def bperp_btemp_master_slave(drsFiles=None):
from dateutil import parser
mresfiles = []
sresfiles = []
iresfiles = []
for f in drsFiles:
d = adore.drs2dict(f)
mresfiles.append(d['general']['m_resfile'].strip())
sresfiles.append(d['general']['s_resfile'].strip())
iresfiles.append(d['general']['i_resfile'].strip())
bperp = []
btemp = []
master = []
slave = []
for f in N.r_[0:len(mresfiles)]:
mobj = adore.dict2obj(adore.res2dict(mresfiles[f]))
sobj = adore.dict2obj(adore.res2dict(sresfiles[f]))
ires = adore.res2dict(iresfiles[f])
iobj = adore.dict2obj(ires)
master.append(parser.parse(mobj.readfiles.First_pixel_azimuth_time))
slave.append(parser.parse(sobj.readfiles.First_pixel_azimuth_time))
bperp.append(iobj.coarse_orbits.Bperp)
btemp.append(iobj.coarse_orbits.Btemp)
return bperp, btemp, master, slave
def bperp_btemp_master_slave(drsFiles=None):
from dateutil import parser
mresfiles=[]
sresfiles=[]
iresfiles=[]
for f in drsFiles:
d=adore.drs2dict(f);
mresfiles.append(d['general']['m_resfile'].strip());
sresfiles.append(d['general']['s_resfile'].strip());
iresfiles.append(d['general']['i_resfile'].strip());
bperp=[]
btemp=[]
master=[]
slave=[]
for f in N.r_[0:len(mresfiles)]:
mobj=adore.dict2obj(adore.res2dict(mresfiles[f]))
sobj=adore.dict2obj(adore.res2dict(sresfiles[f]))
ires=adore.res2dict(iresfiles[f])
iobj=adore.dict2obj(ires)
master.append( parser.parse(mobj.readfiles.First_pixel_azimuth_time) )
slave.append( parser.parse(sobj.readfiles.First_pixel_azimuth_time) )
bperp.append( iobj.coarse_orbits.Bperp )
btemp.append( iobj.coarse_orbits.Btemp )
return bperp, btemp, master, slave
def main(argv=None):
if argv is None:
argv = sys.argv
drsfile = argv[1]
try:
ct = float(argv[2])
except:
ct = 0.0
if drsfile is not None:
d = adore.drs2dict(drsfile)
mresfile = d['general']['m_resfile'].strip()
sresfile = d['general']['s_resfile'].strip()
iresfile = d['general']['i_resfile'].strip()
iobj = adore.dict2obj(adore.res2dict(iresfile))
mobj = adore.dict2obj(adore.res2dict(mresfile))
sobj = adore.dict2obj(adore.res2dict(sresfile))
A = iobj.fine_coreg.results
#ires['fine_coreg']['results'];
A = A[A[:, 5] > ct, :]
#figure
pylab.figure()
pylab.title('Range: Fine Correlation - Coregistration Polynomial')
rg = adore.basic.rescale(
A[:, 2], [-2, 2], arrlim=[mobj.crop.First_pixel, mobj.crop.Last_pixel])
az = adore.basic.rescale(
A[:, 1], [-2, 2], arrlim=[mobj.crop.First_line, mobj.crop.Last_line])
pixelOffset = adore.polyval(rg, az,
iobj.comp_coregpm.Estimated_coefficientsP)
lineOffset = adore.polyval(rg, az,
iobj.comp_coregpm.Estimated_coefficientsL)
Q = pylab.quiver(A[:, 2], A[:, 1], A[:, 4] - pixelOffset,
A[:, 3] - lineOffset, A[:, 5])
azStd = round(pylab.np.std(A[:, 3] - lineOffset))
rgStd = round(pylab.np.std(A[:, 4] - pixelOffset))
qk = pylab.quiverkey(Q,
0.33,
0.92,
azStd, ('%d [px az]' % (azStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
qk = pylab.quiverkey(Q,
0.66,
0.92,
rgStd, ('%d [px rg]' % (rgStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
pylab.colorbar()
pylab.show()
def main(argv=None):
if argv is None:
argv = sys.argv
iresfile = argv[1]
try:
ct = float(argv[2])
except:
ct = 0.0
ires = adore.res2dict(iresfile)
A = ires['fine_coreg']['results']
A = A[A[:, 5] > ct, :]
az = int(ires['fine_coreg']['Initial offsets'].split(',')[0])
rg = int(ires['fine_coreg']['Initial offsets'].split(',')[1])
#figure1
pylab.figure()
pylab.title('Fine Correlation Results')
pylab.quiver(A[:, 2], A[:, 1], A[:, 4], A[:, 3], A[:, 5])
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Fine Correlation Deviations')
pylab.quiver(A[:, 2], A[:, 1], A[:, 4] - rg, A[:, 3] - az, A[:, 5])
pylab.colorbar()
pylab.show()
def main(argv=None):
if argv is None:
argv=sys.argv
iresfile=argv[1];
try:
ct=float(argv[2]);
except:
ct=0.0
ires=adore.res2dict(iresfile);
A=ires['fine_coreg']['results'];
A=A[A[:,5]>ct,:]
az=int(ires['fine_coreg']['Initial offsets'].split(',')[0]);
rg=int(ires['fine_coreg']['Initial offsets'].split(',')[1]);
#figure1
pylab.figure()
pylab.title('Fine Correlation Results')
pylab.quiver(A[:,2], A[:,1], A[:,4], A[:,3], A[:,5]);
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Fine Correlation Deviations')
pylab.quiver(A[:,2], A[:,1], A[:,4]-rg, A[:,3]-az, A[:,5]);
pylab.colorbar()
pylab.show()
def main(argv=None):
if argv is None:
argv = sys.argv
iresfile = argv[1]
try:
ct = float(argv[2])
except:
ct = 0.0
ires = adore.res2dict(iresfile)
A = ires['fine_coreg']['results']
A = A[A[:, 5] > ct, :]
az = int(ires['fine_coreg']['Initial offsets'].split(',')[0])
rg = int(ires['fine_coreg']['Initial offsets'].split(',')[1])
#figure1
pylab.figure()
pylab.title('Fine Correlation Results')
Q = pylab.quiver(A[:, 2], A[:, 1], A[:, 4], A[:, 3], A[:, 5])
azAvg = round(pylab.np.mean(A[:, 3]))
rgAvg = round(pylab.np.mean(A[:, 4]))
qk = pylab.quiverkey(Q,
0.33,
0.92,
azAvg, ('%d [px az]' % (azAvg)),
labelpos='W',
fontproperties={'weight': 'bold'})
qk = pylab.quiverkey(Q,
0.66,
0.92,
rgAvg, ('%d [px rg]' % (rgAvg)),
labelpos='W',
fontproperties={'weight': 'bold'})
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Fine Correlation Deviations')
pylab.quiver(A[:, 2], A[:, 1], A[:, 4] - rg, A[:, 3] - az, A[:, 5])
Q = pylab.quiver(A[:, 2], A[:, 1], A[:, 4] - rg, A[:, 3] - az, A[:, 5])
azStd = round(pylab.np.std(A[:, 3] - az))
rgStd = round(pylab.np.std(A[:, 4] - rg))
qk = pylab.quiverkey(Q,
0.33,
0.92,
azStd, ('%d [px az]' % (azStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
qk = pylab.quiverkey(Q,
0.66,
0.92,
rgStd, ('%d [px rg]' % (rgStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
pylab.colorbar()
pylab.show()
def bperp_btemp(drsFiles):
from dateutil import parser
mresfiles = []
sresfiles = []
iresfiles = []
for f in drsFiles:
d = adore.drs2dict(f)
mresfiles.append(d['general']['m_resfile'].strip())
sresfiles.append(d['general']['s_resfile'].strip())
iresfiles.append(d['general']['i_resfile'].strip())
bperp = []
btemp = []
for f in N.r_[0:len(mresfiles)]:
mobj = adore.dict2obj(adore.res2dict(mresfiles[f]))
sobj = adore.dict2obj(adore.res2dict(sresfiles[f]))
ires = adore.res2dict(iresfiles[f])
iobj = adore.dict2obj(ires)
bperp.append(iobj.coarse_orbits.Bperp)
btemp.append(iobj.coarse_orbits.Btemp)
return bperp, btemp
def bperp_btemp(drsFiles):
from dateutil import parser
mresfiles=[]
sresfiles=[]
iresfiles=[]
for f in drsFiles:
d=adore.drs2dict(f);
mresfiles.append(d['general']['m_resfile'].strip());
sresfiles.append(d['general']['s_resfile'].strip());
iresfiles.append(d['general']['i_resfile'].strip());
bperp=[]
btemp=[]
for f in N.r_[0:len(mresfiles)]:
mobj=adore.dict2obj(adore.res2dict(mresfiles[f]))
sobj=adore.dict2obj(adore.res2dict(sresfiles[f]))
ires=adore.res2dict(iresfiles[f])
iobj=adore.dict2obj(ires)
bperp.append( iobj.coarse_orbits.Bperp )
btemp.append( iobj.coarse_orbits.Btemp )
return bperp, btemp
def main(argv=None):
if argv is None:
argv = sys.argv
iresfile = argv[1]
ires = adore.res2dict(iresfile)
A = ires['coarse_correl']['results']
az = ires['coarse_correl']['Coarse_correlation_translation_lines']
rg = ires['coarse_correl']['Coarse_correlation_translation_pixels']
#figure1
pylab.figure()
pylab.title('Coarse Correlation Results')
Q = pylab.quiver(A[:, 2], A[:, 1], A[:, 5], A[:, 4], A[:, 3])
azAvg = round(pylab.np.mean(A[:, 3]))
rgAvg = round(pylab.np.mean(A[:, 4]))
qk = pylab.quiverkey(Q,
0.33,
0.92,
azAvg, ('%d [px az]' % (azAvg)),
labelpos='W',
fontproperties={'weight': 'bold'})
qk = pylab.quiverkey(Q,
0.66,
0.92,
rgAvg, ('%d [px rg]' % (rgAvg)),
labelpos='W',
fontproperties={'weight': 'bold'})
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Coarse Correlation Deviations')
Q = pylab.quiver(A[:, 2], A[:, 1], A[:, 5] - rg, A[:, 4] - az, A[:, 3])
azStd = round(pylab.np.std(A[:, 3] - az))
rgStd = round(pylab.np.std(A[:, 4] - rg))
qk = pylab.quiverkey(Q,
0.33,
0.92,
azStd, ('%d [px az]' % (azStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
qk = pylab.quiverkey(Q,
0.66,
0.92,
rgStd, ('%d [px rg]' % (rgStd)),
labelpos='W',
fontproperties={'weight': 'bold'})
pylab.colorbar()
pylab.show()
def average_coherence_adore(iresfiles=None, drsFiles=None):
""" avg_coherence=average_coherence_adore(iresfiles=None, drsFiles=None):
"""
from dateutil import parser
if drsFiles is not None:
iresfiles = []
for f in drsFiles:
d = adore.drs2dict(f)
iresfiles.append(d['general']['i_resfile'].strip())
coh = []
for f in N.r_[0:len(iresfiles)]:
ires = adore.res2dict(iresfiles[f])
iobj = adore.dict2obj(ires)
coh.append(adore.getProduct(ires, 'coherence'))
coh = N.rollaxis(N.dstack(coh), 2, 0)
return coh.mean(0)
def average_coherence_adore(iresfiles=None, drsFiles=None):
""" avg_coherence=average_coherence_adore(iresfiles=None, drsFiles=None):
"""
from dateutil import parser
if drsFiles is not None:
iresfiles=[]
for f in drsFiles:
d=adore.drs2dict(f);
iresfiles.append(d['general']['i_resfile'].strip());
coh=[]
for f in N.r_[0:len(iresfiles)]:
ires=adore.res2dict(iresfiles[f])
iobj=adore.dict2obj(ires)
coh.append( adore.getProduct(ires,'coherence') );
coh=N.rollaxis(N.dstack(coh),2,0)
return coh.mean(0);
def main(argv=None):
if argv is None:
argv = sys.argv
iresfile = argv[1]
ires = adore.res2dict(iresfile)
A = ires['coarse_correl']['results']
az = ires['coarse_correl']['Coarse_correlation_translation_lines']
rg = ires['coarse_correl']['Coarse_correlation_translation_pixels']
#figure1
pylab.figure()
pylab.title('Coarse Correlation Results')
pylab.quiver(A[:, 2], A[:, 1], A[:, 5], A[:, 4], A[:, 3])
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Coarse Correlation Deviations')
pylab.quiver(A[:, 2], A[:, 1], A[:, 5] - rg, A[:, 4] - az, A[:, 3])
pylab.colorbar()
pylab.show()
def main(argv=None):
if argv is None:
argv=sys.argv
iresfile=argv[1];
ires=adore.res2dict(iresfile);
A=ires['coarse_correl']['results'];
az=ires['coarse_correl']['Coarse_correlation_translation_lines'];
rg=ires['coarse_correl']['Coarse_correlation_translation_pixels'];
#figure1
pylab.figure()
pylab.title('Coarse Correlation Results')
pylab.quiver(A[:,2], A[:,1], A[:,5], A[:,4], A[:,3]);
pylab.colorbar()
#figure2
pylab.figure()
pylab.title('Coarse Correlation Deviations')
pylab.quiver(A[:,2], A[:,1], A[:,5]-rg, A[:,4]-az, A[:,3]);
pylab.colorbar()
pylab.show()
def estimate_overlap(baselinesFolder, buffers=[200, 200], masterRes=None):
"""estimate_overlap(baselinesFolder, buffers[az_buf, rg_buf])
az_buf=200
rg_buf=200
ex:
baselinesFolder=setobj.adore.baselinesfolder.strip('"')
estimate_overlap(baselinesFolder, [400,400])
"""
import glob
if masterRes is not None:
mobj = adore.dict2obj(adore.res2dict(masterRes))
ifiles = glob.glob(baselinesFolder + '/*_*.res')
i12s = [] #interferogram objects list
master = [] #master names list
slave = [] #slave names list
lines = [] #list of translation lines (az)
pixels = [] #list of translation pixels (rg)
for f in ifiles:
d = adore.res2dict(f) #dictionary
#i12s.append(adore.dict2obj(d))
iobj = adore.dict2obj(d)
master.append(os.path.splitext(os.path.basename(f))[0].split('_')[0])
slave.append(os.path.splitext(os.path.basename(f))[0].split('_')[1])
lines.append(iobj.coarse_orbits.Coarse_orbits_translation_lines)
pixels.append(iobj.coarse_orbits.Coarse_orbits_translation_pixels)
K = len(ifiles) #number of interferograms
allDates = master + slave #merge master and slave lists
allDates = N.sort(list(set(allDates)))
I = len(allDates)
#Number of images (dates)
A = N.zeros([K + 1, I])
if masterRes is None:
masterScene = 0
else:
masterScene = os.path.splitext(os.path.basename(masterRes))[0]
masterScene = (allDates == masterScene)
for k in xrange(K):
A[k, :] = (allDates == master[k]) * -1 + (allDates == slave[k]) * 1
A[-1, masterScene] = 1
l = N.dot(N.linalg.pinv(A), lines + [0]) #merge zero to the end of list
p = N.dot(N.linalg.pinv(A), pixels + [0]) #merge zero to the end of list
neg_line_off = min(l[l < 0]) #negative line offset
pos_line_off = max(l[l > 0]) #positive line offset
neg_pix_off = min(p[p < 0]) #negative px offset
pos_pix_off = max(p[p > 0]) #positive px offset
if masterRes is not None:
return -1
# if lo > 0:
# lmin=0
# if mobj.process_control.oversample == 1:
# lmax=mobj.oversample.Last_line-lo/mobj.oversample.Multilookfactor_azimuth_direction
# else:
# lmax=mobj.crop.Last_line-lo
# else:
# if mobj.process_control.oversample == 1:
# lmin=mobj.oversample.First_line-l0/mobj.oversample.Multilookfactor_azimuth_direction
# lmax=mobj.oversample.Last_line
# else:
# lmin=mobj.crop.First_line-l0
# lmax=mobj.crop.Last_line
# if po > 0:
# pmin=0
# if mobj.process_control.oversample == 1:
# pmax=mobj.oversample.Last_pixel-po/mobj.oversample.Multilookfactor_range_direction
# else:
# pmax=mobj.crop.Last_line-po
# else:
# if mobj.process_control.oversample == 1:
# pmin=mobj.oversample.First_pixel-p0/mobj.oversample.Multilookfactor_range_direction
# pmax=mobj.oversample.Last_pixel
# else:
# lmin=mobj.crop.First_pixel-p0
# lmax=mobj.crop.Last_pixel
# return [mobj.crop.First_line+lo, po]
else:
return [neg_line_off, pos_line_off, neg_pix_off, pos_pix_off]
def estimate_overlap(baselinesFolder,buffers=[200,200], masterRes=None):
"""estimate_overlap(baselinesFolder, buffers[az_buf, rg_buf])
az_buf=200
rg_buf=200
ex:
baselinesFolder=setobj.adore.baselinesfolder.strip('"')
estimate_overlap(baselinesFolder, [400,400])
"""
import glob
if masterRes is not None:
mobj=adore.dict2obj(adore.res2dict( masterRes ))
ifiles=glob.glob(baselinesFolder+'/*_*.res')
i12s=[] #interferogram objects list
master=[] #master names list
slave=[] #slave names list
lines=[] #list of translation lines (az)
pixels=[] #list of translation pixels (rg)
for f in ifiles:
d=adore.res2dict(f) #dictionary
#i12s.append(adore.dict2obj(d))
iobj=adore.dict2obj(d)
master.append(os.path.splitext(os.path.basename(f))[0].split('_')[0])
slave.append(os.path.splitext(os.path.basename(f))[0].split('_')[1])
lines.append(iobj.coarse_orbits.Coarse_orbits_translation_lines)
pixels.append(iobj.coarse_orbits.Coarse_orbits_translation_pixels)
K=len(ifiles) #number of interferograms
allDates=master + slave #merge master and slave lists
allDates=N.sort(list(set(allDates)));
I=len(allDates); #Number of images (dates)
A=N.zeros([K+1,I]);
if masterRes is None:
masterScene=0
else:
masterScene=os.path.splitext(os.path.basename(masterRes))[0]
masterScene=(allDates==masterScene)
for k in xrange(K):
A[k,:]=(allDates==master[k])*-1+(allDates==slave[k])*1;
A[-1,masterScene]=1
l=N.dot(N.linalg.pinv(A),lines+[0]) #merge zero to the end of list
p=N.dot(N.linalg.pinv(A),pixels+[0]) #merge zero to the end of list
neg_line_off=min(l[l<0]) #negative line offset
pos_line_off=max(l[l>0]) #positive line offset
neg_pix_off=min(p[p<0]) #negative px offset
pos_pix_off=max(p[p>0]) #positive px offset
if masterRes is not None:
return -1
# if lo > 0:
# lmin=0
# if mobj.process_control.oversample == 1:
# lmax=mobj.oversample.Last_line-lo/mobj.oversample.Multilookfactor_azimuth_direction
# else:
# lmax=mobj.crop.Last_line-lo
# else:
# if mobj.process_control.oversample == 1:
# lmin=mobj.oversample.First_line-l0/mobj.oversample.Multilookfactor_azimuth_direction
# lmax=mobj.oversample.Last_line
# else:
# lmin=mobj.crop.First_line-l0
# lmax=mobj.crop.Last_line
# if po > 0:
# pmin=0
# if mobj.process_control.oversample == 1:
# pmax=mobj.oversample.Last_pixel-po/mobj.oversample.Multilookfactor_range_direction
# else:
# pmax=mobj.crop.Last_line-po
# else:
# if mobj.process_control.oversample == 1:
# pmin=mobj.oversample.First_pixel-p0/mobj.oversample.Multilookfactor_range_direction
# pmax=mobj.oversample.Last_pixel
# else:
# lmin=mobj.crop.First_pixel-p0
# lmax=mobj.crop.Last_pixel
# return [mobj.crop.First_line+lo, po]
else:
return [neg_line_off, pos_line_off, neg_pix_off, pos_pix_off]
def main(argv=None):
A = adore.Object()
if argv is None:
argv = sys.argv
iresfile = argv[1]
try:
mode = argv[2]
product = argv[3]
except:
product = 'geocoding'
mode = 'p'
ires = adore.res2dict(iresfile)
iobj = adore.dict2obj(ires)
lat = adore.getProduct(iobj.geocoding,
filename=iobj.geocoding.Data_output_file_lamda)
lon = adore.getProduct(iobj.geocoding,
filename=iobj.geocoding.Data_output_file_phi)
if product == 'geocoding':
hei = adore.getProduct(iobj.geocoding,
filename=iobj.geocoding.Data_output_file_hei)
else:
#check if includes colon:
if ":" in product:
filename = product.split(':')[1]
product = product.split(':')[0]
else:
filename = None
#hei is actually any data at this point...
hei = adore.getProduct(ires, product, filename=filename)
#d0 is longitude, d1 is latitude
d0, d1 = numpy.meshgrid(numpy.linspace(lat.min(), lat.max(), lon.shape[1]),
numpy.linspace(lon.min(), lon.max(), lon.shape[0]))
if lat[0, 0] > 0: #northern hemisphere
if d1[0, 0] < d1[-1, 0]:
d1 = numpy.flipud(d1)
hei_gridded = interpolate.griddata((lon.ravel(), lat.ravel()),
hei.ravel(), (d1, d0),
method='linear')
#set-up basemap
print('Please wait... Generating map\n')
m = Basemap(llcrnrlon=d0.min(),
llcrnrlat=d1.min(),
urcrnrlon=d0.max(),
urcrnrlat=d1.max(),
resolution='f',
area_thresh=1.,
projection='cyl')
if 'complex' in ires[product][
'Data_output_format']: #any(numpy.iscomplex(hei_gridded)):
if mode == 'p':
m.imshow(numpy.angle(hei_gridded),
interpolation='nearest',
origin='upper')
else:
m.imshow(10 * numpy.log10(abs(hei_gridded)),
interpolation='nearest',
origin='upper')
pl.gray()
else:
m.imshow(hei_gridded, interpolation='nearest', origin='upper')
m.drawcoastlines(color='w', linewidth=0.8)
m.drawmapboundary() # draw a line around the map region
m.drawrivers()
m.drawparallels(numpy.arange(int(d1.min()), int(d1.max()), 1),
linewidth=0.2,
labels=[1, 0, 0, 0])
m.drawmeridians(numpy.arange(int(d0.min()), int(d0.max()), 1),
linewidth=0.2,
labels=[0, 0, 0, 1])
#MAYAVI TAKES TOO LONG
# #visualize points
# pts =mlab.points3d(lon.ravel(), lat.ravel(), hei.ravel(), hei.ravel(), scale_mode='none', scale_factor=0.2)
# #create the mesh
# mesh=mlab.pipeline.delaunay2d(pts)
# #visualize the mesh
# surf=mlab.pipeline.surf(mesh)
#
# mlab.show()
#do not quit the program until enter
print "Press ENTER to quit."
pl.ginput(n=10000, timeout=0, mouse_add=3, mouse_pop=1)
def main(argv=None):
A=adore.Object()
if argv is None:
argv=sys.argv
iresfile=argv[1];
try:
mode=argv[2];
product=argv[3];
except:
product='geocoding'
mode='p';
ires=adore.res2dict(iresfile);
iobj=adore.dict2obj(ires);
lat=adore.getProduct(iobj.geocoding, filename=iobj.geocoding.Data_output_file_lamda)
lon=adore.getProduct(iobj.geocoding, filename=iobj.geocoding.Data_output_file_phi)
if product=='geocoding':
hei=adore.getProduct(iobj.geocoding, filename=iobj.geocoding.Data_output_file_hei)
else:
#check if includes colon:
if ":" in product:
filename=product.split(':')[1]
product=product.split(':')[0]
else:
filename=None
#hei is actually any data at this point...
hei=adore.getProduct(ires, product, filename=filename)
#d0 is longitude, d1 is latitude
d0,d1=numpy.meshgrid(numpy.linspace(lat.min(),lat.max(), lon.shape[1]),
numpy.linspace(lon.min(), lon.max(), lon.shape[0]))
if lat[0,0] > 0: #northern hemisphere
if d1[0,0]<d1[-1,0]:
d1=numpy.flipud(d1)
hei_gridded = interpolate.griddata((lon.ravel(),lat.ravel()), hei.ravel(), (d1, d0), method='linear')
#set-up basemap
print ('Please wait... Generating map\n')
m = Basemap(llcrnrlon=d0.min(), llcrnrlat=d1.min(), urcrnrlon=d0.max(), urcrnrlat=d1.max(),
resolution='f', area_thresh=1., projection='cyl')
if 'complex' in ires[product]['Data_output_format']:#any(numpy.iscomplex(hei_gridded)):
if mode=='p':
m.imshow(numpy.angle(hei_gridded), interpolation='nearest', origin='upper')
else:
m.imshow(10*numpy.log10(abs(hei_gridded)), interpolation='nearest', origin='upper')
pl.gray();
else:
m.imshow(hei_gridded, interpolation='nearest', origin='upper')
m.drawcoastlines(color='w',linewidth=0.8)
m.drawmapboundary() # draw a line around the map region
m.drawrivers()
m.drawparallels(numpy.arange(int(d1.min()), int(d1.max()), 1),linewidth=0.2,labels=[1,0,0,0])
m.drawmeridians(numpy.arange(int(d0.min()), int(d0.max()), 1),linewidth=0.2,labels=[0,0,0,1])
#MAYAVI TAKES TOO LONG
# #visualize points
# pts =mlab.points3d(lon.ravel(), lat.ravel(), hei.ravel(), hei.ravel(), scale_mode='none', scale_factor=0.2)
# #create the mesh
# mesh=mlab.pipeline.delaunay2d(pts)
# #visualize the mesh
# surf=mlab.pipeline.surf(mesh)
#
# mlab.show()
#do not quit the program until enter
print "Press ENTER to quit."
pl.ginput(n=10000, timeout=0, mouse_add=3, mouse_pop=1)