def main(argv=None):
"""Load in arguments for applying neighbourhood processing when using a
mask."""
from improver.argparser import ArgParser
parser = ArgParser(
description='Apply the requested neighbourhood method via the '
'ApplyNeighbourhoodProcessingWithAMask plugin to a file '
'with one diagnostic dataset in combination with a file '
'containing one or more masks. The mask dataset may have '
'an extra dimension compared to the input diagnostic. '
'In this case, the user specifies the name of '
'the extra coordinate and this coordinate is iterated '
'over so each mask is applied to separate slices over the'
' input data. These intermediate masked datasets are then'
' concatenated, resulting in a dataset that has been '
' processed using multiple masks and has gained an extra '
'dimension from the masking. There is also an option to '
're-mask the output dataset, so that after '
'neighbourhood processing, non-zero values are only '
'present for unmasked grid points. '
'There is an alternative option of collapsing the '
'dimension that we gain using this processing using a '
'weighted average.')
parser.add_argument('coord_for_masking', metavar='COORD_FOR_MASKING',
help='Coordinate to iterate over when applying a mask '
'to the neighbourhood processing. ')
parser.add_argument('input_filepath', metavar='INPUT_FILE',
help='A path to an input NetCDF file to be processed.')
parser.add_argument('input_mask_filepath', metavar='INPUT_MASK_FILE',
help='A path to an input mask NetCDF file to be '
'used to mask the input file.')
parser.add_argument('output_filepath', metavar='OUTPUT_FILE',
help='The output path for the processed NetCDF.')
group = parser.add_mutually_exclusive_group()
group.add_argument('--radius', metavar='RADIUS', type=float,
help='The radius (in m) for neighbourhood processing.')
group.add_argument('--radii-by-lead-time',
metavar=('RADII_BY_LEAD_TIME', 'LEAD_TIME_IN_HOURS'),
nargs=2,
help='The radii for neighbourhood processing '
'and the associated lead times at which the radii are '
'valid. The radii are in metres whilst the lead time '
'has units of hours. The radii and lead times are '
'expected as individual comma-separated lists with '
'the list of radii given first followed by a list of '
'lead times to indicate at what lead time each radii '
'should be used. For example: 10000,12000,14000 1,2,3 '
'where a lead time of 1 hour uses a radius of 10000m, '
'a lead time of 2 hours uses a radius of 12000m, etc.')
parser.add_argument('--sum_or_fraction', default="fraction",
choices=["sum", "fraction"],
help='The neighbourhood output can either be in the '
'form of a sum of the neighbourhood, or a '
'fraction calculated by dividing the sum of the '
'neighbourhood by the neighbourhood area. '
'"fraction" is the default option.')
group2 = parser.add_mutually_exclusive_group()
group2.add_argument('--re_mask', action='store_true',
help='If re_mask is set (i.e. True), the output data '
'following neighbourhood processing is '
're-masked. This re-masking removes any values '
'that have been generated by neighbourhood '
'processing at grid points that were '
'originally masked. '
'If not set, re_mask defaults to False and no '
're-masking is applied to the neighbourhood '
'processed output. Therefore, the neighbourhood '
'processing may result in values being present '
'in areas that were originally masked. This '
'allows the the values in adjacent bands to be'
'weighted together if the additional dimension'
'from the masking process is collapsed.')
group2.add_argument('--collapse_dimension', action='store_true',
help='Collapse the dimension from the mask, by doing '
'a weighted mean using the weights provided. '
'This is only suitable when the result is is '
'left unmasked, so there is data to weight '
'between the points in coordinate we are '
'collapsing.')
parser.add_argument('--weights_for_collapsing_dim', metavar='WEIGHTS',
default=None,
help='A path to an weights NetCDF file containing the '
'weights which are used for collapsing the '
'dimension gained through masking.')
parser.add_argument('--intermediate_filepath', default=None,
help='If provided the result after neighbourhooding, '
'before collapsing the extra dimension is saved '
'in the given filepath.')
args = parser.parse_args(args=argv)
# Load Cubes
cube = cli.inputcube(args.input_filepath)
mask_cube = cli.inputcube(args.input_mask_filepath)
weights = cli.inputcube(args.weights_for_collapsing_dim) if \
args.collapse_dimension else None
# Process Cube
# pylint: disable=E1123
process(cube, mask_cube, weights, coord_for_masking=args.coord_for_masking,
radius=args.radius, radii_by_lead_time=args.radii_by_lead_time,
sum_or_fraction=args.sum_or_fraction, remask=args.re_mask,
collapse_dimension=args.collapse_dimension,
output=args.output_filepath,
intermediate_output=args.intermediate_filepath)
def test_basic(self, m):
"""Tests that input cube calls load_cube with the string"""
result = inputcube("foo")
m.assert_called_with(improver.utilities.load.load_cube, "foo")
self.assertEqual(result, 'return')
def main(argv=None):
"""Load in arguments for the cube combiner plugin.
"""
from improver.argparser import ArgParser
parser = ArgParser(
description="Combine the input files into a single file using "
"the requested operation e.g. + - min max etc.")
parser.add_argument("input_filenames",
metavar="INPUT_FILENAMES",
nargs="+",
type=str,
help="Paths to the input NetCDF files. Each input"
" file should be able to be loaded as a single "
" iris.cube.Cube instance. The resulting file"
" metadata will be based on the first file but"
" its metadata can be overwritten via"
" the metadata_jsonfile option.")
parser.add_argument("output_filepath",
metavar="OUTPUT_FILE",
help="The output path for the processed NetCDF.")
parser.add_argument("--operation",
metavar="OPERATION",
default="+",
choices=[
"+", "-", "*", "add", "subtract", "multiply",
"min", "max", "mean"
],
help="Operation to use in combining NetCDF datasets"
" Default=+ i.e. add ",
type=str)
parser.add_argument("--new-name",
metavar="NEW_NAME",
default=None,
help="New name for the resulting dataset. Will"
" default to the name of the first dataset if "
"not set.",
type=str)
parser.add_argument("--metadata_jsonfile",
metavar="METADATA_JSONFILE",
default=None,
help="Filename for the json file containing "
"required changes to the metadata. "
" default=None",
type=str)
parser.add_argument('--warnings_on',
action='store_true',
help="If warnings_on is set (i.e. True), "
"Warning messages where metadata do not match "
"will be given. Default=False",
default=False)
args = parser.parse_args(args=argv)
new_metadata = cli.inputjson(args.metadata_jsonfile)
# Load cubes
cubelist = []
new_cube_name = args.new_name
for filename in args.input_filenames:
new_cube = cli.inputcube(filename)
cubelist.append(new_cube)
if new_cube_name is None:
new_cube_name = new_cube.name()
if args.warnings_on:
if (args.new_name is None and new_cube_name != new_cube.name()):
msg = ("Defaulting to first cube name, {} but combining with"
"a cube with name, {}.".format(new_cube_name,
new_cube.name()))
warnings.warn(msg)
# Process Cube
# pylint: disable=E1123
process(*cubelist,
operation=args.operation,
new_name=new_cube_name,
new_metadata=new_metadata,
warnings_on=args.warnings_on,
output=args.output_filepath)
