def read_exodus_legacy(filename, variables=None, disp=1, blk_num=1, elem_num=1):
'''Read the specified variables from the exodus file in filepath
'''
if not isfile(filename):
raise IOError('{0}: no such file'.format(filename))
fh = NetCDFFile(filename, 'r')
# global/element vars and mapping
num_glo_var = fh.dimensions.get('num_glo_var', 0)
if num_glo_var:
name_glo_var = exodus.stringify(fh.variables['name_glo_var'].data)
gmap = dict(zip(name_glo_var, range(len(name_glo_var))))
name_elem_var = exodus.stringify(fh.variables['name_elem_var'].data)
emap = dict(zip(name_elem_var, range(len(name_elem_var))))
# retrieve the data from the database
head = ['TIME']
if num_glo_var:
head.extend([H.upper() for H in name_glo_var])
head.extend([H.upper() for H in name_elem_var])
data = []
times = fh.variables['time_whole'].data.flatten()
for (i, time) in enumerate(times):
row = [time]
if num_glo_var:
vals_glo_var = fh.variables['vals_glo_var'].data[i]
for var in name_glo_var:
var_num = gmap[var]
try: row.append(vals_glo_var[var_num])
except KeyError: continue
for var in name_elem_var:
var_num = emap[var]+1
name = 'vals_elem_var{0}eb{1}'.format(var_num, blk_num)
row.append(fh.variables[name].data[i, elem_num-1])
data.append(row)
fh.close()
data = np.asarray(data)
if len(head) != data.shape[1]:
raise ValueError('inconsistent data')
data = np.array(data)
if variables is not None:
variables = [x.upper() for x in variables]
idx = []
for name in variables:
try:
idx.append(head.index(name))
except IndexError:
raise KeyError('{0} not in output database'.format(name))
head = [head[i] for i in idx]
data = data[:, idx]
if disp:
return head, data
return data
def read_exodus_legacy(filename,
variables=None,
disp=1,
blk_num=1,
elem_num=1):
'''Read the specified variables from the exodus file in filepath
'''
if not isfile(filename):
raise IOError('{0}: no such file'.format(filename))
fh = NetCDFFile(filename, 'r')
# global/element vars and mapping
num_glo_var = fh.dimensions.get('num_glo_var', 0)
if num_glo_var:
name_glo_var = exodus.stringify(fh.variables['name_glo_var'].data)
gmap = dict(zip(name_glo_var, range(len(name_glo_var))))
name_elem_var = exodus.stringify(fh.variables['name_elem_var'].data)
emap = dict(zip(name_elem_var, range(len(name_elem_var))))
# retrieve the data from the database
head = ['TIME']
if num_glo_var:
head.extend([H.upper() for H in name_glo_var])
head.extend([H.upper() for H in name_elem_var])
data = []
times = fh.variables['time_whole'].data.flatten()
for (i, time) in enumerate(times):
row = [time]
if num_glo_var:
vals_glo_var = fh.variables['vals_glo_var'].data[i]
for var in name_glo_var:
var_num = gmap[var]
try:
row.append(vals_glo_var[var_num])
except KeyError:
continue
for var in name_elem_var:
var_num = emap[var] + 1
name = 'vals_elem_var{0}eb{1}'.format(var_num, blk_num)
row.append(fh.variables[name].data[i, elem_num - 1])
data.append(row)
fh.close()
data = np.asarray(data)
if len(head) != data.shape[1]:
raise ValueError('inconsistent data')
data = np.array(data)
if variables is not None:
variables = [x.upper() for x in variables]
idx = []
for name in variables:
try:
idx.append(head.index(name))
except IndexError:
raise KeyError('{0} not in output database'.format(name))
head = [head[i] for i in idx]
data = data[:, idx]
if disp:
return head, data
return data
