def process_extents(div_name, dist_name, process_date,
src_dir, extents_list, options):
''' Main function for processing extents. Calls lots of helper
and utility functions.
div_name: string - Name of division, used in output file format.
process_date: datetime.datetime object - date for which data is desired.
extents_list: list - list of namedtuples for each watershed.
Returns the path to the file if new data was written to a DSS file,
None otherwise.
'''
def verbose_print(to_print):
if options.verbose:
print to_print
def clean_up_tmp_dir(tmp_dir):
if not options.keep_tmp_dir:
shutil.rmtree(tmp_dir)
topdir = config.TOP_DIR
verbose_print('Source directory: {0}'.format(src_dir))
# Use 'us' prefix and adjust nodata value for dates before January 24, 2011.
dataset_type = 'zz'
nodata_val = '-9999'
if process_date < datetime.datetime(2011, 1, 24, 0, 0):
dataset_type = 'us'
nodata_val = '55537'
projdir = os.path.join(topdir, div_name, dist_name)
projresdir = os.path.join(projdir, 'results_sn')
projascdir = os.path.join(projresdir, 'asc_files')
projdssdir = os.path.join(projresdir, 'dss_files')
histdir = os.path.join(projresdir, 'history')
# Build our results directories if needed.
mkdir_p(projascdir)
mkdir_p(projdssdir)
mkdir_p(histdir)
dstr = datetime.datetime.now().strftime('%y%m%d%H%M%S')
ymdDate = process_date.strftime('%Y%m%d')
# Break out if processing for the given date has already happened.
histfile = os.path.join(histdir, 'proccomplete' + ymdDate + '.txt')
if os.path.isfile(histfile):
print '{0} {1} grids already processed for: {2}'.format(
div_name, dist_name, process_date.strftime('%Y.%m.%d')
)
return None
print 'Processing {0} {1} grids for: {2}'.format(
div_name, dist_name, process_date.strftime('%Y.%m.%d')
)
tmpdir = os.path.join(projresdir, 'tmp' + dstr)
os.mkdir(tmpdir)
# Set up a dictionary mapping the various properties to their DSS names.
PropDict = SetProps(process_date, div_name)
enameDict = {}
zerolist = ["0001", "0002", "0003"]
extentGProps = {}
maxExtent = getMaxExtent(extents_list)
dssbasename = GetDSSBaseName(process_date)
dssfile = os.path.join(projdssdir, dssbasename)
# Define our files and make sure they all exist.
snodaslist = [
s.format(ds=dataset_type, ymd=ymdDate) for s in SNODAS_FILENAME_LIST
]
# Loop through our source SNODAS files.
for f in snodaslist:
varcode = f[8:12]
varprops = PropDict[varcode]
path = "/" + "/".join(varprops[0]) + "/"
dtype = varprops[1]
easiername = \
div_name + "_" + varprops[0][2].replace(" ", "_").lower() + ymdDate
enameDict[varcode] = os.path.join(projascdir, easiername + ".asc")
shgtif = os.path.join(tmpdir, f + "alb.tif")
shgtifmath = os.path.join(tmpdir, easiername + ".tif")
src_file = os.path.join(src_dir, f + '.bil')
ReprojUseWarpBil(src_file, shgtif, maxExtent, nodata_val)
mathranokay = True
if varprops[2]:
# NOTE: enamedict populated only for prior product numbers
mathranokay = RasterMath(shgtif, shgtifmath, varcode, enameDict)
else:
shgtifmath = shgtif
if mathranokay:
enameDict[varcode] = shgtifmath
for extentarr in extents_list:
ds = gdal.Open(shgtifmath)
if ds is None:
print 'Could not open ' + shgtifmath
return None
nodata = ds.GetRasterBand(1).GetNoDataValue()
fullext = GetDatasetExtent(ds)
cellsize = ds.GetGeoTransform()[1]
subext = extentarr[1]
fullof, subof = min_box_os(fullext, subext, cellsize)
xsize = int(fullof[2])
ysize = int(fullof[3])
dsProj = ds.GetProjection()
cliparr = ds.GetRasterBand(1).ReadAsArray(
int(round(fullof[0])), int(round(fullof[1])),
xsize, ysize
)
outtmpname = os.path.join(tmpdir, extentarr[0] + "tmp.asc")
driver = gdal.GetDriverByName("MEM")
clipgeot = [subext[0], cellsize, 0, subext[3], 0, -cellsize]
extentGProps[extentarr[0]] = [
dsProj, clipgeot, xsize, ysize, nodata]
clipds = driver.Create("", xsize, ysize, 1, GDT_Float32)
clipds.SetGeoTransform(clipgeot)
clipds.SetProjection(ds.GetProjection())
clipds.GetRasterBand(1).SetNoDataValue(nodata)
clipds.GetRasterBand(1).WriteArray(cliparr, 0, 0)
clipds.FlushCache()
ascbasename = extentarr[0] + "_" + \
varprops[0][2].replace(" ", "_").lower() + ymdDate
CreateASCII(clipds, ascbasename, tmpdir)
clipds = None
ds = None
tmpasc = os.path.join(tmpdir, ascbasename + ".asc")
projasc = os.path.join(projascdir, ascbasename + ".asc")
shutil.copy(tmpasc, projasc)
shutil.copy(
os.path.join(tmpdir, ascbasename + "tmp.prj"),
os.path.join(projascdir, ascbasename + ".prj")
)
varprops = PropDict[varcode]
p = varprops[0]
dtype = varprops[1]
path = "/SHG/" + extentarr[0].upper() + "/" + p[2] + \
"/" + p[3] + "/" + p[4] + "/" + p[5] + "/"
WriteToDSS(projasc, dssfile, dtype, path)
outarr = None
cliparr = None
if len(extentGProps) == 0:
print "An error occurred identifying extent properties."
clean_up_tmp_dir(tmpdir)
return None
for varcode in zerolist:
varprops = PropDict[varcode]
for extentarr in extents_list:
p = varprops[0]
dtype = varprops[1]
path = "/SHG/" + extentarr[0].upper() + "/" + p[2] + \
"/" + p[3] + "/" + p[4] + "/" + p[5] + "/"
ascbasename = extentarr[0] + "_" + \
varprops[0][2].replace(" ", "_").lower() + ymdDate
tmpasc = os.path.join(tmpdir, ascbasename + ".asc")
projasc = os.path.join(projascdir, ascbasename + ".asc")
WriteZeroDStoAsc(extentGProps[extentarr[0]], ascbasename, tmpdir)
shutil.copy(tmpasc, projasc)
shutil.copy(os.path.join(tmpdir, ascbasename + "tmp.prj"),
os.path.join(projascdir, ascbasename + ".prj"))
dssdunits = varprops[3]
WriteToDSS(projasc, dssfile, dtype, path, dssdunits)
clean_up_tmp_dir(tmpdir)
clean_up_tmp_dir(projascdir)
# Write out file to track that we've run for this day.
with open(histfile, "w") as fo:
dstr = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
fo.write(process_date.strftime("%a %b %d %H:%M:%S %Y"))
fo.close
return dssfile
def prepare_source_data_for_date(process_date, src_dir, save_tiff=True):
''' Builds an unzip directory and extracts data from source files
for a given day.
Returns the directory path to the unzipped files,
or None if missing any source data. '''
ymd_str = process_date.strftime('%Y%m%d')
unzip_dir = os.path.join(config.TOP_DIR, 'unzipped_data', ymd_str)
us_tif_dir = os.path.join(config.TOP_DIR, 'conus_tiffs')
# Use 'us' prefix and adjust nodata value for dates before January 24, 2011.
ds_type = 'zz'
nodata_val = '-9999'
if process_date < datetime.datetime(2011, 1, 24, 0, 0):
ds_type = 'us'
nodata_val = '55537'
masterhdr = os.path.join(config.TOP_DIR, 'key', ds_type + '_master.hdr')
# Create list of file names for this date.
snodas_src_files = [
f.format(ds=ds_type, ymd=ymd_str) for f in SNODAS_FILENAME_LIST
]
# Make sure all files exist before trying any extractions.
print_dashes()
print 'Processing source data for:', process_date.strftime('%Y.%m.%d')
msgs = []
for filename in snodas_src_files:
if not os.path.isfile(os.path.join(src_dir, filename + '.grz')):
msgs += ['Missing source data file: {0}'.format(filename)]
if msgs:
for msg in msgs:
print msg
print_dashes()
return None
if save_tiff:
mkdir_p(us_tif_dir)
# Loop through our filenames and do the unzipping and other set up.
mkdir_p(unzip_dir)
for filename in snodas_src_files:
src_file = os.path.join(src_dir, filename)
unzip_file = os.path.join(unzip_dir, filename)
ready_file = unzip_file + '.bil'
if not os.path.isfile(ready_file):
print 'Processing source to output file:', ready_file
UnzipLinux(src_file, unzip_file)
RawFileManip(unzip_file, masterhdr)
else:
print 'Using existing source file:', ready_file
# Save a full version of the day's data set.
shgtif = os.path.join(us_tif_dir, filename + 'alb.tif')
if save_tiff:
if not os.path.isfile(shgtif):
print 'Saving CONUS SHG tiff file:', shgtif
ReprojUseWarpBil(ready_file, shgtif, nodata=nodata_val,
tr_x='1000', tr_y='-1000')
else:
print 'CONUS SHG tiff already exists:', shgtif
print_dashes()
return unzip_dir
def process_extents(office_symbol, process_date, src_dir, extents_list,
options):
''' Main function for processing extents. Calls lots of helper
and utility functions.
office_symbol: string - unique office symbol, used in output file format
process_date: datetime.datetime object - date for which data is desired.
extents_list: list - list of namedtuples for each watershed.
Returns the path to the file if new data was written to a DSS file,
None otherwise.
'''
def verbose_print(to_print):
if options.verbose:
print(to_print)
def clean_up_tmp_dir(tmp_dir):
if not options.keep_tmp_dir:
shutil.rmtree(tmp_dir)
verbose_print('Source directory: {0}'.format(src_dir))
# Use 'us' prefix and adjust nodata value for dates before January 24, 2011.
dataset_type = 'zz'
nodata_val = '-9999'
if process_date < datetime.datetime(2011, 1, 24, 0, 0):
dataset_type = 'us'
nodata_val = '55537'
# Use the proper results dir structure based on the config file.
projfltdir = os.path.join(config.FLT_BASE_DIR, office_symbol)
projdssdir = os.path.join(config.DSS_BASE_DIR, office_symbol)
histdir = os.path.join(config.HISTORY_BASE_DIR, office_symbol)
tmpdir = os.path.join(
projfltdir,
'tmp{}'.format(datetime.datetime.now().strftime('%y%m%d%H%M%S')))
# Build our results directories if needed.
for d in (projfltdir, projdssdir, histdir, tmpdir):
mkdir_p(d)
# Break out if processing for the given date has already happened.
histfile = os.path.join(
histdir, 'proccomplete{}.txt'.format(process_date.strftime('%Y%m%d')))
if os.path.isfile(histfile):
print('{0} grids already processed for: {1}'.format(
office_symbol, process_date.strftime('%Y.%m.%d')))
return None
print('Processing {0} grids for: {1}'.format(
office_symbol, process_date.strftime('%Y.%m.%d')))
# Set up a dictionary mapping the various properties to their DSS names.
PropDict = SetProps(process_date, office_symbol)
scratchfile_dict = {}
extentGProps = {}
maxExtent = getMaxExtent(extents_list)
dssfile = os.path.join(projdssdir,
'{}'.format(GetDSSBaseName(process_date)))
# Instantiate new flt2dss.Operation
flt2dss_operation = flt2dss.Operation()
# Loop through our source SNODAS files.
for f in [
s.format(ds=dataset_type, ymd=process_date.strftime('%Y%m%d'))
for s in SNODAS_FILENAME_LIST
]:
# Strip variable key/ID from filename
varcode = f[8:12]
varprops = PropDict[varcode]
# Filenames
src_file = os.path.join(src_dir, '{}.bil'.format(f))
shgtif = os.path.join(tmpdir, '{}alb.tif'.format(f))
shgtifmath = os.path.join(tmpdir, '{}.tif'.format(f))
# Reproject src_file to shgtif
ReprojUseWarpBil(src_file, shgtif, maxExtent, nodata_val)
# Set dictionary entry for variable to filepath to SHG projected TIF
scratchfile_dict[varcode] = shgtif
# if variable does not require computation to define grid values, set
# "shgtifmath" (grid after computation) to shgtif (raw grid)
# else run RasterMath() to write a grid with computed values
mathranokay = True
# If math is not required to derive final grid
if varprops[2] is False:
shgtifmath = shgtif
else:
# NOTE: scratchfile_dict populated only for prior product numbers
mathranokay = RasterMath(shgtif, shgtifmath, varcode,
scratchfile_dict)
if mathranokay:
scratchfile_dict[varcode] = shgtifmath
for extentarr in extents_list:
ds = gdal.Open(shgtifmath)
if ds is None:
print('Could not open {}'.format(shgtifmath))
return None
nodata = ds.GetRasterBand(1).GetNoDataValue()
fullext = GetDatasetExtent(ds)
cellsize = ds.GetGeoTransform()[1]
extent_name, subext = extentarr[0], extentarr[1]
fullof, subof = min_box_os(fullext, subext, cellsize)
xsize = int(fullof[2])
ysize = int(fullof[3])
dsProj = ds.GetProjection()
cliparr = ds.GetRasterBand(1).ReadAsArray(
int(round(fullof[0])), int(round(fullof[1])), xsize, ysize)
clipgeot = [subext[0], cellsize, 0, subext[3], 0, -cellsize]
extentGProps[extent_name] = [
dsProj, clipgeot, xsize, ysize, nodata
]
driver = gdal.GetDriverByName("MEM")
clipds = driver.Create("", xsize, ysize, 1, gdal.GDT_Float32)
clipds.SetGeoTransform(clipgeot)
clipds.SetProjection(ds.GetProjection())
clipds.GetRasterBand(1).SetNoDataValue(nodata)
clipds.GetRasterBand(1).WriteArray(cliparr, 0, 0)
clipds.FlushCache()
file_basename1 = '{}_{}{}'.format(
extent_name.replace(" ", "_"),
varprops[0][2].replace(" ", "_").lower(),
process_date.strftime('%Y.%m.%d'))
# Write grid to "file_basename1" in the tmpdir
WriteGrid(clipds, file_basename1, tmpdir,
config.SCRATCH_FILE_DRIVER)
cliparr = None
clipds = None
ds = None
# Create a flt2dss Task
flt2dss_task = flt2dss.Task(
infile=os.path.join(tmpdir,
'{}.{}'.format(file_basename1, 'bil')),
dss_file=dssfile,
data_type=varprops[1],
pathname='/SHG/{}/{}/{}/{}/{}/'.format(
extentarr[0].upper(), varprops[0][2], varprops[0][3],
varprops[0][4], varprops[0][5]),
grid_type='SHG',
data_unit=varprops[3])
# Add flt2dss Task to Operation
flt2dss_operation.add_task(flt2dss_task)
if len(extentGProps) == 0:
print("An error occurred identifying extent properties.")
clean_up_tmp_dir(tmpdir)
return None
# Write Zero Grids for LIQUID WATER, COLD CONTENT ATI, MELTRATE ATI
for varcode in ["0001", "0002", "0003"]:
varprops = PropDict[varcode]
for extentarr in extents_list:
file_basename2 = '{}_{}{}'.format(
extentarr[0].replace(" ", "_"),
varprops[0][2].replace(" ", "_").lower(),
process_date.strftime('%Y%m%d'))
# Write grid to "file_basename1" in the tmpdir
WriteZeroGrid(extentGProps[extentarr[0]], file_basename2, tmpdir,
config.SCRATCH_FILE_DRIVER)
# Create a flt2dss Task
flt2dss_task = flt2dss.Task(infile=os.path.join(
tmpdir, '{}.{}'.format(file_basename2, 'bil')),
dss_file=dssfile,
data_type=varprops[1],
pathname='/SHG/{}/{}/{}/{}/{}/'.format(
extentarr[0].upper(),
varprops[0][2], varprops[0][3],
varprops[0][4], varprops[0][5]),
grid_type='SHG',
data_unit=varprops[3])
# Add flt2dss Task to Operation
flt2dss_operation.add_task(flt2dss_task)
# Write grids to DSS
flt2dss_operation.execute()
clean_up_tmp_dir(tmpdir)
# Write out file to track that we've run for this day.
with open(histfile, "w") as fo:
fo.write(process_date.strftime("%a %b %d %H:%M:%S %Y"))
fo.close
return dssfile
def prepare_source_data_for_date(process_date, src_dir, save_tiff=True):
''' Builds an unzip directory and extracts data from source files
for a given day.
Returns the directory path to the unzipped files,
or None if missing any source data. '''
ymd_str = process_date.strftime('%Y%m%d')
unzip_dir = os.path.join(config.PROCESSED_SRC_DIR, 'unzipped_data',
ymd_str)
us_tif_dir = os.path.join(config.PROCESSED_SRC_DIR, 'conus_tiffs')
# Use 'us' prefix and adjust nodata value for dates before January 24, 2011.
ds_type = 'zz'
nodata_val = '-9999'
if process_date < datetime.datetime(2011, 1, 24, 0, 0):
ds_type = 'us'
nodata_val = '55537'
masterhdr = os.path.join(config.HEADER_KEY_DIR, ds_type + '_master.hdr')
# Create list of file names for this date.
snodas_src_files = [
f.format(ds=ds_type, ymd=ymd_str) for f in SNODAS_FILENAME_LIST
]
# Make sure all files exist before trying any extractions.
print_dashes()
print('Processing source data for: {}'.format(
process_date.strftime('%Y.%m.%d')))
msgs = []
for filename in snodas_src_files:
_file = os.path.join(src_dir, filename + '.grz')
if not os.path.isfile(_file):
msgs += ['Missing source data file: {0}'.format(_file)]
if msgs:
for msg in msgs:
print(msg)
print_dashes()
return None
if save_tiff:
mkdir_p(us_tif_dir)
# Loop through our filenames and do the unzipping and other set up.
mkdir_p(unzip_dir)
for filename in snodas_src_files:
src_file = os.path.join(src_dir, filename)
unzip_file = os.path.join(unzip_dir, filename)
ready_file = unzip_file + '.bil'
if not os.path.isfile(ready_file):
print('Processing source to output file: {}'.format(ready_file))
try:
UnzipLinux(src_file, unzip_file)
RawFileManip(unzip_file, masterhdr)
except:
print('ERROR: Failure in UnzipLinux or RawFileManip')
return None
else:
print('Using existing source file: {}'.format(ready_file))
# Save a full version of the day's data set.
shgtif = os.path.join(us_tif_dir, filename + 'alb.tif')
if save_tiff:
if not os.path.isfile(shgtif):
print('Saving CONUS SHG tiff file: {}'.format(shgtif))
ReprojUseWarpBil(ready_file,
shgtif,
nodata=nodata_val,
tr_x='1000',
tr_y='-1000')
else:
print('CONUS SHG tiff already exists: {}'.format(shgtif))
print_dashes()
return unzip_dir
def process_extents(div_name, dist_name, process_date, src_dir, extents_list,
options):
''' Main function for processing extents. Calls lots of helper
and utility functions.
div_name: string - Name of division, used in output file format.
process_date: datetime.datetime object - date for which data is desired.
extents_list: list - list of namedtuples for each watershed.
Returns the path to the file if new data was written to a DSS file,
None otherwise.
'''
def verbose_print(to_print):
if options.verbose:
print to_print
def clean_up_tmp_dir(tmp_dir):
if not options.keep_tmp_dir:
shutil.rmtree(tmp_dir)
verbose_print('Source directory: {0}'.format(src_dir))
# Use 'us' prefix and adjust nodata value for dates before January 24, 2011.
dataset_type = 'zz'
nodata_val = '-9999'
if process_date < datetime.datetime(2011, 1, 24, 0, 0):
dataset_type = 'us'
nodata_val = '55537'
projdir = os.path.join(config.TOP_DIR, div_name, dist_name)
# Use the proper results dir structure based on the config file.
if config.LEGACY_DIRECTORY_STRUCTURE:
projresdir = os.path.join(projdir, 'results_sn')
projascdir = os.path.join(projresdir, 'asc_files')
projdssdir = os.path.join(projresdir, 'dss_files')
histdir = os.path.join(projresdir, 'history')
else:
projascdir = os.path.join(config.ASC_BASE_DIR, div_name, dist_name)
projdssdir = os.path.join(config.DSS_BASE_DIR, div_name, dist_name)
histdir = os.path.join(config.HISTORY_BASE_DIR, div_name, dist_name)
# Build our results directories if needed.
mkdir_p(projascdir)
mkdir_p(projdssdir)
mkdir_p(histdir)
dstr = datetime.datetime.now().strftime('%y%m%d%H%M%S')
ymdDate = process_date.strftime('%Y%m%d')
# Break out if processing for the given date has already happened.
histfile = os.path.join(histdir, 'proccomplete' + ymdDate + '.txt')
if os.path.isfile(histfile):
print '{0} {1} grids already processed for: {2}'.format(
div_name, dist_name, process_date.strftime('%Y.%m.%d'))
return None
print 'Processing {0} {1} grids for: {2}'.format(
div_name, dist_name, process_date.strftime('%Y.%m.%d'))
tmpdir = os.path.join(projascdir, 'tmp' + dstr)
os.mkdir(tmpdir)
# Set up a dictionary mapping the various properties to their DSS names.
PropDict = SetProps(process_date, div_name)
enameDict = {}
zerolist = ["0001", "0002", "0003"]
extentGProps = {}
maxExtent = getMaxExtent(extents_list)
dssbasename = GetDSSBaseName(process_date)
dssfile = os.path.join(projdssdir, dssbasename)
# Define our files and make sure they all exist.
snodaslist = [
s.format(ds=dataset_type, ymd=ymdDate) for s in SNODAS_FILENAME_LIST
]
# Loop through our source SNODAS files.
for f in snodaslist:
varcode = f[8:12]
varprops = PropDict[varcode]
path = "/" + "/".join(varprops[0]) + "/"
dtype = varprops[1]
easiername = \
div_name + "_" + varprops[0][2].replace(" ", "_").lower() + ymdDate
enameDict[varcode] = os.path.join(projascdir, easiername + ".asc")
shgtif = os.path.join(tmpdir, f + "alb.tif")
shgtifmath = os.path.join(tmpdir, easiername + ".tif")
src_file = os.path.join(src_dir, f + '.bil')
ReprojUseWarpBil(src_file, shgtif, maxExtent, nodata_val)
mathranokay = True
if varprops[2]:
# NOTE: enamedict populated only for prior product numbers
mathranokay = RasterMath(shgtif, shgtifmath, varcode, enameDict)
else:
shgtifmath = shgtif
if mathranokay:
enameDict[varcode] = shgtifmath
for extentarr in extents_list:
ds = gdal.Open(shgtifmath)
if ds is None:
print 'Could not open ' + shgtifmath
return None
nodata = ds.GetRasterBand(1).GetNoDataValue()
fullext = GetDatasetExtent(ds)
cellsize = ds.GetGeoTransform()[1]
subext = extentarr[1]
fullof, subof = min_box_os(fullext, subext, cellsize)
xsize = int(fullof[2])
ysize = int(fullof[3])
dsProj = ds.GetProjection()
cliparr = ds.GetRasterBand(1).ReadAsArray(
int(round(fullof[0])), int(round(fullof[1])), xsize, ysize)
outtmpname = os.path.join(tmpdir, extentarr[0] + "tmp.asc")
driver = gdal.GetDriverByName("MEM")
clipgeot = [subext[0], cellsize, 0, subext[3], 0, -cellsize]
extentGProps[extentarr[0]] = [
dsProj, clipgeot, xsize, ysize, nodata
]
clipds = driver.Create("", xsize, ysize, 1, GDT_Float32)
clipds.SetGeoTransform(clipgeot)
clipds.SetProjection(ds.GetProjection())
clipds.GetRasterBand(1).SetNoDataValue(nodata)
clipds.GetRasterBand(1).WriteArray(cliparr, 0, 0)
clipds.FlushCache()
ascbasename = extentarr[0] + "_" + \
varprops[0][2].replace(" ", "_").lower() + ymdDate
CreateASCII(clipds, ascbasename, tmpdir)
clipds = None
ds = None
tmpasc = os.path.join(tmpdir, ascbasename + ".asc")
projasc = os.path.join(projascdir, ascbasename + ".asc")
shutil.copy(tmpasc, projasc)
shutil.copy(os.path.join(tmpdir, ascbasename + "tmp.prj"),
os.path.join(projascdir, ascbasename + ".prj"))
varprops = PropDict[varcode]
p = varprops[0]
dtype = varprops[1]
path = "/SHG/" + extentarr[0].upper() + "/" + p[2] + \
"/" + p[3] + "/" + p[4] + "/" + p[5] + "/"
WriteToDSS(projasc, dssfile, dtype, path)
outarr = None
cliparr = None
if len(extentGProps) == 0:
print "An error occurred identifying extent properties."
clean_up_tmp_dir(tmpdir)
return None
for varcode in zerolist:
varprops = PropDict[varcode]
for extentarr in extents_list:
p = varprops[0]
dtype = varprops[1]
path = "/SHG/" + extentarr[0].upper() + "/" + p[2] + \
"/" + p[3] + "/" + p[4] + "/" + p[5] + "/"
ascbasename = extentarr[0] + "_" + \
varprops[0][2].replace(" ", "_").lower() + ymdDate
tmpasc = os.path.join(tmpdir, ascbasename + ".asc")
projasc = os.path.join(projascdir, ascbasename + ".asc")
WriteZeroDStoAsc(extentGProps[extentarr[0]], ascbasename, tmpdir)
shutil.copy(tmpasc, projasc)
shutil.copy(os.path.join(tmpdir, ascbasename + "tmp.prj"),
os.path.join(projascdir, ascbasename + ".prj"))
dssdunits = varprops[3]
WriteToDSS(projasc, dssfile, dtype, path, dssdunits)
clean_up_tmp_dir(tmpdir)
# Write out file to track that we've run for this day.
with open(histfile, "w") as fo:
dstr = datetime.datetime.now().strftime("%Y%m%d%H%M%S")
fo.write(process_date.strftime("%a %b %d %H:%M:%S %Y"))
fo.close
return dssfile
