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insarlab / MintPy

Miami InSAR time-series software in Python
https://mintpy.readthedocs.io
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Geocode error and generate_mask.py error #546

Closed alejobeap closed 3 years ago

alejobeap commented 3 years ago

Dear

I run Mintpy with the Stack in ISCE with TerrasarX data: stackStripMap.py -s /mnt/nas_insar/TX_Pr_Cotopaxi/SLC/ -d /mnt/nas_insar/TX_Pr_Cotopaxi/DEM/demLat_S02_N02_Lon_W079_W077.dem.wgs84 --bbox '-0.61 -0.76 -78.47 -78.38' -w ./ -W interferogram -m 20201106 --nofocus --zero -t 250 -b 1000 -a 14 -r 4 -S TX

I had this error in the geocode part:

step - geocode 

geocode.py /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5 temporalCoherence.h5 avgSpatialCoh.h5 /mnt/nas_insar/TX_Pr_Cotopaxi/timeseries_ramp_demErr.h5 velocity.h5 -l /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5 -t /mnt/nas_insar/TX_Pr_Cotopaxi/smallbaselineApp.cfg --outdir /mnt/nas_insar/TX_Pr_Cotopaxi/geo --update
read input option from template file: /mnt/nas_insar/TX_Pr_Cotopaxi/smallbaselineApp.cfg
number of processor to be used: 1
resampling software: pyresample
read latitude / longitude from lookup table file: /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5
output pixel size in (lat, lon) in degree: (-2.3965129953599953e-05, 1.9254513439806536e-05)
output area extent in (S, N, W, E) in degree: (-0.7590546628284961, -0.596595046873042, -78.54505357256922, -78.33242598065343)
output file row / column number: (6779, 11043)
searching relevant box covering the current SNWE

resampling file: /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5
update mode: ON
['/mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_geometryRadar.h5'] exists and is newer than ['/mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5'] --> skip.

resampling file: temporalCoherence.h5
update mode: ON
['/mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_temporalCoherence.h5'] exists and is newer than ['temporalCoherence.h5', '/mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5'] --> skip.

resampling file: avgSpatialCoh.h5
update mode: ON
['/mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_avgSpatialCoh.h5'] exists and is newer than ['avgSpatialCoh.h5', '/mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5'] --> skip.

resampling file: /mnt/nas_insar/TX_Pr_Cotopaxi/timeseries_ramp_demErr.h5
update mode: ON
['/mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_timeseries_ramp_demErr.h5'] exists and is newer than ['/mnt/nas_insar/TX_Pr_Cotopaxi/timeseries_ramp_demErr.h5', '/mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5'] --> skip.

resampling file: velocity.h5
update mode: ON
update REF_LAT/LON/Y/X

grab dataset structure from ref_file: velocity.h5
create HDF5 file: /mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_velocity.h5 with w mode
create dataset  : velocity    of float32                   in size of (6779, 11043)        with compression = None
create dataset  : velocityStd of float32                   in size of (6779, 11043)        with compression = None
close  HDF5 file: /mnt/nas_insar/TX_Pr_Cotopaxi/geo/geo_velocity.h5

reading velocity    in block (0, 0, 11042, 6778) from velocity.h5 ...
nearest resampling with pyresample.kd_tree using 1 CPU cores in 76 segments ...
Traceback (most recent call last):
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1255, in <module>
    main(sys.argv[1:])
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1237, in main
    app.run(steps=inps.runSteps)
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1071, in run
    self.run_geocode(sname)
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 925, in run_geocode
    mintpy.geocode.main(iargs)
  File "/home/isce/tools/MintPy/mintpy/geocode.py", line 345, in main
    run_geocode(inps)
  File "/home/isce/tools/MintPy/mintpy/geocode.py", line 306, in run_geocode
    data = res_obj.run_resample(src_data=data, box_ind=i)
  File "/home/isce/tools/MintPy/mintpy/objects/resample.py", line 203, in run_resample
    print_msg=self.print_msg)
  File "/home/isce/tools/MintPy/mintpy/objects/resample.py", line 626, in run_pyresample
    epsilon=0.5)
  File "/opt/programas/miniconda3/envs/isce2/lib/python3.7/site-packages/pyresample/kd_tree.py", line 104, in resample_nearest
    reduce_data=reduce_data, nprocs=nprocs, segments=segments)
  File "/opt/programas/miniconda3/envs/isce2/lib/python3.7/site-packages/pyresample/kd_tree.py", line 275, in _resample
    with_uncert=with_uncert)
  File "/opt/programas/miniconda3/envs/isce2/lib/python3.7/site-packages/pyresample/kd_tree.py", line 637, in get_sample_from_neighbour_info
    raise ValueError('Mismatch between geometry and dataset')
ValueError: Mismatch between geometry and dataset

image

Thanks for your help

Also I used this smallbaseline.cfg input file:

# vim: set filetype=cfg:
##------------------------ smallbaselineApp.cfg ------------------------##
########## 1. load_data
mintpy.load.processor      = isce  #[isce, aria, snap, gamma, roipac], auto for isce
mintpy.load.updateMode     = auto  #[yes / no], auto for yes, skip re-loading if HDF5 files are complete
mintpy.load.compression    = auto  #[gzip / lzf / no], auto for no.
##---------for ISCE only:
mintpy.load.metaFile       = ./merged/SLC/*/referenceShelve/data.dat  #[path of common metadata file for the stack], i.e.: ./master/IW1.xml, ./masterShelve/data.dat
mintpy.load.baselineDir    = ./baselines  #[path of the baseline dir], i.e.: ./baselines
##---------interferogram datasets:
mintpy.load.unwFile        = ./Igrams/*/filt_*.unw #[path pattern of unwrapped interferogram files]
mintpy.load.corFile        = ./Igrams/*/filt_*.cor  #[path pattern of spatial coherence       files]
mintpy.load.connCompFile   = ./Igrams/*/filt_*.unw.conncomp  #[path pattern of connected components    files], optional
mintpy.load.intFile        = auto  #[path pattern of wrapped interferogram   files], optional
mintpy.load.ionoFile       = auto  #[path pattern of ionospheric delay       files], optional
##---------offset datasets (optional):
mintpy.load.azOffFile      = auto  #[path pattern of azimuth offset file], optional
mintpy.load.rgOffFile      = auto  #[path pattern of range   offset file], optional
mintpy.load.offSnrFile     = auto  #[path pattern of offset signal-to-noise ratio file], optional
##---------geometry datasets:
mintpy.load.demFile        = ./merged/geom_reference/hgt.rdr  #[path of DEM file]
mintpy.load.lookupYFile    = ./merged/geom_reference/lat.rdr  #[path of latitude /row   /y coordinate file], not required for geocoded data
mintpy.load.lookupXFile    = ./merged/geom_reference/lon.rdr  #[path of longitude/column/x coordinate file], not required for geocoded data
mintpy.load.incAngleFile   = ./merged/geom_reference/los.rdr  #[path of incidence angle file], optional
mintpy.load.azAngleFile    = ./merged/geom_reference/los.rdr  #[path of azimuth   angle file], optional
mintpy.load.shadowMaskFile = ./merged/geom_reference/shadowMask.rdr  #[path of shadow mask file], optional
mintpy.load.waterMaskFile  = auto  #[path of water  mask file], optional
mintpy.load.bperpFile      = auto  #[path pattern of 2D perpendicular baseline file], optional
##---------subset (optional):
if both yx and lalo are specified, use lalo option unless a) no lookup file AND b) dataset is in radar coord
mintpy.subset.yx   = auto    #[1800:2000,700:800 / no], auto for no
mintpy.subset.lalo = auto    #[31.5:32.5,130.5:131.0 / no], auto for no

########## 2. modify_network
reference: Yunjun et al. (2019, section 4.2 and 5.3.1)
1) Coherence-based network modification = (threshold + MST) by default
It calculates a average coherence value for each interferogram using spatial coherence and input mask (with AOI)
Then it finds a minimum spanning tree (MST) network with inverse of average coherence as weight (keepMinSpanTree)
For all interferograms except for MST's, exclude those with average coherence < minCoherence.
mintpy.network.coherenceBased  = auto  #[yes / no], auto for no, exclude interferograms with coherence < minCoherence
mintpy.network.keepMinSpanTree = auto  #[yes / no], auto for yes, keep interferograms in Min Span Tree network
mintpy.network.minCoherence    = auto  #[0.0-1.0], auto for 0.7
mintpy.network.maskFile        = auto  #[file name, no], auto for waterMask.h5 or no [if no waterMask.h5 found]
mintpy.network.aoiYX           = auto  #[y0:y1,x0:x1 / no], auto for no, area of interest for coherence calculation
mintpy.network.aoiLALO         = auto  #[lat0:lat1,lon0:lon1 / no], auto for no - use the whole area

2) Network modification based on temporal/perpendicular baselines, date etc.
mintpy.network.tempBaseMax     = auto  #[1-inf, no], auto for no, maximum temporal baseline in days
mintpy.network.perpBaseMax     = auto  #[1-inf, no], auto for no, maximum perpendicular spatial baseline in meter
mintpy.network.connNumMax      = auto  #[1-inf, no], auto for no, maximum number of neighbors for each acquisition
mintpy.network.startDate       = auto  #[20090101 / no], auto for no
mintpy.network.endDate         = auto  #[20110101 / no], auto for no
mintpy.network.excludeDate     = auto  #[20080520,20090817 / no], auto for no
mintpy.network.excludeIfgIndex = auto  #[1:5,25 / no], auto for no, list of ifg index (start from 0)
mintpy.network.referenceFile   = auto  #[date12_list.txt / ifgramStack.h5 / no], auto for no

######### 3. reference_point
Reference all interferograms to one common point in space
auto - randomly select a pixel with coherence > minCoherence
however, manually specify using prior knowledge of the study area is highly recommended
 with the following guideline (section 4.3 in Yunjun et al., 2019):
1) located in a coherence area
2) not affected by strong atmospheric turbulence, i.e. ionospheric streaks
3) close to and with similar elevation as the AOI to minimize the impact of spatially correlated atmospheric delay
mintpy.reference.yx            = auto   #[257,151 / auto]
mintpy.reference.lalo          = auto #[31.8,130.8 / auto]
mintpy.reference.maskFile      = auto   #[filename / no], auto for maskConnComp.h5
mintpy.reference.coherenceFile = auto   #[filename], auto for avgSpatialCoh.h5
mintpy.reference.minCoherence  = auto   #[0.0-1.0], auto for 0.85, minimum coherence for auto method

########## quick_overview
A quick assessment of:
1) possible groud deformation
 using the velocity from the traditional interferogram stacking
reference: Zebker et al. (1997, JGR)
2) distribution of phase unwrapping error
  from the number of interferogram triplets with non-zero integer ambiguity of closue phase
 reference: T_int in Yunjun et al. (2019, CAGEO). Related to section 3.2, equation (8-9) and Fig. 3d-e.

########## 4. correct_unwrap_error (optional)
connected components (mintpy.load.connCompFile) are required for this step.
reference: Yunjun et al. (2019, section 3)
supported methods:
 a. phase_closure           - suitable for highly redundant network
 b. bridging                - suitable for islands or areas with steep topography
 c. bridging+phase_closure  - recommended
mintpy.unwrapError.method          = auto  #[bridging / phase_closure / bridging+phase_closure / no], auto for no
mintpy.unwrapError.waterMaskFile   = auto  #[waterMask.h5 / no], auto for waterMask.h5 or no [if no waterMask.h5 found]

## briding options:
 ramp - a phase ramp could be estimated based on the largest reliable region, removed from the entire interferogram
      before estimating the phase difference between reliable regions and added back the correction.
 bridgePtsRadius - half size of the window used to calculate the median value of phase difference
mintpy.unwrapError.ramp            = auto  #[linear / quadratic], auto for no; recommend linear for L-band data
mintpy.unwrapError.bridgePtsRadius = auto  #[1-inf], auto for 50, half size of the window around end points

########## 5. invert_network
 Invert network of interferograms into time-series using weighted least sqaure (WLS) estimator.
weighting options for least square inversion [fast option available but not best]:
a. var - use inverse of covariance as weight (Tough et al., 1995; Guarnieri & Tebaldini, 2008) [recommended]
 b. fim - use Fisher Information Matrix as weight (Seymour & Cumming, 1994; Samiei-Esfahany et al., 2016).
 c. coh - use coherence as weight (Perissin & Wang, 2012)
 d. no  - uniform weight (Berardino et al., 2002) [fast]
 SBAS (Berardino et al., 2002) = minNormVelocity (yes) + weightFunc (no)
mintpy.networkInversion.weightFunc      = auto #[var / fim / coh / no], auto for var
mintpy.networkInversion.waterMaskFile   = auto #[filename / no], auto for waterMask.h5 or no [if no waterMask.h5 found]
mintpy.networkInversion.minNormVelocity = auto #[yes / no], auto for yes, min-norm deformation velocity or phase
mintpy.networkInversion.residualNorm    = auto #[L2 ], auto for L2, norm minimization solution

## mask options for unwrapPhase of each interferogram before inversion (recommed if weightFunct=no):
 a. coherence        - mask out pixels with spatial coherence < maskThreshold
 b. connectComponent - mask out pixels with False/0 value
 c. no               - no masking [recommended].
 d. offsetSNR        - mask out pixels with offset SNR < maskThreshold [for offset]
mintpy.networkInversion.maskDataset     = auto #[coherence / connectComponent / offsetSNR / no], auto for no
mintpy.networkInversion.maskThreshold   = auto #[0-inf], auto for 0.4
mintpy.networkInversion.minRedundancy   = auto #[1-inf], auto for 1.0, min num_ifgram for every SAR acquisition

## Parallel processing with Dask for HPC
mintpy.networkInversion.parallel    = auto #[yes / no], auto for no, parallel processing using dask
mintpy.networkInversion.cluster     = auto #[slurm / pbs / lsf], auto for SLURM, cluster type
mintpy.networkInversion.config      = auto #[slurm / pbs / lsf / no], auto for no (same as cluster), configuration name
mintpy.networkInversion.numWorker   = auto #[int > 0], auto for 40, number of works to deploy
mintpy.networkInversion.walltime    = auto #[HH:MM], auto for 00:40, walltime for each dask worker

## Temporal coherence is calculated and used to generate the mask as the reliability measure
reference: Pepe & Lanari (2006, IEEE-TGRS)
mintpy.networkInversion.minTempCoh  = auto #[0.0-1.0], auto for 0.7, min temporal coherence for mask
mintpy.networkInversion.minNumPixel = auto #[int > 0], auto for 100, min number of pixels in mask above
mintpy.networkInversion.shadowMask  = auto #[yes / no], auto for yes [if shadowMask is in geometry file] or no.

########## correct_LOD
 Local Oscillator Drift (LOD) correction (for Envisat only)
 reference: Marinkovic and Larsen (2013, Proc. LPS)
 correct LOD if input dataset comes from Envisat
 skip this step for all the other satellites.

########## 6. correct_troposphere (optional and recommended)
 correct tropospheric delay using the following methods:
 a. height_correlation - correct stratified tropospheric delay (Doin et al., 2009, J Applied Geop)
 b. pyaps - use Global Atmospheric Models (GAMs) data (Jolivet et al., 2011; 2014)
      ERA5  - ERA-5       from ECMWF [need to install pyaps3 on GitHub; recommended and turn ON by default]
      ECMWF - ERA-Interim from ECMWF [need to install pyaps  on Caltech/EarthDef]
      MERRA - MERRA-2     from NASA  [need to install pyaps  on Caltech/EarthDef]
      NARR  - NARR        from NOAA  [need to install pyaps  on Caltech/EarthDef; recommended for North America]
mintpy.troposphericDelay.method = height_correlation #[pyaps / height_correlation / no], auto for pyaps

## Notes for pyaps:
 a. GAM data latency: with the most recent SAR data, there will be GAM data missing, the correction
    will be applied to dates with GAM data available and skipped for the others.
 b. WEATHER_DIR: if you define an environmental variable named WEATHER_DIR to contain the path to a
    directory, then MintPy applications will download the GAM files into the indicated directory. Also MintPy
   application will look for the GAM files in the directory before downloading a new one to prevent downloading
    multiple copies if you work with different dataset that cover the same date/time.
mintpy.troposphericDelay.weatherModel = ECMWF  #[ERA5 / ECMWF / MERRA / NARR], auto for ERA5, for pyaps method
mintpy.troposphericDelay.weatherDir   = auto  #[path2directory], auto for WEATHER_DIR or "./"

## Notes for height_correlation:
mintpy.troposphericDelay.polyOrder      = auto  #[1 / 2 / 3], auto for 1, for height_correlation method
mintpy.troposphericDelay.looks          = auto  #[1-inf], auto for 8, for height_correlation, extra multilooking number
mintpy.troposphericDelay.minCorrelation = auto  #[0.0-1.0], auto for 0, for height_correlation

########## 7. deramp (optional)
 Estimate and remove a phase ramp for each acquisition based on the reliable pixels.
 Recommended for localized deformation signals, i.e. volcanic deformation, landslide and land subsidence, etc.
 NOT recommended for long spatial wavelength deformation signals, i.e. co-, post- and inter-seimic deformation.
mintpy.deramp          = auto #[no / linear / quadratic], auto for no - no ramp will be removed
mintpy.deramp.maskFile = auto  #[filename / no], auto for maskTempCoh.h5, mask file for ramp estimation

########## 8. correct_topography (optional and recommended)
 Topographic residual (DEM error) correction
 reference: Fattahi and Amelung (2013, IEEE-TGRS)
 stepFuncDate      - Specify stepFuncDate option if you know there are sudden displacement jump in your area,
   i.e. volcanic eruption, or earthquake, and check timeseriesStepModel.h5 afterward for their estimation.
 excludeDate       - Dates excluded for error estimation only
 pixelwiseGeometry - Use pixel-wise geometry info, such as incidence angle and slant range distance for error estimation
   yes - use pixel-wise geometry when they are available [slow; used by default]
   no  - use mean geometry [fast]
mintpy.topographicResidual                   = auto  #[yes / no], auto for yes
mintpy.topographicResidual.polyOrder         = auto  #[1-inf], auto for 2, poly order of temporal deformation model
mintpy.topographicResidual.phaseVelocity     = auto  #[yes / no], auto for no - phase, use phase velocity for error estimation
mintpy.topographicResidual.stepFuncDate      = auto  #[20080529,20100611 / no], auto for no, date of step jump
mintpy.topographicResidual.excludeDate       = auto  #[20070321 / txtFile / no], auto for exclude_date.txt
mintpy.topographicResidual.pixelwiseGeometry = auto  #[yes / no], auto for yes, use pixel-wise geometry info

########## 9.1 residual_RMS (root mean squares for noise evaluation)
 Calculate the Root Mean Square (RMS) of residual phase time-series for each acquisition
 reference: Yunjun et al. (2019, section 4.9 and 5.4)
 To get rid of long wavelength component in space, a ramp is removed for each acquisition
 Set optimal reference date to date with min RMS
 Set exclude dates (outliers) to dates with RMS > cutoff * median RMS (Median Absolute Deviation)
mintpy.residualRMS.maskFile = auto  #[file name / no], auto for maskTempCoh.h5, mask for ramp estimation
mintpy.residualRMS.deramp   = auto  #[quadratic / linear / no], auto for quadratic
mintpy.residualRMS.cutoff   = auto  #[0.0-inf], auto for 3

########## 9.2 reference_date
 Reference all time-series to one date in time
 reference: Yunjun et al. (2019, section 4.9)
 no     - do not change the default reference date (1st date)
mintpy.reference.date = auto   #[reference_date.txt / 20090214 / no], auto for reference_date.txt

########## 10. velocity
 Estimate linear velocity from time-series, and from tropospheric delay file if exists.
mintpy.velocity.excludeDate = auto   #[exclude_date.txt / 20080520,20090817 / no], auto for exclude_date.txt
mintpy.velocity.startDate   = auto   #[20070101 / no], auto for no
mintpy.velocity.endDate     = auto   #[20101230 / no], auto for no

########## 11.1 geocode (post-processing)
mintpy.geocode              = auto  #[yes / no], auto for yes
mintpy.geocode.SNWE         = auto  #[-1.2,0.5,-92,-91 / no ], auto for no, output coverage in S N W E in degree
mintpy.geocode.latStep      = auto  #[0.0-90.0 / None], auto for None, output resolution in degree
mintpy.geocode.lonStep      = auto  #[0.0-180.0 / None], auto for None - calculate from lookup file
mintpy.geocode.interpMethod = auto  #[nearest], auto for nearest, interpolation method
mintpy.geocode.fillValue    = auto  #[np.nan, 0, ...], auto for np.nan, fill value for outliers.

########## 11.2 google_earth (post-processing)
mintpy.save.kmz             = auto   #[yes / no], auto for yes, save geocoded velocity to Google Earth KMZ file

########## 11.3 hdfeos5 (post-processing)
mintpy.save.hdfEos5         = auto   #[yes / no], auto for no, save time-series to HDF-EOS5 format
mintpy.save.hdfEos5.update  = auto   #[yes / no], auto for no, put XXXXXXXX as endDate in output filename
mintpy.save.hdfEos5.subset  = auto   #[yes / no], auto for no, put subset range info   in output filename

########## 11.4 plot
mintpy.plot = auto   #[yes / no], auto for yes, plot files generated by default processing to pic folder
yunjunz commented 3 years ago

Hmm..., it's strange that the geocoding step succeeded for the other files but not for velocity.h5. Could you do the following?

  1. check the dataset size info between velocity.h5 and geometryRadar.h5? You could run info.py for it.
  2. fill out the "system info" as listed in the bug report template.
  3. if the above two are normal, I could take a look at your files (velocity.h5 and geometryRadar.h5) if you could send me, as I can not duplicate this error. I could send you an email with a link to my box if it helps with the big file sharing, let me know (yunjunzgeo@gmail.com).
alejobeap commented 3 years ago

Dear I run again the smabaselineApp.py but I had this error now:

generate_mask.py /mnt/nas_insar/TX_Pr_Cotopaxi/temporalCoherence.h5 -m 0.7 -o /mnt/nas_insar/TX_Pr_Cotopaxi/maskTempCoh.h5 --base /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5 --base-dataset shadowMask --base-value 1 update mode: ON run or skip: run input temporalCoherence file: /mnt/nas_insar/TX_Pr_Cotopaxi/temporalCoherence.h5 read /mnt/nas_insar/TX_Pr_Cotopaxi/temporalCoherence.h5 create initial mask with the same size as the input file and all = 1 all pixels with nan value = 0 exclude pixels with value < 0.7 Traceback (most recent call last): File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1255, in main(sys.argv[1:]) File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1237, in main app.run(steps=inps.runSteps) File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1044, in run self.run_network_inversion(sname) File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 558, in run_network_inversion self.generate_temporal_coherence_mask() File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 596, in generate_temporal_coherence_mask mintpy.generate_mask.main(iargs) File "/home/isce/tools/MintPy/mintpy/generate_mask.py", line 281, in main inps.outfile = create_threshold_mask(inps) File "/home/isce/tools/MintPy/mintpy/generate_mask.py", line 219, in create_threshold_mask mask[base_data == float(inps.base_value)] = 0 IndexError: boolean index did not match indexed array along dimension 0; dimension is 484 but corresponding boolean dimension is 6779

image

(isce2) [isce@srvisce TX_Pr_Cotopaxi]$ info.py /mnt/nas_insar/TX_Pr_Cotopaxi/temporalCoherence.h5 **** Basic File Info **** file name: /mnt/nas_insar/TX_Pr_Cotopaxi/temporalCoherence.h5 file type: temporalCoherence coordinates : RADAR

**** HDF5 File Structure **** Attributes in / level: ALOOKS 1 ANTENNA_SIDE -1 AZIMUTH_PIXEL_SIZE 2.2189804256224126 CENTER_INCIDENCE_ANGLE 42.594254 CENTER_LINE_UTC 39582.0 DATA_TYPE float32 DATE12 201106-201117 EARTH_RADIUS 6337071.863357354 END_DATE 20210329 FILE_LENGTH 484 FILE_PATH /mnt/nas_insar/TX_Pr_Cotopaxi/Igrams/20201106_20201117/filt_20201106_20201117_snaphu.unw FILE_TYPE temporalCoherence HEADING -168.84343243665606 HEIGHT 511737.94303342974 ISCE_VERSION Release: 2.3, svn-2531, 20190112. Current: svn-2531. LAT_REF1 -0.6354606966546388 LAT_REF2 -0.5966461840273689 LAT_REF3 -0.7590067962429349 LAT_REF4 -0.7210607138824131 LENGTH 484 LON_REF1 -78.33244131025329 LON_REF2 -78.52693520775199 LON_REF3 -78.35500085632165 LON_REF4 -78.54504074097873 NCORRLOOKS 6.753664841101326e-07 OG_FILE_PATH /mnt/nas_insar/TX_Pr_Cotopaxi/Igrams/20201106_20201117/filt_20201106_20201117_snaphu.unw PLATFORM tdx1 POLARIZATION VV PRF 3465.1269130507903 PROCESSOR isce PROJECT_NAME smallbaseline_Cotopaxi_Tx_old P_BASELINE_BOTTOM_HDR 37.24044320767456 P_BASELINE_TOP_HDR 37.78843052880664 RANGE_PIXEL_SIZE 1.364105402177116 REF_X 1906 REF_Y 51 RLOOKS 1 STARTING_RANGE 660656.3894925686 START_DATE 20201106 UNIT 1 WAVELENGTH 0.03106658265798534 WIDTH 2760 access_mode read altitude 511737.94303342974 azimuthPixelSize 2.2189804256224126 azimuthResolution 2.392 beam_mode SM byte_order l data_type float earthRadius 6337071.863357354 family unwimage file_name /mnt/nas_insar/TX_Pr_Cotopaxi/Igrams/20201106_20201117/filt_20201106_20201117_snaphu.unw image_type unw length 484 mintpy.load.azAngleFile ./merged/geomreference/los.rdr mintpy.load.azOffFile auto mintpy.load.baselineDir ./baselines mintpy.load.bperpFile auto mintpy.load.compression auto mintpy.load.connCompFile ./Igrams/*/filt.unw.conncomp mintpy.load.corFile ./Igrams//filt_.cor mintpy.load.demFile ./merged/geom_reference/hgt.rdr mintpy.load.incAngleFile ./merged/geom_reference/los.rdr mintpy.load.intFile auto mintpy.load.ionoFile auto mintpy.load.lookupXFile ./merged/geom_reference/lon.rdr mintpy.load.lookupYFile ./merged/geom_reference/lat.rdr mintpy.load.metaFile ./merged/SLC//referenceShelve/data.dat mintpy.load.offSnrFile auto mintpy.load.processor isce mintpy.load.rgOffFile auto mintpy.load.shadowMaskFile ./merged/geomreference/shadowMask.rdr mintpy.load.unwFile ./Igrams/*/filt*.unw mintpy.load.updateMode auto mintpy.load.waterMaskFile auto mintpy.networkInversion.maskDataset False mintpy.networkInversion.maskThreshold 0.4 mintpy.networkInversion.minNormVelocity True mintpy.networkInversion.minRedundancy 1.0 mintpy.networkInversion.numIfgram 36 mintpy.networkInversion.obsDatasetName unwrapPhase mintpy.networkInversion.weightFunc var mintpy.subset.lalo auto mintpy.subset.yx auto name unwimage_name number_bands 2 orbitNumber 57560 polarization VV prf 3465.1269130507903 radarWavelength 0.03106658265798534 rangePixelSize 1.364105402177116 rangeResolution 1873702.8625 relative_orbit None scheme BIL startUTC 2020-11-06 10:59:39.792327 startingRange 660656.3894925686 stopUTC 2020-11-06 10:59:45.749107 trackNumber None width 2760 xmax 2760 xmin 0

HDF5 dataset "/temporalCoherence ": shape (484, 2760) , dtype

(isce2) [isce@srvisce TX_Pr_Cotopaxi]$ info.py inputs/geometryRadar.h5 **** Basic File Info **** file name: /mnt/nas_insar/TX_Pr_Cotopaxi/inputs/geometryRadar.h5 file type: geometry coordinates : RADAR

**** HDF5 File Structure **** Attributes in / level: ALOOKS 1 ANTENNA_SIDE -1 AZIMUTH_PIXEL_SIZE 2.2189804256224126 CENTER_INCIDENCE_ANGLE 42.594254 CENTER_LINE_UTC 39582.0 DATA_TYPE float64 EARTH_RADIUS 6337071.863357354 FILE_LENGTH 6779 FILE_PATH /mnt/nas_insar/TX_Pr_Cotopaxi/merged/geom_reference/hgt.rdr FILE_TYPE geometry HEADING -168.84343243665606 HEIGHT 511737.94303342974 ISCE_VERSION Release: 2.3, svn-2531, 20190112. Current: svn-2531. LAT_REF1 -0.6354606966546388 LAT_REF2 -0.5966461840273689 LAT_REF3 -0.7590067962429349 LAT_REF4 -0.7210607138824131 LENGTH 6779 LON_REF1 -78.33244131025329 LON_REF2 -78.52693520775199 LON_REF3 -78.35500085632165 LON_REF4 -78.54504074097873 NCORRLOOKS 6.753664841101326e-07 OG_FILE_PATH /mnt/nas_insar/TX_Pr_Cotopaxi/merged/geom_reference/hgt.rdr PLATFORM tdx1 POLARIZATION VV PRF 3465.1269130507903 PROCESSOR isce PROJECT_NAME smallbaseline_Cotopaxi_Tx_old RANGE_PIXEL_SIZE 1.364105402177116 RLOOKS 1 STARTING_RANGE 660656.3894925686 WAVELENGTH 0.03106658265798534 WIDTH 11043 access_mode read altitude 511737.94303342974 azimuthPixelSize 2.2189804256224126 azimuthResolution 2.392 beam_mode SM byte_order l data_type DOUBLE description ['Pixel-by-pixel height in meters.'] earthRadius 6337071.863357354 extra_file_name /mnt/nas_insar/TX_Pr_Cotopaxi/merged/geom_reference/hgt.rdr.vrt family image file_name /mnt/nas_insar/TX_Pr_Cotopaxi/merged/geom_reference/hgt.rdr length 6779 mintpy.load.azAngleFile ./merged/geomreference/los.rdr mintpy.load.azOffFile auto mintpy.load.baselineDir ./baselines mintpy.load.bperpFile auto mintpy.load.compression auto mintpy.load.connCompFile ./Igrams/*/filt.unw.conncomp mintpy.load.corFile ./Igrams//filt_.cor mintpy.load.demFile ./merged/geom_reference/hgt.rdr mintpy.load.incAngleFile ./merged/geom_reference/los.rdr mintpy.load.intFile auto mintpy.load.ionoFile auto mintpy.load.lookupXFile ./merged/geom_reference/lon.rdr mintpy.load.lookupYFile ./merged/geom_reference/lat.rdr mintpy.load.metaFile ./merged/SLC//referenceShelve/data.dat mintpy.load.offSnrFile auto mintpy.load.processor isce mintpy.load.rgOffFile auto mintpy.load.shadowMaskFile ./merged/geomreference/shadowMask.rdr mintpy.load.unwFile ./Igrams/*/filt*.unw mintpy.load.updateMode auto mintpy.load.waterMaskFile auto mintpy.subset.lalo auto mintpy.subset.yx auto name image_name number_bands 1 orbitNumber 57560 polarization VV prf 3465.1269130507903 radarWavelength 0.03106658265798534 rangePixelSize 1.364105402177116 rangeResolution 1873702.8625 relative_orbit None scheme BIP startUTC 2020-11-06 10:59:39.792327 startingRange 660656.3894925686 stopUTC 2020-11-06 10:59:45.749107 trackNumber None width 11043 xmax 11043 xmin 0

HDF5 dataset "/azimuthAngle ": shape (6779, 11043) , dtype HDF5 dataset "/height ": shape (6779, 11043) , dtype HDF5 dataset "/incidenceAngle ": shape (6779, 11043) , dtype HDF5 dataset "/latitude ": shape (6779, 11043) , dtype HDF5 dataset "/longitude ": shape (6779, 11043) , dtype HDF5 dataset "/shadowMask ": shape (6779, 11043) , dtype HDF5 dataset "/slantRangeDistance ": shape (484, 2760) , dtype

Maybe I did something bad at the stack??

Thanks.

yunjunz commented 3 years ago

The size of the geometry datasets is not consistent, as you could see from the info.py output. You might also want to check the size of the interferogram stack file.

alejobeap commented 2 years ago

Dear @yunjunz I have again this error in the inversion processing, as you mentioned I have made multilook to the files: lon, lat los to the same azimuth and range (4 x 16) image

raceback (most recent call last):
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1255, in <module>
    main(sys.argv[1:])
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1237, in main
    app.run(steps=inps.runSteps)
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 1044, in run
    self.run_network_inversion(sname)
  File "/home/isce/tools/MintPy/mintpy/smallbaselineApp.py", line 555, in run_network_inversion
    mintpy.ifgram_inversion.main(iargs)
  File "/home/isce/tools/MintPy/mintpy/ifgram_inversion.py", line 1193, in main
    ifgram_inversion(inps)
  File "/home/isce/tools/MintPy/mintpy/ifgram_inversion.py", line 1110, in ifgram_inversion
    ts, inv_quality, num_inv_ifg = ifgram_inversion_patch(**data_kwargs)[:-1]
  File "/home/isce/tools/MintPy/mintpy/ifgram_inversion.py", line 798, in ifgram_inversion_patch
    chunk_size=100000)
  File "/home/isce/tools/MintPy/mintpy/ifgram_inversion.py", line 696, in calc_weight
    L = int(stack_obj.metadata['ALOOKS']) * int(stack_obj.metadata['RLOOKS'])
KeyError: 'ALOOKS'

the information for ifgramStack.h5

info.py inputs/ifgramStack.h5 

******************** Basic File Info ************************
file name: /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/inputs/ifgramStack.h5
file type: ifgramStack
coordinates : RADAR

******************** HDF5 File Structure ********************
Attributes in / level:
  ANTENNA_SIDE                                    -1
  AZIMUTH_PIXEL_SIZE                              2.2167761649145166
  CENTER_LINE_UTC                                 39587.0
  DATA_TYPE                                       float32
  DATE12                                          200910-201106
  EARTH_RADIUS                                    6337069.751421896
  FILE_LENGTH                                     1696
  FILE_PATH                                       /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/Igrams/20200910_20201106/filt_20200910_20201106_snaphu.unw
  FILE_TYPE                                       ifgramStack
  HEADING                                         -168.84432009494662
  HEIGHT                                          511612.94733224733
  ISCE_VERSION                                    Release: 2.3, svn-2531, 20190112. Current: svn-2531.
  LENGTH                                          1696
  OG_FILE_PATH                                    /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/Igrams/20200910_20201106/filt_20200910_20201106_snaphu.unw
  PLATFORM                                        tsx1
  POLARIZATION                                    VV
  PRF                                             3468.62720959596
  PROCESSOR                                       isce
  PROJECT_NAME                                    smallbaseline_Cotopaxi_TX
  P_BASELINE_BOTTOM_HDR                           -460.40779120859287
  P_BASELINE_TOP_HDR                              -461.2883015090358
  RANGE_PIXEL_SIZE                                1.3641053359701238
  REF_X                                           98
  REF_Y                                           1215
  STARTING_RANGE                                  660350.7981230943
  WAVELENGTH                                      0.03106658115133631
  WIDTH                                           680
  access_mode                                     read
  altitude                                        511612.94733224733
  azimuthPixelSize                                2.2167761649145166
  azimuthResolution                               2.392
  beam_mode                                       SM
  byte_order                                      l
  data_type                                       float
  earthRadius                                     6337069.751421896
  family                                          unwimage
  file_name                                       /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/Igrams/20200910_20201106/filt_20200910_20201106_snaphu.unw
  image_type                                      unw
  length                                          1696
  mintpy.compute.cluster                          auto
  mintpy.compute.config                           auto
  mintpy.compute.maxMemory                        auto
  mintpy.compute.numWorker                        auto
  mintpy.deramp                                   quadratic
  mintpy.deramp.maskFile                          auto
  mintpy.geocode                                  auto
  mintpy.geocode.SNWE                             auto
  mintpy.geocode.fillValue                        auto
  mintpy.geocode.interpMethod                     auto
  mintpy.geocode.laloStep                         auto
  mintpy.load.autoPath                            auto
  mintpy.load.azAngleFile                         ./merged/geom_reference/los_10.rdr
  mintpy.load.azOffFile                           auto
  mintpy.load.baselineDir                         ./baselines
  mintpy.load.bperpFile                           auto
  mintpy.load.compression                         auto
  mintpy.load.connCompFile                        ./Igrams/*/filt_*.unw.conncomp
  mintpy.load.corFile                             ./Igrams/*/filt_*.cor
  mintpy.load.demFile                             ./merged/geom_reference/hgt_10.rdr
  mintpy.load.incAngleFile                        ./merged/geom_reference/los_10.rdr
  mintpy.load.intFile                             auto
  mintpy.load.ionoFile                            auto
  mintpy.load.lookupXFile                         ./merged/geom_reference/lon_10.rdr
  mintpy.load.lookupYFile                         ./merged/geom_reference/lat_10.rdr
  mintpy.load.magFile                             auto
  mintpy.load.metaFile                            ./merged/SLC/20200910/referenceShelve/data.dat
  mintpy.load.offSnrFile                          auto
  mintpy.load.processor                           isce
  mintpy.load.rgOffFile                           auto
  mintpy.load.shadowMaskFile                      ./merged/geom_reference/shadowMask_10.rdr
  mintpy.load.unwFile                             ./Igrams/*/filt_*.unw
  mintpy.load.updateMode                          auto
  mintpy.load.waterMaskFile                       auto
  mintpy.load.xstep                               auto
  mintpy.load.ystep                               auto
  mintpy.network.aoiLALO                          auto
  mintpy.network.aoiYX                            auto
  mintpy.network.areaRatioBased                   auto
  mintpy.network.coherenceBased                   yes
  mintpy.network.connNumMax                       auto
  mintpy.network.endDate                          auto
  mintpy.network.excludeDate                      auto
  mintpy.network.excludeIfgIndex                  auto
  mintpy.network.keepMinSpanTree                  auto
  mintpy.network.maskFile                         auto
  mintpy.network.minAreaRatio                     auto
  mintpy.network.minCoherence                     0.5
  mintpy.network.perpBaseMax                      auto
  mintpy.network.referenceFile                    auto
  mintpy.network.startDate                        20200910
  mintpy.network.tempBaseMax                      auto
  mintpy.networkInversion.maskDataset             coherence
  mintpy.networkInversion.maskThreshold           auto
  mintpy.networkInversion.minNormVelocity         auto
  mintpy.networkInversion.minNumPixel             auto
  mintpy.networkInversion.minRedundancy           auto
  mintpy.networkInversion.minTempCoh              auto
  mintpy.networkInversion.residualNorm            auto
  mintpy.networkInversion.shadowMask              auto
  mintpy.networkInversion.waterMaskFile           auto
  mintpy.networkInversion.weightFunc              auto
  mintpy.plot                                     auto
  mintpy.reference.coherenceFile                  auto
  mintpy.reference.date                           20200910
  mintpy.reference.lalo                           auto
  mintpy.reference.maskFile                       auto
  mintpy.reference.minCoherence                   auto
  mintpy.reference.yx                             auto
  mintpy.residualRMS.cutoff                       auto
  mintpy.residualRMS.deramp                       auto
  mintpy.residualRMS.maskFile                     auto
  mintpy.save.hdfEos5                             auto
  mintpy.save.hdfEos5.subset                      auto
  mintpy.save.hdfEos5.update                      auto
  mintpy.save.kmz                                 yes
  mintpy.solidEarthTides                          auto
  mintpy.subset.lalo                              auto
  mintpy.subset.yx                                auto
  mintpy.topographicResidual                      auto
  mintpy.topographicResidual.excludeDate          auto
  mintpy.topographicResidual.phaseVelocity        auto
  mintpy.topographicResidual.pixelwiseGeometry    auto
  mintpy.topographicResidual.polyOrder            auto
  mintpy.topographicResidual.stepFuncDate         auto
  mintpy.troposphericDelay.gacosDir               auto
  mintpy.troposphericDelay.looks                  auto
  mintpy.troposphericDelay.method                 height_correlation
  mintpy.troposphericDelay.minCorrelation         auto
  mintpy.troposphericDelay.polyOrder              auto
  mintpy.troposphericDelay.weatherDir             auto
  mintpy.troposphericDelay.weatherModel           auto
  mintpy.unwrapError.bridgePtsRadius              auto
  mintpy.unwrapError.method                       auto
  mintpy.unwrapError.numSample                    auto
  mintpy.unwrapError.ramp                         auto
  mintpy.unwrapError.waterMaskFile                auto
  mintpy.velocity.bootstrap                       auto
  mintpy.velocity.bootstrapCount                  auto
  mintpy.velocity.endDate                         auto
  mintpy.velocity.excludeDate                     auto
  mintpy.velocity.startDate                       20200910
  name                                            unwimage_name
  number_bands                                    2
  orbitNumber                                     78966
  polarization                                    VV
  prf                                             3468.62720959596
  radarWavelength                                 0.03106658115133631
  rangePixelSize                                  1.3641053359701238
  rangeResolution                                 1873702.8625
  relative_orbit                                  None
  scheme                                          BIL
  startUTC                                        2021-09-10 10:59:45.457449
  startingRange                                   660350.7981230943
  stopUTC                                         2021-09-10 10:59:50.413012
  trackNumber                                     None
  width                                           680
  xmax                                            680
  xmin                                            0

HDF5 dataset "/bperp               ": shape (164,)              , dtype <float32>
HDF5 dataset "/coherence           ": shape (164, 1696, 680)    , dtype <float32>
  MODIFICATION_TIME    1633986229.815202

HDF5 dataset "/connectComponent    ": shape (164, 1696, 680)    , dtype <int16>
  MODIFICATION_TIME    1633986230.8177624

HDF5 dataset "/date                ": shape (164, 2)            , dtype <|S8>
HDF5 dataset "/dropIfgram          ": shape (164,)              , dtype <bool>
HDF5 dataset "/unwrapPhase         ": shape (164, 1696, 680)    , dtype <float32>
  MODIFICATION_TIME    1633986228.81245

and the information for geometry.h5:

info.py inputs/geometryRadar.h5
******************** Basic File Info ************************
file name: /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/inputs/geometryRadar.h5
file type: geometry
coordinates : RADAR

******************** HDF5 File Structure ********************
Attributes in / level:
  ALOOKS                                          4
  ANTENNA_SIDE                                    -1
  AZIMUTH_PIXEL_SIZE                              8.867104659658066
  CENTER_LINE_UTC                                 39587.0
  DATA_TYPE                                       float64
  EARTH_RADIUS                                    6337069.751421896
  FILE_LENGTH                                     1696
  FILE_PATH                                       /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/merged/geom_reference/hgt_10.rdr
  FILE_TYPE                                       geometry
  HEADING                                         -168.84432009494662
  HEIGHT                                          511612.94733224733
  ISCE_VERSION                                    Release: 2.3, svn-2531, 20190112. Current: svn-2531.
  LENGTH                                          1696
  OG_FILE_PATH                                    /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/merged/geom_reference/hgt.rdr
  PLATFORM                                        tsx1
  POLARIZATION                                    VV
  PRF                                             3468.62720959596
  PROCESSOR                                       isce
  PROJECT_NAME                                    smallbaseline_Cotopaxi_TX
  RANGE_PIXEL_SIZE                                21.82568537552198
  RLOOKS                                          16
  STARTING_RANGE                                  660350.7981230943
  WAVELENGTH                                      0.03106658115133631
  WIDTH                                           680
  XMAX                                            679
  XMIN                                            0
  YMAX                                            1695
  YMIN                                            0
  access_mode                                     read
  altitude                                        511612.94733224733
  azimuthPixelSize                                2.2167761649145166
  azimuthResolution                               2.392
  beam_mode                                       SM
  byte_order                                      l
  data_type                                       DOUBLE
  description                                     ['Pixel-by-pixel height in meters.']
  earthRadius                                     6337069.751421896
  extra_file_name                                 /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/merged/geom_reference/hgt.rdr.vrt
  family                                          image
  file_name                                       /mnt/nas_insar/TX_Procesamiento/Cotopaxi_TX/merged/geom_reference/hgt.rdr
  length                                          6785
  mintpy.compute.cluster                          auto
  mintpy.compute.config                           auto
  mintpy.compute.maxMemory                        auto
  mintpy.compute.numWorker                        auto
  mintpy.deramp                                   quadratic
  mintpy.deramp.maskFile                          auto
  mintpy.geocode                                  auto
  mintpy.geocode.SNWE                             auto
  mintpy.geocode.fillValue                        auto
  mintpy.geocode.interpMethod                     auto
  mintpy.geocode.laloStep                         auto
  mintpy.load.autoPath                            auto
  mintpy.load.azAngleFile                         ./merged/geom_reference/los_10.rdr
  mintpy.load.azOffFile                           auto
  mintpy.load.baselineDir                         ./baselines
  mintpy.load.bperpFile                           auto
  mintpy.load.compression                         auto
  mintpy.load.connCompFile                        ./Igrams/*/filt_*.unw.conncomp
  mintpy.load.corFile                             ./Igrams/*/filt_*.cor
  mintpy.load.demFile                             ./merged/geom_reference/hgt_10.rdr
  mintpy.load.incAngleFile                        ./merged/geom_reference/los_10.rdr
  mintpy.load.intFile                             auto
  mintpy.load.ionoFile                            auto
  mintpy.load.lookupXFile                         ./merged/geom_reference/lon_10.rdr
  mintpy.load.lookupYFile                         ./merged/geom_reference/lat_10.rdr
  mintpy.load.magFile                             auto
  mintpy.load.metaFile                            ./merged/SLC/20200910/referenceShelve/data.dat
  mintpy.load.offSnrFile                          auto
  mintpy.load.processor                           isce
  mintpy.load.rgOffFile                           auto
  mintpy.load.shadowMaskFile                      ./merged/geom_reference/shadowMask_10.rdr
  mintpy.load.unwFile                             ./Igrams/*/filt_*.unw
  mintpy.load.updateMode                          auto
  mintpy.load.waterMaskFile                       auto
  mintpy.load.xstep                               auto
  mintpy.load.ystep                               auto
  mintpy.network.aoiLALO                          auto
  mintpy.network.aoiYX                            auto
  mintpy.network.areaRatioBased                   auto
  mintpy.network.coherenceBased                   yes
  mintpy.network.connNumMax                       auto
  mintpy.network.endDate                          auto
  mintpy.network.excludeDate                      auto
  mintpy.network.excludeIfgIndex                  auto
  mintpy.network.keepMinSpanTree                  auto
  mintpy.network.maskFile                         auto
  mintpy.network.minAreaRatio                     auto
  mintpy.network.minCoherence                     0.5
  mintpy.network.perpBaseMax                      auto
  mintpy.network.referenceFile                    auto
  mintpy.network.startDate                        20200910
  mintpy.network.tempBaseMax                      auto
  mintpy.networkInversion.maskDataset             coherence
  mintpy.networkInversion.maskThreshold           auto
  mintpy.networkInversion.minNormVelocity         auto
  mintpy.networkInversion.minNumPixel             auto
  mintpy.networkInversion.minRedundancy           auto
  mintpy.networkInversion.minTempCoh              auto
  mintpy.networkInversion.residualNorm            auto
  mintpy.networkInversion.shadowMask              auto
  mintpy.networkInversion.waterMaskFile           auto
  mintpy.networkInversion.weightFunc              auto
  mintpy.plot                                     auto
  mintpy.reference.coherenceFile                  auto
  mintpy.reference.date                           20200910
  mintpy.reference.lalo                           auto
  mintpy.reference.maskFile                       auto
  mintpy.reference.minCoherence                   auto
  mintpy.reference.yx                             auto
  mintpy.residualRMS.cutoff                       auto
  mintpy.residualRMS.deramp                       auto
  mintpy.residualRMS.maskFile                     auto
  mintpy.save.hdfEos5                             auto
  mintpy.save.hdfEos5.subset                      auto
  mintpy.save.hdfEos5.update                      auto
  mintpy.save.kmz                                 yes
  mintpy.solidEarthTides                          auto
  mintpy.subset.lalo                              auto
  mintpy.subset.yx                                auto
  mintpy.topographicResidual                      auto
  mintpy.topographicResidual.excludeDate          auto
  mintpy.topographicResidual.phaseVelocity        auto
  mintpy.topographicResidual.pixelwiseGeometry    auto
  mintpy.topographicResidual.polyOrder            auto
  mintpy.topographicResidual.stepFuncDate         auto
  mintpy.troposphericDelay.gacosDir               auto
  mintpy.troposphericDelay.looks                  auto
  mintpy.troposphericDelay.method                 height_correlation
  mintpy.troposphericDelay.minCorrelation         auto
  mintpy.troposphericDelay.polyOrder              auto
  mintpy.troposphericDelay.weatherDir             auto
  mintpy.troposphericDelay.weatherModel           auto
  mintpy.unwrapError.bridgePtsRadius              auto
  mintpy.unwrapError.method                       auto
  mintpy.unwrapError.numSample                    auto
  mintpy.unwrapError.ramp                         auto
  mintpy.unwrapError.waterMaskFile                auto
  mintpy.velocity.bootstrap                       auto
  mintpy.velocity.bootstrapCount                  auto
  mintpy.velocity.endDate                         auto
  mintpy.velocity.excludeDate                     auto
  mintpy.velocity.startDate                       20200910
  name                                            image_name
  number_bands                                    1
  orbitNumber                                     78966
  polarization                                    VV
  prf                                             3468.62720959596
  radarWavelength                                 0.03106658115133631
  rangePixelSize                                  1.3641053359701238
  rangeResolution                                 1873702.8625
  relative_orbit                                  None
  scheme                                          BIP
  startUTC                                        2021-09-10 10:59:45.457449
  startingRange                                   660350.7981230943
  stopUTC                                         2021-09-10 10:59:50.413012
  trackNumber                                     None
  width                                           10890
  xmax                                            10890
  xmin                                            0

HDF5 dataset "/azimuthAngle        ": shape (1696, 680)         , dtype <float32>
HDF5 dataset "/height              ": shape (1696, 680)         , dtype <float32>
HDF5 dataset "/incidenceAngle      ": shape (1696, 680)         , dtype <float32>
HDF5 dataset "/latitude            ": shape (1696, 680)         , dtype <float32>
HDF5 dataset "/longitude           ": shape (1696, 680)         , dtype <float32>
HDF5 dataset "/shadowMask          ": shape (1696, 680)         , dtype <bool>
HDF5 dataset "/slantRangeDistance  ": shape (1696, 680)         , dtype <float32>

Could you help me what should I do because on another stack it works correctly.

Thanks

Pedro

yunjunz commented 2 years ago

The ALOOKS and RLOOKS metadata are missing in the ifgramStack file, as said in the error msg. Removing the old existing referenceShelve/data.rsc file and inputs folder and re-run mintpy should solve the issue, as the two metadata is correctly exacted for the geometry file.

alejobeap commented 2 years ago

Thank you very much for the recommendation about publishing the error and how to fix this error, I will try it.

alejobeap commented 2 years ago

It's working, Thank you