def get_arrays(casenum): dbz,vvel, ht, dayt = read_sprof.retrieve_arrays(base_directory, casenum) reqdates = precip.request_dates_significant(casenum) idx_st=find_index(dayt,reqdates['ini']) idx_end=find_index(dayt,reqdates['end']) dayt=dayt[idx_st:idx_end+1] vvel=vvel[:,idx_st:idx_end+1] dbz=dbz[:,idx_st:idx_end+1] with np.errstate(invalid='ignore'): vvel[vvel<=-10.]=np.nan vvel[vvel>=4.]=np.nan ' add total seconds to array' ts=[] for d in dayt: ts.append((d-dayt[0]).total_seconds()) ' create equally spaced time grid ' day = dayt[0] end = dayt[-1] step = timedelta(seconds=40) ts2 = [] while day < end: result=(day-dayt[0]).total_seconds() ts2.append(result) day += step return dbz,vvel,ht,ts,ts2,dayt
def get_arrays(casenum):
dbz, vvel, ht, dayt = read_sprof.retrieve_arrays(base_directory, casenum)
reqdates = precip.request_dates_significant(casenum)
idx_st = find_index(dayt, reqdates['ini'])
idx_end = find_index(dayt, reqdates['end'])
dayt = dayt[idx_st:idx_end + 1]
vvel = vvel[:, idx_st:idx_end + 1]
dbz = dbz[:, idx_st:idx_end + 1]
with np.errstate(invalid='ignore'):
vvel[vvel <= -10.] = np.nan
vvel[vvel >= 4.] = np.nan
' add total seconds to array'
ts = []
for d in dayt:
ts.append((d - dayt[0]).total_seconds())
' create equally spaced time grid '
day = dayt[0]
end = dayt[-1]
step = timedelta(seconds=40)
ts2 = []
while day < end:
result = (day - dayt[0]).total_seconds()
ts2.append(result)
day += step
return dbz, vvel, ht, ts, ts2, dayt
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)