def get_exclude_date(inps, date_list_all):
'''Get inps.ex_date full list
Inputs:
inps - Namespace,
date_list_all - list of string for all available date in YYYYMMDD format
Output:
inps.ex_date - list of string for exclude date in YYYYMMDD format
'''
yy_list_all = ptime.yyyymmdd2years(date_list_all)
# 1. template_file
if inps.template_file:
print 'read option from template file: ' + inps.template_file
inps = read_template2inps(inps.template_file, inps)
# 2. ex_date
input_ex_date = list(inps.ex_date)
inps.ex_date = []
if input_ex_date:
for ex_date in input_ex_date:
if os.path.isfile(ex_date):
ex_date = ptime.read_date_list(ex_date)
else:
ex_date = [ptime.yyyymmdd(ex_date)]
inps.ex_date += list(set(ex_date) - set(inps.ex_date))
# delete dates not existed in input file
inps.ex_date = list(set(inps.ex_date).intersection(date_list_all))
print 'exclude date:' + str(inps.ex_date)
# 3. min_date
if inps.min_date:
print 'start date: ' + inps.min_date
yy_min = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.min_date))
for i in range(len(date_list_all)):
date = date_list_all[i]
if yy_list_all[i] < yy_min and date not in inps.ex_date:
print ' remove date: ' + date
inps.ex_date.append(date)
# 4. max_date
if inps.max_date:
print 'end date: ' + inps.max_date
yy_max = ptime.yyyymmdd2years(ptime.yyyymmdd(inps.max_date))
for i in range(len(date_list_all)):
date = date_list_all[i]
if yy_list_all[i] > yy_max and date not in inps.ex_date:
print ' remove date: ' + date
inps.ex_date.append(date)
return inps.ex_date
def correct_lod_file(File, outFile=None):
# Check Sensor Type
print 'input file: ' + File
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
platform = atr['PLATFORM']
print 'platform: ' + platform
if not platform.lower() in ['env', 'envisat']:
print 'No need to correct LOD for ' + platform
sys.exit(1)
# Output Filename
if not outFile:
ext = os.path.splitext(File)[1]
outFile = os.path.splitext(File)[0] + '_LODcor' + ext
# Get LOD phase ramp from empirical model
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
range_resolution = float(atr['RANGE_PIXEL_SIZE'])
r = np.linspace(0, width - 1, width)
R = range_resolution * r * (3.87e-7)
Ramp = np.tile(R, [length, 1])
yref = int(atr['ref_y'])
xref = int(atr['ref_x'])
Ramp -= Ramp[yref][xref]
# Correct LOD Ramp for Input File
if k in multi_group_hdf5_file + multi_dataset_hdf5_file:
h5 = h5py.File(File, 'r')
epochList = sorted(h5[k].keys())
h5out = h5py.File(outFile, 'w')
group = h5out.create_group(k)
if k in ['interferograms', 'wrapped']:
print 'number of interferograms: ' + str(len(epochList))
wvl = float(atr['WAVELENGTH'])
Ramp *= -4 * np.pi / wvl
for epoch in epochList:
print epoch
data = h5[k][epoch].get(epoch)[:]
atr = h5[k][epoch].attrs
dates = ptime.yyyymmdd(atr['DATE12'].split('-'))
dates = ptime.yyyymmdd2years(dates)
dt = date[1] - date[0]
data -= Ramp * dt
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in atr.iteritems():
gg.attrs[key] = value
elif k == 'timeseries':
print 'number of acquisitions: ' + str(len(epochList))
tbase = [
float(dy) / 365.25
for dy in ptime.date_list2tbase(epochList)[0]
]
for i in range(len(epochList)):
epoch = epochList[i]
print epoch
data = h5[k].get(epoch)[:]
data -= Ramp * tbase[i]
dset = group.create_dataset(epoch,
data=data,
compression='gzip')
for key, value in atr.iteritems():
group.attrs[key] = value
else:
print 'No need to correct for LOD for ' + k + ' file'
sys.exit(1)
h5.close()
h5out.close()
else:
data, atr = readfile.read(File)
data -= Ramp
writefile.write(data, atr, outFile)
return outFile
def correct_lod_file(File, rangeDistFile=None, outFile=None):
# Check Sensor Type
print 'correct Local Oscilator Drift for Envisat using an empirical model (Marinkovic and Larsen, 2013)'
print 'input file: ' + File
atr = readfile.read_attribute(File)
k = atr['FILE_TYPE']
platform = atr['PLATFORM']
print 'platform: ' + platform
if not platform.lower() in ['env', 'envisat']:
print 'No need to correct LOD for ' + platform
sys.exit(1)
# Output Filename
if not outFile:
ext = os.path.splitext(File)[1]
outFile = os.path.splitext(File)[0] + '_LODcor' + ext
# Get LOD phase ramp from empirical model
if not rangeDistFile:
print 'calculate range distance from input file attributes'
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
range_resolution = float(atr['RANGE_PIXEL_SIZE'])
rangeDist1D = range_resolution * np.linspace(0, width - 1, width)
rangeDist = np.tile(rangeDist1D, (length, 1))
else:
print 'read range distance from file: %s' % (rangeDistFile)
rangeDist = readfile.read(rangeDistFile, epoch='slantRangeDistance')[0]
yref = int(atr['ref_y'])
xref = int(atr['ref_x'])
rangeDist -= rangeDist[yref][xref]
Ramp = np.array(rangeDist * 3.87e-7, np.float32)
# Correct LOD Ramp for Input File
if k in multi_group_hdf5_file + multi_dataset_hdf5_file:
h5 = h5py.File(File, 'r')
epochList = sorted(h5[k].keys())
epochNum = len(epochList)
print 'writing >>> %s' % (outFile)
h5out = h5py.File(outFile, 'w')
group = h5out.create_group(k)
prog_bar = ptime.progress_bar(maxValue=epochNum)
if k in ['interferograms', 'wrapped']:
Ramp *= -4 * np.pi / float(atr['WAVELENGTH'])
print 'number of interferograms: ' + str(epochNum)
date12List = ptime.list_ifgram2date12(epochList)
for i in range(epochNum):
epoch = epochList[i]
data = h5[k][epoch].get(epoch)[:]
atr = h5[k][epoch].attrs
dates = ptime.yyyymmdd(atr['DATE12'].split('-'))
dates = ptime.yyyymmdd2years(dates)
dt = dates[1] - dates[0]
data -= Ramp * dt
gg = group.create_group(epoch)
dset = gg.create_dataset(epoch, data=data, compression='gzip')
for key, value in atr.iteritems():
gg.attrs[key] = value
prog_bar.update(i + 1, suffix=date12List[i])
elif k == 'timeseries':
print 'number of acquisitions: ' + str(len(epochList))
tbase = [
float(dy) / 365.25
for dy in ptime.date_list2tbase(epochList)[0]
]
for i in range(epochNum):
epoch = epochList[i]
data = h5[k].get(epoch)[:]
data -= Ramp * tbase[i]
dset = group.create_dataset(epoch,
data=data,
compression='gzip')
prog_bar.update(i + 1, suffix=epoch)
for key, value in atr.iteritems():
group.attrs[key] = value
else:
print 'No need to correct for LOD for ' + k + ' file'
sys.exit(1)
prog_bar.close()
h5.close()
h5out.close()
elif k in ['.unw']:
data, atr = readfile.read(File)
Ramp *= -4 * np.pi / float(atr['WAVELENGTH'])
dates = ptime.yyyymmdd(atr['DATE12'].split('-'))
dates = ptime.yyyymmdd2years(dates)
dt = dates[1] - dates[0]
data -= Ramp * dt
print 'writing >>> %s' % (outFile)
writefile.write(data, atr, outFile)
else:
print 'No need to correct for LOD for %s file' % (k)
return outFile
def main(argv):
## Default settings
contour_step = 200.0
contour_sigma = 3.0
demShade = "yes"
demContour = "yes"
global markerSize, markderSize2, markerColor, markerColor2, rectColor
global lineWidth, lineWidth2, edgeWidth, fontSize
# global markerColor_ref, markerColor_ref2
markerSize = 16
markerSize2 = 16
markerColor = "crimson" # g
markerColor2 = "lightgray"
markerColor_ref = "white"
markerColor_ref2 = "lightgray"
rectColor = "black"
lineWidth = 0
lineWidth2 = 0
edgeWidth = 1.5
fontSize = 16
global unit, radius, saveFig, dispFig, fig_dpi
fig_dpi = 300
radius = 0
saveFig = "no"
dispFig = "yes"
unit = "cm"
dispDisplacement = "no"
dispOpposite = "no"
dispContour = "only"
smoothContour = "no"
contour_step = 200
showRef = "yes"
vel_alpha = 1.0
zero_start = "yes"
global ref_xsub, ref_ysub, ref_date
global h5timeseries_2, dates_2, dateList_2
global lbound, hbound
############### Check Inputs ##################
if len(sys.argv) < 2:
Usage()
sys.exit(1)
elif len(sys.argv) == 2:
if argv[0] == "-h":
Usage()
sys.exit(1)
elif os.path.isfile(argv[0]):
timeSeriesFile = argv[0]
h5timeseries = h5py.File(timeSeriesFile)
k = h5timeseries.keys()
if not "timeseries" in k:
print "ERROR: Input file is " + k[0] + ".\n\tOnly timeseries is supported.\n"
sys.exit(1)
else:
Usage()
sys.exit(1)
elif len(sys.argv) > 2:
try:
opts, args = getopt.getopt(
argv,
"f:F:v:a:b:s:m:c:w:u:l:h:D:V:t:T:d:r:x:y:X:Y:o:E:",
[
"save",
"nodisplay",
"unit=",
"exclude=",
"ref-date=",
"rect-color=",
"zero-start=",
"zoom-x=",
"zoom-y=",
"zoom-lon",
"zoom-lat",
"lalo=",
"opposite",
"dem-nocontour",
"dem-noshade",
"displacement",
"contour-step=",
"contour-smooth=",
"LALO=",
],
)
except getopt.GetoptError:
Usage()
sys.exit(1)
for opt, arg in opts:
if opt == "-f":
timeSeriesFile = arg
elif opt == "-F":
timeSeriesFile_2 = arg
elif opt == "-v":
velocityFile = arg
elif opt == "-a":
vmin = float(arg)
elif opt == "-b":
vmax = float(arg)
elif opt == "-s":
fontSize = int(arg)
elif opt == "-m":
markerSize = int(arg)
markerSize2 = int(arg)
elif opt == "-c":
markerColor = arg
elif opt == "-w":
lineWidth = int(arg)
elif opt == "-u":
unit = arg
elif opt == "-l":
lbound = float(arg)
elif opt == "-h":
hbound = float(arg)
elif opt == "-D":
demFile = arg
elif opt == "-V":
contour_step = float(arg)
elif opt == "-t":
minDate = arg
elif opt == "-T":
maxDate = arg
elif opt == "-r":
radius = abs(int(arg))
elif opt == "-x":
xsub = [int(i) for i in arg.split(":")]
xsub.sort()
# dispVelFig='no'
elif opt == "-y":
ysub = [int(i) for i in arg.split(":")]
ysub.sort()
# dispVelFig='no'
elif opt == "-X":
ref_xsub = [int(i) for i in arg.split(":")]
ref_xsub.sort()
elif opt == "-Y":
ref_ysub = [int(i) for i in arg.split(":")]
ref_ysub.sort()
# dispVelFig='no'
elif opt == "--contour-step":
contour_step = float(arg)
elif opt == "--contour-smooth":
contour_sigma = float(arg)
elif opt == "--dem-nocontour":
demContour = "no"
elif opt == "--dem-noshade":
demShade = "no"
elif opt == "--displacement":
dispDisplacement = "yes"
elif opt in ["-E", "--exclude"]:
datesNot2show = arg.split(",")
elif opt in "--lalo":
lalosub = [float(i) for i in arg.split(",")]
elif opt in "--LALO":
ref_lalosub = [float(i) for i in arg.split(",")]
elif opt in ["--rect-color"]:
rectColor = arg
elif opt in ["--ref-date"]:
ref_date = ptime.yyyymmdd(arg)
elif opt in ["-u", "--unit"]:
unit = arg.lower()
elif opt == "--save":
saveFig = "yes"
elif opt == "--nodisplay":
dispFig = "no"
saveFig = "yes"
elif opt == "--opposite":
dispOpposite = "yes"
elif opt == "--zero-start":
zero_start = arg.lower()
elif opt == "--zoom-x":
win_x = [int(i) for i in arg.split(":")]
win_x.sort()
elif opt == "--zoom-y":
win_y = [int(i) for i in arg.split(":")]
win_y.sort()
elif opt == "--zoom-lon":
win_lon = [float(i) for i in arg.split(":")]
win_lon.sort()
elif opt == "--zoom-lat":
win_lat = [float(i) for i in arg.split(":")]
win_lat.sort()
##############################################################
## Read time series file info
if not os.path.isfile(timeSeriesFile):
print "\nERROR: Input time series file does not exist: " + timeSeriesFile + "\n"
sys.exit(1)
h5timeseries = h5py.File(timeSeriesFile)
k = h5timeseries.keys()
# read h5 file and its group type
if not "timeseries" in k:
print "ERROR: Input file is " + k[0] + ".\n\tOnly timeseries is supported.\n"
sys.exit(1)
atr = readfile.read_attributes(timeSeriesFile)
dateList1 = h5timeseries["timeseries"].keys()
dateList1 = sorted(dateList1)
dates1, datevector1 = ptime.date_list2vector(dateList1)
print "\n************ Time Series Display - Point *************"
##### Select Check
try:
lalosub
xsub = subset.coord_geo2radar([lalosub[1]], atr, "longitude")
ysub = subset.coord_geo2radar([lalosub[0]], atr, "latitude")
xsub = [xsub]
ysub = [ysub]
if radius == 0:
radius = 3
except:
pass
try:
ref_lalosub
ref_xsub = subset.coord_geo2radar([ref_lalosub[1]], atr, "longitude")
ref_ysub = subset.coord_geo2radar([ref_lalosub[0]], atr, "latitude")
ref_xsub = [ref_xsub]
ref_ysub = [ref_ysub]
if radius == 0:
radius = 3
except:
pass
##############################################################
global dates, dateList, datevector_all, dateListMinMax
print "*******************"
print "All dates existed:"
print dateList1
print "*******************"
## Check exclude date input
try:
datesNot2show
if os.path.isfile(datesNot2show[0]):
try:
datesNot2show = ptime.read_date_list(datesNot2show[0])
except:
print "Can not read date list file: " + datesNot2show[0]
print "dates not to show: " + str(datesNot2show)
except:
datesNot2show = []
## Check Min / Max Date
dateListMinMax = []
try:
minDate
minDate = ptime.yyyymmdd(minDate)
dateListMinMax.append(minDate)
minDateyy = ptime.yyyymmdd2years(minDate)
print "minimum date: " + minDate
for date in dateList1:
yy = ptime.yyyymmdd2years(date)
if yy < minDateyy:
datesNot2show.append(date)
except:
pass
try:
maxDate
maxDate = ptime.yyyymmdd(maxDate)
dateListMinMax.append(maxDate)
maxDateyy = ptime.yyyymmdd2years(maxDate)
print "maximum date: " + maxDate
for date in dateList1:
yy = ptime.yyyymmdd2years(date)
if yy > maxDateyy:
datesNot2show.append(date)
except:
pass
dateListMinMax = sorted(dateListMinMax)
if not dateListMinMax:
print "no min/max date input."
else:
datesMinMax, dateVecMinMax = ptime.date_list2vector(dateListMinMax)
## Finalize Date List
try:
dateList = []
for date in dateList1:
if date not in datesNot2show:
dateList.append(date)
print "--------------------------------------------"
print "dates used to show time series displacements:"
print dateList
print "--------------------------------------------"
except:
dateList = dateList1
print "using all dates to show time series displacement"
## Read Date Info (x axis for time series display)
dates, datevector = ptime.date_list2vector(dateList)
datevector_all = list(datevector)
## Check reference date input
try:
ref_date
if not ref_date in dateList:
print "Reference date - " + ref_date + " - is not included in date list to show."
sys.exit(1)
else:
print "reference date: " + ref_date
except:
if zero_start == "yes":
ref_date = dateList[0]
print "set the 1st date as reference for displacement display."
else:
pass
##############################################################
##### Plot Fig 1 - Velocity / last epoch of time series / DEM
fig = plt.figure(1)
ax = fig.add_subplot(111)
##### Check subset range
width = int(atr["WIDTH"])
length = int(atr["FILE_LENGTH"])
print "file size: " + str(length) + ", " + str(width)
try:
win_y = subset.coord_geo2radar(win_lat, atr, "latitude")
except:
try:
win_y
except:
win_y = [0, length]
try:
win_x = subset.coord_geo2radar(win_lon, atr, "longitude")
except:
try:
win_x
except:
win_x = [0, width]
win_y, win_x = subset.check_subset_range(win_y, win_x, atr)
try:
velocityFile
try:
vel, vel_atr = readfile.read(velocityFile)
except:
vel, vel_atr = readfile.read(timeSeriesFile, velocityFile)
ax.set_title(velocityFile)
print "display: " + velocityFile
except:
vel, vel_atr = readfile.read(timeSeriesFile, dateList1[-1])
ax.set_title("epoch: " + dateList1[-1])
print "display last epoch"
##### show displacement instead of phase
if vel_atr["FILE_TYPE"] in ["interferograms", ".unw"] and dispDisplacement == "yes":
print "show displacement"
phase2range = -float(vel_atr["WAVELENGTH"]) / (4 * np.pi)
vel *= phase2range
else:
dispDisplacement = "no"
## Reference Point
if showRef == "yes":
try:
ax.plot(int(atr["ref_x"]), int(atr["ref_y"]), "ks", ms=6)
except:
pass
if dispOpposite == "yes":
print "show opposite value in figure/map 1"
vel *= -1
## Flip
try:
flip_lr
except:
try:
flip_ud
except:
flip_lr, flip_ud = view.auto_flip_check(atr)
## Status bar
## Geo coordinate
try:
ullon = float(atr["X_FIRST"])
ullat = float(atr["Y_FIRST"])
lon_step = float(atr["X_STEP"])
lat_step = float(atr["Y_STEP"])
lon_unit = atr["Y_UNIT"]
lat_unit = atr["X_UNIT"]
geocoord = "yes"
print "Input file is Geocoded"
except:
geocoord = "no"
def format_coord(x, y):
col = int(x + 0.5)
row = int(y + 0.5)
if col >= 0 and col <= width and row >= 0 and row <= length:
z = vel[row, col]
try:
lon = ullon + x * lon_step
lat = ullat + y * lat_step
return "x=%.1f, y=%.1f, value=%.4f, lon=%.4f, lat=%.4f" % (x, y, z, lon, lat)
except:
return "x=%.1f, y=%.1f, value=%.4f" % (x, y, z)
ax.format_coord = format_coord
## DEM
try:
demFile
dem, demRsc = readfile.read(demFile)
ax = view.plot_dem_yx(ax, dem, demShade, demContour, contour_step, contour_sigma)
vel_alpha = 0.8
except:
print "No DEM file"
try:
img = ax.imshow(vel, vmin=vmin, vmax=vmax, alpha=vel_alpha)
except:
img = ax.imshow(vel, alpha=vel_alpha)
plt.colorbar(img)
## Zoom In (subset)
if flip_lr == "yes":
ax.set_xlim(win_x[1], win_x[0])
else:
ax.set_xlim(win_x[0], win_x[1])
if flip_ud == "yes":
ax.set_ylim(win_y[0], win_y[1])
else:
ax.set_ylim(win_y[1], win_y[0])
## Flip
# if flip_lr == 'yes': fig.gca().invert_xaxis()
# if flip_ud == 'yes': fig.gca().invert_yaxis()
##########################################
##### Plot Fig 2 - Time series plot
# fig2 = plt.figure(num=2,figsize=(12,6))
fig2 = plt.figure(2, figsize=(12, 6))
ax2 = fig2.add_subplot(111)
try:
timeSeriesFile_2
h5timeseries_2 = h5py.File(timeSeriesFile_2)
dateList_2 = h5timeseries_2["timeseries"].keys()
dateList_2 = sorted(dateList_2)
dates_2, datevector_2 = ptime.date_list2vector(dateList_2)
datevector_all += list(set(datevector_2) - set(datevector_all))
datevector_all = sorted(datevector_all)
except:
pass
################################ Plot Code Package <start> #################################
def plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries):
ax2.cla()
print "\n-------------------------------------------------------------------------------"
disp_min = 0
disp_max = 0
############################# Plot Time Series ##############################
global ref_xsub, ref_ysub
##### 1.1 Plot Reference time series
try:
ref_xsub
ref_ysub
ref_xsub, ref_ysub = check_yx(ref_xsub, ref_ysub, radius, ax, rectColor)
print "----------------------------------------------------"
print "Reference Point:"
print "ref_x=" + str(ref_xsub[0]) + ":" + str(ref_xsub[1])
print "ref_y=" + str(ref_ysub[0]) + ":" + str(ref_ysub[1])
print "-----------------------------"
print "Time series with all dates:"
dis1, dis1_mean, dis1_std, dis1_vel = read_dis(ref_xsub, ref_ysub, dateList1, h5timeseries, unit)
(_, caps, _) = ax2.errorbar(
dates1,
dis1_mean,
yerr=dis1_std,
fmt="-ks",
ms=markerSize2,
lw=0,
alpha=1,
mfc=markerColor_ref,
mew=edgeWidth,
elinewidth=edgeWidth,
ecolor="black",
capsize=markerSize * 0.5,
)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis1_mean, dis1_std)
if not len(dateList) == len(dateList1):
print "-----------------------------"
print "Time series with dates of interest:"
dis12, dis12_mean, dis12_std, dis12_vel = read_dis(ref_xsub, ref_ysub, dateList, h5timeseries, unit)
(_, caps, _) = ax2.errorbar(
dates,
dis12_mean,
yerr=dis12_std,
fmt="-ks",
ms=markerSize2,
lw=0,
alpha=1,
mfc=markerColor_ref2,
mew=edgeWidth,
elinewidth=edgeWidth,
ecolor="black",
capsize=markerSize * 0.5,
)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis12_mean, dis12_std)
except:
pass
##### 1.2.0 Read y/x
print "\n----------------------------------------------------"
print "Point of Interest:"
xsub, ysub = check_yx(xsub, ysub, radius, ax, rectColor)
print "x=" + str(xsub[0]) + ":" + str(xsub[1])
print "y=" + str(ysub[0]) + ":" + str(ysub[1])
##### 1.2.1 Plot 2nd time series
try:
timeSeriesFile_2
print "-----------------------------"
print "2nd Time Series:"
dis2, dis2_mean, dis2_std, dis2_vel = read_dis(xsub, ysub, dateList_2, h5timeseries_2, unit)
(_, caps, _) = ax2.errorbar(
dates_2,
dis2_mean,
yerr=dis2_std,
fmt="-ko",
ms=markerSize2,
lw=0,
alpha=1,
mfc=markerColor2,
elinewidth=0,
ecolor="black",
capsize=0,
)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis2_mean, dis2_std)
except:
pass
##### 1.2.2 Plot 1st time series
print "-----------------------------"
print "Time Series:"
dis, dis_mean, dis_std, dis_vel = read_dis(xsub, ysub, dateList, h5timeseries, unit)
(_, caps, _) = ax2.errorbar(
dates,
dis_mean,
yerr=dis_std,
fmt="-ko",
ms=markerSize,
lw=lineWidth,
alpha=1,
mfc=markerColor,
elinewidth=edgeWidth,
ecolor="black",
capsize=markerSize * 0.5,
)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis_mean, dis_std)
####################### Figure Format #######################
## x axis format
try:
ax2 = ptime.adjust_xaxis_date(ax2, dateVecMinMax, fontSize)
except:
ax2 = ptime.adjust_xaxis_date(ax2, datevector_all, fontSize)
## y axis format
ax2.set_ylabel("Displacement [" + unit + "]", fontsize=fontSize)
try:
lbound
hbound
ax2.set_ylim(lbound, hbound)
except:
disp_buf = 0.2 * (disp_max - disp_min)
ax2.set_ylim(disp_min - disp_buf, disp_max + disp_buf)
for tick in ax2.yaxis.get_major_ticks():
tick.label.set_fontsize(fontSize)
## title
figTitle = "x=" + str(xsub[0]) + ":" + str(xsub[1]) + ", y=" + str(ysub[0]) + ":" + str(ysub[1])
try:
lonc = ullon + (xsub[0] + xsub[1]) / 2.0 * lon_step
latc = ullat + (ysub[0] + ysub[1]) / 2.0 * lat_step
figTitle += ", lalo=" + "%.4f,%.4f" % (latc, lonc)
except:
pass
ax2.set_title(figTitle)
################## Save and Output #####################
if saveFig == "yes":
print "-----------------------------"
Delay = {}
Delay["displacement"] = dis
Delay["unit"] = unit
Delay["time"] = datevector
Delay["velocity"] = dis_vel[0]
Delay["velocity_unit"] = unit + "/yr"
Delay["velocity_std"] = dis_vel[4]
figBase = "x" + str(xsub[0]) + "_" + str(xsub[1] - 1) + "y" + str(ysub[0]) + "_" + str(ysub[1] - 1)
sio.savemat(figBase + "_ts.mat", {"displacement": Delay})
print "saved " + figBase + "_ts.mat"
fig2.savefig(figBase + "_ts.pdf", bbox_inches="tight", transparent=True, dpi=fig_dpi)
print "saved " + figBase + "_ts.pdf"
if dispFig == "no":
fig.savefig(figBase + "_vel.png", bbox_inches="tight", transparent=True, dpi=fig_dpi)
print "saved " + figBase + "_vel.png"
################################ Plot Code Package <end> #################################
########### 1. Plot Time Series with x/y ##########
try:
xsub
ysub
plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries)
except:
print "No x/y input"
pass
########### 2. Plot Time Series with Click ##########
## similar to 1. Plot Time Series with x/y
def onclick(event):
ax2.cla()
xsub = [int(event.xdata)]
ysub = [int(event.ydata)]
plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries)
if dispFig == "yes":
plt.show()
try:
cid = fig.canvas.mpl_connect("button_press_event", onclick)
except:
pass
if dispFig == "yes":
plt.show()
def main(argv):
inps = cmdLineParse()
#print '\n********** Inversion: Time Series to Velocity ***********'
atr = readfile.read_attribute(inps.timeseries_file)
k = atr['FILE_TYPE']
print 'input '+k+' file: '+inps.timeseries_file
if not k == 'timeseries':
sys.exit('ERROR: input file is not timeseries!')
h5file = h5py.File(inps.timeseries_file)
#####################################
## Date Info
dateListAll = sorted(h5file[k].keys())
dateListAll = ptime.yyyymmdd(dateListAll)
yyListAll = ptime.yyyymmdd2years(dateListAll)
print '--------------------------------------------'
print 'Dates from input file: '+str(len(dateListAll))
print dateListAll
# Extrac exclude dates from input arguments
inps.datesNot2include = []
# 1. template_file
if inps.template_file:
inps = update_inps_from_template(inps, inps.template_file)
# 2. ex_date
if inps.ex_date:
for ex_date in inps.ex_date:
if os.path.isfile(ex_date):
ex_date = ptime.read_date_list(ex_date)
else:
ex_date = [ptime.yyyymmdd(ex_date)]
inps.datesNot2include += list(set(ex_date) - set(inps.datesNot2include))
# delete dates not existed in input file
inps.datesNot2include = list(set(inps.datesNot2include).intersection(dateListAll))
print 'date excluded:'+str(inps.datesNot2include)
# 3. min_date
if inps.min_date:
inps.min_date = ptime.yyyymmdd(inps.min_date)
print 'minimum date: '+inps.min_date
yy_min = ptime.yyyymmdd2years(inps.min_date)
for i in range(len(dateListAll)):
date = dateListAll[i]
if yyListAll[i] < yy_min and date not in inps.datesNot2include:
print ' remove date: '+date
inps.datesNot2include.append(date)
# 4. max_date
if inps.max_date:
inps.max_date = ptime.yyyymmdd(inps.max_date)
print 'minimum date: '+inps.max_date
yy_max = ptime.yyyymmdd2years(inps.max_date)
for i in range(len(dateListAll)):
date = dateListAll[i]
if yyListAll[i] > yy_max and date not in inps.datesNot2include:
print ' remove date: '+date
inps.datesNot2include.append(date)
# Summary
dateList = sorted(list(set(dateListAll) - set(inps.datesNot2include)))
print '--------------------------------------------'
if len(dateList) == len(dateListAll):
print 'using all dates to calculate the velocity'
else:
print 'Dates used to estimate the velocity: '+str(len(dateList))
print dateList
print '--------------------------------------------'
# Date Aux Info
dates, datevector = ptime.date_list2vector(dateList)
#####################################
## Inversion
# Design matrix
B=np.ones([len(datevector),2])
B[:,0]=datevector
#B1 = np.linalg.pinv(B)
B1 = np.dot(np.linalg.inv(np.dot(B.T,B)),B.T)
B1 = np.array(B1,np.float32)
# Loading timeseries
print "Loading time series file: "+inps.timeseries_file+' ...'
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
dateNum = len(dateList)
timeseries = np.zeros([dateNum,length*width],np.float32)
start_time = time.time()
for i in range(dateNum):
date = dateList[i]
ut.print_progress(i+1, dateNum, prefix='loading:', suffix=date, elapsed_time=time.time()-start_time)
timeseries[i,:] = h5file[k].get(date)[:].flatten()
h5file.close()
# Velocity Inversion
print 'Calculating velocity ...'
x = np.dot(B1,timeseries)
velocity = np.reshape(x[0,:],[length,width])
print 'Calculating rmse ...'
timeseries_linear = np.dot(B,x)
rmse = np.reshape(np.sqrt((np.sum((timeseries_linear-timeseries)**2,0))/dateNum),[length,width])
print 'Calculating the standard deviation of the estimated velocity ...'
residual = timeseries_linear - timeseries
s1 = np.sqrt(np.sum(residual**2,0)/(dateNum-2))
s2 = np.sqrt(np.sum((datevector-np.mean(datevector))**2))
std = np.reshape(s1/s2,[length,width])
# SSt=np.sum((timeseries-np.mean(timeseries,0))**2,0)
# SSres=np.sum(residual**2,0)
# SS_REG=SSt-SSres
# Rsquared=np.reshape(SS_REG/SSt,[length,width])
######################################################
# covariance of the velocities
#####################################
# Output file name
if not inps.outfile:
inps.outfile = 'velocity.h5'
if inps.datesNot2include:
inps.outfile = os.path.splitext(inps.outfile)[0]+'_ex'+os.path.splitext(inps.outfile)[1]
inps.outfile_rmse = 'rmse_'+inps.outfile
inps.outfile_std = 'std_'+inps.outfile
inps.outfile_r2 = 'R2_'+inps.outfile
# Attributes
atr['date1'] = datevector[0]
atr['date2'] = datevector[dateNum-1]
# File Writing
print '--------------------------------------'
atr['FILE_TYPE'] = 'velocity'
print 'writing >>> '+inps.outfile
writefile.write(velocity, atr, inps.outfile)
atr['FILE_TYPE'] = 'rmse'
print 'writing >>> '+inps.outfile_rmse
writefile.write(rmse, atr, inps.outfile_rmse)
atr['FILE_TYPE'] = 'rmse'
print 'writing >>> '+inps.outfile_std
writefile.write(std, atr, inps.outfile_std)
print 'Done.'
return inps.outfile
def main(argv):
inps = cmdLineParse()
suffix = '_demErr'
if not inps.outfile:
inps.outfile = os.path.splitext(
inps.timeseries_file)[0] + suffix + os.path.splitext(
inps.timeseries_file)[1]
# 1. template_file
if inps.template_file:
print 'read option from template file: ' + inps.template_file
inps = read_template2inps(inps.template_file, inps)
# Read Time Series
print "loading time series: " + inps.timeseries_file
atr = readfile.read_attribute(inps.timeseries_file)
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
h5 = h5py.File(inps.timeseries_file)
date_list = sorted(h5['timeseries'].keys())
date_num = len(date_list)
print 'number of acquisitions: ' + str(date_num)
# Exclude date info
#inps.ex_date = ['20070115','20100310']
if inps.ex_date:
inps = get_exclude_date(inps, date_list)
if inps.ex_date:
inps.ex_flag = np.array([i not in inps.ex_date for i in date_list])
timeseries = np.zeros((len(date_list), length * width), np.float32)
prog_bar = ptime.progress_bar(maxValue=date_num, prefix='loading: ')
for i in range(date_num):
date = date_list[i]
d = h5['timeseries'].get(date)[:]
timeseries[i][:] = d.flatten('F')
prog_bar.update(i + 1, suffix=date)
del d
h5.close()
prog_bar.close()
# Perpendicular Baseline
print 'read perpendicular baseline'
try:
inps.pbase = ut.perp_baseline_timeseries(atr, dimension=0)
if inps.pbase.shape[1] > 1:
print '\tconsider P_BASELINE variation in azimuth direction'
else:
pbase = inps.pbase
except:
print '\tCannot find P_BASELINE_TIMESERIES from timeseries file.'
print '\tTrying to calculate it from interferograms file'
if inps.ifgram_file:
inps.pbase = np.array(
ut.perp_baseline_ifgram2timeseries(
inps.ifgram_file)[0]).reshape(date_num, 1)
else:
message = 'No interferogram file input!\n'+\
'Can not correct for DEM residula without perpendicular base info!'
raise Exception(message)
# Temporal Baseline
print 'read temporal baseline'
inps.tbase = np.array(ptime.date_list2tbase(date_list)[0]).reshape(
date_num, 1)
# Incidence angle (look angle in the paper)
if inps.incidence_angle:
if os.path.isfile(inps.incidence_angle):
print 'reading incidence angle from file: ' + inps.incidence_angle
inps.incidence_angle = readfile.read(inps.incidence_angle)[0]
else:
try:
inps.incidence_angle = np.array(float(inps.incidence_angle))
print 'use input incidence angle : ' + str(
inps.incidence_angle)
except:
raise ValueError('Can not read input incidence angle: ' +
str(inps.incidence_angle))
else:
print 'calculate incidence angle using attributes of time series file'
if inps.pbase.shape[1] > 1:
inps.incidence_angle = ut.incidence_angle(atr, dimension=2)
else:
inps.incidence_angle = ut.incidence_angle(atr, dimension=1)
inps.incidence_angle *= np.pi / 180.0
# Range distance
if inps.range_dis:
if os.path.isfile(inps.range_dis):
print 'reading range distance from file: ' + inps.range_dis
inps.range_dis = readfile.read(inps.range_dis)[0]
else:
try:
inps.range_dis = np.array(float(inps.range_dis))
print 'use input range distance : ' + str(inps.range_dis)
except:
raise ValueError('Can not read input incidence angle: ' +
str(inps.range_dis))
else:
print 'calculate range distance using attributes from time series file'
if inps.pbase.shape[1] > 1:
inps.range_dis = ut.range_distance(atr, dimension=2)
else:
inps.range_dis = ut.range_distance(atr, dimension=1)
# Design matrix - temporal deformation model using tbase
print '-------------------------------------------------'
if inps.phase_velocity:
print 'using phase velocity history'
A1 = np.ones((date_num - 1, 1))
A2 = (inps.tbase[1:date_num] + inps.tbase[0:date_num - 1]) / 2.0
A3 = (inps.tbase[1:date_num]**3 - inps.tbase[0:date_num - 1]**
3) / np.diff(inps.tbase, axis=0) / 6.0
#A3 = (inps.tbase[1:date_num]**2 + inps.tbase[1:date_num]*inps.tbase[0:date_num-1] +\
# inps.tbase[0:date_num-1]**2) / 6.0
else:
print 'using phase history'
A1 = np.hstack((np.ones((date_num, 1)), inps.tbase))
A2 = inps.tbase**2 / 2.0
A3 = inps.tbase**3 / 6.0
# Polynomial order of model
print "temporal deformation model's polynomial order = " + str(
inps.poly_order)
if inps.poly_order == 1: A_def = A1
elif inps.poly_order == 2: A_def = np.hstack((A1, A2))
elif inps.poly_order == 3: A_def = np.hstack((A1, A2, A3))
# step function
if inps.step_date:
print "temporal deformation model's step function step at " + inps.step_date
step_yy = ptime.yyyymmdd2years(inps.step_date)
yy_list = ptime.yyyymmdd2years(date_list)
flag_array = np.array(yy_list) >= step_yy
A_step = np.zeros((date_num, 1))
A_step[flag_array] = 1.0
A_def = np.hstack((A_def, A_step))
# Heresh's original code for phase history approach
#A_def = np.hstack((A2,A1,np.ones((date_num,1))))
print '-------------------------------------------------'
##---------------------------------------- Loop for L2-norm inversion -----------------------------------##
delta_z_mat = np.zeros([length, width], dtype=np.float32)
resid_n = np.zeros([A_def.shape[0], length * width], dtype=np.float32)
constC = np.zeros([length, width], dtype=np.float32)
#delta_a_mat = np.zeros([length, width])
if inps.incidence_angle.ndim == 2 and inps.range_dis.ndim == 2:
print 'inversing using L2-norm minimization (unweighted least squares)'\
' pixel by pixel: %d loops in total' % (length*width)
prog_bar = ptime.progress_bar(maxValue=length * width,
prefix='calculating: ')
for i in range(length * width):
row = i % length
col = i / length
range_dis = inps.range_dis[row, col]
inc_angle = inps.incidence_angle[row, col]
# Consider P_BASELINE variation within one interferogram
if inps.pbase.shape[1] > 1:
pbase = inps.pbase[:, row].reshape(date_num, 1)
# Design matrix - DEM error using pbase, range distance and incidence angle
A_delta_z = pbase / (range_dis * np.sin(inc_angle))
if inps.phase_velocity:
pbase_v = np.diff(pbase, axis=0) / np.diff(inps.tbase, axis=0)
A_delta_z_v = pbase_v / (range_dis * np.sin(inc_angle))
A = np.hstack((A_delta_z_v, A_def))
else:
A = np.hstack((A_delta_z, A_def))
# L-2 norm inversion
if inps.ex_date:
A_inv = np.linalg.pinv(A[inps.ex_flag, :])
else:
A_inv = np.linalg.pinv(A)
# Get unknown parameters X = [delta_z, vel, acc, delta_acc, ...]
ts_dis = timeseries[:, i]
if inps.phase_velocity:
ts_dis = np.diff(ts_dis, axis=0) / np.diff(inps.tbase, axis=0)
if inps.ex_date:
X = np.dot(A_inv, ts_dis[inps.ex_flag])
else:
X = np.dot(A_inv, ts_dis)
# Residual vector n
resid_n[:, i] = ts_dis - np.dot(A, X)
# Update DEM error / timeseries matrix
delta_z = X[0]
delta_z_mat[row, col] = delta_z
if inps.update_timeseries:
timeseries[:, i] -= np.dot(A_delta_z, delta_z).flatten()
prog_bar.update(i + 1, every=length * width / 100)
prog_bar.close()
elif inps.incidence_angle.ndim == 1 and inps.range_dis.ndim == 1:
print 'inversing using L2-norm minimization (unweighted least squares)'\
' column by column: %d loops in total' % (width)
prog_bar = ptime.progress_bar(maxValue=width, prefix='calculating: ')
for i in range(width):
range_dis = inps.range_dis[i]
inc_angle = inps.incidence_angle[i]
# Design matrix - DEM error using pbase, range distance and incidence angle
A_delta_z = pbase / (range_dis * np.sin(inc_angle))
if inps.phase_velocity:
pbase_v = np.diff(pbase, axis=0) / np.diff(inps.tbase, axis=0)
A_delta_z_v = pbase_v / (range_dis * np.sin(inc_angle))
A = np.hstack((A_delta_z_v, A_def))
else:
A = np.hstack((A_delta_z, A_def))
# L-2 norm inversion
if inps.ex_date:
A_inv = np.linalg.pinv(A[inps.ex_flag, :])
else:
A_inv = np.linalg.pinv(A)
# Get unknown parameters X = [delta_z, vel, acc, delta_acc, ...]
ts_dis = timeseries[:, i * length:(i + 1) * length]
if inps.phase_velocity:
ts_dis = np.diff(ts_dis, axis=0) / np.diff(inps.tbase, axis=0)
if inps.ex_date:
X = np.dot(A_inv, ts_dis[inps.ex_flag, :])
else:
X = np.dot(A_inv, ts_dis)
# Residual vector n
resid_n[:, i * length:(i + 1) * length] = ts_dis - np.dot(A, X)
constC[:, i] = X[1].reshape((1, length))
# Update DEM error / timeseries matrix
delta_z = X[0].reshape((1, length))
delta_z_mat[:, i] = delta_z
if inps.update_timeseries:
timeseries[:, i * length:(i + 1) * length] -= np.dot(
A_delta_z, delta_z)
prog_bar.update(i + 1, every=width / 100)
prog_bar.close()
elif inps.incidence_angle.ndim == 0 and inps.range_dis.ndim == 0:
print 'inversing using L2-norm minimization (unweighted least squares) for the whole area'
# Design matrix - DEM error using pbase, range distance and incidence angle
A_delta_z = pbase / (inps.range_dis * np.sin(inps.incidence_angle))
if inps.phase_velocity:
pbase_v = np.diff(pbase, axis=0) / np.diff(inps.tbase, axis=0)
A_delta_z_v = pbase_v / (inps.range_dis *
np.sin(inps.incidence_angle))
A = np.hstack((A_delta_z_v, A_def))
else:
A = np.hstack((A_delta_z, A_def))
# L-2 norm inversion
if inps.ex_date:
A_inv = np.linalg.pinv(A[inps.ex_flag, :])
else:
A_inv = np.linalg.pinv(A)
# Get unknown parameters X = [delta_z, vel, acc, delta_acc, ...]
if inps.phase_velocity:
timeseries = np.diff(timeseries, axis=0) / np.diff(inps.tbase,
axis=0)
if inps.ex_date:
X = np.dot(A_inv, timeseries[inps.ex_flag, :])
else:
X = np.dot(A_inv, timeseries)
# Residual vector n
resid_n = ts_dis - np.dot(A, X)
# Update DEM error / timeseries matrix
delta_z_mat = X[0].reshape((1, length * width))
if inps.update_timeseries:
timeseries -= np.dot(A_delta_z, delta_z_mat)
delta_z_mat = np.reshape(delta_z_mat, [length, width], order='F')
else:
print 'ERROR: Script only support same dimension for both incidence angle and range distance matrix.'
print 'dimension of incidence angle: ' + str(inps.incidence_angle.ndim)
print 'dimension of range distance: ' + str(inps.range_dis.ndim)
sys.exit(1)
##------------------------------------------------ Output --------------------------------------------##
# DEM error file
if 'Y_FIRST' in atr.keys():
dem_error_file = 'demGeo_error.h5'
else:
dem_error_file = 'demRadar_error.h5'
#if inps.phase_velocity: suffix = '_pha_poly'+str(inps.poly_order)
#else: suffix = '_vel_poly'+str(inps.poly_order)
#dem_error_file = os.path.splitext(dem_error_file)[0]+suffix+os.path.splitext(dem_error_file)[1]
print 'writing >>> ' + dem_error_file
atr_dem_error = atr.copy()
atr_dem_error['FILE_TYPE'] = 'dem'
atr_dem_error['UNIT'] = 'm'
writefile.write(delta_z_mat, atr_dem_error, dem_error_file)
## Phase Constant C = resid_n[0,:]
#atrC = atr.copy()
#atrC['FILE_TYPE'] = 'mask'
#atrC['UNIT'] = 'm'
#writefile.write(constC, atrC, 'constD.h5')
## Corrected DEM file
#if inps.dem_file:
# inps.dem_outfile = os.path.splitext(inps.dem_file)[0]+suffix+os.path.splitext(inps.dem_file)[1]
# print '--------------------------------------'
# print 'writing >>> '+inps.dem_outfile
# dem, atr_dem = readfile.read(inps.dem_file)
# writefile.write(dem+delta_z_mat, atr_dem, inps.dem_outfile)
#outfile = 'delta_acc.h5'
#print 'writing >>> '+outfile
#atr_dem_error = atr.copy()
#atr_dem_error['FILE_TYPE'] = 'velocity'
#atr_dem_error['UNIT'] = 'm/s'
#writefile.write(delta_a_mat, atr_dem_error, outfile)
#print '**************************************'
# Corrected Time Series
if inps.update_timeseries:
print 'writing >>> ' + inps.outfile
print 'number of dates: ' + str(len(date_list))
h5out = h5py.File(inps.outfile, 'w')
group = h5out.create_group('timeseries')
prog_bar = ptime.progress_bar(maxValue=date_num, prefix='writing: ')
for i in range(date_num):
date = date_list[i]
d = np.reshape(timeseries[i][:], [length, width], order='F')
dset = group.create_dataset(date, data=d, compression='gzip')
prog_bar.update(i + 1, suffix=date)
prog_bar.close()
for key, value in atr.iteritems():
group.attrs[key] = value
h5out.close()
outFile = os.path.splitext(inps.outfile)[0] + 'InvResid.h5'
print 'writing >>> ' + outFile
print 'number of dates: ' + str(A_def.shape[0])
h5out = h5py.File(outFile, 'w')
group = h5out.create_group('timeseries')
prog_bar = ptime.progress_bar(maxValue=A_def.shape[0], prefix='writing: ')
for i in range(A_def.shape[0]):
date = date_list[i]
d = np.reshape(resid_n[i][:], [length, width], order='F')
dset = group.create_dataset(date, data=d, compression='gzip')
prog_bar.update(i + 1, suffix=date)
prog_bar.close()
# Attribute
for key, value in atr.iteritems():
group.attrs[key] = value
if A_def.shape[0] == date_num:
group.attrs['UNIT'] = 'm'
else:
group.attrs['UNIT'] = 'm/yr'
h5out.close()
return
def main(argv):
inps = cmdLineParse()
suffix = '_demErr'
if not inps.outfile:
inps.outfile = os.path.splitext(inps.timeseries_file)[0]+suffix+os.path.splitext(inps.timeseries_file)[1]
if inps.template_file:
print 'read option from template file: '+inps.template_file
inps = read_template2inps(inps.template_file, inps)
##### Read Data
atr = readfile.read_attribute(inps.timeseries_file)
coordType = 'radar'
if 'Y_FIRST' in atr.keys():
coordType = 'geo'
# 1. Incidence angle
try:
inps.inc_angle_file = ut.get_file_list(inps.inc_angle_file, coord=coordType)[0]
except ValueError:
print 'No incidence angle file found!\nRun incidence_angle.py to generate it.'
print 'read incidence angle from file: '+str(inps.inc_angle_file)
inps.inc_angle = readfile.read(inps.inc_angle_file, epoch='incidenceAngle')[0].flatten()
inps.inc_angle *= np.pi/180.0
# 2. Slant Range distance
try:
inps.range_dist_file = ut.get_file_list(inps.range_dist_file, coord=coordType)[0]
except ValueError:
print 'No range distance file found!\nRun range_distance.py to generate it.'
print 'read slant range distance from file: '+str(inps.range_dist_file)
inps.range_dist = readfile.read(inps.range_dist_file, epoch='slantRangeDistance')[0].flatten()
# 3. Perp Baseline - 1D in time, 0D/1D in space (azimuth)
print 'read perpendicular baseline'
try:
inps.pbase = ut.perp_baseline_timeseries(atr, dimension=1)
if inps.pbase.shape[1] > 1:
print 'consider perp baseline variance in azimuth direction'
except valueError:
print 'No P_BASELINE_TIMESERIES found in timeseries file.\n'+\
'Can not correct for DEM residula without it!'
# 4. Time Series - 1D in time, 1D in space (flattened)
print "read time series file: " + inps.timeseries_file
h5 = h5py.File(inps.timeseries_file)
date_list = sorted(h5['timeseries'].keys())
date_num = len(date_list)
inps.tbase = np.array(ptime.date_list2tbase(date_list)[0]).reshape(-1,1)
#Mark dates used in the estimation
inps.ex_date = check_exclude_date(inps.ex_date, date_list)
inps.date_flag = np.array([i not in inps.ex_date for i in date_list], dtype=np.bool_)
if inps.poly_order > np.sum(inps.date_flag):
raise ValueError("ERROR: input polynomial order=%d is larger than number of acquisition=%d used in estimation!" %\
(inps.poly_order, np.sum(inps.date_flag)))
length = int(atr['FILE_LENGTH'])
width = int(atr['WIDTH'])
pixel_num = length*width
timeseries = np.zeros((date_num, pixel_num),np.float32)
for i in range(date_num):
timeseries[i] = h5['timeseries'].get(date_list[i])[:].flatten()
sys.stdout.write('\rreading acquisition %3d/%3d ...' % (i+1, date_num))
sys.stdout.flush()
h5.close()
print ''
##### Design matrix - temporal deformation model
print '-------------------------------------------------'
print 'Correct topographic phase residual using Fattahi and Amelung (2013, IEEE-TGRS)'
msg = 'minimum-norm constrain on: phase'
if inps.phase_velocity:
msg += ' velocity'
print msg
# Heresh's original code for phase history approach
#A1 = np.hstack((np.ones((date_num, 1)), inps.tbase))
#A2 = inps.tbase**2 / 2.0
#A_def = np.hstack((A2,A1,np.ones((date_num,1))))
# 1. Polynomial - 2D matrix in size of (date_num, polyOrder+1)
print "temporal deformation model: polynomial order = "+str(inps.poly_order)
A_def = np.ones((date_num, 1), np.float32)
for i in range(inps.poly_order):
Ai = inps.tbase**(i+1) / gamma(i+2)
Ai = np.array(Ai, np.float32).reshape(-1,1)
A_def = np.hstack((A_def, Ai))
# 2. Step function - 2D matrix in size of (date_num, stepNum)
if inps.step_date:
print "temporal deformation model: step functions at "+str(inps.step_date)
yySteps = ptime.yyyymmdd2years(inps.step_date)
yyList = np.array(ptime.yyyymmdd2years(date_list)).reshape(-1,1)
for yyStep in yySteps:
Ai = yyList > yyStep
Ai = np.array(Ai, np.float32).reshape(-1,1)
A_def = np.hstack((A_def, Ai))
inps.step_num = len(inps.step_date)
print '-------------------------------------------------'
##---------------------------------------- Loop for L2-norm inversion -----------------------------------##
## Output estimated steps
print 'ordinal least squares (OLS) inversion using L2-norm minimization'
timeseriesCor = np.zeros((date_num, pixel_num), dtype=np.float32)
timeseriesRes = np.zeros((date_num, pixel_num), dtype=np.float32)
topoRes = np.zeros(pixel_num, dtype=np.float32)
constC = np.zeros(pixel_num, dtype=np.float32)
if inps.step_num > 0:
stepModel = np.zeros((inps.step_num, pixel_num), dtype=np.float32)
print 'skip pixels with zero/nan value in geometry files - incidence angle and range distance'
mask = np.multiply(~np.isnan(inps.inc_angle), ~np.isnan(inps.range_dist))
mask[inps.inc_angle == 0.] = 0
mask[inps.range_dist == 0.] = 0
pixel_num2inv = np.sum(mask)
pixel_idx2inv = np.where(mask)[0]
print 'number of pixels in the file: %d' % (pixel_num)
print 'number of pixels to inverse: %d' % (pixel_num2inv)
if inps.pbase.shape[1] == 1:
pbase = inps.pbase
prog_bar = ptime.progress_bar(maxValue=pixel_num)
for i in range(pixel_num2inv):
prog_bar.update(i+1, every=1000, suffix='%s/%s pixels'%(str(i+1), str(pixel_num2inv)))
idx = pixel_idx2inv[i]
r = inps.range_dist[idx]
inc_angle = inps.inc_angle[idx]
if inps.pbase.shape[1] > 1:
pbase = inps.pbase[:, int(idx/width)].reshape(-1,1)
A_deltaZ = pbase / (r * np.sin(inc_angle))
A = np.hstack((A_deltaZ, A_def))
ts = timeseries[:,idx].reshape(date_num,-1)
deltaZ, tsCor, tsRes, stepEst = topographic_residual_inversion(ts, A, inps)
topoRes[idx:idx+1] = deltaZ
timeseriesCor[:,idx:idx+1] = tsCor
timeseriesRes[:,idx:idx+1] = tsRes
if inps.step_num > 0:
stepModel[:,idx:idx+1] = stepEst
prog_bar.close()
##------------------------------------------------ Output --------------------------------------------##
# 1. DEM error file
if 'Y_FIRST' in atr.keys():
deltaZFile = 'demGeo_error.h5'
else:
deltaZFile = 'demRadar_error.h5'
print 'writing >>> '+deltaZFile
atrDeltaZ = atr.copy()
atrDeltaZ['FILE_TYPE'] = 'dem'
atrDeltaZ['UNIT'] = 'm'
writefile.write(topoRes.reshape(length, width), atrDeltaZ, deltaZFile)
# 2. Topo Residual Corrected Time Series
print 'writing >>> '+inps.outfile
h5 = h5py.File(inps.outfile,'w')
group = h5.create_group('timeseries')
for i in range(date_num):
sys.stdout.write('\rwriting acquisition %3d/%3d ...' % (i+1, date_num))
sys.stdout.flush()
dset = group.create_dataset(date_list[i], data=timeseriesCor[i].reshape(length, width), compression='gzip')
print ''
for key,value in atr.iteritems():
group.attrs[key] = value
h5.close()
# 3. Inversion residual Time Series
tsResFile = os.path.join(os.path.dirname(inps.outfile), 'timeseriesResidual.h5')
print 'writing >>> '+os.path.basename(tsResFile)
h5 = h5py.File(tsResFile,'w')
group = h5.create_group('timeseries')
for i in range(date_num):
sys.stdout.write('\rwriting acquisition %3d/%3d ...' % (i+1, date_num))
sys.stdout.flush()
dset = group.create_dataset(date_list[i], data=timeseriesRes[i].reshape(length, width), compression='gzip')
print ''
# Attribute
for key,value in atr.iteritems():
group.attrs[key] = value
h5.close()
# 4. Step temporal Model estimation
if inps.step_num > 0:
stepFile = os.path.join(os.path.dirname(inps.outfile), 'timeseriesStepModel.h5')
print 'writing >>> '+os.path.basename(stepFile)
h5 = h5py.File(stepFile,'w')
group = h5.create_group('timeseries')
for i in range(inps.step_num):
sys.stdout.write('\rwriting acquisition %3d/%3d ...' % (i+1, inps.step_num))
sys.stdout.flush()
dset = group.create_dataset(inps.step_date[i], data=stepModel[i].reshape(length, width), compression='gzip')
print ''
# Attribute
for key,value in atr.iteritems():
group.attrs[key] = value
group.attrs.pop('ref_date')
h5.close()
print 'Done.'
return
def main(argv):
## Default settings
contour_step = 200.0
contour_sigma = 3.0
demShade = 'yes'
demContour = 'yes'
global markerSize, markderSize2, markerColor, markerColor2, rectColor
global lineWidth, lineWidth2, edgeWidth, fontSize
#global markerColor_ref, markerColor_ref2
markerSize = 16
markerSize2 = 16
markerColor = 'crimson' # g
markerColor2 = 'lightgray'
markerColor_ref = 'white'
markerColor_ref2 = 'lightgray'
rectColor = 'black'
lineWidth = 0
lineWidth2 = 0
edgeWidth = 1.5
fontSize = 16
global unit, radius, saveFig, dispFig, fig_dpi
fig_dpi = 300
radius = 0
saveFig = 'no'
dispFig = 'yes'
unit = 'cm'
dispDisplacement = 'no'
dispOpposite = 'no'
dispContour = 'only'
smoothContour = 'no'
contour_step = 200
showRef = 'yes'
vel_alpha = 1.0
zero_start = 'yes'
global ref_xsub, ref_ysub, ref_date
global h5timeseries_2, dates_2, dateList_2
global lbound, hbound
############### Check Inputs ##################
if len(sys.argv) < 2:
usage()
sys.exit(1)
elif len(sys.argv) == 2:
if argv[0] == '-h':
usage()
sys.exit(1)
elif os.path.isfile(argv[0]):
timeSeriesFile = argv[0]
h5timeseries = h5py.File(timeSeriesFile)
k = h5timeseries.keys()
if not 'timeseries' in k:
print 'ERROR: Input file is ' + k[
0] + '.\n\tOnly timeseries is supported.\n'
sys.exit(1)
else:
usage()
sys.exit(1)
elif len(sys.argv) > 2:
try: opts, args = getopt.getopt(argv,"f:F:v:a:b:s:m:c:w:u:l:h:D:V:t:T:d:r:x:y:X:Y:o:E:",
['save','nodisplay','unit=','exclude=','ref-date=','rect-color=',\
'zero-start=','zoom-x=','zoom-y=','zoom-lon','zoom-lat','lalo=',\
'opposite','dem-nocontour','dem-noshade','displacement','contour-step=',\
'contour-smooth=','LALO='])
except getopt.GetoptError:
usage()
sys.exit(1)
for opt, arg in opts:
if opt == '-f': timeSeriesFile = arg
elif opt == '-F': timeSeriesFile_2 = arg
elif opt == '-v': velocityFile = arg
elif opt == '-a': vmin = float(arg)
elif opt == '-b': vmax = float(arg)
elif opt == '-s': fontSize = int(arg)
elif opt == '-m':
markerSize = int(arg)
markerSize2 = int(arg)
elif opt == '-c':
markerColor = arg
elif opt == '-w':
lineWidth = int(arg)
elif opt == '-u':
unit = arg
elif opt == '-l':
lbound = float(arg)
elif opt == '-h':
hbound = float(arg)
elif opt == '-D':
demFile = arg
elif opt == '-V':
contour_step = float(arg)
elif opt == '-t':
minDate = arg
elif opt == '-T':
maxDate = arg
elif opt == '-r':
radius = abs(int(arg))
elif opt == '-x':
xsub = sorted([int(i) for i in arg.split(':')])
elif opt == '-y':
ysub = sorted([int(i) for i in arg.split(':')])
elif opt == '-X':
ref_xsub = sorted([int(i) for i in arg.split(':')])
elif opt == '-Y':
ref_ysub = sorted([int(i) for i in arg.split(':')])
elif opt == '--contour-step':
contour_step = float(arg)
elif opt == '--contour-smooth':
contour_sigma = float(arg)
elif opt == '--dem-nocontour':
demContour = 'no'
elif opt == '--dem-noshade':
demShade = 'no'
elif opt == '--displacement':
dispDisplacement = 'yes'
elif opt in ['-E', '--exclude']:
datesNot2show = arg.split(',')
elif opt in '--lalo':
lalosub = [float(i) for i in arg.split(',')]
elif opt in '--LALO':
ref_lalosub = [float(i) for i in arg.split(',')]
elif opt in ['--rect-color']:
rectColor = arg
elif opt in ['--ref-date']:
ref_date = ptime.yyyymmdd(arg)
elif opt in ['-u', '--unit']:
unit = arg.lower()
elif opt == '--save':
saveFig = 'yes'
elif opt == '--nodisplay':
dispFig = 'no'
saveFig = 'yes'
elif opt == '--opposite':
dispOpposite = 'yes'
elif opt == '--zero-start':
zero_start = arg.lower()
elif opt == '--zoom-x':
win_x = sorted([int(i) for i in arg.split(':')])
elif opt == '--zoom-y':
win_y = sorted([int(i) for i in arg.split(':')])
elif opt == '--zoom-lon':
win_lon = sorted([float(i) for i in arg.split(':')])
elif opt == '--zoom-lat':
win_lat = sorted([float(i) for i in arg.split(':')])
##############################################################
## Read time series file info
if not os.path.isfile(timeSeriesFile):
print '\nERROR: Input time series file does not exist: ' + timeSeriesFile + '\n'
sys.exit(1)
h5timeseries = h5py.File(timeSeriesFile, 'r')
k = h5timeseries.keys()
# read h5 file and its group type
if not 'timeseries' in k:
print 'ERROR: Input file is ' + k[
0] + '.\n\tOnly timeseries is supported.\n'
sys.exit(1)
atr = readfile.read_attribute(timeSeriesFile)
dateList1 = sorted(h5timeseries['timeseries'].keys())
dates1, datevector1 = ptime.date_list2vector(dateList1)
print '\n************ Time Series Display - Point *************'
##### Select Check
try:
lalosub
xsub = subset.coord_geo2radar([lalosub[1]], atr, 'longitude')
ysub = subset.coord_geo2radar([lalosub[0]], atr, 'latitude')
xsub = [xsub]
ysub = [ysub]
if radius == 0: radius = 3
except:
pass
try:
ref_lalosub
ref_xsub = subset.coord_geo2radar([ref_lalosub[1]], atr, 'longitude')
ref_ysub = subset.coord_geo2radar([ref_lalosub[0]], atr, 'latitude')
ref_xsub = [ref_xsub]
ref_ysub = [ref_ysub]
if radius == 0: radius = 3
except:
pass
##############################################################
global dates, dateList, datevector_all, dateListMinMax
print '*******************'
print 'All dates existed:'
print dateList1
print '*******************'
## Check exclude date input
try:
datesNot2show
if os.path.isfile(datesNot2show[0]):
try:
datesNot2show = ptime.read_date_list(datesNot2show[0])
except:
print 'Can not read date list file: ' + datesNot2show[0]
print 'dates not to show: ' + str(datesNot2show)
except:
datesNot2show = []
## Check Min / Max Date
dateListMinMax = []
try:
minDate
minDate = ptime.yyyymmdd(minDate)
dateListMinMax.append(minDate)
minDateyy = ptime.yyyymmdd2years(minDate)
print 'minimum date: ' + minDate
for date in dateList1:
yy = ptime.yyyymmdd2years(date)
if yy < minDateyy:
datesNot2show.append(date)
except:
pass
try:
maxDate
maxDate = ptime.yyyymmdd(maxDate)
dateListMinMax.append(maxDate)
maxDateyy = ptime.yyyymmdd2years(maxDate)
print 'maximum date: ' + maxDate
for date in dateList1:
yy = ptime.yyyymmdd2years(date)
if yy > maxDateyy:
datesNot2show.append(date)
except:
pass
dateListMinMax = sorted(dateListMinMax)
if not dateListMinMax: print 'no min/max date input.'
else: datesMinMax, dateVecMinMax = ptime.date_list2vector(dateListMinMax)
## Finalize Date List
try:
dateList = []
for date in dateList1:
if date not in datesNot2show:
dateList.append(date)
print '--------------------------------------------'
print 'dates used to show time series displacements:'
print dateList
print '--------------------------------------------'
except:
dateList = dateList1
print 'using all dates to show time series displacement'
## Read Date Info (x axis for time series display)
dates, datevector = ptime.date_list2vector(dateList)
datevector_all = list(datevector)
## Check reference date input
try:
ref_date
if not ref_date in dateList:
print 'Reference date - ' + ref_date + ' - is not included in date list to show.'
sys.exit(1)
else:
print 'reference date: ' + ref_date
except:
if zero_start == 'yes':
ref_date = dateList[0]
print 'set the 1st date as reference for displacement display.'
else:
pass
##############################################################
##### Plot Fig 1 - Velocity / last epoch of time series / DEM
fig = plt.figure(1)
ax = fig.add_subplot(111)
##### Check subset range
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
print 'file size: ' + str(length) + ', ' + str(width)
try:
win_y = subset.coord_geo2radar(win_lat, atr, 'latitude')
except:
try:
win_y
except:
win_y = [0, length]
try:
win_x = subset.coord_geo2radar(win_lon, atr, 'longitude')
except:
try:
win_x
except:
win_x = [0, width]
win_box = (win_x[0], win_y[0], win_x[1], win_y[1])
win_box = subset.check_box_within_data_coverage(win_box, atr)
try:
velocityFile
try:
vel, vel_atr = readfile.read(velocityFile)
except:
vel, vel_atr = readfile.read(timeSeriesFile, velocityFile)
ax.set_title(velocityFile)
print 'display: ' + velocityFile
except:
vel, vel_atr = readfile.read(timeSeriesFile, dateList1[-1])
ax.set_title('epoch: ' + dateList1[-1])
print 'display last epoch'
##### show displacement instead of phase
if vel_atr['FILE_TYPE'] in ['interferograms', '.unw'
] and dispDisplacement == 'yes':
print 'show displacement'
phase2range = -float(vel_atr['WAVELENGTH']) / (4 * np.pi)
vel *= phase2range
else:
dispDisplacement = 'no'
## Reference Point
if showRef == 'yes':
try:
ax.plot(int(atr['ref_x']), int(atr['ref_y']), 'ks', ms=6)
except:
pass
if dispOpposite == 'yes':
print 'show opposite value in figure/map 1'
vel *= -1
## Flip
try:
flip_lr
except:
try:
flip_ud
except:
flip_lr, flip_ud = view.auto_flip_direction(atr)
## Status bar
## Geo coordinate
try:
ullon = float(atr['X_FIRST'])
ullat = float(atr['Y_FIRST'])
lon_step = float(atr['X_STEP'])
lat_step = float(atr['Y_STEP'])
lon_unit = atr['Y_UNIT']
lat_unit = atr['X_UNIT']
geocoord = 'yes'
print 'Input file is Geocoded'
except:
geocoord = 'no'
def format_coord(x, y):
col = int(x + 0.5)
row = int(y + 0.5)
if col >= 0 and col <= width and row >= 0 and row <= length:
z = vel[row, col]
try:
lon = ullon + x * lon_step
lat = ullat + y * lat_step
return 'x=%.1f, y=%.1f, value=%.4f, lon=%.4f, lat=%.4f' % (
x, y, z, lon, lat)
except:
return 'x=%.1f, y=%.1f, value=%.4f' % (x, y, z)
ax.format_coord = format_coord
## DEM
try:
demFile
dem, demRsc = readfile.read(demFile)
ax = view.plot_dem_yx(ax, dem, demShade, demContour, contour_step,
contour_sigma)
vel_alpha = 0.8
except:
print 'No DEM file'
try:
img = ax.imshow(vel, vmin=vmin, vmax=vmax, alpha=vel_alpha)
except:
img = ax.imshow(vel, alpha=vel_alpha)
plt.colorbar(img)
## Zoom In (subset)
if flip_lr == 'yes': ax.set_xlim(win_box[2], win_box[0])
else: ax.set_xlim(win_box[0], win_box[2])
if flip_ud == 'yes': ax.set_ylim(win_box[1], win_box[3])
else: ax.set_ylim(win_box[3], win_box[1])
## Flip
#if flip_lr == 'yes': fig.gca().invert_xaxis()
#if flip_ud == 'yes': fig.gca().invert_yaxis()
##########################################
##### Plot Fig 2 - Time series plot
#fig2 = plt.figure(num=2,figsize=(12,6))
fig2 = plt.figure(2, figsize=(12, 6))
ax2 = fig2.add_subplot(111)
try:
timeSeriesFile_2
h5timeseries_2 = h5py.File(timeSeriesFile_2)
dateList_2 = sorted(h5timeseries_2['timeseries'].keys())
dates_2, datevector_2 = ptime.date_list2vector(dateList_2)
datevector_all += list(set(datevector_2) - set(datevector_all))
datevector_all = sorted(datevector_all)
except:
pass
################################ Plot Code Package <start> #################################
def plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries):
ax2.cla()
print '\n-------------------------------------------------------------------------------'
disp_min = 0
disp_max = 0
############################# Plot Time Series ##############################
global ref_xsub, ref_ysub
##### 1.1 Plot Reference time series
try:
ref_xsub
ref_ysub
ref_xsub, ref_ysub = check_yx(ref_xsub, ref_ysub, radius, ax,
rectColor)
print '----------------------------------------------------'
print 'Reference Point:'
print 'ref_x=' + str(ref_xsub[0]) + ':' + str(ref_xsub[1])
print 'ref_y=' + str(ref_ysub[0]) + ':' + str(ref_ysub[1])
print '-----------------------------'
print 'Time series with all dates:'
dis1, dis1_mean, dis1_std, dis1_vel = read_dis_xy(
ref_xsub, ref_ysub, dateList1, h5timeseries, unit)
(_, caps, _)=ax2.errorbar(dates1,dis1_mean,yerr=dis1_std,fmt='-ks',\
ms=markerSize2, lw=0, alpha=1,mfc=markerColor_ref,mew=edgeWidth,\
elinewidth=edgeWidth,ecolor='black',capsize=markerSize*0.5)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis1_mean,
dis1_std)
if not len(dateList) == len(dateList1):
print '-----------------------------'
print 'Time series with dates of interest:'
dis12, dis12_mean, dis12_std, dis12_vel = read_dis_xy(
ref_xsub, ref_ysub, dateList, h5timeseries, unit)
(_, caps, _)=ax2.errorbar(dates,dis12_mean,yerr=dis12_std,fmt='-ks',\
ms=markerSize2, lw=0, alpha=1,mfc=markerColor_ref2,mew=edgeWidth,\
elinewidth=edgeWidth,ecolor='black',capsize=markerSize*0.5)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis12_mean,
dis12_std)
except:
pass
##### 1.2.0 Read y/x
print '\n----------------------------------------------------'
print 'Point of Interest:'
xsub, ysub = check_yx(xsub, ysub, radius, ax, rectColor)
print 'x=' + str(xsub[0]) + ':' + str(xsub[1])
print 'y=' + str(ysub[0]) + ':' + str(ysub[1])
##### 1.2.1 Plot 2nd time series
try:
timeSeriesFile_2
print '-----------------------------'
print '2nd Time Series:'
dis2, dis2_mean, dis2_std, dis2_vel = read_dis_xy(
xsub, ysub, dateList_2, h5timeseries_2, unit)
(_, caps, _)=ax2.errorbar(dates_2,dis2_mean,yerr=dis2_std,fmt='-ko',\
ms=markerSize2, lw=0, alpha=1, mfc=markerColor2,\
elinewidth=0,ecolor='black',capsize=0)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis2_mean,
dis2_std)
except:
pass
##### 1.2.2 Plot 1st time series
print '-----------------------------'
print 'Time Series:'
dis, dis_mean, dis_std, dis_vel = read_dis_xy(xsub, ysub, dateList,
h5timeseries, unit)
(_, caps, _)=ax2.errorbar(dates,dis_mean,yerr=dis_std,fmt='-ko',\
ms=markerSize, lw=lineWidth, alpha=1, mfc=markerColor,\
elinewidth=edgeWidth,ecolor='black',capsize=markerSize*0.5)
for cap in caps:
cap.set_markeredgewidth(edgeWidth)
disp_min, disp_max = update_lim(disp_min, disp_max, dis_mean, dis_std)
####################### Figure Format #######################
## x axis format
try:
ax2 = ptime.auto_adjust_xaxis_date(ax2, dateVecMinMax, fontSize)
except:
ax2 = ptime.auto_adjust_xaxis_date(ax2, datevector_all, fontSize)
## y axis format
ax2.set_ylabel('Displacement [' + unit + ']', fontsize=fontSize)
try:
lbound
hbound
ax2.set_ylim(lbound, hbound)
except:
disp_buf = 0.2 * (disp_max - disp_min)
ax2.set_ylim(disp_min - disp_buf, disp_max + disp_buf)
for tick in ax2.yaxis.get_major_ticks():
tick.label.set_fontsize(fontSize)
## title
figTitle = 'x=' + str(xsub[0]) + ':' + str(xsub[1]) + ', y=' + str(
ysub[0]) + ':' + str(ysub[1])
try:
lonc = ullon + (xsub[0] + xsub[1]) / 2.0 * lon_step
latc = ullat + (ysub[0] + ysub[1]) / 2.0 * lat_step
figTitle += ', lalo=' + '%.4f,%.4f' % (latc, lonc)
except:
pass
ax2.set_title(figTitle)
################## Save and Output #####################
if saveFig == 'yes':
print '-----------------------------'
Delay = {}
Delay['displacement'] = dis
Delay['unit'] = unit
Delay['time'] = datevector
Delay['velocity'] = dis_vel[0]
Delay['velocity_unit'] = unit + '/yr'
Delay['velocity_std'] = dis_vel[4]
figBase = 'x' + str(xsub[0]) + '_' + str(xsub[1] - 1) + 'y' + str(
ysub[0]) + '_' + str(ysub[1] - 1)
sio.savemat(figBase + '_ts.mat', {'displacement': Delay})
print 'saved ' + figBase + '_ts.mat'
fig2.savefig(figBase + '_ts.pdf',
bbox_inches='tight',
transparent=True,
dpi=fig_dpi)
print 'saved ' + figBase + '_ts.pdf'
if dispFig == 'no':
fig.savefig(figBase + '_vel.png',
bbox_inches='tight',
transparent=True,
dpi=fig_dpi)
print 'saved ' + figBase + '_vel.png'
################################ Plot Code Package <end> #################################
########### 1. Plot Time Series with x/y ##########
try:
xsub
ysub
plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries)
except:
print 'No x/y input'
pass
########### 2. Plot Time Series with Click ##########
## similar to 1. Plot Time Series with x/y
def onclick(event):
ax2.cla()
xsub = [int(event.xdata)]
ysub = [int(event.ydata)]
plot_ts(ax, ax2, fig2, xsub, ysub, h5timeseries)
if dispFig == 'yes': plt.show()
try:
cid = fig.canvas.mpl_connect('button_press_event', onclick)
except:
pass
if dispFig == 'yes': plt.show()
