def test_radar_view():
lats=linspace(-13.0, -11.5, 40)
lons=linspace(130., 132., 40)
ber_loc=[-12.4, 130.85] #location of Berrimah radar
gp_loc=[-12.2492, 131.0444]#location of CPOL at Gunn Point
h=2.5*1000.0
t0=systime()
i_a, j_a, k_a=propigation.unit_vector_grid(lats, lons, h, gp_loc)
print "unit_vector_compute took ", systime()-t0, " seconds"
fw=0.1#degrees
m_bump=5.0
#b1=simul_winds.speed_bump(lats, lons, [-12.0, 131.0], fw)*m_bump
#b2=-1.0*simul_winds.speed_bump(lats, lons, [-12.0, 131.1], fw)*m_bump
u,v=simul_winds.unif_wind(lats, lons, 5.0, 75.0)
up,vp=array(simul_winds.vortex(lats, lons, [-12.5, 131.1], fw))*m_bump
#up=u+(b1-b2)
#vp=v-(b1-b2)
w=v*0.0
v_r=i_a*(up+u)+j_a*(vp+v)+k_a*w
f=figure()
mapobj=pres.generate_darwin_plot()
pres.contour_vr(mapobj,lats, lons, v_r)
savefig(os.getenv('HOME')+'/bom_mds/output/test_radar_view_gp.png')
close(f)
f=figure()
mapobj=pres.generate_darwin_plot()
pres.quiver_contour_winds(mapobj, lats, lons, (up+u),(vp+v))
savefig(os.getenv('HOME')+'/bom_mds/output/test_pert2.png')
close(f)
def test_gracon():
#setup
noise_level=0.0#m/s
nx=40
ny=40
fw=0.1
m_bump=10.00
t0=systime()
lats=linspace(-13.5, -12.0, 40)
lons=linspace(130.5, 131.5, 40)
ber_loc=[-12.4, 130.85] #location of Berrimah radar
gp_loc=[-12.2492, 131.0444]#location of CPOL at Gunn Point
h=2.5*1000.0
print 'calculating berimah UV', systime()-t0
i_ber, j_ber, k_ber=propigation.unit_vector_grid(lats, lons, h, ber_loc)
print 'calculating gp UV', systime()-t0
i_gp, j_gp, k_gp=propigation.unit_vector_grid(lats, lons, h, gp_loc)
#make winds
u,v=simul_winds.unif_wind(lats, lons, 10.0, 75.0)
up,vp=array(simul_winds.vortex(lats, lons, [-12.5, 131.1], fw))*m_bump
#make V_r measurements
vr_ber=i_ber*(up+u)+j_ber*(vp+v) + (random.random([nx,ny])-0.5)*(noise_level*2.0)
vr_gp=i_gp*(up+u)+j_gp*(vp+v)+ (random.random([nx,ny])-0.5)*(noise_level*2.0)
#try to reconstruct the wind field
igu, igv= simul_winds.unif_wind(lats, lons, 0.0, 90.0)
gv_u=zeros(u.shape)
gv_v=zeros(v.shape)
f=0.0
print igu.mean()
angs=array(propigation.make_lobe_grid(ber_loc, gp_loc, lats,lons))
wts=zeros(angs.shape, dtype=float)+1.0
#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[i,j]=1.0
print 'Into fortran'
gv_u,gv_v,f,u_array,v_array = gracon_vel2d.gracon_vel2d(gv_u,gv_v,f,igu,igv,i_ber,j_ber,i_gp,j_gp,vr_ber,vr_gp,wts, nx=nx,ny=ny)
print u_array.mean()
print f
bnds=[0.,20.]
f=figure()
mapobj=pres.generate_darwin_plot()
pres.quiver_contour_winds(mapobj, lats, lons, (up+u),(vp+v), bounds=bnds)
savefig(os.getenv('HOME')+'/bom_mds/output/orig_winds_clean.png')
close(f)
f=figure()
mapobj=pres.generate_darwin_plot()
pres.quiver_contour_winds(mapobj, lats, lons, (wts*u_array +0.001),(wts*v_array +0.001), bounds=bnds)
savefig(os.getenv('HOME')+'/bom_mds/output/recon_winds_clean.png')
close(f)
f=figure()
mapobj=pres.generate_darwin_plot()
pres.quiver_contour_winds(mapobj, lats, lons, (wts*u_array - (up+u)),(wts*v_array -(vp+v)))
savefig(os.getenv('HOME')+'/bom_mds/output/errors_clean.png')
close(f)
def simple_reconstruction_3d_pytest(tim, lvl_str, use_guess):
lvl=int(lvl_str)
ber, gp=netcdf_utis.load_cube('/bm/gdata/scollis/cube_data/20060122_'+tim+'_ver_hr_big.nc')
print gp['levs'][lvl]
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
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']
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
f=0.0
gv_u=zeros(ber['CZ'].shape, dtype=float)
gv_v=zeros(ber['CZ'].shape, dtype=float)
wts=mask*mask_vel_ber*wts_ang
gu,gv,f= grad_conj_solver_plus_plus.meas_cost(gv_u, gv_v, f, igu, igv, ber['i_comp'], ber['j_comp'], gp['i_comp'], gp['j_comp'], ber['VR'], gp['VR'], mywts)
print "Mean U gradient", gu.mean(), "gv mean", gv.mean(), "F ", f
for i in range(len(gp['levs'])):
print "U,V ", (igu[:,:,i]).sum()/mywts[:,:,i].sum(), (igv[:,:,i]).sum()/mywts[:,:,i].sum()
#gv_u,gv_v,cost = vel_2d_cost(gv_u,gv_v,cost,u_array,v_array,i_cmpt_r1,j_cmpt_r1,i_cmpt_r2,j_cmpt_r2,vr1,vr2,weights,nx=shape(gv_u,0),ny=shape(gv_u,1))
print gracon_vel2d.vel_2d_cost(gv_u[:,:,i]*0.0,gv_v[:,:,i]*0.0,0.0,igu[:,:,i],igv[:,:,i],ber['i_comp'][:,:,i], ber['j_comp'][:,:,i], gp['i_comp'][:,:,i], gp['j_comp'][:,:,i], ber['VR'][:,:,i], gp['VR'][:,:,i],mywts[:,:,i])[2]
gv_u,gv_v,f,u_array,v_array = grad_conj_solver_plus_plus.gracon_vel2d_3d( gv_u, gv_v, f, igu, igv, ber['i_comp'], ber['j_comp'], gp['i_comp'], gp['j_comp'], ber['VR'], gp['VR'], mywts)#, nx=nx, ny=ny, nz=nz)
gp.update({'u_array': u_array, 'v_array':v_array})
netcdf_utis.save_data_cube(ber, gp, '/bm/gdata/scollis/cube_data/20060122_'+tim+'_winds_ver1.nc', gp['zero_loc'])
plotit=True
if plotit:
for lvl in range(len(gp['levs'])):
print lvl
f=figure()
mapobj=pres.generate_darwin_plot(box=[130.8, 131.2, -12.4, -12.0])
diff=gp['VR']-(u_array*gp['i_comp']+ v_array*gp['j_comp'])
gp.update({'diff':diff})
pres.reconstruction_plot(mapobj, lats, lons, gp, lvl, 'diff',u_array[:,:,lvl],v_array[:,:,lvl], angs, mywts[:,:,lvl])
#pres.quiver_contour_winds(mapobj, lats, lons, (wts*u_array).clip(min=-50, max=50),(wts*v_array).clip(min=-50, max=50))
t1='Gunn Point CAPPI (dBZ) and reconstructed winds (m/s) at %(lev)05dm \n 22/01/06 ' %{'lev':gp['levs'][lvl]}
title(t1+tim)
ff=os.getenv('HOME')+'/bom_mds/output/recons_22012006/real_%(lev)05d_' %{'lev':gp['levs'][lvl]}
savefig(ff+tim+'_2d_3d.png')
close(f)
def test_uniform_winds():
f=figure()
lats=linspace(-13.0, -11.5, 20)
lons=linspace(130., 132., 20)
u,v=simul_winds.unif_wind(lats, lons, 10.0, 45.0)
mapobj=pres.generate_darwin_plot()
pres.quiver_winds(mapobj, lats, lons, u,v)
savefig(os.getenv('HOME')+'/bom_mds/output/test_uniform.png')
close(f)
def test_pert_winds():
f=figure()
lats=linspace(-13.0, -11.5, 20)
lons=linspace(130., 132., 20)
u,v=simul_winds.unif_wind(lats, lons, 5.0, 45.0)
mapobj=pres.generate_darwin_plot()
fw=0.2#degrees
m_bump=15.0
b1=simul_winds.speed_bump(lats, lons, [-12.0, 131.0], fw)*m_bump
b2=-1.0*simul_winds.speed_bump(lats, lons, [-12.0, 131.2], fw)*m_bump
pres.quiver_contour_winds(mapobj, lats, lons, u+(b1+b2),v-(b1+b2))
savefig(os.getenv('HOME')+'/bom_mds/output/test_pert.png')
close(f)
def test_angle_grid2():
lats=linspace(-13.0, -11.5, 100)
lons=linspace(130., 132., 100)
ber_loc=[-12.4, 130.85] #location of Berrimah radar
gp_loc=[-12.2492, 131.0444]#location of CPOL at Gunn Point
h=10.0*1000.0
t0=systime()
i_a, j_a, k_a=propigation.unit_vector_grid(lats, lons, h, ber_loc)
print "compute took ", systime()-t0, " seconds"
f=figure()
mapobj=pres.generate_darwin_plot()
pres.contour_comp(mapobj,lats, lons, k_a)
savefig(os.getenv('HOME')+'/bom_mds/output/test_angs.png')
close(f)
def simple_reconstruction(tim, lvl_str):
#load data
srm=array([15.0, 5.0])/sqrt(2.0)
ber, gp=netcdf_utis.load_cube('/bm/gdata/scollis/cube_data/20060122_'+tim+'_ver1.nc')
lvl=int(lvl_str)
print gp['levs'][lvl]
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]
angs=array(propigation.make_lobe_grid(ber_loc, gp_loc, lats,lons))
wts_ang=zeros(angs.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
#create a weighting grid
mask_reflect=10.0#dBZ
mask=(gp['CZ'][:,:,lvl]/mask_reflect).round().clip(min=0., max=1.0)
mask_vel_ber=(ber['VR'][:,:,lvl]+100.).clip(min=0., max=1.)
#run gracon
print 'Into fortran'
nx,ny=ber['CZ'][:,:,lvl].shape
f=0.0
gv_u=zeros(ber['CZ'][:,:,lvl].shape, dtype=float)
gv_v=zeros(ber['CZ'][:,:,lvl].shape, dtype=float)
igu=ones(ber['CZ'][:,:,lvl].shape, dtype=float)*srm[0]
igv=ones(ber['CZ'][:,:,lvl].shape, dtype=float)*srm[1]
gv_u,gv_v,f,u_array,v_array = gracon_vel2d.gracon_vel2d(gv_u,gv_v,f,igu,igv,ber['i_comp'][:,:,lvl],ber['j_comp'][:,:,lvl],gp['i_comp'][:,:,lvl],gp['j_comp'][:,:,lvl], ber['VR'][:,:,lvl],gp['VR'][:,:,lvl],mask*mask_vel_ber*wts_ang, nx=nx,ny=ny)
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)
wts=mask*mask_vel_ber*wts_ang
f=figure()
mapobj=pres.generate_darwin_plot(box=[130.8, 131.2, -12.4, -12.0])
pres.reconstruction_plot(mapobj, lats, lons, gp, lvl, 'CZ',u_array,v_array, angs, wts)
#pres.quiver_contour_winds(mapobj, lats, lons, (wts*u_array).clip(min=-50, max=50),(wts*v_array).clip(min=-50, max=50))
t1='Gunn Point CAPPI (dBZ) and reconstructed winds (m/s) at %(lev)05dm \n 22/01/06 ' %{'lev':gp['levs'][lvl]}
title(t1+tim)
ff=os.getenv('HOME')+'/bom_mds/output/recons_22012006/real_%(lev)05d_' %{'lev':gp['levs'][lvl]}
savefig(ff+tim+'_2d.png')
close(f)
def test_mapping():
f=figure()
mapobj=pres.generate_darwin_plot()
savefig(os.getenv('HOME')+'/bom_mds/output/test_mapping.png')
close(f)
def simple_reconstruction_3d(tim, lvl_str):
#load data
u=0
l=10
ui=zeros([l],dtype=float)
vi=zeros([l],dtype=float)
#srm=0.0*array([1.0, 5.0])/sqrt(2.0)
ber, gp=netcdf_utis.load_cube('/bm/gdata/scollis/cube_data/20060122_'+tim+'_ver1.nc')
for i in range(l):
ui[i], vi[i]=simple_reco(ber,gp,i)
lvl=int(lvl_str)
print gp['levs'][lvl]
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]
angs=array(propigation.make_lobe_grid(ber_loc, gp_loc, lats,lons))
wts_ang=zeros(gp['CZ'][:,:,u:l].shape, dtype=float)
for i in range(wts_ang.shape[0]):
for j in range(wts_ang.shape[1]):
for k in range(wts_ang.shape[2]):
if (angs[i,j] < 150.0) and (angs[i,j] > 30.0): wts_ang[i,j,k]=1.0
#create a weighting grid
mask_reflect=12.0#dBZ
mask=(ber['CZ'][:,:,u:l]/mask_reflect).round().clip(min=0., max=1.0)
mask_vel_ber=(ber['VR'][:,:,u:l]+100.).clip(min=0., max=1.)
#run gracon
print 'Into fortran'
nx,ny,nz=ber['CZ'][:,:,u:l].shape
print nx,ny,nz
f=0.0
gv_u=zeros(ber['CZ'][:,:,u:l].shape, dtype=float)
gv_v=zeros(ber['CZ'][:,:,u:l].shape, dtype=float)
igu=ones(ber['CZ'][:,:,u:l].shape, dtype=float)
igv=ones(ber['CZ'][:,:,u:l].shape, dtype=float)
for i in range(len(ui)):
igu[:,:,i]=igu[:,:,i]*ui[i]
igv[:,:,i]=igu[:,:,i]*vi[i]
wts=mask*mask_vel_ber*wts_ang
#gv_u,gv_v,f,u_array,v_array = gracon_vel2d_3d(gv_u,gv_v,f,u_array,v_array,i_cmpt_r1,j_cmpt_r1,i_cmpt_r2,j_cmpt_r2,vr1,vr2,weights,nx=shape(gv_u,0),ny=shape(gv_u,1),nz=shape(gv_u,2))
gv_u,gv_v,f,u_array,v_array = gracon_vel2d_3d.gracon_vel2d_3d( gv_u, gv_v, f, igu, igv, ber['i_comp'][:,:,u:l], ber['j_comp'][:,:,u:l], gp['i_comp'][:,:,u:l], gp['j_comp'][:,:,u:l], ber['VR'][:,:,u:l], gp['VR'][:,:,u:l], mywts)#, nx=nx, ny=ny, nz=nz)
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)
f=figure()
mapobj=pres.generate_darwin_plot(box=[130.8, 131.2, -12.4, -12.0])
diff=gp['VR'][:,:,u:l]-(u_array*gp['i_comp'][:,:,u:l]+ v_array*gp['j_comp'][:,:,u:l])
gp.update({'diff':diff})
pres.reconstruction_plot(mapobj, lats, lons, gp, lvl, 'diff',u_array[:,:,lvl],v_array[:,:,lvl], angs, wts[:,:,lvl])
#pres.quiver_contour_winds(mapobj, lats, lons, (wts*u_array).clip(min=-50, max=50),(wts*v_array).clip(min=-50, max=50))
t1='Gunn Point CAPPI (dBZ) and reconstructed winds (m/s) at %(lev)05dm \n 22/01/06 ' %{'lev':gp['levs'][lvl]}
title(t1+tim)
ff=os.getenv('HOME')+'/bom_mds/output/recons_22012006/real_%(lev)05d_' %{'lev':gp['levs'][lvl]}
savefig(ff+tim+'_2d_3d.png')
close(f)