def tta_precip():
import Windprof2 as wp
print "BBY-tta | BBY-notta | CZD-tta | CZD-notta | FRS-tta | FRS-notta "
o = "{:11.1f} {:11.1f} {:11.1f} {:11.1f} {:11.1f} {:11.1f}"
for case in range(8, 15):
bby, czd, frs, _ = get_data(str(case))
tta_times = wp.get_tta_times(case=str(case), continuous=True)
if len(tta_times) > 0:
tta_idx_bby = (bby.index >= tta_times[0]) & (bby.index <= tta_times[-1])
tta_idx_czd = (czd.index >= tta_times[0]) & (czd.index <= tta_times[-1])
tta_idx_frs = (frs.index >= tta_times[0]) & (frs.index <= tta_times[-1])
bby_tta = bby.precip[tta_idx_bby].sum()
bby_notta = bby.precip[~tta_idx_bby].sum()
czd_tta = czd.precip[tta_idx_czd].sum()
czd_notta = czd.precip[~tta_idx_czd].sum()
frs_tta = frs.precip[tta_idx_frs].sum()
frs_notta = frs.precip[~tta_idx_frs].sum()
else:
bby_tta = -999
bby_notta = bby.precip.sum()
czd_tta = -999
czd_notta = czd.precip.sum()
frs_tta = -999
frs_notta = frs.precip.sum()
print o.format(bby_tta, bby_notta, czd_tta, czd_notta, frs_tta, frs_notta)
def compare_with_windprof(SYNTH,**kwargs):
loc=kwargs['location']
U = SYNTH.U
V = SYNTH.V
LAT=SYNTH.LAT
LON=SYNTH.LON
Z=SYNTH.Z
st=SYNTH.start
en=SYNTH.end
''' synthesis '''
# lat_idx=cm.find_index_recursively(array=LAT,value=loc['lat'],decimals=2)
# lon_idx=cm.find_index_recursively(array=LON,value=loc['lon'],decimals=2)
f=interp1d(LAT,range(len(LAT)))
latx=int(np.ceil(f(loc['lat'])))
f=interp1d(LON,range(len(LON)))
lonx=int(np.ceil(f(loc['lon'])))
uprof = U[lonx,latx,:]
vprof = V[lonx,latx,:]
sprofspd=np.sqrt(uprof**2+vprof**2)
sprofdir=270. - ( np.arctan2(vprof,uprof) * 180./np.pi )
''' wind profiler '''
case=kwargs['case']
wspd,wdir,time,hgt = wp.make_arrays(case= str(case),
resolution='coarse',
surface=False)
idx = time.index(datetime.datetime(st.year, st.month, st.day, st.hour, 0))
wprofspd = wspd[:,idx]
wprofdir = wdir[:,idx]
''' profile '''
with sns.axes_style("darkgrid"):
fig,ax=plt.subplots(1,2, figsize=(9,9), sharey=True)
n=0
hl1=ax[n].plot(sprofspd,Z,'-o',label='P3-SYNTH (250 m)')
hl2=ax[n].plot(wprofspd,hgt,'-o',label='WPROF-COARSE (100 m)')
ax[n].set_xlabel('wind speed [m s-1]')
ax[n].set_ylabel('height AGL [km]')
lns = hl1 + hl2
labs = [l.get_label() for l in lns]
ax[n].legend(lns, labs, loc=0)
n=1
ax[n].plot(sprofdir,Z,'-o',label='P3-SYNTH')
ax[n].plot(wprofdir,hgt,'-o',label='WPROF')
ax[n].set_xlabel('wind direction [deg]')
ax[n].invert_xaxis()
t1='Comparison between P3-synthesis and ' +loc['name']+' wind profiler'
t2='\nDate: ' + st.strftime('%Y-%m-%d')
t3='\nSynthesis time: ' + st.strftime('%H:%M') + ' to ' + en.strftime('%H:%M UTC')
t4='\nWind profiler time: ' + time[idx].strftime('%H:%M') + ' to ' + time[idx+1].strftime('%H:%M UTC')
fig.suptitle(t1+t2+t3+t4)
plt.ylim([0,5])
plt.draw()
def get_windprof(case, gapflow_time=None,
top_hgt_km=None,
homedir=None):
" return layer average values; layer is defined \
by top_hgt_km"
import Windprof2 as wp
from scipy.interpolate import interp1d
from datetime import timedelta
out = wp.make_arrays(resolution='coarse',
surface=False, case=str(case), period=False,
homedir=homedir)
wspd, wdir, time, hgt = out
time = np.array(time)
' match surface obs timestamp'
time2 = time - timedelta(minutes=5)
' get corresponding target time index '
index_dict = dict((value, idx) for idx, value in enumerate(time2))
target_idx = [index_dict[x] for x in gapflow_time]
' wp time equivalent to gapflow time '
target_time = time2[target_idx] + timedelta(minutes=5)
wspd_target = []
wdir_target = []
for tt in target_time:
idx = np.where(time == tt)[0]
# ws = np.squeeze(wspd[:, idx])
# wd = np.squeeze(wdir[:, idx])
# ' interpolate at target altitude '
# fws = interp1d(hgt, ws)
# fwd = interp1d(hgt, wd)
# new_ws = fws(target_hgt_km)
# new_wd = fwd(target_hgt_km)
hidx = np.where(hgt <= top_hgt_km)[0]
ws = np.squeeze(wspd[hidx, idx])
wd = np.squeeze(wdir[hidx, idx])
u = -ws*np.sin(np.radians(wd))
v = -ws*np.cos(np.radians(wd))
ubar = np.nanmean(u)
vbar = np.nanmean(v)
new_ws = np.sqrt(ubar**2+vbar**2)
new_wd = 270-np.arctan2(vbar,ubar)*180/np.pi
if new_wd > 360:
new_wd -= 360
wspd_target.append(new_ws)
wdir_target.append(new_wd)
return np.array(wspd_target), np.array(wdir_target)
for tta, time in zip(tta_range, times):
drange = pd.date_range(start=wp_st, end=wp_en, freq='1H')
time['tta'][0] = np.where(drange == tta[0])[0]
time['tta'][1] = np.where(drange == tta[1])[0]
params = [
'WD$<140$, nh$\geq1\,(2,4)$',
'WD$<150$, nh$\geq1$',
'WD$<160$, nh$\geq1$',
'WD$<150$, nh$\geq2$',
]
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(
resolution=res,
add_surface=True,
case=str(c),
)
cbar_inv = False
wspdMerid = -wspd * cosd(wdir)
if c == 13:
foo = wspdMerid
ax, hcbar, im = wp.plot_time_height(ax=ax,
wspd=wspdMerid,
time=time,
height=hgt,
spd_range=[0, 30],
spd_delta=2,
transform=ax.transAxes)
return gapflow
def get_windprof(case, gapflow_time=None, top_hgt_km=None, homedir=None):
" return layer average values; layer is defined \
by top_hgt_km"
import Windprof2 as wp
from scipy.interpolate import interp1d
from datetime import timedelta
out = wp.make_arrays(resolution='coarse',
surface=False,
case=str(case),
period=False,
homedir=homedir)
wspd, wdir, time, hgt = out
time = np.array(time)
' match surface obs timestamp'
time2 = time - timedelta(minutes=5)
' get corresponding target time index '
index_dict = dict((value, idx) for idx, value in enumerate(time2))
target_idx = [index_dict[x] for x in gapflow_time]
' wp time equivalent to gapflow time '
target_time = time2[target_idx] + timedelta(minutes=5)
import Windprof2 as wp
import matplotlib.pyplot as plt
# import numpy as np
fig, axes = plt.subplots(3, 3, figsize=(11, 9), sharex=True, sharey=True)
axes = axes.flatten()
wd_lim_surf = 125
wd_lim_aloft = 170
mAGL, color = [120, 'navy']
# mAGL,color=[500,'green']
for c, ax in zip(range(12, 13), axes):
wspd, wdir, time, hgt = wp.make_arrays(resolution='coarse',
surface=True,
case=str(c))
wp.plot_scatter2(ax=ax,
wdir=wdir,
hgt=hgt,
time=time,
mAGL=mAGL,
lim_surf=wd_lim_surf,
lim_aloft=wd_lim_aloft,
color=color)
ax.text(0., 0.05, 'Case ' + str(c).zfill(2), transform=ax.transAxes)
axes[0].text(0,
1.05,
'Altitude: ' + str(mAGL) + 'm AGL',
transform=axes[0].transAxes)
axes[6].set_xlabel('wind direction surface')
axes[6].text(wd_lim_surf, -20, str(wd_lim_surf), ha='center')
# case=str(case),
# period=False)
# wp.plot_scatter(wdir=wdir,hgt=hgt,title='Case '+str(case).zfill(2))
# plt.show(block=False)
fig, axes = plt.subplots(5, 3, figsize=(11, 15), sharex=True, sharey=True)
axes = axes.flatten()
vline = 130
hline = 170
mAGL, color = [120, 'navy']
# mAGL,color=[500,'green']
for c, ax in zip(range(1, 15), axes):
wspd, wdir, time, hgt = wp.make_arrays(resolution='fine',
surface=True,
case=str(c),
period=False)
wp.plot_scatter2(ax=ax,
wdir=wdir,
hgt=hgt,
mAGL=mAGL,
vline=vline,
hline=hline,
color=color)
ax.text(0., 0.05, 'Case ' + str(c).zfill(2), transform=ax.transAxes)
axes[0].text(0,
1.05,
'Altitude: ' + str(mAGL) + 'm AGL',
transform=axes[0].transAxes)
}
labend = {
8: '15\n00',
9: '24\n00',
10: '17\n00',
11: '11\n00',
12: '04\n00',
13: '19\n00',
14: '27\n00'
}
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
surface=True,
case=str(c),
homedir=homedir)
if c == 14:
cbar = ax
else:
cbar = False
wspdMerid = -wspd * cosd(wdir)
ax, hcbar = wp.plot_time_height(ax=ax,
wspd=wspdMerid,
time=time,
height=hgt,
spd_range=[0, 30],
topdf = False
case = range(13, 14)
res = 'coarse'
o = 'case{}_total_wind_{}.pdf'
t = 'Total wind speed - {} resolution - Case {} - Date: {}'
for c in case:
''' creates plot with seaborn style '''
with sns.axes_style("white"):
scale=0.8
f, ax1 = plt.subplots(figsize=(11*scale, 8.5*scale))
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
surface=True,
case=str(c),
homedir=homedir)
wspdMerid=-wspd*cosd(wdir);
wp.plot_colored_staff(ax=ax1, wspd=wspdMerid, wdir=wdir, time=time,
height=hgt, spd_range=[0, 36], spd_delta=2,
vdensity=0, hdensity=0, cmap='nipy_spectral',
title=t.format(res.title(), str(c).zfill(2),
time[1].strftime('%Y-%b')),cbar=ax1)
# wp.add_soundingTH('bvf_moist', str(c), ax=ax1, wptime=time,
# wphgt=hgt, sigma=1, homedir=homedir)
if topdf:
savename = o.format(str(c).zfill(2), res)
gs0 = gridspec.GridSpec(2, 1, hspace=0.15)
axes = range(2)
axes[0] = plt.subplot(gs0[0], gid='(a) 23-24Jan01')
axes[1] = plt.subplot(gs0[1], gid='(b) 17Feb01')
labend = {
3: '25\n00',
7: '18\n08',
}
for c, ax in zip(case, axes):
out = wp.make_arrays2(resolution=res,
add_surface=True,
case=str(c),
interp_hgts=np.linspace(0.160, 3.74, 40))
wspd, wdir, time, hgt = out
if ax.get_gid() == '(a) 23-24Jan01':
cbar = ax
cbarinvi = False
else:
cbar = True
cbarinvi = True
''' wind speed target '''
ucomp = -wspd * sind(wdir)
vcomp = -wspd * cosd(wdir)
x = ucomp * sind(230)
time['tta'][1] = np.where(drange == tta[1])[0]
''' last xlabel '''
labend = {8: '15\n00',
9: '24\n00',
10: '17\n00',
11: '10\n00',
12: '03\n00',
13: '19\n00',
14: '26\n00'
}
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
add_surface=True,
case=str(c),
)
# print [time[0],time[-1]]
if c == 14:
cbar_inv = False
else:
cbar_inv = True
wspdMerid = -wspd * cosd(wdir)
if c == 13:
foo = wspdMerid
ax, hcbar, img = wp.plot_time_height(ax=ax,
time['tta'][1] = np.where(drange == tta[1])[0]
''' last xlabel '''
labend = {8: '15\n00',
9: '24\n00',
10: '17\n00',
11: '10\n00',
12: '03\n00',
13: '19\n00',
14: '26\n00'
}
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
add_surface=True,
case=str(c),
)
# print [time[0],time[-1]]
if c == 14:
cbar_inv = False
else:
cbar_inv = True
wspdMerid = -wspd * cosd(wdir);
if c == 13:
foo = wspdMerid
ax, hcbar = wp.plot_time_height(ax=ax,
wspd=wspdMerid,
time=time,
drange = pd.date_range(start=wp_st,end=wp_en,freq='1H')
time['tta'][0] = np.where(drange == tta[0])[0]
time['tta'][1] = np.where(drange == tta[1])[0]
params = [
'$\overline{WDIR}_{500}<140$, nh$\geq1\,(2,4)$',
'$\overline{WDIR}_{500}<150$, nh$\geq1$',
'$\overline{WDIR}_{500}<160$, nh$\geq1$',
'$\overline{WDIR}_{500}<150$, nh$\geq2$',
]
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
add_surface=True,
case=str(c),
)
cbar_inv = False
wspdMerid = -wspd*cosd(wdir)
if c == 13:
foo = wspdMerid
ax, hcbar, im = wp.plot_time_height(ax=ax,
wspd=wspdMerid,
time=time,
height=hgt,
spd_range=[0, 30],
spd_delta=2,
cmap='jet',
topdf = False
case = range(13, 14)
res = 'coarse'
o = 'case{}_total_wind_{}.pdf'
t = 'Total wind speed - {} resolution - Case {} - Date: {}'
for c in case:
''' creates plot with seaborn style '''
with sns.axes_style("white"):
scale = 0.8
f, ax1 = plt.subplots(figsize=(11 * scale, 8.5 * scale))
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
surface=True,
case=str(c),
homedir=homedir)
wspdMerid = -wspd * cosd(wdir)
wp.plot_colored_staff(ax=ax1,
wspd=wspdMerid,
wdir=wdir,
time=time,
height=hgt,
spd_range=[0, 36],
spd_delta=2,
vdensity=0,
hdensity=0,
cmap='nipy_spectral',
axes = range(2)
axes[0] = plt.subplot(gs0[0],gid='(a) 23-24Jan01')
axes[1] = plt.subplot(gs0[1],gid='(b) 17Feb01')
labend={3:'25\n00',
7: '18\n08',
}
for c, ax in zip(case, axes):
out = wp.make_arrays2(resolution=res,
add_surface=True,
case=str(c),
interp_hgts=np.linspace(0.160, 3.74, 40))
wspd, wdir, time, hgt = out
if ax.get_gid() == '(a) 23-24Jan01':
cbar = ax
cbarinvi=False
else:
cbar = True
cbarinvi=True
''' wind speed target '''
ucomp = -wspd*sind(wdir)
vcomp = -wspd*cosd(wdir)
import Windprof2 as wp
import matplotlib.pyplot as plt
# import numpy as np
fig, axes = plt.subplots(3, 3, figsize=(11, 9), sharex=True, sharey=True)
axes = axes.flatten()
wd_lim_surf = 125
wd_lim_aloft = 170
mAGL, color = [120, 'navy']
# mAGL,color=[500,'green']
for c, ax in zip(range(12, 13), axes):
wspd, wdir, time, hgt = wp.make_arrays(
resolution='coarse', surface=True, case=str(c))
wp.plot_scatter2(ax=ax, wdir=wdir, hgt=hgt, time=time, mAGL=mAGL,
lim_surf=wd_lim_surf, lim_aloft=wd_lim_aloft, color=color)
ax.text(0., 0.05, 'Case '+str(c).zfill(2), transform=ax.transAxes)
axes[0].text(
0, 1.05, 'Altitude: '+str(mAGL) + 'm AGL', transform=axes[0].transAxes)
axes[6].set_xlabel('wind direction surface')
axes[6].text(wd_lim_surf, -20, str(wd_lim_surf), ha='center')
axes[6].text(0, -20, '0', ha='center')
axes[0].set_ylabel('wind direction aloft')
axes[0].text(380, wd_lim_aloft, str(wd_lim_aloft), va='center', rotation=90)
axes[0].text(380, 0, '0', va='center', rotation=90)
plt.subplots_adjust(bottom=0.05, top=0.95, hspace=0.05, wspace=0.05)
fig.delaxes(axes[7])
fig.delaxes(axes[8])
14:{'tta':[None,None], 'xpol':[0.58,0.41]}
}
labend={8:'15\n00',
9: '24\n00',
10:'17\n00',
11:'11\n00',
12:'04\n00',
13:'19\n00',
14:'27\n00'
}
for c, ax in zip(case, axes):
wspd, wdir, time, hgt = wp.make_arrays2(resolution=res,
surface=True,
case=str(c),
homedir=homedir)
if c == 14:
cbar = ax
else:
cbar = False
wspdMerid=-wspd*cosd(wdir);
ax, hcbar = wp.plot_time_height(ax=ax,
wspd=wspdMerid,
time=time, height=hgt,
spd_range=[0, 30], spd_delta=4,
cmap='nipy_spectral',
cbar=cbar
# surface=True,
# case=str(case),
# period=False)
# wp.plot_scatter(wdir=wdir,hgt=hgt,title='Case '+str(case).zfill(2))
# plt.show(block=False)
fig, axes = plt.subplots(5,3, figsize=(11,15), sharex=True, sharey=True)
axes=axes.flatten()
vline=130
hline=170
mAGL,color=[120,'navy']
# mAGL,color=[500,'green']
for c, ax in zip(range(1,15), axes):
wspd,wdir,time,hgt = wp.make_arrays(resolution='fine', surface=True,
case=str(c),period=False)
wp.plot_scatter2(ax=ax,wdir=wdir,hgt=hgt,mAGL=mAGL,vline=vline,hline=hline,color=color)
ax.text(0.,0.05,'Case '+str(c).zfill(2),transform=ax.transAxes)
axes[0].text(0,1.05,'Altitude: '+str(mAGL) +'m AGL',transform=axes[0].transAxes)
axes[13].set_xlabel('wind direction surface')
axes[13].text(vline,-20,str(vline),ha='center')
axes[13].text(0,-20,'0',ha='center')
axes[6].set_ylabel('wind direction aloft')
axes[6].text(380,hline,str(hline),va='center',rotation=90)
axes[6].text(380,0,'0',va='center', rotation=90)
plt.subplots_adjust(bottom=0.05,top=0.95,hspace=0.05,wspace=0.05)
fig.delaxes(axes[-1])
plt.show(block=False)