def msg_mpe_10dcum(input_file, output_file):
if len(input_file) > 8:
output_file = functions.list_to_element(output_file)
# Get the number of days of that dekad
basename = os.path.basename(output_file)
mydate = functions.get_date_from_path_filename(basename)
nbr_days_dekad = functions.day_per_dekad(mydate)
factor = 1.0
functions.check_output_dir(os.path.dirname(output_file))
args = {
"input_file": input_file,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw",
"scale_factor": factor,
"input_nodata": -32768
}
raster_image_math.do_cumulate(**args)
else:
logger.warning(
'More than 2 files missing for output {0}: Skip'.format(
os.path.basename(output_file)))
def test_do_cumulate(self):
# 1moncum
output_filename = 'fewsnet-rfe/1moncum/20200301_fewsnet-rfe_1moncum_FEWSNET-Africa-8km_2.0.tif'
output_file = os.path.join(self.root_out_dir, output_filename)
ref_file = os.path.join(self.ref_dir, output_filename)
functions.check_output_dir(os.path.dirname(output_file))
input_files = [
self.ref_dir +
'/fewsnet-rfe/10d/20200321_fewsnet-rfe_10d_FEWSNET-Africa-8km_2.0.tif',
self.ref_dir +
'/fewsnet-rfe/10d/20200311_fewsnet-rfe_10d_FEWSNET-Africa-8km_2.0.tif',
self.ref_dir +
'/fewsnet-rfe/10d/20200301_fewsnet-rfe_10d_FEWSNET-Africa-8km_2.0.tif',
]
args = {
"input_file": input_files,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw",
'output_type': 'Float32',
'input_nodata': -32767
}
raster_image_math.do_cumulate(**args)
equal = self.checkFile(ref_file, output_file)
self.assertEqual(equal, 1)
def msg_mpe_1dcum(input_file, output_file):
#
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
tmpdir = tempfile.mkdtemp(prefix=__name__,
suffix='',
dir=es_constants.base_tmp_dir)
tmp_output_file = tmpdir + os.path.sep + os.path.basename(output_file)
# Divide by 10 to pass from 0.01 to 0.1 as scale factor for 1d cum
factor = 0.1
args = {
"input_file": input_file,
"output_file": tmp_output_file,
"output_format": 'GTIFF',
"options": "compress=lzw",
"scale_factor": factor,
"input_nodata": -32768
}
raster_image_math.do_cumulate(**args)
reproject_output(tmp_output_file, native_mapset, target_mapset)
# Copy the non-reprojected file for validation, only in test_mode
if test_mode:
msg_proj_dir = es_constants.processing_dir + functions.set_path_sub_directory(
prod, '1dcum', 'Derived', version, native_mapset)
functions.check_output_dir(msg_proj_dir)
shutil.copy(tmp_output_file, msg_proj_dir + os.path.sep)
# Copy the non-reprojected file for validation, only in test_mode
shutil.rmtree(tmpdir)
def cum(input_files, output_file):
# Ensure out subdirectory exists
functions.check_output_dir(os.path.dirname(output_file))
# If output_file it is a list, force to a string
output_file = functions.list_to_element(output_file)
# Prepare temporary working directory for intermediate results
tmpdirpath = tempfile.mkdtemp()
# Cumulated but not masked output
tmp_output_file = tmpdirpath + os.path.sep + os.path.basename(
output_file)
# Call the function for cumulating
args = {
"input_file": input_files,
"output_file": tmp_output_file,
"output_format": 'GTIFF',
"options": "compress=lzw"
}
raster_image_math.do_cumulate(**args)
# Create from the original mask a new one, by using raster_image_math.do_reprojection()
# and save it as a temporary mask
# raster_image_math.do_reproject(agriculture_mask, tmp_reproj_file, 'SPOTV-SADC-1km', mapset)
raster_image_math.do_reproject(tmp_output_file, output_file,
native_mapset, mapset)
# Remove temp directory
shutil.rmtree(tmpdirpath)
def std_precip_1yearcum(input_file, output_file):
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {"input_file": input_file, "output_file": output_file, "output_format": 'GTIFF', "options": "compress=lzw",\
"scale_factor":scale_factor_conv}
raster_image_math.do_cumulate(**args)
def std_precip_10dmeas(input_file, output_file):
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
# Prepare temporary working directory for intermediate results
tmpdirpath = tempfile.mkdtemp()
# Cumulated but not masked output
tmp_output_file = tmpdirpath + os.path.sep + os.path.basename(
output_file)
# Call the function for cumulating
args = {
"input_file": input_file,
"output_file": tmp_output_file,
"output_format": 'GTIFF',
"options": "compress=lzw"
}
raster_image_math.do_cumulate(**args)
# Call the function for masking
args = {
"input_file": tmp_output_file,
"mask_file": land_mask,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw",
"mask_value": 0,
"out_value": 0
}
raster_image_math.do_mask_image(**args)
# Remove temp directory
shutil.rmtree(tmpdirpath)
def lsasaf_etp_10dcum(input_file, output_file):
output_file = functions.list_to_element(output_file)
# Get the number of days of that dekad
basename=os.path.basename(output_file)
mydate=functions.get_date_from_path_filename(basename)
nbr_days_dekad = functions.day_per_dekad(mydate)
# Compute the correcting factor: we sum-up all 48 30min cycles and:
# Divide by 2 (mm/h -> mm)
# Multiply by number of days
# Divide by 100, so that the scale factor changes from 0.0001 (30min) to 0.01
factor = float(nbr_days_dekad)*0.005
functions.check_output_dir(os.path.dirname(output_file))
tmpdir = tempfile.mkdtemp(prefix=__name__, suffix='',dir=es_constants.base_tmp_dir)
tmp_output_file = tmpdir+os.path.sep+os.path.basename(output_file)
args = {"input_file": input_file, "output_file": tmp_output_file, "output_format": 'GTIFF',
"options": "compress=lzw", "scale_factor": factor, "input_nodata":-32768}
# See ES2-416: we accept at least 40 files out of the expect 48
if len(input_file) >= 40:
raster_image_math.do_cumulate(**args)
reproject_output(tmp_output_file, native_mapset, target_mapset)
# Do also the house-keeping, by deleting the files older than 6 months
number_months_keep = 6
remove_old_files(prod, "10d30min-et", version, native_mapset, 'Derived', number_months_keep)
# Remove tmp dir (moved out of if-clause - 21.11.19)
shutil.rmtree(tmpdir)
def lsasaf_etp_1moncum(input_file, output_file):
#
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {"input_file": input_file, "output_file": output_file, "output_format": 'GTIFF',
"options": "compress=lzw", "input_nodata":-32768}
# See ES2-416: we need all 3 files for the monthly cumulate
if len(input_file) >= 3:
raster_image_math.do_cumulate(**args)
def std_precip_10dcount(input_file, output_file):
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {
"input_file": input_file,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw"
}
raster_image_math.do_cumulate(**args)
def lsasaf_etp_1moncum(input_file, output_file):
#
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {
"input_file": input_file,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw",
"input_nodata": -32768
}
raster_image_math.do_cumulate(**args)
def std_precip_1moncum(input_file, output_file):
#ES2- 235 Do not show temporary products like composite not complete (ex monthly composite available mid month...)
# ex: monthly RFE in the middle of the month should not be available because incomplete and lead to wrong analysis...
# Check current month ---> yes ---> skip
# ----> NO ---> Check No of days (10% tolerance)
# acceptable ---->
# Yes ---> proceed
# No ----> Skip
input_file_date = functions.get_date_from_path_full(input_file[0])
if len(input_file) == 3:
if not functions.is_date_current_month(input_file_date):
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {
"input_file": input_file,
"output_file": output_file,
"output_format": 'GTIFF',
"options": "compress=lzw"
}
raster_image_math.do_cumulate(**args)
def std_precip_1moncum(input_file, output_file):
output_file = functions.list_to_element(output_file)
functions.check_output_dir(os.path.dirname(output_file))
args = {"input_file": input_file,"output_file": output_file, "output_format": 'GTIFF', "options": "compress=lzw"}
raster_image_math.do_cumulate(**args)
