def test_newpres():
gp_0740=read_rays.construct_lassen_scan(path='/bm/gdata/scollis/gunn_pt/20060122_074001/')
ber_0740=read_rays.construct_uf_scan(path='/bm/gdata/scollis/berrimah/20060122_074003/')
ber_loc=[-12.457, 130.925]
gp_loc= [-12.2492, 131.0444]
ldict={'lat_0':gp_loc[0], 'lon_0':gp_loc[1],'llcrnrlat':-13.0, 'llcrnrlon':130.2, 'urcrnrlat':-12.0 , 'urcrnrlon':131.2, 'lat_ts':gp_loc[0]}
az_scan=0
pres.plot_ppi(ber_0740[az_scan], 'CZ', radar_loc=ber_loc, loc_dict=ldict, fig_name='ber_cz_ppi.png')
pres.plot_ppi(gp_0740[az_scan], 'CZ', radar_loc=gp_loc, loc_dict=ldict, fig_name='gp_cz_ppi.png')
pres.plot_ppi(ber_0740[az_scan], 'VR', radar_loc=ber_loc, loc_dict=ldict, fig_name='ber_vr_ppi.png')
pres.plot_ppi(gp_0740[az_scan], 'VR', radar_loc=gp_loc, loc_dict=ldict, fig_name='gp_vr_ppi.png')
disp=mathematics.corner_to_point(gp_loc, ber_loc)
xar=linspace(-50.,50., 100)*1000.0
yar=linspace(-50.,50., 100)*1000.0
lev=1000.0
lstr="%(lev)05d" %{'lev':lev}
pref_dir='20062201_0740_caps/'
cap_gp_vr=radar_to_cart.make_cappi(gp_0740, xar, yar, lev, 'VR')
cap_ber_vr=radar_to_cart.make_cappi(ber_0740, xar-disp[0], yar-disp[1], lev, 'VR')
pres.plot_cappi(xar,yar,cap_gp_vr,gp_0740[0], parm='VR', fig_name=pref_dir+'gp_cappi_vr_'+lstr+'.png', loc_dict=ldict, radar_loc=gp_loc)
pres.plot_cappi(xar,yar,cap_ber_vr,ber_0740[0], parm='VR', fig_name=pref_dir+'ber_cappi_vr_'+lstr+'.png', loc_dict=ldict, radar_loc=gp_loc)
#cap_gp_test=radar_to_cart.make_cappi_testmode(gp_0740, xar, yar, lev, 'VR')
#plot_cappi(xar,yar,cap_gp_test,ber_0740[0], parm='TEST', fig_name='test.png', loc_dict=ldict, radar_loc=gp_loc)
gp_cube_vr=zeros([100,100,31], dtype=float)
ber_cube_vr=zeros([100,100,31], dtype=float)
levs=linspace(500, 10500, 31)
xar=linspace(-50.,50., 100)*1000.0
yar=linspace(-50.,50., 100)*1000.0
for i in range(31):
gp_cap_vr=radar_to_cart.make_cappi(gp_0740, xar, yar, levs[i], 'CZ')
gp_cube_vr[:,:,i]=gp_cap_vr
ber_cap_vr=radar_to_cart.make_cappi(ber_0740, xar-disp[0], yar-disp[1], levs[i], 'CZ')
ber_cube_vr[:,:,i]=ber_cap_vr
for i in range(31):
lstr="%(lev)05d" %{'lev':levs[i]}
pres.plot_cappi(xar,yar,gp_cube_vr[:,:,i],gp_0740[0], parm='CZ', fig_name=pref_dir+'gp_cappi_cz_'+lstr+'.png', loc_dict=ldict, radar_loc=gp_loc)
pres.plot_cappi(xar,yar,ber_cube_vr[:,:,i],ber_0740[0], parm='CZ', fig_name=pref_dir+'ber_cappi_cz_'+lstr+'.png', loc_dict=ldict, radar_loc=gp_loc)
print 'Done', i, ' of 31'
def radar_to_winds(datestr, **kwargs):
#check to see if we have the radar files
#check to see if there are deailased files
#kwargs={}
loud=kwargs.get('loud', False)
#datestr='200601220700'
ini_fname=kwargs.get('ini_fname', os.getenv('HOME')+'/bom_mds/bom_mds.ini')
dateobj=num2date(datestr2num(datestr))
ini_fname=kwargs.get('ini_fname', os.getenv('HOME')+'/bom_mds/bom_mds.ini')
ini_dict=parse_ini.parse_ini(ini_fname)
radar1_deal_list=os.listdir(ini_dict['radar1_path'])
radar2_deal_list=os.listdir(ini_dict['radar2_path'])
radar1_raw_list=os.listdir(ini_dict['radar1_raw_path'])
radar2_raw_list=os.listdir(ini_dict['radar2_raw_path'])
radar1_target=ini_dict['radar1_prefix']+std_datestr(dateobj, ini_dict['radar1_type'])
radar2_target=ini_dict['radar2_prefix']+std_datestr(dateobj, ini_dict['radar2_type'])
poss_deal_files1=[]
for item in radar1_deal_list:
if radar1_target in item: poss_deal_files1.append(item)
if len(poss_deal_files1)==0:
poss_raw_files1=[]
print "No dealiased files found... Dealiasing"
for item in radar1_raw_list:
if radar1_target in item: poss_raw_files1.append(item)
if len(poss_raw_files1)==0:
#print "no files found"
raise IOError, 'Radar 2 File not there'
#return
else:
print "Dealiasing "+poss_raw_files1[0]
radar1_filename=dealias.dealias_arb(poss_raw_files1[0], ini_dict['radar1_type'], ini_dict['radar1_raw_path'], ini_dict['radar1_path'], ini_dict['radar1_prefix'])
else:
radar1_filename=poss_deal_files1[0]
poss_deal_files2=[]
for item in radar2_deal_list:
if radar2_target in item: poss_deal_files2.append(item)
if len(poss_deal_files2)==0:
poss_raw_files2=[]
print "No dealiased files found... Dealiasing"
for item in radar2_raw_list:
if radar2_target in item: poss_raw_files2.append(item)
if len(poss_raw_files2)==0:
#print "no files found"
raise IOError, 'Radar 2 File not there'
else:
radar2_filename=dealias.dealias_arb(poss_raw_files2[0], ini_dict['radar2_type'], ini_dict['radar2_raw_path'], ini_dict['radar2_path'], ini_dict['radar2_prefix'])
else:
radar2_filename=poss_deal_files2[0]
if loud: print "Loading radar file 1"
if 'radar1_path' in ini_dict.keys():
radar1=read_radar.load_radar(ini_dict['radar1_path']+radar1_filename)
else:
radar1=read_radar.load_radar(radar1_filename)
if loud: print "Loading radar file 2"
if 'radar2_path' in ini_dict.keys():
radar2=read_radar.load_radar(ini_dict['radar2_path']+radar2_filename)
else:
radar2=read_radar.load_radar(radar2_filename)
pres.plot_ppi(radar2[2],'VE', fig_path='/scratch/bom_mds_dumps/', fig_name='radar2_ve.png')
pres.plot_ppi(radar2[2],'CZ', fig_path='/scratch/bom_mds_dumps/', fig_name='radar2_cz.png')
cappi_z_bounds=ini_dict.get('cappi_z_bounds', [500,15000])
cappi_xy_bounds=ini_dict.get('cappi_xy_bounds', [-50000, 50000])
cappi_resolution=ini_dict.get('cappi_resolution', [100, 40])
levs=linspace(cappi_z_bounds[0], cappi_z_bounds[1], cappi_resolution[1])
xar=linspace(cappi_xy_bounds[0], cappi_xy_bounds[1], cappi_resolution[0])
yar=linspace(cappi_xy_bounds[0], cappi_xy_bounds[1], cappi_resolution[0])
displace=mathematics.corner_to_point(radar1[0]['radar_loc'], radar2[0]['radar_loc'])
if loud: print "Cappi-ing radar 1"
#radar1_cube_=radar_to_cart.make_cube(radar1, xar, yar, levs)
radar1_cube=cappi_v2.make_cube_all(radar1,xar, yar,levs)
#max_el=array([scan['Elev'][0] for scan in radar1]).max()
#radar1_cube=cappi_v2.blend(radar1_cube_v,radar1_cube_h, max_el,loud=True)
if loud: print "Cappi-ing radar 2"
#radar2_cube_v=radar_to_cart.make_cube(radar2, xar, yar, levs, displacement=displace)
radar2_cube=cappi_v2.make_cube_all(radar2,xar, yar,levs, displacement=displace)
#max_el=array([scan['Elev'][0] for scan in radar2]).max()
#radar2_cube=cappi_v2.blend(radar2_cube_v,radar2_cube_h, max_el,loud=True)
#radar2_cube_v=radar_to_cart.make_cube(radar2, xar, yar, levs, displacement=displace)
cube_fname=ini_dict['cube_path']+'cappi_'+std_datestr(radar1_cube['date'], "uf")+'.nc'
#netcdf_utis.save_data_cube(radar1_cube, radar2_cube, cube_fname)
#Initial Guess
req=[ 'alt(m)', 'wspd(m/s)', 'wdir(degs)', 'tdry(degs)','press(hPa)' ]
first_sonde,second_sonde = read_sounding.get_two_best_conc_sondes(datestr, req_vars=req)
interp_sonde=read_sounding.interp_sonde_time(first_sonde, second_sonde, dateobj, levs)
if ini_dict['initial_guess']=='sonde':
#using a sonde for out initial gues
u_ig=ones(radar1_cube['CZ'].shape, dtype=float)
v_ig=ones(radar1_cube['CZ'].shape, dtype=float)
w_ig=zeros(radar1_cube['CZ'].shape, dtype=float)
for k in range(len(levs)):
u_ig[:,:,k]=1.0*u_ig[:,:,k]*interp_sonde['wspd(m/s)'][k]*sin(pi*interp_sonde['wdir(degs)'][k]/180.0)
v_ig[:,:,k]=1.0*v_ig[:,:,k]*interp_sonde['wspd(m/s)'][k]*cos(pi*interp_sonde['wdir(degs)'][k]/180.0)
else:
u_ig=zeros(radar1_cube['CZ'].shape, dtype=float)
v_ig=zeros(radar1_cube['CZ'].shape, dtype=float)
w_ig=zeros(radar1_cube['CZ'].shape, dtype=float)
Re=6371.0*1000.0
rad_at_radar=Re*sin(pi/2.0 -abs(radar1[0]['radar_loc'][0]*pi/180.0))#ax_radius(float(lat_cpol), units='degrees')
lons=radar1[0]['radar_loc'][1]+360.0*xar/(rad_at_radar*2.0*pi)
lats=radar1[0]['radar_loc'][0] + 360.0*yar/(Re*2.0*pi)
#Masking
angs=array(propigation.make_lobe_grid(radar2[0]['radar_loc'], radar1[0]['radar_loc'], lats,lons))
mywts=met.make_mask_bad1(radar2_cube, radar1_cube, angs, 1.0, 80.0)
print "Mean gp masked Velocity ", (radar1_cube['VE']*mywts).mean()
print "min gp masked Velocity ", (radar1_cube['VE']*mywts).min()
print "max gp masked Velocity ", (radar1_cube['VE']*mywts).max()
print "Mean Berrimah masked Velocity ", (radar2_cube['VE']*mywts).mean()
print "min Berrimah masked Velocity ", (radar2_cube['VE']*mywts).min()
print "max Berrimah masked Velocity ", (radar2_cube['VE']*mywts).max()
print "Mean gp masked CZ ", (radar1_cube['CZ']*mywts).mean()
print "min gp masked CZ ", (radar1_cube['CZ']*mywts).min()
print "max gp masked CZ ", (radar1_cube['CZ']*mywts).max()
print "Mean Berrimah masked CZ ", (radar2_cube['CZ']*mywts).mean()
print "min Berrimah masked CZ ", (radar2_cube['CZ']*mywts).min()
print "max Berrimah masked CZ ", (radar2_cube['CZ']*mywts).max()
print "Number of masked points", (mywts.shape[0]*mywts.shape[1]*mywts.shape[2])-mywts.sum()
print "Number of unmasked points ", mywts.sum()
print "**********************FALLSPEED INFO****************************"
#def terminal_velocity(refl, temps, levs, display=False):
tdry=interp_sonde['tdry(degs)']
pressure=interp_sonde['press(hPa)']
dummy=met.terminal_velocity(radar1_cube['CZ']*mywts, tdry, radar1_cube['levs'], display=True)
print "**********************FALLSPEED INFO****************************"
f=0.0
X=[u_ig,v_ig,w_ig]
G,F,X=grad_conj_solver_3d.gracon_3d_packaged(X ,radar2_cube, radar1_cube, mywts, interp_sonde)
u_array,v_array,w_array=X
radar1_cube.update({'u_array':u_array, 'v_array':v_array, 'w_array':w_array})
netcdf_utis.save_data_cube(radar1_cube, radar2_cube, '/data/cube_data/'+std_datestr(dateobj, "uf") +'_winds.nc')
radar1=read_radar.load_radar(ini_dict['radar1_path']+radar1_filename)
else:
radar1=read_radar.load_radar(radar1_filename)
if loud: print "Loading radar file 2"
if 'radar2_path' in ini_dict.keys():
radar2=read_radar.load_radar(ini_dict['radar2_path']+radar2_filename)
else:
radar2=read_radar.load_radar(radar2_filename)
pres.plot_ppi(radar2[2],'VE', fig_path='/scratch/bom_mds_dumps/', fig_name='radar2_ve.png')
pres.plot_ppi(radar2[2],'CZ', fig_path='/scratch/bom_mds_dumps/', fig_name='radar2_cz.png')
cappi_z_bounds=ini_dict.get('cappi_z_bounds', [500,15000])
cappi_xy_bounds=ini_dict.get('cappi_xy_bounds', [-50000, 50000])
cappi_resolution=ini_dict.get('cappi_resolution', [100, 40])
levs=linspace(cappi_z_bounds[0], cappi_z_bounds[1], cappi_resolution[1])
xar=linspace(cappi_xy_bounds[0], cappi_xy_bounds[1], cappi_resolution[0])
yar=linspace(cappi_xy_bounds[0], cappi_xy_bounds[1], cappi_resolution[0])
displace=mathematics.corner_to_point(radar1[0]['radar_loc'], radar2[0]['radar_loc'])
if loud: print "Cappi-ing radar 1"
#radar1_cube_=radar_to_cart.make_cube(radar1, xar, yar, levs)
radar1_cube=cappi_v2.make_cube_all(radar1,xar, yar,levs)
#max_el=array([scan['Elev'][0] for scan in radar1]).max()
#radar1_cube=cappi_v2.blend(radar1_cube_v,radar1_cube_h, max_el,loud=True)