def _prepare_set_field(field, subfieldname, data, site=None,
scale_factor=1.0, normalise=False, check_site=False):
"""
Internal function used to make some sanity checks before setting a field.
"""
# 1-2 check size and shape of field
_check_field(field, subfieldname, data, site)
# 3 is the data of the right type --> done by ocaml
# 4 check that the site type is a list
if check_site and type(site) != types.ListType:
raise NmagUserError("'site' has to be a list of integers. For "
"first order basis functions, there is only "
"one integer in the list, the node id.")
# Now we can actually set the data.
# Do we need to normalise?
if normalise:
data = normalised_vector(data)
# Do we need to apply the scale factor
if type(data) in [types.IntType, types.FloatType, types.BooleanType]:
data *= float(scale_factor)
else:
# FIXME: this doesn't work with tensors!
data = map(lambda x : x*float(scale_factor), data)
return data
def _prepare_set_field(field, subfieldname, data, site=None,
scale_factor=1.0, normalise=False, check_site=False):
"""
Internal function used to make some sanity checks before setting a field.
"""
# We do a number of sanity checks for which we need some metadata
list_of_subfield_and_shape_tuples = nfem.data_doftypes(field)
# Gets all the shapes mapped by the subfield names
shape_by_subfieldname = {}
for sfname, shape in list_of_subfield_and_shape_tuples:
shape_by_subfieldname[sfname] = shape
# 1 Does the field have this subfield:
if not subfieldname in shape_by_subfieldname.keys():
subfields = shape_by_subfieldname.keys()
msg = ("You want to set %s but I have only found subfield(s) '%s' "
"in the field. By the way, your data is '%s'."
% (_set_what_msg(subfieldname, site), subfields, data))
raise NmagUserError(msg)
# 2 Is the shape of the data right?
shape = list(numpy.array(data).shape) # quite a silly way to get the
# shape, but it works!
if shape != shape_by_subfieldname[subfieldname]:
msg = ("When trying to set %s we have a shape mismatch. The shape of "
"the subfield data is '%s' but the shape of your data is '%s'."
"By the way, your data is '%s'."
% (_set_what_msg(subfieldname, site),
shape_by_subfieldname[subfieldname], shape, data))
raise NmagUserError(msg)
# 3 is the data of the right type --> done by ocaml
# 4 check that the site type is a list
if check_site and type(site) != types.ListType:
raise NmagUserError("'site' has to be a list of integers. For "
"first order basis functions, there is only "
"one integer in the list, the node id.")
# Now we can actually set the data.
# Do we need to normalise?
if normalise:
data = normalised_vector(data)
# Do we need to apply the scale factor
if type(data) in [types.IntType, types.FloatType, types.BooleanType]:
data *= float(scale_factor)
else:
# FIXME: this doesn't work with tensors!
data = map(lambda x : x*float(scale_factor), data)
return data
def _prepare_set_field(field,
subfieldname,
data,
site=None,
scale_factor=1.0,
normalise=False,
check_site=False):
"""
Internal function used to make some sanity checks before setting a field.
"""
# 1-2 check size and shape of field
_check_field(field, subfieldname, data, site)
# 3 is the data of the right type --> done by ocaml
# 4 check that the site type is a list
if check_site and type(site) != types.ListType:
raise NmagUserError("'site' has to be a list of integers. For "
"first order basis functions, there is only "
"one integer in the list, the node id.")
# Now we can actually set the data.
# Do we need to normalise?
if normalise:
data = normalised_vector(data)
# Do we need to apply the scale factor
if type(data) in [types.IntType, types.FloatType, types.BooleanType]:
data *= float(scale_factor)
else:
# FIXME: this doesn't work with tensors!
data = map(lambda x: x * float(scale_factor), data)
return data
def _prepare_set_field(field,
subfieldname,
data,
site=None,
scale_factor=1.0,
normalise=False,
check_site=False):
"""
Internal function used to make some sanity checks before setting a field.
"""
# We do a number of sanity checks for which we need some metadata
list_of_subfield_and_shape_tuples = nfem.data_doftypes(field)
# Gets all the shapes mapped by the subfield names
shape_by_subfieldname = {}
for sfname, shape in list_of_subfield_and_shape_tuples:
shape_by_subfieldname[sfname] = shape
# 1 Does the field have this subfield:
if not subfieldname in shape_by_subfieldname.keys():
subfields = shape_by_subfieldname.keys()
msg = ("You want to set %s but I have only found subfield(s) '%s' "
"in the field. By the way, your data is '%s'." %
(_set_what_msg(subfieldname, site), subfields, data))
raise NmagUserError(msg)
# 2 Is the shape of the data right?
shape = list(numpy.array(data).shape) # quite a silly way to get the
# shape, but it works!
if shape != shape_by_subfieldname[subfieldname]:
msg = ("When trying to set %s we have a shape mismatch. The shape of "
"the subfield data is '%s' but the shape of your data is '%s'."
"By the way, your data is '%s'." %
(_set_what_msg(subfieldname, site),
shape_by_subfieldname[subfieldname], shape, data))
raise NmagUserError(msg)
# 3 is the data of the right type --> done by ocaml
# 4 check that the site type is a list
if check_site and type(site) != types.ListType:
raise NmagUserError("'site' has to be a list of integers. For "
"first order basis functions, there is only "
"one integer in the list, the node id.")
# Now we can actually set the data.
# Do we need to normalise?
if normalise:
data = normalised_vector(data)
# Do we need to apply the scale factor
if type(data) in [types.IntType, types.FloatType, types.BooleanType]:
data *= float(scale_factor)
else:
# FIXME: this doesn't work with tensors!
data = map(lambda x: x * float(scale_factor), data)
return data
