def from_dict(cls, obj):
assert obj['__id__'] == 'Indexer'
assert obj['__name__'] == cls.__name__
return_obj = cls()
for k, v in obj.iteritems():
if k == '_indxr_helper' and v is not None:
from xia2.Schema.Interfaces.Indexer import _IndexerHelper
v = _IndexerHelper(v)
if k == '_indxr_imagesets' and len(v):
assert v[0].get('__id__') == 'imageset'
from dxtbx.serialize.imageset import imageset_from_dict
v = [imageset_from_dict(v_, check_format=False) for v_ in v]
if isinstance(v, dict):
if v.get('__id__') == 'ExperimentList':
from dxtbx.model.experiment.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def from_dict(cls, obj):
assert obj['__id__'] == 'Indexer'
assert obj['__name__'] == cls.__name__
return_obj = cls()
for k, v in obj.iteritems():
if k == '_indxr_helper' and v is not None:
from xia2.Schema.Interfaces.Indexer import _IndexerHelper
v = _IndexerHelper(v)
if k == '_indxr_imagesets' and len(v):
assert v[0].get('__id__') == 'imageset'
from dxtbx.serialize.imageset import imageset_from_dict
v = [imageset_from_dict(v_, check_format=False) for v_ in v]
if isinstance(v, dict):
if v.get('__id__') == 'ExperimentList':
from dxtbx.model.experiment_list import ExperimentListFactory
v = ExperimentListFactory.from_dict(v, check_format=False)
setattr(return_obj, k, v)
return return_obj
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write('Index in %s called from %s %d' %
(self.__class__.__name__, m, l))
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = [ s.get_name() for s in self.get_indexer_sweeps() ]
if len(xsweeps) > 1:
# find "SWEEPn, SWEEP(n+1), (..), SWEEPm" and aggregate to "SWEEPS n-m"
xsweeps = map(lambda x: (int(x[5:]), int(x[5:])) if x.startswith('SWEEP') else x, xsweeps)
xsweeps[0] = [xsweeps[0]]
def compress(seen, nxt):
if isinstance(seen[-1], tuple) and isinstance(nxt, tuple) and (seen[-1][1] + 1 == nxt[0]):
seen[-1] = (seen[-1][0], nxt[1])
else:
seen.append(nxt)
return seen
xsweeps = reduce(compress, xsweeps)
xsweeps = map(lambda x: ('SWEEP%d' % x[0] if x[0] == x[1] else
'SWEEPS %d to %d' % (x[0], x[1])) if isinstance(x, tuple)
else x, xsweeps)
if len(xsweeps) > 1:
sweep_names = ', '.join(xsweeps[:-1])
sweep_names += ' & ' + xsweeps[-1]
else:
sweep_names = xsweeps[0]
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner(
'Autoindexing %s (%s)' %(sweep_names, template))
else:
Chatter.banner('Autoindexing %s' %sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write(
'Looks like indexing failed - try again!')
continue
solutions = { }
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k][
'cell']
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if self._indxr_lattice != solution[0] and \
not self._indxr_input_cell and \
not PhilIndex.params.xia2.settings.integrate_p1:
Chatter.write('Rerunning indexing lattice %s to %s' %
(self._indxr_lattice, solution[0]))
Debug.write(
'Rerunning indexing with target lattice %s' % \
solution[0])
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write(
"Index in %s called from %s %d" % (self.__class__.__name__, m, l)
)
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = [s.get_name() for s in self.get_indexer_sweeps()]
if len(xsweeps) > 1:
# find "SWEEPn, SWEEP(n+1), (..), SWEEPm" and aggregate to "SWEEPS n-m"
xsweeps = map(
lambda x: (int(x[5:]), int(x[5:]))
if x.startswith("SWEEP")
else x,
xsweeps,
)
xsweeps[0] = [xsweeps[0]]
def compress(seen, nxt):
if (
isinstance(seen[-1], tuple)
and isinstance(nxt, tuple)
and (seen[-1][1] + 1 == nxt[0])
):
seen[-1] = (seen[-1][0], nxt[1])
else:
seen.append(nxt)
return seen
xsweeps = reduce(compress, xsweeps)
xsweeps = map(
lambda x: (
"SWEEP%d" % x[0]
if x[0] == x[1]
else "SWEEPS %d to %d" % (x[0], x[1])
)
if isinstance(x, tuple)
else x,
xsweeps,
)
if len(xsweeps) > 1:
sweep_names = ", ".join(xsweeps[:-1])
sweep_names += " & " + xsweeps[-1]
else:
sweep_names = xsweeps[0]
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner("Autoindexing %s (%s)" % (sweep_names, template))
else:
Chatter.banner("Autoindexing %s" % sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write("Looks like indexing failed - try again!")
continue
solutions = {}
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k]["cell"]
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if (
self._indxr_lattice != solution[0]
and not self._indxr_input_cell
and not PhilIndex.params.xia2.settings.integrate_p1
):
Chatter.write(
"Rerunning indexing lattice %s to %s"
% (self._indxr_lattice, solution[0])
)
Debug.write(
"Rerunning indexing with target lattice %s" % solution[0]
)
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
def index(self):
if not self.get_indexer_finish_done():
f = inspect.currentframe().f_back.f_back
m = f.f_code.co_filename
l = f.f_lineno
Debug.write('Index in %s called from %s %d' %
(self.__class__.__name__, m, l))
while not self.get_indexer_finish_done():
while not self.get_indexer_done():
while not self.get_indexer_prepare_done():
# --------------
# call prepare()
# --------------
self.set_indexer_prepare_done(True)
self._index_prepare()
# --------------------------------------------
# then do the proper indexing - using the best
# solution already stored if available (c/f
# eliminate above)
# --------------------------------------------
self.set_indexer_done(True)
if self.get_indexer_sweeps():
xsweeps = self.get_indexer_sweeps()
if len(xsweeps) > 1:
sweep_names = ', '.join(x.get_name() for x in xsweeps[:-1])
sweep_names += ' & ' + xsweeps[-1].get_name()
else:
sweep_names = xsweeps[0].get_name()
if PhilIndex.params.xia2.settings.show_template:
template = self.get_indexer_sweep().get_template()
Chatter.banner(
'Autoindexing %s (%s)' %(sweep_names, template))
else:
Chatter.banner('Autoindexing %s' %sweep_names)
if not self._indxr_helper:
result = self._index()
if not self._indxr_done:
Debug.write(
'Looks like indexing failed - try again!')
continue
solutions = { }
for k in self._indxr_other_lattice_cell.keys():
solutions[k] = self._indxr_other_lattice_cell[k][
'cell']
# create a helper for the indexer to manage solutions
self._indxr_helper = _IndexerHelper(solutions)
solution = self._indxr_helper.get()
# compare these against the final solution, if different
# reject solution and return - correct solution will
# be used next cycle
if self._indxr_lattice != solution[0] and \
not self._indxr_input_cell and \
not PhilIndex.params.xia2.settings.integrate_p1:
Chatter.write('Rerunning indexing lattice %s to %s' %
(self._indxr_lattice, solution[0]))
Debug.write(
'Rerunning indexing with target lattice %s' % \
solution[0])
self.set_indexer_done(False)
else:
# rerun autoindexing with the best known current solution
solution = self._indxr_helper.get()
self._indxr_input_lattice = solution[0]
self._indxr_input_cell = solution[1]
result = self._index()
# next finish up...
self.set_indexer_finish_done(True)
self._index_finish()
if self._indxr_print:
Chatter.write(self.show_indexer_solutions())
# FIXED 23/OCT/06 at this stage I need to look at the list of
# reasonable solutions and try to figure out if the indexing
# program has picked the highest - if not, then constrain the
# unit cell (need to implement this somewhere, sure it's
# around!) then rerun the autoindexing (perhaps?) with this
# new target - this means that we are always working from the
# top downwards with these things. Once we decide somewhere
# else (e.g. in cell refinement) that this cell isn't good
# then we can eliminate it from the list, select the next
# lower symmetry solution and continue. This solution is a
# general one, so may be implemented in the general indexer
# interface rather than in specific code...
return
