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):
##### Default
fontSize = 12
lineWidth = 2
markerColor = 'crimson'
markerSize = 16
disp_fig = 'no'
save_fig = 'yes'
save_list = 'yes'
ref_file = 'reference_date.txt'
drop_file = 'drop_date.txt'
##### Check Inputs
if len(sys.argv)>3:
try:
opts, args = getopt.getopt(argv,'h:f:m:o:x:y:',['help','circle='])
except getopt.GetoptError:
print 'Error in reading input options!'; usage() ; sys.exit(1)
for opt,arg in opts:
if opt in ("-h","--help"): usage() ; sys.exit()
elif opt == '-f': File = arg
elif opt == '-m': maskFile = arg
elif opt == '-x': xsub = [int(i) for i in arg.split(':')]; xsub.sort()
elif opt == '-y': ysub = [int(i) for i in arg.split(':')]; ysub.sort()
elif opt == '--circle' : cir_par = [i for i in arg.split(';')]
#elif opt == '-o': outName = arg
else:
try: File = argv[0]
except: usage(); sys.exit(1)
try: maskFile = argv[1]
except: pass
try: atr = readfile.read_attribute(File)
except: usage(); sys.exit(1)
ext = os.path.splitext(File)[1].lower()
FileBase = os.path.basename(File).split(ext)[0]
outNameBase = 'spatialMean_'+FileBase
print '\n*************** Spatial Average ******************'
##### Input File Info
k = atr['FILE_TYPE']
print 'Input file is '+k
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
h5file = h5py.File(File)
epochList = h5file[k].keys()
epochList = sorted(epochList)
epochNum = len(epochList)
print 'number of epoch: '+str(epochNum)
if
dates,datevector = ptime.date_list2vector(epochList)
##### Mask Info
try:
Mask_orig,Matr = readfile.read(maskFile)
print 'mask file: '+maskFile
Masking = 'yes'
except:
print 'No mask. Use the whole area for ramp estimation.'
Masking = 'no'
Mask_orig=np.ones((length,width))
Mask = np.zeros((length,width))
Mask[:] = Mask_orig[:]
## Bounding Subset
try:
xsub
ysub
ysub,xsub = subset.check_subset_range(ysub,xsub,atr)
Mask[ysub[0]:ysub[1],xsub[0]:xsub[1]] = Mask_orig[ysub[0]:ysub[1],xsub[0]:xsub[1]]*2
#Mask[0:ysub[0],:] = 0
#Mask[ysub[1]:length,:] = 0
#Mask[:,0:xsub[0]] = 0
#Mask[:,xsub[1]:width] = 0
except:
Mask = Mask_orig*2
print 'No subset input.'
## Circle Inputs
try:
cir_par
for i in range(len(cir_par)):
cir_idx = circle_index(atr,cir_par[i])
Mask[cir_idx] = Mask_orig[cir_idx]
print 'Circle '+str(i)+': '+cir_par[i]
except: print 'No circle of interest input.'
## Mask output
idx = Mask == 2
idxNum = float(sum(sum(idx)))
fig = plt.figure()
plt.imshow(Mask,cmap='gray')
plt.savefig(outNameBase+'_mask.png',bbox_inches='tight')
print 'save mask to '+outNameBase+'_mask.png'
#fig.clf()
##### Calculation
meanList = np.zeros(epochNum)
pixPercent = np.zeros(epochNum)
pixT = 0.7
print 'calculating ...'
print ' Date Mean Percentage'
for i in range(epochNum):
epoch = epochList[i]
d = h5file[k].get(epoch)[:]
#d[Mask==0] = np.nan
meanList[i] = np.nanmean(d[idx])
pixPercent[i] = np.sum(d[idx] >= pixT)/idxNum
print epoch+' : %.2f %.1f%%'%(meanList[i],pixPercent[i]*100)
del d
h5file.close()
##### Reference date - Max Value
top3 = sorted(zip(meanList,epochList), reverse=True)[:3]
print '------------ Top 3 Mean ------------------'
print top3
## Write to txt file
fref = open(ref_file,'w')
fref.write(str(top3[0][1])+'\n')
fref.close()
print 'write optimal reference date to '+ref_file
idxMean = meanList == np.nanmax(meanList)
##### Drop dates - mean threshold
#meanT = 0.7
#idxMean = meanList < meanT
#print '------------ Mean Value < '+str(meanT)+' --------'
#print np.array(epochList)[idxMean]
#print meanList[idxMean]
##### Drop dates - good pixel percentage
pixNumT = 0.7
print '------------ Good Pixel Percentage < %.0f%% -------'%(pixNumT*100)
idxPix = pixPercent < pixNumT
dropEpochList = np.array(epochList)[idxPix]
print dropEpochList
print pixPercent[idxPix]
## Write to txt file
fdrop = open(drop_file,'w')
for i in range(len(dropEpochList)):
fdrop.write(str(dropEpochList[i])+'\n')
fdrop.close()
print 'write drop dates to '+drop_file
print '-------------------------------------------'
##### Display
fig = plt.figure(figsize=(12,12))
ax = fig.add_subplot(211)
ax.plot(dates, meanList, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor)
#ax.plot([dates[0],dates[-1]],[meanT,meanT], '--b', lw=lineWidth)
#sc = ax.scatter(dates, np.tile(0.5,epochNum), c=meanList, s=22**2, alpha=0.3, vmin=0.0, vmax=1.0)
#ax.scatter(np.array(dates)[idxMean], 0.5, c=meanList[idxMean], s=22**2, alpha=1.0, vmin=0.0, vmax=1.0)
ax = ptime.auto_adjust_xaxis_date(ax,datevector)
ax.set_ylim(0,1)
ax.set_title('Spatial Average Value', fontsize=fontSize)
ax.set_xlabel('Time [years]', fontsize=fontSize)
#cbar = plt.colorbar(sc)
#cbar.set_label('Spatial Mean of Normalized Sum Epochs')
ax = fig.add_subplot(212)
ax.plot(dates, pixPercent, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor)
ax.plot([dates[0],dates[-1]],[pixNumT,pixNumT], '--b', lw=lineWidth)
ax = ptime.auto_adjust_xaxis_date(ax,datevector)
ax.set_ylim(0,1)
ax.set_title('Percenrage of Pixels with Value > '+str(pixNumT), fontsize=fontSize)
ax.set_xlabel('Time [years]', fontsize=fontSize)
vals = ax.get_yticks()
ax.set_yticklabels(['{:3.0f}%'.format(i*100) for i in vals])
if save_fig == 'yes':
plt.savefig(outNameBase+'.png',bbox_inches='tight')
print 'save figure to '+outNameBase+'.png'
if disp_fig == 'yes':
plt.show()
##### Output
if save_list == 'yes':
epochList6 = ptime.yymmdd(epochList)
fl = open(outNameBase+'.txt','w')
for i in range(epochNum):
str_line = epochList6[i]+' %.2f %.2f\n'%(meanList[i],pixPercent[i])
fl.write(str_line)
fl.close()
print 'write data to '+outNameBase+'.txt\n'
def main(argv):
##### Default
fontSize = 12
lineWidth = 2
markerColor = 'crimson'
markerSize = 16
disp_fig = 'no'
save_fig = 'yes'
save_list = 'yes'
ref_file = 'reference_date.txt'
drop_file = 'drop_date.txt'
##### Check Inputs
if len(sys.argv)>3:
try:
opts, args = getopt.getopt(argv,'h:f:m:o:x:y:',['help','circle='])
except getopt.GetoptError:
print 'Error in reading input options!'; Usage() ; sys.exit(1)
for opt,arg in opts:
if opt in ("-h","--help"): Usage() ; sys.exit()
elif opt == '-f': File = arg
elif opt == '-m': maskFile = arg
elif opt == '-x': xsub = [int(i) for i in arg.split(':')]; xsub.sort()
elif opt == '-y': ysub = [int(i) for i in arg.split(':')]; ysub.sort()
elif opt == '--circle' : cir_par = [i for i in arg.split(';')]
#elif opt == '-o': outName = arg
else:
try: File = argv[0]
except: Usage(); sys.exit(1)
try: maskFile = argv[1]
except: pass
try: atr = readfile.read_attributes(File)
except: Usage(); sys.exit(1)
ext = os.path.splitext(File)[1].lower()
FileBase = os.path.basename(File).split(ext)[0]
outNameBase = 'spatialMean_'+FileBase
print '\n*************** Spatial Average ******************'
##### Input File Info
k = atr['FILE_TYPE']
print 'Input file is '+k
width = int(atr['WIDTH'])
length = int(atr['FILE_LENGTH'])
h5file = h5py.File(File)
epochList = h5file[k].keys();
epochList = sorted(epochList)
epochNum = len(epochList)
print 'number of epoch: '+str(epochNum)
dates,datevector = ptime.date_list2vector(epochList)
##### Mask Info
try:
Mask_orig,Matr = readfile.read(maskFile)
print 'mask file: '+maskFile
Masking = 'yes'
except:
print 'No mask. Use the whole area for ramp estimation.'
Masking = 'no'
Mask_orig=np.ones((length,width))
Mask = np.zeros((length,width))
Mask[:] = Mask_orig[:]
## Bounding Subset
try:
xsub
ysub
ysub,xsub = subset.check_subset_range(ysub,xsub,atr)
Mask[ysub[0]:ysub[1],xsub[0]:xsub[1]] = Mask_orig[ysub[0]:ysub[1],xsub[0]:xsub[1]]*2
#Mask[0:ysub[0],:] = 0
#Mask[ysub[1]:length,:] = 0
#Mask[:,0:xsub[0]] = 0
#Mask[:,xsub[1]:width] = 0
except:
Mask = Mask_orig*2
print 'No subset input.'
## Circle Inputs
try:
cir_par
for i in range(len(cir_par)):
cir_idx = circle_index(atr,cir_par[i])
Mask[cir_idx] = Mask_orig[cir_idx]
print 'Circle '+str(i)+': '+cir_par[i]
except: print 'No circle of interest input.'
## Mask output
idx = Mask == 2
idxNum = float(sum(sum(idx)))
fig = plt.figure()
plt.imshow(Mask,cmap='gray')
plt.savefig(outNameBase+'_mask.png',bbox_inches='tight')
print 'save mask to '+outNameBase+'_mask.png'
#fig.clf()
##### Calculation
meanList = np.zeros(epochNum)
pixPercent = np.zeros(epochNum)
pixT = 0.7
print 'calculating ...'
print ' Date Mean Percentage'
for i in range(epochNum):
epoch = epochList[i]
d = h5file[k].get(epoch)[:]
#d[Mask==0] = np.nan
meanList[i] = np.nanmean(d[idx])
pixPercent[i] = np.sum(d[idx] >= pixT)/idxNum
print epoch+' : %.2f %.1f%%'%(meanList[i],pixPercent[i]*100)
del d
h5file.close()
##### Reference date - Max Value
top3 = sorted(zip(meanList,epochList), reverse=True)[:3]
print '------------ Top 3 Mean ------------------'
print top3
## Write to txt file
fref = open(ref_file,'w')
fref.write(str(top3[0][1])+'\n')
fref.close()
print 'write optimal reference date to '+ref_file
idxMean = meanList == np.nanmax(meanList)
##### Drop dates - mean threshold
#meanT = 0.7
#idxMean = meanList < meanT
#print '------------ Mean Value < '+str(meanT)+' --------'
#print np.array(epochList)[idxMean]
#print meanList[idxMean]
##### Drop dates - good pixel percentage
pixNumT = 0.7
print '------------ Good Pixel Percentage < %.0f%% -------'%(pixNumT*100)
idxPix = pixPercent < pixNumT
dropEpochList = np.array(epochList)[idxPix]
print dropEpochList
print pixPercent[idxPix]
## Write to txt file
fdrop = open(drop_file,'w')
for i in range(len(dropEpochList)):
fdrop.write(str(dropEpochList[i])+'\n')
fdrop.close()
print 'write drop dates to '+drop_file
print '-------------------------------------------'
##### Display
fig = plt.figure(figsize=(12,12))
ax = fig.add_subplot(211)
ax.plot(dates, meanList, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor)
#ax.plot([dates[0],dates[-1]],[meanT,meanT], '--b', lw=lineWidth)
#sc = ax.scatter(dates, np.tile(0.5,epochNum), c=meanList, s=22**2, alpha=0.3, vmin=0.0, vmax=1.0)
#ax.scatter(np.array(dates)[idxMean], 0.5, c=meanList[idxMean], s=22**2, alpha=1.0, vmin=0.0, vmax=1.0)
ax = ptime.adjust_xaxis_date(ax,datevector)
ax.set_ylim(0,1)
ax.set_title('Spatial Average Value', fontsize=fontSize)
ax.set_xlabel('Time [years]', fontsize=fontSize)
#cbar = plt.colorbar(sc)
#cbar.set_label('Spatial Mean of Normalized Sum Epochs')
ax = fig.add_subplot(212)
ax.plot(dates, pixPercent, '-ko', ms=markerSize, lw=lineWidth, alpha=0.7, mfc=markerColor)
ax.plot([dates[0],dates[-1]],[pixNumT,pixNumT], '--b', lw=lineWidth)
ax = ptime.adjust_xaxis_date(ax,datevector)
ax.set_ylim(0,1)
ax.set_title('Percenrage of Pixels with Value > '+str(pixNumT), fontsize=fontSize)
ax.set_xlabel('Time [years]', fontsize=fontSize)
vals = ax.get_yticks()
ax.set_yticklabels(['{:3.0f}%'.format(i*100) for i in vals])
if save_fig == 'yes':
plt.savefig(outNameBase+'.png',bbox_inches='tight')
print 'save figure to '+outNameBase+'.png'
if disp_fig == 'yes':
plt.show()
##### Output
if save_list == 'yes':
epochList6 = ptime.yymmdd(epochList)
fl = open(outNameBase+'.txt','w')
for i in range(epochNum):
str_line = epochList6[i]+' %.2f %.2f\n'%(meanList[i],pixPercent[i])
fl.write(str_line)
fl.close()
print 'write data to '+outNameBase+'.txt\n'
