def plot_BSF(var, TorUgrid, nlevels=100, mappingtoolbox='basemap', proj='ortho', min = [], max = []):
''' uses utils_plt.emptyBasemapFig()'''
# colormap
if min == []: min = np.floor(np.nanmin(var)) # minimum value of varin
if max == []: max = np.ceil(np.nanmax(var)) # maximum value of varin
#cmap, norm = utils_plt.get_cmap(min, max, nlevels, scheme=utils_plt.get_viridis()) # viridis
cmap = utils_plt.shiftCMap(ml.cm.seismic, midpoint=1-max/(max-min), name='shifted') # shifted blue white red
# add cyclic border (to prevent gap in pcolor plot)
var = utils_conv.add_cyclic(var)
# choose U or T grid
if TorUgrid == 'U':
xvar = var.ULONG.values
yvar = var.ULAT.values
elif TorUgrid == 'T':
xvar = var.TLONG.values
yvar = var.TLAT.values
# draw plot in new figure
if mappingtoolbox == 'basemap':
fig, map = utils_plt.emptyBasemapFig(proj)
c1 = map.pcolor(xvar,yvar,var.values,latlon=True, cmap=cmap, rasterized=True)
map.colorbar()
elif mappingtoolbox == 'cartopy':
fig, map = True, True#TODO
return(fig, map)
def plot_BSF(var,
TorUgrid,
nlevels=100,
mappingtoolbox='basemap',
proj='ortho',
min=[],
max=[]):
''' uses utils_plt.emptyBasemapFig()'''
# colormap
if min == []: min = np.floor(np.nanmin(var)) # minimum value of varin
if max == []: max = np.ceil(np.nanmax(var)) # maximum value of varin
#cmap, norm = utils_plt.get_cmap(min, max, nlevels, scheme=utils_plt.get_viridis()) # viridis
cmap = utils_plt.shiftCMap(ml.cm.seismic,
midpoint=1 - max / (max - min),
name='shifted') # shifted blue white red
# add cyclic border (to prevent gap in pcolor plot)
var = utils_conv.add_cyclic(var)
# choose U or T grid
if TorUgrid == 'U':
xvar = var.ULONG.values
yvar = var.ULAT.values
elif TorUgrid == 'T':
xvar = var.TLONG.values
yvar = var.TLAT.values
# draw plot in new figure
if mappingtoolbox == 'basemap':
fig, map = utils_plt.emptyBasemapFig(proj)
c1 = map.pcolor(xvar,
yvar,
var.values,
latlon=True,
cmap=cmap,
rasterized=True)
map.colorbar()
elif mappingtoolbox == 'cartopy':
fig, map = True, True #TODO
return (fig, map)
# -----------------------------------------------------------------------------
# horizontal plot of Temperatures columnwise integrated over depth/density axis
# -----------------------------------------------------------------------------
# - TEMPERATURE
plt.figure()
T_int = utils_ana.integrate_along_dens(T, ncdat.dz)
#T_dens_int = utils_ana.integrate_along_dens(T_dens[1:-1], ddb)
T_dens_int = utils_ana.integrate_along_dens(T_dens, vol_dbs_col)
min_T = np.nanmin([T_int])
max_T = np.nanmax([T_int])
cmap_T = utils_plt.shiftCMap(ml.cm.seismic, midpoint = 1-max_T/(max_T-min_T), name='shifted')
min_T_dens = np.nanmin([T_dens_int])
max_T_dens = np.nanmax([T_dens_int])
cmap_T_dens = utils_plt.shiftCMap(ml.cm.seismic, midpoint = 1-max_T_dens/(max_T_dens-min_T_dens), name='shifted')
# - plotting
plt.suptitle('Values integrated over columns')
plt.subplot(1,2,1)
plt.imshow(utils_conv.rollATL(T_int), cmap=cmap_T)
plt.colorbar()
#plt.contour(utils_conv.rollATL(T_int), cmap='Reds', levels=np.linspace(-5, 30, 5))
plt.contour(utils_conv.rollATL(ncdat.HT), levels=np.linspace(0,560000,2), cmap='hot') # draw continents
plt.title('Temperature on depth axis')
ax = plt.gca(); ax.invert_yaxis()
print(np.nanmin(T_int), np.nanmax(T_int))
plt.legend(loc='best')
# -----------------------------------------------------------------------------
# horizontal plot of Temperatures columnwise integrated over depth/density axis
# -----------------------------------------------------------------------------
# - TEMPERATURE
plt.figure()
T_int = utils_ana.integrate_along_dens(T, ncdat.dz)
#T_dens_int = utils_ana.integrate_along_dens(T_dens[1:-1], ddb)
T_dens_int = utils_ana.integrate_along_dens(T_dens, vol_dbs_col)
min_T = np.nanmin([T_int])
max_T = np.nanmax([T_int])
cmap_T = utils_plt.shiftCMap(ml.cm.seismic,
midpoint=1 - max_T / (max_T - min_T),
name='shifted')
min_T_dens = np.nanmin([T_dens_int])
max_T_dens = np.nanmax([T_dens_int])
cmap_T_dens = utils_plt.shiftCMap(ml.cm.seismic,
midpoint=1 - max_T_dens /
(max_T_dens - min_T_dens),
name='shifted')
# - plotting
plt.suptitle('Values integrated over columns')
plt.subplot(1, 2, 1)
plt.imshow(utils_conv.rollATL(T_int), cmap=cmap_T)
plt.colorbar()
#plt.contour(utils_conv.rollATL(T_int), cmap='Reds', levels=np.linspace(-5, 30, 5))
plt.contour(utils_conv.rollATL(ncdat.HT),