Esempio n. 1
0
def pres_winds(datestr,  **kwargs): #latstr, lonstr,
	ini_fname=kwargs.get('ini_fname', os.getenv('HOME')+'/bom_mds/bom_mds.ini')
	ini_dict=parse_ini.parse_ini(ini_fname)
	parm=kwargs.get('parm','CZ')
	dateobj=num2date(datestr2num(datestr))
	tim_date=num2date(datestr2num(datestr))
	radar1, radar2=netcdf_utis.load_cube('/data/cube_data/'+std_datestr(tim_date)+'_winds.nc')
	print radar1['radar_name']
	print radar2['radar_name']
	lvl=kwargs.get('lvl',3000.0)
	lvl_num=argsort(abs(radar1['levs']-lvl))[0]
	print "Level_num=", lvl_num
	Re=6371.0*1000.0
	rad_at_radar=Re*sin(pi/2.0 -abs(radar1['radar_loc'][0]*pi/180.0))
	lons=radar1['radar_loc'][1]+360.0*radar1['xar']/(rad_at_radar*2.0*pi)
	lats=radar1['radar_loc'][0] + 360.0*radar1['yar']/(Re*2.0*pi)	
	ber_loc=[-12.457, 130.925]
	gp_loc=[-12.2492,  131.0444]
	angs=array(propigation.make_lobe_grid(radar2['radar_loc'], radar1['radar_loc'], lats,lons))
	mywts=met.make_mask_bad1(radar2, radar1, angs, 1.0, 80.0)
	if ini_dict['cross'][0]=='max' or ini_dict['cross'][1]=='max':
		 #maskedcz=radar1['CZ'][:,:,lvl_num]*mywts[:,:,lvl_num]
		 #i,j=mathematics.where_closest_2d(maskedcz.max(), maskedcz)
		 maskedw=radar1['w_array'][:,:,7]*mywts[:,:,7]
		 i,j=mathematics.where_closest_2d(maskedw.max(), maskedw)
		 print i,j
		 lat=lats[j[0]]
		 lon=lons[i[0]]
		 print "Max w at ", lat, lon 
	else:
		 lon=ini_dict['cross'][1]#float(lonstr)
		 lat=ini_dict['cross'][0]#float(latstr)
	f=figure()
	alat, alon, alvl=pres.plot_slices(lat, lon, lvl, radar1, lats, lons, radar1['levs'], radar1['u_array'], radar1['v_array'], radar1['w_array'], angs, mywts, par=parm, w_mag=1.0,box=ini_dict['pres_box'], bquiver=[0.05, 0.75], ksp=0.05,qscale=ini_dict['qscale'])
	t1='Gunn Point reflectivity (dBZ) and reconstructed winds (m/s)\n sliced at %(alat)2.2fS and %(alon)3.2fE and %(alvl)d Metres on  %(day)02d/%(mon)02d/%(yr)04d at ' %{'day':tim_date.day, 'mon':tim_date.month, 'yr':tim_date.year,'alat':abs(alat), 'alon':alon, 'alvl':alvl}
	t2=" %(HH)02d%(MM)02dZ" %{'HH':tim_date.hour, 'MM':tim_date.minute}
	f.text( .1, .92, t1+t2) 
	inte_part=1000*(float(int(lat))-lat)
	print  {'alat':abs(alat), 'alon':alon, 'alvl':alvl}
	#ff=os.getenv('HOME')+'/bom_mds/output/recons_'+std_datestr(tim_date)[0:-5]+'/slicer3_%(alat)2.02f_%(alon)3.02f_%(alvl)05d_' %{'alat':abs(alat), 'alon':alon, 'alvl':alvl}
	ff=os.getenv('HOME')+'/bom_mds/output/tests/slicer_'+std_datestr(tim_date)+'_%(alat)2.02f_%(alon)3.02f_%(alvl)05d_' %{'alat':abs(alat), 'alon':alon, 'alvl':alvl}
	print ff
	savefig(ff+t2+'.png', dpi=200)
	close(f)
Esempio n. 2
0
def recon(date_str, latstr, lonstr):
     use_guess='sonde'
     sonde_file='/bm/gdata/scollis/twpice/darwin.txt'
     #tim='1350'
     tim_date=num2date(datestr2num(date_str)) 
     ber, gp=netcdf_utis.load_cube('/bm/gdata/scollis/cube_data/'+std_datestr(tim_date)+'_deal.nc')
     sonde_list=read_sounding.read_sounding_within_a_day(sonde_file, tim_date)
     #launch_dates=[sonde['date_list'][0] for sonde in sonde_list]
     #launch_date_offset=[date2num(sonde['date_list'][0])- date2num(tim_date)  for sonde in sonde_list]
     #best_sonde=sonde_list[argsort(abs(array(launch_date_offset)))[0]]
     #print 'Time of radar: ', tim_date, ' Time of sonde_launch: ', best_sonde['date_list'][0], ' Time of sonde_termination: ', best_sonde['date_list'][-1]
     req=[ 'alt(m)',  'wspd(m/s)', 'tdry(degs)',  'wdir(degs)']	
     first_sonde, second_sonde=read_sounding.get_two_best_conc_sondes(date_str, req_vars=req)
     interp_sonde=read_sounding.interp_sonde_time(first_sonde, second_sonde, tim_date, gp['levs'])
     u_sonde=ones(gp['CZ'].shape, dtype=float)
     v_sonde=ones(gp['CZ'].shape, dtype=float)
     w_sonde=zeros(gp['CZ'].shape, dtype=float)
     for k in range(len(gp['levs'])):
	     u_sonde[:,:,k]=-1.0*u_sonde[:,:,k]*interp_sonde['wspd(m/s)'][k]*sin(pi*interp_sonde['wdir(degs)'][k]/180.0)
	     v_sonde[:,:,k]=-1.0*v_sonde[:,:,k]*interp_sonde['wspd(m/s)'][k]*cos(pi*interp_sonde['wdir(degs)'][k]/180.0)
     Re=6371.0*1000.0
     rad_at_radar=Re*sin(pi/2.0 -abs(gp['zero_loc'][0]*pi/180.0))#ax_radius(float(lat_cpol), units='degrees')
     lons=gp['zero_loc'][1]+360.0*gp['xar']/(rad_at_radar*2.0*pi)
     lats=gp['zero_loc'][0] + 360.0*gp['yar']/(Re*2.0*pi)	
     ber_loc=[-12.457, 130.925]
     gp_loc= [-12.2492,  131.0444]
     
     if use_guess=='none':
	  igu=ones(ber['CZ'].shape, dtype=float)*0.0
	  igv=ones(ber['CZ'].shape, dtype=float)*0.0
	  igw=ones(ber['CZ'].shape, dtype=float)*0.0
     elif use_guess=='sonde':
	  igu=u_sonde
	  igv=v_sonde
	  igw=w_sonde
     else:
	  ber_ig, gp_ig=netcdf_utis.load_cube(use_guess)
	  print gp_ig.keys()
	  igu=gp_ig['u_array']
	  igv=gp_ig['v_array']
	  igw=ones(ber['CZ'].shape, dtype=float)*0.0
     
     #mywts=ones(ber['CZ'].shape, dtype=float)
     angs=array(propigation.make_lobe_grid(ber_loc, gp_loc, lats,lons))
     #wts_ang=zeros(gp['CZ'][:,:,0].shape, dtype=float)
     #for i in range(angs.shape[0]):
     #    for j in range(angs.shape[1]):
     #		 if (angs[i,j] < 150.0) and (angs[i,j] > 30.0): wts_ang[i,j]=1.0
     #for lvl_num in range(len(gp['levs'])):
     #	  #create a weighting grid
     #	  mask_reflect=10.0#dBZ	
     #	  mask=(gp['CZ'][:,:,lvl_num]/mask_reflect).round().clip(min=0., max=1.0) 
     #	  mask_vel_ber=(ber['VR'][:,:,lvl_num]+100.).clip(min=0., max=1.)
     #	  mywts[:,:,lvl_num]=mask*mask_vel_ber*wts_ang	
     mywts=met.make_mask(ber, gp, angs, 1.0, 80.0)
     print "Mean gp masked Velocity ", (gp['VE']*mywts).mean()
     print "min gp masked Velocity ", (gp['VE']*mywts).min()
     print "max gp masked Velocity ", (gp['VE']*mywts).max()
     print "Mean Berrimah masked Velocity ", (ber['VE']*mywts).mean()
     print "min Berrimah masked Velocity ", (ber['VE']*mywts).min()
     print "max Berrimah masked Velocity ", (ber['VE']*mywts).max()
     print "Mean gp masked CZ ", (gp['CZ']*mywts).mean()
     print "min gp masked CZ ", (gp['CZ']*mywts).min()
     print "max gp masked CZ ", (gp['CZ']*mywts).max()
     print "Mean Berrimah masked CZ ", (ber['CZ']*mywts).mean()
     print "min Berrimah masked CZ ", (ber['CZ']*mywts).min()
     print "max Berrimah masked CZ ", (ber['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(gp['CZ']*mywts, tdry, gp['levs'], display=True)
     print "**********************FALLSPEED INFO****************************"
     #print 
     
     
     f=0.0
     X=[igu,igv,igw]
     G,F,X=grad_conj_solver_3d.gracon_3d_packaged(X ,ber, gp, mywts, interp_sonde)
     u_array,v_array,w_array=X 
     lvl=2500.0
     lvl_num=argsort(abs(gp['levs']-lvl))[0]
     print "Level_num=", lvl_num
     if latstr=='max' or lonstr=='max':
	     maskedcz=gp['CZ'][:,:,lvl_num]*mywts[:,:,lvl_num]
	     i,j=mathematics.where_closest_2d(maskedcz.max(), maskedcz)
	     print i,j
	     lat=lats[j[0]]
	     lon=lons[i[0]]
	     print "Max CZ at ", lat, lon 
     else:
	     lon=float(lonstr)
	     lat=float(latstr)
     f=figure()
     #(lat_sl, lon_sl, lvl, data_cube, lats, lons, levs, u, v, w, angs, mask, par='CZ', w_mag=2.0, **kwargs)
     alat, alon, alvl=pres.plot_slices(lat, lon, lvl, gp, lats, lons, gp['levs'], u_array, v_array, w_array, angs, mywts, par='CZ', w_mag=2.0,box=[130.5, 131.5, -12.7, -12.0], bquiver=[0.05, 0.75], ksp=0.05)
     t1='Gunn Point reflectivity (dBZ) and reconstructed winds (m/s, *2.0 for w)\n sliced at %(alat)2.2fS and %(alon)3.2fE and %(alvl)d Metres on 22/01/06 at ' %{'alat':abs(alat), 'alon':alon, 'alvl':alvl}
     t2=" %(HH)02d%(MM)02dZ" %{'HH':tim_date.hour, 'MM':tim_date.minute}
     f.text( .1, .92, t1+t2) 
     inte_part=1000*(float(int(lat))-lat)
     print  {'alat':abs(alat), 'alon':alon, 'alvl':alvl}
     ff=os.getenv('HOME')+'/bom_mds/output/recons_'+std_datestr(tim_date)[0:-5]+'/slicer3_%(alat)2.02f_%(alon)3.02f_%(alvl)05d_' %{'alat':abs(alat), 'alon':alon, 'alvl':alvl}
     print ff
     savefig(ff+t2+'.png', dpi=200)
     gp.update({'u_array':u_array, 'v_array':v_array, 'w_array':w_array})
     netcdf_utis.save_data_cube(ber, gp, '/bm/gdata/scollis/cube_data/'+std_datestr(tim_date)+'_winds.nc', gp_loc)
     close(f)