def bravais_lattice_to_space_groups(chiral_only=True):
from cctbx import sgtbx
from cctbx.sgtbx import bravais_types
from libtbx.containers import OrderedDict
bravais_lattice_to_sg = OrderedDict()
for sgn in range(230):
sg = sgtbx.space_group_info(number=sgn+1).group()
if (not chiral_only) or (sg.is_chiral()):
bravais_lattice = bravais_types.bravais_lattice(group=sg)
bravais_lattice_to_sg.setdefault(str(bravais_lattice), [])
bravais_lattice_to_sg[str(bravais_lattice)].append(sg)
return bravais_lattice_to_sg
def unique_beams(self):
''' Iterate through unique beams. '''
from dxtbx.imageset import ImageSweep
from libtbx.containers import OrderedDict
obj = OrderedDict()
for iset in self._imagesets:
if isinstance(iset, ImageSweep):
obj[iset.get_beam()] = None
else:
for i in range(len(iset)):
obj[iset.get_beam(i)] = None
return obj.keys()
class cctbx_data_structures_from_cif(object):
def __init__(self,
file_object=None,
file_path=None,
cif_model=None,
data_structure_builder=None,
data_block_name=None,
base_array_info=None,
**kwds):
assert file_object is None or cif_model is None
if data_structure_builder is None:
data_structure_builders = (
builders.miller_array_builder, builders.crystal_structure_builder)
else:
assert data_structure_builder in (
builders.miller_array_builder, builders.crystal_structure_builder)
data_structure_builders = (data_structure_builder,)
self.xray_structures = OrderedDict()
self.miller_arrays = OrderedDict()
if cif_model is None:
cif_model = reader(file_path=file_path, file_object=file_object).model()
if not len(cif_model):
raise Sorry("No data block found in CIF")
if data_block_name is not None and not data_block_name in cif_model:
if (file_path is None):
msg = 'Unknown CIF data block name: "%s"' % data_block_name
else:
msg = 'Unknown CIF data block name "%s" in file: "%s"' % (
data_block_name, file_path)
raise RuntimeError(msg)
errors = []
wavelengths = {}
for key, block in cif_model.items():
if data_block_name is not None and key != data_block_name: continue
for builder in data_structure_builders:
if builder == builders.crystal_structure_builder:
if '_atom_site_fract_x' in block or '_atom_site_Cartn_x' in block:
self.xray_structures.setdefault(key, builder(block).structure)
elif builder == builders.miller_array_builder:
block_wavelengths = builders.get_wavelengths(block)
if (block_wavelengths is not None) :
wavelengths = block_wavelengths
if base_array_info is not None:
base_array_info = base_array_info.customized_copy(labels=[key])
if ( '_refln_index_h' in block or '_refln.index_h' in block or
'_diffrn_refln' in block
):
self.miller_arrays.setdefault(
key, builder(block, base_array_info=base_array_info,
wavelengths=wavelengths).arrays())
class image_data_cache(object):
def __init__(self, imageset, size=10):
self.imageset = imageset
self.size = size
self._image_data = OrderedDict()
def __getitem__(self, i):
image_data = self._image_data.get(i)
if image_data is None:
image_data = self.imageset.get_raw_data(i)
if len(self._image_data) >= self.size:
# remove the oldest entry in the cache
del self._image_data[self._image_data.keys()[0]]
self._image_data[i] = image_data
return image_data
def _unique_detectors_dict(self):
''' Returns an ordered dictionary of detector objects. '''
from dxtbx.imageset import ImageSweep
from libtbx.containers import OrderedDict
obj = OrderedDict()
for iset in self._imagesets:
if isinstance(iset, ImageSweep):
obj[iset.get_detector()] = None
else:
for i in range(len(iset)):
obj[iset.get_detector(i)] = None
detector_id = 0
for detector in obj.keys():
obj[detector] = detector_id
detector_id = detector_id + 1
return obj
def unique_scans(self):
''' Iterate through unique scans. '''
from dxtbx.imageset import ImageSweep
from libtbx.containers import OrderedDict
obj = OrderedDict()
for iset in self._imagesets:
if isinstance(iset, ImageSweep):
obj[iset.get_scan()] = None
else:
for i in range(len(iset)):
try:
model = iset.get_scan(i)
if model is not None:
obj[model] = None
except Exception:
pass
return obj.keys()
def exercise_odict():
from libtbx.containers import OrderedDict as odict
d = odict([('banana',3), ('apple',4), ('pear',1)])
d.setdefault('orange', 2)
assert d.has_key('orange')
assert d['orange'] == 2
assert d.keys() == ['banana', 'apple', 'pear', 'orange']
assert d.values() == [3, 4, 1, 2]
d = odict.fromkeys(('b','c','a'))
assert d.keys() == ['b', 'c', 'a']
def __init__(self, header=None, data=None):
self._columns = OrderedDict()
self.keys_lower = {}
if header is not None:
for key in header:
self.setdefault(key, flex.std_string())
if data is not None:
# the number of data items must be an exact multiple of the number of headers
assert len(data) % len(header) == 0, "Wrong number of data items for loop"
n_rows = len(data)//len(header)
n_columns = len(header)
for i in range(n_rows):
self.add_row([data[i*n_columns+j] for j in range(n_columns)])
elif header is None and data is not None:
assert isinstance(data, dict) or isinstance(data, OrderedDict)
self.add_columns(data)
self.keys_lower = dict(
[(key.lower(), key) for key in self._columns.keys()])
def __init__(self, unmerged_intensities, batches_all, n_bins=20, d_min=None,
id_to_batches=None):
sel = unmerged_intensities.sigmas() > 0
unmerged_intensities = unmerged_intensities.select(sel)
batches_all = batches_all.select(sel)
unmerged_intensities.setup_binner(n_bins=n_bins)
unmerged_intensities.show_summary()
self.unmerged_intensities = unmerged_intensities
self.merged_intensities = unmerged_intensities.merge_equivalents().array()
separate = separate_unmerged(
unmerged_intensities, batches_all, id_to_batches=id_to_batches)
self.intensities = separate.intensities
self.batches = separate.batches
run_id_to_batch_id = separate.run_id_to_batch_id
self.individual_merged_intensities = OrderedDict()
for k in self.intensities.keys():
self.intensities[k] = self.intensities[k].resolution_filter(d_min=d_min)
self.batches[k] = self.batches[k].resolution_filter(d_min=d_min)
self.individual_merged_intensities[k] = self.intensities[k].merge_equivalents().array()
if run_id_to_batch_id is not None:
labels = run_id_to_batch_id.values()
else:
labels = None
racc = self.relative_anomalous_cc()
if racc is not None:
self.plot_relative_anomalous_cc(racc, labels=labels)
correlation_matrix, linkage_matrix = self.compute_correlation_coefficient_matrix()
self._cluster_dict = self.to_dict(correlation_matrix, linkage_matrix)
self.plot_cc_matrix(correlation_matrix, linkage_matrix, labels=labels)
self.write_output()
def __init__(self, xinfo_file, sweep_ids=None, sweep_ranges=None):
'''Initialise myself from an input .xinfo file.'''
# first initialise all of the data structures which will hold the
# information...
self._project = None
self._crystals = OrderedDict()
if sweep_ids is not None:
sweep_ids = [s.lower() for s in sweep_ids]
if sweep_ranges is not None:
assert sweep_ids is not None
assert len(sweep_ids) == len(sweep_ranges)
self._sweep_ids = sweep_ids
self._sweep_ranges = sweep_ranges
# read the contents of the xinfo file
self._parse_project(xinfo_file)
self._validate()
return
def run(args):
from dials.util.options import OptionParser
from dials.util.options import flatten_experiments
from dials.util.options import flatten_datablocks
from dials.util.options import flatten_reflections
import libtbx.load_env
usage = "%s [options] datablock.json | experiments.json | image_*.cbf" % (
libtbx.env.dispatcher_name)
parser = OptionParser(usage=usage,
phil=phil_scope,
read_experiments=True,
read_datablocks=True,
read_datablocks_from_images=True,
read_reflections=True,
check_format=False,
epilog=help_message)
params, options = parser.parse_args(show_diff_phil=True)
experiments = flatten_experiments(params.input.experiments)
datablocks = flatten_datablocks(params.input.datablock)
reflections = flatten_reflections(params.input.reflections)
if len(datablocks) == 0 and len(experiments) == 0 and len(
reflections) == 0:
parser.print_help()
exit()
for i_expt, expt in enumerate(experiments):
print "Experiment %i:" % i_expt
print str(expt.detector)
print 'Max resolution (at corners): %f' % (
expt.detector.get_max_resolution(expt.beam.get_s0()))
print 'Max resolution (inscribed): %f' % (
expt.detector.get_max_inscribed_resolution(expt.beam.get_s0()))
if params.show_panel_distance:
for ipanel, panel in enumerate(expt.detector):
from scitbx import matrix
fast = matrix.col(panel.get_fast_axis())
slow = matrix.col(panel.get_slow_axis())
normal = fast.cross(slow).normalize()
origin = matrix.col(panel.get_origin())
distance = origin.dot(normal)
fast_origin = -(origin - distance * normal).dot(fast)
slow_origin = -(origin - distance * normal).dot(slow)
print 'Panel %d: distance %.2f origin %.2f %.2f' % \
(ipanel, distance, fast_origin, slow_origin)
print ''
print ''
print show_beam(expt.detector, expt.beam)
if expt.scan is not None:
print expt.scan
if expt.goniometer is not None:
print expt.goniometer
expt.crystal.show(show_scan_varying=params.show_scan_varying)
if expt.crystal.num_scan_points:
from scitbx.array_family import flex
from cctbx import uctbx
abc = flex.vec3_double()
angles = flex.vec3_double()
for n in range(expt.crystal.num_scan_points):
a, b, c, alpha, beta, gamma = expt.crystal.get_unit_cell_at_scan_point(
n).parameters()
abc.append((a, b, c))
angles.append((alpha, beta, gamma))
a, b, c = abc.mean()
alpha, beta, gamma = angles.mean()
mean_unit_cell = uctbx.unit_cell((a, b, c, alpha, beta, gamma))
print " Average unit cell: %s" % mean_unit_cell
print
if expt.profile is not None:
print expt.profile
for datablock in datablocks:
if datablock.format_class() is not None:
print 'Format: %s' % datablock.format_class()
imagesets = datablock.extract_imagesets()
for imageset in imagesets:
try:
print imageset.get_template()
except Exception:
pass
detector = imageset.get_detector()
print str(detector)
print 'Max resolution (at corners): %f' % (
detector.get_max_resolution(imageset.get_beam().get_s0()))
print 'Max resolution (inscribed): %f' % (
detector.get_max_inscribed_resolution(
imageset.get_beam().get_s0()))
if params.show_panel_distance:
for ipanel, panel in enumerate(detector):
from scitbx import matrix
fast = matrix.col(panel.get_fast_axis())
slow = matrix.col(panel.get_slow_axis())
normal = fast.cross(slow)
origin = matrix.col(panel.get_origin())
distance = origin.dot(normal)
fast_origin = -(origin - distance * normal).dot(fast)
slow_origin = -(origin - distance * normal).dot(slow)
print 'Panel %d: distance %.2f origin %.2f %.2f' % \
(ipanel, distance, fast_origin, slow_origin)
print ''
print ''
print show_beam(detector, imageset.get_beam())
if imageset.get_scan() is not None:
print imageset.get_scan()
if imageset.get_goniometer() is not None:
print imageset.get_goniometer()
from libtbx.containers import OrderedDict, OrderedSet
formats = OrderedDict([
('miller_index', '%i, %i, %i'),
('d', '%.2f'),
('dqe', '%.3f'),
('id', '%i'),
('imageset_id', '%i'),
('panel', '%i'),
('flags', '%i'),
('background.mean', '%.1f'),
('background.dispersion', '%.1f'),
('background.mse', '%.1f'),
('background.sum.value', '%.1f'),
('background.sum.variance', '%.1f'),
('intensity.prf.value', '%.1f'),
('intensity.prf.variance', '%.1f'),
('intensity.sum.value', '%.1f'),
('intensity.sum.variance', '%.1f'),
('intensity.cor.value', '%.1f'),
('intensity.cor.variance', '%.1f'),
('lp', '%.3f'),
('num_pixels.background', '%i'),
('num_pixels.background_used', '%i'),
('num_pixels.foreground', '%i'),
('num_pixels.valid', '%i'),
('partial_id', '%i'),
('partiality', '%.4f'),
('profile.correlation', '%.3f'),
('profile.rmsd', '%.3f'),
('xyzcal.mm', '%.2f, %.2f, %.2f'),
('xyzcal.px', '%.2f, %.2f, %.2f'),
('delpsical.rad', '%.3f'),
('delpsical2', '%.3f'),
('delpsical.weights', '%.3f'),
('xyzobs.mm.value', '%.2f, %.2f, %.2f'),
('xyzobs.mm.variance', '%.4e, %.4e, %.4e'),
('xyzobs.px.value', '%.2f, %.2f, %.2f'),
('xyzobs.px.variance', '%.4f, %.4f, %.4f'),
('s1', '%.4f, %.4f, %.4f'),
('rlp', '%.4f, %.4f, %.4f'),
('zeta', '%.3f'),
('x_resid', '%.3f'),
('x_resid2', '%.3f'),
('y_resid', '%.3f'),
('y_resid2', '%.3f'),
('kapton_absorption_correction', '%.3f'),
('kapton_absorption_correction_sigmas', '%.3f'),
])
for rlist in reflections:
from cctbx.array_family import flex
print
print "Reflection list contains %i reflections" % (len(rlist))
if len(rlist) == 0:
continue
rows = [["Column", "min", "max", "mean"]]
for k, col in rlist.cols():
if type(col) in (flex.double, flex.int, flex.size_t):
if type(col) in (flex.int, flex.size_t):
col = col.as_double()
rows.append([
k, formats[k] % flex.min(col), formats[k] % flex.max(col),
formats[k] % flex.mean(col)
])
elif type(col) in (flex.vec3_double, flex.miller_index):
if type(col) == flex.miller_index:
col = col.as_vec3_double()
rows.append([
k, formats[k] % col.min(), formats[k] % col.max(),
formats[k] % col.mean()
])
from libtbx import table_utils
print table_utils.format(rows,
has_header=True,
prefix="| ",
postfix=" |")
intensity_keys = ('miller_index', 'd', 'intensity.prf.value',
'intensity.prf.variance', 'intensity.sum.value',
'intensity.sum.variance', 'background.mean',
'profile.correlation', 'profile.rmsd')
profile_fit_keys = (
'miller_index',
'd',
)
centroid_keys = ('miller_index', 'd', 'xyzcal.mm', 'xyzcal.px',
'xyzobs.mm.value', 'xyzobs.mm.variance',
'xyzobs.px.value', 'xyzobs.px.variance')
keys_to_print = OrderedSet()
if params.show_intensities:
for k in intensity_keys:
keys_to_print.add(k)
if params.show_profile_fit:
for k in profile_fit_keys:
keys_to_print.add(k)
if params.show_centroids:
for k in centroid_keys:
keys_to_print.add(k)
if params.show_all_reflection_data:
for k in formats:
keys_to_print.add(k)
def format_column(key, data, format_strings=None):
if isinstance(data, flex.vec3_double):
c_strings = [
c.as_string(format_strings[i].strip())
for i, c in enumerate(data.parts())
]
elif isinstance(data, flex.miller_index):
c_strings = [
c.as_string(format_strings[i].strip())
for i, c in enumerate(data.as_vec3_double().parts())
]
elif isinstance(data, flex.size_t):
c_strings = [data.as_int().as_string(format_strings[0].strip())]
else:
c_strings = [data.as_string(format_strings[0].strip())]
column = flex.std_string()
max_element_lengths = [c.max_element_length() for c in c_strings]
for i in range(len(c_strings[0])):
column.append(('%%%is' % len(key)) % ', '.join(
('%%%is' % max_element_lengths[j]) % c_strings[j][i]
for j in range(len(c_strings))))
return column
if keys_to_print:
keys = [k for k in keys_to_print if k in rlist]
rows = [keys]
max_reflections = len(rlist)
if params.max_reflections is not None:
max_reflections = min(len(rlist), params.max_reflections)
columns = []
for k in keys:
columns.append(
format_column(k,
rlist[k],
format_strings=formats[k].split(',')))
print
print "Printing %i of %i reflections:" % (max_reflections, len(rlist))
for j in range(len(columns)):
key = keys[j]
width = max(len(key), columns[j].max_element_length())
print("%%%is" % width) % key,
print
for i in range(max_reflections):
for j in range(len(columns)):
print columns[j][i],
print
return
class miller_array_builder(crystal_symmetry_builder):
# Changes to this class should pass regression tests:
# cctbx_project\mmtbx\regression\tst_cif_as_mtz_wavelengths.py
# cctbx_project\iotbx\cif\tests\tst_lex_parse_build.py
# phenix_regression\cif_as_mtz\tst_cif_as_mtz.py
observation_types = {
# known types of column data to be tagged as either amplitudes or intensities as per
# https://www.iucr.org/__data/iucr/cifdic_html/2/cif_mm.dic/index.html
'_refln.F_squared': xray.intensity(),
'_refln_F_squared': xray.intensity(),
'_refln.intensity': xray.intensity(),
'_refln.I(+)': xray.intensity(),
'_refln.I(-)': xray.intensity(),
'_refln.F_calc': xray.amplitude(),
'_refln.F_meas': xray.amplitude(),
'_refln.FP': xray.amplitude(),
'_refln.F-obs': xray.amplitude(),
'_refln.Fobs': xray.amplitude(),
'_refln.F-calc': xray.amplitude(),
'_refln.Fcalc': xray.amplitude(),
'_refln.pdbx_F_': xray.amplitude(),
'_refln.pdbx_I_': xray.intensity(),
'_refln.pdbx_anom_difference': xray.amplitude(),
}
def guess_observationtype(self, labl):
for okey in self.observation_types.keys():
if labl.startswith(okey):
return self.observation_types[okey]
return None
def __init__(self, cif_block, base_array_info=None, wavelengths=None):
crystal_symmetry_builder.__init__(self, cif_block)
self._arrays = OrderedDict()
self._origarrays = OrderedDict(
) # used for presenting raw data tables in HKLviewer
basearraylabels = []
if base_array_info is not None:
self.crystal_symmetry = self.crystal_symmetry.join_symmetry(
other_symmetry=base_array_info.crystal_symmetry_from_file,
force=True)
if base_array_info.labels:
basearraylabels = base_array_info.labels
if (wavelengths is None):
wavelengths = {}
if base_array_info is None:
base_array_info = miller.array_info(source_type="cif")
refln_containing_loops = self.get_miller_indices_containing_loops()
for self.indices, refln_loop in refln_containing_loops:
self.wavelength_id_array = None
self.crystal_id_array = None
self.scale_group_array = None
wavelength_ids = [None]
crystal_ids = [None]
scale_groups = [None]
for key, value in six.iteritems(refln_loop):
# Get wavelength_ids, crystal_id, scale_group_code columns for selecting data of other
# columns in self.get_selection() used by self.flex_std_string_as_miller_array()
if (key.endswith('wavelength_id') or key.endswith('crystal_id')
or key.endswith('scale_group_code')):
data = as_int_or_none_if_all_question_marks(
value, column_name=key)
if data is None:
continue
counts = data.counts()
if key.endswith('wavelength_id'):
wavelength_ids = list(counts.keys())
if len(counts) == 1: continue
array = miller.array(
miller.set(self.crystal_symmetry,
self.indices).auto_anomalous(), data)
if key.endswith('wavelength_id'):
self.wavelength_id_array = array
wavelength_ids = list(counts.keys())
elif key.endswith('crystal_id'):
self.crystal_id_array = array
crystal_ids = list(counts.keys())
elif key.endswith('scale_group_code'):
self.scale_group_array = array
scale_groups = list(counts.keys())
labelsuffix = []
wavelbl = []
cryslbl = []
scalegrplbl = []
self._origarrays["HKLs"] = self.indices
alllabels = list(sorted(refln_loop.keys()))
remaininglabls = alllabels[:] # deep copy the list
# Parse labels matching cif column conventions
# https://mmcif.wwpdb.org/dictionaries/mmcif_pdbx_v50.dic/Categories/refln.html
# and extract groups of labels or just single columns.
# Groups corresponds to the map coefficients, phase and amplitudes,
# amplitudes or intensities with sigmas and hendrickson-lattman columns.
phaseamplabls, remaininglabls = self.get_phase_amplitude_labels(
remaininglabls)
mapcoefflabls, remaininglabls = self.get_mapcoefficient_labels(
remaininglabls)
HLcoefflabls, remaininglabls = self.get_HL_labels(remaininglabls)
data_sig_obstype_labls, remaininglabls = self.get_FSigF_ISigI_labels(
remaininglabls)
for w_id in wavelength_ids:
for crys_id in crystal_ids:
for scale_group in scale_groups:
# If reflection data files contain more than one crystal, wavelength or scalegroup
# then add their id(s) as a suffix to data labels computed below. Needed for avoiding
# ambuguity but avoid when not needed to make labels more human readable!
if (len(wavelength_ids) > 1
or len(wavelengths) > 1) and w_id is not None:
wavelbl = ["wavelength_id=%i" % w_id]
if len(crystal_ids) > 1 and crys_id is not None:
cryslbl = ["crystal_id=%i" % crys_id]
if len(scale_groups) > 1 and scale_group is not None:
scalegrplbl = ["scale_group_code=%i" % scale_group]
labelsuffix = scalegrplbl + cryslbl + wavelbl
jlablsufx = ""
if len(labelsuffix):
jlablsufx = "," + ",".join(labelsuffix)
for mapcoefflabl in mapcoefflabls:
A_array = refln_loop[mapcoefflabl[0]]
B_array = refln_loop[mapcoefflabl[1]]
# deselect any ? marks in the two arrays, assuming both A and B have the same ? marks
selection = self.get_selection(
A_array,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
A_array = A_array.select(selection)
B_array = B_array.select(selection)
# form the miller array with map coefficients
data = flex.complex_double(flex.double(A_array),
flex.double(B_array))
millarr = miller.array(
miller.set(self.crystal_symmetry,
self.indices.select(
selection)).auto_anomalous(),
data)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None: continue
labl = basearraylabels + mapcoefflabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=labl,
wavelength=wavelengths.get(w_id, None)))
self._arrays[mapcoefflabl[0] + jlablsufx] = millarr
for phaseamplabl in phaseamplabls:
amplitudestrarray = refln_loop[phaseamplabl[0]]
phasestrarray = refln_loop[phaseamplabl[1]]
millarr = self.flex_std_string_as_miller_array(
amplitudestrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
phasesmillarr = self.flex_std_string_as_miller_array(
phasestrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None or phasesmillarr is None:
continue
phases = as_flex_double(phasesmillarr,
phaseamplabl[1])
millarr = millarr.phase_transfer(phases, deg=True)
labl = basearraylabels + phaseamplabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=labl,
wavelength=wavelengths.get(w_id, None)))
self._arrays[phaseamplabl[0] + jlablsufx] = millarr
for datlabl, siglabl, otype in data_sig_obstype_labls:
datastrarray = refln_loop[datlabl]
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None: continue
millarr = as_flex_double(millarr, datlabl)
datsiglabl = [datlabl]
if siglabl:
sigmasstrarray = refln_loop[siglabl]
sigmas = self.flex_std_string_as_miller_array(
sigmasstrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
sigmas = as_flex_double(sigmas, siglabl)
millarr.set_sigmas(sigmas.data())
datsiglabl = [datlabl, siglabl]
datsiglabl = basearraylabels + datsiglabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=datsiglabl,
wavelength=wavelengths.get(w_id, None)))
if otype is not None:
millarr.set_observation_type(otype)
self._arrays[datlabl + jlablsufx] = millarr
for hl_labels in HLcoefflabls:
hl_values = [
cif_block.get(hl_key) for hl_key in hl_labels
]
if hl_values.count(None) == 0:
selection = self.get_selection(
hl_values[0],
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
hl_values = [
as_double_or_none_if_all_question_marks(
hl.select(selection), column_name=lab)
for hl, lab in zip(hl_values, hl_labels)
]
# hl_values will be None for column data not matching w_id,crys_id,scale_group values
if hl_values == [None, None, None, None]:
continue
millarr = miller.array(
miller.set(
self.crystal_symmetry,
self.indices.select(
selection)).auto_anomalous(),
flex.hendrickson_lattman(*hl_values))
hlabels = basearraylabels + hl_labels + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=hlabels,
wavelength=wavelengths.get(w_id,
None)))
self._arrays[hl_labels[0] +
jlablsufx] = millarr
# pick up remaining columns if any that weren't identified above
for label in alllabels:
if "index_" in label:
continue
datastrarray = refln_loop[label]
if label in remaininglabls:
labels = basearraylabels + [label
] + labelsuffix
lablsufx = jlablsufx
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if (label.endswith(
'wavelength_id'
) or label.endswith(
'crystal_id'
) or # get full array if any of these labels, not just subsets
label.endswith('scale_group_code')):
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=None,
crystal_id=None,
scale_group_code=None)
lablsufx = ""
labels = basearraylabels + [label]
if millarr is None: continue
otype = self.guess_observationtype(label)
if otype is not None:
millarr.set_observation_type(otype)
millarr.set_info(
base_array_info.customized_copy(
labels=labels,
wavelength=wavelengths.get(w_id,
None)))
self._arrays[label + lablsufx] = millarr
origarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
newlabel = label.replace("_refln.", "")
newlabel2 = newlabel.replace("_refln_", "")
if origarr: # want only genuine miller arrays
self._origarrays[newlabel2 +
jlablsufx] = origarr.data()
# Convert any groups of I+,I-,SigI+,SigI- (or amplitudes) arrays into anomalous arrays
# i.e. both friedel mates in the same array
for key, array in six.iteritems(self._arrays.copy()):
plus_key = ""
if '_minus' in key:
minus_key = key
plus_key = key.replace('_minus', '_plus')
elif '-' in key:
minus_key = key
plus_key = key.replace('-', '+')
elif '_plus' in key:
plus_key = key
minus_key = key.replace('_plus', '_minus')
elif '+' in key:
plus_key = key
minus_key = key.replace('+', '-')
if plus_key in self._arrays and minus_key in self._arrays:
plus_array = self._arrays.pop(plus_key)
minus_array = self._arrays.pop(minus_key)
minus_array = minus_array.customized_copy(
indices=-minus_array.indices()).set_info(
minus_array.info())
array = plus_array.concatenate(
minus_array, assert_is_similar_symmetry=False)
array = array.customized_copy(anomalous_flag=True)
array.set_info(minus_array.info().customized_copy(labels=list(
OrderedSet(plus_array.info().labels +
minus_array.info().labels))))
array.set_observation_type(plus_array.observation_type())
self._arrays.setdefault(key, array)
if len(self._arrays) == 0:
raise CifBuilderError("No reflection data present in cif block")
# Sort the ordered dictionary to resemble the order of columns in the cif file
# This is to avoid any F_meas arrays accidentally being put adjacent to
# pdbx_anom_difference arrays in the self._arrays OrderedDict. Otherwise these
# arrays may unintentionally be combined into a reconstructed anomalous amplitude
# array when saving as an mtz file due to a problem in the iotbx/mtz module.
# See http://phenix-online.org/pipermail/cctbxbb/2021-March/002289.html
arrlstord = []
arrlst = list(self._arrays)
for arr in arrlst:
for i, k in enumerate(refln_loop.keys()):
if arr.split(",")[0] == k:
arrlstord.append((arr, i))
# arrlstord must have the same keys as in the self._arrays dictionary
assert sorted(arrlst) == sorted([e[0] for e in arrlstord])
sortarrlst = sorted(arrlstord, key=lambda arrord: arrord[1])
self._ordarrays = OrderedDict()
for sortkey, i in sortarrlst:
self._ordarrays.setdefault(sortkey, self._arrays[sortkey])
self._arrays = self._ordarrays
def get_HL_labels(self, keys):
lstkeys = list(keys) # cast into list if not a list
HLquads = []
alllabels = " ".join(lstkeys)
""" Hendrickson-Lattmann labels could look like: 'HLAM', 'HLBM', 'HLCM', 'HLDM'
or like 'HLanomA', 'HLanomB', 'HLanomC', 'HLanomD'
Use a regular expression to group them accordingly
"""
allmatches = re.findall(r"(\S*(HL(\S*)[abcdABCD](\S*)))", alllabels)
HLtagslst = list(set([(e[2], e[3]) for e in allmatches]))
usedkeys = []
for m in HLtagslst:
hllist = []
for hm in allmatches:
if m == (hm[2], hm[3]):
hllist.append((hm[0], hm[1]))
if len(hllist) == 4:
HLquads.append([e[0] for e in hllist])
for e in hllist:
usedkeys.append(e[0])
remainingkeys = []
for e in lstkeys:
if e not in usedkeys:
remainingkeys.append(e)
return HLquads, remainingkeys
def get_mapcoefficient_labels(self, keys):
# extract map coeffficients labels from list of cif column labels
# e.g. ( _refln.A_calc_au _refln.B_calc_au ) , ( _refln.A_calc _refln.B_calc )
lstkeys = list(keys) # cast into list if not a list
remainingkeys = lstkeys[:] # deep copy the list
alllabels = " ".join(lstkeys)
mapcoefflabels = []
A_matches = re.findall(
r"( (\s*_refln[\._]A_)(\S*) )", alllabels, re.VERBOSE
) # [('_refln.PHWT', '_refln.PH', 'WT'), ('_refln.PHDELWT', '_refln.PH', 'DELWT')]
for label in lstkeys:
for m in A_matches:
Blabel = m[1].replace("A_", "B_") + m[2]
if Blabel == label:
mapcoefflabels.append([m[0], label])
remainingkeys.remove(m[0])
remainingkeys.remove(label)
return mapcoefflabels, remainingkeys
def get_phase_amplitude_labels(self, keys):
# extract phase and amplitudes labels from list of cif column labels
# e.g. ( _refln.F_calc _refln.phase_calc ) , ( _refln.FC_ALL _refln.PHIC_ALL ), ( _refln.FWT _refln.PHWT )
lstkeys = list(keys) # cast into list if not a list
remainingkeys = lstkeys[:] # deep copy the list
alllabels = " ".join(lstkeys)
phase_amplitudelabels = []
PHmatches = re.findall(
r"((\S*PH)([^I]\S*))", alllabels
) # [('_refln.PHWT', '_refln.PH', 'WT'), ('_refln.PHDELWT', '_refln.PH', 'DELWT')]
for label in lstkeys:
for m in PHmatches:
PFlabel = m[1].replace("PH", "F") + m[2]
Flabel = m[1].replace("PH", "") + m[2]
if Flabel == label or PFlabel == label:
phase_amplitudelabels.append([label, m[0]])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
alllabels = " ".join(remainingkeys)
PHImatches = re.findall(
r"((\S*PHI)(\S*))", alllabels
) # [('_refln.PHIC', '_refln.PHI', 'C'), ('_refln.PHIC_ALL', '_refln.PHI', 'C_ALL')]
for label in lstkeys:
for m in PHImatches:
PFlabel = m[1].replace("PHI", "F") + m[2]
Flabel = m[1].replace("PHI", "") + m[2]
if Flabel == label or PFlabel == label:
phase_amplitudelabels.append([label, m[0]])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
alllabels = " ".join(remainingkeys)
PHDELmatches = re.findall(
r"(((\S*)PH)([^I]\S*(WT)))", alllabels
) # [('_refln.PHDELWT', '_refln.PH', '_refln.', 'DELWT', 'WT')]
for label in lstkeys:
for m in PHDELmatches:
Flabel = m[2] + m[3].replace("WT", "FWT")
if Flabel == label:
phase_amplitudelabels.append([label, m[0]])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
alllabels = " ".join(remainingkeys)
phase_matches = re.findall(
r"((\S*[\._])phase(\S*))",
alllabels) # [('_refln.phase_calc', '_refln.', '')]
for label in lstkeys:
for m in phase_matches:
phaselabel = m[0]
Flabl = m[1] + m[2]
Flabel = m[1] + "F" + m[2]
Faulabel = m[1] + "F" + m[2] + "_au"
if Flabl in label or Flabel in label or Faulabel in label: # in case of _refln.F_calc_au and _refln.phase_calc
if label in remainingkeys and m[
0] in remainingkeys: # in case
if (Flabel + "_sigma_au") in remainingkeys or (
Flabel + "_sigma") in remainingkeys:
continue # give priority to F_meas, F_meas_sigma or F_meas_au, F_meas_sigma_au
phase_amplitudelabels.append([label, m[0]])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
return phase_amplitudelabels, remainingkeys
def get_FSigF_ISigI_labels(self, keys):
# extract amplitudea, sigmas or intensitiy, sigmas labels from list of cif column labels
# e.g. ( _refln.F_meas_sigma_au _refln.F_meas), ( _refln.intensity_sigma _refln.intensity ) ,
# ( _refln.pdbx_I_plus_sigma _refln.pdbx_I_plus )
lstkeys = list(keys) # cast into list if not a list
remainingkeys = lstkeys[:] # deep copy the list
alllabels = " ".join(lstkeys)
labelpairs = []
sigma_matches = re.findall(
r"((\S*[\._])SIG(\S*))",
alllabels) # catch label pairs like F(+),SIGF(+)
for label in lstkeys:
for m in sigma_matches:
FIlabel = m[1] + m[2]
if FIlabel == label:
labelpairs.append(
[label, m[0],
self.guess_observationtype(label)])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
alllabels = " ".join(remainingkeys)
sigma_matches = re.findall(
r"((\S*)_sigma(_*\S*))", alllabels
) # [('_refln.F_meas_sigma_au', '_refln.F_meas', '_au'), ('_refln.intensity_sigma', '_refln.intensity', ''), ('_refln.pdbx_I_plus_sigma', '_refln.pdbx_I_plus', '')]
for label in lstkeys:
for m in sigma_matches:
FIlabel = m[1] + m[2]
if FIlabel == label:
labelpairs.append(
[label, m[0],
self.guess_observationtype(label)])
remainingkeys.remove(label)
remainingkeys.remove(m[0])
alllabels = " ".join(remainingkeys)
# catch generic meas and sigma labels
anymeas_matches = re.findall(r"((\S*)_meas(\S*))",
alllabels) + re.findall(
r"((\S*)_calc(\S*))", alllabels)
anysigma_matches = re.findall(r"((\S*)_sigma(\S*))", alllabels)
for mmatch in anymeas_matches:
for smatch in anysigma_matches:
if mmatch[1] == smatch[1] and mmatch[2] == smatch[2]:
remainingkeys.remove(mmatch[0])
if smatch[
0] in remainingkeys: # in case of say F_squared_calc, F_squared_meas, F_squared_sigma all being present
remainingkeys.remove(smatch[0])
labelpairs.append([
mmatch[0], smatch[0],
self.guess_observationtype(mmatch[0])
])
else:
labelpairs.append([
mmatch[0], None,
self.guess_observationtype(mmatch[0])
])
return labelpairs, remainingkeys
def get_miller_indices_containing_loops(self):
loops = []
for loop in self.cif_block.loops.values():
for key in loop.keys():
if 'index_h' not in key: continue
hkl_str = [
loop.get(key.replace('index_h', 'index_%s' % i))
for i in 'hkl'
]
if hkl_str.count(None) > 0:
raise CifBuilderError(
"Miller indices missing from current CIF block (%s)" %
key.replace('index_h',
'index_%s' % 'hkl'[hkl_str.index(None)]))
hkl_int = []
for i, h_str in enumerate(hkl_str):
try:
h_int = flex.int(h_str)
except ValueError as e:
raise CifBuilderError(
"Invalid item for Miller index %s: %s" %
("HKL"[i], str(e)))
hkl_int.append(h_int)
indices = flex.miller_index(*hkl_int)
loops.append((indices, loop))
break
return loops
def get_selection(self,
value,
wavelength_id=None,
crystal_id=None,
scale_group_code=None):
selection = ~((value == '.') | (value == '?'))
if self.wavelength_id_array is not None and wavelength_id is not None:
selection &= (self.wavelength_id_array.data() == wavelength_id)
if self.crystal_id_array is not None and crystal_id is not None:
selection &= (self.crystal_id_array.data() == crystal_id)
if self.scale_group_array is not None and scale_group_code is not None:
selection &= (self.scale_group_array.data() == scale_group_code)
return selection
def flex_std_string_as_miller_array(self,
value,
wavelength_id=None,
crystal_id=None,
scale_group_code=None):
# Create a miller_array object of only the data and indices matching the
# wavelength_id, crystal_id and scale_group_code submitted or full array if these are None
selection = self.get_selection(value,
wavelength_id=wavelength_id,
crystal_id=crystal_id,
scale_group_code=scale_group_code)
data = value.select(selection)
#if not isinstance(data, flex.double):
try:
data = flex.int(data)
indices = self.indices.select(selection)
except ValueError:
try:
data = flex.double(data)
indices = self.indices.select(selection)
except ValueError:
# if flex.std_string return all values including '.' and '?'
data = value
indices = self.indices
if data.size() == 0: return None
return miller.array(
miller.set(self.crystal_symmetry, indices).auto_anomalous(), data)
def arrays(self):
return self._arrays
def origarrays(self):
"""
return dictionary of raw data found in cif file cast into flex.double arrays
or just string arrays as a fall back.
"""
return self._origarrays
def get_raw_data(self):
if self._raw_data is None:
import numpy
from scitbx.array_family import flex
from libtbx.containers import OrderedDict
self._raw_data = []
cbf = self._get_cbf_handle()
cbf.find_category('array_structure')
cbf.find_column('encoding_type')
cbf.select_row(0)
types = []
for i in xrange(cbf.count_rows()):
types.append(cbf.get_value())
cbf.next_row()
assert len(types) == cbf.count_rows()
# read the data
data = OrderedDict()
cbf.find_category("array_data")
for i in xrange(cbf.count_rows()):
cbf.find_column("array_id")
name = cbf.get_value()
cbf.find_column("data")
assert cbf.get_typeofvalue().find('bnry') > -1
if types[i] == 'signed 32-bit integer':
array_string = cbf.get_integerarray_as_string()
array = flex.int(
numpy.fromstring(array_string, numpy.int32))
parameters = cbf.get_integerarrayparameters_wdims_fs()
array_size = (parameters[11], parameters[10],
parameters[9])
elif types[i] == 'signed 64-bit real IEEE':
array_string = cbf.get_realarray_as_string()
array = flex.double(
numpy.fromstring(array_string, numpy.float))
parameters = cbf.get_realarrayparameters_wdims_fs()
array_size = (parameters[7], parameters[6], parameters[5])
else:
return None # type not supported
array.reshape(flex.grid(*array_size))
data[name] = array
cbf.next_row()
# extract the data for each panel
if cbf.has_sections():
section_shapes = OrderedDict()
for i in xrange(cbf.count_rows()):
cbf.find_column("id")
section_name = cbf.get_value()
if not section_name in section_shapes:
section_shapes[section_name] = {}
cbf.find_column("array_id")
if not "array_id" in section_shapes[section_name]:
section_shapes[section_name][
"array_id"] = cbf.get_value()
else:
assert section_shapes[section_name][
"array_id"] == cbf.get_value()
cbf.find_column("index")
axis_index = int(cbf.get_value()) - 1
cbf.find_column("start")
axis_start = int(cbf.get_value()) - 1
cbf.find_column("end")
axis_end = int(cbf.get_value())
section_shapes[section_name][axis_index] = slice(
axis_start, axis_end)
cbf.next_row()
for section_name in section_shapes:
section_shape = section_shapes[section_name]
section = data[section_shape["array_id"]][ \
section_shape[2], section_shape[1], section_shape[0]]
section.reshape(
flex.grid(section.focus()[-2],
section.focus()[-1]))
self._raw_data.append(section)
else:
for key in data:
data[key].reshape(
flex.grid(data[key].focus()[-2],
data[key].focus()[-1]))
self._raw_data.append(data[key])
d = self.get_detector()
assert len(d) == len(self._raw_data)
return tuple(self._raw_data)
def __init__(self, pdb_hierarchy,
sequences,
alignment_params=None,
crystal_symmetry=None,
coordinate_precision=5,
occupancy_precision=3,
b_iso_precision=5,
u_aniso_precision=5):
pdb_hierarchy_as_cif_block.__init__(
self, pdb_hierarchy, crystal_symmetry=crystal_symmetry,
coordinate_precision=coordinate_precision,
occupancy_precision=occupancy_precision,
b_iso_precision=b_iso_precision,
u_aniso_precision=u_aniso_precision)
import mmtbx.validation.sequence
validation = mmtbx.validation.sequence.validation(
pdb_hierarchy=pdb_hierarchy,
sequences=sequences,
params=alignment_params,
extract_residue_groups=True,
log=null_out(), # silence output
)
entity_loop = iotbx.cif.model.loop(header=(
'_entity.id',
'_entity.type',
#'_entity.src_method',
#'_entity.pdbx_description',
'_entity.formula_weight',
'_entity.pdbx_number_of_molecules',
#'_entity.details',
#'_entity.pdbx_mutation',
#'_entity.pdbx_fragment',
#'_entity.pdbx_ec'
))
entity_poly_loop = iotbx.cif.model.loop(header=(
'_entity_poly.entity_id',
'_entity_poly.type',
'_entity_poly.nstd_chirality',
'_entity_poly.nstd_linkage',
'_entity_poly.nstd_monomer',
'_entity_poly.pdbx_seq_one_letter_code',
'_entity_poly.pdbx_seq_one_letter_code_can',
'_entity_poly.pdbx_strand_id',
'_entity_poly.type_details'
))
entity_poly_seq_loop = iotbx.cif.model.loop(header=(
'_entity_poly_seq.entity_id',
'_entity_poly_seq.num',
'_entity_poly_seq.mon_id',
'_entity_poly_seq.hetero',
))
sequence_counts = OrderedDict()
sequence_to_chain_ids = {}
entity_id = 0
sequence_to_entity_id = {}
chain_id_to_entity_id = {}
sequence_to_chains = {}
residue_group_to_seq_num_mapping = {}
aligned_pdb_chains = OrderedSet()
non_polymer_counts = dict_with_default_0()
non_polymer_resname_to_entity_id = OrderedDict()
for chain in validation.chains:
sequence = chain.alignment.b
if sequence not in sequence_to_entity_id:
entity_id += 1
sequence_to_entity_id[sequence] = entity_id
sequence_counts.setdefault(sequence, 0)
sequence_counts[sequence] += 1
sequence_to_chain_ids.setdefault(sequence, [])
sequence_to_chain_ids[sequence].append(chain.chain_id)
sequence_to_chains.setdefault(sequence, [])
sequence_to_chains[sequence].append(chain)
chain_id_to_entity_id[chain.chain_id] = sequence_to_entity_id[sequence]
aligned_pdb_chains.add(chain.residue_groups[0].parent())
unaligned_pdb_chains = OrderedSet(pdb_hierarchy.chains()) - aligned_pdb_chains
assert len(chain.residue_groups) + chain.n_missing_start + chain.n_missing_end == len(sequence)
residue_groups = [None] * chain.n_missing_start + chain.residue_groups + [None] * chain.n_missing_end
i = chain.n_missing_start
seq_num = 0
for i, residue_group in enumerate(residue_groups):
if residue_group is None and chain.alignment.b[i] == '-':
# a deletion
continue
seq_num += 1
if residue_group is not None:
residue_group_to_seq_num_mapping[
residue_group] = seq_num
for pdb_chain in unaligned_pdb_chains:
for residue_group in pdb_chain.residue_groups():
for resname in residue_group.unique_resnames():
if resname not in non_polymer_resname_to_entity_id:
entity_id += 1
non_polymer_resname_to_entity_id[resname] = entity_id
non_polymer_counts[resname] += 1
for sequence, count in sequence_counts.iteritems():
entity_poly_seq_num = 0
entity_id = sequence_to_entity_id[sequence]
entity_loop.add_row((
entity_id,
'polymer', #polymer/non-polymer/macrolide/water
#'?', #src_method
#'?', # pdbx_description
'?', # formula_weight
len(sequence_to_chains[sequence]), # pdbx_number_of_molecules
#'?', # details
#'?', # pdbx_mutation
#'?', # pdbx_fragment
#'?' # pdbx_ec
))
# The definition of the cif item _entity_poly.pdbx_seq_one_letter_code
# says that modifications and non-standard amino acids should be encoded
# as 'X', however in practice the PDB seem to encode them as the three-letter
# code in parentheses.
pdbx_seq_one_letter_code = []
pdbx_seq_one_letter_code_can = []
chains = sequence_to_chains[sequence]
from iotbx.pdb import amino_acid_codes
chain = chains[0]
matches = chain.alignment.matches()
for i, one_letter_code in enumerate(sequence):
#Data items in the ENTITY_POLY_SEQ category specify the sequence
#of monomers in a polymer. Allowance is made for the possibility
#of microheterogeneity in a sample by allowing a given sequence
#number to be correlated with more than one monomer ID. The
#corresponding ATOM_SITE entries should reflect this
#heterogeneity.
monomer_id = None
if i >= chain.n_missing_start and i < (len(sequence) - chain.n_missing_end):
monomer_id = chain.resnames[i-chain.n_missing_start]
if monomer_id is None and one_letter_code == '-': continue
pdbx_seq_one_letter_code_can.append(one_letter_code)
if monomer_id is None:
if sequence_to_chains[sequence][0].chain_type == mmtbx.validation.sequence.PROTEIN:
monomer_id = amino_acid_codes.three_letter_given_one_letter.get(
one_letter_code, "UNK") # XXX
else:
monomer_id = one_letter_code
else:
if sequence_to_chains[sequence][0].chain_type == mmtbx.validation.sequence.PROTEIN:
one_letter_code = amino_acid_codes.one_letter_given_three_letter.get(
monomer_id, "(%s)" %monomer_id)
pdbx_seq_one_letter_code.append(one_letter_code)
entity_poly_seq_num += 1
entity_poly_seq_loop.add_row((
entity_id,
entity_poly_seq_num,
monomer_id,
'no', #XXX
))
entity_poly_type = '?'
entity_nstd_chirality = 'n'
# we should probably determine the chirality more correctly by examining
# the chirality of the backbone chain rather than relying on the residue
# names to be correct
if chain.chain_type == mmtbx.validation.sequence.PROTEIN:
n_d_peptides = 0
n_l_peptides = 0
n_achiral_peptides = 0
n_unknown = 0
for resname in chain.resnames:
if resname == "GLY":
n_achiral_peptides += 1
elif resname in iotbx.pdb.common_residue_names_amino_acid:
n_l_peptides += 1
elif resname in amino_acid_codes.three_letter_l_given_three_letter_d:
n_d_peptides += 1
else:
n_unknown += 1
n_total = sum([n_d_peptides, n_l_peptides, n_achiral_peptides, n_unknown])
if (n_l_peptides + n_achiral_peptides)/n_total > 0.5:
entity_poly_type = 'polypeptide(L)'
if n_d_peptides > 0:
entity_nstd_chirality = 'y'
elif (n_d_peptides + n_achiral_peptides)/n_total > 0.5:
entity_poly_type = 'polypeptide(D)'
if n_l_peptides > 0:
entity_nstd_chirality = 'y'
elif chain.chain_type == mmtbx.validation.sequence.NUCLEIC_ACID:
n_dna = 0
n_rna = 0
n_unknown = 0
for resname in chain.resnames:
if resname is not None and resname.strip().upper() in (
'AD', 'CD', 'GD', 'TD', 'DA', 'DC', 'DG', 'DT'):
n_dna += 1
elif resname is not None and resname.strip().upper() in (
'A', 'C', 'G', 'T', '+A', '+C', '+G', '+T'):
n_rna += 1
else:
n_unknown += 1
n_total = sum([n_dna + n_rna + n_unknown])
if n_dna/n_total > 0.5 and n_rna == 0:
entity_poly_type = 'polydeoxyribonucleotide'
elif n_rna/n_total > 0.5 and n_dna == 0:
entity_poly_type = 'polyribonucleotide'
elif (n_rna + n_dna)/n_total > 0.5:
entity_poly_type = 'polydeoxyribonucleotide/polyribonucleotide hybrid'
entity_poly_loop.add_row((
entity_id,
entity_poly_type,
entity_nstd_chirality,
'no',
'no',
wrap_always("".join(pdbx_seq_one_letter_code), width=80).strip(),
wrap_always("".join(pdbx_seq_one_letter_code_can), width=80).strip(),
','.join(sequence_to_chain_ids[sequence]),
'?'
))
for resname, entity_id in non_polymer_resname_to_entity_id.iteritems():
entity_type = "non-polymer"
if resname == "HOH":
entity_type = "water" # XXX
entity_loop.add_row((
entity_id,
entity_type, #polymer/non-polymer/macrolide/water
#'?', #src_method
#'?', # pdbx_description
'?', # formula_weight
non_polymer_counts[resname], # pdbx_number_of_molecules
#'?', # details
#'?', # pdbx_mutation
#'?', # pdbx_fragment
#'?' # pdbx_ec
))
self.cif_block.add_loop(entity_loop)
self.cif_block.add_loop(entity_poly_loop)
self.cif_block.add_loop(entity_poly_seq_loop)
self.cif_block.update(pdb_hierarchy.as_cif_block())
label_entity_id = self.cif_block['_atom_site.label_entity_id']
auth_seq_id = self.cif_block['_atom_site.auth_seq_id']
ins_code = self.cif_block['_atom_site.pdbx_PDB_ins_code']
auth_asym_id = self.cif_block['_atom_site.auth_asym_id']
label_seq_id = flex.std_string(auth_seq_id.size(), '.')
ins_code = ins_code.deep_copy()
ins_code.set_selected(ins_code == '?', '')
for residue_group, seq_num in residue_group_to_seq_num_mapping.iteritems():
sel = ((auth_asym_id == residue_group.parent().id) &
(ins_code == residue_group.icode.strip()) &
(auth_seq_id == residue_group.resseq.strip()))
label_seq_id.set_selected(sel, str(seq_num))
label_entity_id.set_selected(
sel, str(chain_id_to_entity_id[residue_group.parent().id]))
for pdb_chain in unaligned_pdb_chains:
for residue_group in pdb_chain.residue_groups():
sel = ((auth_asym_id == residue_group.parent().id) &
(ins_code == residue_group.icode.strip()) &
(auth_seq_id == residue_group.resseq.strip()))
label_entity_id.set_selected(
sel, str(non_polymer_resname_to_entity_id[residue_group.unique_resnames()[0]]))
self.cif_block['_atom_site.label_seq_id'] = label_seq_id
# reorder the loops
atom_site_loop = self.cif_block['_atom_site']
atom_site_aniso_loop = self.cif_block.get('_atom_site_anisotrop')
del self.cif_block['_atom_site']
self.cif_block.add_loop(atom_site_loop)
if atom_site_aniso_loop is not None:
del self.cif_block['_atom_site_anisotrop']
self.cif_block.add_loop(atom_site_aniso_loop)
def __init__(self, cif_block):
crystal_symmetry_builder.__init__(self, cif_block)
self.hierarchy = hierarchy.root()
# These items are mandatory for the _atom_site loop, all others are optional
type_symbol = self._wrap_loop_if_needed(cif_block,
"_atom_site.type_symbol")
atom_labels = self._wrap_loop_if_needed(cif_block,
"_atom_site.auth_atom_id")
if atom_labels is None:
atom_labels = self._wrap_loop_if_needed(
cif_block, "_atom_site.label_atom_id"
) # corresponds to chem comp atom name
alt_id = self._wrap_loop_if_needed(
cif_block, "_atom_site.label_alt_id") # alternate conformer id
label_asym_id = self._wrap_loop_if_needed(
cif_block, "_atom_site.label_asym_id") # chain id
auth_asym_id = self._wrap_loop_if_needed(cif_block,
"_atom_site.auth_asym_id")
if label_asym_id is None: label_asym_id = auth_asym_id
if auth_asym_id is None: auth_asym_id = label_asym_id
comp_id = self._wrap_loop_if_needed(cif_block,
"_atom_site.auth_comp_id")
if comp_id is None:
comp_id = self._wrap_loop_if_needed(
cif_block, "_atom_site.label_comp_id") # residue name
entity_id = self._wrap_loop_if_needed(cif_block,
"_atom_site.label_entity_id")
seq_id = self._wrap_loop_if_needed(cif_block, "_atom_site.auth_seq_id")
if seq_id is None:
seq_id = self._wrap_loop_if_needed(
cif_block, "_atom_site.label_seq_id") # residue number
assert [atom_labels, alt_id, auth_asym_id, comp_id, entity_id,
seq_id].count(None) == 0, "something is not present"
assert type_symbol is not None
atom_site_fp = cif_block.get('_atom_site.phenix_scat_dispersion_real')
atom_site_fdp = cif_block.get('_atom_site.phenix_scat_dispersion_imag')
pdb_ins_code = cif_block.get(
"_atom_site.pdbx_PDB_ins_code") # insertion code
model_ids = cif_block.get("_atom_site.pdbx_PDB_model_num")
atom_site_id = cif_block.get("_atom_site.id")
# only permitted values are ATOM or HETATM
group_PDB = cif_block.get("_atom_site.group_PDB")
# TODO: read esds
B_iso_or_equiv = flex.double(
self._wrap_loop_if_needed(cif_block, "_atom_site.B_iso_or_equiv"))
cart_x = flex.double(
self._wrap_loop_if_needed(cif_block, "_atom_site.Cartn_x"))
cart_y = flex.double(
self._wrap_loop_if_needed(cif_block, "_atom_site.Cartn_y"))
cart_z = flex.double(
self._wrap_loop_if_needed(cif_block, "_atom_site.Cartn_z"))
occu = flex.double(
self._wrap_loop_if_needed(cif_block, "_atom_site.occupancy"))
formal_charge = self._wrap_loop_if_needed(
cif_block, "_atom_site.pdbx_formal_charge")
# anisotropic b-factors
# TODO: read esds
anisotrop_id = self._wrap_loop_if_needed(cif_block,
"_atom_site_anisotrop.id")
adps = None
if anisotrop_id is not None:
u_ij = [
self._wrap_loop_if_needed(
cif_block,
"_atom_site_anisotrop.U[%s][%s]" % (ij[0], ij[1]))
for ij in ("11", "22", "33", "12", "13", "23")
]
assert u_ij.count(None) in (0, 6)
if u_ij.count(None) == 0:
adps = u_ij
else:
assert u_ij.count(None) == 6
b_ij = [
self._wrap_loop_if_needed(
cif_block,
"_atom_site_anisotrop.B[%s][%s]" % (ij[0], ij[1]))
for ij in ("11", "22", "33", "12", "13", "23")
]
assert b_ij.count(None) in (0, 6)
if b_ij.count(None) == 0:
adps = adptbx.b_as_u(b_ij)
assert not (u_ij.count(None) and b_ij.count(None)
) # illegal for both to be present
if adps is not None:
try:
adps = [flex.double(adp) for adp in adps]
except ValueError as e:
raise CifBuilderError("Error interpreting ADPs: " + str(e))
adps = flex.sym_mat3_double(*adps)
py_adps = {}
if anisotrop_id is not None and adps is not None:
for an_id, adp in zip(list(anisotrop_id), list(adps)):
py_adps[an_id] = adp
current_model_id = None
current_label_asym_id = None
current_auth_asym_id = None
current_residue_id = None
current_ins_code = None
for i_atom in range(atom_labels.size()):
# model(s)
last_model_id = current_model_id
current_model_id = model_ids[i_atom]
assert current_model_id is not None
if current_model_id != last_model_id:
model = hierarchy.model(id=current_model_id)
self.hierarchy.append_model(model)
# chain(s)
last_label_asym_id = current_label_asym_id
current_label_asym_id = label_asym_id[i_atom]
assert current_label_asym_id is not None
last_auth_asym_id = current_auth_asym_id
current_auth_asym_id = auth_asym_id[i_atom]
assert current_auth_asym_id not in [".", "?", " "], "mmCIF file contains " + \
"record with empty auth_asym_id, which is wrong."
assert current_label_asym_id is not None
if (current_auth_asym_id != last_auth_asym_id
or current_model_id != last_model_id):
chain = hierarchy.chain(id=current_auth_asym_id)
model.append_chain(chain)
else:
assert current_auth_asym_id == last_auth_asym_id
# residue_group(s)
# defined by residue id and insertion code
last_residue_id = current_residue_id
current_residue_id = seq_id[i_atom]
assert current_residue_id is not None
last_ins_code = current_ins_code
if pdb_ins_code is not None:
current_ins_code = pdb_ins_code[i_atom]
if current_ins_code in ("?", ".", None): current_ins_code = " "
if (current_residue_id != last_residue_id
or current_ins_code != last_ins_code
or current_auth_asym_id != last_auth_asym_id
or current_model_id != last_model_id):
try:
resseq = hy36encode(width=4, value=int(current_residue_id))
except ValueError as e:
resseq = current_residue_id
assert len(resseq) == 4
residue_group = hierarchy.residue_group(resseq=resseq,
icode=current_ins_code)
chain.append_residue_group(residue_group)
atom_groups = OrderedDict() # reset atom_groups cache
# atom_group(s)
# defined by resname and altloc id
current_altloc = alt_id[i_atom]
if current_altloc == "." or current_altloc == "?":
current_altloc = "" # Main chain atoms
current_resname = comp_id[i_atom]
if (current_altloc, current_resname) not in atom_groups:
atom_group = hierarchy.atom_group(altloc=current_altloc,
resname=current_resname)
atom_groups[(current_altloc, current_resname)] = atom_group
if current_altloc == "":
residue_group.insert_atom_group(0, atom_group)
else:
residue_group.append_atom_group(atom_group)
else:
atom_group = atom_groups[(current_altloc, current_resname)]
# atom(s)
atom = hierarchy.atom()
atom_group.append_atom(atom)
atom.set_element(type_symbol[i_atom])
atom.set_name(
format_pdb_atom_name(atom_labels[i_atom], type_symbol[i_atom]))
atom.set_xyz(new_xyz=(cart_x[i_atom], cart_y[i_atom],
cart_z[i_atom]))
atom.set_b(B_iso_or_equiv[i_atom])
atom.set_occ(occu[i_atom])
# hy36encode should go once the pdb.hierarchy has been
# modified to no longer store fixed-width strings
atom.set_serial(
hy36encode(width=5, value=int(atom_site_id[i_atom])))
# some code relies on an empty segid being 4 spaces
atom.set_segid(" ")
if group_PDB is not None and group_PDB[i_atom] == "HETATM":
atom.hetero = True
if formal_charge is not None:
charge = formal_charge[i_atom]
if charge not in ("?", "."):
if charge.endswith("-") or charge.startswith("-"):
sign = "-"
else:
sign = "+"
charge = charge.strip(" -+")
charge = int(charge)
if charge == 0: sign = ""
atom.set_charge("%i%s" % (charge, sign))
if atom_site_fp is not None:
fp = atom_site_fp[i_atom]
if fp not in ("?", "."):
atom.set_fp(new_fp=float(fp))
if atom_site_fdp is not None:
fdp = atom_site_fdp[i_atom]
if fdp not in ("?", "."):
atom.set_fdp(new_fdp=float(fdp))
if anisotrop_id is not None and adps is not None:
py_u_ij = py_adps.get(atom.serial.strip(), None)
if py_u_ij is not None:
atom.set_uij(py_u_ij)
if len(self.hierarchy.models()) == 1:
# for compatibility with single-model PDB files
self.hierarchy.models()[0].id = ""
def cache_restraint(self, cmd, cmd_residue, line, args):
from libtbx.containers import OrderedDict
if cmd not in self.cached_restraints:
self.cached_restraints.setdefault(cmd, OrderedDict())
self.cached_restraints[cmd].setdefault(line, (cmd_residue, args))
class loop(DictMixin):
def __init__(self, header=None, data=None):
self._columns = OrderedDict()
self.keys_lower = {}
if header is not None:
for key in header:
self.setdefault(key, flex.std_string())
if data is not None:
# the number of data items must be an exact multiple of the number of headers
assert len(data) % len(header) == 0, "Wrong number of data items for loop"
n_rows = len(data)//len(header)
n_columns = len(header)
for i in range(n_rows):
self.add_row([data[i*n_columns+j] for j in range(n_columns)])
elif header is None and data is not None:
assert isinstance(data, dict) or isinstance(data, OrderedDict)
self.add_columns(data)
self.keys_lower = dict(
[(key.lower(), key) for key in self._columns.keys()])
def __setitem__(self, key, value):
if not re.match(tag_re, key):
raise Sorry("%s is not a valid data name" %key)
if len(self) > 0:
assert len(value) == self.size()
if not isinstance(value, flex.std_string):
for flex_numeric_type in (flex.int, flex.double):
if isinstance(value, flex_numeric_type):
value = value.as_string()
else:
try:
value = flex_numeric_type(value).as_string()
except TypeError:
continue
else:
break
if not isinstance(value, flex.std_string):
value = flex.std_string(value)
# value must be a mutable type
assert hasattr(value, '__setitem__')
self._columns[key] = value
self.keys_lower[key.lower()] = key
def __getitem__(self, key):
return self._columns[self.keys_lower[key.lower()]]
def __delitem__(self, key):
del self._columns[self.keys_lower[key.lower()]]
del self.keys_lower[key.lower()]
def keys(self):
return self._columns.keys()
def __repr__(self):
return repr(OrderedDict(self.iteritems()))
def name(self):
return common_substring(self.keys()).rstrip('_').rstrip('.')
def size(self):
size = 0
for column in self.values():
size = max(size, len(column))
return size
def n_rows(self):
size = 0
for column in self.values():
size = max(size, len(column))
return size
def n_columns(self):
return len(self.keys())
def add_row(self, row, default_value="?"):
if isinstance(row, dict):
for key in self:
if key in row:
self[key].append(str(row[key]))
else:
self[key].append(default_value)
else:
assert len(row) == len(self)
for i, key in enumerate(self):
self[key].append(str(row[i]))
def add_column(self, key, values):
if self.size() != 0:
assert len(values) == self.size()
self[key] = values
self.keys_lower[key.lower()] = key
def add_columns(self, columns):
assert isinstance(columns, dict) or isinstance(columns, OrderedDict)
for key, value in columns.iteritems():
self.add_column(key, value)
def update_column(self, key, values):
assert type(key)==type(""), "first argument is column key string"
if self.size() != 0:
assert len(values) == self.size(), "len(values) %d != self.size() %d" % (
len(values),
self.size(),
)
self[key] = values
self.keys_lower[key.lower()] = key
def delete_row(self, index):
assert index < self.n_rows()
for column in self._columns.values():
del column[index]
def __copy__(self):
new = loop()
new._columns = self._columns.copy()
new.keys_lower = self.keys_lower.copy()
return new
copy = __copy__
def __deepcopy__(self, memo):
new = loop()
new._columns = copy.deepcopy(self._columns, memo)
new.keys_lower = copy.deepcopy(self.keys_lower, memo)
return new
def deepcopy(self):
return copy.deepcopy(self)
def show(self, out=None, indent=" ", indent_row=None, fmt_str=None, align_columns=True):
assert self.n_rows() > 0 and self.n_columns() > 0, "keys: %s %d %d" % (
self.keys(),
self.n_rows(),
self.n_columns(),
)
if out is None:
out = sys.stdout
if indent_row is None:
indent_row = indent
assert indent.strip() == ""
assert indent_row.strip() == ""
print >> out, "loop_"
for k in self.keys():
print >> out, indent + k
values = self._columns.values()
if fmt_str is not None:
# Pretty printing:
# The user is responsible for providing a valid format string.
# Values are not quoted - it is the user's responsibility to place
# appropriate quotes in the format string if a particular value may
# contain spaces.
values = copy.deepcopy(values)
for i, v in enumerate(values):
for flex_numeric_type in (flex.int, flex.double):
if not isinstance(v, flex_numeric_type):
try:
values[i] = flex_numeric_type(v)
except ValueError:
continue
else:
break
if fmt_str is None:
fmt_str = indent_row + ' '.join(["%s"]*len(values))
for i in range(self.size()):
print >> out, fmt_str % tuple([values[j][i] for j in range(len(values))])
elif align_columns:
fmt_str = []
for i, (k, v) in enumerate(self.iteritems()):
for i_v in range(v.size()):
v[i_v] = format_value(v[i_v])
# exclude and semicolon text fields from column width calculation
v_ = flex.std_string(item for item in v if "\n" not in item)
width = v_.max_element_length()
# See if column contains only number, '.' or '?'
# right-align numerical columns, left-align everything else
v = v.select(~( (v == ".") | (v == "?") ))
try:
flex.double(v)
except ValueError:
width *= -1
fmt_str.append("%%%is" %width)
fmt_str = indent_row + " ".join(fmt_str)
for i in range(self.size()):
print >> out, (fmt_str %
tuple([values[j][i]
for j in range(len(values))])).rstrip()
else:
for i in range(self.size()):
values_to_print = [format_value(values[j][i]) for j in range(len(values))]
print >> out, ' '.join([indent] + values_to_print)
def __str__(self):
s = StringIO()
self.show(out=s)
return s.getvalue()
def iterrows(self):
keys = self.keys()
for j in range(self.size()):
yield OrderedDict(zip(keys, [self.values()[i][j] for i in range(len(self))]))
def sort(self, key=None, reverse=False):
self._columns = OrderedDict(
sorted(self._columns.items(), key=key, reverse=reverse))
def order(self, order):
def _cmp_key(k1, k2):
for i, o in enumerate(order):
if k1==o: break
for j, o in enumerate(order):
if k2==o: break
if k1<k2: return -1
return 1
keys = self._columns.keys()
keys.sort(_cmp_key)
tmp = OrderedDict()
for o in order:
tmp[o]=self._columns[o]
self._columns = tmp
def __eq__(self, other):
if (len(self) != len(other) or
self.size() != other.size() or
self.keys() != other.keys()):
return False
for value, other_value in zip(self.values(), other.values()):
if (value == other_value).count(True) != len(value):
return False
return True
def __init__(self, cif_block, base_array_info=None, wavelengths=None):
crystal_symmetry_builder.__init__(self, cif_block)
self._arrays = OrderedDict()
self._origarrays = OrderedDict(
) # used for presenting raw data tables in HKLviewer
basearraylabels = []
if base_array_info is not None:
self.crystal_symmetry = self.crystal_symmetry.join_symmetry(
other_symmetry=base_array_info.crystal_symmetry_from_file,
force=True)
if base_array_info.labels:
basearraylabels = base_array_info.labels
if (wavelengths is None):
wavelengths = {}
if base_array_info is None:
base_array_info = miller.array_info(source_type="cif")
refln_containing_loops = self.get_miller_indices_containing_loops()
for self.indices, refln_loop in refln_containing_loops:
self.wavelength_id_array = None
self.crystal_id_array = None
self.scale_group_array = None
wavelength_ids = [None]
crystal_ids = [None]
scale_groups = [None]
for key, value in six.iteritems(refln_loop):
# Get wavelength_ids, crystal_id, scale_group_code columns for selecting data of other
# columns in self.get_selection() used by self.flex_std_string_as_miller_array()
if (key.endswith('wavelength_id') or key.endswith('crystal_id')
or key.endswith('scale_group_code')):
data = as_int_or_none_if_all_question_marks(
value, column_name=key)
if data is None:
continue
counts = data.counts()
if key.endswith('wavelength_id'):
wavelength_ids = list(counts.keys())
if len(counts) == 1: continue
array = miller.array(
miller.set(self.crystal_symmetry,
self.indices).auto_anomalous(), data)
if key.endswith('wavelength_id'):
self.wavelength_id_array = array
wavelength_ids = list(counts.keys())
elif key.endswith('crystal_id'):
self.crystal_id_array = array
crystal_ids = list(counts.keys())
elif key.endswith('scale_group_code'):
self.scale_group_array = array
scale_groups = list(counts.keys())
labelsuffix = []
wavelbl = []
cryslbl = []
scalegrplbl = []
self._origarrays["HKLs"] = self.indices
alllabels = list(sorted(refln_loop.keys()))
remaininglabls = alllabels[:] # deep copy the list
# Parse labels matching cif column conventions
# https://mmcif.wwpdb.org/dictionaries/mmcif_pdbx_v50.dic/Categories/refln.html
# and extract groups of labels or just single columns.
# Groups corresponds to the map coefficients, phase and amplitudes,
# amplitudes or intensities with sigmas and hendrickson-lattman columns.
phaseamplabls, remaininglabls = self.get_phase_amplitude_labels(
remaininglabls)
mapcoefflabls, remaininglabls = self.get_mapcoefficient_labels(
remaininglabls)
HLcoefflabls, remaininglabls = self.get_HL_labels(remaininglabls)
data_sig_obstype_labls, remaininglabls = self.get_FSigF_ISigI_labels(
remaininglabls)
for w_id in wavelength_ids:
for crys_id in crystal_ids:
for scale_group in scale_groups:
# If reflection data files contain more than one crystal, wavelength or scalegroup
# then add their id(s) as a suffix to data labels computed below. Needed for avoiding
# ambuguity but avoid when not needed to make labels more human readable!
if (len(wavelength_ids) > 1
or len(wavelengths) > 1) and w_id is not None:
wavelbl = ["wavelength_id=%i" % w_id]
if len(crystal_ids) > 1 and crys_id is not None:
cryslbl = ["crystal_id=%i" % crys_id]
if len(scale_groups) > 1 and scale_group is not None:
scalegrplbl = ["scale_group_code=%i" % scale_group]
labelsuffix = scalegrplbl + cryslbl + wavelbl
jlablsufx = ""
if len(labelsuffix):
jlablsufx = "," + ",".join(labelsuffix)
for mapcoefflabl in mapcoefflabls:
A_array = refln_loop[mapcoefflabl[0]]
B_array = refln_loop[mapcoefflabl[1]]
# deselect any ? marks in the two arrays, assuming both A and B have the same ? marks
selection = self.get_selection(
A_array,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
A_array = A_array.select(selection)
B_array = B_array.select(selection)
# form the miller array with map coefficients
data = flex.complex_double(flex.double(A_array),
flex.double(B_array))
millarr = miller.array(
miller.set(self.crystal_symmetry,
self.indices.select(
selection)).auto_anomalous(),
data)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None: continue
labl = basearraylabels + mapcoefflabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=labl,
wavelength=wavelengths.get(w_id, None)))
self._arrays[mapcoefflabl[0] + jlablsufx] = millarr
for phaseamplabl in phaseamplabls:
amplitudestrarray = refln_loop[phaseamplabl[0]]
phasestrarray = refln_loop[phaseamplabl[1]]
millarr = self.flex_std_string_as_miller_array(
amplitudestrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
phasesmillarr = self.flex_std_string_as_miller_array(
phasestrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None or phasesmillarr is None:
continue
phases = as_flex_double(phasesmillarr,
phaseamplabl[1])
millarr = millarr.phase_transfer(phases, deg=True)
labl = basearraylabels + phaseamplabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=labl,
wavelength=wavelengths.get(w_id, None)))
self._arrays[phaseamplabl[0] + jlablsufx] = millarr
for datlabl, siglabl, otype in data_sig_obstype_labls:
datastrarray = refln_loop[datlabl]
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if millarr is None: continue
millarr = as_flex_double(millarr, datlabl)
datsiglabl = [datlabl]
if siglabl:
sigmasstrarray = refln_loop[siglabl]
sigmas = self.flex_std_string_as_miller_array(
sigmasstrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
sigmas = as_flex_double(sigmas, siglabl)
millarr.set_sigmas(sigmas.data())
datsiglabl = [datlabl, siglabl]
datsiglabl = basearraylabels + datsiglabl + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=datsiglabl,
wavelength=wavelengths.get(w_id, None)))
if otype is not None:
millarr.set_observation_type(otype)
self._arrays[datlabl + jlablsufx] = millarr
for hl_labels in HLcoefflabls:
hl_values = [
cif_block.get(hl_key) for hl_key in hl_labels
]
if hl_values.count(None) == 0:
selection = self.get_selection(
hl_values[0],
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
hl_values = [
as_double_or_none_if_all_question_marks(
hl.select(selection), column_name=lab)
for hl, lab in zip(hl_values, hl_labels)
]
# hl_values will be None for column data not matching w_id,crys_id,scale_group values
if hl_values == [None, None, None, None]:
continue
millarr = miller.array(
miller.set(
self.crystal_symmetry,
self.indices.select(
selection)).auto_anomalous(),
flex.hendrickson_lattman(*hl_values))
hlabels = basearraylabels + hl_labels + labelsuffix
millarr.set_info(
base_array_info.customized_copy(
labels=hlabels,
wavelength=wavelengths.get(w_id,
None)))
self._arrays[hl_labels[0] +
jlablsufx] = millarr
# pick up remaining columns if any that weren't identified above
for label in alllabels:
if "index_" in label:
continue
datastrarray = refln_loop[label]
if label in remaininglabls:
labels = basearraylabels + [label
] + labelsuffix
lablsufx = jlablsufx
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
# millarr will be None for column data not matching w_id,crys_id,scale_group values
if (label.endswith(
'wavelength_id'
) or label.endswith(
'crystal_id'
) or # get full array if any of these labels, not just subsets
label.endswith('scale_group_code')):
millarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=None,
crystal_id=None,
scale_group_code=None)
lablsufx = ""
labels = basearraylabels + [label]
if millarr is None: continue
otype = self.guess_observationtype(label)
if otype is not None:
millarr.set_observation_type(otype)
millarr.set_info(
base_array_info.customized_copy(
labels=labels,
wavelength=wavelengths.get(w_id,
None)))
self._arrays[label + lablsufx] = millarr
origarr = self.flex_std_string_as_miller_array(
datastrarray,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
newlabel = label.replace("_refln.", "")
newlabel2 = newlabel.replace("_refln_", "")
if origarr: # want only genuine miller arrays
self._origarrays[newlabel2 +
jlablsufx] = origarr.data()
# Convert any groups of I+,I-,SigI+,SigI- (or amplitudes) arrays into anomalous arrays
# i.e. both friedel mates in the same array
for key, array in six.iteritems(self._arrays.copy()):
plus_key = ""
if '_minus' in key:
minus_key = key
plus_key = key.replace('_minus', '_plus')
elif '-' in key:
minus_key = key
plus_key = key.replace('-', '+')
elif '_plus' in key:
plus_key = key
minus_key = key.replace('_plus', '_minus')
elif '+' in key:
plus_key = key
minus_key = key.replace('+', '-')
if plus_key in self._arrays and minus_key in self._arrays:
plus_array = self._arrays.pop(plus_key)
minus_array = self._arrays.pop(minus_key)
minus_array = minus_array.customized_copy(
indices=-minus_array.indices()).set_info(
minus_array.info())
array = plus_array.concatenate(
minus_array, assert_is_similar_symmetry=False)
array = array.customized_copy(anomalous_flag=True)
array.set_info(minus_array.info().customized_copy(labels=list(
OrderedSet(plus_array.info().labels +
minus_array.info().labels))))
array.set_observation_type(plus_array.observation_type())
self._arrays.setdefault(key, array)
if len(self._arrays) == 0:
raise CifBuilderError("No reflection data present in cif block")
# Sort the ordered dictionary to resemble the order of columns in the cif file
# This is to avoid any F_meas arrays accidentally being put adjacent to
# pdbx_anom_difference arrays in the self._arrays OrderedDict. Otherwise these
# arrays may unintentionally be combined into a reconstructed anomalous amplitude
# array when saving as an mtz file due to a problem in the iotbx/mtz module.
# See http://phenix-online.org/pipermail/cctbxbb/2021-March/002289.html
arrlstord = []
arrlst = list(self._arrays)
for arr in arrlst:
for i, k in enumerate(refln_loop.keys()):
if arr.split(",")[0] == k:
arrlstord.append((arr, i))
# arrlstord must have the same keys as in the self._arrays dictionary
assert sorted(arrlst) == sorted([e[0] for e in arrlstord])
sortarrlst = sorted(arrlstord, key=lambda arrord: arrord[1])
self._ordarrays = OrderedDict()
for sortkey, i in sortarrlst:
self._ordarrays.setdefault(sortkey, self._arrays[sortkey])
self._arrays = self._ordarrays
class cif(DictMixin):
def __init__(self, blocks=None):
self._errors = None
if blocks is not None:
self.blocks = OrderedDict(blocks)
else:
self.blocks = OrderedDict()
self.keys_lower = dict([(key.lower(), key) for key in self.blocks.keys()])
def __setitem__(self, key, value):
assert isinstance(value, block)
if not re.match(tag_re, '_'+key):
raise Sorry("%s is not a valid data block name" %key)
self.blocks[key] = value
self.keys_lower[key.lower()] = key
def get(self, key, default=None):
key_lower = self.keys_lower.get(key.lower())
if (key_lower is None):
return default
return self.blocks.get(key_lower, default)
def __getitem__(self, key):
result = self.get(key)
if (result is None):
raise KeyError('Unknown CIF data block name: "%s"' % key)
return result
def __delitem__(self, key):
del self.blocks[self.keys_lower[key.lower()]]
del self.keys_lower[key.lower()]
def keys(self):
return self.blocks.keys()
def __repr__(self):
return repr(OrderedDict(self.iteritems()))
def __copy__(self):
return cif(self.blocks.copy())
copy = __copy__
def __deepcopy__(self, memo):
return cif(copy.deepcopy(self.blocks, memo))
def deepcopy(self):
return copy.deepcopy(self)
def show(self, out=None, indent=" ", indent_row=None,
data_name_field_width=34,
loop_format_strings=None,
align_columns=True):
if out is None:
out = sys.stdout
for name, block in self.items():
print >> out, "data_%s" %name
block.show(
out=out, indent=indent, indent_row=indent_row,
data_name_field_width=data_name_field_width,
loop_format_strings=loop_format_strings,
align_columns=align_columns)
def __str__(self):
s = StringIO()
self.show(out=s)
return s.getvalue()
def validate(self, dictionary, show_warnings=True, error_handler=None, out=None):
if out is None: out = sys.stdout
from iotbx.cif import validation
self._errors = {}
if error_handler is None:
error_handler = validation.ErrorHandler()
for key, block in self.blocks.iteritems():
error_handler = error_handler.__class__()
dictionary.set_error_handler(error_handler)
block.validate(dictionary)
self._errors.setdefault(key, error_handler)
if error_handler.error_count or error_handler.warning_count:
error_handler.show(show_warnings=show_warnings, out=out)
return error_handler
def get_errors(self):
return self._errors
def sort(self, recursive=False, key=None, reverse=False):
self.blocks = OrderedDict(sorted(self.blocks.items(), key=key, reverse=reverse))
if recursive:
for b in self.blocks.values():
b.sort(recursive=recursive, reverse=reverse)
def __init__(self, cif_block, base_array_info=None, wavelengths=None):
crystal_symmetry_builder.__init__(self, cif_block)
if base_array_info is not None:
self.crystal_symmetry = self.crystal_symmetry.join_symmetry(
other_symmetry=base_array_info.crystal_symmetry_from_file,
force=True)
self._arrays = OrderedDict()
if (wavelengths is None):
wavelengths = {}
if base_array_info is None:
base_array_info = miller.array_info(source_type="cif")
refln_containing_loops = self.get_miller_indices_containing_loops()
for self.indices, refln_loop in refln_containing_loops:
self.wavelength_id_array = None
self.crystal_id_array = None
self.scale_group_array = None
wavelength_ids = [None]
crystal_ids = [None]
scale_groups = [None]
for key, value in refln_loop.iteritems():
# need to get these arrays first
if (key.endswith('wavelength_id') or key.endswith('crystal_id')
or key.endswith('scale_group_code')):
data = as_int_or_none_if_all_question_marks(
value, column_name=key)
if data is None:
continue
counts = data.counts()
if key.endswith('wavelength_id'):
wavelength_ids = counts.keys()
if len(counts) == 1: continue
array = miller.array(
miller.set(self.crystal_symmetry,
self.indices).auto_anomalous(), data)
if key.endswith('wavelength_id'):
self.wavelength_id_array = array
wavelength_ids = counts.keys()
elif key.endswith('crystal_id'):
self.crystal_id_array = array
crystal_ids = counts.keys()
elif key.endswith('scale_group_code'):
self.scale_group_array = array
scale_groups = counts.keys()
for label, value in sorted(refln_loop.items()):
for w_id in wavelength_ids:
for crys_id in crystal_ids:
for scale_group in scale_groups:
if 'index_' in label: continue
key = label
labels = [label]
wavelength = None
if (key.endswith('wavelength_id')
or key.endswith('crystal_id')
or key.endswith('scale_group_code')):
w_id = None
crys_id = None
scale_group = None
key_suffix = ''
if w_id is not None:
key_suffix += '_%i' % w_id
labels.insert(0, "wavelength_id=%i" % w_id)
wavelength = wavelengths.get(w_id, None)
if crys_id is not None:
key_suffix += '_%i' % crys_id
labels.insert(0, "crystal_id=%i" % crys_id)
if scale_group is not None:
key_suffix += '_%i' % scale_group
labels.insert(
0, "scale_group_code=%i" % scale_group)
key += key_suffix
sigmas = None
if key in self._arrays: continue
array = self.flex_std_string_as_miller_array(
value,
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
if array is None: continue
if '_sigma' in key:
sigmas_label = label
key = None
for suffix in ('', '_meas', '_calc'):
if sigmas_label.replace(
'_sigma', suffix) in refln_loop:
key = sigmas_label.replace(
'_sigma', suffix) + key_suffix
break
if key is None:
key = sigmas_label + key_suffix
elif key in self._arrays and self._arrays[
key].sigmas() is None:
sigmas = array
array = self._arrays[key]
if (not check_array_sizes(
array, sigmas, key, sigmas_label)):
continue
sigmas = as_flex_double(
sigmas, sigmas_label)
array.set_sigmas(sigmas.data())
info = array.info()
array.set_info(
info.customized_copy(
labels=info.labels +
[sigmas_label],
wavelength=wavelength))
continue
elif 'PHWT' in key:
phwt_label = label
fwt_label = label.replace('PHWT', 'FWT')
if fwt_label not in refln_loop: continue
phwt_array = array
if fwt_label in self._arrays:
array = self._arrays[fwt_label]
if (not check_array_sizes(
array, phwt_array, fwt_label,
phwt_label)):
continue
phases = as_flex_double(
phwt_array, phwt_label)
info = array.info()
array = array.phase_transfer(phases,
deg=True)
array.set_info(
info.customized_copy(
labels=info.labels + [phwt_label]))
self._arrays[fwt_label] = array
continue
elif 'HL_' in key:
hl_letter = key[key.find('HL_') + 3]
hl_key = 'HL_' + hl_letter
key = key.replace(hl_key, 'HL_A')
if key in self._arrays:
continue # this array is already dealt with
hl_labels = [
label.replace(hl_key, 'HL_' + letter)
for letter in 'ABCD'
]
hl_keys = [
key.replace(hl_key, 'HL_' + letter)
for letter in 'ABCD'
]
hl_values = [
cif_block.get(hl_key)
for hl_key in hl_labels
]
if hl_values.count(None) == 0:
selection = self.get_selection(
hl_values[0],
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
hl_values = [
as_double_or_none_if_all_question_marks(
hl.select(selection),
column_name=lab)
for hl, lab in zip(
hl_values, hl_labels)
]
array = miller.array(
miller.set(
self.crystal_symmetry,
self.indices.select(
selection)).auto_anomalous(),
flex.hendrickson_lattman(*hl_values))
labels = labels[:-1] + hl_labels
elif '.B_' in key or '_B_' in key:
if '.B_' in key:
key, key_b = key.replace('.B_', '.A_'), key
label, label_b = label.replace(
'.B_', '.A_'), label
elif '_B_' in key:
key, key_b = key.replace('_B', '_A'), key
label, label_b = label.replace('_B',
'_A'), label
if key in refln_loop and key_b in refln_loop:
b_part = array.data()
if key in self._arrays:
info = self._arrays[key].info()
a_part = self._arrays[key].data()
self._arrays[key] = self._arrays[
key].array(
data=flex.complex_double(
a_part, b_part))
self._arrays[key].set_info(
info.customized_copy(
labels=info.labels + [key_b]))
continue
elif ('phase_' in key and not "_meas" in key
and self.crystal_symmetry.space_group()
is not None):
alt_key1 = label.replace('phase_', 'F_')
alt_key2 = alt_key1 + '_au'
if alt_key1 in refln_loop:
phase_key = label
key = alt_key1 + key_suffix
elif alt_key2 in refln_loop:
phase_key = label
key = alt_key2 + key_suffix
else:
phase_key = None
if phase_key is not None:
phases = array.data()
if key in self._arrays:
array = self._arrays[key]
array = as_flex_double(array, key)
if (not check_array_sizes(
array, phases, key,
phase_key)):
continue
info = self._arrays[key].info()
self._arrays[
key] = array.phase_transfer(
phases, deg=True)
self._arrays[key].set_info(
info.customized_copy(
labels=info.labels +
[phase_key]))
else:
array = self.flex_std_string_as_miller_array(
refln_loop[label],
wavelength_id=w_id,
crystal_id=crys_id,
scale_group_code=scale_group)
if (not check_array_sizes(
array, phases, key,
phase_key)):
continue
array.phase_transfer(phases, deg=True)
labels = labels + [label, phase_key]
if base_array_info.labels is not None:
labels = base_array_info.labels + labels
def rstrip_substrings(string, substrings):
for substr in substrings:
if substr == '': continue
if string.endswith(substr):
string = string[:-len(substr)]
return string
# determine observation type
stripped_key = rstrip_substrings(
key, [
key_suffix, '_au', '_meas', '_calc',
'_plus', '_minus'
])
if (stripped_key.endswith('F_squared')
or stripped_key.endswith('intensity')
or stripped_key.endswith('.I')
or stripped_key.endswith('_I')) and (
array.is_real_array()
or array.is_integer_array()):
array.set_observation_type_xray_intensity()
elif (stripped_key.endswith('F')
and (array.is_real_array()
or array.is_integer_array())):
array.set_observation_type_xray_amplitude()
if (array.is_xray_amplitude_array()
or array.is_xray_amplitude_array()):
# e.g. merge_equivalents treats integer arrays differently, so must
# convert integer observation arrays here to be safe
if isinstance(array.data(), flex.int):
array = array.customized_copy(
data=array.data().as_double())
array.set_info(
base_array_info.customized_copy(labels=labels))
if (array.is_xray_amplitude_array()
or array.is_xray_amplitude_array()):
info = array.info()
array.set_info(
info.customized_copy(
wavelength=wavelength))
self._arrays.setdefault(key, array)
for key, array in self._arrays.copy().iteritems():
if (key.endswith('_minus') or '_minus_' in key
or key.endswith('_plus') or '_plus_' in key):
if '_minus' in key:
minus_key = key
plus_key = key.replace('_minus', '_plus')
elif '_plus' in key:
plus_key = key
minus_key = key.replace('_plus', '_minus')
if plus_key in self._arrays and minus_key in self._arrays:
plus_array = self._arrays.pop(plus_key)
minus_array = self._arrays.pop(minus_key)
minus_array = minus_array.customized_copy(
indices=-minus_array.indices()).set_info(
minus_array.info())
array = plus_array.concatenate(
minus_array, assert_is_similar_symmetry=False)
array = array.customized_copy(anomalous_flag=True)
array.set_info(
minus_array.info().customized_copy(labels=list(
OrderedSet(plus_array.info().labels +
minus_array.info().labels))))
array.set_observation_type(plus_array.observation_type())
self._arrays.setdefault(key, array)
if len(self._arrays) == 0:
raise CifBuilderError("No reflection data present in cif block")
class XInfo(object):
'''A class to represent all of the input to the xia2dpa system, with
enough information to allow structure solution, as parsed from a
.xinfo file, an example of which is in the source code.'''
def __init__(self, xinfo_file, sweep_ids=None, sweep_ranges=None):
'''Initialise myself from an input .xinfo file.'''
# first initialise all of the data structures which will hold the
# information...
self._project = None
self._crystals = OrderedDict()
if sweep_ids is not None:
sweep_ids = [s.lower() for s in sweep_ids]
if sweep_ranges is not None:
assert sweep_ids is not None
assert len(sweep_ids) == len(sweep_ranges)
self._sweep_ids = sweep_ids
self._sweep_ranges = sweep_ranges
# read the contents of the xinfo file
self._parse_project(xinfo_file)
self._validate()
return
def get_output(self):
'''Generate a string representation of the project.'''
text = 'Project %s\n' % self._project
for crystal in self._crystals.keys():
text += 'Crystal %s\n' % crystal
text += '%s\n' % self._crystals[crystal].get_output()
# remove a trailing newline...
return text[:-1]
def get_project(self):
return self._project
def get_crystals(self):
return self._crystals
def _validate(self):
'''Validate the structure of this object, ensuring that
everything looks right... raise exception if I find something
wrong.'''
return True
def _parse_project(self, xinfo_file):
'''Parse & validate the contents of the .xinfo file. This parses the
project element (i.e. the whole thing..)'''
project_records = []
for r in open(xinfo_file, 'r').readlines():
record = r.strip()
if not record:
pass
elif record[0] == '!' or record[0] == '#':
pass
else :
# then it may contain something useful...
project_records.append(record)
# so now we have loaded the whole file into memory stripping
# out the crud... let's look for something useful
for i in range(len(project_records)):
record = project_records[i]
if 'BEGIN PROJECT' in record:
self._project = record.replace('BEGIN PROJECT', '').strip()
if 'END PROJECT' in record:
if not self._project == record.replace(
'END PROJECT', '').strip():
raise RuntimeError, 'error parsing END PROJECT record'
# next look for crystals
if 'BEGIN CRYSTAL ' in record:
crystal_records = [record]
while True:
i += 1
record = project_records[i]
crystal_records.append(record)
if 'END CRYSTAL ' in record:
break
self._parse_crystal(crystal_records)
# that's everything, because parse_crystal handles
# the rest...
return
def _parse_crystal(self, crystal_records):
'''Parse the interesting information out of the crystal
description.'''
crystal = ''
for i in range(len(crystal_records)):
record = crystal_records[i]
if 'BEGIN CRYSTAL ' in record:
# we should only ever have one of these records in
# a call to this method
if crystal != '':
raise RuntimeError, 'error in BEGIN CRYSTAL record'
crystal = record.replace('BEGIN CRYSTAL ', '').strip()
if crystal in self._crystals:
raise RuntimeError, 'crystal %s already exists' % \
crystal
# cardinality:
#
# sequence - exactly one, a long string
# wavelengths - a dictionary of data structures keyed by the
# wavelength id
# sweeps - a dictionary of data structures keyed by the
# sweep id
# ha_info - exactly one dictionary containing the heavy atom
# information
self._crystals[crystal] = {
'sequence':'',
'wavelengths': OrderedDict(),
'samples': OrderedDict(),
'sweeps': OrderedDict(),
'ha_info': OrderedDict(),
'crystal_data': OrderedDict()
}
# next look for interesting stuff in the data structure...
# starting with the sequence
if 'BEGIN AA_SEQUENCE' in record:
sequence = ''
i += 1
record = crystal_records[i]
while record != 'END AA_SEQUENCE':
if not '#' in record or '!' in record:
sequence += record.strip()
i += 1
record = crystal_records[i]
if self._crystals[crystal]['sequence'] != '':
raise RuntimeError, 'error two SEQUENCE records found'
self._crystals[crystal]['sequence'] = sequence
# look for heavy atom information
if 'BEGIN HA_INFO' in record:
i += 1
record = crystal_records[i]
while record != 'END HA_INFO':
key = record.split()[0].lower()
value = record.split()[1]
# things which are numbers are integers...
if 'number' in key:
value = int(value)
self._crystals[crystal]['ha_info'][key] = value
i += 1
record = crystal_records[i]
if 'BEGIN SAMPLE' in record:
sample = record.replace('BEGIN SAMPLE ', '').strip()
i += 1
record = crystal_records[i]
while not 'END SAMPLE' in record:
i += 1
record = crystal_records[i]
self._crystals[crystal]['samples'][sample] = {}
# look for wavelength definitions
# FIXME need to check that there are not two wavelength
# definitions with the same numerical value for the wavelength -
# unless this is some way of handling RIP? maybe a NOFIXME.
# look for data blocks
if 'BEGIN CRYSTAL_DATA' in record:
i += 1
record = crystal_records[i]
while not 'END CRYSTAL_DATA' in record:
key = record.split()[0].lower()
value = record.replace(record.split()[0], '').strip()
self._crystals[crystal]['crystal_data'][key] = value
i += 1
record = crystal_records[i]
if 'BEGIN WAVELENGTH ' in record:
wavelength = record.replace('BEGIN WAVELENGTH ', '').strip()
# check that this is a new wavelength definition
if wavelength in self._crystals[crystal]['wavelengths']:
raise RuntimeError, \
'wavelength %s already exists for crystal %s' % \
(wavelength, crystal)
self._crystals[crystal]['wavelengths'][wavelength] = { }
i += 1
record = crystal_records[i]
# populate this with interesting things
while not 'END WAVELENGTH' in record:
# deal with a nested WAVELENGTH_STATISTICS block
if 'BEGIN WAVELENGTH_STATISTICS' in record:
self._crystals[crystal]['wavelengths'][
wavelength]['statistics'] = { }
i += 1
record = crystal_records[i]
while not 'END WAVELENGTH_STATISTICS' in record:
key, value = tuple(record.split())
self._crystals[crystal]['wavelengths'][
wavelength]['statistics'][
key.lower()] = float(value)
i += 1
record = crystal_records[i]
# else deal with the usual tokens
key = record.split()[0].lower()
if key == 'resolution':
lst = record.split()
if len(lst) < 2 or len(lst) > 3:
raise RuntimeError, 'resolution dmin [dmax]'
if len(lst) == 2:
dmin = float(lst[1])
self._crystals[crystal]['wavelengths'][
wavelength]['dmin'] = dmin
else:
dmin = min(map(float, lst[1:]))
dmax = max(map(float, lst[1:]))
self._crystals[crystal]['wavelengths'][
wavelength]['dmin'] = dmin
self._crystals[crystal]['wavelengths'][
wavelength]['dmax'] = dmax
i += 1
record = crystal_records[i]
continue
if len(record.split()) == 1:
raise RuntimeError, 'missing value for token %s' % \
record.split()[0]
try:
value = float(record.split()[1])
except ValueError, e:
value = record.replace(record.split()[0], '').strip()
self._crystals[crystal]['wavelengths'][
wavelength][key] = value
i += 1
record = crystal_records[i]
# next look for sweeps, checking that the wavelength
# definitions match up...
if 'BEGIN SWEEP' in record:
sweep = record.replace('BEGIN SWEEP', '').strip()
if self._sweep_ids is not None and sweep.lower() not in self._sweep_ids:
continue
elif self._sweep_ranges is not None:
start_end = self._sweep_ranges[self._sweep_ids.index(sweep.lower())]
else:
start_end = None
if sweep in self._crystals[crystal]['sweeps']:
raise RuntimeError, \
'sweep %s already exists for crystal %s' % \
(sweep, crystal)
self._crystals[crystal]['sweeps'][sweep] = { }
self._crystals[crystal]['sweeps'][sweep][
'excluded_regions'] = []
if start_end is not None:
self._crystals[crystal]['sweeps'][sweep][
'start_end'] = start_end
# in here I expect to find IMAGE, DIRECTORY, WAVELENGTH
# and optionally BEAM
# FIXME 30/OCT/06 this may not be the case, for instance
# if an INTEGRATED_REFLECTION_FILE record is in there...
# c/f XProject.py, XSweep.py
i += 1
record = crystal_records[i]
# populate this with interesting things
while not 'END SWEEP' in record:
# allow for WAVELENGTH_ID (bug # 2358)
if 'WAVELENGTH_ID' == record.split()[0]:
record = record.replace('WAVELENGTH_ID',
'WAVELENGTH')
if 'WAVELENGTH' == record.split()[0]:
wavelength = record.replace('WAVELENGTH', '').strip()
if not wavelength in self._crystals[crystal]['wavelengths'].keys():
raise RuntimeError, \
'wavelength %s unknown for crystal %s' % \
(wavelength, crystal)
self._crystals[crystal]['sweeps'][sweep]['wavelength'] = wavelength
elif 'SAMPLE' == record.split()[0]:
sample = record.replace('SAMPLE ', '').strip()
if not sample in self._crystals[crystal]['samples'].keys():
raise RuntimeError, \
'sample %s unknown for crystal %s' % (sample, crystal)
self._crystals[crystal]['sweeps'][sweep]['sample'] = sample
elif 'BEAM' == record.split()[0]:
beam = map(float, record.split()[1:])
self._crystals[crystal]['sweeps'][sweep]['beam'] = beam
elif 'DISTANCE' == record.split()[0]:
distance = float(record.split()[1])
self._crystals[crystal]['sweeps'][sweep]['distance'] = distance
elif 'EPOCH' == record.split()[0]:
epoch = int(record.split()[1])
self._crystals[crystal]['sweeps'][sweep]['epoch'] = epoch
elif 'REVERSEPHI' == record.split()[0]:
self._crystals[crystal]['sweeps'][sweep]['reversephi'] = True
elif 'START_END' == record.split()[0]:
if 'start_end' not in self._crystals[crystal]['sweeps'][sweep]:
start_end = map(int, record.split()[1:])
if len(start_end) != 2:
raise RuntimeError, \
'START_END start end, not "%s"' % record
self._crystals[crystal]['sweeps'][sweep]['start_end'] = start_end
elif 'EXCLUDE' == record.split()[0]:
if record.split()[1].upper() == 'ICE':
self._crystals[crystal]['sweeps'][sweep]['ice'] = True
else:
excluded_region = map(float, record.split()[1:])
if len(excluded_region) != 2:
raise RuntimeError, \
'EXCLUDE upper lower, not "%s". \
eg. EXCLUDE 2.28 2.22' % record
if excluded_region[0] <= excluded_region[1]:
raise RuntimeError, \
'EXCLUDE upper lower, where upper \
must be greater than lower (not "%s").\n\
eg. EXCLUDE 2.28 2.22' % record
self._crystals[crystal]['sweeps'][sweep]['excluded_regions'].append(
excluded_region)
else:
key = record.split()[0]
value = record.replace(key, '').strip()
self._crystals[crystal]['sweeps'][sweep][key] = value
i += 1
record = crystal_records[i]
# now look for one-record things
if 'SCALED_MERGED_REFLECTION_FILE' in record:
self._crystals[crystal][
'scaled_merged_reflection_file'] = \
record.replace('SCALED_MERGED_REFLECTION_FILE',
'').strip()
if 'REFERENCE_REFLECTION_FILE' in record:
self._crystals[crystal][
'reference_reflection_file'] = \
record.replace('REFERENCE_REFLECTION_FILE',
'').strip()
if 'FREER_FILE' in record:
# free file also needs to be used for indexing reference to
# make any sense at all...
self._crystals[crystal][
'freer_file'] = record.replace('FREER_FILE', '').strip()
self._crystals[crystal][
'reference_reflection_file'] = \
record.replace('FREER_FILE', '').strip()
# user assigned spacegroup and cell constants
if 'USER_SPACEGROUP' in record:
self._crystals[crystal][
'user_spacegroup'] = record.replace(
'USER_SPACEGROUP', '').strip()
if 'USER_CELL' in record:
self._crystals[crystal][
'user_cell'] = tuple(map(float, record.split()[1:]))
def as_json(self, filename=None, compact=False, split=False):
''' Dump experiment list as json '''
import json
from os.path import splitext
from libtbx.containers import OrderedDict
# Get the dictionary and get the JSON string
dictionary = self._experiment_list.to_dict()
# Split into separate files
if filename is not None and split:
# Get lists of models by filename
basepath = splitext(filename)[0]
ilist = [('%s_imageset_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['imageset'])]
blist = [('%s_beam_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['beam'])]
dlist = [('%s_detector_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['detector'])]
glist = [('%s_goniometer_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['goniometer'])]
slist = [('%s_scan_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['scan'])]
clist = [('%s_crystal_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['crystal'])]
plist = [('%s_profile_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['profile'])]
scalelist = [('%s_scaling_model_%d.json' % (basepath, i), d)
for i, d in enumerate(dictionary['scaling_model'])]
# Get the list of experiments
edict = OrderedDict([('__id__', 'ExperimentList'),
('experiment', dictionary['experiment'])])
# Set paths rather than indices
for e in edict['experiment']:
if 'imageset' in e:
e['imageset'] = ilist[e['imageset']][0]
if 'beam' in e:
e['beam'] = blist[e['beam']][0]
if 'detector' in e:
e['detector'] = dlist[e['detector']][0]
if 'goniometer' in e:
e['goniometer'] = glist[e['goniometer']][0]
if 'scan' in e:
e['scan'] = slist[e['scan']][0]
if 'crystal' in e:
e['crystal'] = clist[e['crystal']][0]
if 'profile' in e:
e['profile'] = plist[e['profile']][0]
if 'scaling_model' in e:
e['scaling_model'] = scalelist[e['scaling_model']][0]
to_write = ilist + blist + dlist + glist + \
slist + clist + plist + scalelist + [(filename, edict)]
else:
to_write = [(filename, dictionary)]
for fname, obj in to_write:
if compact:
text = json.dumps(obj,
separators=(',', ':'),
ensure_ascii=True)
else:
text = json.dumps(obj, indent=2, ensure_ascii=True)
# If a filename is set then dump to file otherwise return string
if fname is not None:
with open(fname, 'w') as outfile:
outfile.write(text)
else:
return text
class cif(DictMixin):
def __init__(self, blocks=None):
if blocks is not None:
self.blocks = OrderedDict(blocks)
else:
self.blocks = OrderedDict()
self.keys_lower = dict([(key.lower(), key) for key in self.blocks.keys()])
def __setitem__(self, key, value):
assert isinstance(value, block)
if not re.match(tag_re, '_'+key):
raise Sorry("%s is not a valid data block name" %key)
self.blocks[key] = value
self.keys_lower[key.lower()] = key
def get(self, key, default=None):
key_lower = self.keys_lower.get(key.lower())
if (key_lower is None):
return default
return self.blocks.get(key_lower, default)
def __getitem__(self, key):
result = self.get(key)
if (result is None):
raise KeyError('Unknown CIF data block name: "%s"' % key)
return result
def __delitem__(self, key):
del self.blocks[self.keys_lower[key.lower()]]
del self.keys_lower[key.lower()]
def keys(self):
return self.blocks.keys()
def __repr__(self):
return repr(OrderedDict(self.iteritems()))
def __copy__(self):
return cif(self.blocks.copy())
copy = __copy__
def __deepcopy__(self, memo):
return cif(copy.deepcopy(self.blocks, memo))
def deepcopy(self):
return copy.deepcopy(self)
def show(self, out=None, indent=" ", indent_row=None,
data_name_field_width=34,
loop_format_strings=None):
if out is None:
out = sys.stdout
for name, block in self.items():
print >> out, "data_%s" %name
block.show(
out=out, indent=indent, indent_row=indent_row,
data_name_field_width=data_name_field_width,
loop_format_strings=loop_format_strings)
def __str__(self):
s = StringIO()
self.show(out=s)
return s.getvalue()
def validate(self, dictionary, show_warnings=True, error_handler=None, out=None):
if out is None: out = sys.stdout
from iotbx.cif import validation
errors = {}
if error_handler is None:
error_handler = validation.ErrorHandler()
for key, block in self.blocks.iteritems():
error_handler = error_handler.__class__()
dictionary.set_error_handler(error_handler)
block.validate(dictionary)
errors.setdefault(key, error_handler)
if error_handler.error_count or error_handler.warning_count:
error_handler.show(show_warnings=show_warnings, out=out)
return error_handler
def sort(self, recursive=False, key=None, reverse=False):
self.blocks = OrderedDict(sorted(self.blocks.items(), key=key, reverse=reverse))
if recursive:
for b in self.blocks.values():
b.sort(recursive=recursive, reverse=reverse)
def sort(self, key=None, reverse=False):
self._columns = OrderedDict(
sorted(self._columns.items(), key=key, reverse=reverse))
def __init__(self, blocks=None):
if blocks is not None:
self.blocks = OrderedDict(blocks)
else:
self.blocks = OrderedDict()
self.keys_lower = dict([(key.lower(), key) for key in self.blocks.keys()])
def __init__(self, imageset, size=10):
self.imageset = imageset
self.size = size
self._image_data = OrderedDict()
def __init__(self, imageset, size=10): self.imageset = imageset self.size = size self._image_data = OrderedDict()
def add_miller_array(self,
array,
array_type=None,
column_name=None,
column_names=None):
"""
Accepts a miller array, and one of array_type, column_name or column_names.
"""
assert [array_type, column_name, column_names].count(None) == 2
if array_type is not None:
assert array_type in ('calc', 'meas')
elif column_name is not None:
column_names = [column_name]
if array.is_complex_array():
if column_names is None:
column_names = [
self.prefix + 'F_' + array_type,
self.prefix + 'phase_' + array_type
]
else:
assert len(column_names) == 2
if (('_A_' in column_names[0] and '_B_' in column_names[1]) or
('.A_' in column_names[0] and '.B_' in column_names[1])):
data = [
flex.real(array.data()).as_string(),
flex.imag(array.data()).as_string()
]
else:
data = [
flex.abs(array.data()).as_string(),
array.phases(deg=True).data().as_string()
]
elif array.is_hendrickson_lattman_array():
if column_names is None:
column_names = [
self.prefix + 'HL_%s_iso' % abcd for abcd in 'ABCD'
]
else:
assert len(column_names) == 4
data = [d.as_string() for d in array.data().as_abcd()]
else:
if array_type is not None:
if array.is_xray_intensity_array():
obs_ext = 'squared_'
else:
obs_ext = ''
column_names = [self.prefix + 'F_' + obs_ext + array_type]
if array.sigmas() is not None:
column_names.append(self.prefix + 'F_' + obs_ext + 'sigma')
if isinstance(array.data(), flex.std_string):
data = [array.data()]
else:
data = [array.data().as_string()]
if array.anomalous_flag():
if ((array.sigmas() is not None and len(column_names) == 4) or
(array.sigmas() is None and len(column_names) == 2)):
data = []
asu, matches = array.match_bijvoet_mates()
for anomalous_sign in ("+", "-"):
sel = matches.pairs_hemisphere_selection(
anomalous_sign)
sel.extend(
matches.singles_hemisphere_selection(
anomalous_sign))
if (anomalous_sign == "+"):
indices = asu.indices().select(sel)
hemisphere_column_names = column_names[:len(
column_names) // 2]
else:
indices = -asu.indices().select(sel)
hemisphere_column_names = column_names[
len(column_names) // 2:]
hemisphere_data = asu.data().select(sel)
hemisphere_array = miller.array(
miller.set(array.crystal_symmetry(), indices),
hemisphere_data)
if array.sigmas() is not None:
hemisphere_array.set_sigmas(
asu.sigmas().select(sel))
if self.refln_loop is None:
# then this is the first array to be added to the loop,
# hack so we don't have both hemispheres of indices
self.indices = indices
self.add_miller_array(
hemisphere_array,
column_names=hemisphere_column_names)
return
if array.sigmas() is not None and len(column_names) == 2:
data.append(array.sigmas().as_string())
if not (self.indices.size() == array.indices().size()
and self.indices.all_eq(array.indices())):
from cctbx.miller import match_indices
other_indices = array.indices().deep_copy()
match = match_indices(self.indices, other_indices)
if match.singles(0).size():
# array is missing some reflections indices that already appear in the loop
# therefore pad the data with '?' values
other_indices.extend(
self.indices.select(match.single_selection(0)))
for d in data:
d.extend(
flex.std_string(['?'] *
(other_indices.size() - d.size())))
for d in data:
assert d.size() == other_indices.size()
match = match_indices(self.indices, other_indices)
if match.singles(1).size():
# this array contains some reflections that are not already present in the
# cif loop, therefore need to add rows of '?' values
single_indices = other_indices.select(
match.single_selection(1))
self.indices.extend(single_indices)
n_data_columns = len(self.refln_loop) - 3
for hkl in single_indices:
row = list(hkl) + ['?'] * n_data_columns
self.refln_loop.add_row(row)
match = match_indices(self.indices, other_indices)
match = match_indices(self.indices, other_indices)
perm = match.permutation()
data = [d.select(perm) for d in data]
if self.refln_loop is None:
self.refln_loop = miller_indices_as_cif_loop(self.indices,
prefix=self.prefix)
columns = OrderedDict(zip(column_names, data))
for key in columns:
assert key not in self.refln_loop
self.refln_loop.add_columns(columns)
def sort(self, recursive=False, key=None, reverse=False):
self.blocks = OrderedDict(sorted(self.blocks.items(), key=key, reverse=reverse))
if recursive:
for b in self.blocks.values():
b.sort(recursive=recursive, reverse=reverse)
def sort(self, key=None, reverse=False):
self._columns = OrderedDict(
sorted(self._columns.items(), key=key, reverse=reverse))
class loop(DictMixin):
def __init__(self, header=None, data=None):
self._columns = OrderedDict()
self.keys_lower = {}
if header is not None:
for key in header:
self.setdefault(key, flex.std_string())
if data is not None:
# the number of data items must be an exact multiple of the number of headers
assert len(data) % len(header) == 0, "Wrong number of data items for loop"
n_rows = len(data)//len(header)
n_columns = len(header)
for i in range(n_rows):
self.add_row([data[i*n_columns+j] for j in range(n_columns)])
elif header is None and data is not None:
assert isinstance(data, dict) or isinstance(data, OrderedDict)
self.add_columns(data)
self.keys_lower = dict(
[(key.lower(), key) for key in self._columns.keys()])
def __setitem__(self, key, value):
if not re.match(tag_re, key):
raise Sorry("%s is not a valid data name" %key)
if len(self) > 0:
assert len(value) == self.size()
if not isinstance(value, flex.std_string):
for flex_numeric_type in (flex.int, flex.double):
if isinstance(value, flex_numeric_type):
value = value.as_string()
else:
try:
value = flex_numeric_type(value).as_string()
except TypeError:
continue
else:
break
if not isinstance(value, flex.std_string):
value = flex.std_string(value)
# value must be a mutable type
assert hasattr(value, '__setitem__')
self._columns[key] = value
self.keys_lower[key.lower()] = key
def __getitem__(self, key):
return self._columns[self.keys_lower[key.lower()]]
def __delitem__(self, key):
del self._columns[self.keys_lower[key.lower()]]
del self.keys_lower[key.lower()]
def keys(self):
return self._columns.keys()
def __repr__(self):
return repr(OrderedDict(self.iteritems()))
def name(self):
return common_substring(self.keys()).rstrip('_').rstrip('.')
def size(self):
size = 0
for column in self.values():
size = max(size, len(column))
return size
def n_rows(self):
return self.size()
def n_columns(self):
return len(self.keys())
def add_row(self, row, default_value="?"):
if isinstance(row, dict):
for key in self:
if key in row:
self[key].append(str(row[key]))
else:
self[key].append(default_value)
else:
assert len(row) == len(self)
for i, key in enumerate(self):
self[key].append(str(row[i]))
def add_column(self, key, values):
if self.size() != 0:
assert len(values) == self.size()
self[key] = values
self.keys_lower[key.lower()] = key
def add_columns(self, columns):
assert isinstance(columns, dict) or isinstance(columns, OrderedDict)
for key, value in columns.iteritems():
self.add_column(key, value)
def update_column(self, key, values):
assert type(key)==type(""), "first argument is column key string"
if self.size() != 0:
assert len(values) == self.size(), "len(values) %d != self.size() %d" % (
len(values),
self.size(),
)
self[key] = values
self.keys_lower[key.lower()] = key
def delete_row(self, index):
assert index < self.n_rows()
for column in self._columns.values():
del column[index]
def __copy__(self):
new = loop()
new._columns = self._columns.copy()
new.keys_lower = self.keys_lower.copy()
return new
copy = __copy__
def __deepcopy__(self, memo):
new = loop()
new._columns = copy.deepcopy(self._columns, memo)
new.keys_lower = copy.deepcopy(self.keys_lower, memo)
return new
def deepcopy(self):
return copy.deepcopy(self)
def show(self, out=None, indent=" ", indent_row=None, fmt_str=None, align_columns=True):
assert self.n_rows() > 0 and self.n_columns() > 0, "keys: %s %d %d" % (
self.keys(),
self.n_rows(),
self.n_columns(),
)
if out is None:
out = sys.stdout
if indent_row is None:
indent_row = indent
assert indent.strip() == ""
assert indent_row.strip() == ""
print >> out, "loop_"
for k in self.keys():
print >> out, indent + k
values = self._columns.values()
range_len_values = range(len(values))
if fmt_str is not None:
# Pretty printing:
# The user is responsible for providing a valid format string.
# Values are not quoted - it is the user's responsibility to place
# appropriate quotes in the format string if a particular value may
# contain spaces.
values = copy.deepcopy(values)
for i, v in enumerate(values):
for flex_numeric_type in (flex.int, flex.double):
if not isinstance(v, flex_numeric_type):
try:
values[i] = flex_numeric_type(v)
except ValueError:
continue
else:
break
if fmt_str is None:
fmt_str = indent_row + ' '.join(["%s"]*len(values))
for i in range(self.size()):
print >> out, fmt_str % tuple([values[j][i] for j in range_len_values])
elif align_columns:
fmt_str = []
for i, (k, v) in enumerate(self.iteritems()):
for i_v in range(v.size()):
v[i_v] = format_value(v[i_v])
# exclude and semicolon text fields from column width calculation
v_ = flex.std_string(item for item in v if "\n" not in item)
width = v_.max_element_length()
# See if column contains only number, '.' or '?'
# right-align numerical columns, left-align everything else
v = v.select(~( (v == ".") | (v == "?") ))
try:
flex.double(v)
except ValueError:
width *= -1
fmt_str.append("%%%is" %width)
fmt_str = indent_row + " ".join(fmt_str)
for i in range(self.size()):
print >> out, (fmt_str %
tuple([values[j][i]
for j in range_len_values])).rstrip()
else:
for i in range(self.size()):
values_to_print = [format_value(values[j][i]) for j in range_len_values]
print >> out, ' '.join([indent] + values_to_print)
def __str__(self):
s = StringIO()
self.show(out=s)
return s.getvalue()
def iterrows(self):
""" Warning! Still super-slow! """
keys = self.keys()
s_values = self.values()
range_len_self = range(len(self))
# range is 1% faster than xrange in this particular place.
# tuple (s_values...) is slightly faster than list
for j in range(self.size()):
yield OrderedDict(zip(keys, (s_values[i][j] for i in range_len_self)))
def find_row(self, kv_dict):
self_keys = self.keys()
for k in kv_dict.keys():
assert k in self_keys
result = []
s_values = self.values()
range_len_self = range(len(self))
for i in range(self.size()):
goodrow = True
for k, v in kv_dict.iteritems():
if self[k][i] != v:
goodrow = False
break
if goodrow:
result.append(OrderedDict(zip(self_keys, [s_values[j][i] for j in range_len_self])))
return result
def sort(self, key=None, reverse=False):
self._columns = OrderedDict(
sorted(self._columns.items(), key=key, reverse=reverse))
def order(self, order):
def _cmp_key(k1, k2):
for i, o in enumerate(order):
if k1==o: break
for j, o in enumerate(order):
if k2==o: break
if k1<k2: return -1
return 1
keys = self._columns.keys()
keys.sort(_cmp_key)
tmp = OrderedDict()
for o in order:
tmp[o]=self._columns[o]
self._columns = tmp
def __eq__(self, other):
if (len(self) != len(other) or
self.size() != other.size() or
self.keys() != other.keys()):
return False
for value, other_value in zip(self.values(), other.values()):
if (value == other_value).count(True) != len(value):
return False
return True
def __init__(self, unmerged_intensities, batches_all, n_bins=20, d_min=None,
id_to_batches=None):
intensities = OrderedDict()
individual_merged_intensities = OrderedDict()
batches = OrderedDict()
#m_isym = OrderedDict()
sel = unmerged_intensities.sigmas() > 0
unmerged_intensities = unmerged_intensities.select(sel)
batches_all = batches_all.select(sel)
if id_to_batches is None:
run_id_to_batch_id = None
run_id = 0
unique_batches = sorted(set(batches_all.data()))
last_batch = None
run_start = unique_batches[0]
for i, batch in enumerate(unique_batches):
if last_batch is not None and batch > (last_batch + 1) or (i+1) == len(unique_batches):
batch_sel = (batches_all.data() >= run_start) & (batches_all.data() <= last_batch)
batches[run_id] = batches_all.select(batch_sel).resolution_filter(d_min=d_min)
intensities[run_id] = unmerged_intensities.select(batch_sel).resolution_filter(d_min=d_min)
individual_merged_intensities[run_id] = intensities[run_id].merge_equivalents().array()
Debug.write("run %i batch %i to %i" %(run_id+1, run_start, last_batch))
run_id += 1
run_start = batch
last_batch = batch
else:
run_id_to_batch_id = OrderedDict()
run_id = 0
for batch_id, batch_range in id_to_batches.iteritems():
run_id_to_batch_id[run_id] = batch_id
run_start, last_batch = batch_range
batch_sel = (batches_all.data() >= run_start) & (batches_all.data() <= last_batch)
batches[run_id] = batches_all.select(batch_sel).resolution_filter(d_min=d_min)
intensities[run_id] = unmerged_intensities.select(batch_sel).resolution_filter(d_min=d_min)
individual_merged_intensities[run_id] = intensities[run_id].merge_equivalents().array()
Debug.write("run %i batch %i to %i" %(run_id+1, run_start, last_batch))
run_id += 1
unmerged_intensities.setup_binner(n_bins=n_bins)
unmerged_intensities.show_summary()
#result = unmerged_intensities.cc_one_half(use_binning=True)
#result.show()
self.unmerged_intensities = unmerged_intensities
self.merged_intensities = unmerged_intensities.merge_equivalents().array()
self.intensities = intensities
self.individual_merged_intensities = individual_merged_intensities
self.batches = batches
if run_id_to_batch_id is not None:
labels = run_id_to_batch_id.values()
else:
labels = None
racc = self.relative_anomalous_cc()
if racc is not None:
self.plot_relative_anomalous_cc(racc, labels=labels)
correlation_matrix, linkage_matrix = self.compute_correlation_coefficient_matrix()
self._cluster_dict = self.to_dict(correlation_matrix, linkage_matrix)
self.plot_cc_matrix(correlation_matrix, linkage_matrix, labels=labels)
self.write_output()
def __repr__(self): return repr(OrderedDict(self.iteritems()))
class multi_crystal_analysis(object):
def __init__(self, unmerged_intensities, batches_all, n_bins=20, d_min=None,
id_to_batches=None):
sel = unmerged_intensities.sigmas() > 0
unmerged_intensities = unmerged_intensities.select(sel)
batches_all = batches_all.select(sel)
unmerged_intensities.setup_binner(n_bins=n_bins)
unmerged_intensities.show_summary()
self.unmerged_intensities = unmerged_intensities
self.merged_intensities = unmerged_intensities.merge_equivalents().array()
separate = separate_unmerged(
unmerged_intensities, batches_all, id_to_batches=id_to_batches)
self.intensities = separate.intensities
self.batches = separate.batches
run_id_to_batch_id = separate.run_id_to_batch_id
self.individual_merged_intensities = OrderedDict()
for k in self.intensities.keys():
self.intensities[k] = self.intensities[k].resolution_filter(d_min=d_min)
self.batches[k] = self.batches[k].resolution_filter(d_min=d_min)
self.individual_merged_intensities[k] = self.intensities[k].merge_equivalents().array()
if run_id_to_batch_id is not None:
labels = run_id_to_batch_id.values()
else:
labels = None
racc = self.relative_anomalous_cc()
if racc is not None:
self.plot_relative_anomalous_cc(racc, labels=labels)
correlation_matrix, linkage_matrix = self.compute_correlation_coefficient_matrix()
self._cluster_dict = self.to_dict(correlation_matrix, linkage_matrix)
self.plot_cc_matrix(correlation_matrix, linkage_matrix, labels=labels)
self.write_output()
def to_dict(self, correlation_matrix, linkage_matrix):
from scipy.cluster import hierarchy
tree = hierarchy.to_tree(linkage_matrix, rd=False)
leaves_list = hierarchy.leaves_list(linkage_matrix)
d = {}
# http://w3facility.org/question/scipy-dendrogram-to-json-for-d3-js-tree-visualisation/
# https://gist.github.com/mdml/7537455
def add_node(node):
if node.is_leaf(): return
cluster_id = node.get_id() - len(linkage_matrix) - 1
row = linkage_matrix[cluster_id]
d[cluster_id+1] = {
'datasets': [i+1 for i in sorted(node.pre_order())],
'height': row[2],
}
# Recursively add the current node's children
if node.left: add_node(node.left)
if node.right: add_node(node.right)
add_node(tree)
return d
def relative_anomalous_cc(self):
if self.unmerged_intensities.anomalous_flag():
d_min = min([ma.d_min() for ma in self.intensities.values()])
racc = flex.double()
full_set_anom_diffs = self.merged_intensities.anomalous_differences()
for i_wedge in self.individual_merged_intensities.keys():
ma_i = self.individual_merged_intensities[i_wedge].resolution_filter(d_min=d_min)
anom_i = ma_i.anomalous_differences()
anom_cc = anom_i.correlation(full_set_anom_diffs, assert_is_similar_symmetry=False).coefficient()
racc.append(anom_cc)
return racc
def plot_relative_anomalous_cc(self, racc, labels=None):
perm = flex.sort_permutation(racc)
fig = pyplot.figure(dpi=1200, figsize=(16,12))
pyplot.bar(range(len(racc)), list(racc.select(perm)))
if labels is None:
labels = ["%.0f" %(j+1) for j in perm]
assert len(labels) == len(racc)
pyplot.xticks([i+0.5 for i in range(len(racc))], labels)
locs, labels = pyplot.xticks()
pyplot.setp(labels, rotation=70)
pyplot.xlabel("Dataset")
pyplot.ylabel("Relative anomalous correlation coefficient")
fig.savefig("racc.png")
def compute_correlation_coefficient_matrix(self):
from scipy.cluster import hierarchy
import scipy.spatial.distance as ssd
correlation_matrix = flex.double(
flex.grid(len(self.intensities), len(self.intensities)))
d_min = min([ma.d_min() for ma in self.intensities.values()])
for i_wedge in self.individual_merged_intensities.keys():
for j_wedge in self.individual_merged_intensities.keys():
if j_wedge < i_wedge: continue
ma_i = self.individual_merged_intensities[i_wedge].resolution_filter(d_min=d_min)
ma_j = self.individual_merged_intensities[j_wedge].resolution_filter(d_min=d_min)
cc_ij = ma_i.correlation(ma_j).coefficient()
correlation_matrix[(i_wedge,j_wedge)] = cc_ij
correlation_matrix[j_wedge,i_wedge] = cc_ij
diffraction_dissimilarity = 1-correlation_matrix
dist_mat = diffraction_dissimilarity.as_numpy_array()
# convert the redundant n*n square matrix form into a condensed nC2 array
dist_mat = ssd.squareform(dist_mat) # distArray[{n choose 2}-{n-i choose 2} + (j-i-1)] is the distance between points i and j
method = ['single', 'complete', 'average', 'weighted'][2]
linkage_matrix = hierarchy.linkage(dist_mat, method=method)
return correlation_matrix, linkage_matrix
def plot_cc_matrix(self, correlation_matrix, linkage_matrix, labels=None):
from scipy.cluster import hierarchy
ind = hierarchy.fcluster(linkage_matrix, t=0.05, criterion='distance')
# Compute and plot dendrogram.
fig = pyplot.figure(dpi=1200, figsize=(16,12))
axdendro = fig.add_axes([0.09,0.1,0.2,0.8])
Y = linkage_matrix
Z = hierarchy.dendrogram(Y,
color_threshold=0.05,
orientation='right')
axdendro.set_xticks([])
axdendro.set_yticks([])
# Plot distance matrix.
axmatrix = fig.add_axes([0.3,0.1,0.6,0.8])
index = Z['leaves']
D = correlation_matrix.as_numpy_array()
D = D[index,:]
D = D[:,index]
im = axmatrix.matshow(D, aspect='auto', origin='lower')
axmatrix.yaxis.tick_right()
if labels is not None:
axmatrix.xaxis.tick_bottom()
axmatrix.set_xticks(list(range(len(labels))))
axmatrix.set_xticklabels([labels[i] for i in index], rotation=70)
axmatrix.yaxis.set_ticks([])
# Plot colorbar.
axcolor = fig.add_axes([0.91,0.1,0.02,0.8])
pyplot.colorbar(im, cax=axcolor)
# Display and save figure.
fig.savefig('correlation_matrix.png')
fig.clear()
fig = pyplot.figure(dpi=1200, figsize=(16,12))
if labels is None:
labels = ['%i' %(i+1) for i in range(len(self.intensities))]
ddict = hierarchy.dendrogram(linkage_matrix,
#truncate_mode='lastp',
color_threshold=0.05,
labels=labels,
#leaf_rotation=90,
show_leaf_counts=False)
locs, labels = pyplot.xticks()
pyplot.setp(labels, rotation=70)
fig.savefig('dendrogram.png')
import copy
y2_dict = scipy_dendrogram_to_plotly_json(ddict) # above heatmap
x2_dict = copy.deepcopy(y2_dict) # left of heatmap, rotated
for d in y2_dict['data']:
d['yaxis'] = 'y2'
d['xaxis'] = 'x2'
for d in x2_dict['data']:
x = d['x']
y = d['y']
d['x'] = y
d['y'] = x
d['yaxis'] = 'y3'
d['xaxis'] = 'x3'
ccdict = {
'data': [{
'name': 'correlation_matrix',
'x': list(range(D.shape[0])),
'y': list(range(D.shape[1])),
'z': D.tolist(),
'type': 'heatmap',
'colorbar': {
'title': 'Correlation coefficient',
'titleside': 'right',
#'x': 0.96,
#'y': 0.9,
#'titleside': 'top',
#'xanchor': 'right',
'xpad': 0,
#'yanchor': 'top'
},
'colorscale': 'Jet',
'xaxis': 'x',
'yaxis': 'y',
}],
'layout': {
'autosize': False,
'bargap': 0,
'height': 1000,
'hovermode': 'closest',
'margin': {
'r': 20,
't': 50,
'autoexpand': True,
'l': 20
},
'showlegend': False,
'title': 'Dendrogram Heatmap',
'width': 1000,
'xaxis': {
'domain': [0.2, 0.9],
'mirror': 'allticks',
'showgrid': False,
'showline': False,
'showticklabels': True,
'tickmode': 'array',
'ticks': '',
'ticktext': y2_dict['layout']['xaxis']['ticktext'],
'tickvals': list(range(len(y2_dict['layout']['xaxis']['ticktext']))),
'tickangle': 300,
'title': '',
'type': 'linear',
'zeroline': False
},
'yaxis': {
'domain': [0, 0.78],
'anchor': 'x',
'mirror': 'allticks',
'showgrid': False,
'showline': False,
'showticklabels': True,
'tickmode': 'array',
'ticks': '',
'ticktext': y2_dict['layout']['xaxis']['ticktext'],
'tickvals': list(range(len(y2_dict['layout']['xaxis']['ticktext']))),
'title': '',
'type': 'linear',
'zeroline': False
},
'xaxis2': {
'domain': [0.2, 0.9],
'anchor': 'y2',
'showgrid': False,
'showline': False,
'showticklabels': False,
'zeroline': False
},
'yaxis2': {
'domain': [0.8, 1],
'anchor': 'x2',
'showgrid': False,
'showline': False,
'zeroline': False
},
'xaxis3': {
'domain': [0.0, 0.1],
'anchor': 'y3',
'range': [max(max(d['x']) for d in x2_dict['data']), 0],
'showgrid': False,
'showline': False,
'tickangle': 300,
'zeroline': False
},
'yaxis3': {
'domain': [0, 0.78],
'anchor': 'x3',
'showgrid': False,
'showline': False,
'showticklabels': False,
'zeroline': False
},
}
}
d = ccdict
d['data'].extend(y2_dict['data'])
d['data'].extend(x2_dict['data'])
d['clusters'] = self._cluster_dict
import json
with open('intensity_clusters.json', 'wb') as f:
json.dump(d, f, indent=2)
def write_output(self):
rows = [["cluster_id", "# datasets", "height", "datasets"]]
for cid in sorted(self._cluster_dict.keys()):
cluster = self._cluster_dict[cid]
datasets = cluster['datasets']
rows.append([str(cid), str(len(datasets)),
'%.2f' %cluster['height'], ' '.join(['%s'] * len(datasets)) % tuple(datasets)])
with open('intensity_clustering.txt', 'wb') as f:
from libtbx import table_utils
print >> f, table_utils.format(
rows, has_header=True, prefix="|", postfix="|")
def __init__(self, cif_block, base_array_info=None, wavelengths=None):
crystal_symmetry_builder.__init__(self, cif_block)
if base_array_info is not None:
self.crystal_symmetry = self.crystal_symmetry.join_symmetry(
other_symmetry=base_array_info.crystal_symmetry_from_file,
force=True)
self._arrays = OrderedDict()
if (wavelengths is None) :
wavelengths = {}
if base_array_info is None:
base_array_info = miller.array_info(source_type="cif")
refln_containing_loops = self.get_miller_indices_containing_loops()
for self.indices, refln_loop in refln_containing_loops:
self.wavelength_id_array = None
self.crystal_id_array = None
self.scale_group_array = None
wavelength_ids = [None]
crystal_ids = [None]
scale_groups = [None]
for key, value in refln_loop.iteritems():
# need to get these arrays first
if (key.endswith('wavelength_id') or
key.endswith('crystal_id') or
key.endswith('scale_group_code')):
data = as_int_or_none_if_all_question_marks(value, column_name=key)
if data is None:
continue
counts = data.counts()
if key.endswith('wavelength_id'):
wavelength_ids = counts.keys()
if len(counts) == 1: continue
array = miller.array(
miller.set(self.crystal_symmetry, self.indices).auto_anomalous(), data)
if key.endswith('wavelength_id'):
self.wavelength_id_array = array
wavelength_ids = counts.keys()
elif key.endswith('crystal_id'):
self.crystal_id_array = array
crystal_ids = counts.keys()
elif key.endswith('scale_group_code'):
self.scale_group_array = array
scale_groups = counts.keys()
for label, value in sorted(refln_loop.items()):
for w_id in wavelength_ids:
for crys_id in crystal_ids:
for scale_group in scale_groups:
if 'index_' in label: continue
key = label
labels = [label]
wavelength = None
if (key.endswith('wavelength_id') or
key.endswith('crystal_id') or
key.endswith('scale_group_code')):
w_id = None
crys_id = None
scale_group = None
key_suffix = ''
if w_id is not None:
key_suffix += '_%i' %w_id
labels.insert(0, "wavelength_id=%i" %w_id)
wavelength = wavelengths.get(w_id, None)
if crys_id is not None:
key_suffix += '_%i' %crys_id
labels.insert(0, "crystal_id=%i" %crys_id)
if scale_group is not None:
key_suffix += '_%i' %scale_group
labels.insert(0, "scale_group_code=%i" %scale_group)
key += key_suffix
sigmas = None
if key in self._arrays: continue
array = self.flex_std_string_as_miller_array(
value, wavelength_id=w_id, crystal_id=crys_id,
scale_group_code=scale_group)
if array is None: continue
if '_sigma' in key:
sigmas_label = label
key = None
for suffix in ('', '_meas', '_calc'):
if sigmas_label.replace('_sigma', suffix) in refln_loop:
key = sigmas_label.replace('_sigma', suffix) + key_suffix
break
if key is None:
key = sigmas_label + key_suffix
elif key in self._arrays and self._arrays[key].sigmas() is None:
sigmas = array
array = self._arrays[key]
check_array_sizes(array, sigmas, key, sigmas_label)
sigmas = as_flex_double(sigmas, sigmas_label)
array.set_sigmas(sigmas.data())
info = array.info()
array.set_info(
info.customized_copy(labels=info.labels+[sigmas_label],
wavelength=wavelength))
continue
elif 'PHWT' in key:
phwt_label = label
fwt_label = label.replace('PHWT', 'FWT')
if fwt_label not in refln_loop: continue
phwt_array = array
if fwt_label in self._arrays:
array = self._arrays[fwt_label]
check_array_sizes(array, phwt_array, fwt_label, phwt_label)
phases = as_flex_double(phwt_array, phwt_label)
info = array.info()
array = array.phase_transfer(phases, deg=True)
array.set_info(
info.customized_copy(labels=info.labels+[phwt_label]))
self._arrays[fwt_label] = array
continue
elif 'HL_' in key:
hl_letter = key[key.find('HL_')+3]
hl_key = 'HL_' + hl_letter
key = key.replace(hl_key, 'HL_A')
if key in self._arrays:
continue # this array is already dealt with
hl_labels = [label.replace(hl_key, 'HL_'+letter) for letter in 'ABCD']
hl_keys = [key.replace(hl_key, 'HL_'+letter) for letter in 'ABCD']
hl_values = [cif_block.get(hl_key) for hl_key in hl_labels]
if hl_values.count(None) == 0:
selection = self.get_selection(
hl_values[0], wavelength_id=w_id,
crystal_id=crys_id, scale_group_code=scale_group)
hl_values = [as_double_or_none_if_all_question_marks(
hl.select(selection), column_name=lab)
for hl, lab in zip(hl_values, hl_labels)]
array = miller.array(miller.set(
self.crystal_symmetry, self.indices.select(selection)
).auto_anomalous(), flex.hendrickson_lattman(*hl_values))
labels = labels[:-1]+hl_labels
elif '.B_' in key or '_B_' in key:
if '.B_' in key:
key, key_b = key.replace('.B_', '.A_'), key
label, label_b = label.replace('.B_', '.A_'), label
elif '_B_' in key:
key, key_b = key.replace('_B', '_A'), key
label, label_b = label.replace('_B', '_A'), label
if key in refln_loop and key_b in refln_loop:
b_part = array.data()
if key in self._arrays:
info = self._arrays[key].info()
a_part = self._arrays[key].data()
self._arrays[key] = self._arrays[key].array(
data=flex.complex_double(a_part, b_part))
self._arrays[key].set_info(
info.customized_copy(labels=info.labels+[key_b]))
continue
elif ('phase_' in key and not "_meas" in key and
self.crystal_symmetry.space_group() is not None):
alt_key1 = label.replace('phase_', 'F_')
alt_key2 = alt_key1 + '_au'
if alt_key1 in refln_loop:
phase_key = label
key = alt_key1+key_suffix
elif alt_key2 in refln_loop:
phase_key = label
key = alt_key2+key_suffix
else: phase_key = None
if phase_key is not None:
phases = array.data()
if key in self._arrays:
array = self._arrays[key]
array = as_flex_double(array, key)
check_array_sizes(array, phases, key, phase_key)
info = self._arrays[key].info()
self._arrays[key] = array.phase_transfer(phases, deg=True)
self._arrays[key].set_info(
info.customized_copy(labels=info.labels+[phase_key]))
else:
array = self.flex_std_string_as_miller_array(
refln_loop[label], wavelength_id=w_id, crystal_id=crys_id,
scale_group_code=scale_group)
check_array_sizes(array, phases, key, phase_key)
array.phase_transfer(phases, deg=True)
labels = labels+[label, phase_key]
if base_array_info.labels is not None:
labels = base_array_info.labels + labels
def rstrip_substrings(string, substrings):
for substr in substrings:
if substr == '': continue
if string.endswith(substr):
string = string[:-len(substr)]
return string
# determine observation type
stripped_key = rstrip_substrings(
key, [key_suffix, '_au', '_meas', '_calc', '_plus', '_minus'])
if (stripped_key.endswith('F_squared') or
stripped_key.endswith('intensity') or
stripped_key.endswith('.I') or
stripped_key.endswith('_I')) and (
array.is_real_array() or array.is_integer_array()):
array.set_observation_type_xray_intensity()
elif (stripped_key.endswith('F') and (
array.is_real_array() or array.is_integer_array())):
array.set_observation_type_xray_amplitude()
if (array.is_xray_amplitude_array() or
array.is_xray_amplitude_array()):
# e.g. merge_equivalents treats integer arrays differently, so must
# convert integer observation arrays here to be safe
if isinstance(array.data(), flex.int):
array = array.customized_copy(data=array.data().as_double())
array.set_info(base_array_info.customized_copy(labels=labels))
if (array.is_xray_amplitude_array() or
array.is_xray_amplitude_array()):
info = array.info()
array.set_info(info.customized_copy(wavelength=wavelength))
self._arrays.setdefault(key, array)
for key, array in self._arrays.copy().iteritems():
if ( key.endswith('_minus') or '_minus_' in key
or key.endswith('_plus') or '_plus_' in key):
if '_minus' in key:
minus_key = key
plus_key = key.replace('_minus', '_plus')
elif '_plus' in key:
plus_key = key
minus_key = key.replace('_plus', '_minus')
if plus_key in self._arrays and minus_key in self._arrays:
plus_array = self._arrays.pop(plus_key)
minus_array = self._arrays.pop(minus_key)
minus_array = minus_array.customized_copy(
indices=-minus_array.indices()).set_info(minus_array.info())
array = plus_array.concatenate(
minus_array, assert_is_similar_symmetry=False)
array = array.customized_copy(anomalous_flag=True)
array.set_info(minus_array.info().customized_copy(
labels=list(
OrderedSet(plus_array.info().labels+minus_array.info().labels))))
array.set_observation_type(plus_array.observation_type())
self._arrays.setdefault(key, array)
if len(self._arrays) == 0:
raise CifBuilderError("No reflection data present in cif block")
def sort(self, recursive=False, key=None, reverse=False):
self.blocks = OrderedDict(
sorted(self.blocks.items(), key=key, reverse=reverse))
if recursive:
for b in self.blocks.values():
b.sort(recursive=recursive, reverse=reverse)