def read_and_save_output(self, ts_names, nts_names, save_file=None,
timesteps=None, save=False):
"""
Reads in output files from this fulldomain and saves to a file.
NOTE THIS DOES NOT CURRENTLY WORK FOR STATION DATA! ONLY USE FOR GLOBAL
DATA i.e files that are fort.*3 or fort.*4
NOTE THIS DOES NOT CURRENTLY WORK FOR ANY NTS DATA EXCEPT FOR MAXELE
:param list ts_names: names of ADCIRC timeseries
output files to be recorded from each run
:param list nts_names: names of ADCIRC non timeseries
output files to be recorded from each run
:param string save_file: name of file to save comparision matricies to
:param int timesteps: number of timesteps to read from file
:rtype: dict
:returns: full_dict
"""
if save_file is None:
save_file = os.path.join(self.path, 'full.mat')
fulldict = dict()
# Get nts_error
for fid in nts_names:
key = fid.replace('.', '')
fulldict[key] = output.get_nts_sr(self.path, self, fid)
# Get ts_data
for fid in ts_names:
key = fid.replace('.', '')
fulldict[key] = output.get_ts_sr(self.path,
fid, timesteps=timesteps,
ihot=self.ihot)[0]
# fix dry nodes
if fulldict.has_key('fort63'):
fulldict['fort63'] = np.expand_dims(fulldict['fort63'], axis=2)
fulldict = rmn.fix_dry_nodes(fulldict, self)
fulldict['fort63'] = np.squeeze(fulldict['fort63'])
# fix dry data
if fulldict.has_key('fort61'):
fulldict['fort61'] = np.expand_dims(fulldict['fort61'], axis=1)
fulldict = rmn.fix_dry_data(fulldict, self)
fulldict['fort61'] = np.squeeze(fulldict['fort61'])
# fix dry nodes nts
if fulldict.has_key('maxele63'):
fulldict['maxele63'] = np.expand_dims(fulldict['maxele63'], axis=1)
fulldict = rmn.fix_dry_nodes_nts(fulldict, self)
fulldict['maxele63'] = np.squeeze(fulldict['maxele63'])
if save:
sio.savemat(save_file, fulldict, do_compression=True)
return fulldict
def compare_to_fulldomain(self,
ts_names,
nts_names,
save_file=None,
timesteps=None,
savefull=True,
readmatfull=False,
savesub=True,
readmatsub=False,
fulldict=None):
"""
Reads in output files from this subdomain and from it's fulldomain and
compares them.
NOTE THIS DOES NOT CURRENTLY WORK FOR STATION DATA! ONLY USE FOR GLOBAL
DATA i.e files that are fort.*3 or fort.*4
NOTE THIS DOES NOT CURRENTLY WORK FOR ANY NTS DATA EXCEPT FOR MAXELE
comparision_data = fulldomain_data - subdomain_data
:param list ts_names: names of ADCIRC timeseries
output files to be recorded from each run
:param list nts_names: names of ADCIRC non timeseries
output files to be recorded from each run
:param string save_file: name of file to save comparision matricies to
:param int timesteps: number of timesteps to read from file
:rtype: tuple
:returns: (ts_error, nts_error, time_obs, ts_data, nts_data)
"""
if save_file is None:
save_file = os.path.join(self.path, 'compare_s2f.mat')
full_file = os.path.join(self.fulldomain.path, 'full.mat')
sub_file = os.path.join(self.path, 'sub.mat')
# Save matricies to *.mat file for use by MATLAB or Python
mdict = dict()
if readmatsub:
subdict = sio.loadmat(sub_file)
savesub = False
else:
subdict = dict()
if fulldict is None:
if readmatfull:
fulldict = sio.loadmat(full_file)
savefull = False
else:
fulldict = dict()
else:
readmatfull = True
savefull = False
# Pre-allocate arrays for non-timeseries data
nts_error = {}
ts_error = {}
time_obs = {}
fulldom_nodes = [v - 1 for v in self.sub2full_node.values()]
# Get nts_data
for fid in nts_names:
key = fid.replace('.', '')
if not readmatfull:
fulldict[key] = output.get_nts_sr(self.fulldomain.path,
self.fulldomain, fid)
if not readmatsub:
subdict[key] = output.get_nts_sr(self.path, self, fid)
# Get ts_data
for fid in ts_names:
key = fid.replace('.', '')
if not readmatsub:
subdict[key], time_obs[key] = output.get_ts_sr(self.path,
fid,
True,
ihot=self.ihot)
subdict[key + '_time'] = time_obs[key]
if not readmatfull:
fulldict[key] = output.get_ts_sr(self.fulldomain.path,
fid,
timesteps=timesteps,
ihot=self.fulldomain.ihot)[0]
if not readmatsub:
# fix dry nodes
if subdict.has_key('fort63'):
subdict['fort63'] = np.expand_dims(subdict['fort63'], axis=2)
subdict = rmn.fix_dry_nodes(subdict, self)
subdict['fort63'] = np.squeeze(subdict['fort63'])
# fix dry data
if subdict.has_key('fort61'):
subdict['fort61'] = np.expand_dims(subdict['fort61'], axis=1)
subdict = rmn.fix_dry_data(subdict, self)
subdict['fort61'] = np.squeeze(subdict['fort61'])
# fix dry nodes nts
if subdict.has_key('maxele63'):
subdict['maxele63'] = np.expand_dims(subdict['maxele63'],
axis=1)
subdict = rmn.fix_dry_nodes_nts(subdict, self)
subdict['maxele63'] = np.squeeze(subdict['maxele63'])
if not readmatfull:
# fix dry nodes
if fulldict.has_key('fort63'):
fulldict['fort63'] = np.expand_dims(fulldict['fort63'], axis=2)
fulldict = rmn.fix_dry_nodes(fulldict, self)
fulldict['fort63'] = np.squeeze(fulldict['fort63'])
# fix dry data
if fulldict.has_key('fort61'):
fulldict['fort61'] = np.expand_dims(fulldict['fort61'], axis=1)
fulldict = rmn.fix_dry_data(fulldict, self)
fulldict['fort61'] = np.squeeze(fulldict['fort61'])
# fix dry nodes nts
if fulldict.has_key('maxele63'):
fulldict['maxele63'] = np.expand_dims(fulldict['maxele63'],
axis=1)
fulldict = rmn.fix_dry_nodes_nts(fulldict, self)
fulldict['maxele63'] = np.squeeze(fulldict['maxele63'])
# Get ts_error
for fid in ts_names:
key = fid.replace('.', '')
sub_data, time_obs[key] = subdict[key], subdict[key + '_time']
total_obs = sub_data.shape[1]
if timesteps and timesteps < total_obs:
total_obs = timesteps
full_data = fulldict[key]
if self.recording[key][2] == 1:
full_data = full_data[fulldom_nodes, 0:total_obs]
else:
full_data = full_data[fulldom_nodes, 0:total_obs, :]
ts_error[key] = (full_data - sub_data)
if key == 'fort63' and (subdict.has_key('maxele63') or\
subdict.has_key('maxele.63')):
nts_error['maxele63'] = np.max(full_data,
axis=1) - subdict['maxele63']
if key == 'fort64' and (subdict.has_key('maxvel63') or\
subdict.has_key('maxvel.63')):
nts_error['maxvel63'] = np.max(
np.sqrt(full_data[:, :, 0]**2 + full_data[:, :, 1]**2),
axis=1) - subdict['maxvel63']
# Get nts_error
for fid in nts_names:
key = fid.replace('.', '')
if key != 'maxele63' and key != 'maxevel63':
nts_error[key] = fulldict[key][fulldom_nodes] - subdict[key]
# Update and save
# export nontimeseries data
for k, v in nts_error.iteritems():
mdict[k] = v
print k
#b = np.ma.fix_invalid(v, fill_value=0)
b = v
print np.max(abs(b)), np.argmax(abs(b))
print "Nodes above threshold", sum(np.abs(b) > 1e-2)
# export timeseries data
for k, v in ts_error.iteritems():
mdict[k] = v
print k
#b = np.ma.fix_invalid(v, fill_value=0)
b = v
print np.max(abs(b)), np.argmax(abs(b))
print "Nodes above threshold", sum(np.abs(b) > 1e-2)
# export time_obs data
for k, v in time_obs.iteritems():
mdict[k + '_time'] = v
sio.savemat(save_file, mdict, do_compression=True)
if savesub:
sio.savemat(sub_file, subdict, do_compression=True)
if savefull:
sio.savemat(full_file, fulldict, do_compression=True)
return (ts_error, nts_error, time_obs, None, None)
def compare_to_fulldomain(self, ts_names, nts_names, save_file=None,
timesteps=None, savefull=True, readmatfull=False,
savesub=True, readmatsub=False, fulldict=None):
"""
Reads in output files from this subdomain and from it's fulldomain and
compares them.
NOTE THIS DOES NOT CURRENTLY WORK FOR STATION DATA! ONLY USE FOR GLOBAL
DATA i.e files that are fort.*3 or fort.*4
NOTE THIS DOES NOT CURRENTLY WORK FOR ANY NTS DATA EXCEPT FOR MAXELE
comparision_data = fulldomain_data - subdomain_data
:param list ts_names: names of ADCIRC timeseries
output files to be recorded from each run
:param list nts_names: names of ADCIRC non timeseries
output files to be recorded from each run
:param string save_file: name of file to save comparision matricies to
:param int timesteps: number of timesteps to read from file
:rtype: tuple
:returns: (ts_error, nts_error, time_obs, ts_data, nts_data)
"""
if save_file is None:
save_file = os.path.join(self.path, 'compare_s2f.mat')
full_file = os.path.join(self.fulldomain.path, 'full.mat')
sub_file = os.path.join(self.path, 'sub.mat')
# Save matricies to *.mat file for use by MATLAB or Python
mdict = dict()
if readmatsub:
subdict = sio.loadmat(sub_file)
savesub = False
else:
subdict = dict()
if fulldict is None:
if readmatfull:
fulldict = sio.loadmat(full_file)
savefull = False
else:
fulldict = dict()
else:
readmatfull = True
savefull = False
# Pre-allocate arrays for non-timeseries data
nts_error = {}
ts_error = {}
time_obs = {}
fulldom_nodes = [v-1 for v in self.sub2full_node.values()]
# Get nts_data
for fid in nts_names:
key = fid.replace('.', '')
if not readmatfull:
fulldict[key] = output.get_nts_sr(self.fulldomain.path,
self.fulldomain, fid)
if not readmatsub:
subdict[key] = output.get_nts_sr(self.path, self, fid)
# Get ts_data
for fid in ts_names:
key = fid.replace('.', '')
if not readmatsub:
subdict[key], time_obs[key] = output.get_ts_sr(self.path, fid,
True,
ihot=self.ihot)
subdict[key+'_time'] = time_obs[key]
if not readmatfull:
fulldict[key] = output.get_ts_sr(self.fulldomain.path,
fid, timesteps=timesteps,
ihot=self.fulldomain.ihot)[0]
if not readmatsub:
# fix dry nodes
if subdict.has_key('fort63'):
subdict['fort63'] = np.expand_dims(subdict['fort63'], axis=2)
subdict = rmn.fix_dry_nodes(subdict, self)
subdict['fort63'] = np.squeeze(subdict['fort63'])
# fix dry data
if subdict.has_key('fort61'):
subdict['fort61'] = np.expand_dims(subdict['fort61'], axis=1)
subdict = rmn.fix_dry_data(subdict, self)
subdict['fort61'] = np.squeeze(subdict['fort61'])
# fix dry nodes nts
if subdict.has_key('maxele63'):
subdict['maxele63'] = np.expand_dims(subdict['maxele63'],
axis=1)
subdict = rmn.fix_dry_nodes_nts(subdict, self)
subdict['maxele63'] = np.squeeze(subdict['maxele63'])
if not readmatfull:
# fix dry nodes
if fulldict.has_key('fort63'):
fulldict['fort63'] = np.expand_dims(fulldict['fort63'], axis=2)
fulldict = rmn.fix_dry_nodes(fulldict, self)
fulldict['fort63'] = np.squeeze(fulldict['fort63'])
# fix dry data
if fulldict.has_key('fort61'):
fulldict['fort61'] = np.expand_dims(fulldict['fort61'], axis=1)
fulldict = rmn.fix_dry_data(fulldict, self)
fulldict['fort61'] = np.squeeze(fulldict['fort61'])
# fix dry nodes nts
if fulldict.has_key('maxele63'):
fulldict['maxele63'] = np.expand_dims(fulldict['maxele63'],
axis=1)
fulldict = rmn.fix_dry_nodes_nts(fulldict, self)
fulldict['maxele63'] = np.squeeze(fulldict['maxele63'])
# Get ts_error
for fid in ts_names:
key = fid.replace('.', '')
sub_data, time_obs[key] = subdict[key], subdict[key+'_time']
total_obs = sub_data.shape[1]
if timesteps and timesteps < total_obs:
total_obs = timesteps
full_data = fulldict[key]
if self.recording[key][2] == 1:
full_data = full_data[fulldom_nodes, 0:total_obs]
else:
full_data = full_data[fulldom_nodes, 0:total_obs, :]
ts_error[key] = (full_data - sub_data)
if key == 'fort63' and (subdict.has_key('maxele63') or\
subdict.has_key('maxele.63')):
nts_error['maxele63'] = np.max(full_data,
axis=1) - subdict['maxele63']
if key == 'fort64' and (subdict.has_key('maxvel63') or\
subdict.has_key('maxvel.63')):
nts_error['maxvel63'] = np.max(np.sqrt(full_data[:, :, 0]**2 +
full_data[:, :, 1]**2),
axis=1) - subdict['maxvel63']
# Get nts_error
for fid in nts_names:
key = fid.replace('.', '')
if key != 'maxele63' and key != 'maxevel63':
nts_error[key] = fulldict[key][fulldom_nodes] - subdict[key]
# Update and save
# export nontimeseries data
for k, v in nts_error.iteritems():
mdict[k] = v
print k
#b = np.ma.fix_invalid(v, fill_value=0)
b = v
print np.max(abs(b)), np.argmax(abs(b))
print "Nodes above threshold", sum(np.abs(b) > 1e-2)
# export timeseries data
for k, v in ts_error.iteritems():
mdict[k] = v
print k
#b = np.ma.fix_invalid(v, fill_value=0)
b = v
print np.max(abs(b)), np.argmax(abs(b))
print "Nodes above threshold", sum(np.abs(b) > 1e-2)
# export time_obs data
for k, v in time_obs.iteritems():
mdict[k+'_time'] = v
sio.savemat(save_file, mdict, do_compression=True)
if savesub:
sio.savemat(sub_file, subdict, do_compression=True)
if savefull:
sio.savemat(full_file, fulldict, do_compression=True)
return (ts_error, nts_error, time_obs, None, None)