def save_results(self):
if self.nc is None:
return
output_file = self.get_output()
if output_file is None:
print "No output file selected; cannot proceed."
return
print "Saving the mask to %s" % output_file
nc = NC(output_file, 'w')
nc.createDimension('x', self.x.size)
nc.createDimension('y', self.y.size)
x = nc.createVariable("x", 'f8', ('x',))
y = nc.createVariable("y", 'f8', ('y',))
mask = nc.createVariable("ftt_mask", 'i4', ('y', 'x'))
mask.long_name = "Drainage basin area for regional modeling"
x_orig = self.nc.variables['x']
y_orig = self.nc.variables['y']
for var, old_var in zip([x,y], [x_orig, y_orig]):
for attr in old_var.ncattrs():
var.setncattr(attr, old_var.getncattr(attr))
x[:] = self.x
y[:] = self.y
nc.variables['ftt_mask'][:] = (self.mask == 2)
nc.close()
print "Done."
nprocs=nprocs)
# binary density (0: no data, 1: data)
rho = np.ones_like(result)
rho[result==fill_value] = 0
# Make a quick plot
fig_str = out_filename.split('.')[0]
fig_name = fig_str + '.png'
pr.plot.save_quicklook(fig_name, area_def, result, label='ice thickness')
# Write the data:
nc = CDF(out_filename, "w", format="NETCDF3_CLASSIC")
nc.createDimension("y", size=northing.shape[0])
nc.createDimension("x", size=easting.shape[0])
x = nc.createVariable("x", 'f', dimensions=("x",))
x.units = "m";
x.long_name = "easting"
x.standard_name = "projection_x_coordinate"
y = nc.createVariable("y", 'f', dimensions=("y",))
y.units = "m";
y.long_name = "northing"
y.standard_name = "projection_y_coordinate"
mapping_var = 'mapping'
mapping = nc.createVariable(mapping_var, 'b')
mapping.grid_mapping_name = "polar_stereographic"
mapping.latitude_of_projection_origin = 90.
mapping.straight_vertical_longitude_from_pole = -45.0
mapping.standard_parallel = 70.0
output_filename = '_'.join([project_name, gs_str, alpha_str,
gamma_str, vel_str, dHdt_str, bmelt_str,]) + '.nc'
mesh_out = RectangleMesh(np.float(xmin), np.float(ymin),
np.float(xmax), np.float(ymax),
M, N)
print "Creating output file..."
nc = CDF('/'.join([project_name, output_filename]), 'w')
nc.createDimension("y", size=y.shape[0])
nc.createDimension("x", size=x.shape[0])
nc.createDimension("time")
x_var = nc.createVariable("x", 'f', dimensions=("x",))
x_var.units = "m";
x_var.long_name = "easting"
x_var.standard_name = "projection_x_coordinate"
x_var[:] = x
y_var = nc.createVariable("y", 'f', dimensions=("y",))
y_var.units = "m";
y_var.long_name = "northing"
y_var.standard_name = "projection_y_coordinate"
y_var[:] = y
t_var = nc.createVariable("time", 'f', dimensions=("time",))
t_var.units = "years"
t_var.long_name = "time"
t_var.axis = "T"
try:
from netCDF3 import Dataset as CDF
except:
from netCDF4 import Dataset as CDF
x, topg, thk = np.loadtxt('sg_35m_flowline.txt', unpack=True)
output = 'storglaciaren_flowline.nc'
# Write the data:
print("Writing the data to '%s'... " % output)
nc = CDF(output, "w")
nc.createDimension("x", size=len(x))
x_var = nc.createVariable("x", 'f', dimensions=("x", ))
x_var.units = "m"
x_var[:] = x
topg_var = nc.createVariable("topg", 'f', dimensions=("x", ))
topg_var.units = "m"
topg_var.standard_name = "bedrock_altitude"
topg_var[:] = topg
thk_var = nc.createVariable("thk", 'f', dimensions=("x", ))
thk_var.units = "m"
thk_var.standard_name = "land_ice_thickness"
thk_var[:] = thk
usurf_var = nc.createVariable("usurf", 'f', dimensions=("x", ))
usurf_var.units = "m"
options = parser.parse_args()
args = options.FILE
infile = args[0]
nc = CDF(infile, 'a')
mapping_var = 'mapping'
for var in nc.variables.keys():
if hasattr(var, 'grid_mapping'):
mapping_var = var.grid_mapping
pass
if not var in nc.variables.keys():
mapping = nc.createVariable(mapping_var, 'b')
else:
mapping = nc.variables[mapping_var]
mapping.grid_mapping_name = "polar_stereographic"
mapping.latitude_of_projection_origin = 90.
mapping.straight_vertical_longitude_from_pole = -45.0
mapping.standard_parallel = 70.0
mapping.false_easting = 0.
mapping.false_northing = 0.
mapping.units = "m"
# Save the projection information:
nc.proj4 = "+init=epsg:3413"
npz_vars={}
one_d={}
out_vars={}
for the_dim in ['x','y','z']:
one_d[the_dim]=nc_in.variables[the_dim]
npz_vars={}
sub_x=one_d['x'][new_x]
sub_y=one_d['y'][new_y]
sub_z=one_d['z'][:]
nc_out.createDimension('x',len(sub_x))
nc_out.createDimension('y',len(sub_y))
nc_out.createDimension('z',len(sub_z))
for the_dim in ['x','y','z']:
out_vars[the_dim]=nc_out.createVariable(the_dim,sub_x.dtype,(the_dim,))
press_var=nc_in.variables['p']
npz_vars['p']=press_var
out_vars['p']=nc_out.createVariable('p',press_var.dtype,press_var.dimensions)
out_vars['p'][...]=nc_in.variables['p'][...]
npz_vars['p']=nc_in.variables['p'][...]
for the_att in nc_in.variables['p'].ncattrs():
setattr(out_vars['p'],the_att,getattr(nc_in.variables['p'],the_att))
out_vars['x'][:]=sub_x[:]
npz_vars['x']=sub_x
out_vars['y'][:]=sub_y[:]
npz_vars['y']=sub_y
out_vars['z'][:]=sub_z[:]
npz_vars['z']=sub_z
M_out, N_out, area_extent)
fill_value = 4 # ocean
area_con_in_nn = pr.image.ImageContainerNearest(data, area_in_def,
radius_of_influence=radius_of_influence,
fill_value=fill_value,
nprocs=nprocs)
area_con_out_nn = area_con_in_nn.resample(area_out_def)
result = area_con_out_nn.image_data
pr.plot.save_quicklook('foo.png', area_out_def, result, label='mask')
try:
var = nc.createVariable("mask", 'b', dimensions=("y", "x"))
except:
var = nc.variables['mask']
#var[:] = np.flipud(result)
var[:] = result
# Save the projection information:
nc.projection = proj4_str
nc.Conventions = "CF-1.5"
# writing global attributes
import time
script_command = ' '.join([time.ctime(), ':', __file__.split('/')[-1],
' '.join([str(l) for l in args])])
nc.history = script_command
try:
from netCDF3 import Dataset as CDF
except:
from netCDF4 import Dataset as CDF
x,topg,thk = np.loadtxt('sg_35m_flowline.txt',unpack=True)
output = 'storglaciaren_flowline.nc'
# Write the data:
print("Writing the data to '%s'... " % output)
nc = CDF(output, "w")
nc.createDimension("x", size=len(x))
x_var = nc.createVariable("x", 'f', dimensions=("x",))
x_var.units = "m";
x_var[:] = x
topg_var = nc.createVariable("topg", 'f', dimensions=("x",))
topg_var.units = "m";
topg_var.standard_name = "bedrock_altitude"
topg_var[:] = topg
thk_var = nc.createVariable("thk", 'f', dimensions=("x",))
thk_var.units = "m";
thk_var.standard_name = "land_ice_thickness"
thk_var[:] = thk
usurf_var = nc.createVariable("usurf", 'f', dimensions=("x",))
usurf_var.units = "m";
