def __myGetAxisWeights(x, i, axisoptions=None):
""" Assume x is an MV2 duh! and get the weights associated with axis index i.
index i can be any of the dimensions in x whose bounds are available.
If bounds are not available then an error is raised.
"""
if x.getAxis(i).isLatitude():
Lataxis = x.getAxis(i)
xgr = cdms2.createGenericGrid(Lataxis[:], numpy.array(range(1), numpy.float), latBounds=Lataxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlatwt
elif x.getAxis(i).isLongitude():
Lonaxis = x.getAxis(i)
xgr = cdms2.createGenericGrid(numpy.array(range(1), numpy.float), Lonaxis[:], lonBounds=Lonaxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlonwt
else:
axis_bounds = x.getAxis(i).getBounds()
if axis_bounds is None:
ax=x.getAxis(i)
if axisoptions is not None:
axo=cdms2.orderparse(axisoptions)
if (i in axo ) or (ax.isTime() and 't' in axo) or (ax.isLevel() and 'z' in axo) or ('('+ax.id+')' in axo):
raise AveragerError, 'Bounds not available to compute weights on dimension: '+ax.id
else:
axis_wts=numpy.ones(x.getAxis(i)[:].shape)
else:
raise AveragerError, 'Bounds not available to compute weights for dimension: '+ax.id
else:
axis_wts = abs(axis_bounds[..., 1] - axis_bounds[..., 0])
return axis_wts
def __myGetAxisWeights(x, i, axisoptions=None):
""" Assume x is an MV2 duh! and get the weights associated with axis index i.
index i can be any of the dimensions in x whose bounds are available.
If bounds are not available then an error is raised.
"""
if x.getAxis(i).isLatitude():
Lataxis = x.getAxis(i)
xgr = cdms2.createGenericGrid(Lataxis[:], numpy.array(range(1), numpy.float), latBounds=Lataxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlatwt
elif x.getAxis(i).isLongitude():
Lonaxis = x.getAxis(i)
xgr = cdms2.createGenericGrid(numpy.array(range(1), numpy.float), Lonaxis[:], lonBounds=Lonaxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlonwt
else:
axis_bounds = x.getAxis(i).getBounds()
if axis_bounds is None:
ax=x.getAxis(i)
if axisoptions is not None:
axo=cdms2.orderparse(axisoptions)
if (i in axo ) or (ax.isTime() and 't' in axo) or (ax.isLevel() and 'z' in axo) or ('('+ax.id+')' in axo):
raise AveragerError, 'Bounds not available to compute weights on dimension: '+ax.id
else:
axis_wts=numpy.ones(x.getAxis(i)[:].shape)
else:
raise AveragerError, 'Bounds not available to compute weights for dimension: '+ax.id
else:
axis_wts = abs(axis_bounds[..., 1] - axis_bounds[..., 0])
return axis_wts
def __myGetAxisWeightsByName(x, name):
""" Get the weights associated with axis name.
The name can be any of the dimensions in x whose bounds are available.
If bounds are not available then an error is raised.
This is a slight modifications on the _myGetAxisWeight. The only difference
is that the name is used to define the axis instead of the index.
"""
if x.getAxisList(axes=name)[0].isLatitude():
Lataxis = x.getAxisList(axes=name)[0]
xgr = cdms2.createGenericGrid(Lataxis[:],
numpy.array(range(1), numpy.float),
latBounds=Lataxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlatwt
elif x.getAxisList(axes=name)[0].isLongitude():
Lonaxis = x.getAxisList(axes=name)[0]
xgr = cdms2.createGenericGrid(numpy.array(range(1), numpy.float),
Lonaxis[:],
lonBounds=Lonaxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlonwt
else:
axis_bounds = x.getAxisList(axes=name)[0].getBounds()
if not axis_bounds:
raise AveragerError, 'Bounds not available to compute weights'
else:
axis_wts = abs(axis_bounds[..., 1] - axis_bounds[..., 0])
return axis_wts
def __myGetAxisWeightsByName(x, name):
""" Get the weights associated with axis name.
The name can be any of the dimensions in x whose bounds are available.
If bounds are not available then an error is raised.
This is a slight modifications on the _myGetAxisWeight. The only difference
is that the name is used to define the axis instead of the index.
"""
if x.getAxisList( axes = name )[0].isLatitude():
Lataxis = x.getAxisList( axes = name )[0]
xgr = cdms2.createGenericGrid(Lataxis[:], numpy.array(range(1), numpy.float), latBounds=Lataxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlatwt
elif x.getAxisList( axes = name )[0].isLongitude():
Lonaxis = x.getAxisList( axes = name )[0]
xgr = cdms2.createGenericGrid(numpy.array(range(1), numpy.float), Lonaxis[:], lonBounds=Lonaxis.getBounds())
xlatwt, xlonwt = xgr.getWeights()
return xlonwt
else:
axis_bounds = x.getAxisList( axes = name )[0].getBounds()
if not axis_bounds:
raise AveragerError, 'Bounds not available to compute weights'
else:
axis_wts = abs(axis_bounds[..., 1] - axis_bounds[..., 0])
return axis_wts
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 getgrid(grid="coarse"):
file1 =sys.prefix+'/sample_data/hadcrut2_sample.nc'
a = cdms.open(file1)
data=a('temanom')
if grid=="coarse":
LATS=data.getLatitude()[::4]
ub=data.getLatitude().getBounds()[1::4][:,0]
lb=data.getLatitude().getBounds()[::4][:,1]
latbounds=np.array(zip(ub,lb))
LONS=data.getLongitude()[::4]
ub=data.getLongitude().getBounds()[1::4][:,0]
lb=data.getLongitude().getBounds()[::4][:,1]
lonbounds=np.array(zip(ub,lb))
else:
LATS=data.getLatitude()[::2]
ub=data.getLatitude().getBounds()[1::2][:,0]
lb=data.getLatitude().getBounds()[::2][:,1]
latbounds=np.array(zip(ub,lb))
LONS=data.getLongitude()[::2]
ub=data.getLongitude().getBounds()[1::2][:,0]
lb=data.getLongitude().getBounds()[::2][:,1]
lonbounds=np.array(zip(ub,lb))
return cdms.createGenericGrid(LATS,LONS,latBounds=latbounds,lonBounds=lonbounds)
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 makeGrid(xstart=0, xend=359, xstep=1, ystart=-90, yend=89, ystep=1):
lon_bnds=[]
lon=[]
for ii in numpy.arange(xstart, xend, xstep):
lon_bnds.append( [ii, ii+xstep] )
lon.append(ii+0.5*xstep)
lon_bnds=numpy.array(lon_bnds)
lon=numpy.array(lon)
lat_bnds=[]
lat=[]
for ii in numpy.arange(ystart, yend, ystep):
lat_bnds.append([ii, ii+ystep])
lat.append(ii+0.5*ystep)
lat_bnds=numpy.array(lat_bnds)
lat=numpy.array(lat)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units='degrees_north'
latAxis.long_name='Latitude'
latAxis.id='latitude'
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, 360.0)
lonAxis.units='degrees_east'
lonAxis.id='longitude'
lonAxis.long_name='Longitude'
return((cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds), latAxis, lonAxis, lat_bnds, lon_bnds))
def makeGrid():
xstart = 0
xend = 360
xstep = 0.5
ystart = -85
yend = 85
ystep = 0.5
lon_bnds = []
lon = []
for ii in numpy.arange(xstart, xend, xstep):
lon_bnds.append([ii, ii + xstep])
lon.append(ii + 0.5 * xstep)
lon_bnds = numpy.array(lon_bnds)
lon = numpy.array(lon)
lat_bnds = []
lat = []
for ii in numpy.arange(ystart, yend, ystep):
lat_bnds.append([ii, ii + ystep])
lat.append(ii + 0.5 * ystep)
lat_bnds = numpy.array(lat_bnds)
lat = numpy.array(lat)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units = "degree_north"
latAxis.long_name = "Latitude"
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, 360.0)
return cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds)
def Xtest1(self):
"""
Test from Kate Marvel
As the following code snippet demonstrates, regridding a
cdms2.tvariable.TransientVariable instance using regridTool='regrid2'
results in a new array that is masked everywhere. regridTool='esmf'
and regridTool='libcf' both work as expected.
This is similar to test0 but we only onterpolate over a single elevation,
also fails. Likely GRID is not constructed correctly.
"""
import cdms2 as cdms
import numpy as np
filename = cdat_info.get_sampledata_path() + '/clt.nc'
a=cdms.open(filename)
data=a('clt')[0,...]
print data.mask #verify this data is not masked
## Now create a new grid using every other latitude and every
# other longitude
LATS=data.getLatitude()[::2]
ub = data.getLatitude().getBounds()[1::2][:,0]
lb = data.getLatitude().getBounds()[::2][:,1]
latbounds = np.array(zip(ub,lb))
self.assertEqual((ub != lb).all(), True)
LONS=data.getLongitude()[::2]
ub=data.getLongitude().getBounds()[1::2][:,0]
lb=data.getLongitude().getBounds()[::2][:,1]
lonbounds=np.array(zip(ub,lb))
self.assertEqual((ub != lb).all(), True)
GRID=cdms.createGenericGrid(LATS,LONS,
latBounds=latbounds,
lonBounds=lonbounds)
test_data=data.regrid(GRID,regridTool='regrid2')
# check that the mask does not extend everywhere...
self.assertNotEqual(test_data.mask.sum(), test_data.size)
if PLOT:
pylab.subplot(2, 1, 1)
pylab.pcolor(data[...])
pylab.title('data')
pylab.subplot(2, 1, 2)
pylab.pcolor(test_data[...])
pylab.title('test_data (interpolated data)')
pylab.show()
def Xtest1(self):
"""
Test from Kate Marvel
As the following code snippet demonstrates, regridding a
cdms2.tvariable.TransientVariable instance using regridTool='regrid2'
results in a new array that is masked everywhere. regridTool='esmf'
and regridTool='libcf' both work as expected.
This is similar to test0 but we only onterpolate over a single elevation,
also fails. Likely GRID is not constructed correctly.
"""
import cdms2 as cdms
import numpy as np
filename = cdat_info.get_prefix() + '/sample_data/clt.nc'
a = cdms.open(filename)
data = a('clt')[0, ...]
print data.mask #verify this data is not masked
## Now create a new grid using every other latitude and every
# other longitude
LATS = data.getLatitude()[::2]
ub = data.getLatitude().getBounds()[1::2][:, 0]
lb = data.getLatitude().getBounds()[::2][:, 1]
latbounds = np.array(zip(ub, lb))
self.assertEqual((ub != lb).all(), True)
LONS = data.getLongitude()[::2]
ub = data.getLongitude().getBounds()[1::2][:, 0]
lb = data.getLongitude().getBounds()[::2][:, 1]
lonbounds = np.array(zip(ub, lb))
self.assertEqual((ub != lb).all(), True)
GRID = cdms.createGenericGrid(LATS,
LONS,
latBounds=latbounds,
lonBounds=lonbounds)
test_data = data.regrid(GRID, regridTool='regrid2')
# check that the mask does not extend everywhere...
self.assertNotEqual(test_data.mask.sum(), test_data.size)
if PLOT:
pylab.subplot(2, 1, 1)
pylab.pcolor(data[...])
pylab.title('data')
pylab.subplot(2, 1, 2)
pylab.pcolor(test_data[...])
pylab.title('test_data (interpolated data)')
pylab.show()
def testGenGrids2(self):
latb = [62.47686472, 69.70600048]
lonb = [102.87075526, 105.51598035]
fn = self.getDataFile('sampleCurveGrid4.nc')
s = fn("sample")
g = s.getGrid()
lat = g.getLatitude()
lon = g.getLongitude()
g2 = cdms2.createGenericGrid(lat, lon)
datalat = g2.getLatitude().getBounds()[22, 25]
datalon = g2.getLongitude().getBounds()[22, 25]
self.assertTrue(numpy.ma.allclose(datalat, latb))
self.assertTrue(numpy.ma.allclose(datalon, lonb))
def __init__(self, state_xmlfile_dir, state_xmlfile_name):
#---------------------------------------------------------
"""
Initializes dataInterim class.
state_files_dir # TBD.
state_file_name #
"""
self.state_xmlfile_dir = state_xmlfile_dir
self.state_xmlfile_name = state_xmlfile_name
# These are to conform with MERRA names.
#---------------------------------------
self.var_dict = {'PHIS': 'var129', 'PS': 'var152', 'QV': 'var133',
'V': 'var132', 'U': 'var131', 'T': 'var130'}
fin = \
cdms2.open(self.state_xmlfile_dir + '/' + self.state_xmlfile_name)
zsfc = fin.variables['var129']
# Get coordinates.
#-----------------
lats = zsfc.getLatitude()[:]
lons = zsfc.getLongitude()[:]
self.lons = lons
self.lats = lats
# Create a CDMS grid object, so can use later for regridding.
#------------------------------------------------------------
self.grid = cdms2.createGenericGrid(self.lats, self.lons)
# Get hybrid coordinate information.
#-----------------------------------
p0, hyam, hybm, hyai, hybi = get_ab_interim.get_ab_interim()
self.p0 = p0
self.hyam = hyam
self.hybm = hybm
self.hyai = hyai
self.hybi = hybi
self.fin = fin
def makeGrid():
xstart=0
xend=360
xstep=0.5
ystart=-85
yend=85
ystep=0.5
lon_bnds=[]
lon=[]
for ii in numpy.arange(xstart, xend, xstep):
lon_bnds.append( [ii, ii+xstep] )
lon.append(ii+0.5*xstep)
lon_bnds=numpy.array(lon_bnds)
lon=numpy.array(lon)
lat_bnds=[]
lat=[]
for ii in numpy.arange(ystart, yend, ystep):
lat_bnds.append([ii, ii+ystep])
lat.append(ii+0.5*ystep)
lat_bnds=numpy.array(lat_bnds)
lat=numpy.array(lat)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units='degrees_north'
latAxis.long_name='Latitude'
latAxis.id='latitude'
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, 360.0)
lonAxis.units='degrees_east'
lonAxis.id='longitude'
lonAxis.long_name='Longitude'
lvl_bnds=numpy.array([[0,10], [10, 20], [20,30], [30,40], [40,50], [50,60], [60,70], [70,80], [80,90], [90,100], [100, 125], [125, 150], [150,175], [175,200], [200,250],[250,300],[300,400],[400,500], [500,600], [600,700], [700,800]])
lvl = [ 0.5*(lvls[0] + lvls[1]) for lvls in lvl_bnds ]
# lvl = numpy.zeros(len(lvl_bnds))
# for ii in range(len(lvl_bnds)): lvl[ii]=0.5*(lvl_bnds[ii,0]+lvl_bnds[ii,1])
return((cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds), latAxis, lonAxis, lat_bnds, lon_bnds, lvl_bnds, lvl))
def doRegrid(infile, varname, outfile, lon, lat, lon_bnds, lat_bnds):
cdms2.setNetcdfShuffleFlag(1)
cdms2.setNetcdfDeflateFlag(1)
cdms2.setNetcdfDeflateLevelFlag(2)
fh = cdms2.open(infile)
if fh is None:
exitMessage("Could not open file {0}. Exit 2.".format(infile), 2)
if varname not in fh.variables.keys():
exitMessage('variable named '+varname+' could not be found. Exit 4.', 4)
yVar = fh(varname)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units = 'degree_north'
latAxis.long_name = 'Latitude'
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, 360.0)
lonAxis.units = 'degree_east'
lonAxis.long_name='Longitude'
listAxisOrg = yVar.getAxisList()
timeAxis = listAxisOrg[0]
grid = cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds)
regridded = yVar.regrid(grid)
g=cdms2.open(outfile, 'w')
#g.write(regridded, None, None, None, varname, None, 1.e20, None, cdms2.CdFloat)
temp1 = cdms2.createVariable(regridded, typecode='f', id=varname, fill_value=1.e20, axes=[timeAxis, latAxis, lonAxis], copyaxes=0, attributes=dict(long_name=yVar.long_name, units=yVar.units) )
g.write(temp1)
g.close()
def makeGrid(thisStep=0.5):
xstart=0
xend=360
xstep=thisStep
ystart=-85
yend=85
ystep=thisStep
lon_bnds=[]
lon=[]
for ii in numpy.arange(xstart, xend, xstep):
lon_bnds.append( [ii, ii + xstep] )
lon.append(ii+0.5*xstep)
lon_bnds=numpy.array(lon_bnds)
lon=numpy.array(lon)
lat_bnds=[]
lat=[]
for ii in numpy.arange(ystart, yend, ystep):
lat_bnds.append([ii, ii + ystep])
lat.append(ii+0.5*ystep)
lat_bnds=numpy.array(lat_bnds)
lat=numpy.array(lat)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units='degrees_north'
latAxis.id='latitude'
latAxis.long_name='Latitude'
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, xend)
lonAxis.designateCircular(xend)
lonAxis.units='degrees_east'
lonAxis.id='longitude'
lonAxis.long_name='Longitude'
return((cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds), latAxis, lonAxis, lat_bnds, lon_bnds))
def test0FixedByKindig(self):
"""
Test from Kate Marvel
As the following code snippet demonstrates, regridding a
cdms2.tvariable.TransientVariable instance using regridTool='regrid2'
results in a new array that is masked everywhere. regridTool='esmf'
and regridTool='libcf' both work as expected.
Modified by Kindig to run.
"""
import cdms2 as cdms
import numpy as np
filename = cdat_info.get_sampledata_path() + '/clt.nc'
a=cdms.open(filename)
data=a('clt')[0,...]
print data.mask #verify this data is not masked
## Now create a new grid using every other latitude and every
# other longitude
LATS=data.getLatitude()[::2]
lb = data.getLatitude().getBounds()[::2][:,0]
ub = data.getLatitude().getBounds()[::2][:,1]
latbounds = np.array(zip(lb, ub))
self.assertEqual((ub != lb).all(), True)
self.assertEqual(lb.min(), -90.0)
LONS=data.getLongitude()[::2]
lb=data.getLongitude().getBounds()[::2][:,0]
ub=data.getLongitude().getBounds()[::2][:,1]
lonbounds=np.array(zip(lb, ub))
self.assertEqual((ub != lb).all(), True)
self.assertEqual(lb.min(), -182.5)
GRID=cdms.createGenericGrid(LATS,LONS,
latBounds=latbounds,
lonBounds=lonbounds)
uniGrid = cdms.grid.createUniformGrid(-90, 23, 8, -180, 36, 10)
test_gen = data.regrid(GRID,regridTool='regrid2')
test_uni = data.regrid(uniGrid, regridTool = 'regrid2')
# check that the mask does not extend everywhere...
print data.mask, data.size
print 'GENERIC', test_gen.mask.sum(), test_gen.size
print 'UNIFORM', test_uni.mask.sum(), test_uni.size
self.assertNotEqual(test_uni.mask.sum(), test_uni.size)
self.assertNotEqual(test_gen.mask.sum(), test_gen.size)
if PLOT:
pylab.subplot(2, 1, 1)
pylab.pcolor(data[...])
pylab.title('data')
pylab.subplot(2, 1, 2)
pylab.pcolor(test_gen[...])
pylab.title('test_gen (interpolated data)')
pylab.show()
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()
f.close()
# Test pressure regridder --------------------------------
import numpy
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)
CTIminlati = np.argmin(np.abs(lats - (-6)))
CTImaxlati = np.argmin(np.abs(lats - 6))
CTIminloni = np.argmin(np.abs(lons - 0))
CTImaxloni = np.argmin(np.abs(lons - 90))
CTI = spatial_ave(sst[:, CTIminlati:CTImaxlati, CTIminloni:CTImaxloni],
lats[CTIminlati:CTImaxlati])
#SUBTRACT COLD TONGUE INDEX FROM SST
#coarse grid lat/lon spacing
cstep = 1
lats = np.arange(minlat, maxlat + cstep, cstep)
lons = np.arange(0, 360 + cstep, cstep)
cgrid = cdms2.createGenericGrid(lats, lons)
#regridfunc = Regridder(ingrid, cgrid)
sst = sst.regrid(cgrid, regridTool="esmf", regridMethod="linear")
field = field.regrid(cgrid, regridTool="esmf", regridMethod="linear")
u = u.regrid(cgrid, regridTool="esmf", regridMethod="linear")
v = v.regrid(cgrid, regridTool="esmf", regridMethod="linear")
ps = ps.regrid(cgrid, regridTool="esmf", regridMethod="linear")
sst = sst.subRegion(latitude=(latbounds[0], latbounds[1]),
longitude=(lonbounds[0], lonbounds[1]))
field = field.subRegion(latitude=(latbounds[0], latbounds[1]),
longitude=(lonbounds[0], lonbounds[1]))
u = u.subRegion(latitude=(latbounds[0], latbounds[1]),
longitude=(lonbounds[0], lonbounds[1]))
v = v.subRegion(latitude=(latbounds[0], latbounds[1]),
longitude=(lonbounds[0], lonbounds[1]))
def makeGrid4D():
xstart=0
xend=360
xstep=0.5
ystart=-85
yend=85
ystep=0.5
# zlevels=[6, 17, 27, 37, 47, 57, 68.5, 82.5, 100, 122.5, 150, 182.5, 220, 262.5, 310, 362.5, 420, 485, 560, 645, 740, 845, 960, 1085]
zlevels=[3.3, 10, 20, 30, 50, 75, 100, 125, 150, 200, 250, 300, 400, 500]
lvl_bnds=[]
for ii in range(0, len(zlevels)):
if ii==0:
xs = 0
else:
xs = 0.5 * ( zlevels[ii-1] + zlevels[ii] )
if ii==(len(zlevels)-1):
xe = zlevels[ii] + 0.5 * (zlevels[ii] - zlevels[ii-1])
else:
xe = 0.5 * ( zlevels[ii] + zlevels[ii+1] )
lvl_bnds.append( [xs, xe] )
zlevels=numpy.array(zlevels)
lvl_bnds=numpy.array(lvl_bnds)
print zlevels
print lvl_bnds
lvlAxis = cdms2.createAxis(zlevels, lvl_bnds)
lvlAxis.units='m'
lvlAxis.long_name='depth'
lvlAxis.id='level'
lvlAxis.designateLevel(True)
lon_bnds=[]
lon=[]
for ii in numpy.arange(xstart, xend, xstep):
lon_bnds.append( [ii, ii+xstep] )
lon.append(ii+0.5*xstep)
lon_bnds=numpy.array(lon_bnds)
lon=numpy.array(lon)
lat_bnds=[]
lat=[]
for ii in numpy.arange(ystart, yend, ystep):
lat_bnds.append([ii, ii+ystep])
lat.append(ii+0.5*ystep)
lat_bnds=numpy.array(lat_bnds)
lat=numpy.array(lat)
latAxis = cdms2.createAxis(lat, lat_bnds)
latAxis.designateLatitude(True)
latAxis.units='degrees_north'
latAxis.long_name='Latitude'
latAxis.id='latitude'
lonAxis = cdms2.createAxis(lon, lon_bnds)
lonAxis.designateLongitude(True, 360.0)
lonAxis.units='degrees_east'
lonAxis.id='longitude'
lonAxis.long_name='Longitude'
return((cdms2.createGenericGrid(latAxis, lonAxis, lat_bnds, lon_bnds), latAxis, lonAxis, lat_bnds, lon_bnds, lvlAxis, lvl_bnds))
def test0FixedByKindig(self):
"""
Test from Kate Marvel
As the following code snippet demonstrates, regridding a
cdms2.tvariable.TransientVariable instance using regridTool='regrid2'
results in a new array that is masked everywhere. regridTool='esmf'
and regridTool='libcf' both work as expected.
Modified by Kindig to run.
"""
import cdms2 as cdms
import numpy as np
filename = cdat_info.get_prefix() + '/sample_data/clt.nc'
a = cdms.open(filename)
data = a('clt')[0, ...]
print data.mask #verify this data is not masked
## Now create a new grid using every other latitude and every
# other longitude
LATS = data.getLatitude()[::2]
lb = data.getLatitude().getBounds()[::2][:, 0]
ub = data.getLatitude().getBounds()[::2][:, 1]
latbounds = np.array(zip(lb, ub))
self.assertEqual((ub != lb).all(), True)
self.assertEqual(lb.min(), -90.0)
LONS = data.getLongitude()[::2]
lb = data.getLongitude().getBounds()[::2][:, 0]
ub = data.getLongitude().getBounds()[::2][:, 1]
lonbounds = np.array(zip(lb, ub))
self.assertEqual((ub != lb).all(), True)
self.assertEqual(lb.min(), -182.5)
GRID = cdms.createGenericGrid(LATS,
LONS,
latBounds=latbounds,
lonBounds=lonbounds)
uniGrid = cdms.grid.createUniformGrid(-90, 23, 8, -180, 36, 10)
test_gen = data.regrid(GRID, regridTool='regrid2')
test_uni = data.regrid(uniGrid, regridTool='regrid2')
# check that the mask does not extend everywhere...
print data.mask, data.size
print 'GENERIC', test_gen.mask.sum(), test_gen.size
print 'UNIFORM', test_uni.mask.sum(), test_uni.size
self.assertNotEqual(test_uni.mask.sum(), test_uni.size)
self.assertNotEqual(test_gen.mask.sum(), test_gen.size)
if PLOT:
pylab.subplot(2, 1, 1)
pylab.pcolor(data[...])
pylab.title('data')
pylab.subplot(2, 1, 2)
pylab.pcolor(test_gen[...])
pylab.title('test_gen (interpolated data)')
pylab.show()
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)
if (abs(newar[0][-1]-488.4763488) > 1.e-3): markError('regrid numpy array with grid input mask',newar[0][-1])
# Dataset
g = cdms2.open(os.path.join(pth,'test.xml'))
u = g.variables['u']
outgrid = cdms2.createGaussianGrid(24)
regridf3 = Regridder(u.getGrid(), outgrid)
try:
unew = regridf3(u)
except:
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()
f.close()
# Test pressure regridder --------------------------------
import numpy
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
f.close()
LWkernel = MV.masked_where(np.isnan(LWkernel), LWkernel)
SWkernel = MV.masked_where(np.isnan(SWkernel), SWkernel)
albcs = np.arange(
0.0, 1.5, 0.5) # the clear-sky albedos over which the kernel is computed
# Define the cloud kernel axis attributes
lats = cdms.createAxis(LWkernel.getLatitude()[:])
lats.id = "lat"
lats.units = "degrees_N"
lats.designateLatitude()
lons = cdms.createAxis(np.arange(1.25, 360, 2.5))
lons.id = "lon"
lons.units = "degrees_E"
lons.designateLongitude()
kern_grid = cdms.createGenericGrid(lats, lons)
kern_grid.getLatitude().id = 'lat'
kern_grid.getLongitude().id = 'lon'
##########################################################
##### Load in ISCCP HGG clisccp climo annual cycle ######
##########################################################
f = cdms.open(datadir + 'AC_clisccp_ISCCP_HGG_198301-200812.nc', 'r')
#f.history='Written by /work/zelinka1/scripts/load_ISCCP_HGG.py on feedback.llnl.gov'
#f.comment='Monthly-resolved climatological annual cycle over 198301-200812'
obs_clisccp_AC = f('AC_clisccp')
f.close()
f = cdms.open(datadir + 'AC_clisccp_wap_ISCCP_HGG_198301-200812.nc', 'r')
#f.history='Written by /work/zelinka1/scripts/load_ISCCP_HGG.py on feedback.llnl.gov'
#f.comment='Monthly-resolved climatological annual cycle over 198301-200812, in omega500 space'
