def P_carbon(in_dict):
# START
fig = plt.figure(figsize=figsize)
ds = nc.Dataset(in_dict['fn'])
vlims = in_dict['vlims'].copy()
out_dict['vlims'] = vlims
# PLOT CODE
# panel 1
t_str = 'Surface TIC'
ax = fig.add_subplot(121)
vn = 'TIC'
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap='YlOrBr')
fig.colorbar(cs)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
pfun.add_info(ax, in_dict['fn'])
pfun.add_windstress_flower(ax, ds)
# panel 2
t_str = 'Surface Alkalinity'
ax = fig.add_subplot(122)
vn = 'alkalinity'
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap='RdYlGn')
fig.colorbar(cs)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
pfun.add_velocity_vectors(ax, ds, in_dict['fn'])
# FINISH
ds.close()
if len(in_dict['fn_out']) > 0:
plt.savefig(in_dict['fn_out'])
plt.close()
else:
plt.show()
return out_dict
plt.rc('font', size=fs)
plt.close('all')
for add_stations in [True, False]:
fig = plt.figure(figsize=(16,11))
# -------------- FULL MAP -----------------------------------------------
ax = fig.add_subplot(121)
cs = ax.pcolormesh(lon[6:-6,6:],lat[6:-6,6:],v[6:-6,6:], cmap=cmap, vmin=vmin, vmax=vmax)
nudge_alpha = .1
ax.pcolormesh(lon[:,:6],lat[:,:6],v[:,:6], cmap=cmap, vmin=vmin, vmax=vmax, alpha=nudge_alpha)
ax.pcolormesh(lon[:6,:],lat[:6,:],v[:6,:], cmap=cmap, vmin=vmin, vmax=vmax, alpha=nudge_alpha)
ax.pcolormesh(lon[-6:,:],lat[-6:,:],v[-6:,:], cmap=cmap, vmin=vmin, vmax=vmax, alpha=nudge_alpha)
pfun.add_bathy_contours(ax, ds, txt=False)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
if add_stations:
add_sta_loc(ax, moor_df, ctd_df, tide_df, do_leg=True)
# Inset colorbar
from mpl_toolkits.axes_grid1.inset_locator import inset_axes
cbaxes = inset_axes(ax, width="4%", height="40%", loc='lower left', borderpad=3)
cb = fig.colorbar(cs, cax=cbaxes, orientation='vertical')
ax.text(.08, .53, r'SST $[^\circ C]$', transform=ax.transAxes)
ax.text(.08, .03, dstr, size=fs2, transform=ax.transAxes, style='italic')
m_list.append(m)
for inname in m_list:
out_fn = outdir + 'odell_5day_' + inname.split('_')[-2] + '.png'
print('Printing ' + out_fn)
P, G, S, PLdir = pickle.load(open(indir + inname, 'rb'))
NT, NP = P['lon'].shape
lonp = G['lon_psi']
latp = G['lat_psi']
aa = [lonp.min(), lonp.max(), latp.min(), latp.max()]
# PLOTTING
plt.close()
fig = plt.figure(figsize=(12, 12))
ax = fig.add_subplot(111)
pfun.add_coast(ax)
pfun.add_bathy_contours(ax, G, txt=True)
ax.axis(aa)
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.text(.06,
.04,
' '.join(inname.split('_')),
verticalalignment='bottom',
transform=ax.transAxes,
rotation='vertical')
ax.set_title('Start ' + inname.split('_')[-2])
# add the tracks
ax.plot(P['lon'], P['lat'], '-k', alpha=0.1)
beach_mask = P['u'][-1, :] == 0
ax.plot(P['lon'][:, beach_mask],
def P_nest_plot(in_dict):
# plots a field nested inside the corresponding HYCOM field
# - currently only works for salt and temp -
# START
fig = plt.figure(figsize=figsize)
ds = nc.Dataset(in_dict['fn'])
vlims = in_dict['vlims'].copy()
out_dict['vlims'] = vlims
# PLOT CODE
# ** choose the variable to plot **
which_var = 'temp'
# need to get Ldir, which means unpacking gtagex
fn = in_dict['fn']
gtagex = fn.split('/')[-3]
gtx_list = gtagex.split('_')
import Lfun
Ldir = Lfun.Lstart(gtx_list[0], gtx_list[1])
# Get HYCOM field
hyvar_dict = {'temp': 't3d', 'salt': 's3d'}
hvar = hyvar_dict[which_var]
f_string = fn.split('/')[-2]
fnhy = (Ldir['LOo'] + Ldir['gtag'] + '/' + f_string + '/ocn/Data/' + hvar +
'.nc')
ds = nc.Dataset(fnhy)
lon = ds.variables['lon'][:]
lat = ds.variables['lat'][:]
z = ds.variables['z'][:]
# make sure zlev is in the HYCOM z
zlev = zfun.find_nearest(z, in_dict['z_level'])
nz = list(z).index(zlev)
laym_hy = ds.variables[hvar + '_filt'][0, nz, :, :].squeeze()
vlims = pfun.auto_lims(laym_hy)
ds.close()
aa = [lon.min(), lon.max(), lat.min(), lat.max()]
# Get ROMS field
ds = nc.Dataset(fn)
zfull = pfun.get_zfull(ds, fn, 'rho')
laym = pfun.get_laym(ds, zfull, ds['mask_rho'][:], which_var, zlev)
# PLOTTING
cmap = plt.get_cmap(name='gist_ncar')
plt.close()
fig, axes = plt.subplots(nrows=1, ncols=2, figsize=figsize, squeeze=False)
# panel 1
ax = axes[0, 0]
ax.set_title('HYCOM: z=' + str(zlev) + 'm, var=' + which_var)
cs = ax.pcolormesh(lon,
lat,
laym_hy,
vmin=vlims[0],
vmax=vlims[1],
cmap=cmap)
ax.axis(aa)
fig.colorbar(cs, ax=ax)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
# panel 2
ax = axes[0, 1]
ax.set_title('HYCOM + ROMS')
cs = ax.pcolormesh(lon,
lat,
laym_hy,
vmin=vlims[0],
vmax=vlims[1],
cmap=cmap)
ax.axis(aa)
laymd = laym.data
laymd[laym.mask] = 1e6
ax.pcolormesh(ds['lon_psi'][:],
ds['lat_psi'][:],
laymd[1:-1, 1:-1],
vmin=vlims[0],
vmax=vlims[1],
cmap=cmap)
fig.colorbar(cs, ax=ax)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
pfun.dar(ax)
ax.set_xlabel('Longitude')
# FINISH
ds.close()
if len(in_dict['fn_out']) > 0:
plt.savefig(in_dict['fn_out'])
plt.close()
else:
plt.show()
return out_dict
def P_basic(in_dict):
# This creates, and optionally saves, a basic plot of surface fields
# from a ROMS history file.
# INPUT a dict containing:
# fn: text string with the full path name of the history file to plot
# fn_out: text string with full path of output file name
# in_dict: a tuple with optional information to pass to the plot
# OUTPUT: either a screen image or a graphics file, and a dict of other
# information such as axis limits.
# START
fig = plt.figure(figsize=figsize)
ds = nc.Dataset(in_dict['fn'])
vlims = in_dict['vlims'].copy()
out_dict['vlims'] = vlims
# PLOT CODE
# panel 1
t_str = 'Surface Salinity'
ax = fig.add_subplot(121)
vn = 'salt'
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap='rainbow')
fig.colorbar(cs)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_title(t_str)
pfun.add_info(ax, in_dict['fn'])
pfun.add_windstress_flower(ax, ds)
# panel 2
t_str = 'Surface Temperature'
ax = fig.add_subplot(122)
vn = 'temp'
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap='bwr')
fig.colorbar(cs)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
pfun.add_velocity_vectors(ax, ds, in_dict['fn'])
# FINISH
ds.close()
if len(in_dict['fn_out']) > 0:
plt.savefig(in_dict['fn_out'])
plt.close()
else:
plt.show()
return out_dict
def P_layer(in_dict):
# START
fig = plt.figure(figsize=figsize)
ds = nc.Dataset(in_dict['fn'])
vlims = in_dict['vlims'].copy()
out_dict['vlims'] = vlims
# PLOT CODE
zfull = pfun.get_zfull(ds, in_dict['fn'], 'rho')
# panel 1
t_str = 'Salinity'
ax = fig.add_subplot(121)
vn = 'salt'
laym = pfun.get_laym(ds, zfull, ds['mask_rho'][:], vn, in_dict['z_level'])
if len(vlims[vn]) == 0:
vlims[vn] = pfun.auto_lims(laym)
out_dict['vlims'][vn] = vlims[vn]
cs = ax.pcolormesh(ds['lon_psi'][:],
ds['lat_psi'][:],
laym[1:-1, 1:-1],
vmin=vlims[vn][0],
vmax=vlims[vn][1],
cmap='rainbow')
cb = fig.colorbar(cs)
cb.formatter.set_useOffset(False)
cb.update_ticks()
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
ax.set_title(t_str + ' on Z = ' + str(in_dict['z_level']) + ' m')
pfun.add_info(ax, in_dict['fn'])
pfun.add_windstress_flower(ax, ds)
# panel 2
t_str = 'Temperature'
ax = fig.add_subplot(122)
vn = 'temp'
laym = pfun.get_laym(ds, zfull, ds['mask_rho'][:], vn, in_dict['z_level'])
if len(vlims[vn]) == 0:
vlims[vn] = pfun.auto_lims(laym)
out_dict['vlims'][vn] = vlims[vn]
cs = ax.pcolormesh(ds['lon_psi'][:],
ds['lat_psi'][:],
laym[1:-1, 1:-1],
vmin=vlims[vn][0],
vmax=vlims[vn][1],
cmap='bwr')
cb = fig.colorbar(cs)
cb.formatter.set_useOffset(False)
cb.update_ticks()
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_xlabel('Longitude')
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
# FINISH
ds.close()
if len(in_dict['fn_out']) > 0:
plt.savefig(in_dict['fn_out'])
plt.close()
else:
plt.show()
return out_dict
def P_bio(in_dict):
# START
ds = nc.Dataset(in_dict['fn'])
vlims = in_dict['vlims'].copy()
out_dict['vlims'] = vlims
vn_list = ['NO3', 'phytoplankton', 'zooplankton', 'oxygen']
cmap_list = ['Oranges', 'Greens', 'BuPu', 'Spectral']
cmap_dict = dict(zip(vn_list, cmap_list))
NP = len(vn_list)
if False:
NR = np.maximum(1, np.ceil(np.sqrt(NP)).astype(int))
NC = np.ceil(np.sqrt(NP)).astype(int)
figsize = (16, 16)
else:
NR = 1
NC = NP
figsize = (23, 7)
fig, axes = plt.subplots(nrows=NR,
ncols=NC,
figsize=figsize,
squeeze=False)
cc = 0
for vn in vn_list:
ir = int(np.floor(cc / NC))
ic = int(cc - NC * ir)
# PLOT CODE
ax = axes[ir, ic]
t_str = vn
try:
vlims[vn]
except KeyError:
vlims[vn] = ()
if vn == 'oxygen':
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap=cmap_dict[vn],
slev=0)
ax.text(.95,
.04,
'BOTTOM',
horizontalalignment='right',
transform=ax.transAxes)
else:
cs, out_dict['vlims'][vn] = pfun.add_map_field(ax,
ds,
vn,
vlims=vlims[vn],
cmap=cmap_dict[vn])
fig.colorbar(cs, ax=ax)
pfun.add_bathy_contours(ax, ds)
pfun.add_coast(ax)
ax.axis(pfun.get_aa(ds))
pfun.dar(ax)
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
if ir == NR - 1:
ax.set_xlabel('Longitude')
if ic == 0:
ax.set_ylabel('Latitude')
ax.set_title(t_str + ' (' + pfun.get_units(ds, vn) + ')')
if cc == 0:
pfun.add_info(ax, in_dict['fn'])
cc += 1
# FINISH
ds.close()
if len(in_dict['fn_out']) > 0:
plt.savefig(in_dict['fn_out'])
plt.close()
else:
plt.show()
return out_dict