*******************************************************
*	   Storm Surge Calculation System (SSCS)		 *
*******************************************************
Now is :  2019-04-24 12:21:03.960551  UTC

inp1= 20190424.00
ncores= 5
var= rain
submitting calc 2019-04-24 00:00:00 2019-04-24 00:00:00 delft3d 19.4 59.72 -36.0 -3.0 4.0 GFS 120 15 True GDACS/1000559/00_GFS 6 1 False False 5  20190424.00   rain False
*************---------------------******************
ndt: 1
it:  0
ndt: 1
idate:  2019-04-24 00:00:00
running case from  2019-04-24 00:00:00  for  120  h   start= 1
var rain
**** gometeo:  120
listWindows
rundate:20190424.00
RUNNING  2019-04-24 00:00:00  for  120 hours
prevCalcDate 2019-04-23 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/1000559/00_GFS/
ret -3
classifications
============================================
1. Set INPUT/OUTPUT
============================================
startdate 2019-04-24 00:00:00
currdate 2019-04-24 00:00:00
ndt:  0 delta: 6
nt 120
alldate:  DatetimeIndex(['2019-04-24'], dtype='datetime64[ns]', freq='6H')
============================================
2. Processing meteo files: nc2tif
============================================

 >> 2.1. Process curr + past files
processing curr bull... 2019-04-24 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 120 133 161 121
nt,nx,ny, ntmax 120 133 161 121
[19.5, 0.25, 0, -3.0, 0, -0.25]
*********** 6 1 6
varMAX.shape  (133, 161)


lonmin 19.5
latmin -36.0
lonmax 59.5
latmax -3.0
<type 'netCDF4.Variable'>
float64 latitude(latitude)
    units: degrees_north
    point_spacing: even
unlimited dimensions: 
current shape = (133,)
filling off

<type 'netCDF4.Variable'>
float64 longitude(longitude)
    units: degrees_east
    point_spacing: even
unlimited dimensions: 
current shape = (161,)
filling off

19.5 59.5 -36.0 -3.0
lon 161
lat 133
savemap /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_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/1000559/00_GFS/tif/final/20190424.00_Final_completed_rain.txt
FINAL
alldate:  DatetimeIndex(['2019-04-24'], dtype='datetime64[ns]', freq='6H')
1
**FIRST
cp  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain.tif /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif
max file created /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif


lonminH 19.625
latminH -36.125
lonmaxH 59.625
latmaxH -3.125
[[ -3.125  -3.125  -3.125 ...,  -3.125  -3.125  -3.125]
 [ -3.375  -3.375  -3.375 ...,  -3.375  -3.375  -3.375]
 [ -3.625  -3.625  -3.625 ...,  -3.625  -3.625  -3.625]
 ..., 
 [-35.625 -35.625 -35.625 ..., -35.625 -35.625 -35.625]
 [-35.875 -35.875 -35.875 ..., -35.875 -35.875 -35.875]
 [-36.125 -36.125 -36.125 ..., -36.125 -36.125 -36.125]]
[[ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]
 [ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]
 [ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]
 ..., 
 [ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]
 [ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]
 [ 19.625  19.875  20.125 ...,  59.125  59.375  59.625]]
19.625 59.625 -36.125 -3.125
lon 161
lat 133
savemap /mnt/output/SSCS/2019/GDACS/1000559/00_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 4830P x 3990L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain_t0.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain_t0.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain_t0.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_res_t0.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 4830P x 3990L.
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/1000559/00_GFS/class/20190424.00//rain_popfile_t0_clipped.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 4830P x 3990L.
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/1000559/00_GFS/class/20190424.00//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/1000559/00_GFS/tif/20190424.00/20190424.00_rain_t0.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_popfile_t0_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_countryfile_t0_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00/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
>>  6.  print / save output in  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00/rain_popDensValues_t0.xml
>>  7.  remove files 
done
t0 completed 

Creating output file that is 4830P x 3990L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/20190424.00/20190424.00_rain.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_res_all.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 4830P x 3990L.
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/1000559/00_GFS/class/20190424.00//rain_popfile_all_clipped.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 4830P x 3990L.
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/1000559/00_GFS/class/20190424.00//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/1000559/00_GFS/tif/20190424.00/20190424.00_rain.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_popfile_all_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00//rain_countryfile_all_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/20190424.00/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/1000559/00_GFS/class/20190424.00/rain_popDensValues_all.xml
>>  7.  remove files 
done
Creating output file that is 4830P x 3990L.
Processing input file /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif.
Using internal nodata values (e.g. -999) for image /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif.
Copying nodata values from source /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif to destination /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final//rain_res_final.tif.
0...10...20...30...40...50...60...70...80...90...100 - done.
Creating output file that is 4830P x 3990L.
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/1000559/00_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 4830P x 3990L.
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/1000559/00_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/1000559/00_GFS/class/20190424.00/rain_popDensValues_all.xml in:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/delft3d/20190424.00/rain_popDensValues_all.xml

 >> 3.2. Classify final folder
/mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final/20190424.00_final_completed_rain.txt
input var: rain
Input File: /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/tif/final/rain_final.tif
hurName:  
hdate:  
var:  rain
description:  rain: _ (GFS)
OutDir:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final//
PopFile:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final//rain_popfile_final_clipped.tif
country:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final//rain_countryfile_final_clipped.tif
outxml file:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/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/1000559/00_GFS/class/final/rain_popDensValues_final.xml
>>  7.  remove files 
done
copy:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/class/final/rain_popDensValues_final.xml in:  /mnt/output/SSCS/2019/GDACS/1000559/00_GFS/delft3d/final/rain_popDensValues_final.xml
==============================================================