def loadmat(save_file, base_dir, grid_dir, save_dir, basis_dir):
"""
Loads data from ``save_file`` into a
:class:`~polyadcirc.run_framwork.random_manningsn.runSet` object.
Reconstructs :class:`~polyadcirc.run_framwork.random_manningsn.subdomain`.
:param string save_file: local file name
:param string grid_dir: directory containing ``fort.14``, ``fort.15``, and
``fort.22``
:param string save_dir: directory where ``RF_directory_*`` are
saved, and where fort.13 is located
:param string basis_dir: directory where ``landuse_*`` folders are located
:param string base_dir: directory that contains ADCIRC executables, and
machine specific ``in.prep#`` files
:rtype: tuple of :class:`~polyadcirc.run_framwork.random_manningsn.runSet`
and :class:`~polyadcirc.run_framwork.random_manningsn.domain` objects
:returns: (main_run, domain)
"""
# the lines below are only necessary if you need to update what the
# directories are when swithcing from euclid to your desktop/laptop
# assumes that the landuse directory and ADCIRC_landuse directory are in
# the same directory
domain = subdomain(grid_dir)
domain.update()
domain.get_Triangulation()
#domain.set_station_bathymetry()
main_run = rmn.runSet(grid_dir, save_dir, basis_dir, base_dir=base_dir)
main_run.ts_error = {}
main_run.nts_error = {}
main_run.time_obs = {}
# load the data from at *.mat file
mdat = sio.loadmat(os.path.join(save_dir, save_file))
for k, v in mdat.iteritems():
skey = k.split('_')
if skey[-1] == 'time':
# check to see if the key is "*_time"
main_run.time_obs[skey[0]] = v
elif f15.filetype.has_key(skey[0]):
if not re.match('fort', skey[0]):
# check to see if key is nts_data
main_run.nts_error[skey[0]] = v
else:
# check to see if key is ts_data
main_run.ts_error[skey[0]] = v
#print k, v
return (main_run, domain)
def loadmat(save_file, base_dir, grid_dir, save_dir, basis_dir):
"""
Loads data from ``save_file`` into a
:class:`~polyadcirc.run_framwork.random_manningsn.runSet` object.
Reconstructs :class:`~polyadcirc.run_framwork.random_manningsn.subdomain`.
:param string save_file: local file name
:param string grid_dir: directory containing ``fort.14``, ``fort.15``, and
``fort.22``
:param string save_dir: directory where ``RF_directory_*`` are
saved, and where fort.13 is located
:param string basis_dir: directory where ``landuse_*`` folders are located
:param string base_dir: directory that contains ADCIRC executables, and
machine specific ``in.prep#`` files
:rtype: tuple of :class:`~polyadcirc.run_framwork.random_manningsn.runSet`
and :class:`~polyadcirc.run_framwork.random_manningsn.domain` objects
:returns: (main_run, domain)
"""
# the lines below are only necessary if you need to update what the
# directories are when swithcing from euclid to your desktop/laptop
# assumes that the landuse directory and ADCIRC_landuse directory are in
# the same directory
domain = subdomain(grid_dir)
domain.update()
domain.get_Triangulation()
#domain.set_station_bathymetry()
main_run = rmn.runSet(grid_dir, save_dir, basis_dir, base_dir=base_dir)
main_run.ts_error = {}
main_run.nts_error = {}
main_run.time_obs = {}
# load the data from at *.mat file
mdat = sio.loadmat(os.path.join(save_dir, save_file))
for k, v in mdat.iteritems():
skey = k.split('_')
if skey[-1] == 'time':
# check to see if the key is "*_time"
main_run.time_obs[skey[0]] = v
elif f15.filetype.has_key(skey[0]):
if not re.match('fort', skey[0]):
# check to see if key is nts_data
main_run.nts_error[skey[0]] = v
else:
# check to see if key is ts_data
main_run.ts_error[skey[0]] = v
#print k, v
return (main_run, domain)
nontimeseries_files = ["tinun.63", "maxvel.63"]
# NoNx12/TpN where NoN is number of nodes and TpN is tasks per node, 12 is the
# number of cores per node See -pe line in submission_script <TpN>way<NoN x
# 12>
nprocs = 2 # number of processors per PADCIRC run
ppnode = 12
NoN = 2
num_of_parallel_runs = (ppnode * NoN) / nprocs # procs_pnode * NoN / nproc
domain = dom.domain(grid_dir)
domain.update()
main_run = rmn.runSet(grid_dir,
save_dir,
basis_dir,
num_of_parallel_runs,
base_dir=adcirc_dir,
script_name=script)
main_run.initialize_random_field_directories(num_procs=nprocs)
# Set samples
lam_domain = np.array([[.02, .2], [.02, .2], [.02, .2]])
lam1 = np.linspace(lam_domain[0, 0], lam_domain[0, 1], 3)
lam2 = np.linspace(lam_domain[1, 0], lam_domain[1, 1], 3)
lam3 = np.linspace(lam_domain[2, 0], lam_domain[2, 1], 3)
lam4 = 0.02
lam1, lam2, lam3, lam4 = np.meshgrid(lam1, lam2, lam3, lam4)
lam_samples = np.column_stack(
(lam1.ravel(), lam2.ravel(), lam3.ravel(), lam4.ravel()))
mann_pts = lam_samples.transpose()
save_file = "py_save_file" timeseries_files = ["fort.61", "fort.63", "fort.62", "fort.64"] nontimeseries_files = ["tinun.63", "maxvel.63"] # NoNx12/TpN where NoN is number of nodes and TpN is tasks per node, 12 is the # number of cores per node See -pe line in submission_script <TpN>way<NoN x # 12> nprocs = 2 # number of processors per PADCIRC run ppnode = 12 NoN = 2 num_of_parallel_runs = (ppnode * NoN) / nprocs # procs_pnode * NoN / nproc domain = dom.domain(grid_dir) domain.update() main_run = rmn.runSet(grid_dir, save_dir, basis_dir, num_of_parallel_runs, base_dir=adcirc_dir, script_name=script) main_run.initialize_random_field_directories(num_procs=nprocs) # Set samples lam_domain = np.array([[0.02, 0.2], [0.02, 0.2], [0.02, 0.2]]) lam1 = np.linspace(lam_domain[0, 0], lam_domain[0, 1], 3) lam2 = np.linspace(lam_domain[1, 0], lam_domain[1, 1], 3) lam3 = np.linspace(lam_domain[2, 0], lam_domain[2, 1], 3) lam4 = 0.02 lam1, lam2, lam3, lam4 = np.meshgrid(lam1, lam2, lam3, lam4) lam_samples = np.column_stack((lam1.ravel(), lam2.ravel(), lam3.ravel(), lam4.ravel())) mann_pts = lam_samples.transpose() # Run experiments
