def cold_pool_strength(self,
time,
wrf_sd=0,
wrf_nc=0,
out_sd=0,
swath_width=100,
dom=1,
twoplot=0,
fig=0,
axes=0,
dz=0):
"""
Pick A, B points on sim ref overlay
This sets the angle between north and line AB
Also sets the length in along-line direction
For every gridpt along line AB:
Locate gust front via shear
Starting at front, do 3-grid-pt-average in line-normal
direction
time : time (tuple or datenum) to plot
wrf_sd : string - subdirectory of wrfout file
wrf_nc : filename of wrf file requested.
If no wrfout file is explicitly specified, the
netCDF file in that folder is chosen if unambiguous.
out_sd : subdirectory of output .png.
swath_width : length in gridpoints in cross-section-normal direction
dom : domain number
return2 : return two figures. cold pool strength and cref/cross-section.
axes : if two-length tuple, this is the first and second axes for
cross-section/cref and cold pool strength, respectively
dz : plot height of cold pool only.
"""
# Initialise
self.W = self.get_wrfout(wrf_sd, wrf_nc, dom=dom)
outpath = self.get_outpath(out_sd)
# keyword arguments for plots
line_kwargs = {}
cps_kwargs = {}
# Create two-panel figure
if twoplot:
P2 = Figure(self.C, self.W, plotn=(1, 2))
line_kwargs['ax'] = P2.ax.flat[0]
line_kwargs['fig'] = P2.fig
P2.ax.flat[0].set_size_inches(3, 3)
cps_kwargs['ax'] = P2.ax.flat[1]
cps_kwargs['fig'] = P2.fig
P2.ax.flat[1].set_size_inches(6, 6)
elif isinstance(axes, tuple) and len(axes) == 2:
line_kwargs['ax'] = axes[0]
line_kwargs['fig'] = fig
cps_kwargs['ax'] = axes[1]
cps_kwargs['fig'] = fig
return_ax = 1
# Plot sim ref, send basemap axis to clicker function
F = BirdsEye(self.C, self.W)
self.data = F.plot2D('cref',
time,
2000,
dom,
outpath,
save=0,
return_data=1)
C = Clicker(self.C, self.W, data=self.data, **line_kwargs)
# C.fig.tight_layout()
# Line from front to back of system
C.draw_line()
# C.draw_box()
lon0, lat0 = C.bmap(C.x0, C.y0, inverse=True)
lon1, lat1 = C.bmap(C.x1, C.y1, inverse=True)
# Pick location for environmental dpt
# C.click_x_y()
# Here, it is the end of the cross-section
lon_env, lat_env = C.bmap(C.x1, C.y1, inverse=True)
y_env, x_env, exactlat, exactlon = utils.getXY(self.W.lats1D,
self.W.lons1D, lat_env,
lon_env)
# Create the cross-section object
X = CrossSection(self.C, self.W, lat0, lon0, lat1, lon1)
# Ask user the line-normal box width (self.km)
#C.set_box_width(X)
# Compute the grid (DX x DY)
cps = self.W.cold_pool_strength(X,
time,
swath_width=swath_width,
env=(x_env, y_env),
dz=dz)
# import pdb; pdb.set_trace()
# Plot this array
CPfig = BirdsEye(self.C, self.W, **cps_kwargs)
tstr = utils.string_from_time('output', time)
if dz:
fprefix = 'ColdPoolDepth_'
else:
fprefix = 'ColdPoolStrength_'
fname = fprefix + tstr
pdb.set_trace()
# imfig,imax = plt.subplots(1)
# imax.imshow(cps)
# plt.show(imfig)
# CPfig.plot_data(cps,'contourf',outpath,fname,time,V=N.arange(5,105,5))
mplcommand = 'contour'
plotkwargs = {}
if dz:
clvs = N.arange(100, 5100, 100)
else:
clvs = N.arange(10, 85, 2.5)
if mplcommand[:7] == 'contour':
plotkwargs['levels'] = clvs
plotkwargs['cmap'] = plt.cm.ocean_r
cf2 = CPfig.plot_data(cps, mplcommand, outpath, fname, time,
**plotkwargs)
# CPfig.fig.tight_layout()
plt.close(fig)
if twoplot:
P2.save(outpath, fname + "_twopanel")
if return_ax:
return C.cf, cf2
