def read_plot_ts_slice_diff (file_path_1, file_path_2, grid=None, lon0=None, lat0=None, point0=None, point1=None, time_index=None, t_start=None, t_end=None, time_average=False, time_index_2=None, t_start_2=None, t_end_2=None, hmin=None, hmax=None, zmin=None, zmax=None, tmin=None, tmax=None, smin=None, smax=None, tcontours=None, scontours=None, date_string=None, fig_name=None, second_file_path_1=None, second_file_path_2=None):
diff_time = (time_index_2 is not None) or (time_average and (t_start_2 is not None or t_end_2 is not None))
grid = choose_grid(grid, file_path_1)
check_single_time(time_index, time_average)
date_string = check_date_string(date_string, file_path_1, time_index)
# Inner function to read a variable from the correct NetCDF file and mask appropriately
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)
# Interface to call read_and_mask for each variable
def read_and_mask_both (var_name):
data1 = read_and_mask(var_name, file_path_1, second_file_path=second_file_path_1)
data2 = read_and_mask(var_name, file_path_2, second_file_path=second_file_path_2, check_diff_time=True)
return data1, data2
# Read temperature and salinity for each simulation
temp_1, temp_2 = read_and_mask_both('THETA')
salt_1, salt_2 = read_and_mask_both('SALT')
# Plot
ts_slice_plot_diff(temp_1, temp_2, salt_1, salt_2, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, tmin=tmin, tmax=tmax, smin=smin, smax=smax, tcontours=tcontours, scontours=scontours, date_string=date_string, fig_name=fig_name)
def read_plot_ts_slice (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, tmin=None, tmax=None, smin=None, smax=None, tcontours=None, scontours=None, date_string=None, fig_name=None, second_file_path=None):
grid = choose_grid(grid, file_path)
check_single_time(time_index, time_average)
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):
# 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
data = 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)
return data
# Read temperature and salinity
temp = read_and_mask('THETA')
salt = read_and_mask('SALT')
# Plot
ts_slice_plot(temp, salt, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, tmin=tmin, tmax=tmax, smin=smin, smax=smax, tcontours=tcontours, scontours=scontours, date_string=date_string, fig_name=fig_name)
def read_plot_slice_diff (var, file_path_1, file_path_2, grid=None, lon0=None, lat0=None, point0=None, point1=None, time_index=None, t_start=None, t_end=None, time_average=False, time_index_2=None, t_start_2=None, t_end_2=None, hmin=None, hmax=None, zmin=None, zmax=None, vmin=None, vmax=None, contours=None, date_string=None, fig_name=None, eosType='MDJWF', rhoConst=None, Tref=None, Sref=None, tAlpha=None, sBeta=None, ref_depth=0):
# Figure out if the two files use different time indices
diff_time = (time_index_2 is not None) or (time_average and (t_start_2 is not None or t_end_2 is not None))
# Get set up just like read_plot_slice
grid = choose_grid(grid, file_path_1)
check_single_time(time_index, time_average)
date_string = check_date_string(date_string, file_path_1, time_index)
# Inner function to read a variable from a NetCDF file and mask appropriately
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)
# Interface to call read_and_mask for each variable
def read_and_mask_both (var_name, gtype='t'):
data1 = read_and_mask(var_name, file_path_1, gtype=gtype)
data2 = read_and_mask(var_name, file_path_2, check_diff_time=True, gtype=gtype)
return data1, data2
if var in ['vnorm', 'valong', 'tadv_along', 'tdif_along'] and None in [point0, point1]:
print 'Error (read_plot_slice_diff): normal or along-transect variables require point0 and point1 to be specified.'
sys.exit()
# Read variables and make plots
if var == 'temp':
temp_1, temp_2 = read_and_mask_both('THETA')
slice_plot_diff(temp_1, temp_2, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in temperature ('+deg_string+'C)', date_string=date_string, fig_name=fig_name)
elif var == 'salt':
salt_1, salt_2 = read_and_mask_both('SALT')
slice_plot_diff(salt_1, salt_2, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in salinity (psu)', date_string=date_string, fig_name=fig_name)
elif var == 'tminustf':
tmtf_1, tmtf_2 = read_and_mask_both('tminustf')
slice_plot_diff(tmtf_1, tmtf_2, grid, lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in difference from in-situ freezing point ('+deg_string+')', date_string=date_string, fig_name=fig_name)
elif var == 'rho':
rho_1, rho_2 = read_and_mask_both('rho')
slice_plot_diff(rho_1, rho_2, 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'Change in density (kg/m$^3$)', date_string=date_string, fig_name=fig_name)
elif var == 'u':
u_1, u_2 = read_and_mask_both('UVEL', gtype='u')
slice_plot_diff(u_1, u_2, grid, gtype='u', lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in zonal velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'v':
v_1, v_2 = read_and_mask_both('VVEL', gtype='v')
slice_plot_diff(v_1, v_2, grid, gtype='v', lon0=lon0, lat0=lat0, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in meridional velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'vnorm':
vnorm_1, vnorm_2 = read_and_mask_both(var)
slice_plot_diff(vnorm_1, vnorm_2, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in normal velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'valong':
valong_1, valong_2 = read_and_mask_both(var)
slice_plot_diff(valong_1, valong_2, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title='Change in along-transect velocity (m/s)', date_string=date_string, fig_name=fig_name)
elif var == 'tadv_along':
tadv_along_1, tadv_along_2 = read_and_mask_both(var)
slice_plot_diff(tadv_along_1, tadv_along_2, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title=r'Change in along-transect advective heat transport (Km$^3$/s)', date_string=date_string, fig_name=fig_name)
elif var == 'tdif_along':
tdif_along_1, tdif_along_2 = read_and_mask_both(var)
slice_plot_diff(tdif_along_1, tdif_along_2, grid, point0=point0, point1=point1, hmin=hmin, hmax=hmax, zmin=zmin, zmax=zmax, vmin=vmin, vmax=vmax, contours=contours, title=r'Change in along-transect diffusive heat transport (Km$^3$/s)', date_string=date_string, fig_name=fig_name)
else:
print 'Error (read_plot_slice_diff): variable key ' + str(var) + ' does not exist'
sys.exit()
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 ts_distribution_plot(file_path,
option='fris',
grid=None,
time_index=None,
t_start=None,
t_end=None,
time_average=False,
second_file_path=None,
tmin=None,
tmax=None,
smin=None,
smax=None,
num_bins=1000,
date_string=None,
figsize=(8, 6),
fig_name=None):
# 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)
# Quick inner function to read data (THETA or SALT)
def read_data(var_name):
# First choose the right file
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path)
else:
file_path_use = file_path
data = read_netcdf(file_path_use,
var_name,
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average)
return data
# Call this function for each variable
temp = read_data('THETA')
salt = read_data('SALT')
# Select the points we care about
if option == 'fris':
# Select all points in the FRIS cavity
loc_index = (grid.hfac > 0) * xy_to_xyz(grid.fris_mask, grid)
elif option == 'cavities':
# Select all points in ice shelf cavities
loc_index = (grid.hfac > 0) * xy_to_xyz(grid.ice_mask, grid)
elif option == 'all':
# Select all unmasked points
loc_index = grid.hfac > 0
else:
print 'Error (plot_misc): invalid option ' + option
sys.exit()
# Inner function to set up bins for a given variable (temp or salt)
def set_bins(data):
# Find the bounds on the data at the points we care about
vmin = np.amin(data[loc_index])
vmax = np.amax(data[loc_index])
# Choose a small epsilon to add/subtract from the boundaries
# This way nothing will be at the edge of a beginning/end bin
eps = (vmax - vmin) * 1e-3
# Calculate boundaries of bins
bins = np.linspace(vmin - eps, vmax + eps, num=num_bins)
# Now calculate the centres of bins for plotting
centres = 0.5 * (bins[:-1] + bins[1:])
return bins, centres
# Call this function for each variable
temp_bins, temp_centres = set_bins(temp)
salt_bins, salt_centres = set_bins(salt)
# Now set up a 2D array to increment with volume of water masses
volume = np.zeros([temp_centres.size, salt_centres.size])
# Loop over all cells to increment volume
# This can't really be vectorised unfortunately
for i in range(grid.nx):
for j in range(grid.ny):
if option == 'fris' and not grid.fris_mask[j, i]:
# Disregard all points not in FRIS cavity
continue
if option == 'cavities' and not grid.ice_mask[j, i]:
# Disregard all points not in ice shelf cavities
continue
for k in range(grid.nz):
if grid.hfac[k, j, i] == 0:
# Disregard all masked points
continue
# If we're still here, it's a point we care about
# Figure out which bins it falls into
temp_index = np.nonzero(temp_bins > temp[k, j, i])[0][0] - 1
salt_index = np.nonzero(salt_bins > salt[k, j, i])[0][0] - 1
# Increment volume array
volume[temp_index, salt_index] += grid.dV[k, j, i]
# Mask bins with zero volume
volume = np.ma.masked_where(volume == 0, volume)
# Find the volume bounds for plotting
min_vol = np.log(np.amin(volume))
max_vol = np.log(np.amax(volume))
# Calculate the surface freezing point for plotting
tfreeze_sfc = tfreeze(salt_centres, 0)
# Choose the plotting bounds if not set
if tmin is None:
tmin = temp_bins[0]
if tmax is None:
tmax = temp_bins[-1]
if smin is None:
smin = salt_bins[0]
if smax is None:
smax = salt_bins[-1]
# Construct the title
title = 'Water masses'
if option == 'fris':
title += ' in FRIS cavity'
elif option == 'cavities':
title += ' in ice shelf cavities'
if date_string != '':
title += ', ' + date_string
# Plot
fig, ax = plt.subplots(figsize=figsize)
# Use a log scale for visibility
img = plt.pcolor(salt_centres,
temp_centres,
np.log(volume),
vmin=min_vol,
vmax=max_vol)
# Add the surface freezing point
plt.plot(salt_centres,
tfreeze_sfc,
color='black',
linestyle='dashed',
linewidth=2)
ax.grid(True)
ax.set_xlim([smin, smax])
ax.set_ylim([tmin, tmax])
plt.xlabel('Salinity (psu)')
plt.ylabel('Temperature (' + deg_string + 'C)')
plt.colorbar(img)
plt.text(.9,
.6,
'log of volume',
ha='center',
rotation=-90,
transform=fig.transFigure)
plt.title(title)
finished_plot(fig, fig_name=fig_name)
def ts_distribution_plot(file_path,
region='all',
grid=None,
time_index=None,
t_start=None,
t_end=None,
time_average=False,
second_file_path=None,
tmin=None,
tmax=None,
smin=None,
smax=None,
num_bins=1000,
date_string=None,
figsize=(8, 6),
fig_name=None):
# 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)
# Quick inner function to read data (THETA or SALT)
def read_data(var_name):
# First choose the right file
if second_file_path is not None:
file_path_use = find_variable(file_path, second_file_path)
else:
file_path_use = file_path
data = read_netcdf(file_path_use,
var_name,
time_index=time_index,
t_start=t_start,
t_end=t_end,
time_average=time_average)
return data
# Call this function for each variable
temp = read_data('THETA')
salt = read_data('SALT')
if region == 'all':
mask = grid.hfac > 0
elif region == 'cavities':
mask = grid.ice_mask
else:
mask = grid.get_region_mask(region)
# Make the bins
volume, temp_centres, salt_centres, temp_edges, salt_edges = ts_binning(
temp, salt, grid, mask, num_bins=num_bins)
# Find the volume bounds for plotting
min_vol = np.log(np.amin(volume))
max_vol = np.log(np.amax(volume))
# Calculate the surface freezing point for plotting
tfreeze_sfc = tfreeze(salt_centres, 0)
# Choose the plotting bounds if not set
if tmin is None:
tmin = temp_bins[0]
if tmax is None:
tmax = temp_bins[-1]
if smin is None:
smin = salt_bins[0]
if smax is None:
smax = salt_bins[-1]
# Construct the title
title = 'Water masses'
if region == 'all':
pass
elif region == 'cavities':
title += ' in ice shelf cavities'
elif region.endswith('cavity'):
title += ' in ' + region_names[region[:region.index('_cavity')]]
else:
title += ' in ' + region_names[region]
if date_string != '':
title += ', ' + date_string
# Plot
fig, ax = plt.subplots(figsize=figsize)
# Use a log scale for visibility
img = plt.pcolor(salt_centres,
temp_centres,
np.log(volume),
vmin=min_vol,
vmax=max_vol)
# Add the surface freezing point
plt.plot(salt_centres,
tfreeze_sfc,
color='black',
linestyle='dashed',
linewidth=2)
ax.grid(True)
ax.set_xlim([smin, smax])
ax.set_ylim([tmin, tmax])
plt.xlabel('Salinity (psu)')
plt.ylabel('Temperature (' + deg_string + 'C)')
plt.colorbar(img)
plt.text(.9,
.6,
'log of volume',
ha='center',
rotation=-90,
transform=fig.transFigure)
plt.title(title)
finished_plot(fig, fig_name=fig_name)