with-appending")
else:
print 'Ok writing with a suffix',append_to
cmor.write(iv,data,time_vals=time_vals,file_suffix=append_to,time_bnds=cell_bounds)
print 'and back'
file = cmor.close(iv,file_name=True)
print 'Ok dumped to:',file
cmor.close()
return file
