Open falkamelung opened 2 years ago
Hi Professor,
I modified the script. But I need some example file to test the modifation part.
Could you please past or send me the template file of one ascending or descending track whose data have upload to the jetstream?
For example, I need the template file of MakranBigSenAT115.template
and its SAFE_list.txt
. So I can run download_ERA5_data.py
. Then I can used timeseries.h5 file downloaded from jetstream to debug the modified script.
Xiaoran.
Below the files. They should be also on jetstream https://js-104-223.jetstream-cloud.org/data/HDF5EOS/MakranChunk28SenAT115/mintpy/inputs/
I am not sure whether SenAT115 caused a problem. I also uploaded the data set where I noticed the problem (MakranChunk28SenAT57) https://js-104-223.jetstream-cloud.org/data/HDF5EOS/MakranChunk28SenAT57/mintpy/
The mintpy command it runs is
tropo_pyaps3.py -f /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5 --model ERA5 -g /scratch/05861/tg851601/MakranChu
nk28SenAT57/mintpy/inputs/geometryRadar.h5
cd ../MakranChunk28SenAT115/
//login3/scratch/05861/tg851601/MakranChunk28SenAT115[1700] cat SAFE_files.txt
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201005T134502_20201005T134529_034662_040976_5726.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190613T134424_20190613T134451_027662_031F4B_3289.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190731T134452_20190731T134519_028362_033477_15FC.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210322T134458_20210322T134525_037112_045E85_12CD.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180125T134440_20180125T134507_020312_022B00_961F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180817T134447_20180817T134514_023287_02883F_2B76.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200127T134428_20200127T134455_030987_038F07_7978.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20191128T134455_20191128T134522_030112_0370A8_B3B8.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210121T134459_20210121T134526_036237_044014_EAAE.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190707T134451_20190707T134518_028012_0329D7_51CA.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20171021T134443_20171021T134510_018912_01FF45_D0E6.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210825T134441_20210825T134508_039387_04A707_1B3A.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20151231T134346_20151231T134414_009287_00D68F_9466.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20160429T134412_20160429T134439_011037_01099D_2775.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20151207T134413_20151207T134440_008937_00CCBD_442C.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190120T134422_20190120T134449_025562_02D60E_FF49.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150529T134354_20150529T134421_006137_007F7A_A207.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200923T134437_20200923T134504_034487_040353_0CB4.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150411T134416_20150411T134443_005437_006ECC_844F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170717T134439_20170717T134506_017512_01D47C_5089.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180724T134446_20180724T134513_022937_027D1C_DA7F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20161014T134357_20161014T134425_013487_015901_D429.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20160312T134345_20160312T134413_010337_00F4ED_8271.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190321T134421_20190321T134448_026437_02F5A4_0C69.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150318T134416_20150318T134443_005087_006648_5FB3.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20181203T134424_20181203T134451_024862_02BCE2_432E.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210906T134442_20210906T134509_039562_04AD18_44EC.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201216T134501_20201216T134527_035712_042DD1_4350.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200115T134453_20200115T134520_030812_0388DD_C7FD.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200725T134434_20200725T134501_033612_03E541_856F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200408T134453_20200408T134519_032037_03B39C_B0FD.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180525T134417_20180525T134444_022062_026269_82FA.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20191116T134431_20191116T134457_029937_036A96_03F3.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20160920T134357_20160920T134425_013137_014DDE_5DD6.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150505T134352_20150505T134419_005787_0076FA_8E3C.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201110T134502_20201110T134529_035187_041BAB_7342.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170211T134353_20170211T134421_015237_018F4E_6046.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200208T134427_20200208T134454_031162_039527_9CDB.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210509T134500_20210509T134527_037812_04767F_B563.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200514T134454_20200514T134521_032562_03C57B_43F1.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170729T134415_20170729T134442_017687_01D9D7_A1A0.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190120T134447_20190120T134514_025562_02D60E_04FF.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210521T134436_20210521T134503_037987_047BC6_90EC.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210720T134439_20210720T134506_038862_0495F5_F444.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20171126T134417_20171126T134444_019437_020F93_E5AB.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170307T134353_20170307T134421_015587_019A00_DDE1.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20160217T134411_20160217T134437_009987_00EADE_52C8.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180712T134445_20180712T134512_022762_027799_3C45.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150809T134422_20150809T134450_007187_009D19_C751.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190707T134426_20190707T134453_028012_0329D7_1D6F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201228T134435_20201228T134502_035887_0433E6_0810.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200303T134427_20200303T134454_031512_03A136_4CA1.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180501T134441_20180501T134508_021712_025746_AFCA.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210602T134501_20210602T134528_038162_048106_479F.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180218T134414_20180218T134441_020662_02362C_5686.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200830T134501_20200830T134528_034137_03F6FE_5B01.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210202T134458_20210202T134525_036412_044625_64BA.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200713T134458_20200713T134525_033437_03DFE1_9774.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210403T134434_20210403T134500_037287_04648B_EB7D.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20180606T134418_20180606T134445_022237_0267E9_8DEB.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20160429T134347_20160429T134415_011037_01099D_A010.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200911T134501_20200911T134528_034312_03FD1E_2670.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200115T134428_20200115T134455_030812_0388DD_EE78.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190108T134447_20190108T134514_025387_02CFB4_4FAE.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210813T134505_20210813T134532_039212_04A10A_B926.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200315T134452_20200315T134519_031687_03A745_578C.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20200725T134459_20200725T134526_033612_03E541_0468.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20191011T134431_20191011T134458_029412_035850_93FF.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170223T134419_20170223T134446_015412_0194B7_3D2C.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190812T134428_20190812T134455_028537_033A14_5F61.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150129T134350_20150129T134418_004387_0055AA_351D.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190414T134422_20190414T134449_026787_030282_94DA.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201204T134501_20201204T134528_035537_0427B5_1E35.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150105T134351_20150105T134419_004037_004DDD_D9DB.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20181121T134424_20181121T134451_024687_02B6CB_D767.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20170915T134442_20170915T134509_018387_01EF35_6515.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150622T134420_20150622T134448_006487_0089A2_BCEE.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20210226T134433_20210226T134500_036762_045259_52BC.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20201017T134502_20201017T134529_034837_040F9A_F799.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20181028T134449_20181028T134516_024337_02AA27_94E0.zip
/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SSV_20150622T134355_20150622T134422_006487_0089A2_7A91.zip
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/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20211024T134443_20211024T134510_040262_04C539_E877.zip
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/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20190426T134422_20190426T134449_026962_0308D3_7715.zip
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/scratch/05861/tg851601/MakranBigSenAT115/SLC/S1A_IW_SLC__1SDV_20171208T134417_20171208T134444_019612_021506_BD74.zip
cat MakranChunk28SenAT115.template
#######################################
dataset = MakranBigSenAT115
processor = isce
#######################################
ssaraopt.platform = SENTINEL-1A,SENTINEL-1B
ssaraopt.relativeOrbit = 115
#######################################
topsStack.boundingBox = 27.9 29.1 57.0 69.0
topsStack.subswath = 1 2 3
topsStack.numConnections = 4
topsStack.azimuthLooks = 21
topsStack.rangeLooks = 57
topsStack.filtStrength = 0.2
topsStack.unwMethod = snaphu
topsStack.coregistration = auto
#######################################
mintpy.load.autoPath = yes
mintpy.compute.cluster = local
mintpy.compute.numWorker = 36
mintpy.troposphericDelay.method = auto
mintpy.network.startDate = auto
mintpy.geocode.laloStep = 0.0025,0.0025
mintpy.solidEarthTides = yes
mintpy.save.hdfEos5 = yes
mintpy.save.hdfEos5.update = yes
insarmaps_flag = False
topsStack.slcDir = $SCRATCHDIR/MakranBigSenAT115/SLC
topsStack.demDir = $SCRATCHDIR/MakranBigSenAT115/DEM
Hi @ranneylxr I forgot the SAFE file for a descending. For this dataset is also downloads different chunks of the model:
tropo_pyaps3.py -f /scratch/05861/tg851601/MakranChunk25SenDT20/mintpy/timeseries_SET.h5 --model ERA5 -g /scratch/05861/tg851601/MakranChunk25SenDT20/mintpy/inputs/geometryRadar.h5 -w tmpWEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
weather model: ERA5 - dry (hydrostatic) and wet delay
weather directory: /scratch/05861/tg851601/MakranChunk25SenDT20/tmpWEATHER
output tropospheric delay file: /scratch/05861/tg851601/MakranChunk25SenDT20/mintpy/inputs/ERA5.h5
output corrected time-series file: /scratch/05861/tg851601/MakranChunk25SenDT20/mintpy/timeseries_SET_ERA5.h5
read dates/time info from file: /scratch/05861/tg851601/MakranChunk25SenDT20/mintpy/timeseries_SET.h5
time of cloest available product: 02:00 UTC
make directory: /scratch/05861/tg851601/MakranChunk25SenDT20/tmpWEATHER/ERA5
------------------------------------------------------------------------------
downloading weather model data using PyAPS ...
number of grib files to download: 163
------------------------------------------------------------------------------
INFO: You are using the latest ECMWF platform for downloading datasets: https://cds.climate.copernicus.eu/api/v2
Downloading 1 of 163: /scratch/05861/tg851601/MakranChunk25SenDT20/tmpWEATHER/ERA5/ERA5_N20_N30_E50_E70_20141007_02.grb
download_ERA5_data.py --date_list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenDT20/chunk_templates/MakranChunk25SenDT20.template --weather_dir /scratch/05861/tg851601/WEATHER
//login3/scratch/05861/tg851601/MakranChunk25SenDT20[1721] download_ERA5_data.py --date_list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenDT20/chunk_templates/MakranChunk25SenDT20.template --weather_dir tmpWEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
read safe_list SAFE_files.txt and get the date and hour
------------------------------------------------------------------------------
downloading weather model data using PyAPS ...
number of grib files to download: 172
------------------------------------------------------------------------------
INFO: You are using the latest ECMWF platform for downloading datasets: https://cds.climate.copernicus.eu/api/v2
Downloading 1 of 172: tmpWEATHER/ERA5/ERA5_N20_N30_E50_E80_20141007_02.grb
more SAFE_files.txt
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20180823T015824_20180823T015851_023367_028AC4_4BA2.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20210409T015835_20210409T015902_037367_04674A_55AD.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SSV_20160411T015827_20160411T015846_010767_010152_56A5.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20180212T015841_20180212T015909_020567_02331C_7B31.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20200214T015828_20200214T015855_031242_0397CF_C9FE.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20191029T015832_20191029T015859_029667_03611C_C7B7.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SSV_20150429T015832_20150429T015847_005692_0074E0_2556.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20180107T015817_20180107T015844_020042_022263_C250.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20190514T015824_20190514T015851_027217_031187_7C25.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20170524T015812_20170524T015839_016717_01BC2B_BFFC.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20180612T015820_20180612T015847_022317_026A66_FECA.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20170921T015818_20170921T015845_018467_01F19A_CC62.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20181115T015825_20181115T015852_024592_02B349_B072.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20190911T015856_20190911T015924_028967_0348FF_94B1.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20200625T015858_20200625T015926_033167_03D7A1_1B20.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20190303T015847_20190303T015915_026167_02EBBA_6B46.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20170430T015836_20170430T015904_016367_01B17C_9139.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20160223T015801_20160223T015828_010067_00ED33_441F.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20170723T015841_20170723T015908_017592_01D6DF_00D7.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SSV_20160716T015834_20160716T015854_012167_012DD6_90D6.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20210220T015859_20210220T015927_036667_044F07_A6AE.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20180916T015850_20180916T015918_023717_0295F2_21F7.zip
/scratch/05861/tg851601/MakranBigSenDT20/SLC/S1A_IW_SLC__1SDV_20210208T015835_20210208T015902_036492_0448EA_177C.zip
Hi Professor,
I upload the changed tropo_pyaps3_lxr.py script to mimtpy repo. I added a new def check_subset_grib_file
in the script and a line of grib_files = check_subset_grib_file(grib_files)
at line 645.
Because the extremely low download speed of ERA5 files. I have to change the name of already downloaded EAR5 files [virtual EAR5 data]to debug the script so I can not check the output ERA5.h5 results for a chunk.
The script works well under my server. But please check the EAR5.h5 file of the chunk data. For example, for the MakranChunk28SenAT57, please make sure the EAR5.h5 results is correct even if we used the ERA5 files with larger spatial range [I am sure the crop of EAR5 file to the sentinel-1 data spatial range is done by pyaps3, but it would be better to recheck it].
There maybe some potential bugs considering I only used the virtual data and only debug for one track... So, if you have any problems please send it to me.
Xiaoran
Thank you! Did anything else change? I am now getting this error
tropo_pyaps3_lxr.py --date-list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenAT57/chunk_templates/MakranChunk29SenAT57.template --weather-dir /work2/05861/tg851601/stampede2/insarlab/WEATHERtropo_pyaps3_lxr.py --date-list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenAT57/chunk_templates/MakranChunk29SenAT57.template --weather-dir /work2/05861/tg851601/stampede2/insarlab/WEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
weather model: ERA5 - dry (hydrostatic) and wet delay
weather directory: /work2/05861/tg851601/stampede2/insarlab/WEATHER
Traceback (most recent call last):
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 938, in <module>
main(sys.argv[1:])
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 898, in main
read_inps2date_time(inps)
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 237, in read_inps2date_time
raise AttributeError('time info (--hour) not found!')
AttributeError: time info (--hour) not found!
And could you please add 2-3 sentences about the cause of the problem to the issuue? Then I can check myself of it happens again.
The command looks wrong. You typed two parameters for --date-list
argument.
It should be
tropo_pyaps3_lxr.py --date-list SAFE_files.txt -g inputs/geometryRadar.h5 --weather-dir /work2/05861/tg851601/stampede2/insarlab/WEATHER.
Or after downloading ERA5 data using download_ERA5_data.py
you use command:
tropo_pyaps3.py -f /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5 --model ERA5 -g /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/inputs/geometryRadar.h5 -w /work2/05861/tg851601/stampede2/insarlab/WEATHER
Sorry, there is quite a lot of confusion and I did not copy-paste the command right. Sorry.
I used download_ERA5_data.py
from minsar. It is almost the same as tropo_pyaps3_lxr.py
except that it uses minsar-style commands instead of mintpy-style commands: --data_list
instead of --data-list
(I think. Or maybe not? I think I just renamed your script, did the minor changes and committed to minsar).
It is run once the SAFE_files.txt
is generated. The hope is that ERA5 download is completed while running ISCE. So the inputs/geometryRadar.h5
does not yet exist.
I used to run this command which works:
download_ERA5_data.py --date_list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenAT57/chunk_templates/MakranChunk29SenAT57.template --weather_dir /work2/05861/tg851601/stampede2/insarlab/WEATHER
but tropo_pyaps3_lxr.py gives an error:
tropo_pyaps3_lxr.py --date-list SAFE_files.txt /scratch/05861/tg851601/MakranBigSenAT57/chunk_templates/MakranChunk29SenAT57.template --weather-dir /work2/05861/tg851601/stampede2/insarlab/WEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
weather model: ERA5 - dry (hydrostatic) and wet delay
weather directory: /work2/05861/tg851601/stampede2/insarlab/WEATHER
Traceback (most recent call last):
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 938, in <module>
main(sys.argv[1:])
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 898, in main
read_inps2date_time(inps)
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 237, in read_inps2date_time
raise AttributeError('time info (--hour) not found!')
AttributeError: time info (--hour) not found!
I can switch to tropo_pyaps3_lxr.py
if that makes it easier for maintenance (we could call it tropo_pyaps3_minsar.py
. But it can't require any mintpy files as this defeats the purpose.
Or are you saying I should use download_ERA5_data.py
without change and use within mintpy tropo_pyaps3_lxr.py
instead of tropo_pyaps3.py
? The preferred way would be to force download_ERA5_data.py
to download exactly the files that tropo_pyaps3.py
will want, but maybe this is not possible.
Yes. I understand now. So,
The key is the longitude range. download_ERA5_data.py
uses bounding box of topsStack in the template to determin the ERA5 data to be downloaded buttropo_pyaps3[_lxr].py
uses geomeyRadar info of Mintpy product to determin the ERA5 data to be downloaded.
Therefore, if you want to make download_ERA5_data.py
download the exactly the files that tropo_pyaps3.py will want, you must determin the exactly bounding box manually. Could this be possible? [I don't think this is possible].
Thus, the possible way is that we firstly used the download_EAR5_data.py
to download the ERA5, then we use tropo_pyaps3_lxr.py
to calculate the ERA5.h5 file. In this tropo_pyaps3_lxr.py
script, it will first check whether there are downloaded ERA5 file which covers the EAR5 data it needed. For example, tropo_pyaps3_lxr.py
needs ERA5_N20_N40_E50_E60_date1_hour.h5
, and there is downloaded ERA5_N20_N40_E50_E80_date1_hour.h5
. If this situation occurrs, the script will use ERA5_N20_N40_E50_E80_date1_hour.h5
for this date1 and only download ERA5_N20_N40_E50_E60_date2_hour.h5
for date2.
Xiaoran.
Regarding longitude range, there is a function get_boundingBox_from_kml.py
used by dem_rsmas.py
that gets coordinates from the ssara*kml
file. As the image starts about 1.5 degrees south and north of the actual image min_lat and max_lat, respectively, we would have to adjust the longitude range a bit and it might be wrong occasionally when the longitude range is off. Here some boundingBoxes examples it calculates:
get_boundingBox_from_kml.py MakranBigSenAT13/SLC/ssara_search_20211108175103.kml
SNWE: 23.6 32.0 60.7 64.8
//login3/scratch/05861/tg851601[1025] get_boundingBox_from_kml.py MakranBigSenAT42/SLC/ssara_search_20211109122914.kml
SNWE: 23.3 32.2 64.7 69.0
//login3/scratch/05861/tg851601[1026] get_boundingBox_from_kml.py MakranBigSenAT57/SLC/ssara_search_20211114121732.kml
SNWE: 22.9 31.7 54.6 58.8
//login3/scratch/05861/tg851601[1027] get_boundingBox_from_kml.py MakranBigSenAT93/SLC/ssara_search_20211103152950.kml
SNWE: 23.1 32.2 55.7 60.0
//login3/scratch/05861/tg851601[1028] get_boundingBox_from_kml.py MakranBigSenDT122/SLC/ssara_search_20211024131008.kml
SNWE: 24.1 32.0 60.0 64.1
//login3/scratch/05861/tg851601[1029] get_boundingBox_from_kml.py MakranBigSenDT166/SLC/ssara_search_20211030055550.kml
SNWE: 23.4 32.3 53.7 58.0
//login3/scratch/05861/tg851601[1030] get_boundingBox_from_kml.py MakranBigSenDT20/SLC/ssara_search_20211026131210.kml
SNWE: 24.3 32.2 58.0 62.1
//login3/scratch/05861/tg851601[1031] get_boundingBox_from_kml.py MakranBigSenDT78/SLC/ssara_search_20211027131621.kml
SNWE: 23.0 31.2 66.0 70.1
MakranBigSenAT13.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenAT159.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenAT42.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenAT57.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenAT86.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenAT93.template:topsStack.boundingBox = 24.9 30.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT122.template:topsStack.boundingBox = 24.9 30.1 55.0 70.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT151.template:topsStack.boundingBox = 29.9 35.1 57.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT166.template:topsStack.boundingBox = 24.9 30.1 55.0 70.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT20.template:topsStack.boundingBox = 24.9 30.1 55.0 70.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT49.template:topsStack.boundingBox = 24.9 30.1 62.0 69.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT78.template:topsStack.boundingBox = 24.9 30.1 55.0 70.0 # '-1 0.15 -91.6 -90.9'
MakranBigSenDT93.template:topsStack.boundingBox = 24.9 30.1 55.0 70.0 # '-1 0.15 -91.6 -90.9'
Alternatively, regarding your second solution, do you mean I should use tropo_pyaps3_lxr.py
instead of mintpy/tropo_pyaps3.py
, i.e. just replace in my mintpy folder?
Regarding to the longitude range, do you mean determine the boundingBox of topsStack can not always be acurate according to the get_boundingBox_from_kml.py
results?
Regarding to the second solution: Yes. Please just replace the tropo_pyaps3_lxr.py
with the tropo_pyaps3.py
.
I prefer the second solution. It seems we can download the ERA5 file only once based on the topstack.boundingBox, then we can calculate the ERA5.h5 file for all chunks.
When I run the lxr version I am still getting an error. Any idea?
tropo_pyaps3_lxr.py -f /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5 --model ERA5 -g /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/inputs/geometryRadar.h5 -w /work2/05861/tg851601/stampede2/insarlab/WEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
weather model: ERA5 - dry (hydrostatic) and wet delay
weather directory: /work2/05861/tg851601/stampede2/insarlab/WEATHER
output tropospheric delay file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/inputs/ERA5.h5
output corrected time-series file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET_ERA5.h5
read dates/time info from file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5
time of cloest available product: 14:00 UTC
------------------------------------------------------------------------------
downloading weather model data using PyAPS ...
Traceback (most recent call last):
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 938, in <module>
main(sys.argv[1:])
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 904, in main
inps.grib_files = dload_grib_files(inps.grib_files,
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 645, in dload_grib_files
grib_files = check_subset_grib_file(grib_files)
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 542, in check_subset_grib_file
lon_grib = np.array([np.array([int(tmp[14:16]) for tmp in grib_exist_uni]).T, np.array([int(tmp[18:20]) for tmp in grib_exist_uni]).T]).T
File "/work2/05861/tg851601/stampede2/code/rsmas_insar/sources/MimtPy/mimtpy/tropo_pyaps3_lxr.py", line 542, in <listcomp>
lon_grib = np.array([np.array([int(tmp[14:16]) for tmp in grib_exist_uni]).T, np.array([int(tmp[18:20]) for tmp in grib_exist_uni]).T]).T
ValueError: invalid literal for int() with base 10: 'W1'
The regular mintpy version works fine:
tropo_pyaps3.py -f /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5 --model ERA5 -g /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/inputs/geometryRadar.h5 -w /work2/05861/tg851601/stampede2/insarlab/WEATHER
connect /private/tmp/com.apple.launchd.xt3AJkRKdV/org.macosforge.xquartz:0: Connection refused
weather model: ERA5 - dry (hydrostatic) and wet delay
weather directory: /work2/05861/tg851601/stampede2/insarlab/WEATHER
output tropospheric delay file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/inputs/ERA5.h5
output corrected time-series file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET_ERA5.h5
read dates/time info from file: /scratch/05861/tg851601/MakranChunk28SenAT57/mintpy/timeseries_SET.h5
time of cloest available product: 14:00 UTC
------------------------------------------------------------------------------
downloading weather model data using PyAPS ...
common file size: 759240 bytes
number of grib files existed : 71
number of grib files to download: 105
------------------------------------------------------------------------------
INFO: You are using the latest ECMWF platform for downloading datasets: https://cds.climate.copernicus.eu/api/v2
Downloading 1 of 105: /work2/05861/tg851601/stampede2/insarlab/WEATHER/ERA5/ERA5_N20_N40_E50_E60_20180602_14.grb
{'product_type': 'reanalysis', 'format': 'grib', 'variable': ['geopotential', 'temperature', 'specific_humidity'], 'pressure_level': ['1', '2', '3', '5', '7', '10', '20', '30', '50', '70', '100', '125', '150', '175', '200', '225', '250', '300', '350', '400', '450', '500', '550', '600', '650', '700', '750', '775', '800', '825', '850', '875', '900', '925', '950', '975', '1000'], 'year': '2018', 'month': '06', 'day': '02', 'time': '14:00', 'area': '40.00/50.00/20.00/60.00'}
2021-11-19 12:33:35,304 INFO Welcome to the CDS
2021-11-19 12:33:35,304 INFO Sending request to https://cds.climate.copernicus.eu/api/v2/resources/reanalysis-era5-pressure-levels
2021-11-19 12:33:35,424 INFO Request is queued
^CWARNING: the 1 attampt to download failed, retry it.
Could you please print the 'grib_file_exist' variable? or could you please just print the files in your $WEATHER_DIR
folder?
Hi Xiaoran @ranneylxr I found the cause for some of the download problems.
download_ERA5_data.py
downloads me the fileERA5_N20_N40_E50_E80_20150326_14.grb
When I run
mintpy
for a chunk it runsand downloads
ERA5_N20_N40_E50_E60_20150326_14.grb
. So it downloads different subsets of the same model data. Is there any chance to forcetropo_pyaps3.py
to use thesubset that is already downloaded?Below the SAFE_file: