def plot_depth(self, figname=None, show=False, imshow=False):
"""
plot the depth
"""
from matplotlib import pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
depth = self.get_depths()
mindep = depth.min()
maxdep = depth.max()
print("\nMin depth (m) = " + str(mindep))
print("Max depth (m) = " + str(maxdep) + "\n")
if imshow:
IM = ax.imshow(depth.transpose(), origin='lower')
else:
# need lon,lat
qlon, qlat = self.get_corners()
# make basemap for plotting
import fns_plotting as Fplt
bbox = [qlon.min(), qlat.min(), qlon.max(), qlat.max()]
bmap = Fplt.start_map(bbox)
IM = bmap.pcolor(qlon,
qlat,
depth,
latlon=True,
ax=ax,
vmin=mindep,
vmax=maxdep)
Fplt.finish_map(bmap, do_fill=False)
# colorbar
cbar = fig.colorbar(IM)
cbar.set_label("Depth, m", rotation=270, labelpad=20, fontsize=16)
if figname is not None:
print("\nSaving " + figname + "\n")
fig.savefig(figname)
else:
show = True
if show:
plt.show(fig)
ax.cla()
plt.close(fig)
return
def plot_field(grid, field, bmap):
from matplotlib import pyplot
# get corners - better for pcolor plots
lon = grid.get_coords(0, ESMF.StaggerLoc.CORNER)
lat = grid.get_coords(1, ESMF.StaggerLoc.CORNER)
# data
V = field.data[:, :]
#plot
pobj = FP.plot_object()
PC = bmap.pcolor(lon, lat, V, latlon=True, ax=pobj.ax)
pobj.fig.colorbar(PC)
FP.finish_map(bmap)
plt.show(pobj.fig)
return pobj
lstil = ['-', '--']
for Poly in Polys:
x, y = np.array(Poly.xy_coords).transpose()
shp = SHgeom.Polygon(Poly.xy_coords)
if shp.is_valid:
bmap.plot(x, y, 'k', linewidth=2, ax=ax1)
else:
bmap.plot(x, y, 'c', linewidth=2, ax=ax1)
# MIZ line
x, y = np.array(Lino_ref.xy_coords).transpose()
bmap.plot(x, y, linestyle=lstil[Lino_ref.func_val], ax=ax1)
bmap.plot(x[:1], y[:1], 'v', ax=ax1) # 1st point
# ice edges
for Lino in Linos:
x, y = np.array(Lino.xy_coords).transpose()
bmap.plot(x, y, linestyle=lstil[Lino.func_val], ax=ax1)
bmap.plot(x[:1], y[:1], '^', ax=ax1) # 1st point
Fplt.finish_map(bmap, ax=ax1)
if show:
plt.show(fig)
else:
figname = figdir + '/' + cdate + "_polys.png"
print('>' + figname)
fig.savefig(figname)
ax1.cla()
plt.close(fig)
for vbl in ['depth','landmask']:
if vbl=='depth':
PC = bmap.pcolor(qlon,qlat,depth,latlon=True,ax=po.ax)
cols = ['b']
else:
PC = bmap.pcolor(qlon,qlat,landmask,latlon=True,ax=po.ax)
cols = ['c']
cb = po.fig.colorbar(mappable=PC,cax=cax)
# plot original selection
vertices.append(vertices[0])
vlon,vlat = np.array(vertices).transpose()
bmap.plot(vlon,vlat,'m',linewidth=4,ax=po.ax,latlon=True)
if 0:
# finish with coast etc
Fplt.finish_map(bmap,ax=po.ax)
# depth=0 contour
bmap.contour(plon,plat,depth,colors=cols,linewidth=4,latlon=True,ax=po.ax,levels=[0.])
# save fig
figname = outdir+"/test_"+gridname+"_"+vbl+".png"
print('\nSaving '+figname+'\n')
po.fig.savefig(figname)
po.ax.cla()
plt.close(po.fig)
else:
# plot binary
bm.pcolor(plon, plat, B, vmin=0., vmax=1., latlon=True)
bm.colorbar()
Nconts = len(contours)
if Nconts > 0:
print('number of contours: ' + str(Nconts) + '...\n')
for n, contour in enumerate(contours):
# print('contour: '+str(n))
# print('number of points: '+str(len(contour))+'\n')
ivec = np.array(contour[:, 0], dtype=int)
jvec = np.array(contour[:, 1], dtype=int)
bm.plot(plon[ivec, jvec],
plat[ivec, jvec],
Ccol,
linewidth=1.5,
latlon=True)
plt.title(vbl)
Mplt.finish_map(bm)
if 0:
plt.show()
else:
figname = 'out/TP4test_' + vbl + '.png'
print('\nsaving to ' + figname + '...\n')
plt.savefig(figname)
plt.close()
fig.clf()
np.savez(outdir+'/thickness_anomaly_'+cdate1+'.npz',lon=olon,lat=olat,\
anomaly=hdiff.data,mask=hdiff.mask)
print('\n-------------------')
print('RMSE (m) = '+str(RMSEe))
print('Bias (m) = '+str(BIASe))
print('-------------------\n')
# mask water for plotting
hdiff.mask = np.logical_not(either_ice)
if 0:
print('Plotting weekly average')
PC = bmap.pcolor(mlon,mlat,hav_m,ax=po.ax,vmin=0,vmax=hmax,latlon=True)
if DOCB:
po.fig.colorbar(PC)
FP.finish_map(bmap,ax=po.ax)
# po.ax.set_title('Mod')
elif 0:
print('Plotting weekly average - interpolated')
PC = bmap.pcolor(olon,olat,hav_m2,ax=po.ax,vmin=0,vmax=hmax,latlon=True)
if DOCB:
po.fig.colorbar(PC)
FP.finish_map(bmap,ax=po.ax)
figname = figname.replace('.png','_interp.png')
else:
print('Plotting weekly average - anomaly')
PC = bmap.pcolor(olon,olat,hdiff,ax=po.ax,latlon=True,vmin=-1.5,vmax=1.5)
#
if DOCB:
cbar = po.fig.colorbar(PC)
cbar.set_label('Thickness anomaly, m',rotation=270,labelpad=20,fontsize=16)
