def _init_derived_scopes(self):
if self.scope_ids is None:
if len(self.scopes) != self.natom:
raise TypeError('When the scope_ids are derived automatically, the length of the scopes list must match the number of atoms.')
lookup = {}
scopes = []
self.scope_ids = np.zeros(self.natom, int)
for i in xrange(self.natom):
scope = self.scopes[i]
scope_id = lookup.get(scope)
if scope_id is None:
scope_id = len(scopes)
scopes.append(scope)
lookup[scope] = scope_id
self.scope_ids[i] = scope_id
self.scopes = scopes
for scope in self.scopes:
check_name(scope)
# check the range of the ids
if self.scope_ids.min() != 0 or self.scope_ids.max() != len(self.scopes)-1:
raise ValueError('The ffatype_ids have incorrect bounds.')
if log.do_medium:
log('The following scopes are present in the system:')
log.hline()
log(' Scope ID Number of atoms')
log.hline()
for scope_id, scope in enumerate(self.scopes):
log('%22s %3i %3i' % (scope, scope_id, (self.scope_ids==scope_id).sum()))
log.hline()
log.blank()
def _init_derived_scopes(self):
if self.scope_ids is None:
if len(self.scopes) != self.natom:
raise TypeError(
'When the scope_ids are derived automatically, the length of the scopes list must match the number of atoms.'
)
lookup = {}
scopes = []
self.scope_ids = np.zeros(self.natom, int)
for i in range(self.natom):
scope = self.scopes[i]
scope_id = lookup.get(scope)
if scope_id is None:
scope_id = len(scopes)
scopes.append(scope)
lookup[scope] = scope_id
self.scope_ids[i] = scope_id
self.scopes = scopes
for scope in self.scopes:
check_name(scope)
# check the range of the ids
if self.scope_ids.min() != 0 or self.scope_ids.max() != len(
self.scopes) - 1:
raise ValueError('The ffatype_ids have incorrect bounds.')
if log.do_medium:
log('The following scopes are present in the system:')
log.hline()
log(' Scope ID Number of atoms')
log.hline()
for scope_id, scope in enumerate(self.scopes):
log('%22s %3i %3i' %
(scope, scope_id, (self.scope_ids == scope_id).sum()))
log.hline()
log.blank()
def detect_ffatypes(self, rules):
"""Initialize the ``ffatypes`` attribute based on ATSELECT rules.
**Argument:**
rules
A list of (ffatype, rule) pairs that will be used to initialize
the attributes ``self.ffatypes`` and ``self.ffatype_ids``.
If the system already has FF atom types, they will be overwritten.
"""
with log.section('SYS'):
# Give warning if needed
if self.ffatypes is not None:
if log.do_warning:
log.warn('Overwriting existing FF atom types.')
# Compile all the rules
my_rules = []
for ffatype, rule in rules:
check_name(ffatype)
if isinstance(rule, str):
rule = atsel_compile(rule)
my_rules.append((ffatype, rule))
# Use the rules to detect the atom types
lookup = {}
self.ffatypes = []
self.ffatype_ids = np.zeros(self.natom, int)
for i in range(self.natom):
my_ffatype = None
for ffatype, rule in my_rules:
if rule(self, i):
my_ffatype = ffatype
break
if my_ffatype is None:
raise ValueError(
'Could not detect FF atom type of atom %i.' % i)
ffatype_id = lookup.get(my_ffatype)
if ffatype_id is None:
ffatype_id = len(lookup)
self.ffatypes.append(my_ffatype)
lookup[my_ffatype] = ffatype_id
self.ffatype_ids[i] = ffatype_id
# Make sure all is done well ...
self._init_derived_ffatypes()
def detect_ffatypes(self, rules):
"""Initialize the ``ffatypes`` attribute based on ATSELECT rules.
**Argument:**
rules
A list of (ffatype, rule) pairs that will be used to initialize
the attributes ``self.ffatypes`` and ``self.ffatype_ids``.
If the system already has FF atom types, they will be overwritten.
"""
with log.section('SYS'):
# Give warning if needed
if self.ffatypes is not None:
if log.do_warning:
log.warn('Overwriting existing FF atom types.')
# Compile all the rules
my_rules = []
for ffatype, rule in rules:
check_name(ffatype)
if isinstance(rule, basestring):
rule = atsel_compile(rule)
my_rules.append((ffatype, rule))
# Use the rules to detect the atom types
lookup = {}
self.ffatypes = []
self.ffatype_ids = np.zeros(self.natom, int)
for i in xrange(self.natom):
my_ffatype = None
for ffatype, rule in my_rules:
if rule(self, i):
my_ffatype = ffatype
break
if my_ffatype is None:
raise ValueError('Could not detect FF atom type of atom %i.' % i)
ffatype_id = lookup.get(my_ffatype)
if ffatype_id is None:
ffatype_id = len(lookup)
self.ffatypes.append(my_ffatype)
lookup[my_ffatype] = ffatype_id
self.ffatype_ids[i] = ffatype_id
# Make sure all is done well ...
self._init_derived_ffatypes()
def _init_derived_ffatypes(self):
if self.ffatype_ids is None:
if len(self.ffatypes) != self.natom:
raise TypeError('When the ffatype_ids are derived automatically, the length of the ffatypes list must match the number of atoms.')
lookup = {}
ffatypes = []
self.ffatype_ids = np.zeros(self.natom, int)
for i in xrange(self.natom):
if self.scope_ids is None:
ffatype = self.ffatypes[i]
key = ffatype, None
else:
scope_id = self.scope_ids[i]
ffatype = self.ffatypes[i]
key = ffatype, scope_id
ffatype_id = lookup.get(key)
if ffatype_id is None:
ffatype_id = len(ffatypes)
ffatypes.append(ffatype)
lookup[key] = ffatype_id
self.ffatype_ids[i] = ffatype_id
self.ffatypes = ffatypes
for ffatype in self.ffatypes:
check_name(ffatype)
# check the range of the ids
if self.ffatype_ids.min() != 0 or self.ffatype_ids.max() != len(self.ffatypes)-1:
raise ValueError('The ffatype_ids have incorrect bounds.')
# differentiate ffatype_ids if the same ffatype_id is used in different
# scopes
if self.scopes is not None:
self.ffatype_id_to_scope_id = {}
fixed_fids = {}
for i in xrange(self.natom):
fid = self.ffatype_ids[i]
sid = self.ffatype_id_to_scope_id.get(fid)
if sid is None:
self.ffatype_id_to_scope_id[fid] = self.scope_ids[i]
elif sid != self.scope_ids[i]:
# We found the same ffatype_id in a different scope_id. This
# must be fixed. First check if we have already a new
# scope_id ready
sid = self.scope_ids[i]
new_fid = fixed_fids.get((sid, fid))
if new_fid is None:
# No previous new fid create, do it now.
new_fid = len(self.ffatypes)
# Copy the ffatype label
self.ffatypes.append(self.ffatypes[fid])
# Keep track of the new fid
fixed_fids[(sid, fid)] = new_fid
if log.do_warning:
log.warn('Atoms with type ID %i in scope %s were changed to type ID %i.' % (fid, self.scopes[sid], new_fid))
# Apply the new fid
self.ffatype_ids[i] = new_fid
self.ffatype_id_to_scope_id[new_fid] = sid
# Turn the ffatypes in the scopes into array
if self.ffatypes is not None:
self.ffatypes = np.array(self.ffatypes, copy=False)
if self.scopes is not None:
self.scopes = np.array(self.scopes, copy=False)
# check the range of the ids
if self.ffatype_ids.min() != 0 or self.ffatype_ids.max() != len(self.ffatypes)-1:
raise ValueError('The ffatype_ids have incorrect bounds.')
if log.do_medium:
log('The following atom types are present in the system:')
log.hline()
if self.scopes is None:
log(' Atom type ID Number of atoms')
log.hline()
for ffatype_id, ffatype in enumerate(self.ffatypes):
log('%22s %3i %3i' % (ffatype, ffatype_id, (self.ffatype_ids==ffatype_id).sum()))
else:
log(' Scope Atom type ID Number of atoms')
log.hline()
for ffatype_id, ffatype in enumerate(self.ffatypes):
scope = self.scopes[self.ffatype_id_to_scope_id[ffatype_id]]
log('%22s %22s %3i %3i' % (scope, ffatype, ffatype_id, (self.ffatype_ids==ffatype_id).sum()))
log.hline()
log.blank()
def _init_derived_ffatypes(self):
if self.ffatype_ids is None:
if len(self.ffatypes) != self.natom:
raise TypeError(
'When the ffatype_ids are derived automatically, the length of the ffatypes list must match the number of atoms.'
)
lookup = {}
ffatypes = []
self.ffatype_ids = np.zeros(self.natom, int)
for i in range(self.natom):
if self.scope_ids is None:
ffatype = self.ffatypes[i]
key = ffatype, None
else:
scope_id = self.scope_ids[i]
ffatype = self.ffatypes[i]
key = ffatype, scope_id
ffatype_id = lookup.get(key)
if ffatype_id is None:
ffatype_id = len(ffatypes)
ffatypes.append(ffatype)
lookup[key] = ffatype_id
self.ffatype_ids[i] = ffatype_id
self.ffatypes = ffatypes
for ffatype in self.ffatypes:
check_name(ffatype)
# check the range of the ids
if self.ffatype_ids.min() != 0 or self.ffatype_ids.max() != len(
self.ffatypes) - 1:
raise ValueError('The ffatype_ids have incorrect bounds.')
# differentiate ffatype_ids if the same ffatype_id is used in different
# scopes
if self.scopes is not None:
self.ffatype_id_to_scope_id = {}
fixed_fids = {}
for i in range(self.natom):
fid = self.ffatype_ids[i]
sid = self.ffatype_id_to_scope_id.get(fid)
if sid is None:
self.ffatype_id_to_scope_id[fid] = self.scope_ids[i]
elif sid != self.scope_ids[i]:
# We found the same ffatype_id in a different scope_id. This
# must be fixed. First check if we have already a new
# scope_id ready
sid = self.scope_ids[i]
new_fid = fixed_fids.get((sid, fid))
if new_fid is None:
# No previous new fid create, do it now.
new_fid = len(self.ffatypes)
# Copy the ffatype label
self.ffatypes.append(self.ffatypes[fid])
# Keep track of the new fid
fixed_fids[(sid, fid)] = new_fid
if log.do_warning:
log.warn(
'Atoms with type ID %i in scope %s were changed to type ID %i.'
% (fid, self.scopes[sid], new_fid))
# Apply the new fid
self.ffatype_ids[i] = new_fid
self.ffatype_id_to_scope_id[new_fid] = sid
# Turn the ffatypes in the scopes into array
if self.ffatypes is not None:
self.ffatypes = np.array(self.ffatypes, copy=False)
if self.scopes is not None:
self.scopes = np.array(self.scopes, copy=False)
# check the range of the ids
if self.ffatype_ids.min() != 0 or self.ffatype_ids.max() != len(
self.ffatypes) - 1:
raise ValueError('The ffatype_ids have incorrect bounds.')
if log.do_medium:
log('The following atom types are present in the system:')
log.hline()
if self.scopes is None:
log(' Atom type ID Number of atoms')
log.hline()
for ffatype_id, ffatype in enumerate(self.ffatypes):
log('%22s %3i %3i' %
(ffatype, ffatype_id,
(self.ffatype_ids == ffatype_id).sum()))
else:
log(' Scope Atom type ID Number of atoms'
)
log.hline()
for ffatype_id, ffatype in enumerate(self.ffatypes):
scope = self.scopes[
self.ffatype_id_to_scope_id[ffatype_id]]
log('%22s %22s %3i %3i' %
(scope, ffatype, ffatype_id,
(self.ffatype_ids == ffatype_id).sum()))
log.hline()
log.blank()