*******************************************************
*	   Storm Surge Calculation System (SSCS)		 *
*******************************************************
Now is :  2019-05-02 09:51:20.825297  UTC

inp1= 20190502.00
ncores= 5
var= rain
submitting calc 2019-05-02 00:00:00 2019-05-02 00:00:00 delft3d 71.79 102.69 3.0 29.87 4.0 GFS 120 15 True GDACS/1000561/0_GFS_rain 6 1 False False 5  20190502.00   rain False
*************---------------------******************
ndt: 1
it:  0
ndt: 1
idate:  2019-05-02 00:00:00
running case from  2019-05-02 00:00:00  for  120  h   start= 1
var rain
**** gometeo:  120
listWindows
rundate:20190502.00
RUNNING  2019-05-02 00:00:00  for  120 hours
prevCalcDate 2019-05-01 18:00:00
Nothing to do, case already completed
ret= -3 newcase= False  forceFinal= False  forceBulletin= False
netcdf already created
home dir /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/
ret -3
classifications
============================================
1. Set INPUT/OUTPUT
============================================
startdate 2019-05-02 00:00:00
currdate 2019-05-02 00:00:00
ndt:  0 delta: 6
nt 120
alldate:  DatetimeIndex(['2019-05-02'], dtype='datetime64[ns]', freq='6H')
============================================
2. Processing meteo files: nc2tif
============================================

 >> 2.1. Process curr + past files
processing curr bull... 2019-05-02 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 120 108 123 121
nt,nx,ny, ntmax 120 108 123 121
[72.0, 0.25, 0, 29.75, 0, -0.25]
*********** 6 1 6
varMAX.shape  (108, 123)


lonmin 72.0
latmin 3.0
lonmax 102.5
latmax 29.75
<type 'netCDF4.Variable'>
float64 latitude(latitude)
    units: degrees_north
    point_spacing: even
unlimited dimensions: 
current shape = (108,)
filling off

<type 'netCDF4.Variable'>
float64 longitude(longitude)
    units: degrees_east
    point_spacing: even
unlimited dimensions: 
current shape = (123,)
filling off

72.0 102.5 3.0 29.75
lon 123
lat 108
savemap /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.jpg
dtk,nt,ntmax 6 120 121 115
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


k1, k2, ht 72 78 72


k1, k2, ht 78 84 78


k1, k2, ht 84 90 84


k1, k2, ht 90 96 90


k1, k2, ht 96 102 96


k1, k2, ht 102 108 102


k1, k2, ht 108 114 108


k1, k2, ht 114 120 114


processing all past bull only if Past=True... False
no past

 >> 2.2. Process final data files
compfile /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/20190502.00_Final_completed_rain.txt
FINAL
alldate:  DatetimeIndex(['2019-05-02'], dtype='datetime64[ns]', freq='6H')
1
**FIRST
cp  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.tif /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif
max file created /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif


lonminH 72.125
latminH 2.875
lonmaxH 102.625
latmaxH 29.625
[[ 29.625  29.625  29.625 ...,  29.625  29.625  29.625]
 [ 29.375  29.375  29.375 ...,  29.375  29.375  29.375]
 [ 29.125  29.125  29.125 ...,  29.125  29.125  29.125]
 ..., 
 [  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]]
[[  72.125   72.375   72.625 ...,  102.125  102.375  102.625]
 [  72.125   72.375   72.625 ...,  102.125  102.375  102.625]
 [  72.125   72.375   72.625 ...,  102.125  102.375  102.625]
 ..., 
 [  72.125   72.375   72.625 ...,  102.125  102.375  102.625]
 [  72.125   72.375   72.625 ...,  102.125  102.375  102.625]
 [  72.125   72.375   72.625 ...,  102.125  102.375  102.625]]
72.125 102.625 2.875 29.625
lon 123
lat 108
savemap /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_FINAL.jpg
ret:  0
============================================
3. Classify meteo + GDACS index score
============================================

 >> 3.1. Classify curr + past forecast
Creating output file that is 3690P x 3240L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain_t0.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain_t0.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_res_t0.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/class/20190502.00//rain_popfile_t0_clipped.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/class/20190502.00//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/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain_t0.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_popfile_t0_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_countryfile_t0_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00/rain_popDensValues_t0.xml
outDir created
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/1000561/0_GFS_rain/class/20190502.00/rain_popDensValues_t0.xml
>>  7.  remove files 
done
t0 completed 

Creating output file that is 3690P x 3240L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_res_all.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/class/20190502.00//rain_popfile_all_clipped.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/class/20190502.00//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/1000561/0_GFS_rain/tif/20190502.00/20190502.00_rain.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_popfile_all_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00//rain_countryfile_all_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/20190502.00/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/1000561/0_GFS_rain/class/20190502.00/rain_popDensValues_all.xml
>>  7.  remove files 
done
Creating output file that is 3690P x 3240L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final//rain_res_final.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/class/final//rain_popfile_final_clipped.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 3690P x 3240L.
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/1000561/0_GFS_rain/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/1000561/0_GFS_rain/class/20190502.00/rain_popDensValues_all.xml in:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/delft3d/20190502.00/rain_popDensValues_all.xml

 >> 3.2. Classify final folder
/mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final/20190502.00_final_completed_rain.txt
input var: rain
Input File: /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/tif/final/rain_final.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final//rain_popfile_final_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final//rain_countryfile_final_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final/rain_popDensValues_final.xml
outDir created
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/1000561/0_GFS_rain/class/final/rain_popDensValues_final.xml
>>  7.  remove files 
done
copy:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/class/final/rain_popDensValues_final.xml in:  /mnt/output/SSCS/2019/GDACS/1000561/0_GFS_rain/delft3d/final/rain_popDensValues_final.xml
==============================================================