def main(inps=None):
inps = cmdLineParse()
print("***Time-series Preparation Function:***")
# if user bbox was specified, file(s) not meeting imposed spatial criteria are rejected.
# Outputs = arrays ['standardproduct_info.products'] containing grouped “radarmetadata info” and “data layer keys+paths” dictionaries for each standard product
# In addition, path to bbox file ['standardproduct_info.bbox_file'] (if bbox specified)
standardproduct_info = ARIA_standardproduct(inps.imgfile, bbox=inps.bbox, workdir=inps.workdir, verbose=inps.verbose)
# pass number of threads for gdal multiprocessing computation
if inps.num_threads.lower()=='all':
import multiprocessing
print('User specified use of all %s threads for gdal multiprocessing'%(str(multiprocessing.cpu_count())))
inps.num_threads='ALL_CPUS'
print('Thread count specified for gdal multiprocessing = %s'%(inps.num_threads))
# extract/merge productBoundingBox layers for each pair and update dict,
# report common track bbox (default is to take common intersection, but user may specify union), and expected shape for DEM.
standardproduct_info.products[0], standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, prods_TOTbbox_metadatalyr, arrshape, proj = merged_productbbox(standardproduct_info.products[0], standardproduct_info.products[1], os.path.join(inps.workdir,'productBoundingBox'), standardproduct_info.bbox_file, inps.croptounion, num_threads=inps.num_threads, minimumOverlap=inps.minimumOverlap, verbose=inps.verbose)
# Download/Load DEM & Lat/Lon arrays, providing bbox, expected DEM shape, and output dir as input.
if inps.demfile is not None:
print('Download/cropping DEM')
# Pass DEM-filename, loaded DEM array, and lat/lon arrays
inps.demfile, demfile, Latitude, Longitude = prep_dem(inps.demfile, standardproduct_info.bbox_file, prods_TOTbbox, \
prods_TOTbbox_metadatalyr, proj, arrshape=arrshape, workdir=inps.workdir, outputFormat=inps.outputFormat, num_threads=inps.num_threads)
# Load or download mask (if specified).
if inps.mask is not None:
inps.mask = prep_mask([[item for sublist in [list(set(d['amplitude'])) for d in standardproduct_info.products[1] if 'amplitude' in d] for item in sublist], [item for sublist in [list(set(d['pair_name'])) for d in standardproduct_info.products[1] if 'pair_name' in d] for item in sublist]],inps.mask, standardproduct_info.bbox_file, prods_TOTbbox, proj, amp_thresh=inps.amp_thresh, arrshape=arrshape, workdir=inps.workdir, outputFormat=inps.outputFormat, num_threads=inps.num_threads)
# Extract
layers=['unwrappedPhase','coherence']
print('\nExtracting unwrapped phase, coherence, and connected components for each interferogram pair')
export_products(standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose, num_threads=inps.num_threads, multilooking=inps.multilooking)
layers=['incidenceAngle','lookAngle','azimuthAngle']
print('\nExtracting single incidence angle, look angle and azimuth angle files valid over common interferometric grid')
export_products([dict(zip([k for k in set(k for d in standardproduct_info.products[1] for k in d)], [[item for sublist in [list(set(d[k])) for d in standardproduct_info.products[1] if k in d] for item in sublist] for k in set(k for d in standardproduct_info.products[1] for k in d)]))], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose, num_threads=inps.num_threads, multilooking=inps.multilooking)
if inps.bperp==True:
layers=['bPerpendicular']
print('\nExtracting perpendicular baseline grids for each interferogram pair')
export_products(standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose, num_threads=inps.num_threads, multilooking=inps.multilooking)
# Extracting other layers, if specified
if inps.layers:
if inps.layers.lower()=='all':
inps.layers=list(standardproduct_info.products[1][0].keys())
# Must also remove productBoundingBoxes & pair-names because they are not raster layers
layers=[i for i in inps.layers if i not in ['unwrappedPhase','coherence','incidenceAngle','lookAngle','azimuthAngle','bPerpendicular','productBoundingBox','productBoundingBoxFrames','pair_name']]
else:
inps.layers=list(inps.layers.split(','))
layers=[i for i in inps.layers if i not in ['unwrappedPhase','coherence','incidenceAngle','lookAngle','azimuthAngle','bPerpendicular']]
layers=[i.replace(' ','') for i in layers]
if layers!=[]:
print('\nExtracting optional, user-specified layers %s for each interferogram pair'%(layers))
export_products(standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose, num_threads=inps.num_threads, multilooking=inps.multilooking)
# If necessary, resample DEM/mask AFTER they have been used to extract metadata layers and mask output layers, respectively
if inps.multilooking is not None:
# Import functions
from ARIAtools.shapefile_util import open_shapefile
from ARIAtools.vrtmanager import resampleRaster
bounds=open_shapefile(standardproduct_info.bbox_file, 0, 0).bounds
# Resample mask
if inps.mask is not None:
resampleRaster(inps.mask.GetDescription(), inps.multilooking, bounds, prods_TOTbbox, inps.rankedResampling, outputFormat=inps.outputFormat, num_threads=inps.num_threads)
# Resample DEM
if demfile is not None:
resampleRaster(demfile.GetDescription(), inps.multilooking, bounds, prods_TOTbbox, inps.rankedResampling, outputFormat=inps.outputFormat, num_threads=inps.num_threads)
# Perform GACOS-based tropospheric corrections (if specified).
if inps.tropo_products:
tropo_correction(standardproduct_info.products, inps.tropo_products, standardproduct_info.bbox_file, prods_TOTbbox, outDir=inps.workdir, outputFormat=inps.outputFormat, verbose=inps.verbose, num_threads=inps.num_threads)
# Generate Stack
generateStack(standardproduct_info,'coherence','cohStack',workdir=inps.workdir)
generateStack(standardproduct_info,'connectedComponents','connCompStack',workdir=inps.workdir)
if inps.tropo_products:
generateStack(standardproduct_info,'tropocorrected_products','unwrapStack',workdir=inps.workdir)
else:
generateStack(standardproduct_info,'unwrappedPhase','unwrapStack',workdir=inps.workdir)
def main(inps=None):
'''
Main driver.
'''
inps = cmdLineParse()
print("***Time-series Preparation Function:***")
# if user bbox was specified, file(s) not meeting imposed spatial criteria are rejected.
# Outputs = arrays ['standardproduct_info.products'] containing grouped “radarmetadata info” and “data layer keys+paths” dictionaries for each standard product
# In addition, path to bbox file ['standardproduct_info.bbox_file'] (if bbox specified)
standardproduct_info = ARIA_standardproduct(inps.imgfile, bbox=inps.bbox, workdir=inps.workdir, verbose=inps.verbose)
# extract/merge productBoundingBox layers for each pair and update dict,
# report common track bbox (default is to take common intersection, but user may specify union), and expected shape for DEM.
standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, arrshape, proj = merged_productbbox(standardproduct_info.products[1], os.path.join(inps.workdir,'productBoundingBox'), standardproduct_info.bbox_file, inps.croptounion)
# Load or download mask (if specified).
if inps.mask is not None:
inps.mask = prep_mask(inps.mask, standardproduct_info.bbox_file, prods_TOTbbox, proj, amp_thresh=inps.amp_thresh, arrshape=arrshape, workdir=inps.workdir, outputFormat=inps.outputFormat)
# Download/Load DEM & Lat/Lon arrays, providing bbox, expected DEM shape, and output dir as input.
if inps.demfile is not None:
print('Download/cropping DEM')
# Pass DEM-filename, loaded DEM array, and lat/lon arrays
inps.demfile, demfile, Latitude, Longitude = prep_dem(inps.demfile, standardproduct_info.bbox_file, prods_TOTbbox, proj, arrshape=arrshape, workdir=inps.workdir, outputFormat=inps.outputFormat)
# Extract
layers=['unwrappedPhase','coherence']
print('Extracting unwrapped phase, coherence, and connected components for each interferogram pair')
export_products(standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose)
layers=['incidenceAngle','lookAngle','azimuthAngle']
print('Extracting incidence angle, look angle and azimuth angle grids of the first interferogram pair')
export_products([standardproduct_info.products[1][0]], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose)
if inps.bperp==True:
layers=['bPerpendicular']
print('Extracting perpendicular baseline grids for each interferogram pair')
export_products(standardproduct_info.products[1], standardproduct_info.bbox_file, prods_TOTbbox, layers, dem=demfile, lat=Latitude, lon=Longitude, mask=inps.mask, outDir=inps.workdir, outputFormat=inps.outputFormat, stitchMethodType='overlap', verbose=inps.verbose)
# Generate Stack
generateStack(standardproduct_info,'unwrappedPhase','unwrapStack',workdir=inps.workdir)
generateStack(standardproduct_info,'coherence','cohStack',workdir=inps.workdir)
generateStack(standardproduct_info,'connectedComponents','connCompStack',workdir=inps.workdir)
def main(inps=None):
from ARIAtools.ARIAProduct import ARIA_standardproduct
logger.setLevel(logging.INFO)
print('*****************************************************************')
print('*** Plotting Function ***')
print('*****************************************************************')
# if user bbox was specified, file(s) not meeting imposed spatial criteria are rejected.
# Outputs = arrays ['standardproduct_info.products'] containing grouped “radarmetadata info” and “data layer keys+paths” dictionaries for each standard product
# In addition, path to bbox file ['standardproduct_info.bbox_file'] (if bbox specified)
standardproduct_info = ARIA_standardproduct(inps.imgfile,
bbox=inps.bbox,
workdir=inps.workdir,
num_threads=inps.num_threads,
url_version=inps.version,
verbose=inps.verbose)
# If user requests to generate all plots.
if inps.plotall:
log.info('"-plotall"==True. All plots will be made.')
inps.plottracks = True
inps.plotbperp = True
inps.plotcoh = True
inps.plotbperpcoh = True
inps.makeavgoh = True
# pass number of threads for gdal multiprocessing computation
if inps.num_threads.lower() == 'all':
import multiprocessing
log.info(
'User specified use of all %s threads for gdal multiprocessing',
multiprocessing.cpu_count())
inps.num_threads = 'ALL_CPUS'
log.info('Thread count specified for gdal multiprocessing = %s',
inps.num_threads)
if inps.plottracks or inps.plotcoh or inps.makeavgoh or inps.plotbperpcoh:
from ARIAtools.extractProduct import merged_productbbox
# extract/merge productBoundingBox layers for each pair and update dict,
# report common track bbox (default is to take common intersection, but user may specify union), and expected shape for DEM.
standardproduct_info.products[0], standardproduct_info.products[1], \
standardproduct_info.bbox_file, prods_TOTbbox, \
prods_TOTbbox_metadatalyr, arrshape, proj = merged_productbbox(
standardproduct_info.products[0], standardproduct_info.products[1],
os.path.join(inps.workdir, 'productBoundingBox'),
standardproduct_info.bbox_file, inps.croptounion,
num_threads=inps.num_threads,
minimumOverlap=inps.minimumOverlap, verbose=inps.verbose)
# Load or download mask (if specified).
if inps.mask is not None:
inps.mask = prep_mask(
[[
item for sublist in [
list(set(d['amplitude']))
for d in standardproduct_info.products[1]
if 'amplitude' in d
] for item in sublist
],
[
item for sublist in [
list(set(d['pair_name']))
for d in standardproduct_info.products[1]
if 'pair_name' in d
] for item in sublist
]],
inps.mask,
standardproduct_info.bbox_file,
prods_TOTbbox,
proj,
amp_thresh=inps.amp_thresh,
arrshape=arrshape,
workdir=inps.workdir,
outputFormat=inps.outputFormat,
num_threads=inps.num_threads)
# Make spatial extent plot
if inps.plottracks:
log.info(
"- Make plot of track latitude extents vs bounding bbox/common track extent."
)
make_plot = PlotClass([[
j['productBoundingBox'] for j in standardproduct_info.products[1]
], [j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
croptounion=inps.croptounion)
make_plot.plot_extents(figwidth=inps.figwidth)
# Make pbaseline plot
if inps.plotbperp:
log.info("- Make baseline plot and histogram.")
make_plot = PlotClass(
[[j['bPerpendicular'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir)
make_plot.plot_pbaselines()
# Make average land coherence plot
if inps.plotcoh:
log.info(
"- Make average IFG coherence plot in time, and histogram of average IFG coherence."
)
make_plot = PlotClass(
[[j['coherence'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask,
num_threads=inps.num_threads)
make_plot.plot_coherence()
# Generate average land coherence raster
if inps.makeavgoh:
log.info("- Generate 2D raster of average coherence.")
make_plot = PlotClass(
[[j['coherence'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask,
outputFormat=inps.outputFormat,
num_threads=inps.num_threads)
make_plot.plot_avgcoherence()
# Make pbaseline/coherence combo plot
if inps.plotbperpcoh:
log.info(
"- Make baseline plot that is color-coded with respect to mean IFG coherence."
)
make_plot = PlotClass(
[[j['bPerpendicular'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]],
[j['coherence'] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask)
make_plot.plotbperpcoh()
def main(inps=None):
from ARIAtools.ARIAProduct import ARIA_standardproduct
from ARIAtools.shapefile_util import open_shapefile
print("***Plotting Function:***")
# if user bbox was specified, file(s) not meeting imposed spatial criteria are rejected.
# Outputs = arrays ['standardproduct_info.products'] containing grouped “radarmetadata info” and “data layer keys+paths” dictionaries for each standard product
# In addition, path to bbox file ['standardproduct_info.bbox_file'] (if bbox specified)
standardproduct_info = ARIA_standardproduct(inps.imgfile,
bbox=inps.bbox,
workdir=inps.workdir,
verbose=inps.verbose)
# If user requests to generate all plots.
if inps.plotall:
print('"-plotall"==True. All plots will be made.')
inps.plottracks = True
inps.plotbperp = True
inps.plotcoh = True
inps.plotbperpcoh = True
inps.makeavgoh = True
if inps.plottracks or inps.plotcoh or inps.makeavgoh or inps.plotbperpcoh:
# Import functions
from ARIAtools.extractProduct import merged_productbbox
# extract/merge productBoundingBox layers for each pair and update dict,
# report common track bbox (default is to take common intersection, but user may specify union), and expected shape for DEM.
standardproduct_info.products[
1], standardproduct_info.bbox_file, prods_TOTbbox, arrshape, proj = merged_productbbox(
standardproduct_info.products[1],
os.path.join(inps.workdir, 'productBoundingBox'),
standardproduct_info.bbox_file, inps.croptounion)
# Load or download mask (if specified).
if inps.mask is not None:
inps.mask = prep_mask(inps.mask,
standardproduct_info.bbox_file,
prods_TOTbbox,
proj,
amp_thresh=inps.amp_thresh,
arrshape=arrshape,
workdir=inps.workdir,
outputFormat=inps.outputFormat)
# Make spatial extent plot
if inps.plottracks:
print(
"- Make plot of track latitude extents vs bounding bbox/common track extent."
)
make_plot = plot_class([[
j['productBoundingBox'] for j in standardproduct_info.products[1]
], [j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
croptounion=inps.croptounion)
make_plot.plot_extents()
# Make pbaseline plot
if inps.plotbperp:
print("- Make baseline plot and histogram.")
make_plot = plot_class(
[[j['bPerpendicular'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir)
make_plot.plot_pbaselines()
# Make average land coherence plot
if inps.plotcoh:
print(
"- Make average IFG coherence plot in time, and histogram of average IFG coherence."
)
make_plot = plot_class(
[[j['coherence'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask)
make_plot.plot_coherence()
# Generate average land coherence raster
if inps.makeavgoh:
print("- Generate 2D raster of average coherence.")
make_plot = plot_class(
[[j['coherence'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask,
outputFormat=inps.outputFormat)
make_plot.plot_avgcoherence()
# Make pbaseline/coherence combo plot
if inps.plotbperpcoh:
print(
"- Make baseline plot that is color-coded with respect to mean IFG coherence."
)
make_plot = plot_class(
[[j['bPerpendicular'] for j in standardproduct_info.products[1]],
[j["pair_name"] for j in standardproduct_info.products[1]],
[j['coherence'] for j in standardproduct_info.products[1]]],
workdir=inps.workdir,
bbox_file=standardproduct_info.bbox_file,
prods_TOTbbox=prods_TOTbbox,
mask=inps.mask)
make_plot.plotbperpcoh()