def read_and_mask (var_name, file_path, check_diff_time=False, gtype='t'):
if var_name in ['tminustf', 'rho']:
# Need to read 2 variables
temp = read_and_mask('THETA', file_path, check_diff_time=check_diff_time)
salt = read_and_mask('SALT', file_path, check_diff_time=check_diff_time)
if var_name == 'rho':
return mask_3d(density(eosType, salt, temp, ref_depth, rhoConst=rhoConst, Tref=Tref, Sref=Sref, tAlpha=tAlpha, sBeta=sBeta), grid)
elif var_name == 'tminustf':
return t_minus_tf(temp, salt, grid)
elif var_name in ['vnorm', 'valong']:
u = read_and_mask('UVEL', file_path, check_diff_time=check_diff_time, gtype='u')
v = read_and_mask('VVEL', file_path, check_diff_time=check_diff_time, gtype='v')
if var_name == 'vnorm':
return normal_vector(u, v, grid, point0, point1)
elif var_name == 'valong':
return parallel_vector(u, v, grid, point0, point1)
elif var_name == 'tadv_along':
tadv_x = read_and_mask('ADVx_TH', file_path, check_diff_time=check_diff_time)
tadv_y = read_and_mask('ADVy_TH', file_path, check_diff_time=check_diff_time)
return parallel_vector(tadv_x, tadv_y, grid, point0, point1)
elif var_name == 'tdif_along':
tdif_x = read_and_mask('DFxE_TH', file_path, check_diff_time=check_diff_time)
tdif_y = read_and_mask('DFyE_TH', file_path, check_diff_time=check_diff_time)
return parallel_vector(tdif_x, tdif_y, grid, point0, point1)
else:
if check_diff_time and diff_time:
return mask_3d(read_netcdf(file_path, var_name, time_index=time_index_2, t_start=t_start_2, t_end=t_end_2, time_average=time_average), grid, gtype=gtype)
else:
return mask_3d(read_netcdf(file_path, var_name, time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid, gtype=gtype)
def read_plot_ts_slice (file_path, grid, lon0=None, lat0=None, time_index=None, t_start=None, t_end=None, time_average=False, hmin=None, hmax=None, zmin=None, zmax=None, tmin=None, tmax=None, smin=None, smax=None, date_string=None, fig_name=None, second_file_path=None):
# Make sure we'll end up with a single record in time
if time_index is None and not time_average:
print 'Error (read_plot_ts_slice): either specify time_index or set time_average=True.'
sys.exit()
if date_string is None and time_index is not None:
# Determine what to write about the date
date_string = parse_date(file_path=file_path, time_index=time_index)
if not isinstance(grid, Grid):
# This is the path to the NetCDF grid file, not a Grid object
# Make a grid object from it
grid = Grid(grid)
# Read temperature
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'THETA')
else:
file_path_use = file_path
temp = mask_3d(read_netcdf(file_path_use, 'THETA', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid)
# Read salinity
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'SALT')
else:
file_path_use = file_path
salt = mask_3d(read_netcdf(file_path_use, 'SALT', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid)
# Plot
ts_slice_plot(temp, salt, grid, lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, tmin=tmin, tmax=tmax, smin=smin, smax=smax, date_string=date_string, fig_name=fig_name)
def read_and_mask (var_name, file_path, second_file_path=None, check_diff_time=False):
# Do we need to choose the right file?
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, var_name)
else:
file_path_use = file_path
# Read and mask the data
if check_diff_time and diff_time:
return mask_3d(read_netcdf(file_path_use, var_name, time_index=time_index_2, t_start=t_start_2, t_end=t_end_2, time_average=time_average), grid)
else:
return mask_3d(read_netcdf(file_path_use, var_name, time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid)
def timeseries_transport_transect(file_path,
grid,
point0,
point1,
direction='N',
time_index=None,
t_start=None,
t_end=None,
time_average=False):
# Read u and v
u = mask_3d(read_netcdf(file_path,
'UVEL',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='u',
time_dependent=True)
v = mask_3d(read_netcdf(file_path,
'VVEL',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='v',
time_dependent=True)
if len(u.shape) == 3:
# Just one timestep; add a dummy time dimension
u = np.expand_dims(u, 0)
v = np.expand_dims(v, 0)
# Build the timeseries
timeseries = []
for t in range(u.shape[0]):
# Get the "southward" and "northward" components
trans_S, trans_N = transport_transect(u[t, :], v[t, :], grid, point0,
point1)
# Combine them
if direction == 'N':
trans = trans_N - trans_S
elif direction == 'S':
trans = trans_S - trans_N
else:
print 'Error (timeseries_transport_transect): invalid direction ' + direction
sys.exit()
timeseries.append(trans)
return np.array(timeseries)
def read_plot_slice (var, file_path, grid, lon0=None, lat0=None, time_index=None, t_start=None, t_end=None, time_average=False, hmin=None, hmax=None, zmin=None, zmax=None, vmin=None, vmax=None, date_string=None, fig_name=None, second_file_path=None):
# Make sure we'll end up with a single record in time
if time_index is None and not time_average:
print 'Error (read_plot_slice): either specify time_index or set time_average=True.'
sys.exit()
if date_string is None and time_index is not None:
# Determine what to write about the date
date_string = parse_date(file_path=file_path, time_index=time_index)
if not isinstance(grid, Grid):
# This is the path to the NetCDF grid file, not a Grid object
# Make a grid object from it
grid = Grid(grid)
# Read necessary variables from NetCDF file and mask appropriately
if var in ['temp', 'tminustf']:
# Read temperature. Some of these variables need more than temperature and so second_file_path might be set.
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'THETA')
else:
file_path_use = file_path
temp = mask_3d(read_netcdf(file_path_use, 'THETA', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid)
if var in ['salt', 'tminustf']:
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'SALT')
else:
file_path_use = file_path
salt = mask_3d(read_netcdf(file_path_use, 'SALT', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid)
if var == 'u':
u = mask_3d(read_netcdf(file_path, 'UVEL', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid, gtype='u')
if var == 'v':
v = mask_3d(read_netcdf(file_path, 'VVEL', time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid, gtype='v')
# Plot
if var == 'temp':
slice_plot(temp, grid, lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, title=r'Temperature ($^{\circ}$C)', date_string=date_string, fig_name=fig_name)
elif var == 'salt':
slice_plot(salt, grid, lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, title='Salinity (psu)', date_string=date_string, fig_name=fig_name)
elif var == 'tminustf':
slice_plot(t_minus_tf(temp, salt, grid), grid, lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', title=r'Difference from in-situ freezing point ($^{\circ}$C)', date_string=date_string, fig_name=fig_name)
elif var == 'u':
slice_plot(u, grid, gtype='u', lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', title='Zonal velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'v':
slice_plot(v, grid, gtype='v', lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', title='Zonal velocity (m/s)', date_string=date_string, fig_name=fig_name)
else:
print 'Error (read_plot_slice): variable key ' + str(var) + ' does not exist'
sys.exit()
def read_process_data (file_path, var_name, grid, mask_option='3d', gtype='t', lev_option=None, ismr=False, psi=False):
data = read_netcdf(file_path, var_name)
if mask_option == '3d':
data = mask_3d(data, grid, gtype=gtype, time_dependent=True)
elif mask_option == 'except_ice':
data = mask_except_ice(data, grid, gtype=gtype, time_dependent=True)
elif mask_option == 'land':
data = mask_land(data, grid, gtype=gtype, time_dependent=True)
elif mask_option == 'land_ice':
data = mask_land_ice(data, grid, gtype=gtype, time_dependent=True)
else:
print 'Error (read_process_data): invalid mask_option ' + mask_option
sys.exit()
if lev_option is not None:
if lev_option == 'top':
data = select_top(data)
elif lev_option == 'bottom':
data = select_bottom(data)
else:
print 'Error (read_process_data): invalid lev_option ' + lev_option
sys.exit()
if ismr:
data = convert_ismr(data)
if psi:
data = np.sum(data, axis=-3)*1e-6
return data
def timeseries_avg_3d(file_path,
var_name,
grid,
gtype='t',
time_index=None,
t_start=None,
t_end=None,
time_average=False,
mask=None):
data = read_netcdf(file_path,
var_name,
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average)
if len(data.shape) == 3:
# Just one timestep; add a dummy time dimension
data = np.expand_dims(data, 0)
# Process one time index at a time to save memory
timeseries = []
for t in range(data.shape[0]):
if mask is None:
data_tmp = mask_3d(data[t, :], grid, gtype=gtype)
else:
data_tmp = apply_mask(data[t, :],
np.invert(mask),
depth_dependent=True)
# Volume average
timeseries.append(volume_average(data_tmp, grid, gtype=gtype))
return np.array(timeseries)
def read_and_mask (var_name, check_second=False, gtype='t'):
# Do we need to choose the right file?
if check_second and second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, var_name)
else:
file_path_use = file_path
# Read and mask the data
return mask_3d(read_netcdf(file_path_use, var_name, time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid, gtype=gtype)
def vertical_resolution (grid, lon0=None, lat0=None, hmin=None, hmax=None, zmin=None, zmax=None, vmin=None, vmax=None, fig_name=None):
if not isinstance(grid, Grid):
# Create a Grid object from the given path
grid = Grid(grid)
# Tile dz so it's 3D, and apply mask and hFac
dz = mask_3d(z_to_xyz(grid.dz, grid), grid)*grid.hfac
# Plot
slice_plot(dz, grid, lon0=lon0, lat0=lat0, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, title='Vertical resolution (m)', fig_name=fig_name)
def precompute_hovmoller (mit_file, hovmoller_file, loc=['PIB', 'Dot'], var=['temp', 'salt'], monthly=True):
# Build the grid
grid = Grid(mit_file)
# Set up or update the file and time axis
id = set_update_file(hovmoller_file, grid, 'zt')
num_time = set_update_time(id, mit_file, monthly=monthly)
for v in var:
print 'Processing ' + v
if v == 'temp':
var_name = 'THETA'
title = 'Temperature'
units = 'degC'
elif v == 'salt':
var_name = 'SALT'
title = 'Salinity'
units = 'psu'
# Read data and mask land/ice shelves
data_full = mask_3d(read_netcdf(mit_file, var_name), grid, time_dependent=True)
for l in loc:
print '...at ' + l
if l == 'PIB':
loc_name = 'Pine Island Bay'
[xmin, xmax, ymin, ymax] = bounds_PIB
elif l == 'Dot':
loc_name = 'Dotson front'
[xmin, xmax, ymin, ymax] = bounds_Dot
# Average over the correct region
data = mask_outside_box(data_full, grid, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, time_dependent=True)
data = area_average(data, grid, time_dependent=True)
set_update_var(id, num_time, data, 'zt', l+'_'+v, loc_name+' '+title, units)
# Finished
if isinstance(id, nc.Dataset):
id.close()
elif isinstance(id, NCfile):
id.close()
def interp_grid(data,
grid,
gtype_in,
gtype_out,
time_dependent=False,
mask=True,
mask_shelf=False,
mask_with_zeros=False,
periodic=False):
depth_dependent = is_depth_dependent(data, time_dependent=time_dependent)
# Make sure we're not trying to mask the ice shelf from a depth-dependent field
if mask_shelf and depth_dependent:
print "Error (interp_grid): can't set mask_shelf=True for a depth-dependent field."
sys.exit()
if mask and gtype_in in ['u', 'v', 'psi', 'w']:
# Fill the mask with zeros (okay because no-slip boundary condition)
data_tmp = np.copy(data)
data_tmp[data.mask] = 0.0
else:
# Tracer land mask is the least restrictive, so it doesn't matter what the masked values are - they will definitely get re-masked at the end.
data_tmp = data
# Interpolate
data_interp = np.empty(data_tmp.shape)
if gtype_in == 'u' and gtype_out == 't':
# Midpoints in the x direction
data_interp[..., :-1] = 0.5 * (data_tmp[..., :-1] + data_tmp[..., 1:])
# Extend/wrap the easternmost column
if periodic:
data_interp[..., -1] = data_interp[..., 0]
else:
data_interp[..., -1] = data_tmp[..., -1]
elif gtype_in == 'v' and gtype_out == 't':
# Midpoints in the y direction
data_interp[..., :-1, :] = 0.5 * (data_tmp[..., :-1, :] +
data_tmp[..., 1:, :])
# Extend the northernmost row
data_interp[..., -1, :] = data_tmp[..., -1, :]
elif gtype_in == 't' and gtype_out == 'u':
# Midpoints in the x direction
data_interp[..., 1:] = 0.5 * (data_tmp[..., :-1] + data_tmp[..., 1:])
# Extend/wrap the westernmost column
if periodic:
data_interp[..., 0] = data_interp[..., -1]
else:
data_interp[..., 0] = data_tmp[..., 0]
elif gtype_in == 't' and gtype_out == 'v':
# Midpoints in the y direction
data_interp[..., 1:, :] = 0.5 * (data_tmp[..., :-1, :] +
data_tmp[..., :-1, :])
# Extend the southernmost row
data_interp[..., 0, :] = data_tmp[..., 0, :]
else:
print 'Error (interp_grid): interpolation from the ' + gtype_in + '-grid to the ' + gtype_out + '-grid is not yet supported'
sys.exit()
if mask:
# Now apply the mask
if depth_dependent:
data_interp = mask_3d(data_interp,
grid,
gtype=gtype_out,
time_dependent=time_dependent)
else:
if mask_shelf:
data_interp = mask_land_ice(data_interp,
grid,
gtype=gtype_out,
time_dependent=time_dependent)
else:
data_interp = mask_land(data_interp,
grid,
gtype=gtype_out,
time_dependent=time_dependent)
if mask_with_zeros:
# Remove mask and fill with zeros
data_interp[data_interp.mask] = 0
data_interp = data_interp.data
return data_interp
def read_plot_slice (var, file_path, grid=None, lon0=None, lat0=None, point0=None, point1=None, time_index=None, t_start=None, t_end=None, time_average=False, hmin=None, hmax=None, zmin=None, zmax=None, vmin=None, vmax=None, contours=None, date_string=None, fig_name=None, second_file_path=None, eosType='MDJWF', rhoConst=None, Tref=None, Sref=None, tAlpha=None, sBeta=None, ref_depth=0):
# Build the grid if needed
grid = choose_grid(grid, file_path)
# Make sure we'll end up with a single record in time
check_single_time(time_index, time_average)
# Determine what to write about the date
date_string = check_date_string(date_string, file_path, time_index)
# Inner function to read a variable from the correct NetCDF file and mask appropriately
def read_and_mask (var_name, check_second=False, gtype='t'):
# Do we need to choose the right file?
if check_second and second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, var_name)
else:
file_path_use = file_path
# Read and mask the data
return mask_3d(read_netcdf(file_path_use, var_name, time_index=time_index, t_start=t_start, t_end=t_end, time_average=time_average), grid, gtype=gtype)
# Read necessary variables from NetCDF file and mask appropriately
if var in ['temp', 'tminustf', 'rho']:
temp = read_and_mask('THETA', check_second=True)
if var in ['salt', 'tminustf', 'rho']:
salt = read_and_mask('SALT', check_second=True)
if var in ['u', 'vnorm', 'valong']:
u = read_and_mask('UVEL', gtype='u')
if var in ['v', 'vnorm', 'valong']:
v = read_and_mask('VVEL', gtype='v')
if var == 'tadv_along':
tadv_x = read_and_mask('ADVx_TH')
tadv_y = read_and_mask('ADVy_TH')
if var == 'tdif_along':
tdif_x = read_and_mask('DFxE_TH')
tdif_y = read_and_mask('DFyE_TH')
if var in ['vnorm', 'valong', 'tadv_along', 'tdif_along'] and None in [point0, point1]:
print 'Error (read_plot_slice): normal or along-transect variables require point0 and point1 to be specified.'
sys.exit()
# Plot
if var == 'temp':
slice_plot(temp, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Temperature ('+deg_string+'C)', date_string=date_string, fig_name=fig_name)
elif var == 'salt':
slice_plot(salt, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Salinity (psu)', date_string=date_string, fig_name=fig_name)
elif var == 'tminustf':
slice_plot(t_minus_tf(temp, salt, grid), grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, ctype='plusminus', title='Difference from in-situ freezing point ('+deg_string+'C)', date_string=date_string, fig_name=fig_name)
elif var == 'rho':
# Calculate density
rho = mask_3d(density(eosType, salt, temp, ref_depth, rhoConst=rhoConst, Tref=Tref, Sref=Sref, tAlpha=tAlpha, sBeta=sBeta), grid)
slice_plot(rho, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title=r'Density (kg/m$^3$)', date_string=date_string, fig_name=fig_name)
elif var == 'u':
slice_plot(u, grid, gtype='u', lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title='Zonal velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'v':
slice_plot(v, grid, gtype='v', lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title='Meridional velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'vnorm':
vnorm = normal_vector(u, v, grid, point0, point1)
slice_plot(vnorm, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title='Normal velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'valong':
valong = parallel_vector(u, v, grid, point0, point1)
slice_plot(valong, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title='Along-transect velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'tadv_along':
tadv_along = parallel_vector(tadv_x, tadv_y, grid, point0, point1)
slice_plot(tadv_along, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title=r'Along-transect advective heat transport (Km$^3$/s)', date_string=date_string, fig_name=fig_name)
elif var == 'tdif_along':
tdif_along = parallel_vector(tdif_x, tdif_y, grid, point0, point1)
slice_plot(tdif_along, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, ctype='plusminus', contours=contours, title=r'Along-transect diffusive heat transport (Km$^3$/s)', date_string=date_string, fig_name=fig_name)
else:
print 'Error (read_plot_slice): variable key ' + str(var) + ' does not exist'
sys.exit()
def read_plot_latlon(var,
file_path,
grid,
time_index=None,
t_start=None,
t_end=None,
time_average=False,
vmin=None,
vmax=None,
zoom_fris=False,
xmin=None,
xmax=None,
ymin=None,
ymax=None,
date_string=None,
fig_name=None,
second_file_path=None,
change_points=None,
tf_option='min',
vel_option='avg'):
# Make sure we'll end up with a single record in time
if time_index is None and not time_average:
print 'Error (read_plot_latlon): either specify time_index or set time_average=True.'
sys.exit()
if date_string is None and time_index is not None:
# Determine what to write about the date
date_string = parse_date(file_path=file_path, time_index=time_index)
if not isinstance(grid, Grid):
# This is the path to the NetCDF grid file, not a Grid object
# Make a grid object from it
grid = Grid(grid)
# Read necessary variables from NetCDF file(s), and mask appropriately
if var == 'ismr':
shifwflx = mask_except_zice(
read_netcdf(file_path,
'SHIfwFlx',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var in ['bwtemp', 'sst', 'tminustf']:
# Read temperature. Some of these variables need more than temperature and so second_file_path might be set.
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'THETA')
else:
file_path_use = file_path
temp = mask_3d(
read_netcdf(file_path_use,
'THETA',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var in ['bwsalt', 'sss', 'tminustf']:
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'SALT')
else:
file_path_use = file_path
salt = mask_3d(
read_netcdf(file_path_use,
'SALT',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'aice':
aice = mask_land_zice(
read_netcdf(file_path,
'SIarea',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'hice':
hice = mask_land_zice(
read_netcdf(file_path,
'SIheff',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'mld':
mld = mask_land_zice(
read_netcdf(file_path,
'MXLDEPTH',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'eta':
eta = mask_land_zice(
read_netcdf(file_path,
'ETAN',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'saltflx':
saltflx = mask_land_zice(
read_netcdf(file_path,
'SIempmr',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average), grid)
if var == 'vel':
# First read u
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'UVEL')
else:
file_path_use = file_path
u = mask_3d(read_netcdf(file_path_use,
'UVEL',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='u')
# Now read v
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path, 'VVEL')
else:
file_path_use = file_path
v = mask_3d(read_netcdf(file_path_use,
'VVEL',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='v')
if var == 'velice':
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path,
'SIuice')
else:
file_path_use = file_path
uice = mask_land_zice(read_netcdf(file_path_use,
'SIuice',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='u')
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path,
'SIvice')
else:
file_path_use = file_path
vice = mask_land_zice(read_netcdf(file_path_use,
'SIvice',
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average),
grid,
gtype='v')
# Plot
if var == 'ismr':
plot_ismr(shifwflx,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
change_points=change_points,
date_string=date_string,
fig_name=fig_name)
elif var == 'bwtemp':
plot_bw('temp',
temp,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'bwsalt':
plot_bw('salt',
salt,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'sst':
plot_ss('temp',
temp,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'sss':
plot_ss('salt',
salt,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'aice':
plot_2d_noshelf('aice',
aice,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'hice':
plot_2d_noshelf('hice',
hice,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'mld':
plot_2d_noshelf('mld',
mld,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'eta':
plot_2d_noshelf('eta',
eta,
grid,
ctype='plusminus',
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'saltflx':
plot_2d_noshelf('saltflx',
saltflx,
grid,
ctype='plusminus',
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'tminustf':
plot_tminustf(temp,
salt,
grid,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
tf_option=tf_option,
date_string=date_string,
fig_name=fig_name)
elif var == 'vel':
plot_vel(u,
v,
grid,
vel_option=vel_option,
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
elif var == 'velice':
plot_vel(uice,
vice,
grid,
vel_option='ice',
vmin=vmin,
vmax=vmax,
zoom_fris=zoom_fris,
xmin=xmin,
xmax=xmax,
ymin=ymin,
ymax=ymax,
date_string=date_string,
fig_name=fig_name)
else:
print 'Error (read_plot_latlon): variable key ' + str(
var) + ' does not exist'
sys.exit()