def init(args: Optional[argparse.Namespace] = None):
"""Initialize a simulation and read configuration.
Attributes
----------
args : None or argparse.Namespace
By default, None means getting arguments from command-line. If not None, it should be the
return from ArgumentParser.parse().
Returns:
--------
config : a torchswe.utils.config.Config
A Config instance holding a case's simulation configurations. All paths are converted to
absolute paths. The temporal scheme is replaced with the corresponding function.
grid : torch.utils.data.Gridlines
Contains gridline coordinates.
topo : torch.utils.data.Topography
Contains topography elevation data.
state_ic : torchswe.utils.data.WHUHVModel
Initial confitions.
"""
# get cmd arguments
if args is None:
args = get_cmd_arguments()
args.case_folder = args.case_folder.expanduser().resolve()
args.yaml = args.case_folder.joinpath("config.yaml")
# read yaml config file
with open(args.yaml, "r") as fobj:
config = yaml.load(fobj, yaml.Loader)
assert isinstance(config, Config), \
"Failed to parse {} as an Config object. ".format(args.yaml) + \
"Check if `--- !Config` appears in the header of the YAML"
# add args to config
config.case = args.case_folder
config.dtype = "float32" if args.sp else "float64"
if args.log_steps is not None:
config.params.log_steps = args.log_steps
if args.tm is not None: # overwrite the setting in config.yaml
config.temporal.scheme = args.tm
# if topo filepath is relative, change to abs path
config.topo.file = config.topo.file.expanduser()
if not config.topo.file.is_absolute():
config.topo.file = config.case.joinpath(config.topo.file).resolve()
# if ic filepath is relative, change to abs path
if config.ic.file is not None:
config.ic.file = config.ic.file.expanduser()
if not config.ic.file.is_absolute():
config.ic.file = config.case.joinpath(config.ic.file).resolve()
# if filepath of the prehook script is relative, change to abs path
if config.prehook is not None:
config.prehook = config.prehook.expanduser()
if not config.prehook.is_absolute():
config.prehook = config.case.joinpath(config.prehook).resolve()
# spatial discretization + output time values
grid = get_gridlines(
*config.spatial.discretization, *config.spatial.domain,
get_snapshot_times(config.temporal.output[0],
config.temporal.output[1:], config.temporal.dt),
config.dtype)
# topography
topo = get_topography(config.topo.file, config.topo.key, grid.x.vert,
grid.y.vert, config.dtype)
# initial conditions
state_ic = create_ic(config.ic, grid, topo, config.dtype)
return config, grid, topo, state_ic
import numpy
from torchswe.utils.data import get_gridlines
from torchswe.utils.io import create_topography_file
def main():
"""Main function"""
# pylint: disable=invalid-name
case = pathlib.Path(__file__).expanduser().resolve().parent
with open(case.joinpath("config.yaml"), 'r') as f:
config = yaml.load(f, Loader=yaml.Loader)
# gridlines; ignore temporal axis
grid = get_gridlines(*config.spatial.discretization,
*config.spatial.domain, [], config.dtype)
# topography, defined on cell vertices
B = numpy.tile(5. * numpy.exp(-0.4 * ((grid.x.vert - 5.)**2)),
(grid.y.n + 1, 1))
create_topography_file(case.joinpath(config.topo.file),
[grid.x.vert, grid.y.vert], B)
return 0
if __name__ == "__main__":
import sys
sys.exit(main())
