def main(args, logger: Logger = get_basic_logger()):
params = utils.load_sim_params(os.path.join(args.rel_dir, "sim_params.yaml"))
sim_dir = params.sim_dir
mgmt_db_loc = params.mgmt_db_location
submit_yes = True if args.auto else confirm("Also submit the job for you?")
# get the srf(rup) name without extensions
srf_name = os.path.splitext(os.path.basename(params.srf_file))[0]
# if srf(variation) is provided as args, only create the slurm
# with same name provided
if args.srf is not None and srf_name != args.srf:
return
write_directory = args.write_directory if args.write_directory else sim_dir
# get lf_sim_dir
lf_sim_dir = os.path.join(sim_dir, "LF")
header_dict = {
"platform_specific_args": get_platform_node_requirements(
platform_config[const.PLATFORM_CONFIG.MERGE_TS_DEFAULT_NCORES.name]
),
"wallclock_limit": default_run_time_merge_ts,
"job_name": "merge_ts.{}".format(srf_name),
"job_description": "post emod3d: merge_ts",
"additional_lines": "###SBATCH -C avx",
}
command_template_parameters = {
"run_command": platform_config[const.PLATFORM_CONFIG.RUN_COMMAND.name],
"merge_ts_path": binary_version.get_unversioned_bin(
"merge_tsP3_par", get_machine_config(args.machine)["tools_dir"]
),
}
body_template_params = (
"{}.sl.template".format(merge_ts_name_prefix),
{"lf_sim_dir": lf_sim_dir},
)
script_prefix = "{}_{}".format(merge_ts_name_prefix, srf_name)
script_file_path = write_sl_script(
write_directory,
sim_dir,
const.ProcessType.merge_ts,
script_prefix,
header_dict,
body_template_params,
command_template_parameters,
)
if submit_yes:
submit_script_to_scheduler(
script_file_path,
const.ProcessType.merge_ts.value,
sim_struct.get_mgmt_db_queue(mgmt_db_loc),
sim_dir,
srf_name,
target_machine=args.machine,
logger=logger,
)
def gp2ll_multi(coords, mlat, mlon, rot, nx, ny, hh):
"""
Converts gridpoint positions to longitude, latitude.
coords: 2d list in format [[x0, y0], [x1, y1], ...]
"""
# derived parameters
xlen = nx * hh
ylen = ny * hh
# where the x plane points
xazim = (rot + 90) % 360
# convert gridpoint to offset km
max_x = (nx - 1) * hh
max_y = (ny - 1) * hh
for c in coords:
# length from corner
c[0] *= hh
c[1] *= hh
# length from centre origin
c[0] -= max_x * 0.5
c[1] -= max_y * 0.5
# run binary, get output
p_conv = Popen(
[
get_unversioned_bin("xy2ll"),
"mlat=%s" % (mlat),
"mlon=%s" % (mlon),
"geoproj=1",
"center_origin=1",
"h=%s" % (hh),
"xazim=%s" % (xazim),
"xlen=%s" % (xlen),
"ylen=%s" % (ylen),
],
stdin=PIPE,
stdout=PIPE,
)
stdout = p_conv.communicate("\n".join(["%s %s" % tuple(c) for c in coords
]).encode())[0].decode()
# lon, lat
return [
list(map(float, line.split())) for line in stdout.rstrip().split("\n")
]
def srf2llv(srf, seg=-1, value="slip", lonlatdep=True, depth=False):
"""
Get longitude, latitude, depth (optional) and value of 'type'
srf: filepath of SRF file
seg: which segmentsto read (-1 for all)
type: which parameter to read
depth: whether to also include depth at point
"""
proc = Popen(
[
get_unversioned_bin("srf2xyz"),
"calc_xy=0",
"lonlatdep=%d" % (lonlatdep),
"dump_slip=0",
"infile=%s" % (srf),
"type=%s" % (value),
"nseg=%d" % (seg),
],
stdout=PIPE,
)
out, err = proc.communicate()
code = proc.wait()
# process output
llv = np.fromstring(out, dtype="f4", sep=" ")
# create a slice filter if depth not wanted
# longitude, latitude, depth, value
if not depth:
mask = np.array([True, True, False, True])
else:
mask = np.array([True, True, True, True])
if lonlatdep:
# output from srf2xyz is 4 columns wide
return np.reshape(llv, (len(llv) // 4, 4))[:, mask]
return np.reshape(llv, (len(llv) // 3, 3))
def ll2gp_multi(
coords,
mlon,
mlat,
rot,
nx,
ny,
hh,
dx=1,
dy=1,
decimated=False,
verbose=False,
keep_outside=False,
):
"""
Converts longitude/latitude positions to gridpoints.
Three main modes of operation:
1: No dx, dy (= 1): gridpoint
2: dx or dy != 1: closest gridpoint considering dx/dy
3: decimated: gridpoint number if only decimated points existed
coords: 2d list in format [[lon0, lat0], [lon1, lat1], ...]
keep_outside: False will remove values outside the sim domain,
True will replace those entries with None
"""
# derived parameters
xlen = nx * hh
ylen = ny * hh
# where the x plane points
xazim = (rot + 90) % 360
# run binary, get output
# output is displacement (x, y) from center, in kilometres
cmd = [
get_unversioned_bin("ll2xy"),
"mlat=%s" % (mlat),
"mlon=%s" % (mlon),
"geoproj=1",
"center_origin=1",
"h=%s" % (hh),
"xazim=%s" % (xazim),
"xlen=%s" % (xlen),
"ylen=%s" % (ylen),
]
if verbose:
print(" ".join(cmd))
# Has to be a byte string
p_conv = Popen(cmd, stdin=PIPE, stdout=PIPE)
stdout = p_conv.communicate("\n".join(["%s %s" % tuple(c) for c in coords
]).encode())[0].decode()
xy = [
list(map(float, line.split())) for line in stdout.rstrip().split("\n")
]
# convert displacement to grid points
# has to be 'nx - 1', because the first gridpoint is offset 0km
# nx = 1400 means the greatest offset is 1399 * hh km
mid_x = (nx - 1) * hh * 0.5
mid_y = (ny - 1) * hh * 0.5
for i, c in enumerate(xy[::-1]):
# make the distance relative to top corner
# convert back to grid spacing
# gridpoints are discrete
c[0] = int(round((c[0] + mid_x) / hh))
c[1] = int(round((c[1] + mid_y) / hh))
# x values range from 0 -> nx - 1
if not (0 <= c[0] < nx and 0 <= c[1] < ny):
if keep_outside:
xy[-(i + 1)] = None
else:
# this is why xy is looped in reverse
xy.remove(c)
continue
if decimated:
c[0] //= dx
c[1] //= dy
else:
# closest gridpoint considering decimation
c[0] -= c[0] % dx
c[1] -= c[1] % dy
return xy