def spatiofreq2_season(s,lat,lon,yrs,eventkeys,figno=1,season='coreseason',\
key='noaa-olr-0-all',flagonly=False,file_suffix='test',savefig=False,\
fontdict=False):
'''spatiofreq2_season(s,lat,lon,yrs,figno=1,season='coreseason',\
flagonly=False,file_suffix='test')
Produces subplots of cloud-band gridpoint count by month
'''
if not fontdict: fd = {'fontsize': 14, 'fontweight': 'bold'}
else: fd = fontdict
mbkl = key.split('-')
if mbkl[0] == 'noaa': dclim = (1, 9, 1)
if mbkl[0] == 'hadam3p': dclim = (1, 11, 1)
if isinstance(season, str):
if season == 'coreseason': mns = [10, 11, 12, 1, 2, 3]
elif season == 'fullseason':
mns = [8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7]
elif isinstance(season, list):
mns = season
m, f = blb.SAfrBasemap(lat[4:-7],lon[3:-2],drawstuff=True,prj='cyl',\
fno=figno,rsltn='l',fontdict=fd)
if len(mns) == 12:
plt.close()
plt.figure(figsize=[12, 10])
elif len(mns) == 6:
plt.close()
plt.figure(figsize=[13, 8])
cnt = 1
msklist = []
for mn in mns:
if len(mns) == 12: plt.subplot(4, 3, cnt)
elif len(mns) == 6: plt.subplot(3, 2, cnt)
if flagonly:
allmask=stats.spatiofreq2(m,s,lat,lon,yrs,eventkeys,\
clim=(1.,9.,1.),month=mn,flagonly=True,fontdict=fd)
else:
allmask=stats.spatiofreq2(m,s,lat,lon,yrs,eventkeys,clim=dclim,\
month=mn,flagonly=False,fontdict=fd)
if cnt % 2 == 0:
syp.redrawmap(m,
lns=True,
resol='verylow',
parallel=False,
fontdict=fd)
else:
syp.redrawmap(m, lns=True, resol='verylow', fontdict=fd)
cnt += 1
msklist.append(allmask)
my.xtickfonts()
my.ytickfonts()
plt.subplots_adjust(left=0.05,right=0.92,top=0.97,bottom=0.02,\
wspace=0.02,hspace=0.1)
if savefig:
if flagonly:
plt.savefig(stats.figdir + file_suffix + '_flagonly.png', dpi=150)
else:
plt.savefig(stats.figdir + file_suffix + '.png', dpi=150)
return msklist
def quickplot(m,
rain,
rlat,
rlon,
reftime,
maskval=0.0,
clim=[0, 50],
wait=1,
saveto=False):
plt.ion()
plt.show()
if isinstance(rain, np.ma.MaskedArray):
msk = (rain.data <= maskval) | erainm.mask
rainm = np.ma.MaskedArray(rain.data, mask=msk, dtype=np.float32)
else:
msk = (rain <= maskval) | np.isnan(rain)
rainm = np.ma.MaskedArray(rain, mask=msk, dtype=np.float32)
#m, f = blb.SAfrBasemap(np.arange(-38,-18),np.arange(10,40),drawstuff=True,prj='cyl',fno=1,rsltn='l')
#m, f = blb.SAfrBasemap(rlat,rlon,drawstuff=True,prj='cyl',fno=1,rsltn='l')
for i in xrange(rainm.shape[1]):
rdata = rainm[:, i]
if reftime == 'season': ttl = mndict[season[i]]
else: ttl = str(reftime[i])
if not np.any(~rdata.mask):
print 'NOTHING TO SHOW'
#m.scatter(rlon,rlat,15,rainm[:,i],cmap=plt.cm.OrRd,edgecolor='none');plt.clim(0,50)
syp.redrawmap(m, lns=True, resol='hi')
plt.text(22,
-28,
'NOTHING TO VALID SHOW',
fontsize=20,
rotation=25)
plt.title(ttl)
plt.draw()
sleep(wait)
plt.clf()
continue
#rdata=np.where(rdata<1,np.nan,rdata)
#m.scatter(rlon,rlat,15,rainw[:,i],cmap=plt.cm.OrRd,edgecolor='none');plt.clim(0,50)#;plt.colorbar()
#print np.any(~np.isnan(rdata.data))
m.scatter(rlon, rlat, 5, rdata, cmap=my.goodraincm(), edgecolor='none')
plt.clim(clim)
plt.colorbar()
syp.redrawmap(m, lns=True, resol='hi')
plt.title(ttl)
plt.draw()
sleep(wait)
plt.clf()
if saveto:
fname = figdir + saveto + '_' + ttl + '.png'
plt.savefig(fname, dpi=150)
def projectrainmask_in2_rawdata(rainmasks,
rawrain,
rawhrtime,
flagdetail,
everywhere=False):
'''projectrainmask_in2_rawdata(rainmask,rawrain)
Usage: rainmask would be output from SynopticPlot.multirainmasks
rawrain is for example WRC time x stations data'''
erain, etime, ekeys, flagarr = rainmasks['rain']
# SUBSET DATA FURTHER IF SPECIFY FLAGDETAILS
ixsub = syp.flagdetailsub(flagarr, ekeys, flagdetail)
if len(ixsub) > 0:
erain, etime, ekeys, flagarr = erain[
ixsub, :], etime[ixsub], ekeys[ixsub], flagarr[ixsub, :]
# CORE OF THE FUNCTION
erain = erain.T
projdata = rawrain.copy()
projmsk = np.ones(projdata.shape, dtype=np.bool)
for i in xrange(rawhrtime.shape[0]):
ix = np.where(etime == rawhrtime[i])[0]
if len(ix) == 0: # NO TIME MATCHES
continue
elif len(ix) > 4: # NUMEROUS TIME MATCHES IN MULTIPLE EVENTTRACKS
iux, ix_iux = np.unique(ekeys[ix], return_index=True)
#print ekeys[ix[ix_iux]]
masklist = []
for index in ix_iux:
if everywhere and np.any(~erain.mask[:, ix[index]]):
erain.mask[:, ix[index]][:] = False
#print ekeys[ix[index]]
projmsk[:,
i] = ~((~projmsk[:, i]) | (~erain.mask[:, ix[index]]))
else: # STANDARD EXPECTED FOR 4 TIME MATCHES (REASON IS HAVE 4 TIME DAILY TIMESTEPPING DUE TO NCEP SO FILL UP THESE STEPS FOR DAILY VARIABLES SUCH AS RAINFALL)
ixt = ix[0]
if everywhere and np.any(~erain.mask[:, ixt]):
erain.mask[:, ixt][:] = False
projmsk[:, i] = erain.mask[:, ixt]
projected = np.ma.MaskedArray(projdata, mask=projmsk, dtype=np.float32)
return projected
def quicksubplot(m,
rain,
rlat,
rlon,
reftime,
maskval=0.0,
clim=[0, 50, 5],
wait=1,
saveto=False):
plt.ion()
plt.show()
mycm = my.goodraincm()
#mycm=plt.cm.gray_r
mycm = plt.cm.jet
if isinstance(rain, np.ma.MaskedArray):
msk = (rain.data <= maskval) | erainm.mask
rainm = np.ma.MaskedArray(rain.data, mask=msk, dtype=np.float32)
else:
msk = (rain <= maskval) | np.isnan(rain)
rainm = np.ma.MaskedArray(rain, mask=msk, dtype=np.float32)
#m, f = blb.SAfrBasemap(np.arange(-38,-18),np.arange(10,40),drawstuff=True,prj='cyl',fno=1,rsltn='l')
#m, f = blb.SAfrBasemap(rlat,rlon,drawstuff=True,prj='cyl',fno=1,rsltn='l')
for i in xrange(rainm.shape[1]):
if reftime == 'season':
ttl = mndict[season[i]]
exec('plt.subplot(3,4,' + str(i + 1) + ')')
elif reftime == 'coreseason':
ttl = mndict[coreseason[i]]
exec('plt.subplot(2,3,' + str(i + 1) + ')')
else:
ttl = str(reftime[i])
exec('plt.subplot(3,4,' + str(i + 1) + ')')
rdata = rainm[:, i]
if not np.any(~rdata.mask):
print 'NOTHING TO SHOW'
#m.scatter(rlon,rlat,15,rainm[:,i],cmap=plt.cm.OrRd,edgecolor='none');plt.clim(0,50)
syp.redrawmap(m) #,lns=True,resol='hi')
plt.text(22, -28, 'NOTHING TO VALID SHOW', fontsize=5, rotation=25)
plt.title(ttl)
plt.draw()
sleep(wait)
continue
#rdata=np.where(rdata<1,np.nan,rdata)
#m.scatter(rlon,rlat,15,rainw[:,i],cmap=plt.cm.OrRd,edgecolor='none');plt.clim(0,50)#;plt.colorbar()
#print np.any(~np.isnan(rdata.data))
m.scatter(rlon, rlat, 5, rdata, cmap=mycm, edgecolor='none')
plt.clim(clim[:2])
syp.redrawmap(m) #,lns=True)
plt.title(ttl)
plt.subplots_adjust(left=0.05,
right=0.88,
top=0.95,
bottom=0.02,
wspace=0.02,
hspace=0.1)
if i == 3:
#f=plt.gcf()
im_col = plt.gci()
#bounds = np.arange(clim[0],clim[1],1)
#axcol = f.add_axes([0.90,0.2,0.015,0.5])
#plt.colorbar(mappable=im_col,cax=axcol,boundaries=bounds)
f = plt.gcf()
bounds = np.arange(clim[0], clim[1] + clim[2], clim[2])
axcol = f.add_axes([0.90, 0.15, 0.015, 0.6])
plt.colorbar(mappable=im_col, cax=axcol, boundaries=bounds)
plt.draw()
sleep(wait)
#plt.clf()
if saveto:
fname = figdir + saveto + '.png'
plt.savefig(fname, dpi=150)