def test_timing_use_optimizations(self):
n = list(range(10))
t = {True: [], False: []}
for use_optimizations in [True, False]:
for ii in n:
t1 = time.time()
rd = self.test_data.get_rd('cancm4_tas')
ops = ocgis.OcgOperations(dataset=rd,
calc=[{
'func': 'mean',
'name': 'mean'
}],
calc_grouping=['month'],
output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
prefix=str(ii) +
str(use_optimizations),
agg_selection=True)
compute(ops,
5,
verbose=False,
use_optimizations=use_optimizations)
t2 = time.time()
t[use_optimizations].append(t2 - t1)
tmean = {
k: {
'mean': np.array(v).mean(),
'stdev': np.array(v).std()
}
for k, v in t.items()
}
self.assertTrue(tmean[True]['mean'] < tmean[False]['mean'])
def test_compute_with_geom(self):
rd = self.test_data.get_rd('cancm4_tas')
ops = ocgis.OcgOperations(dataset=rd,
calc=[{
'func': 'mean',
'name': 'mean'
}],
calc_grouping=['month'],
output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
agg_selection=True)
ret = compute(ops, 5, verbose=False)
ops.prefix = 'ocgis'
ret_ocgis = ops.execute()
self.assertNcEqual(ret,
ret_ocgis,
check_fill_value=False,
check_types=False,
ignore_attributes={
'global': ['history'],
'mean': ['_FillValue']
})
def test_compute_small(self):
rd = self.test_data.get_rd('cancm4_tas')
# use a smaller netCDF as target
ops = ocgis.OcgOperations(dataset=rd,
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
output_format='nc',
prefix='sub',
add_auxiliary_files=False,
agg_selection=True)
sub = ops.execute()
# use the compute function
rd_sub = ocgis.RequestDataset(sub, 'tas')
ops = ocgis.OcgOperations(dataset=rd_sub, calc=[{'func': 'mean', 'name': 'mean'}],
calc_grouping=['month'], output_format='nc',
add_auxiliary_files=False)
ret_compute = compute(ops, 5, verbose=False)
# now just run normally and ensure the answers are the same!
ops.prefix = 'ocgis_compare'
ops.add_auxiliary_files = False
ret_ocgis = ops.execute()
self.assertNcEqual(ret_compute, ret_ocgis, check_fill_value=False, check_types=False,
ignore_attributes={'global': ['history'], 'mean': ['_FillValue']})
def test_with_callback(self):
"""Test callback reports status appropriately."""
percentages = []
def callback(a, b):
percentages.append(a)
rd = self.test_data.get_rd('cancm4_tas',
kwds={'time_region': {
'month': [3]
}})
ops = ocgis.OcgOperations(dataset=rd,
calc=[{
'func': 'mean',
'name': 'mean'
}],
calc_grouping=['month'],
output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
callback=callback,
agg_selection=True)
ret = compute(ops, 3, verbose=False)
hundreds = np.array(percentages)
hundreds = hundreds >= 100.0
self.assertEqual(hundreds.sum(), 1)
def test_compute(self):
rd = self.test_data.get_rd('cancm4_tas')
kwds = {'percentile': 90, 'window_width': 5}
calc = [{'func': 'daily_perc', 'name': 'dp', 'kwds': kwds}]
ops = ocgis.OcgOperations(dataset=rd, geom='state_boundaries', select_ugid=[23], calc=calc,
output_format='nc', time_region={'year': [2002, 2003]})
ret = compute(ops, 2, verbose=False)
rd = ocgis.RequestDataset(uri=ret)
self.assertEqual(rd.get().shape, (1, 365, 1, 4, 3))
def test_compute_2d_grid(self):
path = self.get_path_to_2d_grid_netcdf()
rd = RequestDataset(path)
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}], calc_grouping=['month'],
output_format='nc', add_auxiliary_files=False, geom=[33.7, -35.9, 109.1, 9.4])
ret = compute(ops, 3, verbose=False)
field = RequestDataset(ret).get()
self.assertEqual(field['mean'].shape, (4, 17, 28))
def test_compute_2d_grid(self):
path = self.get_path_to_2d_grid_netcdf()
rd = RequestDataset(path)
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}], calc_grouping=['month'],
output_format='nc', add_auxiliary_files=False, geom=[33.7, -35.9, 109.1, 9.4])
ret = compute(ops, 3, verbose=False)
field = RequestDataset(ret).get()
self.assertEqual(field.shape, (1, 4, 1, 16, 27))
def test_timing_use_optimizations(self):
n = range(10)
t = {True: [], False: []}
for use_optimizations in [True, False]:
for ii in n:
t1 = time.time()
rd = self.test_data.get_rd('cancm4_tas')
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}],
calc_grouping=['month'], output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
prefix=str(ii) + str(use_optimizations))
compute(ops, 5, verbose=False, use_optimizations=use_optimizations)
t2 = time.time()
t[use_optimizations].append(t2 - t1)
tmean = {k: {'mean': np.array(v).mean(), 'stdev': np.array(v).std()} for k, v in t.iteritems()}
self.assertTrue(tmean[True]['mean'] < tmean[False]['mean'])
def test_compute(self):
# ocgis.env.VERBOSE = True
# ocgis.env.DEBUG = True
verbose = False
n_tile_dimensions = 1
tile_range = [100,100]
rd = RequestDatasetCollection(self.test_data.get_rd('cancm4_tasmax_2011'))
calc = [{'func':'mean','name':'my_mean'},
{'func':'freq_perc','name':'perc_90','kwds':{'percentile':90,}},
{'func':'freq_perc','name':'perc_95','kwds':{'percentile':95,}},
{'func':'freq_perc','name':'perc_99','kwds':{'percentile':99,}}
]
calc_grouping = ['month']
## perform computations the standard way
if verbose: print('computing standard file...')
ops = ocgis.OcgOperations(dataset=rd,output_format='nc',calc=calc,
calc_grouping=calc_grouping,prefix='std')
std_file = ops.execute()
if verbose: print('standard file is: {0}'.format(std_file))
std_ds = nc.Dataset(std_file,'r')
std_meta = ocgis.Inspect(std_file).meta
for ii in range(n_tile_dimensions):
tile_dimension = np.random.random_integers(tile_range[0],tile_range[1])
if verbose: print('tile dimension: {0}'.format(tile_dimension))
## perform computations using tiling
tile_file = compute(rd,calc,calc_grouping,tile_dimension,verbose=verbose,
prefix='tile')
## ensure output paths are different
self.assertNotEqual(tile_file,std_file)
## confirm each variable is identical
tile_ds = nc.Dataset(tile_file,'r')
## compare calculated values
for element in calc:
tile_value,std_value = [ds.variables[element['name']][:] for ds in [tile_ds,std_ds]]
cmp = tile_value == std_value
self.assertTrue(cmp.all())
## compare meta dictionaries
tile_meta = ocgis.Inspect(tile_file).meta
for k in tile_meta.iterkeys():
for k2,v2 in tile_meta[k].iteritems():
ref = std_meta[k][k2]
self.assertEqual(v2,ref)
tile_ds.close()
std_ds.close()
def test_calculate_compute(self):
# ocgis.env.VERBOSE = True
# ocgis.env.DEBUG = True
calc = [{'func':'sfwe','name':'sfwe','kwds':{'tas':'tas','pr':'pr'}}]
time_range = None
rds = []
for var in [self.maurer_pr,self.maurer_tas]:
var.update({'time_range':time_range})
rds.append(var)
rdc = RequestDatasetCollection(rds)
sfwe = compute(rdc,calc,['month','year'],50,verbose=True,prefix='sfwe')
import ipdb;ipdb.set_trace()
def test_compute_with_geom(self):
rd = self.test_data.get_rd('cancm4_tas')
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}],
calc_grouping=['month'], output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False)
ret = compute(ops, 5, verbose=False)
ops.prefix = 'ocgis'
ret_ocgis = ops.execute()
self.assertNcEqual(ret, ret_ocgis, ignore_attributes={'global': ['history']})
def compute_sfwe_maurer():
def maurer_pr():
ret = {'uri':'Maurer02new_OBS_pr_daily.1971-2000.nc','variable':'pr'}
return(ret)
def maurer_tas():
ret = {'uri':'Maurer02new_OBS_tas_daily.1971-2000.nc','variable':'tas'}
return(ret)
ocgis.env.DIR_DATA = '/usr/local/climate_data/'
ocgis.env.DIR_OUTPUT = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2'
ocgis.env.OVERWRITE = True
calc = [{'func':'sfwe','name':'sfwe','kwds':{'tas':'tas','pr':'pr'}}]
time_range = None
rds = []
for var in [maurer_pr(),maurer_tas()]:
var.update({'time_range':time_range})
rds.append(var)
rdc = RequestDatasetCollection(rds)
sfwe = compute(rdc,calc,['month','year'],175,verbose=True,prefix='sfwe')
print(sfwe)
#sfwe = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/sfwe/sfwe.nc'
calc = [{'func':'sum','name':'p'}]
time_range = None
rds = [maurer_pr()]
rdc = RequestDatasetCollection(rds)
pr = compute(rdc,calc,['month','year'],175,verbose=True,prefix='pr')
print(pr)
#pr = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/pr/pr.nc'
calc = [{'func':'ratio_sfwe_p','name':'sfwe_p','kwds':{'sfwe':'sfwe','p':'p'}}]
rds = [RequestDataset(sfwe,'sfwe'),RequestDataset(pr,'p')]
rdc = RequestDatasetCollection(rds)
sfwe_p = compute(rdc,calc,None,175,verbose=True,prefix='sfwe_p')
print(sfwe_p)
def compute_sfwe_other():
ocgis.env.DIR_DATA = '/data/ben.koziol/sfwe/data'
ocgis.env.DIR_OUTPUT = '/home/local/WX/ben.koziol'
ocgis.env.OVERWRITE = False
tas = [['bcca_gfdl_cm2_1.gregorian.20c3m.run1.tas.1971-2000.nc','tas',None,'bcca_gfdl'],
['bcca_cccma_cgcm3_1.gregorian.20c3m.run1.tas.1971-2000.nc','tas',None,'bcca_cccma_cgcm3'],
['arrm_cgcm3_t63.20c3m.tas.NAm.1971-2000.nc','tas','365_day','arrm_cgcm3'],
['arrm_gfdl_2.1.20c3m.tas.NAm.1971-2000.nc','tas','365_day','arrm_gfdl']]
pr = [['bcca_gfdl_cm2_1.gregorian.20c3m.run1.pr.1971-2000.nc','pr',None,'bcca_gfdl'],
['bcca_cccma_cgcm3_1.gregorian.20c3m.run1.pr.1971-2000.nc','pr',None,'bcca_cccma_cgcm3'],
['arrm_cgcm3_t63.20c3m.pr.NAm.1971-2000.nc','pr','365_day','arrm_cgcm3'],
['arrm_gfdl_2.1.20c3m.pr.NAm.1971-2000.nc','pr','365_day','arrm_gfdl']]
for t,p in zip(tas,pr):
tas_rd = ocgis.RequestDataset(t[0],t[1],t_calendar=t[2])
pr_rd = ocgis.RequestDataset(p[0],p[1],t_calendar=p[2])
calc = [{'func':'sfwe','name':'sfwe','kwds':{'tas':'tas','pr':'pr'}}]
rdc = RequestDatasetCollection([tas_rd,pr_rd])
sfwe = compute(rdc,calc,['month','year'],175,verbose=True,prefix='sfwe_'+t[3])
print(sfwe)
#sfwe = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/sfwe/sfwe.nc'
calc = [{'func':'sum','name':'p'}]
rds = [pr_rd]
rdc = RequestDatasetCollection(rds)
pr = compute(rdc,calc,['month','year'],175,verbose=True,prefix='pr_'+t[3])
print(pr)
#pr = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/pr/pr.nc'
calc = [{'func':'ratio_sfwe_p','name':'sfwe_p','kwds':{'sfwe':'sfwe','p':'p'}}]
rds = [RequestDataset(sfwe,'sfwe',t_calendar=t[2]),RequestDataset(pr,'p',t_calendar=t[2])]
rdc = RequestDatasetCollection(rds)
sfwe_p = compute(rdc,calc,None,175,verbose=True,prefix='sfwe_p_'+t[3])
print(sfwe_p)
def test_compute_with_time_region(self):
rd = self.test_data.get_rd('cancm4_tas', kwds={'time_region': {'month': [3]}})
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}],
calc_grouping=['month'], output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
agg_selection=True)
ret = compute(ops, 5, verbose=False)
ops.prefix = 'ocgis'
ret_ocgis = ops.execute()
self.assertNcEqual(ret, ret_ocgis, check_fill_value=False, check_types=False,
ignore_attributes={'global': ['history'], 'mean': ['_FillValue']})
def test_system_compute(self):
rd = self.test_data.get_rd('cancm4_tas')
kwds = {'percentile': 90, 'window_width': 5}
calc = [{'func': 'daily_perc', 'name': 'dp', 'kwds': kwds}]
ops = ocgis.OcgOperations(dataset=rd,
geom='state_boundaries',
select_ugid=[23],
calc=calc,
output_format='nc',
time_region={'year': [2002, 2003]})
ret = compute(ops, 2, verbose=False)
rd = ocgis.RequestDataset(uri=ret)
actual_field = rd.get()
self.assertEqual(actual_field.data_variables[0].shape, (365, 3, 3))
def test_large_array_compute_local(self):
"""Test tiling works for percentile-based indice on a local dataset."""
raise SkipTest('function is very slow with ICCLIM 4.2.5')
calc = [{'func': 'icclim_TG10p', 'name': 'itg'}]
calc_grouping = ['month']
rd = self.test_data.get_rd('cancm4_tas')
ops = ocgis.OcgOperations(dataset=rd, calc=calc, calc_grouping=calc_grouping, output_format='nc',
geom='state_boundaries',
select_ugid=[24])
ret = compute(ops, 5, verbose=False)
with nc_scope(ret) as ds:
self.assertAlmostEqual(ds.variables['itg'][:].sum(), 2121.0, 6)
def test_multivariate_computation(self):
rd = self.test_data.get_rd('cancm4_tas', kwds={'time_region': {'month': [3]}})
rd2 = deepcopy(rd)
rd2.alias = 'tas2'
calc = [{'func': 'divide', 'name': 'ln', 'kwds': {'arr1': 'tas', 'arr2': 'tas2'}}]
ops = ocgis.OcgOperations(dataset=[rd, rd2], calc=calc,
calc_grouping=['month'], output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False)
ret = compute(ops, 5, verbose=False)
ops.prefix = 'ocgis'
ret_ocgis = ops.execute()
self.assertNcEqual(ret, ret_ocgis, ignore_attributes={'global': ['history']})
def test_compute_large(self):
"""Test calculations using compute are equivalent with standard calculations."""
# ocgis.env.VERBOSE = True
# ocgis.env.DEBUG = True
verbose = False
n_tile_dimensions = 1
tile_range = [100, 100]
rd = RequestDatasetCollection(self.test_data.get_rd('cancm4_tasmax_2011'))
calc = [{'func': 'mean', 'name': 'my_mean'},
{'func': 'freq_perc', 'name': 'perc_90', 'kwds': {'percentile': 90}},
{'func': 'freq_perc', 'name': 'perc_95', 'kwds': {'percentile': 95}},
{'func': 'freq_perc', 'name': 'perc_99', 'kwds': {'percentile': 99}}]
calc_grouping = ['month']
# construct the operational arguments to compute
ops_compute = ocgis.OcgOperations(dataset=rd, calc=calc, calc_grouping=calc_grouping, output_format='nc',
prefix='tile')
# perform computations the standard way
if verbose:
print('computing standard file...')
ops = ocgis.OcgOperations(dataset=rd, output_format='nc', calc=calc, calc_grouping=calc_grouping, prefix='std')
std_file = ops.execute()
if verbose:
print('standard file is: {0}'.format(std_file))
std_ds = nc.Dataset(std_file, 'r')
for ii in range(n_tile_dimensions):
tile_dimension = np.random.random_integers(tile_range[0], tile_range[1])
if verbose:
print('tile dimension: {0}'.format(tile_dimension))
# perform computations using tiling
tile_file = compute(ops_compute, tile_dimension, verbose=verbose)
# ensure output paths are different
self.assertNotEqual(tile_file, std_file)
self.assertNcEqual(std_file, tile_file, ignore_attributes={'global': ['history']})
# confirm each variable is identical
tile_ds = nc.Dataset(tile_file, 'r')
tile_ds.close()
std_ds.close()
def test_compute_with_geom(self):
grid = create_gridxy_global(resolution=5.0)
field = create_exact_field(grid, 'exact')
path = self.get_temporary_file_path('foo.nc')
field.write(path)
rd = RequestDataset(path)
calcs = [[{'func': 'mean', 'name': 'mean'}], None]
for ii, c in enumerate(calcs):
ops = ocgis.OcgOperations(dataset=rd, calc=c, calc_grouping=['month'], output_format='nc',
geom=self.path_state_boundaries, select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False, agg_selection=True, prefix=str(ii) + '_foo')
ret = compute(ops, 5, verbose=False)
ops.prefix = str(ii)
ret_ocgis = ops.execute()
self.assertNcEqual(ret, ret_ocgis, check_fill_value=False, check_types=False,
ignore_attributes={'global': ['history'], 'mean': ['_FillValue']})
def test_multivariate_computation(self):
rd = self.test_data.get_rd('cancm4_tas',
kwds={'time_region': {
'month': [3]
}})
rd2 = self.test_data.get_rd('cancm4_tas',
kwds={
'time_region': {
'month': [3]
},
'field_name': 'tas2',
'rename_variable': 'tas2'
})
calc = [{
'func': 'divide',
'name': 'ln',
'kwds': {
'arr1': 'tas',
'arr2': 'tas2'
}
}]
ops = ocgis.OcgOperations(dataset=[rd, rd2],
calc=calc,
calc_grouping=['month'],
output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
agg_selection=True)
ret = compute(ops, 5, verbose=False)
ops.prefix = 'ocgis'
ret_ocgis = ops.execute()
self.assertNcEqual(ret,
ret_ocgis,
check_fill_value=False,
check_types=False,
ignore_attributes={
'global': ['history'],
'ln': ['_FillValue']
})
def test_with_callback(self):
"""Test callback reports status appropriately."""
percentages = []
def callback(a, b):
percentages.append(a)
rd = self.test_data.get_rd('cancm4_tas', kwds={'time_region': {'month': [3]}})
ops = ocgis.OcgOperations(dataset=rd, calc=[{'func': 'mean', 'name': 'mean'}],
calc_grouping=['month'], output_format='nc',
geom='state_boundaries',
select_ugid=[2, 9, 12, 23, 25],
add_auxiliary_files=False,
callback=callback)
ret = compute(ops, 3, verbose=False)
hundreds = np.array(percentages)
hundreds = hundreds >= 100.0
self.assertEqual(hundreds.sum(), 1)
def test_calculate_compute(self):
# ocgis.env.VERBOSE = True
# ocgis.env.DEBUG = True
calc = [{
'func': 'sfwe',
'name': 'sfwe',
'kwds': {
'tas': 'tas',
'pr': 'pr'
}
}]
time_range = None
rds = []
for var in [self.maurer_pr, self.maurer_tas]:
var.update({'time_range': time_range})
rds.append(var)
rdc = RequestDatasetCollection(rds)
sfwe = compute(rdc,
calc, ['month', 'year'],
50,
verbose=True,
prefix='sfwe')
import ipdb
ipdb.set_trace()
output_format='nc',
prefix='ocgis_module_optimisation',
dir_output='/home/nils/data/',
add_auxiliary_files=False)
shnip = dt.now()
geom = ops.execute()
shnap = dt.now()
duration = (shnap - shnip).total_seconds()
print("operation performed with execute in {} sec.".format(duration))
print(geom)
tile_dimension=5 # default
shnip = dt.now()
geom = compute(ops, tile_dimension=tile_dimension, verbose=True)
shnap = dt.now()
duration = (shnap - shnip).total_seconds()
print("operation performed with compute in {} sec.".format(duration))
print(geom)
# ###################################
# check free memory available somehow
# from eggshell import util_functions as ufs
# free_memory = ufs.FreeMemory(unit='MB')
#
# # ###########################
# # check required memory space
#
def test_compute(self):
# ocgis.env.VERBOSE = True
# ocgis.env.DEBUG = True
verbose = False
n_tile_dimensions = 1
tile_range = [100, 100]
rd = RequestDatasetCollection(
self.test_data.get_rd('cancm4_tasmax_2011'))
calc = [{
'func': 'mean',
'name': 'my_mean'
}, {
'func': 'freq_perc',
'name': 'perc_90',
'kwds': {
'percentile': 90,
}
}, {
'func': 'freq_perc',
'name': 'perc_95',
'kwds': {
'percentile': 95,
}
}, {
'func': 'freq_perc',
'name': 'perc_99',
'kwds': {
'percentile': 99,
}
}]
calc_grouping = ['month']
## perform computations the standard way
if verbose: print('computing standard file...')
ops = ocgis.OcgOperations(dataset=rd,
output_format='nc',
calc=calc,
calc_grouping=calc_grouping,
prefix='std')
std_file = ops.execute()
if verbose: print('standard file is: {0}'.format(std_file))
std_ds = nc.Dataset(std_file, 'r')
std_meta = ocgis.Inspect(std_file).meta
for ii in range(n_tile_dimensions):
tile_dimension = np.random.random_integers(tile_range[0],
tile_range[1])
if verbose: print('tile dimension: {0}'.format(tile_dimension))
## perform computations using tiling
tile_file = compute(rd,
calc,
calc_grouping,
tile_dimension,
verbose=verbose,
prefix='tile')
## ensure output paths are different
self.assertNotEqual(tile_file, std_file)
## confirm each variable is identical
tile_ds = nc.Dataset(tile_file, 'r')
## compare calculated values
for element in calc:
tile_value, std_value = [
ds.variables[element['name']][:]
for ds in [tile_ds, std_ds]
]
cmp = tile_value == std_value
self.assertTrue(cmp.all())
## compare meta dictionaries
tile_meta = ocgis.Inspect(tile_file).meta
for k in tile_meta.iterkeys():
for k2, v2 in tile_meta[k].iteritems():
ref = std_meta[k][k2]
self.assertEqual(v2, ref)
tile_ds.close()
std_ds.close()
def call(resource=[], variable=None, dimension_map=None, calc=None,
calc_grouping= None, conform_units_to=None, memory_limit=None, prefix=None,
regrid_destination=None, regrid_options='bil', level_range=None,
geom=None, output_format_options=False, search_radius_mult=2.,
select_nearest=False, select_ugid=None, spatial_wrapping=None, t_calendar=None, time_region=None, time_range=None,
dir_output=curdir, output_format='nc'):
'''
ocgis operation call
:param resource:
:param variable: variable in the input file to be picked
:param dimension_map: dimension map in case of unconventional storage of data
:param calc: ocgis calc syntax for calculation partion
:param calc_grouping: time aggregate grouping
:param conform_units_to:
:param memory_limit: limit the amount of data to be loaded into the memory at once if None (default) free memory is detected by birdhouse
:param level_range: subset of given levels
:param prefix: string for the file base name
:param regrid_destination: file path with netCDF file with grid for output file
:param geom: name of shapefile stored in birdhouse shape cabinet
:param output_format_options: output options for netCDF e.g compression level()
:param regrid_destination: file containing the targed grid (griddes.txt or netCDF file)
:param regrid_options: methods for regridding:
'bil' = Bilinear interpolation
'bic' = Bicubic interpolation
'dis' = Distance-weighted average remapping
'nn' = nearest neighbour
'con' = First-order conservative remapping
'laf' = largest area fraction reamapping
:param search_radius_mult: search radius for point geometries. All included gridboxes will be returned
:param select_nearest: nearest neighbour selection for point geometries
:param select_ugid: ugid for appropriate polygons
:param spatial_wrapping: how to handle coordinates in case of subsets, options: None (default), 'wrap', 'unwrap'
:param time_region: select single month
:param time_range: sequence of two datetime.datetime objects to mark start and end point
:param dir_output (default= curdir):
:param output_format:
:return: output file path
'''
logger.info('Start ocgis module call function')
from ocgis import OcgOperations, RequestDataset , env
from ocgis.util.large_array import compute
import uuid
# prepare the environment
env.DIR_SHPCABINET = DIR_SHP
env.OVERWRITE = True
env.DIR_OUTPUT = dir_output
if geom != None:
spatial_reorder = True
spatial_wrapping = 'wrap'
else:
spatial_reorder = False
spatial_wrapping = None
if prefix == None:
prefix = str(uuid.uuid1())
env.PREFIX = prefix
if output_format_options == False:
output_format_options = None
elif output_format_options == True:
output_format_options={'data_model': 'NETCDF4', # NETCDF4_CLASSIC
'variable_kwargs': {'zlib': True, 'complevel': 9}}
else:
logger.info('output_format_options are set to %s ' % ( output_format_options ))
if type(resource) != list:
resource = list([resource])
# execute ocgis
logger.info('Execute ocgis module call function')
#if time_range != None:
#time_range = eval_timerange(resource, time_range)
if has_Lambert_Conformal(resource) == True and not geom == None:
logger.debug('input has Lambert_Conformal projection and can not subsetted with geom')
output = None
else:
try:
#if regrid_destination != None:
#rd_regrid = RequestDataset(uri=regrid_destination)
#else:
#rd_regrid = None
rd = RequestDataset(resource, variable=variable, level_range=level_range,
dimension_map=dimension_map, conform_units_to=conform_units_to,
time_region=time_region,t_calendar=t_calendar, time_range=time_range)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
spatial_wrapping=spatial_wrapping,
spatial_reorder=spatial_reorder,
# regrid_destination=rd_regrid,
# options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
output_format=output_format,
prefix=prefix,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
logger.info('OcgOperations set')
except Exception as e:
logger.debug('failed to setup OcgOperations')
raise
try:
from numpy import sqrt
from flyingpigeon.utils import FreeMemory
if memory_limit == None:
f = FreeMemory()
mem_kb = f.user_free
mem_mb = mem_kb / 1024.
mem_limit = mem_mb / 2. # set limit to half of the free memory
else:
mem_limit = memory_limit
if mem_limit >= 1024. * 4:
mem_limit = 1024. * 4
# 475.0 MB for openDAP
data_kb = ops.get_base_request_size()['total']
data_mb = data_kb / 1024.
if variable == None:
variable = rd.variable
logger.info('%s as variable dedected' % (variable))
#data_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
logger.info('data_mb = %s ; memory_limit = %s ' % (data_mb , mem_limit ))
except Exception as e:
logger.debug('failed to compare dataload with free memory %s ' % e)
raise
## check memory load
#from os import stat
#if memory_limit == None:
#f = FreeMemory()
#mem_kb = f.user_free
#mem_mb = mem_kb / 1024.
#mem_limit = mem_mb / 2. # set limit to half of the free memory
#else:
#mem_limit = memory_limit
#if mem_limit >= 1024. * 4:
#mem_limit = 1024. * 4
## 475.0 MB for openDAP
##if type(resource) == list :
##data_kb = stat(resource[0]).st_size * len(resource)
##else:
##data_kb = stat(resource).st_size
#size = ops.get_base_request_size()['total']
#data_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
#data_mb = data_kb / 1024.
#if variable == None:
#variable = rd.variable
#logger.info('%s as variable dedected' % (variable))
#logger.info('data_mb = %s ; memory_limit = %s ' % (data_mb , mem_limit ))
if data_mb <= mem_limit : # input is smaler than the half of free memory size
try:
logger.info('ocgis module call as ops.execute()')
geom_file = ops.execute()
except Exception as e:
logger.debug('failed to execute ocgis operation')
raise
else:
##########################
# calcultion of chunk size
##########################
try:
size = ops.get_base_request_size()
nb_time_coordinates_rd = size['variables'][variable]['temporal']['shape'][0]
element_in_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
element_in_mb = element_in_kb / 1024.
tile_dim = sqrt(mem_limit/(element_in_mb*nb_time_coordinates_rd)) # maximum chunk size
logger.info('ocgis module call compute with chunks')
print 'ocgis module call compute with chunks'
if calc == None:
calc = '%s=%s*1' % (variable, variable)
logger.info('calc set to = %s ' % calc)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
spatial_wrapping=spatial_wrapping,
spatial_reorder=spatial_reorder,
# regrid_destination=rd_regrid,
# options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
output_format=output_format,
prefix=prefix,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
geom_file = compute(ops, tile_dimension=int(tile_dim) , verbose=True)
except Exception as e:
logger.debug('failed to compute ocgis with chunks')
raise
logger.info('Succeeded with ocgis module call function')
############################################
# remapping according to regrid informations
############################################
if not regrid_destination == None:
try:
from tempfile import mkstemp
from cdo import Cdo
cdo = Cdo()
output = '%s.nc' % uuid.uuid1()
remap = 'remap%s' % regrid_options
call = [op for op in dir(cdo) if remap in op]
cmd = "output = cdo.%s('%s',input='%s', output='%s')" % (str(call[0]), regrid_destination, geom_file, output)
exec cmd
except Exception as e:
logger.debug('failed to remap')
raise
else:
output = geom_file
return output
def compute_sfwe_maurer():
def maurer_pr():
ret = {
'uri': 'Maurer02new_OBS_pr_daily.1971-2000.nc',
'variable': 'pr'
}
return (ret)
def maurer_tas():
ret = {
'uri': 'Maurer02new_OBS_tas_daily.1971-2000.nc',
'variable': 'tas'
}
return (ret)
ocgis.env.DIR_DATA = '/usr/local/climate_data/'
ocgis.env.DIR_OUTPUT = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2'
ocgis.env.OVERWRITE = True
calc = [{
'func': 'sfwe',
'name': 'sfwe',
'kwds': {
'tas': 'tas',
'pr': 'pr'
}
}]
time_range = None
rds = []
for var in [maurer_pr(), maurer_tas()]:
var.update({'time_range': time_range})
rds.append(var)
rdc = RequestDatasetCollection(rds)
sfwe = compute(rdc,
calc, ['month', 'year'],
175,
verbose=True,
prefix='sfwe')
print(sfwe)
#sfwe = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/sfwe/sfwe.nc'
calc = [{'func': 'sum', 'name': 'p'}]
time_range = None
rds = [maurer_pr()]
rdc = RequestDatasetCollection(rds)
pr = compute(rdc, calc, ['month', 'year'], 175, verbose=True, prefix='pr')
print(pr)
#pr = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/pr/pr.nc'
calc = [{
'func': 'ratio_sfwe_p',
'name': 'sfwe_p',
'kwds': {
'sfwe': 'sfwe',
'p': 'p'
}
}]
rds = [RequestDataset(sfwe, 'sfwe'), RequestDataset(pr, 'p')]
rdc = RequestDatasetCollection(rds)
sfwe_p = compute(rdc, calc, None, 175, verbose=True, prefix='sfwe_p')
print(sfwe_p)
def compute_sfwe_other():
ocgis.env.DIR_DATA = '/data/ben.koziol/sfwe/data'
ocgis.env.DIR_OUTPUT = '/home/local/WX/ben.koziol'
ocgis.env.OVERWRITE = False
tas = [[
'bcca_gfdl_cm2_1.gregorian.20c3m.run1.tas.1971-2000.nc', 'tas', None,
'bcca_gfdl'
],
[
'bcca_cccma_cgcm3_1.gregorian.20c3m.run1.tas.1971-2000.nc',
'tas', None, 'bcca_cccma_cgcm3'
],
[
'arrm_cgcm3_t63.20c3m.tas.NAm.1971-2000.nc', 'tas', '365_day',
'arrm_cgcm3'
],
[
'arrm_gfdl_2.1.20c3m.tas.NAm.1971-2000.nc', 'tas', '365_day',
'arrm_gfdl'
]]
pr = [[
'bcca_gfdl_cm2_1.gregorian.20c3m.run1.pr.1971-2000.nc', 'pr', None,
'bcca_gfdl'
],
[
'bcca_cccma_cgcm3_1.gregorian.20c3m.run1.pr.1971-2000.nc', 'pr',
None, 'bcca_cccma_cgcm3'
],
[
'arrm_cgcm3_t63.20c3m.pr.NAm.1971-2000.nc', 'pr', '365_day',
'arrm_cgcm3'
],
[
'arrm_gfdl_2.1.20c3m.pr.NAm.1971-2000.nc', 'pr', '365_day',
'arrm_gfdl'
]]
for t, p in zip(tas, pr):
tas_rd = ocgis.RequestDataset(t[0], t[1], t_calendar=t[2])
pr_rd = ocgis.RequestDataset(p[0], p[1], t_calendar=p[2])
calc = [{
'func': 'sfwe',
'name': 'sfwe',
'kwds': {
'tas': 'tas',
'pr': 'pr'
}
}]
rdc = RequestDatasetCollection([tas_rd, pr_rd])
sfwe = compute(rdc,
calc, ['month', 'year'],
175,
verbose=True,
prefix='sfwe_' + t[3])
print(sfwe)
#sfwe = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/sfwe/sfwe.nc'
calc = [{'func': 'sum', 'name': 'p'}]
rds = [pr_rd]
rdc = RequestDatasetCollection(rds)
pr = compute(rdc,
calc, ['month', 'year'],
175,
verbose=True,
prefix='pr_' + t[3])
print(pr)
#pr = '/home/local/WX/ben.koziol/climate_data/QED-2013/sfwe/maurer02v2/pr/pr.nc'
calc = [{
'func': 'ratio_sfwe_p',
'name': 'sfwe_p',
'kwds': {
'sfwe': 'sfwe',
'p': 'p'
}
}]
rds = [
RequestDataset(sfwe, 'sfwe', t_calendar=t[2]),
RequestDataset(pr, 'p', t_calendar=t[2])
]
rdc = RequestDatasetCollection(rds)
sfwe_p = compute(rdc,
calc,
None,
175,
verbose=True,
prefix='sfwe_p_' + t[3])
print(sfwe_p)
def call(resource=[], variable=None, dimension_map=None, calc=None,
calc_grouping= None, conform_units_to=None, memory_limit=None, prefix=None,
regrid_destination=None, regrid_options='bil', level_range=None,
geom=None, output_format_options=False, search_radius_mult=2.,
select_nearest=False, select_ugid=None, spatial_wrapping=None, time_region=None, time_range=None,
dir_output=curdir, output_format='nc'):
'''
ocgis operation call
:param resource:
:param variable: variable in the input file to be picked
:param dimension_map: dimension map in case of unconventional starage of data
:param calc: ocgis calc syntax for calcultion opartion
:param calc_grouping: time aggregate grouping
:param conform_units_to:
:param memory_limit: limit the amout of data to be loaded into the memory at once if None(default) free memory is detected by birdhouse
:param level_range: subset of given levels
:param prefix: string for the file base name
:param regrid_destination: file path with netCDF file with grid for outout file
:param geom: name of shapefile stored in birdhouse shape cabinet
:param output_format_options: output options for netCDF e.g compression level()
:param regrid_destination: file containing the targed grid (griddes.txt or netCDF file)
:param regrid_options: methods for regridding:
'bil' = Biliniar interpolation
'bic' = Bicubic interpolation
'dis' = Distance weighted average remapping
'nn' = nearest neighbour
'con' = First order concerative remapping
'laf' = largest area fraction reamapping
:param search_radius_mult: search radius for point geometries. All included gridboxes will be returned
:param select_nearest: neares neighbour selection for point geometries
:param select_ugid: ugid for appropriate poligons
:param spatial_wrapping: how to handle coordinates in case of subsets, options: None(default), 'wrap', 'unwrap'
:param time_region: select single month
:param time_range: sequence of two datetime.datetime objects to mark start and end point
:param dir_output (default= curdir):
:param output_format:
:return: output file path
'''
logger.info('Start ocgis module call function')
from ocgis import OcgOperations, RequestDataset , env
from ocgis.util.large_array import compute
import uuid
# prepare the environment
env.DIR_SHPCABINET = DIR_SHP
env.OVERWRITE = True
env.DIR_OUTPUT = dir_output
if geom != None:
spatial_reorder = True
spatial_wrapping = 'wrap'
else:
spatial_reorder = False
spatial_wrapping = None
if prefix == None:
prefix = str(uuid.uuid1())
env.PREFIX = prefix
if output_format_options == False:
output_format_options = None
elif output_format_options == True:
output_format_options={'data_model': 'NETCDF4', # NETCDF4_CLASSIC
'variable_kwargs': {'zlib': True, 'complevel': 9}}
else:
logger.info('output_format_options are set to %s ' % ( output_format_options ))
if type(resource) != list:
resource = list([resource])
# execute ocgis
logger.info('Execute ocgis module call function')
if has_Lambert_Conformal(resource) == True and not geom == None:
logger.debug('input has Lambert_Conformal projection and can not subsetted with geom')
output = None
else:
try:
rd = RequestDataset(resource, variable=variable, level_range=level_range,
dimension_map=dimension_map, conform_units_to=conform_units_to,
time_region=time_region, time_range=time_range)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
spatial_wrapping=spatial_wrapping,
spatial_reorder=spatial_reorder,
# options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
output_format=output_format,
prefix=prefix,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
logger.info('OcgOperations set')
except Exception as e:
logger.debug('failed to setup OcgOperations')
raise
# check memory load
from numpy import sqrt
from flyingpigeon.utils import FreeMemory
if memory_limit == None:
f = FreeMemory()
mem_kb = f.user_free
mem_mb = mem_kb / 1024.
mem_limit = mem_mb / 2. # set limit to half of the free memory
else:
mem_limit = memory_limit
if mem_limit >= 1024. * 4:
mem_limit = 1024. * 4
# 475.0 MB for openDAP
data_kb = ops.get_base_request_size()['total']
data_mb = data_kb / 1024.
if variable == None:
variable = rd.variable
logger.info('%s as variable dedected' % (variable))
#data_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
logger.info('data_mb = %s ; memory_limit = %s ' % (data_mb , mem_limit ))
if data_mb <= mem_limit : # input is smaler than the half of free memory size
try:
logger.info('ocgis module call as ops.execute()')
geom_file = ops.execute()
except Exception as e:
logger.debug('failed to execute ocgis operation')
raise
else:
##########################
# calcultion of chunk size
##########################
size = ops.get_base_request_size()
nb_time_coordinates_rd = size['variables'][variable]['temporal']['shape'][0]
element_in_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
element_in_mb = element_in_kb / 1024.
tile_dim = sqrt(mem_limit/(element_in_mb*nb_time_coordinates_rd)) # maximum chunk size
try:
logger.info('ocgis module call compute with chunks')
print 'ocgis module call compute with chunks'
if calc == None:
calc = '%s=%s*1' % (variable, variable)
logger.info('calc set to = %s ' % calc)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
spatial_wrapping=spatial_wrapping,
# options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
output_format=output_format,
prefix=prefix,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
geom_file = compute(ops, tile_dimension=int(tile_dim) , verbose=True)
except Exception as e:
logger.debug('failed to compute ocgis with chunks')
raise
logger.info('Succeeded with ocgis module call function')
############################################
# remapping according to regrid informations
############################################
if not regrid_destination == None:
try:
from tempfile import mkstemp
from cdo import Cdo
cdo = Cdo()
output = '%s.nc' % uuid.uuid1()
remap = 'remap%s' % regrid_options
call = [op for op in dir(cdo) if remap in op]
cmd = "output = cdo.%s('%s',input='%s', output='%s')" % (str(call[0]), regrid_destination, geom_file, output)
exec cmd
except Exception as e:
logger.debug('failed to remap')
raise
else:
output = geom_file
return output
def call(resource=[], variable=None, dimension_map=None, calc=None,
calc_grouping= None, conform_units_to=None, memory_limit=None, prefix=None,
geom=None, output_format_options=False, search_radius_mult=2., select_nearest=False, select_ugid=None, time_region=None, time_range=None,
dir_output=None, output_format='nc'):
'''
ocgis operation call
:param resource:
:param variable: variable in the input file to be picked
:param dimension_map: dimension map in case of unconventional starage of data
:param calc: ocgis calc syntax for calcultion opartion
:param calc_grouping: time aggregate grouping
:param conform_units_to:
:param memory_limit: limit the amout of data to be loaded into the memory at once if None(default) free memory is detected by birdhouse
:param prefix:
:param geom: name of shapefile stored in birdhouse shape cabinet
:param output_format_options: output options for netCDF e.g compression level()
:param search_radius_mult: search radius for point geometries. All included gridboxes will be returned
:param select_nearest: neares neighbour selection for point geometries
:param select_ugid: ugid for appropriate poligons
:param time_region:
:param time_range: sequence of two datetime.datetime objects to mark start and end point
:param dir_output:
:param output_format:
:return: output file path
'''
print 'start ocgis module'
logger.info('Start ocgis module call function')
from ocgis import OcgOperations, RequestDataset , env
from ocgis.util.large_array import compute
# prepare the environment
env.DIR_SHPCABINET = DIR_SHP
env.OVERWRITE = True
env.DIR_OUTPUT = dir_output
env.PREFIX = prefix
if output_format_options == False:
output_format_options = None
elif output_format_options == True:
output_format_options={'data_model': 'NETCDF4', # NETCDF4_CLASSIC
'variable_kwargs': {'zlib': True, 'complevel': 9}}
else:
logger.info('output_format_options are set to %s ' % ( output_format_options ))
if type(resource) != list:
resource = list([resource])
# execute ocgis
logger.info('Execute ocgis module call function')
try:
rd = RequestDataset(resource, variable=variable,
dimension_map=dimension_map, conform_units_to=conform_units_to,
time_region=time_region)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
#options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
output_format=output_format,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
logger.info('OcgOperations set')
except Exception as e:
logger.debug('failed to setup OcgOperations')
raise
# check memory load
from numpy import sqrt
from flyingpigeon.utils import FreeMemory
if memory_limit == None:
f = FreeMemory()
mem_kb = f.user_free
mem_mb = mem_kb / 1024.
mem_limit = mem_mb / 2. # set limit to half of the free memory
else:
mem_limit = memory_limit
if mem_limit >= 1024. * 4:
mem_limit = 1024. * 4
# 475.0 MB for openDAP
data_kb = ops.get_base_request_size()['total']
data_mb = data_kb / 1024.
if variable == None:
variable = rd.variable
logger.info('%s as variable dedected' % (variable))
#data_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
logger.info('data_mb = %s ; memory_limit = %s ' % (data_mb , mem_limit ))
if data_mb <= mem_limit : # input is smaler than the half of free memory size
logger.info('ocgis module call as ops.execute()')
try:
geom_file = ops.execute()
except Exception as e:
logger.debug('failed to execute ocgis operation')
raise
else:
size = ops.get_base_request_size()
nb_time_coordinates_rd = size['variables'][variable]['temporal']['shape'][0]
element_in_kb = size['total']/reduce(lambda x,y: x*y,size['variables'][variable]['value']['shape'])
element_in_mb = element_in_kb / 1024.
tile_dim = sqrt(mem_limit/(element_in_mb*nb_time_coordinates_rd)) # maximum chunk size
# calcultion of chunk size
try:
logger.info('tile_dim = %s; calc = %s ' % (tile_dim, calc))
if calc == None:
calc = '%s=%s*1' % (variable, variable)
logger.info('calc set to = %s ' % calc)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
calc=calc,
output_format=output_format, # 'nc' is necessary for chunked execution
select_ugid=select_ugid,
geom=geom,
add_auxiliary_files=False)
geom_file = compute(ops, tile_dimension=int(tile_dim) , verbose=True)
except Exception as e:
logger.debug('failed to compute ocgis operation')
raise
logger.info('Succeeded with ocgis module call function')
return geom_file
def call(resource=[], variable=None, dimension_map=None, agg_selection=True,
calc=None, calc_grouping=None, conform_units_to=None, crs=None,
memory_limit=None, prefix=None,
regrid_destination=None, regrid_options='bil', level_range=None, # cdover='python',
geom=None, output_format_options=None, search_radius_mult=2.,
select_nearest=False, select_ugid=None, spatial_wrapping=None,
t_calendar=None, time_region=None,
time_range=None, dir_output=None, output_format='nc'):
"""
Call OCGIS operation.
:param resource: Input netCDF file.
:param variable: variable in the input file to be picked
:param dimension_map: dimension map in case of unconventional storage of data
:param agg_selection: For aggregation of in case of mulitple polygons geoms
:param calc: ocgis calc syntax for calculation partion
:param calc_grouping: time aggregate grouping
:param cdover: OUTDATED use py-cdo ('python', by default) or cdo from the system ('system')
:param conform_units_to:
:param crs: coordinate reference system
:param memory_limit: limit the amount of data to be loaded into the memory at once \
if None (default) free memory is detected by birdhouse
:param level_range: subset of given levels
:param prefix: string for the file base name
:param regrid_destination: file path with netCDF file with grid for output file
:param geom: name of shapefile stored in birdhouse shape cabinet
:param output_format_options: output options for netCDF e.g compression level()
:param regrid_destination: file containing the targed grid (griddes.txt or netCDF file)
:param regrid_options: methods for regridding:
'bil' = Bilinear interpolation
'bic' = Bicubic interpolation
'dis' = Distance-weighted average remapping
'nn' = nearest neighbour
'con' = First-order conservative remapping
'laf' = largest area fraction reamapping
:param search_radius_mult: search radius for point geometries. All included gridboxes will be returned
:param select_nearest: nearest neighbour selection for point geometries
:param select_ugid: ugid for appropriate polygons
:param spatial_wrapping: how to handle coordinates in case of subsets, options: None (default), 'wrap', 'unwrap'
:param time_region: select single month
:param time_range: sequence of two datetime.datetime objects to mark start and end point
:param dir_output: path to folder to store ouput files (default= curdir)
:param output_format: format in which results will be returned.
:return: output file path
"""
LOGGER.info('Start ocgis module call function')
from ocgis import OcgOperations, RequestDataset, env, DimensionMap, crs
from ocgis.util.large_array import compute
from datetime import datetime as dt
from datetime import date as dd
from datetime import time as dt_time
import uuid
# prepare the environment
env.OVERWRITE = True
if dir_output is None:
dir_output = abspath(curdir)
# check time_range format:
if time_range is not None:
try:
LOGGER.debug('time_range type= %s , %s ' % (type(time_range[0]), type(time_range[1])))
LOGGER.debug('time_range= %s , %s ' % (time_range[0], time_range[1]))
# if type(time_range[0] is 'datetime.date'):
if (isinstance(time_range[0], dd) and not isinstance(time_range[0], dt)):
time_range = [dt.combine(time_range[0], dt.min.time()),
dt.combine(time_range[1], dt.min.time())]
# time_range = [dt.combine(time_range[0], dt_time(12,0)),
# dt.combine(time_range[1], dt_time(12,0))]
LOGGER.debug('time_range changed to type= %s , %s ' % (type(time_range[0]), type(time_range[1])))
LOGGER.debug('time_range changed to= %s , %s ' % (time_range[0], time_range[1]))
except Exception as ex:
LOGGER.exception('failed to convert data to datetime {}'.format(ex))
if spatial_wrapping == 'wrap':
spatial_reorder = True
else:
spatial_reorder = False
LOGGER.debug('spatial_reorder: %s and spatial_wrapping: %s ' % (spatial_reorder, spatial_wrapping))
if prefix is None:
prefix = str(uuid.uuid1())
env.PREFIX = prefix
#
# if output_format_options is False:
# output_format_options = None
# elif output_format_options is True:
# output_format_options = {'data_model': 'NETCDF4', # NETCDF4_CLASSIC
# 'variable_kwargs': {'zlib': True, 'complevel': 9}}
# else:
if output_format_options is not None:
LOGGER.info('output_format_options are set to %s ' % (output_format_options))
if type(resource) != list:
resource = list([resource])
# execute ocgis
LOGGER.info('Execute ocgis module call function')
try:
LOGGER.debug('call module dir_output = %s ' % abspath(dir_output))
rd = RequestDataset(resource,
variable=variable,
level_range=level_range,
dimension_map=dimension_map,
conform_units_to=conform_units_to,
time_region=time_region,
t_calendar=t_calendar,
time_range=time_range)
from ocgis.constants import DimensionMapKey
rd.dimension_map.set_bounds(DimensionMapKey.TIME, None)
ops = OcgOperations(dataset=rd,
output_format_options=output_format_options,
dir_output=dir_output,
spatial_wrapping=spatial_wrapping,
spatial_reorder=spatial_reorder,
# regrid_destination=rd_regrid,
# options=options,
calc=calc,
calc_grouping=calc_grouping,
geom=geom,
agg_selection=agg_selection,
output_format=output_format,
prefix=prefix,
search_radius_mult=search_radius_mult,
select_nearest=select_nearest,
select_ugid=select_ugid,
add_auxiliary_files=False)
LOGGER.info('OcgOperations set')
except Exception as ex:
LOGGER.exception('failed to setup OcgOperations: {}'.format(ex))
return None
# TODO include comaprison dataload to available memory
dataload = 1
available_memory = 2
try:
if dataload < available_memory: # compare dataload to free_memory
LOGGER.info('ocgis module call as ops.execute()')
geom_file = ops.execute()
else:
# LOGGER.info('ocgis module call as compute(ops)')
# TODO: estimate right tile_dimensionS
tile_dimension = 10 # default
LOGGER.info('Not enough memory for data load, ocgis module call compute in chunks')
geom_file = compute(ops, tile_dimension=tile_dimension, verbose=True)
except Exception as ex:
LOGGER.exception('failed to execute ocgis operation : {}'.format(ex))
return None
return geom_file
