def plot_thsections(dbz,vvel,ht,dayt,**kwargs):
fig,ax = plt.subplots(2,1,sharex=True)
'colormap for vvel'
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
' add images and colorbar'
im0=ax[0].imshow(dbz,interpolation='none',cmap='nipy_spectral',vmin=-20,vmax=60,aspect='auto',origin='lower')
im1=ax[1].imshow(vvel,interpolation='none',cmap=shifted_cmap,vmin=-10,vmax=4,aspect='auto',origin='lower')
divider0 = make_axes_locatable(ax[0])
cax0 = divider0.append_axes("right", size="2%", pad=0.05)
cbar0 = plt.colorbar(im0, cax=cax0)
divider1 = make_axes_locatable(ax[1])
cax1 = divider1.append_axes("right", size="2%", pad=0.05)
cbar1 = plt.colorbar(im1, cax=cax1)
if 'echotop' in kwargs:
echot=kwargs['echotop']
ax[0].plot(echot,color='k')
format_yaxis(ax[0],ht)
format_yaxis(ax[1],ht)
format_xaxis(ax[1], dayt, minutes_tick=30, labels=True)
ax[1].invert_xaxis()
ax[0].set_ylabel('Hgt MSL [km]')
ax[1].set_ylabel('Hgt MSL [km]')
ax[1].set_xlabel(r'$\Leftarrow$'+' Time [UTC]')
plt.subplots_adjust(hspace=0.05)
plt.suptitle('SPROF observations. Date: '+dayt[0].strftime('%Y-%b'))
plt.draw()
def plot_thsections_single(ht, dayt, **kwargs):
matplotlib.rcParams.update({'font.size': 20})
fig, ax = plt.subplots()
str_etop = ''
if 'dbz' in kwargs:
im = ax.imshow(kwargs['dbz'],
interpolation='none',
cmap='nipy_spectral',
vmin=-30,
vmax=60,
aspect='auto',
origin='lower')
elif 'vvel' in kwargs:
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
im = ax.imshow(kwargs['vvel'],
interpolation='none',
cmap=shifted_cmap,
vmin=-10,
vmax=4,
aspect='auto',
origin='lower')
if 'echotop' in kwargs:
ax.plot(kwargs['echotop'][0], color='black')
units = r'$\mathregular{km^{-2}}$'
str_etop = 'etop_var: {:2.1f}'.format(np.nanvar(kwargs['echotop'][1]))
str_etop += units
if 'bband' in kwargs:
bbht = kwargs['bband'][0]
idx_bbht = kwargs['bband'][1]
f = interp1d(ht, range(len(ht)))
ax.plot(idx_bbht, f(bbht), marker='o', linestyle='--', color='black')
if kwargs['colorbar']:
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="2%", pad=0.)
cbar = plt.colorbar(im, cax=cax)
format_yaxis(ax, ht, toplimit=11)
format_xaxis(ax, dayt, labels=True, format='%H')
ax.invert_xaxis()
str_date = dayt[0].strftime('%Y-%b')
str_tbeg = dayt[0].strftime(' %dT%H:00') + '-'
str_tend = (dayt[-1]).strftime('%dT%H:00')
c = kwargs['case']
annot = 'Case ' + str(
c) + ' ' + str_date + str_tbeg + str_tend + ' UTC' + ' ' + str_etop
ax.text(0.02, 0.02, annot, transform=ax.transAxes, fontsize=14)
plt.subplots_adjust(top=0.98, bottom=0.05, left=0.04, right=0.91)
plt.draw()
def plot_thsections(dbz, vvel, ht, dayt, **kwargs):
fig, ax = plt.subplots(2, 1, sharex=True)
'colormap for vvel'
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
' add images and colorbar'
im0 = ax[0].imshow(dbz,
interpolation='none',
cmap='nipy_spectral',
vmin=-20,
vmax=60,
aspect='auto',
origin='lower')
im1 = ax[1].imshow(vvel,
interpolation='none',
cmap=shifted_cmap,
vmin=-10,
vmax=4,
aspect='auto',
origin='lower')
divider0 = make_axes_locatable(ax[0])
cax0 = divider0.append_axes("right", size="2%", pad=0.05)
cbar0 = plt.colorbar(im0, cax=cax0)
divider1 = make_axes_locatable(ax[1])
cax1 = divider1.append_axes("right", size="2%", pad=0.05)
cbar1 = plt.colorbar(im1, cax=cax1)
if 'echotop' in kwargs:
echot = kwargs['echotop']
ax[0].plot(echot, color='k')
format_yaxis(ax[0], ht)
format_yaxis(ax[1], ht)
format_xaxis(ax[1], dayt, minutes_tick=30, labels=True)
ax[1].invert_xaxis()
ax[0].set_ylabel('Hgt MSL [km]')
ax[1].set_ylabel('Hgt MSL [km]')
ax[1].set_xlabel(r'$\Leftarrow$' + ' Time [UTC]')
plt.subplots_adjust(hspace=0.05)
plt.suptitle('SPROF observations. Date: ' + dayt[0].strftime('%Y-%b'))
plt.draw()
def plot_thsections_single(ht,dayt,**kwargs):
matplotlib.rcParams.update({'font.size':20})
fig,ax = plt.subplots()
str_etop=''
if 'dbz' in kwargs:
im=ax.imshow(kwargs['dbz'],interpolation='none',cmap='nipy_spectral',vmin=-30,vmax=60,aspect='auto',origin='lower')
elif 'vvel' in kwargs:
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
im=ax.imshow(kwargs['vvel'],interpolation='none',cmap=shifted_cmap,vmin=-10,vmax=4,aspect='auto',origin='lower')
if 'echotop' in kwargs:
ax.plot(kwargs['echotop'][0],color='black')
units=r'$\mathregular{km^{-2}}$'
str_etop='etop_var: {:2.1f}'.format(np.nanvar(kwargs['echotop'][1]))
str_etop+=units
if 'bband' in kwargs:
bbht=kwargs['bband'][0]
idx_bbht=kwargs['bband'][1]
f = interp1d(ht, range(len(ht)))
ax.plot(idx_bbht, f(bbht),marker='o',linestyle='--',color='black')
if kwargs['colorbar']:
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="2%", pad=0.)
cbar = plt.colorbar(im, cax=cax)
format_yaxis(ax,ht,toplimit=11)
format_xaxis(ax, dayt, labels=True,format='%H')
ax.invert_xaxis()
str_date=dayt[0].strftime('%Y-%b')
str_tbeg=dayt[0].strftime(' %dT%H:00')+'-'
str_tend=(dayt[-1]).strftime('%dT%H:00')
c=kwargs['case']
annot='Case '+str(c)+' '+str_date+str_tbeg+str_tend+' UTC'+' '+str_etop
ax.text(0.02,0.02,annot,transform=ax.transAxes,fontsize=14)
plt.subplots_adjust(top=0.98, bottom=0.05,left=0.04, right=0.91)
plt.draw()
def plot_turbulence_spectra(dbz,vvel,ts,ts2,ht,dayt):
' setup new figure '
fig = plt.figure(figsize=(8,10))
' images axes'
gs = gridspec.GridSpec(4,1)
gs.update(top=0.95, bottom=0.46, hspace=.05)
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
' vvel axis'
gs = gridspec.GridSpec(1,1)
gs.update(top=0.7, bottom=0.48,right=0.88)
ax2 = plt.subplot(gs[0])
' power spectrum axis'
gs = gridspec.GridSpec(1,1)
gs.update(top=0.4, bottom=0.05,right=0.88)
ax3 = plt.subplot(gs[0])
'colormap for vvel'
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
' add images and colorbar'
im0= ax0.imshow(dbz,interpolation='none',cmap='nipy_spectral',vmin=-20,vmax=60,aspect='auto',origin='lower')
im1= ax1.imshow(vvel,interpolation='none',cmap=shifted_cmap,vmin=-10,vmax=4,aspect='auto',origin='lower')
divider0 = make_axes_locatable(ax0)
cax0 = divider0.append_axes("right", size="2%", pad=0.05)
cbar0 = plt.colorbar(im0, cax=cax0)
divider1 = make_axes_locatable(ax1)
cax1 = divider1.append_axes("right", size="2%", pad=0.05)
cbar1 = plt.colorbar(im1, cax=cax1)
' add levels, Doppler velocity, and power spectrum'
levels=[10, 20,30,40]
colors=['y', 'k', 'g', 'r']
variance_y=[0.7, 0.78, 0.86, 0.94]
for n,x in enumerate(levels):
' add levels '
ax0.plot([x]*len(vvel[x,:]),color=colors[n])
ax1.plot([x]*len(vvel[x,:]),color=colors[n])
' get traces at level x'
trace_doppler=vvel[x,:]
trace_dbz=dbz[x,:]
' extract hydrometeor vvel from Doppler vvel'
trace_z = 10.**(trace_dbz/10.)
vvel_hydrometeor = 0.817*trace_z**0.063 # Atlas et al. 1973
trace_wind = trace_doppler - (-vvel_hydrometeor)
' plot Doppler velocity at given levels '
ax2.plot(trace_doppler,color=colors[n])
ax2.plot(vvel_hydrometeor,color=colors[n])
ax2.plot(trace_wind,color=colors[n], linestyle=':',linewidth=1)
ax2.set_ylim([-10,8])
' add variance annotation '
variance=np.nanvar(trace_doppler)
ax2.text(0.2, variance_y[n], 'Variance: '+'{:3.2f}'.format(variance),
color=colors[n], transform=ax2.transAxes)
' create interpolant with regular time grid of 40 seconds'
asd = check_trace(trace_doppler)
f=interp1d(ts,asd)
trace_doppler2= f(ts2)
' plot power spectrum density'
if ~np.any(np.isnan(trace_doppler2)):
print 'level: '+str(x)
asd = check_trace(trace_wind)
power_spectrum(ax3, asd,colors[n],linestyle=':',marker=None)
power_spectrum(ax3,trace_doppler2,colors[n],linestyle='-',marker=None)
format_yaxis(ax0,ht)
format_yaxis(ax1,ht)
format_xaxis(ax0, dayt, freqMinutes=60,labels=False )
format_xaxis(ax1, dayt, freqMinutes=60,labels=False )
format_xaxis(ax2, dayt, freqMinutes=60,labels=True )
ax0.set_ylabel('Hgt MSL [km]')
ax1.set_ylabel('Hgt MSL [km]')
ax2.set_ylabel('VVel [ms^-1]')
ax2.set_xlabel(r'$\Leftarrow$'+' Time [UTC]')
ax0.set_xlim([0, len(vvel[0,:])])
ax0.invert_xaxis()
ax0.set_xticklabels([])
ax1.set_xlim([0, len(vvel[0,:])])
# ax1.set_ylim([0, 20])
ax1.invert_xaxis()
ax1.set_xticklabels([])
ax2.set_xlim([0, len(vvel[0,:])])
ax2.invert_xaxis()
plt.suptitle('SPROF observations. Date: '+dayt[0].strftime('%Y-%b'))
plt.draw()
def main():
global extent
global dayt
casenum = raw_input('\nIndicate case number (i.e. 1): ')
dbz,vvel, ht, dayt = read_sprof.retrieve_arrays(base_directory, casenum)
extent=[0, len(dayt), 0, len(ht)]
''' set index for time zooming '''
try:
idx_st=find_index(dayt,reqdates[casenum]['ini'])
idx_end=find_index(dayt,reqdates[casenum]['end'])
except KeyError:
idx_st=0
idx_end=len(dayt)-1
''' Precipitation partition
**************************'''
partition=read_partition.partition(dayt[0].year)
bbht=partition.get_bbht()
rtype=partition.get_rtype()
begdayt=partition.get_begdayt()
enddayt=partition.get_enddayt()
beg_aux = np.asarray([datetime(t.year, t.month, t.day, t.hour,0,0) for t in begdayt])
end_aux = np.asarray([datetime(t.year, t.month, t.day, t.hour,0,0) for t in enddayt])
dayt_aux=np.asarray([datetime(t.year, t.month, t.day, t.hour,0,0) for t in dayt])
beg_index = np.where(beg_aux==dayt_aux[0])[0][0]
end_index = np.where(end_aux==dayt_aux[-1])[0][1]
bbht = bbht[beg_index+1:end_index]
rtype = rtype[beg_index+1:end_index]
begdayt = begdayt[beg_index:end_index]
enddayt = enddayt[beg_index:end_index]
d = [[t.year, t.month, t.day, t.hour,t.minute] for t in begdayt]
idx_be=np.asarray([find_index(dayt,x) for x in d[1:]])
d = [[t.year, t.month, t.day, t.hour,t.minute] for t in enddayt]
idx_en=np.asarray([find_index(dayt,x) for x in d[1:]])
idx_bbht=(idx_be+idx_en)/2
''' Plots
**************'''
fig,ax=plt.subplots(2,1,sharex=True, figsize=(12,8))
plot_reflectivity(ax[0],dbz,ht, cmap='nipy_spectral',vmin=-20,vmax=60)
plot_velocity(ax[1],vvel,ht, cmap='bwr',vmin=-3,vmax=3)
f = interp1d(ht, range(len(ht)))
ax[0].plot(idx_bbht, f(bbht),marker='o',linestyle='--',color='black')
for n, s in enumerate(rtype):
if s[0] != 'NaN':
ax[0].text(idx_bbht[n], -5, s[0][0].upper(), horizontalalignment='center',clip_on=True)
ax[1].plot(idx_bbht, f(bbht),marker='o',linestyle='--',color='black')
' it has to be before set_xlim'
# format_xaxis(ax[1],dayt,2,casenum)
format_xaxis(ax[1],dayt,labels=True,format='%d\n%H')
ax[0].set_xlim([idx_st,idx_end])
ax[0].set_ylim([-10,len(ht)])
ax[1].set_ylim([-10,len(ht)])
fig.subplots_adjust(hspace=.07)
ax[1].invert_xaxis()
ax[1].set_xlabel(r'$\Leftarrow$'+' Time [UTC]')
# ax[1].set_xlabel(' Time [UTC]'+r'$\Rightarrow$')
# ax[0].grid(b=True, which='major', color='b', linestyle='-')
plt.suptitle('SPROF observations. Date: '+dayt[0].strftime('%Y-%b'))
plt.subplots_adjust(left=0.05, right=0.95, top=0.95, bottom=0.1)
plt.draw()
# plt.show()
plt.show(block=False)
def plot_turbulence_spectra(dbz, vvel, ts, ts2, ht, dayt):
' setup new figure '
fig = plt.figure(figsize=(8, 10))
' images axes'
gs = gridspec.GridSpec(4, 1)
gs.update(top=0.95, bottom=0.46, hspace=.05)
ax0 = plt.subplot(gs[0])
ax1 = plt.subplot(gs[1])
' vvel axis'
gs = gridspec.GridSpec(1, 1)
gs.update(top=0.7, bottom=0.48, right=0.88)
ax2 = plt.subplot(gs[0])
' power spectrum axis'
gs = gridspec.GridSpec(1, 1)
gs.update(top=0.4, bottom=0.05, right=0.88)
ax3 = plt.subplot(gs[0])
'colormap for vvel'
orig_cmap = cm.bwr
shifted_cmap = shiftedColorMap(orig_cmap, midpoint=0.7, name='shifted')
' add images and colorbar'
im0 = ax0.imshow(dbz,
interpolation='none',
cmap='nipy_spectral',
vmin=-20,
vmax=60,
aspect='auto',
origin='lower')
im1 = ax1.imshow(vvel,
interpolation='none',
cmap=shifted_cmap,
vmin=-10,
vmax=4,
aspect='auto',
origin='lower')
divider0 = make_axes_locatable(ax0)
cax0 = divider0.append_axes("right", size="2%", pad=0.05)
cbar0 = plt.colorbar(im0, cax=cax0)
divider1 = make_axes_locatable(ax1)
cax1 = divider1.append_axes("right", size="2%", pad=0.05)
cbar1 = plt.colorbar(im1, cax=cax1)
' add levels, Doppler velocity, and power spectrum'
levels = [10, 20, 30, 40]
colors = ['y', 'k', 'g', 'r']
variance_y = [0.7, 0.78, 0.86, 0.94]
for n, x in enumerate(levels):
' add levels '
ax0.plot([x] * len(vvel[x, :]), color=colors[n])
ax1.plot([x] * len(vvel[x, :]), color=colors[n])
' get traces at level x'
trace_doppler = vvel[x, :]
trace_dbz = dbz[x, :]
' extract hydrometeor vvel from Doppler vvel'
trace_z = 10.**(trace_dbz / 10.)
vvel_hydrometeor = 0.817 * trace_z**0.063 # Atlas et al. 1973
trace_wind = trace_doppler - (-vvel_hydrometeor)
' plot Doppler velocity at given levels '
ax2.plot(trace_doppler, color=colors[n])
ax2.plot(vvel_hydrometeor, color=colors[n])
ax2.plot(trace_wind, color=colors[n], linestyle=':', linewidth=1)
ax2.set_ylim([-10, 8])
' add variance annotation '
variance = np.nanvar(trace_doppler)
ax2.text(0.2,
variance_y[n],
'Variance: ' + '{:3.2f}'.format(variance),
color=colors[n],
transform=ax2.transAxes)
' create interpolant with regular time grid of 40 seconds'
asd = check_trace(trace_doppler)
f = interp1d(ts, asd)
trace_doppler2 = f(ts2)
' plot power spectrum density'
if ~np.any(np.isnan(trace_doppler2)):
print 'level: ' + str(x)
asd = check_trace(trace_wind)
power_spectrum(ax3, asd, colors[n], linestyle=':', marker=None)
power_spectrum(ax3,
trace_doppler2,
colors[n],
linestyle='-',
marker=None)
format_yaxis(ax0, ht)
format_yaxis(ax1, ht)
format_xaxis(ax0, dayt, freqMinutes=60, labels=False)
format_xaxis(ax1, dayt, freqMinutes=60, labels=False)
format_xaxis(ax2, dayt, freqMinutes=60, labels=True)
ax0.set_ylabel('Hgt MSL [km]')
ax1.set_ylabel('Hgt MSL [km]')
ax2.set_ylabel('VVel [ms^-1]')
ax2.set_xlabel(r'$\Leftarrow$' + ' Time [UTC]')
ax0.set_xlim([0, len(vvel[0, :])])
ax0.invert_xaxis()
ax0.set_xticklabels([])
ax1.set_xlim([0, len(vvel[0, :])])
# ax1.set_ylim([0, 20])
ax1.invert_xaxis()
ax1.set_xticklabels([])
ax2.set_xlim([0, len(vvel[0, :])])
ax2.invert_xaxis()
plt.suptitle('SPROF observations. Date: ' + dayt[0].strftime('%Y-%b'))
plt.draw()