def seed_attributes(atr_in, x, y):
atr = dict()
for key, value in atr_in.iteritems():
atr[key] = str(value)
atr['ref_y'] = str(y)
atr['ref_x'] = str(x)
if 'X_FIRST' in atr.keys():
atr['ref_lat'] = str(subset.coord_radar2geo(y, atr, 'y'))
atr['ref_lon'] = str(subset.coord_radar2geo(x, atr, 'x'))
return atr
def format_coord(x,y):
col = int(x)
row = int(y)
if 0 <= col < data0.shape[1] and 0 <= row < data0.shape[0]:
z = data0[row,col]
if 'X_FIRST' in atr0.keys():
lat = sub.coord_radar2geo(row, atr0, 'row')
lon = sub.coord_radar2geo(col, atr0, 'col')
return 'lon=%.4f, lat=%.4f, x=%.0f, y=%.0f, value=%.4f' % (lon, lat, x,y,z)
else:
return 'x=%.0f, y=%.0f, value=%.4f'%(x,y,z)
else:
return 'x=%.0f, y=%.0f'%(x,y)
def seed_attributes(atr_in,x,y):
atr = dict()
for key, value in atr_in.iteritems(): atr[key] = str(value)
atr['ref_y']=y
atr['ref_x']=x
try:
atr['X_FIRST']
lat = subset.coord_radar2geo(y,atr,'y')
lon = subset.coord_radar2geo(x,atr,'x')
atr['ref_lat']=lat
atr['ref_lon']=lon
geocoord='yes'
except: geocoord='no'
return atr
def seed_attributes(atr_in,x,y):
atr = dict()
for key, value in atr_in.iteritems(): atr[key] = str(value)
atr['ref_y']=y
atr['ref_x']=x
try:
atr['X_FIRST']
lat = sub.coord_radar2geo(y,atr,'y')
lon = sub.coord_radar2geo(x,atr,'x')
atr['ref_lat']=lat
atr['ref_lon']=lon
geocoord='yes'
except: geocoord='no'
return atr
def transect_yx(z,atr,start_yx,end_yx,interpolation='nearest'):
'''Extract 2D matrix (z) value along the line [x0,y0;x1,y1]
Ref link: http://stackoverflow.com/questions/7878398/how-to-e
xtract-an-arbitrary-line-of-values-from-a-numpy-array
Inputs:
z - (np.array) 2D data matrix
atr - (dictionary) 2D data matrix attribute dictionary
start_yx - (list) y,x coordinate of start point
end_yx - (list) y,x coordinate of end point
interpolation - sampling/interpolation method, including:
'nearest' - nearest neighbour, by default
'cubic' - cubic interpolation
'bilinear' - bilinear interpolation
Output:
transect - N*2 matrix containing distance - 1st col - and its corresponding
values - 2nd col - along the line, N is the number of points.
Example:
transect = transect_yx(dem,demRsc,[10,15],[100,115])
'''
## Extract the line
[y0,x0] = start_yx
[y1,x1] = end_yx
length = int(np.hypot(x1-x0, y1-y0))
x, y = np.linspace(x0, x1, length), np.linspace(y0, y1, length)
transect = np.zeros([length,2])
## Y - Extract the value along the line
if interpolation.lower() == 'nearest' : zi = z[np.rint(y).astype(np.int), np.rint(x).astype(np.int)]
elif interpolation.lower() == 'cubic' : zi = scipy.ndimage.map_coordinates(z,np.vstack((y,x)))
elif interpolation.lower() == 'bilinear': zi = scipy.ndimage.map_coordinates(z,np.vstack((y,x)),order=2)
else:
print 'Unrecognized interpolation method: '+interpolation
print 'Continue with nearest ...'
zi = z[np.rint(y).astype(np.int), np.rint(x).astype(np.int)] # nearest neighbour
transect[:,1] = zi
## X - Distance along the line
earth_radius = 6371.0e3; # in meter
try:
atr['X_FIRST']
[lat0,lat1] = sub.coord_radar2geo([y0,y1],atr,'y')
x_step = float(atr['X_STEP'])*np.pi/180.0*earth_radius*np.sin((lat0+lat1)/2*np.pi/180)
y_step = float(atr['Y_STEP'])*np.pi/180.0*earth_radius
except:
x_step = ut.range_resolution(atr)
y_step = ut.azimuth_resolution(atr)
dis_x = (x-x0)*x_step
dis_y = (y-y0)*y_step
transect[:,0] = np.hypot(dis_x,dis_y)
return transect
def seed_file_inps(File, inps=None, outFile=None):
'''Seed input file with option from input namespace
Return output file name if succeed; otherwise, return None
'''
# Optional inputs
if not outFile: outFile = 'Seeded_'+os.path.basename(File)
if not inps: inps = cmdLineParse([''])
print '----------------------------------------------------'
print 'seeding file: '+File
# Get stack and mask
stack = ut.get_file_stack(File, inps.mask_file)
mask = ~np.isnan(stack)
if np.nansum(mask) == 0.0:
print '\n*****************************************************'
print 'ERROR:'
print 'There is no pixel that has valid phase value in all datasets.'
print 'Check the file!'
print 'Seeding failed'
sys.exit(1)
atr = readfile.read_attribute(File)
# 1. Reference using global average
if inps.method == 'global-average':
print '\n---------------------------------------------------------'
print 'Automatically Seeding using Global Spatial Average Value '
print '---------------------------------------------------------'
print 'Calculating the global spatial average value for each epoch'+\
' of all valid pixels ...'
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
box = (0,0,width,length)
meanList = ut.spatial_average(File, mask, box)[0]
inps.ref_y = ''
inps.ref_x = ''
outFile = seed_file_reference_value(File, outFile, meanList, inps.ref_y, inps.ref_x)
return outFile
# 2. Reference using specific pixel
# 2.1 Find reference y/x
if not inps.ref_y or not inps.ref_x:
if inps.coherence_file:
inps.method = 'max-coherence'
inps.ref_y, inps.ref_x = select_max_coherence_yx(inps.coherence_file, mask, inps.min_coherence)
elif inps.method == 'random':
inps.ref_y, inps.ref_x = random_select_reference_yx(mask)
elif inps.method == 'manual':
inps = manual_select_reference_yx(stack, inps)
# 2.2 Seeding file with reference y/x
if inps.ref_y and inps.ref_x and mask[inps.ref_y, inps.ref_x]:
if inps.mark_attribute:
re_select = True
try:
ref_x_orig == int(atr['ref_x'])
ref_y_orig == int(atr['ref_y'])
if inps.ref_x == ref_x_orig and inps.ref_y == ref_y_orig:
re_select = False
print 'Same reference pixel is already selected/saved in file, skip updating file attributes'
except: pass
if re_select:
print 'Add/update ref_x/y attribute to file: '+File
atr_ref = dict()
atr_ref['ref_x'] = str(inps.ref_x)
atr_ref['ref_y'] = str(inps.ref_y)
if 'X_FIRST' in atr.keys():
atr_ref['ref_lat'] = str(subset.coord_radar2geo(inps.ref_y, atr, 'y'))
atr_ref['ref_lon'] = str(subset.coord_radar2geo(inps.ref_x, atr, 'x'))
print atr_ref
outFile = ut.add_attribute(File, atr_ref)
else:
print 'Referencing input file to pixel in y/x: (%d, %d)'%(inps.ref_y, inps.ref_x)
box = (inps.ref_x, inps.ref_y, inps.ref_x+1, inps.ref_y+1)
refList = ut.spatial_average(File, mask, box)[0]
outFile = seed_file_reference_value(File, outFile, refList, inps.ref_y, inps.ref_x)
else:
raise ValueError('Can not find reference y/x or Nan value.')
return outFile
