def sort(self, recursive=False, key=None, reverse=False): self._set = OrderedSet( sorted(self._items.keys(), key=key, reverse=reverse) \ + sorted(self.loops.keys(), key=key, reverse=reverse)) if recursive: for l in self.loops.values(): l.sort(key=key, reverse=reverse)
def imagesets(self): ''' Get a list of the unique imagesets (includes None). This returns unique complete sets rather than partial. ''' return list( OrderedSet([e.imageset for e in self if e.imageset is not None]))
def imagesets(self): """Get a list of the unique imagesets.""" return list( OrderedSet([e.imageset for e in self if e.imageset is not None]))
def scans(self): """ Get a list of the unique scans (includes None). """ return list(OrderedSet(e.scan for e in self))
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())) print '' panel_id, (x, y) = beam_centre(expt.detector, expt.beam) if panel_id >= 0 and x is not None and y is not None: if len(expt.detector) > 1: beam_centre_str = "Beam centre: panel %i, (%.2f,%.2f)" %(panel_id, x, y) else: beam_centre_str = "Beam centre: (%.2f,%.2f)" %(x, y) else: beam_centre_str = "" print str(expt.beam) + beam_centre_str + '\n' 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 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) + 'Max resolution: %f\n' %( detector.get_max_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 '' panel_id, (x, y) = beam_centre(detector, imageset.get_beam()) if panel_id >= 0 and x is not None and y is not None: if len(detector) > 1: beam_centre_str = "Beam centre: panel %i, (%.2f,%.2f)" %(panel_id, x, y) else: beam_centre_str = "Beam centre: (%.2f,%.2f)" %(x, y) else: beam_centre_str = "" print str(imageset.get_beam()) + beam_centre_str + '\n' 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'), ('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'), ]) for rlist in reflections: from cctbx.array_family import flex print print "Reflection list contains %i reflections" %(len(rlist)) 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
def scaling_models(self): ''' Get a list of the unique scaling models (includes None). ''' return list(OrderedSet(e.scaling_model for e in self))
def crystals(self): ''' Get a list of the unique crystals (includes None). ''' return list(OrderedSet(e.crystal for e in self))
def detectors(self): ''' Get a list of the unique detectors (includes None). ''' return list(OrderedSet(e.detector for e in self))
def __init__(self): self._items = {} self.loops = {} self._set = OrderedSet() self.keys_lower = {}
class block_base(DictMixin): def __init__(self): self._items = {} self.loops = {} self._set = OrderedSet() self.keys_lower = {} def __setitem__(self, key, value): if not re.match(tag_re, key): raise Sorry("%s is not a valid data name" %key) if isinstance(value, loop): self.loops[key] = value for k in value.keys(): self.keys_lower[k.lower()] = k elif isinstance(value, basestring): v = str(value) if not (re.match(any_print_char_re, v) or re.match(quoted_string_re, v) or re.match(semicolon_string_re, v)): raise Sorry("Invalid data item for %s" %key) self._items[key] = v self.keys_lower[key.lower()] = key else: try: float(value) self[key] = str(value) except TypeError: if key in self._items: del self._items[key] for loop_ in self.loops.values(): if key in loop_: loop_[key] = value if key not in self: self.add_loop(loop(header=(key,), data=(value,))) if key in self._items or isinstance(value, loop): self._set.add(key) def __getitem__(self, key): key = self.keys_lower.get(key.lower(), key) if key in self._items: return self._items[key] else: # give precedence to returning the actual data items in the event of a # single looped item when the loop name and data name coincide for loop in self.loops.values(): if key in loop: return loop[key] if key in self.loops: return self.loops[key] raise KeyError def __delitem__(self, key): key = self.keys_lower.get(key.lower(), key) if key in self._items: del self._items[key] self._set.discard(key) elif key in self.keys(): # must be a looped item for k, loop in self.loops.iteritems(): if key in loop: if len(loop) == 1: # remove the now empty loop del self[k] else: del loop[key] return raise KeyError elif key in self.loops: del self.loops[key] self._set.discard(key) else: raise KeyError def get_looped_item(self, key, key_error=KeyError, value_error=None, default=None): if key not in self: if key_error is None: return default else: raise key_error(key) value = self[key] if isinstance(value, flex.std_string): return value elif value_error is not None: raise value_error("%s is not a looped item" %key) elif default is not None: return default else: return flex.std_string([value]) def loop_keys(self): done = [] for key in self: key = key.split(".")[0] if key in done: continue done.append(key) return done def iterloops(self): for key in self.loop_keys(): yield self.get(key) def get_single_item(self, key, key_error=KeyError, value_error=ValueError, default=None): if key not in self: if key_error is None: return default else: raise key_error(key) value = self[key] if not isinstance(value, flex.std_string): return value elif value_error is not None: raise value_error("%s appears as a looped item" %key) else: return default def keys(self): keys = [] for key in self._set: if key in self._items: keys.append(key) elif key in self.loops: keys.extend(self.loops[key].keys()) return keys def __repr__(self): return repr(OrderedDict(self.iteritems())) def update(self, other=None, **kwargs): if other is None: return if isinstance(other, OrderedDict) or isinstance(other, dict): for key, value in other.iteritems(): self[key] = value else: self._items.update(other._items) self.loops.update(other.loops) self._set |= other._set self.keys_lower.update(other.keys_lower) def add_data_item(self, tag, value): self[tag] = value def add_loop(self, loop): try: self.setdefault(loop.name(), loop) except Sorry: # create a unique loop name self.setdefault('_'+str(hash(tuple(loop.keys()))), loop) def get_loop(self, loop_name, default=None): loop_ = self.loops.get(loop_name.lower()) if loop_ is None: return default return loop_ def get_loop_with_defaults(self, loop_name, default_dict): loop_ = self.get_loop(loop_name) if loop_ is None: loop_ = loop(header=default_dict.keys()) n_rows = loop_.n_rows() for key, value in default_dict.iteritems(): if key not in loop_: loop_.add_column(key, flex.std_string(n_rows, value)) return loop_ def __copy__(self): new = self.__class__() new._items = self._items.copy() new.loops = self.loops.copy() new._set = copy.copy(self._set) new.keys_lower = self.keys_lower.copy() return new copy = __copy__ def __deepcopy__(self, memo): new = self.__class__() new._items = copy.deepcopy(self._items, memo) new.loops = copy.deepcopy(self.loops, memo) new._set = copy.deepcopy(self._set, memo) new.keys_lower = copy.deepcopy(self.keys_lower, memo) return new def deepcopy(self): return copy.deepcopy(self) def __str__(self): s = StringIO() self.show(out=s) return s.getvalue() def validate(self, dictionary): for key, value in self._items.iteritems(): dictionary.validate_single_item(key, value, self) for loop in self.loops.values(): dictionary.validate_loop(loop, self) if isinstance(self, block): for value in self.saves.itervalues(): value.validate(dictionary) def sort(self, recursive=False, key=None, reverse=False): self._set = OrderedSet( sorted(self._items.keys(), key=key, reverse=reverse) \ + sorted(self.loops.keys(), key=key, reverse=reverse)) if recursive: for l in self.loops.values(): l.sort(key=key, reverse=reverse) """Items that either appear in both self and other and the value has changed or appear in self but not other.""" def difference(self, other): new = self.__class__() for items in (self._items, self.loops): for key, value in items.iteritems(): if key in other: other_value = other[key] if other_value == value: continue else: new[key] = other_value else: new[key] = value return new
def __init__(self, cif_block, base_array_info=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 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 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] 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) 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])) 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 key.endswith('_meas') 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)) 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 __init__(self, experiment, vectors, frame='reciprocal', mode='main'): from libtbx.utils import Sorry self.experiment = experiment self.vectors = vectors self.frame = frame self.mode = mode gonio = experiment.goniometer scan = experiment.scan self.s0 = matrix.col(self.experiment.beam.get_s0()) self.rotation_axis = matrix.col(gonio.get_rotation_axis()) from dxtbx.model import MultiAxisGoniometer if not isinstance(gonio, MultiAxisGoniometer): raise Sorry('Only MultiAxisGoniometer models supported') axes = gonio.get_axes() if len(axes) != 3: raise Sorry('Only 3-axis goniometers supported') e1, e2, e3 = (matrix.col(e) for e in reversed(axes)) fixed_rotation = matrix.sqr(gonio.get_fixed_rotation()) setting_rotation = matrix.sqr(gonio.get_setting_rotation()) rotation_axis = matrix.col(gonio.get_rotation_axis_datum()) rotation_matrix = rotation_axis.axis_and_angle_as_r3_rotation_matrix( experiment.scan.get_oscillation()[0], deg=True) from dials.algorithms.refinement import rotation_decomposition results = OrderedDict() # from https://github.com/legrandp/xdsme/blob/master/XOalign/XOalign.py#L427 # referential_permutations sign permutations for four permutations of # parallel/antiparallel (rotation axis & beam) # y1 // e1, y2 // beamVector; y1 anti// e1, y2 // beamVector # y1 // e1, y2 anti// beamVector; y1 anti// e1, y2 anti// beamVector ex = matrix.col((1, 0, 0)) ey = matrix.col((0, 1, 0)) ez = matrix.col((0, 0, 1)) referential_permutations = ([ ex, ey, ez], [-ex, -ey, ez], [ ex, -ey, -ez], [-ex, ey, -ez]) for (v1_, v2_) in self.vectors: results[(v1_, v2_)] = OrderedDict() space_group = self.experiment.crystal.get_space_group() for smx in list(space_group.smx())[:]: results[(v1_, v2_)][smx] = [] crystal = copy.deepcopy(self.experiment.crystal) cb_op = sgtbx.change_of_basis_op(smx) crystal = crystal.change_basis(cb_op) # Goniometer datum setting [D] at which the orientation was determined D = (setting_rotation * rotation_matrix * fixed_rotation).inverse() # The setting matrix [U] will vary with the datum setting according to # [U] = [D] [U0] U = matrix.sqr(crystal.get_U()) # XXX In DIALS recorded U is equivalent to U0 - D is applied to U inside # prediction U0 = U B = matrix.sqr(crystal.get_B()) if self.frame == 'direct': B = B.inverse().transpose() v1_0 = U0 * B * v1_ v2_0 = U0 * B * v2_ #c (b) The laboratory frame vectors l1 & l2 are normally specified with the #c MODE command: MODE MAIN (the default) sets l1 (along which v1 will be #c placed) along the principle goniostat axis e1 (Omega), and l2 along #c the beam s0. This allows rotation for instance around a principle axis. #c The other mode is MODE CUSP, which puts l1 (v1) perpendicular to the #c beam (s0) and the e1 (Omega) axis, and l2 (v2) in the plane containing #c l1 & e1 (ie l1 = e1 x s0, l2 = e1). if self.mode == 'cusp': l1 = self.rotation_axis.cross(self.s0) l2 = self.rotation_axis else: l1 = self.rotation_axis.normalize() l3 = l1.cross(self.s0).normalize() l2 = l1.cross(l3) for perm in referential_permutations: S = matrix.sqr(perm[0].elems + perm[1].elems + perm[2].elems) from rstbx.cftbx.coordinate_frame_helpers import align_reference_frame R = align_reference_frame(v1_0, S * l1, v2_0, S * l2) solutions = rotation_decomposition.solve_r3_rotation_for_angles_given_axes( R, e1, e2, e3, return_both_solutions=True, deg=True) if solutions is None: continue results[(v1_, v2_)][smx].extend(solutions) self.all_solutions = results self.unique_solutions = OrderedDict() for (v1, v2), result in results.iteritems(): for solutions in result.itervalues(): for solution in solutions: k = tuple(round(a, 3) for a in solution[1:]) self.unique_solutions.setdefault(k, OrderedSet()) self.unique_solutions[k].add((v1, v2))
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)
class block_base(DictMixin): def __init__(self): self._items = {} self.loops = {} self._set = OrderedSet() self.keys_lower = {} def __setitem__(self, key, value): if not re.match(tag_re, key): raise Sorry("%s is not a valid data name" % key) if isinstance(value, loop): self.loops[key] = value self.keys_lower[key.lower()] = key for k in value.keys(): self.keys_lower[k.lower()] = k elif isinstance(value, basestring): v = str(value) if not (re.match(any_print_char_re, v) or re.match( quoted_string_re, v) or re.match(semicolon_string_re, v)): raise Sorry("Invalid data item for %s" % key) self._items[key] = v self.keys_lower[key.lower()] = key else: try: float(value) self[key] = str(value) except TypeError: if key in self._items: del self._items[key] for loop_ in self.loops.values(): if key in loop_: loop_[key] = value if key not in self: self.add_loop(loop(header=(key, ), data=(value, ))) if key in self._items or isinstance(value, loop): self._set.add(key) def __getitem__(self, key): key = self.keys_lower.get(key.lower(), key) if key in self._items: return self._items[key] else: # give precedence to returning the actual data items in the event of a # single looped item when the loop name and data name coincide for loop in self.loops.values(): if key in loop: return loop[key] if key in self.loops: return self.loops[key] raise KeyError(key) def __delitem__(self, key): key = self.keys_lower.get(key.lower(), key) if key in self._items: del self._items[key] self._set.discard(key) elif key in self.keys(): # must be a looped item for k, loop in self.loops.iteritems(): if key in loop: if len(loop) == 1: # remove the now empty loop del self[k] else: del loop[key] return raise KeyError(key) elif key in self.loops: del self.loops[key] self._set.discard(key) else: raise KeyError def get_looped_item(self, key, key_error=KeyError, value_error=None, default=None): if key not in self: if key_error is None: return default else: raise key_error(key) value = self[key] if isinstance(value, flex.std_string): return value elif value_error is not None: raise value_error("%s is not a looped item" % key) elif default is not None: return default else: return flex.std_string([value]) def loop_keys(self): done = [] for key in self: key = key.split(".")[0] if key in done: continue done.append(key) return done def iterloops(self): for key in self.loop_keys(): yield self.get(key) def get_single_item(self, key, key_error=KeyError, value_error=ValueError, default=None): if key not in self: if key_error is None: return default else: raise key_error(key) value = self[key] if not isinstance(value, flex.std_string): return value elif value_error is not None: raise value_error("%s appears as a looped item" % key) else: return default def keys(self): keys = [] for key in self._set: if key in self._items: keys.append(key) elif key in self.loops: keys.extend(self.loops[key].keys()) return keys def item_keys(self): '''Returns names of all entries that are not loops''' return self._items.keys() def __repr__(self): return repr(OrderedDict(self.iteritems())) def update(self, other=None, **kwargs): if other is None: return if isinstance(other, OrderedDict) or isinstance(other, dict): for key, value in other.iteritems(): self[key] = value else: self._items.update(other._items) self.loops.update(other.loops) self._set |= other._set self.keys_lower.update(other.keys_lower) def add_data_item(self, tag, value): self[tag] = value def add_loop(self, loop): try: self.setdefault(loop.name(), loop) except Sorry: # create a unique loop name self.setdefault('_' + str(hash(tuple(loop.keys()))), loop) def get_loop(self, loop_name, default=None): loop_ = self.loops.get( self.keys_lower.get(loop_name.lower(), loop_name)) if loop_ is None: return default return loop_ def get_loop_or_row(self, loop_name, default=None): loop_ = self.get_loop(loop_name, None) if loop_ is None: ln = loop_name if ln[-1] != '.': ln += '.' found_keys = {} for key, value in self.iteritems(): if key.startswith(ln): found_keys[key] = flex.std_string([value]) # constructing the loop if len(found_keys) > 0: loop_ = loop(data=found_keys) if loop_ is None: return default return loop_ def get_loop_with_defaults(self, loop_name, default_dict): loop_ = self.get_loop(loop_name) if loop_ is None: loop_ = loop(header=default_dict.keys()) n_rows = loop_.n_rows() for key, value in default_dict.iteritems(): if key not in loop_: loop_.add_column(key, flex.std_string(n_rows, value)) return loop_ def __copy__(self): new = self.__class__() new._items = self._items.copy() new.loops = self.loops.copy() new._set = copy.copy(self._set) new.keys_lower = self.keys_lower.copy() return new copy = __copy__ def __deepcopy__(self, memo): new = self.__class__() new._items = copy.deepcopy(self._items, memo) new.loops = copy.deepcopy(self.loops, memo) new._set = copy.deepcopy(self._set, memo) new.keys_lower = copy.deepcopy(self.keys_lower, memo) return new def deepcopy(self): return copy.deepcopy(self) def __str__(self): s = StringIO() self.show(out=s) return s.getvalue() def validate(self, dictionary): for key, value in self._items.iteritems(): dictionary.validate_single_item(key, value, self) for loop in self.loops.values(): dictionary.validate_loop(loop, self) if isinstance(self, block): for value in self.saves.itervalues(): value.validate(dictionary) def sort(self, recursive=False, key=None, reverse=False): self._set = OrderedSet( sorted(self._items.keys(), key=key, reverse=reverse) \ + sorted(self.loops.keys(), key=key, reverse=reverse)) if recursive: for l in self.loops.values(): l.sort(key=key, reverse=reverse) """Items that either appear in both self and other and the value has changed or appear in self but not other.""" def difference(self, other): new = self.__class__() for items in (self._items, self.loops): for key, value in items.iteritems(): if key in other: other_value = other[key] if other_value == value: continue else: new[key] = other_value else: new[key] = value return new
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) 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 '' panel_id, (x, y) = beam_centre(expt.detector, expt.beam) if panel_id >= 0 and x is not None and y is not None: if len(expt.detector) > 1: beam_centre_str = "Beam centre: panel %i, (%.2f,%.2f)" %(panel_id, x, y) else: beam_centre_str = "Beam centre: (%.2f,%.2f)" %(x, y) else: beam_centre_str = "" print str(expt.beam) + beam_centre_str + '\n' 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 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) + 'Max resolution: %f\n' %( detector.get_max_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 '' panel_id, (x, y) = beam_centre(detector, imageset.get_beam()) if panel_id >= 0 and x is not None and y is not None: if len(detector) > 1: beam_centre_str = "Beam centre: panel %i, (%.2f,%.2f)" %(panel_id, x, y) else: beam_centre_str = "Beam centre: (%.2f,%.2f)" %(x, y) else: beam_centre_str = "" print str(imageset.get_beam()) + beam_centre_str + '\n' 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'), ('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'), ]) for rlist in reflections: from cctbx.array_family import flex print print "Reflection list contains %i reflections" %(len(rlist)) 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
def beams(self): ''' Get a list of the unique beams (includes None). ''' return list(OrderedSet(e.beam for e in self))
def goniometers(self): ''' Get a list of the unique goniometers (includes None). ''' from libtbx.containers import OrderedSet return list(OrderedSet([e.goniometer for e in self]))
def goniometers(self): ''' Get a list of the unique goniometers (includes None). ''' return list(OrderedSet(e.goniometer for e in self))
def crystals(self): ''' Get a list of the unique crystals (includes None). ''' from libtbx.containers import OrderedSet return list(OrderedSet([e.crystal for e in self]))
def profiles(self): ''' Get a list of the unique profile models (includes None). ''' return list(OrderedSet(e.profile for e in self))
def profiles(self): ''' Get a list of the unique profile models (includes None). ''' from libtbx.containers import OrderedSet return list(OrderedSet([e.profile for e in self]))
def show_reflections(reflections, show_intensities=False, show_profile_fit=False, show_centroids=False, show_all_reflection_data=False, show_flags=False, max_reflections=None): text = [] import collections from libtbx.containers import OrderedSet formats = collections.OrderedDict(( ('miller_index', '%i, %i, %i'), ('d', '%.2f'), ('qe', '%.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'), ('shoebox', '%.1f'), ('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 dials.array_family import flex from dials.algorithms.shoebox import MaskCode foreground_valid = MaskCode.Valid | MaskCode.Foreground text.append('') text.append('Reflection list contains %i reflections' % (len(rlist))) if len(rlist) == 0: continue rows = [["Column", "min", "max", "mean"]] for k, col in rlist.cols(): if k in formats and not "%" in formats[k]: # Allow blanking out of entries that wouldn't make sense rows.append([k, formats[k], formats[k], formats[k]]) elif 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 isinstance(col, flex.miller_index): col = col.as_vec3_double() rows.append([ k, formats[k] % col.min(), formats[k] % col.max(), formats[k] % col.mean() ]) elif isinstance(col, flex.shoebox): rows.append([k, "", "", ""]) si = col.summed_intensity().observed_value() rows.append([ " summed I", formats[k] % flex.min(si), formats[k] % flex.max(si), formats[k] % flex.mean(si) ]) x1, x2, y1, y2, z1, z2 = col.bounding_boxes().parts() bbox_sizes = ((z2 - z1) * (y2 - y1) * (x2 - x1)).as_double() rows.append([ " N pix", formats[k] % flex.min(bbox_sizes), formats[k] % flex.max(bbox_sizes), formats[k] % flex.mean(bbox_sizes) ]) fore_valid = col.count_mask_values( foreground_valid).as_double() rows.append([ " N valid foreground pix", formats[k] % flex.min(fore_valid), formats[k] % flex.max(fore_valid), formats[k] % flex.mean(fore_valid) ]) text.append( table_utils.format(rows, has_header=True, prefix="| ", postfix=" |")) if show_flags: text.append(_create_flag_count_table(rlist)) 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 show_intensities: for k in intensity_keys: keys_to_print.add(k) if show_profile_fit: for k in profile_fit_keys: keys_to_print.add(k) if show_centroids: for k in centroid_keys: keys_to_print.add(k) if 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())] elif isinstance(data, flex.shoebox): x1, x2, y1, y2, z1, z2 = data.bounding_boxes().parts() bbox_sizes = ((z2 - z1) * (y2 - y1) * (x2 - x1)).as_double() c_strings = [bbox_sizes.as_string(format_strings[0].strip())] key += " (N pix)" 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] if max_reflections is not None: max_reflections = min(len(rlist), max_reflections) columns = [] for k in keys: columns.append( format_column(k, rlist[k], format_strings=formats[k].split(','))) text.append('') text.append('Printing %i of %i reflections:' % (max_reflections, len(rlist))) line = [] for j in range(len(columns)): key = keys[j] if key == 'shoebox': key += " (N pix)" width = max(len(key), columns[j].max_element_length()) line.append('%%%is' % width % key) text.append(' '.join(line)) for i in range(max_reflections): line = [] for j in range(len(columns)): line.append(columns[j][i]) text.append(' '.join(line)) return '\n'.join(text)
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