******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-11 09:29:19.345482 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-11 00:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 3 it: 0 ndt: 3 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 3 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 3 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-11 00:00:00 ndt: 12 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-11 00:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 itdate, istime 2019-06-10 18:00:00 20190610.18 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190611.00_Final_completed_rain.txt FINAL alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00'], dtype='datetime64[ns]', freq='6H') 3 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_res_t0.tif. 0.........101010.........202020.........303030.........404040.........505050.........606060.........707070.........808080.........909090.........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_popfile_t0_clipped.tif. 0..Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_popfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_popfile_t0_clipped.tif. 0.10.........2010.10......30...2020......40...3030......50..4040......5050.......6060........607070.........708080.........909080.........90...100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_countryfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_countryfile_t0_clipped.tif. 0......Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_countryfile_t0_clipped.tif. 01010.........2020.10.......3030...20......4040...30......5050...40......6060...50......7070...60......8080...70......9090...80.......90...100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_res_all.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_res_all.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_res_all.tif. 0.........101010.........202020.........303030.........404040.........5050.50.......60.60.60.......70.70.70.......80.80.80.......90.90.90........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_popfile_all_clipped.tif. 0.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_popfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_popfile_all_clipped.tif. 0....10......1010...20......20.20.30.......30.30.40.......4040...50....5050......6060.........706070.........807080........90.90.80........90...100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_countryfile_all_clipped.tif. 0...Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_countryfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_countryfile_all_clipped.tif. 010.........201010.......30...2020......40...3030......50...4040......60...5050......70...6060......80...7070......90...8080........9090......100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190611.00_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-11 12:46:50.131458 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-11 06:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 4 it: 0 ndt: 4 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 4 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 4 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 4 idate: 2019-06-11 06:00:00 running case from 2019-06-11 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.06 RUNNING 2019-06-11 06:00:00 for 72 hours prevCalcDate 2019-06-11 00:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-11 06:00:00 ndt: 18 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-11 06:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 meteo-processing past forecast already completed itdate, istime 2019-06-10 18:00:00 20190610.18 meteo-processing past forecast already completed itdate, istime 2019-06-11 00:00:00 20190611.00 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190611.06_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00'], dtype='datetime64[ns]', freq='6H') 4 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190611.06_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-12 07:11:17.849255 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-12 00:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 7 it: 0 ndt: 7 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 7 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 7 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 7 idate: 2019-06-11 06:00:00 running case from 2019-06-11 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.06 RUNNING 2019-06-11 06:00:00 for 72 hours prevCalcDate 2019-06-11 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 7 idate: 2019-06-11 12:00:00 running case from 2019-06-11 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.12 RUNNING 2019-06-11 12:00:00 for 72 hours prevCalcDate 2019-06-11 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 5 ndt: 7 idate: 2019-06-11 18:00:00 running case from 2019-06-11 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.18 RUNNING 2019-06-11 18:00:00 for 72 hours prevCalcDate 2019-06-11 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 6 ndt: 7 idate: 2019-06-12 00:00:00 running case from 2019-06-12 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.00 RUNNING 2019-06-12 00:00:00 for 72 hours prevCalcDate 2019-06-11 18:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-12 00:00:00 ndt: 36 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-12 00:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 meteo-processing past forecast already completed itdate, istime 2019-06-10 18:00:00 20190610.18 meteo-processing past forecast already completed itdate, istime 2019-06-11 00:00:00 20190611.00 meteo-processing past forecast already completed itdate, istime 2019-06-11 06:00:00 20190611.06 meteo-processing past forecast already completed itdate, istime 2019-06-11 12:00:00 20190611.12 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 itdate, istime 2019-06-11 18:00:00 20190611.18 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190612.00_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00'], dtype='datetime64[ns]', freq='6H') 7 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_res_t0.tif. 0.........101010.........202020.........303030.........404040.........505050.........606060.........707070.........808080.........909090.........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_popfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_popfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_popfile_t0_clipped.tif. 0.......10...10.10...20......2020...30......3030...40......4040...50....5050.......60...6060......70...7070......80...8080......90...9090........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_countryfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_countryfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_countryfile_t0_clipped.tif. 0.........101010........20.20.20......30...3030......40...4040......50...5050......60...6060......70...7070......80...8080......90...9090........100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_res_all.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_res_all.tif. 0.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_res_all.tif. 0......10...1010......20...2020......30...3030......40...4040......50...5050......60...6060......70...7070......80...8080......90...9090........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_popfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_popfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_popfile_all_clipped.tif. 0.........101010.........202020.........303030.........404040.........505050........6060...60......7070....70....80.80.....80...9090.......90....100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_countryfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_countryfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_countryfile_all_clipped.tif. 0.........101010.........202020.........303030.........404040.........505050.........606060.........707070.........808080.........909090.........100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190612.00_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-12 15:20:21.391951 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-12 06:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 8 it: 0 ndt: 8 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 8 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 8 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 8 idate: 2019-06-11 06:00:00 running case from 2019-06-11 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.06 RUNNING 2019-06-11 06:00:00 for 72 hours prevCalcDate 2019-06-11 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 8 idate: 2019-06-11 12:00:00 running case from 2019-06-11 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.12 RUNNING 2019-06-11 12:00:00 for 72 hours prevCalcDate 2019-06-11 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 5 ndt: 8 idate: 2019-06-11 18:00:00 running case from 2019-06-11 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.18 RUNNING 2019-06-11 18:00:00 for 72 hours prevCalcDate 2019-06-11 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 6 ndt: 8 idate: 2019-06-12 00:00:00 running case from 2019-06-12 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.00 RUNNING 2019-06-12 00:00:00 for 72 hours prevCalcDate 2019-06-11 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 7 ndt: 8 idate: 2019-06-12 06:00:00 running case from 2019-06-12 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.06 RUNNING 2019-06-12 06:00:00 for 72 hours prevCalcDate 2019-06-12 00:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-12 06:00:00 ndt: 42 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-12 06:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 meteo-processing past forecast already completed itdate, istime 2019-06-10 18:00:00 20190610.18 meteo-processing past forecast already completed itdate, istime 2019-06-11 00:00:00 20190611.00 meteo-processing past forecast already completed itdate, istime 2019-06-11 06:00:00 20190611.06 meteo-processing past forecast already completed itdate, istime 2019-06-11 12:00:00 20190611.12 meteo-processing past forecast already completed itdate, istime 2019-06-11 18:00:00 20190611.18 meteo-processing past forecast already completed itdate, istime 2019-06-12 00:00:00 20190612.00 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190612.06_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00'], dtype='datetime64[ns]', freq='6H') 8 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190612.06_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-13 12:04:23.350109 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-13 00:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 11 it: 0 ndt: 11 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 11 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 11 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 11 idate: 2019-06-11 06:00:00 running case from 2019-06-11 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.06 RUNNING 2019-06-11 06:00:00 for 72 hours prevCalcDate 2019-06-11 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 11 idate: 2019-06-11 12:00:00 running case from 2019-06-11 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.12 RUNNING 2019-06-11 12:00:00 for 72 hours prevCalcDate 2019-06-11 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 5 ndt: 11 idate: 2019-06-11 18:00:00 running case from 2019-06-11 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.18 RUNNING 2019-06-11 18:00:00 for 72 hours prevCalcDate 2019-06-11 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 6 ndt: 11 idate: 2019-06-12 00:00:00 running case from 2019-06-12 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.00 RUNNING 2019-06-12 00:00:00 for 72 hours prevCalcDate 2019-06-11 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 7 ndt: 11 idate: 2019-06-12 06:00:00 running case from 2019-06-12 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.06 RUNNING 2019-06-12 06:00:00 for 72 hours prevCalcDate 2019-06-12 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 8 ndt: 11 idate: 2019-06-12 12:00:00 running case from 2019-06-12 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.12 RUNNING 2019-06-12 12:00:00 for 72 hours prevCalcDate 2019-06-12 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 9 ndt: 11 idate: 2019-06-12 18:00:00 running case from 2019-06-12 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.18 RUNNING 2019-06-12 18:00:00 for 72 hours prevCalcDate 2019-06-12 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 10 ndt: 11 idate: 2019-06-13 00:00:00 running case from 2019-06-13 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190613.00 RUNNING 2019-06-13 00:00:00 for 72 hours prevCalcDate 2019-06-12 18:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-13 00:00:00 ndt: 60 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00', '2019-06-12 12:00:00', '2019-06-12 18:00:00', '2019-06-13 00:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-13 00:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 meteo-processing past forecast already completed itdate, istime 2019-06-10 18:00:00 20190610.18 meteo-processing past forecast already completed itdate, istime 2019-06-11 00:00:00 20190611.00 meteo-processing past forecast already completed itdate, istime 2019-06-11 06:00:00 20190611.06 meteo-processing past forecast already completed itdate, istime 2019-06-11 12:00:00 20190611.12 meteo-processing past forecast already completed itdate, istime 2019-06-11 18:00:00 20190611.18 meteo-processing past forecast already completed itdate, istime 2019-06-12 00:00:00 20190612.00 meteo-processing past forecast already completed itdate, istime 2019-06-12 06:00:00 20190612.06 meteo-processing past forecast already completed itdate, istime 2019-06-12 12:00:00 20190612.12 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 itdate, istime 2019-06-12 18:00:00 20190612.18 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190613.00_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00', '2019-06-12 12:00:00', '2019-06-12 18:00:00', '2019-06-13 00:00:00'], dtype='datetime64[ns]', freq='6H') 11 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-13 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_res_t0.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_res_t0.tif. 0........10.10.10.....20....20.20...30......30.30.40........404050.........605050........70.60.60......80...70.70...90......8080.......9090......100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_popfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_popfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_popfile_t0_clipped.tif. 0.........101010.........202020.........303030.........404040.........505050.........606060.........707070.........808080.........909090.........100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_countryfile_t0_clipped.tif. 0...10.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_countryfile_t0_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_countryfile_t0_clipped.tif. 0....20.......103010........40.20.20.....50...30...30...60....40...4070......50..80.50.......60.90.60.......70..70....80..80....90..90.....100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_t0.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_res_all.tif. 0.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_res_all.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_res_all.tif. 0......10....1010...20......2020..30........303040.........504040.........6050.50......70...6060....80......7070...90.......8080......9090......100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_popfile_all_clipped.tif. 0.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_popfile_all_clipped.tif. 0Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_popfile_all_clipped.tif. 0....10.......101020.........202030.........303040.........404050......5050......60...60...60...70...70...70..80....80....80.90....90.....90....100 - done. 100 - done. 100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_countryfile_all_clipped.tif. 0...10.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_countryfile_all_clipped.tif. 0.Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_countryfile_all_clipped.tif. 0...20.......301010.......40...2020....50......3030..60........404070.........805050........90.60.60........7070......8080......9090......100 - done. 100 - done. 100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_all.xml >> 7. remove files done input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.00/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190613.00_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ============================================================== ******************************************************* * Storm Surge Calculation System (SSCS) * ******************************************************* Now is : 2019-06-13 13:34:19.441977 UTC inp1= 20190610.12 ncores= 5 var= rain submitting calc 2019-06-10 12:00:00 2019-06-13 06:00:00 delft3d 57.52 83.14 3.0 27.77 4.0 GFS 72 15 True GDACS/1000565/1_GFS 6 1 False False 5 20190610.12 rain False *************---------------------****************** ndt: 12 it: 0 ndt: 12 idate: 2019-06-10 12:00:00 running case from 2019-06-10 12:00:00 for 72 h start= 1 var rain **** gometeo: 72 listWindows rundate:20190610.12 RUNNING 2019-06-10 12:00:00 for 72 hours prevCalcDate 2019-06-10 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 1 ndt: 12 idate: 2019-06-10 18:00:00 running case from 2019-06-10 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190610.18 RUNNING 2019-06-10 18:00:00 for 72 hours prevCalcDate 2019-06-10 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 2 ndt: 12 idate: 2019-06-11 00:00:00 running case from 2019-06-11 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.00 RUNNING 2019-06-11 00:00:00 for 72 hours prevCalcDate 2019-06-10 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 3 ndt: 12 idate: 2019-06-11 06:00:00 running case from 2019-06-11 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.06 RUNNING 2019-06-11 06:00:00 for 72 hours prevCalcDate 2019-06-11 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 4 ndt: 12 idate: 2019-06-11 12:00:00 running case from 2019-06-11 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.12 RUNNING 2019-06-11 12:00:00 for 72 hours prevCalcDate 2019-06-11 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 5 ndt: 12 idate: 2019-06-11 18:00:00 running case from 2019-06-11 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190611.18 RUNNING 2019-06-11 18:00:00 for 72 hours prevCalcDate 2019-06-11 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 6 ndt: 12 idate: 2019-06-12 00:00:00 running case from 2019-06-12 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.00 RUNNING 2019-06-12 00:00:00 for 72 hours prevCalcDate 2019-06-11 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 7 ndt: 12 idate: 2019-06-12 06:00:00 running case from 2019-06-12 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.06 RUNNING 2019-06-12 06:00:00 for 72 hours prevCalcDate 2019-06-12 00:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 8 ndt: 12 idate: 2019-06-12 12:00:00 running case from 2019-06-12 12:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.12 RUNNING 2019-06-12 12:00:00 for 72 hours prevCalcDate 2019-06-12 06:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 9 ndt: 12 idate: 2019-06-12 18:00:00 running case from 2019-06-12 18:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190612.18 RUNNING 2019-06-12 18:00:00 for 72 hours prevCalcDate 2019-06-12 12:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 10 ndt: 12 idate: 2019-06-13 00:00:00 running case from 2019-06-13 00:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190613.00 RUNNING 2019-06-13 00:00:00 for 72 hours prevCalcDate 2019-06-12 18:00:00 Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created it: 11 ndt: 12 idate: 2019-06-13 06:00:00 running case from 2019-06-13 06:00:00 for 72 h start= 0 var rain **** gometeo: 72 listWindows rundate:20190613.06 RUNNING 2019-06-13 06:00:00 for 72 hours prevCalcDate 2019-06-13 00:00:00 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done 0 .. 20 .. 40 .. 60 .. 80 .. 100 - Done Nothing to do, case already completed ret= -3 newcase= False forceFinal= False forceBulletin= False netcdf already created home dir /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/ ret -3 classifications ============================================ 1. Set INPUT/OUTPUT ============================================ startdate 2019-06-10 12:00:00 currdate 2019-06-13 06:00:00 ndt: 66 delta: 6 nt1=delta 6 nt 72 alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00', '2019-06-12 12:00:00', '2019-06-12 18:00:00', '2019-06-13 00:00:00', '2019-06-13 06:00:00'], dtype='datetime64[ns]', freq='6H') ============================================ 2. Processing meteo files: nc2tif ============================================ >> 2.1. Process curr + past files processing curr bull... 2019-06-13 06:00:00 forcing GFS verifying that input file is present start reading nc... rain use all data in nc file nt,nx,ny, ntmax 72 100 102 73 nt,nx,ny, ntmax 72 100 102 73 [57.75, 0.25, 0, 27.75, 0, -0.25] varMAX.shape (100, 102) 57.75 83.0 3.0 27.75 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.jpg dtk,nt,ntmax 6 72 73 67 k1, k2, ht 0 6 0 k1, k2, ht 6 12 6 k1, k2, ht 12 18 12 k1, k2, ht 18 24 18 k1, k2, ht 24 30 24 k1, k2, ht 30 36 30 k1, k2, ht 36 42 36 k1, k2, ht 42 48 42 k1, k2, ht 48 54 48 k1, k2, ht 54 60 54 k1, k2, ht 60 66 60 k1, k2, ht 66 72 66 processing all past bull only if Past=True... True itdate, istime 2019-06-10 12:00:00 20190610.12 meteo-processing past forecast already completed itdate, istime 2019-06-10 18:00:00 20190610.18 meteo-processing past forecast already completed itdate, istime 2019-06-11 00:00:00 20190611.00 meteo-processing past forecast already completed itdate, istime 2019-06-11 06:00:00 20190611.06 meteo-processing past forecast already completed itdate, istime 2019-06-11 12:00:00 20190611.12 meteo-processing past forecast already completed itdate, istime 2019-06-11 18:00:00 20190611.18 meteo-processing past forecast already completed itdate, istime 2019-06-12 00:00:00 20190612.00 meteo-processing past forecast already completed itdate, istime 2019-06-12 06:00:00 20190612.06 meteo-processing past forecast already completed itdate, istime 2019-06-12 12:00:00 20190612.12 meteo-processing past forecast already completed itdate, istime 2019-06-12 18:00:00 20190612.18 meteo-processing past forecast already completed itdate, istime 2019-06-13 00:00:00 20190613.00 meteo-processing past forecast already completed >> 2.2. Process final data files compfile /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/20190613.06_Final_completed_rain.txt FINAL remove maxtif alldate: DatetimeIndex(['2019-06-10 12:00:00', '2019-06-10 18:00:00', '2019-06-11 00:00:00', '2019-06-11 06:00:00', '2019-06-11 12:00:00', '2019-06-11 18:00:00', '2019-06-12 00:00:00', '2019-06-12 06:00:00', '2019-06-12 12:00:00', '2019-06-12 18:00:00', '2019-06-13 00:00:00', '2019-06-13 06:00:00'], dtype='datetime64[ns]', freq='6H') 12 date: 2019-06-10 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain_stept0.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-11 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 12:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-12 18:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-13 00:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain_stept0.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" date: 2019-06-13 06:00:00 python /mnt/output/SSCS/scripts_NEW/gdal_calc.py -A /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif -B /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.tif --outfile=/mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif --calc="A+B" max file created /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif lonminH 57.875 latminH 2.875 lonmaxH 83.125 latmaxH 27.625 [[ 27.625 27.625 27.625 ..., 27.625 27.625 27.625] [ 27.375 27.375 27.375 ..., 27.375 27.375 27.375] [ 27.125 27.125 27.125 ..., 27.125 27.125 27.125] ..., [ 3.375 3.375 3.375 ..., 3.375 3.375 3.375] [ 3.125 3.125 3.125 ..., 3.125 3.125 3.125] [ 2.875 2.875 2.875 ..., 2.875 2.875 2.875]] [[ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] ..., [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125] [ 57.875 58.125 58.375 ..., 82.625 82.875 83.125]] 57.875 83.125 2.875 27.625 lon 102 lat 100 savemap /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg ret: 0 ============================================ 3. Classify meteo + GDACS index score ============================================ >> 3.1. Classify curr + past forecast Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain_t0.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain_t0.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_res_t0.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_popfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_countryfile_t0_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain_t0.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_popfile_t0_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_countryfile_t0_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06/rain_popDensValues_t0.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06/rain_popDensValues_t0.xml >> 7. remove files done t0 completed Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.tif. Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_res_all.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_popfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_countryfile_all_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_popfile_all_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06//rain_countryfile_all_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06/rain_popDensValues_all.xml popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06/rain_popDensValues_all.xml >> 7. remove files done Creating output file that is 3060P x 3000L. Processing input file /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Using internal nodata values (e.g. 3.40282e+38) for image /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif. Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_res_final.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/lspop20141.tif. Using internal nodata values (e.g. -2.14748e+09) for image /mnt/output/GDACS/DATA/lspop20141.tif. Copying nodata values from source /mnt/output/GDACS/DATA/lspop20141.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. Creating output file that is 3060P x 3000L. Processing input file /mnt/output/GDACS/DATA/countries.tif. Using internal nodata values (e.g. -32768) for image /mnt/output/GDACS/DATA/countries.tif. Copying nodata values from source /mnt/output/GDACS/DATA/countries.tif to destination /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif. 0...10...20...30...40...50...60...70...80...90...100 - done. t0 completed copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.12/20190610.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190610.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190610.18/20190610.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190610.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.00/20190611.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.06/20190611.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.12/20190611.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190611.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190611.18/20190611.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190611.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.00/20190612.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.06/20190612.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.06/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.12/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.12/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.12/20190612.12_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.12/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190612.18/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.18/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190612.18/20190612.18_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190612.18/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.00/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.00/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.00/20190613.00_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.00/rain.jpg copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/20190613.06/rain_popDensValues_all.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.06/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/20190613.06/20190613.06_rain.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/20190613.06/rain.jpg >> 3.2. Classify final folder /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/20190613.06_final_completed_rain.txt input var: rain Input File: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_final.tif hurName: hdate: var: rain description: rain: _ (GFS) OutDir: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final// PopFile: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_popfile_final_clipped.tif country: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final//rain_countryfile_final_clipped.tif outxml file: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml xml file exists...REMOVE popfile: LandScan popCellSize= 0.00833333333333 projection= GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0],UNIT["degree",0.0174532925199433],AUTHORITY["EPSG","4326"]] >> 1. resample the tif file to the resolution and proj of pop density 0.00833333333333 deg >> 2. read the charactristics of the input file >> 3a. extract a piece of pop. file corresponding to the required bounding box >> 3b. extract a piece of countries corresponding to the required bounding box and resolution/proj of pop density >> 4. classify the vmax file creating another array of values classified cellsize 0.00833333333333 cellsize 0.00833333333333 cellsize 0.00833333333333 >> 5. count the popolation in each cell and assign to the class and write to output >> 6. print / save output in /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml >> 7. remove files done copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/class/final/rain_popDensValues_final.xml in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain_popDensValues.xml copy: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/tif/final/rain_FINAL.jpg in: /mnt/output/SSCS/2019/GDACS/1000565/1_GFS/delft3d/final/rain.jpg ==============================================================