def get(self):
value=self.grid
if value is None:
if not self.latitude.n is None: # Ok we seem to have grid definition
if self.latitude.type == 1: # Gaussian
if self.longitude.first is None:
value=cdms2.createGaussianGrid(self.latitude.n)
else:
value=cdms2.createGaussianGrid(self.latitude.n,self.longitude.first)
elif self.latitude.type == 0: # Uniform
value=cdms2.createUniformGrid(self.latitude.first,
self.latitude.n,
self.latitude.delta,
self.longitude.first,
self.longitude.n,
self.longitude.delta)
elif self.latitude.type== 2: # Equalarea
lat=cdms2.createEqualAreaAxis(self.latitude.n)
lon=cdms2.createUniformLongitude(self.longitude.first,
self.longitude.n,
self.longitude.delta)
value=cdms2.createGenericGrid(lat[:],lon[:],lat.getBounds(),lon.getBounds())
elif not self.file is None:
f=cdms2.open(self.file)
value=f[self.var].getGrid()
## Ok temporary stuff to try to be able to close the file
lat=value.getLatitude()
lon=value.getLongitude()
value=cdms2.createRectGrid(lat,lon)
f.close()
return value
def get(self):
value = self.grid
if value is None:
if not self.latitude.n is None: # Ok we seem to have grid definition
if self.latitude.type == 1: # Gaussian
if self.longitude.first is None:
value = cdms2.createGaussianGrid(self.latitude.n)
else:
value = cdms2.createGaussianGrid(
self.latitude.n, self.longitude.first)
elif self.latitude.type == 0: # Uniform
value = cdms2.createUniformGrid(self.latitude.first,
self.latitude.n,
self.latitude.delta,
self.longitude.first,
self.longitude.n,
self.longitude.delta)
elif self.latitude.type == 2: # Equalarea
lat = cdms2.createEqualAreaAxis(self.latitude.n)
lon = cdms2.createUniformLongitude(self.longitude.first,
self.longitude.n,
self.longitude.delta)
value = cdms2.createGenericGrid(lat[:], lon[:],
lat.getBounds(),
lon.getBounds())
elif not self.file is None:
f = cdms2.open(self.file)
value = f[self.var].getGrid()
## Ok temporary stuff to try to be able to close the file
lat = value.getLatitude()
lon = value.getLongitude()
value = cdms2.createRectGrid(lat, lon)
f.close()
return value
def testRegridZonal(self):
f = self.getFile(
os.path.join(cdat_info.get_sampledata_path(), "clt.nc"))
s = f("clt", slice(0, 1))
g = cdms2.createGaussianGrid(64)
gl = cdms2.createZonalGrid(g)
regridded = s.regrid(gl)
def testContiguousRegridNANIssue(self):
a = MV2.reshape(MV2.sin(MV2.arange(20000)), (2, 1, 100, 100))
lon = cdms2.createAxis(MV2.arange(100) * 3.6)
lon.designateLongitude()
lon.units = "degrees_east"
lon.id = "longitude"
lat = cdms2.createAxis(MV2.arange(100) * 1.8 - 90.)
lat.id = "latitude"
lat.designateLatitude()
lat.units = "degrees_north"
lev = cdms2.createAxis([1000.])
lev.id = "plev"
lev.designateLevel()
lev.units = "hPa"
t = cdms2.createAxis([0, 31.])
t.id = "time"
t.designateTime()
t.units = "days since 2014"
cdutil.setTimeBoundsMonthly(t)
a.setAxisList((t, lev, lat, lon))
a = MV2.masked_less(a, .5)
grd = cdms2.createGaussianGrid(64)
a = a.ascontiguous()
a = a.regrid(grd, regridTool="regrid2")
a = cdutil.averager(a, axis='txy')
self.assertEqual(a[0], 0.7921019540305255)
def generate_grid(self, gridder, spatial, chunk):
try:
grid_type, grid_param = gridder.grid.split('~')
except ValueError:
raise WPSError('Error generating grid "{name}"', name=gridder.grid)
if grid_type.lower() == 'uniform':
result = re.match('^(.*)x(.*)$', grid_param)
if result is None:
raise WPSError('Failed to parse uniform configuration from {value}', value=grid_param)
try:
start_lat, nlat, delta_lat = self.parse_uniform_arg(result.group(1), -90.0, 180.0)
except WPSError:
raise
try:
start_lon, nlon, delta_lon = self.parse_uniform_arg(result.group(2), 0.0, 360.0)
except WPSError:
raise
grid = cdms2.createUniformGrid(start_lat, nlat, delta_lat, start_lon, nlon, delta_lon)
logger.info('Created target uniform grid {} from lat {}:{}:{} lon {}:{}:{}'.format(
grid.shape, start_lat, delta_lat, nlat, start_lon, delta_lon, nlon))
else:
try:
nlats = int(grid_param)
except ValueError:
raise WPSError('Error converting gaussian parameter to an int')
grid = cdms2.createGaussianGrid(nlats)
logger.info('Created target gaussian grid {}'.format(grid.shape))
target = cdms2.MV2.ones(grid.shape)
target.setAxisList(grid.getAxisList())
lat = chunk.getLatitude()
lon = chunk.getLongitude()
try:
lat_spec = spatial[lat.id]
lon_spec = spatial[lon.id]
except KeyError as e:
logger.debug('Skipping subsetting the target grid')
else:
target = target(latitude=lat_spec, longitude=lon_spec)
return target.getGrid()
def test0(self):
"""
One way interpolation
"""
fnm = sys.prefix + '/sample_data/clt.nc'
f = cdms2.open(fnm)
s = f("clt")
grdori = s.getGrid()
nLon = s.shape[-1]
nLat = s.shape[-2]
xx = numpy.outer(numpy.ones((nLat, ), numpy.float32),
s.getLongitude()[:])
yy = numpy.outer(s.getLatitude(), numpy.ones((nLon, ), numpy.float32))
print s.shape, xx.shape, yy.shape
#s[0,...] = 50.0*(1.0 + numpy.sin(4*numpy.pi * xx / 180.0) * numpy.cos(2*numpy.pi * yy / 180.0))
grid = cdms2.createGaussianGrid(32, 64)
sInterps = {}
sInterps['regrid2'] = s.regrid(grid, regridTool='regrid2')
sInterps['esmf linear'] = s.regrid(grid,
regridTool='esmf',
regridMethod='linear')
diag = {}
sInterps['libcf'] = s.regrid(grid, regridTool='libcf', diag=diag)
print diag
diag = {}
sInterps['esmf conserve'] = s.regrid(grid,
regridTool='esmf',
regridMethod='conserve',
diag=diag)
print diag
diff = abs(sInterps['esmf linear'] - sInterps['regrid2']).max()
self.assertLess(diff, 18.0)
diff = abs(sInterps['esmf conserve'] - sInterps['regrid2']).max()
self.assertLess(diff, 86.0)
diff = abs(sInterps['libcf'] - sInterps['regrid2']).max()
self.assertLess(diff, 18.0)
if PLOT:
row = 0
for mth in sInterps:
row += 1
pylab.subplot(2, 2, row)
pylab.pcolor(sInterps[mth][0, ...] -
sInterps['regrid2'][0, ...],
vmin=-10,
vmax=10)
pylab.colorbar()
pylab.title(mth + ' - regrid2')
def generate_user_defined_grid(self, gridder):
try:
grid_type, grid_param = gridder.grid.split('~')
except AttributeError:
return None
except ValueError:
raise WPSError('Error generating grid "{name}"', name=gridder.grid)
logger.info('Generating grid %r %r', grid_type, grid_param)
if grid_type.lower() == 'uniform':
result = re.match('^(.*)x(.*)$', grid_param)
if result is None:
raise WPSError(
'Failed to parse uniform configuration from {value}',
value=grid_param)
try:
start_lat, nlat, delta_lat = self.parse_uniform_arg(
result.group(1), -90.0, 180.0)
except WPSError:
raise
try:
start_lon, nlon, delta_lon = self.parse_uniform_arg(
result.group(2), 0.0, 360.0)
except WPSError:
raise
grid = cdms2.createUniformGrid(start_lat, nlat, delta_lat,
start_lon, nlon, delta_lon)
logger.info(
'Created target uniform grid {} from lat {}:{}:{} lon {}:{}:{}'
.format(grid.shape, start_lat, delta_lat, nlat, start_lon,
delta_lon, nlon))
elif grid_type.lower() == 'gaussian':
try:
nlats = int(grid_param)
except ValueError:
raise WPSError('Error converting gaussian parameter to an int')
grid = cdms2.createGaussianGrid(nlats)
logger.info('Created target gaussian grid {}'.format(grid.shape))
else:
raise WPSError('Unknown grid type for regridding: {}', grid_type)
return grid
def interp2commonGrid(d, dlat, debug=False):
"""
input
- d: cdms array
- dlat: resolution (i.e. grid distance) in degree
output
- d2: d interpolated to dlat resolution grid
"""
nlat = int(180/dlat)
grid = cdms2.createGaussianGrid(nlat, xorigin=0.0, order="yx")
d2 = d.regrid(grid, regridTool='regrid2', mkCyclic=True)
d2 = d2(latitude=(-10, 10))
if debug:
print('debug: d2.shape:', d2.shape)
return d2
def Xtest1(self):
"""
Forward/backward interpolation
"""
fnm=vcs.sample_data+'/clt.nc'
f=cdms2.open(fnm)
s=f("clt")
grdori = s.getGrid()
nLon = s.shape[-1]
nLat = s.shape[-2]
xx = numpy.outer(numpy.ones( (nLat,), numpy.float32 ), s.getLongitude()[:])
yy = numpy.outer(s.getLatitude(), numpy.ones( (nLon,), numpy.float32) )
print s.shape, xx.shape, yy.shape
#s[0,...] = 50.0*(1.0 + numpy.sin(4*numpy.pi * xx / 180.0) * numpy.cos(2*numpy.pi * yy / 180.0))
grid = cdms2.createGaussianGrid(64,128)
sInterps = {}
sInterps['regrid2'] = s.regrid(grid, regridTool='regrid2').regrid(grdori, regridTool='regrid2')
sInterps['esmf linear'] = s.regrid(grid, regridTool='esmf', regridMethod = 'linear').regrid(grdori, regridTool='esmf', regridMethod = 'linear')
diag = {}
sInterps['libcf'] = s.regrid(grid, regridTool='libcf', diag=diag).regrid(grdori, regridTool='libcf', diag=diag)
print diag
diag = {}
sInterps['esmf conserve'] = s.regrid(grid, regridTool='esmf', regridMethod = 'conserve', diag=diag).regrid(grdori, regridTool='esmf', regridMethod = 'conserve')
print diag
diff = abs(sInterps['regrid2'] - s).max()
self.assertLess(diff, 63.0)
diff = abs(sInterps['esmf linear'] - s).max()
self.assertLess(diff, 45.0)
diff = abs(sInterps['esmf conserve'] - s).max()
self.assertLess(diff, 103.534)
diff = abs(sInterps['libcf'] - s).max()
self.assertLess(diff, 45.0)
if PLOT:
row = 0
for mth in sInterps:
row += 1
pylab.subplot(2, 2, row)
pylab.pcolor(sInterps[mth][0,...] - s[0,...], vmin = -10, vmax = 10)
pylab.colorbar()
pylab.title(mth + ' - original')
def executeOperations(self, task, _inputs):
cdms2.setAutoBounds(2)
t0 = time.time()
self.logger.info( " Execute REGRID Task with metadata: " + str( task.metadata ) )
crsSpec = task.metadata.get("crs","")
if( len(crsSpec) and (crsSpec[0] == '~') ):
crsId = crsSpec[1:]
grid_input = _inputs.get( crsId, None )
if not grid_input: raise Exception( "Can't find grid variable uid: " + crsId + ", variable uids = " + str( _inputs.keys() ) )
toGrid = grid_input.getGrid()
else:
crsToks = crsSpec.split('~')
if( len(crsToks) > 1 ):
if crsToks[0] == "gaussian":
resolution = int(crsToks[1])
toGrid = cdms2.createGaussianGrid( resolution )
else: raise Exception( "Unrecognized grid type: " + crsToks[0])
else:
gridSpec = task.metadata.get("gridSpec","")
if not gridSpec: raise Exception( "Can't find crs spec in regrid kernel: " + str(crsToks))
toGrid = getGrid( gridSpec )
results = []
for input_id in task.inputs:
_input = _inputs.get( input_id.split('-')[0] )
variable = _input.getVariable()
ingrid = _input.getGrid()
inlatBounds, inlonBounds = ingrid.getBounds()
self.logger.info( " >> in LAT Bounds shape: " + str(inlatBounds.shape) )
self.logger.info( " >> in LON Bounds shape: " + str(inlonBounds.shape) )
outlatBounds, outlonBounds = toGrid.getBounds()
self.logger.info( " >> out LAT Bounds shape: " + str(outlatBounds.shape) )
self.logger.info( " >> out LON Bounds shape: " + str(outlonBounds.shape) )
if( not ingrid == toGrid ):
self.logger.info( " Regridding Variable {0} using grid {1} ".format( variable.id, str(toGrid) ) )
if self._debug:
self.logger.info( " >> Input Data Sample: [ {0} ]".format( ', '.join( [ str( variable.data.flat[i] ) for i in range(20,90) ] ) ) )
self.logger.info( " >> Input Variable Shape: {0}, Grid Shape: {1} ".format( str(variable.shape), str([len(ingrid.getLatitude()),len(ingrid.getLongitude())] )))
result_var = variable.regrid( toGrid, regridTool="esmf", regridMethod="linear" )
self.logger.info( " >> Gridded Data Sample: [ {0} ]".format( ', '.join( [ str( result_var.data.flat[i] ) for i in range(20,90) ] ) ) )
results.append( self.createResult( result_var, _input, task ) )
t1 = time.time()
self.logger.info(" @RRR@ Completed regrid operation for input variables: {0} in time {1}".format( str(_inputs.keys), (t1 - t0)))
return results
def execOp( self, op, context, inputs ):
t0 = time.time()
opToks = op.split(".")
module = opToks[0]
opIdToks = opToks[1].split("-")
opName = opIdToks[0]
opId = opIdToks[1]
crsToks = context.get("crs","gaussian~128").split("~")
regridder = context.get("regridder","regrid2")
crs = crsToks[0]
resolution = int(crsToks[1]) if len(crsToks) > 1 else 128
if opName.lower() == "regrid":
if crs == "gaussian":
t42 = cdms2.createGaussianGrid( resolution )
results = [ input.regrid( t42 , regridTool=regridder ) for input in inputs ]
self.logger.info( " >> Regridded variables in time {0}, nresults = {1}".format( (time.time()-t0), len(results) ) )
return results
return []
def generate_user_defined_grid(cls,
grid_type,
grid_param,
lat_bounds=None,
lon_bounds=None):
logger.info('Generating grid %r %r', grid_type, grid_param)
if grid_type.lower() == 'uniform':
result = re.match('^(.*)x(.*)$', grid_param)
if result is None:
raise Exception(
f'Failed to parse uniform configuration from {grid_param}')
start_lat, nlat, delta_lat = cls.parse_uniform_arg(
result.group(1), -90.0, 180.0, lat_bounds)
start_lon, nlon, delta_lon = cls.parse_uniform_arg(
result.group(2), 0.0, 360.0, lon_bounds)
grid = cdms2.createUniformGrid(start_lat, nlat, delta_lat,
start_lon, nlon, delta_lon)
logger.info(
'Created target uniform grid {} from lat {}:{}:{} lon {}:{}:{}'
.format(grid.shape, start_lat, delta_lat, nlat, start_lon,
delta_lon, nlon))
elif grid_type.lower() == 'gaussian':
try:
nlats = int(grid_param)
except ValueError:
raise Exception(
'Error converting gaussian parameter to an int')
grid = cdms2.createGaussianGrid(nlats)
logger.info(f'Created target gaussian grid {grid.shape}')
else:
raise Exception(f'Unknown grid type for regridding: {grid_type}')
return grid
#!/usr/bin/env python
import cdms2, numpy.ma, regrid2 as regrid, os, sys
from regrid2 import Regridder
from markError import clearError, markError, reportError
from markError import get_sample_data_dir
clearError()
print 'Test 8: Regridding ...',
## lat = cdms2.createGaussianAxis(32)
## lon = cdms2.createUniformLongitudeAxis(0.0,64,360.0/64.)
## outgrid = cdms2.createRectGrid(lat,lon,'yx','gaussian')
outgrid = cdms2.createGaussianGrid(32)
f = cdms2.openDataset(os.path.join(get_sample_data_dir(), 'readonly.nc'))
u = f.variables['u']
ingrid = u.getGrid()
try:
sh = ingrid.shape
except:
markError('Grid shape')
regridf = Regridder(ingrid, outgrid)
newu = regridf(u)
if (abs(newu[0, 0, -1] - 488.4763488) > 1.e-3):
markError('regrid', newu[0, 0, -1])
newu = u.regrid(outgrid)
import cdms2
import MV2
import sys
f = cdms2.open(sys.prefix + "/sample_data/clt.nc")
s = f('clt')
S2 = MV2.masked_greater(s, 87)
G = cdms2.createGaussianGrid(22)
S3 = S2.regrid(G)
assert (S3.max() < 87.1)
import cdms2
inputPath = "http://aims3.llnl.gov/thredds/dodsC/cmip5_css02_data/cmip5/output1/CMCC/CMCC-CESM/historical/mon/atmos/Amon/r1i1p1/tas/1/tas_Amon_CMCC-CESM_historical_r1i1p1_198001-198412.nc"
dataset = cdms2.open(inputPath)
resolution = 128
regridder = "regrid2"
input = dataset("tas")
t42 = cdms2.createGaussianGrid(resolution)
result = input.regrid(t42, regridTool=regridder)
axes = result.getAxisList()
grid = result.getGrid()
newDataset = cdms2.createDataset("/tmp/test")
for axis in axes:
newDataset.copyAxis(axis)
newDataset.copyGrid(grid)
newDataset.createVariableCopy(result)
newDataset.close()
print "."
def testGenmask(self):
f = cdms2.open(os.path.join(egg_path, "navy_land.nc"))
navy_frac_one = f('sftlf')
g = navy_frac_one.getGrid()
print(("SOURCE GRID:", g))
print(("LON:", g.getLongitude()))
print(("LAT:", g.getLatitude()))
navy_frac = navy_frac_one / 100.
g = navy_frac.getGrid()
print(("SOURCE GRID 2:", g))
print(("LON:", g.getLongitude()))
print(("LAT:", g.getLatitude()))
target = cdms2.open(
os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt", slice(0, 1)).getGrid()
print(("TARGET:", navy_frac.getGrid()))
mask = cdutil.generateLandSeaMask(target, navy_frac)
target = cdms2.open(
os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt", slice(0, 1))
mask = cdutil.generateLandSeaMask(target, navy_frac)
target = cdms2.createGaussianGrid(64)
mask = cdutil.generateLandSeaMask(target)
target = cdms2.open(
os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt",
slice(0, 1),
latitude=(15, 85),
longitude=(-175, -65)).getGrid()
mask = cdutil.generateLandSeaMask(target)
self.assertEqual(mask.shape, (17, 23))
good = numpy.array([
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0, 0.0, 1.0, 1.0, 1.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0
],
[
0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0
],
[
1.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0, 1.0
],
[
0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0,
1.0, 1.0, 1.0, 0.0, 1.0, 0.0, 1.0, 1.0, 1.0, 1.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0,
1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 0.0, 0.0, 1.0
],
[
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0
]
])
#good = numpy.ma.masked_equal(good,1.0)
self.assertTrue(numpy.ma.allclose(mask.filled(3.) - good, 0))
import cdms2
import cdat_info
import os
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(), "clt.nc"))
s = f("clt", slice(0, 1))
g = cdms2.createGaussianGrid(64)
gl = cdms2.createZonalGrid(g)
regridded = s.regrid(gl)
import cdms2,sys,cdutil,os,cdat_info
f=cdms2.open(os.path.join(cdat_info.get_prefix(),"sample_data","navy_land.nc"))
navy_frac = f("sftlf")/100.
target = cdms2.open(os.path.join(cdat_info.get_prefix(),'sample_data','clt.nc'))("clt",slice(0,1)).getGrid()
mask = cdutil.generateLandSeaMask(target,navy_frac)
target = cdms2.open(os.path.join(cdat_info.get_prefix(),'sample_data','clt.nc'))("clt",slice(0,1))
mask = cdutil.generateLandSeaMask(target,navy_frac)
target=cdms2.createGaussianGrid(64)
mask = cdutil.generateLandSeaMask(target)
target = cdms2.open(os.path.join(cdat_info.get_prefix(),'sample_data','clt.nc'))("clt",slice(0,1),latitude=(15,85),longitude=(-175,-65)).getGrid()
mask = cdutil.generateLandSeaMask(target)
#import vcs
#x=vcs.init()
#x.plot(mask)
#raw_input()
lon=cdms2.createAxis(MV2.arange(100)*3.6) lon.designateLongitude() lon.units="degrees_east" lon.id="longitude" lat = cdms2.createAxis(MV2.arange(100)*1.8-90.) lat.id="latitude" lat.designateLatitude() lat.units="degrees_north" lev = cdms2.createAxis([1000.]) lev.id="plev" lev.designateLevel() lev.units="hPa" t=cdms2.createAxis([0,31.]) t.id="time" t.designateTime() t.units="days since 2014" cdutil.setTimeBoundsMonthly(t) a.setAxisList((t,lev,lat,lon)) a=MV2.masked_less(a,.5) grd=cdms2.createGaussianGrid(64) a=a.ascontiguous() a=a.regrid(grd,regridTool="regrid2") a=cdutil.averager(a,axis='txy') assert a[0]==0.7921019540305255
## Automatically adapted for numpy.oldnumeric Aug 01, 2007 by
#!/usr/bin/env python
import cdms2,numpy.ma, regrid2 as regrid, os, sys
from regrid2 import Regridder
from markError import clearError,markError,reportError
clearError()
print 'Test 8: Regridding ...',
## lat = cdms2.createGaussianAxis(32)
## lon = cdms2.createUniformLongitudeAxis(0.0,64,360.0/64.)
## outgrid = cdms2.createRectGrid(lat,lon,'yx','gaussian')
outgrid = cdms2.createGaussianGrid(32)
pth = os.path.dirname(os.path.abspath(__file__))
f = cdms2.open(os.path.join(pth,'readonly.nc'))
u = f.variables['u']
ingrid = u.getGrid()
try:
sh = ingrid.shape
except:
markError('Grid shape')
regridf = Regridder(ingrid, outgrid)
newu = regridf(u)
if (abs(newu[0,0,-1]-488.4763488) > 1.e-3): markError('regrid',newu[0,0,-1])
newu = u.regrid(outgrid,regridTool='regrid2')
if (abs(newu[0,0,-1]-488.4763488) > 1.e-3): markError('regrid',newu[0,0,-1])
import cdms2,cdat_info
import MV2
import sys
f = cdms2.open(cdat_info.get_prefix() + "/sample_data/clt.nc")
s = f('clt')
S2 = MV2.masked_greater(s, 87)
G = cdms2.createGaussianGrid(22)
S3 = S2.regrid(G)
assert(S3.max() < 87.1)
import cdms2, sys, cdutil, os, cdat_info
f = cdms2.open(os.path.join(cdat_info.get_sampledata_path(), "navy_land.nc"))
navy_frac = f("sftlf") / 100.
target = cdms2.open(os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt", slice(0, 1)).getGrid()
mask = cdutil.generateLandSeaMask(target, navy_frac)
target = cdms2.open(os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt", slice(0, 1))
mask = cdutil.generateLandSeaMask(target, navy_frac)
target = cdms2.createGaussianGrid(64)
mask = cdutil.generateLandSeaMask(target)
target = cdms2.open(os.path.join(cdat_info.get_sampledata_path(),
'clt.nc'))("clt",
slice(0, 1),
latitude=(15, 85),
longitude=(-175, -65)).getGrid()
mask = cdutil.generateLandSeaMask(target)
#import vcs
#x=vcs.init()
#x.plot(mask)
#raw_input()
def testRegrid2(self):
outgrid = cdms2.createGaussianGrid(32)
pth = os.path.dirname(os.path.abspath(__file__))
f = self.getDataFile('readonly.nc')
u = f.variables['u']
ingrid = u.getGrid()
sh = ingrid.shape
regridf = Horizontal(ingrid, outgrid)
newu = regridf(u)
self.assertLess(abs(newu[0, 0, -1] - 488.4763488), 1.e-3)
newu = u.regrid(outgrid, regridTool='regrid2')
self.assertLess(abs(newu[0, 0, -1] - 488.4763488), 1.e-3)
# Regrid TV
tv = u.subSlice(0)
newtv = regridf(tv)
self.assertLess(abs(newtv[0, 0, -1] - 488.4763488), 1.e-3)
newtv = tv.regrid(outgrid, regridTool='regrid2')
self.assertLess(abs(newtv[0, 0, -1] - 488.4763488), 1.e-3)
# Regrid numpy.ma
ma = u[0]
newma = regridf(ma)
# Force slice result to be a scalar
self.assertLess(abs(newma[0][-1] - 488.4763488), 1.e-3)
# Regrid numpy
numar = numpy.ma.filled(u[0])
newar = regridf(numar)
self.assertLess(abs(newar[0][-1] - 488.4763488), 1.e-3)
# Regrid masked Variable
umasked = f.variables['umasked']
newum = regridf(umasked)
self.assertLess(abs(newum[0, 0, -1] - 488.4763488), 1.e-3)
# Set explicit missing variable
numar = numpy.ma.filled(umasked[0])
newar = regridf(numar, missing=-99.9)
self.assertLess(abs(newar[0][-1] - 488.4763488), 1.e-3)
# Set explicit mask
mask = umasked.subRegion().mask[0]
newar = regridf(numar, mask=mask)
self.assertLess(abs(newar[0][-1] - 488.4763488), 1.e-3)
# Set the input grid mask
ingrid.setMask(mask)
regridf2 = Horizontal(ingrid, outgrid)
newar = regridf2(numar)
self.assertLess(abs(newar[0][-1] - 488.4763488), 1.e-3)
# Dataset
g = self.getDataFile('test.xml')
u = g.variables['u']
outgrid = cdms2.createGaussianGrid(24)
regridf3 = Horizontal(u.getGrid(), outgrid)
try:
unew = regridf3(u)
except BaseException:
markError('regrid dataset variable')
lon2 = numpy.ma.array([
90.,
101.25,
112.5,
123.75,
135.,
146.25,
157.5,
168.75,
180.,
191.25,
202.5,
213.75,
225.,
236.25,
247.5,
258.75,
])
lat2 = numpy.ma.array([
-42.,
-30.,
-18.,
-6.,
6.,
18.,
30.,
42.,
])
grid2 = cdms2.createGenericGrid(lat2, lon2)
b1, b2 = grid2.getBounds()
grid2.setBounds(b1, b2)
latw, lonw = grid2.getWeights()
g = cdms2.createGaussianGrid(16)
levs = numpy.array([1.0, 3.0, 5.0])
lev = cdms2.createAxis(levs, id='level')
levsout = numpy.array([2.0, 4.0])
levout = cdms2.createAxis(levsout, id='level')
dat = numpy.zeros((3, 16, 32), numpy.float32)
dat2 = numpy.zeros((2, 16, 32), numpy.float32)
dat[0] = 2.0
dat[1] = 4.0
dat[2] = 6.0
var = cdms2.createVariable(dat,
axes=(lev, g),
attributes={'units': 'N/A'},
id='test')
result = var.pressureRegrid(levout)
self.assertLess(abs(result[0, 0, 0] - 3.26185), 1.e-4)
# Test cross-section regridder --------------------------------
latin = cdms2.createGaussianAxis(16)
latout = cdms2.createGaussianAxis(24)
levsin = numpy.array([1.0, 3.0, 5.0])
lev = cdms2.createAxis(levsin, id='level')
levsout = numpy.array([2.0, 4.0])
levout = cdms2.createAxis(levsout, id='level')
dat = numpy.zeros((3, 16), numpy.float32)
dat[0] = 2.0
dat[1] = 4.0
dat[2] = 6.0
var = cdms2.createVariable(dat,
axes=(lev, latin),
attributes={'units': 'N/A'},
id='test')
dat2 = var.crossSectionRegrid(levout, latout)
self.assertLess(abs(dat2[0, 0] - 3.26185), 1.e-4)