def thetaeq(self, filled=True, cmap=None, **kwargs):
self.initialize_plot()
self.level = kwargs['level']*100
clevels = kwargs['clevels']
t_arrays = read_files(self, 'temperature') # [C]
q_arrays = read_files(self, 'sphum') # [kg/kg]
rh_arrays = read_files(self, 'relhumid')
press = np.zeros(rh_arrays[0].shape)+kwargs['level'] # [hPa]
X, Y = np.meshgrid(self.lons, self.lats)
self.series['thetaeq'] = []
for i in range(len(self.dates)):
mixr = thermo.mixing_ratio(specific_humidity=q_arrays[i])
theta = thermo.theta_equiv2(C=t_arrays[i], hPa=press,
mixing_ratio=mixr, relh=rh_arrays[i])
val = get_value_at(-123., 38.5, theta, self) # closest to BBY
self.series['thetaeq'].append(val)
if filled:
cf = self.axes[i].contourf(X, Y, theta, clevels, cmap=cmap)
try:
self.axes[i].cax.colorbar(cf, ticks=clevels[::4])
except AttributeError:
add_colorbar(self.axes[i], cf)
else:
cs = self.axes[i].contour(X, Y, theta, clevels, colors='r',
linewidths=0.6)
clabels = self.axes[i].clabel(cs, clevels[::5],
fontweight='bold',
fontsize=10,
fmt='%1.0f')
[txt.set_color('r') for txt in clabels]
set_limits(self, i)
self.add_date(i)
txt = 'Equivalent Potential Temperature [K] at {} hPa\n'
self.title += txt.format(str(self.level/100))
def theta(self, **kwargs):
self.initialize_plot()
self.level = kwargs['level']*100
cmap = kwargs['cmap']
t_arrays = read_files(self, 'temperature') # [C]
q_arrays = read_files(self, 'sphum') # [kg/kg]
X, Y = np.meshgrid(self.lons, self.lats)
clevels = kwargs['clevels']
self.series['theta'] = []
for i in range(len(self.dates)):
mixr = thermo.mixing_ratio(specific_humidity=q_arrays[i])
press = np.zeros(mixr.shape)+kwargs['level'] # [hPa]
theta = thermo.theta2(C=t_arrays[i], hPa=press, mixing_ratio=mixr)
val = get_value_at(-123., 38.5, theta, self) # closest to BBY
self.series['theta'].append(val)
cf = self.axes[i].contourf(X, Y, theta, clevels, cmap=cmap)
self.axes[i].cax.colorbar(cf, ticks=clevels[::4])
set_limits(self, i)
self.add_date(i)
self.l1 = 'Potential Temperature [K] at ' + \
str(self.level/100) + ' hPa'
def cross_section(self, **kwargs):
field = kwargs['field']
clevels = kwargs['clevels']
cmap = kwargs['cmap']
self.orientation = kwargs['orientation']
self.initialize_plot()
self.horizontal = False
t_arrays = read_files(self, 'temperature') # [C]
q_arrays = read_files(self, 'sphum') # [kg/kg]
rh_arrays = read_files(self, 'relhumid')
isob = get_vertical_array(self)/100. # to [hPa]
z, n = t_arrays[0].shape
press = np.tile(np.array([isob]).transpose(), (1, n))
X, Y = np.meshgrid(range(len(self.lons)), range(len(isob)))
if len(clevels) == 2:
foo = clevels[0]
boundsc = clevels[1]
clevels = foo
''' make a color map of fixed colors '''
vmin = min(clevels)
vmax = max(clevels)
bounds = clevels
snsmap = sns.color_palette(cmap, n_colors=len(bounds))
cmap = colors.ListedColormap(snsmap)
norm = colors.BoundaryNorm(bounds, cmap.N)
plot_field = []
if field == 'thetaeq':
for i in range(6):
mixr = thermo.mixing_ratio(specific_humidity=q_arrays[i])
theta = thermo.theta_equiv2(
C=t_arrays[i], hPa=press,
mixing_ratio=mixr, relh=rh_arrays[i])
theta[theta > 320] = np.nan
plot_field.append(theta)
plot_fieldc = plot_field
cboundaries = bounds
cticks = bounds
boundsc = bounds
ti = ' - Equivalent potential temperature [K]'
elif field == 'q':
for i in range(6):
q = q_arrays[i]
plot_field.append(q*1000.) # [g kg-1]
plot_fieldc = plot_field
cboundaries = bounds
cticks = bounds
boundsc = bounds
ti = ' - Specific humidity [g kg-1]'
elif field == 'U':
plot_field = read_files(self, 'u')
plot_fieldc = plot_field
cboundaries = bounds
cticks = bounds
boundsc = bounds
ti = ' - Wind speed zonal component [m s-1]'
elif field == 'V':
plot_field = read_files(self, 'v')
plot_fieldc = plot_field
cboundaries = bounds
cticks = bounds
boundsc = bounds
ti = ' - Wind speed meridional component [m s-1]'
elif field == 'thetaeq+U':
for i in range(6):
mixr = thermo.mixing_ratio(specific_humidity=q_arrays[i])
theta = thermo.theta_equiv2(
C=t_arrays[i], hPa=press,
mixing_ratio=mixr, relh=rh_arrays[i])
theta[theta > 320] = np.nan
plot_field.append(theta)
plot_fieldc = read_files(self, 'u')
cboundaries = bounds
cticks = bounds
t0 = '\nEquivalent potential temperature [K] (color coded)'
t1 = '\nWind speed zonal component [m s-1] (contour lines)'
ti = t0+t1
elif field == 'thetaeq+V':
for i in range(6):
mixr = thermo.mixing_ratio(specific_humidity=q_arrays[i])
theta = thermo.theta_equiv2(
C=t_arrays[i], hPa=press,
mixing_ratio=mixr, relh=rh_arrays[i])
theta[theta > 320] = np.nan
plot_field.append(theta)
plot_fieldc = read_files(self, 'v')
cboundaries = bounds
cticks = bounds
t0 = '\nEquivalent potential temperature [K] (color coded)'
t1 = '\nWind speed meridional component [m s-1] (contour lines)'
ti = t0+t1
for i in range(6):
im = self.axes[i].imshow(plot_field[i],
interpolation='none',
vmin=vmin,
vmax=vmax,
cmap=cmap,
norm=norm)
self.axes[i].cax.colorbar(im,
cmap=cmap, norm=norm,
boundaries=cboundaries,
ticks=cticks[::4])
xticks = self.lons[::10]
xticklabs = [str(x) for x in xticks]
xticklabs.reverse()
xticklabs.append(' ')
xticklabs.reverse()
self.axes[i].set_xticklabels(xticklabs)
yidx = np.where(isob == self.zboundary)[0]
self.axes[i].set_ylim([36, yidx])
yticks = self.axes[i].get_yticks()
isob_yticks = [isob[y] for y in yticks]
if i == 0:
yticklabs = [str(x) for x in isob_yticks]
else:
yticklabs = [' ' for x in isob_yticks]
self.axes[i].set_yticklabels(yticklabs)
''' add contour lines '''
cs = self.axes[i].contour(X, Y, plot_fieldc[i],
origin='lower', levels=boundsc,
colors='k', linewidths=0.5)
if field in ['thetaeq+U', 'thetaeq+V']:
self.axes[i].clabel(cs, boundsc,
fmt='%1.0f',
fontsize=10)
self.axes[i].set_ylim([36, yidx])
''' add vertical line '''
xidx = np.where(self.lons == -123.0)
self.axes[i].axvline(xidx, color='k', linestyle=':')
''' add date to subplot '''
self.add_date(i)
''' add axis label '''
self.axes[i].set_xlabel('Longitude [deg]')
if i == 0:
self.axes[i].set_ylabel('Pressure level [hPa]')
t1 = 'Climate Forecast System Reanalysis'+ti
if self.orientation[0] == 'zonal':
t2 = '\nLatitude: ' + str(self.orientation[1])
elif self.orientation[0] == 'meridional':
t2 = '\nLongitude: ' + str(self.orientation[1])
plt.suptitle(t1+t2)
