contourf=True, pdfsuffix=False, wdsurf=None, wdwpro=None,

rainbb=None, raincz=None, nhours=None):

name={'wdir':'Wind Direction',

'wspd':'Wind Speed'}

if target == 'wdir':

bins = np.arange(0,370,10)

hist_xticks = np.arange(0,420,60)

hist_xlim = [0,360]

elif target == 'wspd':

bins = np.arange(0,36,1)

hist_xticks = np.arange(0,40,5)

hist_xlim = [0,35]

first = True

for y in year:

print('Processing year {}'.format(y))

' tta analysis '

tta = tta_analysis(y)

tta.start_df(wdir_surf=wdsurf,

wdir_wprof=wdwpro,

rain_bby=rainbb,

rain_czd=raincz,

nhours=nhours)

' retrieve dates '

include_dates = tta.include_dates

tta_dates = tta.tta_dates

notta_dates = tta.notta_dates

' read wprof '

wprof_df = parse_data.windprof(y)

wprof = wprof_df.dframe[target]

' wprof partition '

wprof = wprof.loc[include_dates] # all included

wprof_tta = wprof.loc[tta_dates] # only tta

wprof_notta = wprof.loc[notta_dates]# only notta

s1 = np.squeeze(pandas2stack(wprof))

s2 = np.squeeze(pandas2stack(wprof_tta))

s3 = np.squeeze(pandas2stack(wprof_notta))

if first:

wp = s1

wp_tta = s2

wp_notta = s3

first = False

else:

wp = np.hstack((wp,s1))

wp_tta = np.hstack((wp_tta,s2))

wp_notta = np.hstack((wp_notta, s3))

_,wp_hours = wp.shape

_,tta_hours = wp_tta.shape

_,notta_hours = wp_notta.shape

' makes CFAD '

hist_array = np.empty((40,len(bins)-1,3))

for hgt in range(wp.shape[0]):

row1 = wp[hgt,:]

row2 = wp_tta[hgt,:]

row3 = wp_notta[hgt,:]

for n,r in enumerate([row1,row2,row3]):

' following CFAD Yuter et al (1995) '

freq,bins=np.histogram(r[~np.isnan(r)],

bins=bins)

if normalized:

hist_array[hgt,:,n] = 100.*(freq/float(freq.sum()))

else:

hist_array[hgt,:,n] = freq

fig,axs = plt.subplots(1,3,sharey=True,figsize=(10,8))

ax1 = axs[0]

ax2 = axs[1]

ax3 = axs[2]

hist_wp = np.squeeze(hist_array[:,:,0])

hist_wptta = np.squeeze(hist_array[:,:,1])

hist_wpnotta = np.squeeze(hist_array[:,:,2])

x = bins

y = wprof_df.hgt

if contourf:

X,Y = np.meshgrid(x,y)

nancol = np.zeros((40,1))+np.nan

hist_wp = np.hstack((hist_wp,nancol))

hist_wptta = np.hstack((hist_wptta,nancol))

hist_wpnotta = np.hstack((hist_wpnotta,nancol))

vmax=20

nlevels = 10

delta = int(vmax/nlevels)

v = np.arange(2,vmax+delta,delta)

cmap = cm.get_cmap('plasma')

ax1.contourf(X,Y,hist_wp,v,cmap=cmap)

p = ax2.contourf(X,Y,hist_wptta,v,cmap=cmap,extend='max')

p.cmap.set_over(cmap(1.0))

ax3.contourf(X,Y,hist_wpnotta,v,cmap=cmap)

cbar = add_colorbar(ax3,p,size='4%')

else:

p = ax1.pcolormesh(x,y,hist_wp,cmap='viridis')

ax2.pcolormesh(x,y,hist_wptta,cmap='viridis')

ax3.pcolormesh(x,y,hist_wpnotta,cmap='viridis')

amin = np.amin(hist_wpnotta)

amax = np.amax(hist_wpnotta)

cbar = add_colorbar(ax3,p,size='4%',ticks=[amin,amax])

cbar.ax.set_yticklabels(['low','high'])

' --- setup ax1 --- '

amin = np.amin(hist_wp)

amax = np.amax(hist_wp)

ax1.set_xticks(hist_xticks)

ax1.set_xlim(hist_xlim)

ax1.set_ylim([0,4000])

txt = 'All profiles (n={})'.format(wp_hours)

ax1.text(0.5,0.95,txt,fontsize=15,

transform=ax1.transAxes,va='bottom',ha='center')

ax1.set_ylabel('Altitude [m] MSL')

' --- setup ax2 --- '

amin = np.amin(hist_wptta)

amax = np.amax(hist_wptta)

ax2.set_xticks(hist_xticks)

ax2.set_xlim(hist_xlim)

ax2.set_ylim([0,4000])

ax2.set_xlabel(name[target])

txt = 'TTA (n={})'.format(tta_hours)

ax2.text(0.5,0.95,txt,fontsize=15,

transform=ax2.transAxes,va='bottom',ha='center')

' --- setup ax3 --- '

ax3.set_xticks(hist_xticks)

ax3.set_xlim(hist_xlim)

ax3.set_ylim([0,4000])

txt = 'NO-TTA (n={})'.format(notta_hours)

ax3.text(0.5,0.95,txt,fontsize=15,

transform=ax3.transAxes,va='bottom',ha='center')

title = 'Normalized frequencies of BBY wind profiles {} \n'

title += 'TTA wdir_surf:{}, wdir_wp:{}, '

title += 'rain_bby:{}, rain_czd:{}, nhours:{}'

if len(year) == 1:

yy = 'year {}'.format(year[0])

else:

yy = 'year {} to {}'.format(year[0],year[-1])

plt.suptitle(title.format(yy, wdsurf, wdwpro, rainbb, raincz, nhours),

fontsize=15)

plt.subplots_adjust(top=0.9,left=0.1,right=0.95,bottom=0.1, wspace=0.1)

if pngsuffix:

out_name = 'wprof_{}_cfad{}.png'

plt.savefig(out_name.format(target,pngsuffix))

plt.close()

elif pdfsuffix:

out_name = 'wprof_{}_cfad{}.pdf'

plt.savefig(out_name.format(target,pdfsuffix))

plt.close()

else: