def write_xml(self, file, command_line=''):
fout = open(file, 'w')
fout.write('<?xml version="1.0"?>')
fout.write('<AutoProcContainer>\n')
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write('<AutoProc><spaceGroup>%s</spaceGroup>' % spacegroup)
self.write_refined_cell(fout, cell)
fout.write('</AutoProc>')
fout.write('<AutoProcScalingContainer>')
fout.write('<AutoProcScaling>')
self.write_date(fout)
fout.write('</AutoProcScaling>')
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+/-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(['overall', 'innerShell', 'outerShell']):
statistics_cache = {}
for s in stats:
if isinstance(statistics_all[key][s], type([])):
statistics_cache[s] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name, statistics_cache)
for sweep in sweeps:
fout.write('<AutoProcIntegrationContainer>\n')
if '#' in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
fout.write('<Image><fileName>%s</fileName>' % \
os.path.split(image_name)[-1])
fout.write('<fileLocation>%s</fileLocation></Image>' %
sanitize(os.path.split(image_name)[0]))
fout.write('<AutoProcIntegration>\n')
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write('<startImageNumber>%d</startImageNumber>' % \
start)
fout.write('<endImageNumber>%d</endImageNumber>' % \
end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
'<refinedDetectorDistance>%f</refinedDetectorDistance>' % \
indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre()
fout.write('<refinedXBeam>%f</refinedXBeam>' % beam[0])
fout.write('<refinedYBeam>%f</refinedYBeam>' % beam[1])
fout.write('</AutoProcIntegration>\n')
fout.write('</AutoProcIntegrationContainer>\n')
fout.write('</AutoProcScalingContainer>')
# file unpacking nonsense
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
fout.write('<AutoProcProgramContainer><AutoProcProgram>')
fout.write('<processingCommandLine>%s</processingCommandLine>' \
% sanitize(command_line))
fout.write('<processingPrograms>xia2</processingPrograms>')
fout.write('</AutoProcProgram>')
from xia2.Handlers.Environment import Environment
data_directory = Environment.generate_directory('DataFiles')
log_directory = Environment.generate_directory('LogFiles')
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type('')):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
basename = os.path.basename(reflection_file)
if os.path.isfile(os.path.join(data_directory, basename)):
# Use file in DataFiles directory in preference (if it exists)
reflection_file = os.path.join(data_directory, basename)
fout.write('<AutoProcProgramAttachment><fileType>Result')
fout.write('</fileType><fileName>%s</fileName>' % \
os.path.split(reflection_file)[-1])
fout.write('<filePath>%s</filePath>' % \
sanitize(os.path.split(reflection_file)[0]))
fout.write('</AutoProcProgramAttachment>\n')
import glob
g = glob.glob(os.path.join(log_directory, '*merging-statistics.json'))
for merging_stats_json in g:
fout.write('<AutoProcProgramAttachment><fileType>Graph')
fout.write('</fileType><fileName>%s</fileName>' %
os.path.split(merging_stats_json)[-1])
fout.write('<filePath>%s</filePath>' % sanitize(log_directory))
fout.write('</AutoProcProgramAttachment>\n')
# add the xia2.txt file...
fout.write('<AutoProcProgramAttachment><fileType>Log')
fout.write('</fileType><fileName>xia2.txt</fileName>')
fout.write('<filePath>%s</filePath>' % sanitize(os.getcwd()))
fout.write('</AutoProcProgramAttachment>\n')
fout.write('</AutoProcProgramContainer>')
fout.write('</AutoProcContainer>\n')
fout.close()
def json_object(self, command_line=''):
result = {}
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
result['AutoProc'] = {}
tmp = result['AutoProc']
tmp['spaceGroup'] = spacegroup
for name, value in zip(['a', 'b', 'c', 'alpha', 'beta', 'gamma'], cell):
tmp['refinedCell_%s' % name] = value
result['AutoProcScalingContainer'] = {}
tmp = result['AutoProcScalingContainer']
tmp['AutoProcScaling'] = {
'recordTimeStamp': time.strftime('%Y-%m-%d %H:%M:%S',
time.localtime())
}
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+/-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
tmp['AutoProcScalingStatistics'] = []
tmp2 = tmp['AutoProcScalingStatistics']
for j, name in enumerate(
['overall', 'innerShell', 'outerShell']):
statistics_cache = {'scalingStatisticsType':name}
for s in stats:
if s in self._name_map:
n = self._name_map[s]
else:
continue
if isinstance(statistics_all[key][s], type([])):
statistics_cache[n] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[n] = statistics_all[key][s][j]
tmp2.append(statistics_cache)
tmp['AutoProcIntegrationContainer'] = []
tmp2 = tmp['AutoProcIntegrationContainer']
for sweep in sweeps:
if '#' in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
cell = sweep.get_integrater_cell()
intgr_tmp = {}
for name, value in zip(['a', 'b', 'c', 'alpha', 'beta', 'gamma'],
cell):
intgr_tmp['cell_%s' % name] = value
# FIXME this is naughty
indxr = sweep._get_indexer()
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
intgr_tmp['startImageNumber'] = start
intgr_tmp['endImageNumber'] = end
intgr_tmp['refinedDetectorDistance'] = indxr.get_indexer_distance()
beam = indxr.get_indexer_beam_centre()
intgr_tmp['refinedXBeam'] = beam[0]
intgr_tmp['refinedYBeam'] = beam[1]
tmp2.append(
{'Image':{'fileName':os.path.split(image_name)[-1],
'fileLocation':sanitize(os.path.split(image_name)[0])},
'AutoProcIntegration': intgr_tmp})
# file unpacking nonsense
result['AutoProcProgramContainer'] = {}
tmp = result['AutoProcProgramContainer']
tmp2 = {}
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
tmp2['processingCommandLine'] = sanitize(command_line)
tmp2['processingProgram'] = 'xia2'
tmp['AutoProcProgram'] = tmp2
tmp['AutoProcProgramAttachment'] = []
tmp2 = tmp['AutoProcProgramAttachment']
from xia2.Handlers.Environment import Environment
data_directory = Environment.generate_directory('DataFiles')
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type('')):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
basename = os.path.basename(reflection_file)
if os.path.isfile(os.path.join(data_directory, basename)):
# Use file in DataFiles directory in preference (if it exists)
reflection_file = os.path.join(data_directory, basename)
tmp2.append({
'fileType': 'Result',
'fileName': os.path.split(reflection_file)[-1],
'filePath': sanitize(os.path.split(reflection_file)[0]),
})
tmp2.append({'fileType':'Log',
'fileName':'xia2.txt',
'filePath':sanitize(os.getcwd())})
return result
def get_output(self):
result = "Crystal: %s\n" % self._name
if self._aa_sequence:
result += "Sequence: %s\n" % self._aa_sequence.get_sequence()
for wavelength in self._wavelengths.keys():
result += self._wavelengths[wavelength].get_output()
scaler = self._get_scaler()
if scaler.get_scaler_finish_done():
for wname, xwav in self._wavelengths.iteritems():
for xsweep in xwav.get_sweeps():
idxr = xsweep._get_indexer()
if PhilIndex.params.xia2.settings.show_template:
result += "%s\n" % banner(
"Autoindexing %s (%s)" %
(idxr.get_indexer_sweep_name(),
idxr.get_template()))
else:
result += "%s\n" % banner(
"Autoindexing %s" % idxr.get_indexer_sweep_name())
result += "%s\n" % idxr.show_indexer_solutions()
intgr = xsweep._get_integrater()
if PhilIndex.params.xia2.settings.show_template:
result += "%s\n" % banner(
"Integrating %s (%s)" %
(intgr.get_integrater_sweep_name(),
intgr.get_template()))
else:
result += "%s\n" % banner(
"Integrating %s" %
intgr.get_integrater_sweep_name())
result += "%s\n" % intgr.show_per_image_statistics()
result += "%s\n" % banner("Scaling %s" % self.get_name())
for (
(dname, sname),
(limit, suggested),
) in scaler.get_scaler_resolution_limits().iteritems():
if suggested is None or limit == suggested:
result += "Resolution limit for %s/%s: %5.2f\n" % (
dname,
sname,
limit,
)
else:
result += (
"Resolution limit for %s/%s: %5.2f (%5.2f suggested)\n"
% (dname, sname, limit, suggested))
# this is now deprecated - be explicit in what you are
# asking for...
reflections_all = self.get_scaled_merged_reflections()
statistics_all = self._get_scaler().get_scaler_statistics()
# print some of these statistics, perhaps?
for key in statistics_all.keys():
result += format_statistics(statistics_all[key],
caption="For %s/%s/%s" % key)
# then print out some "derived" information based on the
# scaling - this is presented through the Scaler interface
# explicitly...
cell = self._get_scaler().get_scaler_cell()
cell_esd = self._get_scaler().get_scaler_cell_esd()
spacegroups = self._get_scaler().get_scaler_likely_spacegroups()
spacegroup = spacegroups[0]
resolution = self._get_scaler().get_scaler_highest_resolution()
from cctbx import sgtbx
sg = sgtbx.space_group_type(str(spacegroup))
spacegroup = sg.lookup_symbol()
CIF.set_spacegroup(sg)
mmCIF.set_spacegroup(sg)
if len(self._wavelengths) == 1:
CIF.set_wavelengths(
[w.get_wavelength() for w in self._wavelengths.itervalues()])
mmCIF.set_wavelengths(
[w.get_wavelength() for w in self._wavelengths.itervalues()])
else:
for wavelength in self._wavelengths.keys():
full_wave_name = "%s_%s_%s" % (
self._project._name,
self._name,
wavelength,
)
CIF.get_block(full_wave_name)[
"_diffrn_radiation_wavelength"] = self._wavelengths[
wavelength].get_wavelength()
mmCIF.get_block(full_wave_name)[
"_diffrn_radiation_wavelength"] = self._wavelengths[
wavelength].get_wavelength()
CIF.set_wavelengths({
name: wave.get_wavelength()
for name, wave in self._wavelengths.iteritems()
})
mmCIF.set_wavelengths({
name: wave.get_wavelength()
for name, wave in self._wavelengths.iteritems()
})
result += "Assuming spacegroup: %s\n" % spacegroup
if len(spacegroups) > 1:
result += "Other likely alternatives are:\n"
for sg in spacegroups[1:]:
result += "%s\n" % sg
if cell_esd:
from libtbx.utils import format_float_with_standard_uncertainty
def match_formatting(dimA, dimB):
def conditional_split(s):
return ((s[:s.index(".")],
s[s.index("."):]) if "." in s else (s, ""))
A, B = conditional_split(dimA), conditional_split(dimB)
maxlen = (max(len(A[0]), len(B[0])), max(len(A[1]), len(B[1])))
return (
A[0].rjust(maxlen[0]) + A[1].ljust(maxlen[1]),
B[0].rjust(maxlen[0]) + B[1].ljust(maxlen[1]),
)
formatted_cell_esds = tuple(
format_float_with_standard_uncertainty(v, sd)
for v, sd in zip(cell, cell_esd))
formatted_rows = (formatted_cell_esds[0:3],
formatted_cell_esds[3:6])
formatted_rows = zip(*(match_formatting(l, a)
for l, a in zip(*formatted_rows)))
result += "Unit cell (with estimated std devs):\n"
result += "%s %s %s\n%s %s %s\n" % (formatted_rows[0] +
formatted_rows[1])
else:
result += "Unit cell:\n"
result += "%7.3f %7.3f %7.3f\n%7.3f %7.3f %7.3f\n" % tuple(cell)
# now, use this information and the sequence (if provided)
# and also matthews_coef (should I be using this directly, here?)
# to compute a likely number of molecules in the ASU and also
# the solvent content...
if self._aa_sequence:
residues = self._aa_sequence.get_sequence()
if residues:
nres = len(residues)
# first compute the number of molecules using the K&R
# method
nmol = compute_nmol(
cell[0],
cell[1],
cell[2],
cell[3],
cell[4],
cell[5],
spacegroup,
resolution,
nres,
)
# then compute the solvent fraction
solvent = compute_solvent(
cell[0],
cell[1],
cell[2],
cell[3],
cell[4],
cell[5],
spacegroup,
nmol,
nres,
)
result += "Likely number of molecules in ASU: %d\n" % nmol
result += "Giving solvent fraction: %4.2f\n" % solvent
self._nmol = nmol
if isinstance(reflections_all, type({})):
for format in reflections_all.keys():
result += "%s format:\n" % format
reflections = reflections_all[format]
if isinstance(reflections, type({})):
for wavelength in reflections.keys():
target = FileHandler.get_data_file(
reflections[wavelength])
result += "Scaled reflections (%s): %s\n" % (
wavelength, target)
else:
target = FileHandler.get_data_file(reflections)
result += "Scaled reflections: %s\n" % target
CIF.write_cif()
mmCIF.write_cif()
return result
def json_object(self, command_line=""):
result = {}
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
result["AutoProc"] = {}
tmp = result["AutoProc"]
tmp["spaceGroup"] = spacegroup
for name, value in zip(["a", "b", "c", "alpha", "beta", "gamma"],
cell):
tmp["refinedCell_%s" % name] = value
result["AutoProcScalingContainer"] = {}
tmp = result["AutoProcScalingContainer"]
tmp["AutoProcScaling"] = {
"recordTimeStamp":
time.strftime("%Y-%m-%d %H:%M:%S", time.localtime())
}
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
for key in list(statistics_all.keys()):
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
keys = [
"High resolution limit",
"Low resolution limit",
"Completeness",
"Multiplicity",
"I/sigma",
"Rmerge(I+/-)",
"CC half",
"Anomalous completeness",
"Anomalous correlation",
"Anomalous multiplicity",
"Total observations",
"Total unique",
"Rmeas(I)",
"Rmeas(I+/-)",
"Rpim(I)",
"Rpim(I+/-)",
"Partial Bias",
]
stats = [k for k in keys if k in statistics_all[key]]
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
tmp["AutoProcScalingStatistics"] = []
tmp2 = tmp["AutoProcScalingStatistics"]
for j, name in enumerate(
["overall", "innerShell", "outerShell"]):
statistics_cache = {"scalingStatisticsType": name}
for s in stats:
if s in self._name_map:
n = self._name_map[s]
else:
continue
if isinstance(statistics_all[key][s], type([])):
statistics_cache[n] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[n] = statistics_all[key][s][j]
tmp2.append(statistics_cache)
tmp["AutoProcIntegrationContainer"] = []
tmp2 = tmp["AutoProcIntegrationContainer"]
for sweep in sweeps:
if "#" in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
cell = sweep.get_integrater_cell()
intgr_tmp = {}
for name, value in zip(
["a", "b", "c", "alpha", "beta", "gamma"], cell):
intgr_tmp["cell_%s" % name] = value
# FIXME this is naughty
indxr = sweep._get_indexer()
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
intgr_tmp["startImageNumber"] = start
intgr_tmp["endImageNumber"] = end
intgr_tmp[
"refinedDetectorDistance"] = indxr.get_indexer_distance(
)
beam = indxr.get_indexer_beam_centre_raw_image()
intgr_tmp["refinedXBeam"] = beam[0]
intgr_tmp["refinedYBeam"] = beam[1]
tmp2.append({
"Image": {
"fileName": os.path.split(image_name)[-1],
"fileLocation":
sanitize(os.path.split(image_name)[0]),
},
"AutoProcIntegration": intgr_tmp,
})
# file unpacking nonsense
result["AutoProcProgramContainer"] = {}
tmp = result["AutoProcProgramContainer"]
tmp2 = {}
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
tmp2["processingCommandLine"] = sanitize(command_line)
tmp2["processingProgram"] = "xia2"
tmp["AutoProcProgram"] = tmp2
tmp["AutoProcProgramAttachment"] = []
tmp2 = tmp["AutoProcProgramAttachment"]
data_directory = self._project.path / "DataFiles"
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type("")):
continue
reflection_file = FileHandler.get_data_file(
self._project.path, reflection_file)
basename = os.path.basename(reflection_file)
if data_directory.joinpath(basename).exists():
# Use file in DataFiles directory in preference (if it exists)
reflection_file = str(data_directory.joinpath(basename))
tmp2.append({
"fileType":
"Result",
"fileName":
os.path.split(reflection_file)[-1],
"filePath":
sanitize(os.path.split(reflection_file)[0]),
})
tmp2.append({
"fileType": "Log",
"fileName": "xia2.txt",
"filePath": sanitize(os.getcwd()),
})
return result
def write_xml(self, file, command_line="", working_phil=None):
if working_phil is not None:
PhilIndex.merge_phil(working_phil)
params = PhilIndex.get_python_object()
fout = open(file, "w")
fout.write('<?xml version="1.0"?>')
fout.write("<AutoProcContainer>\n")
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write("<AutoProc><spaceGroup>%s</spaceGroup>" % spacegroup)
self.write_refined_cell(fout, cell)
fout.write("</AutoProc>")
fout.write("<AutoProcScalingContainer>")
fout.write("<AutoProcScaling>")
self.write_date(fout)
fout.write("</AutoProcScaling>")
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
for key in statistics_all:
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
keys = [
"High resolution limit",
"Low resolution limit",
"Completeness",
"Multiplicity",
"I/sigma",
"Rmerge(I+/-)",
"CC half",
"Anomalous completeness",
"Anomalous correlation",
"Anomalous multiplicity",
"Total observations",
"Total unique",
"Rmeas(I)",
"Rmeas(I+/-)",
"Rpim(I)",
"Rpim(I+/-)",
"Partial Bias",
]
stats = [k for k in keys if k in statistics_all[key]]
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(
["overall", "innerShell", "outerShell"]):
statistics_cache = {}
for s in stats:
if isinstance(statistics_all[key][s], type([])):
statistics_cache[s] = statistics_all[key][s][j]
elif isinstance(statistics_all[key][s], type(())):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name, statistics_cache)
for sweep in sweeps:
fout.write("<AutoProcIntegrationContainer>\n")
if "#" in sweep.get_template():
image_name = sweep.get_image_name(0)
else:
image_name = os.path.join(sweep.get_directory(),
sweep.get_template())
fout.write("<Image><fileName>%s</fileName>" %
os.path.split(image_name)[-1])
fout.write("<fileLocation>%s</fileLocation></Image>" %
sanitize(os.path.split(image_name)[0]))
fout.write("<AutoProcIntegration>\n")
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write("<startImageNumber>%d</startImageNumber>" %
start)
fout.write("<endImageNumber>%d</endImageNumber>" % end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
"<refinedDetectorDistance>%f</refinedDetectorDistance>"
% indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre_raw_image()
fout.write("<refinedXBeam>%f</refinedXBeam>" % beam[0])
fout.write("<refinedYBeam>%f</refinedYBeam>" % beam[1])
fout.write("</AutoProcIntegration>\n")
fout.write("</AutoProcIntegrationContainer>\n")
fout.write("</AutoProcScalingContainer>")
# file unpacking nonsense
if not command_line:
from xia2.Handlers.CommandLine import CommandLine
command_line = CommandLine.get_command_line()
pipeline = params.xia2.settings.pipeline
fout.write("<AutoProcProgramContainer><AutoProcProgram>")
fout.write("<processingCommandLine>%s</processingCommandLine>" %
sanitize(command_line))
fout.write("<processingPrograms>xia2 %s</processingPrograms>" %
pipeline)
fout.write("</AutoProcProgram>")
data_directory = self._project.path / "DataFiles"
log_directory = self._project.path / "LogFiles"
for k in reflection_files:
reflection_file = reflection_files[k]
if not isinstance(reflection_file, type("")):
continue
reflection_file = FileHandler.get_data_file(
self._project.path, reflection_file)
basename = os.path.basename(reflection_file)
if data_directory.joinpath(basename).exists():
# Use file in DataFiles directory in preference (if it exists)
reflection_file = str(data_directory.joinpath(basename))
fout.write("<AutoProcProgramAttachment><fileType>Result")
fout.write("</fileType><fileName>%s</fileName>" %
os.path.split(reflection_file)[-1])
fout.write("<filePath>%s</filePath>" %
sanitize(os.path.split(reflection_file)[0]))
fout.write("</AutoProcProgramAttachment>\n")
g = log_directory.glob("*merging-statistics.json")
for merging_stats_json in g:
fout.write("<AutoProcProgramAttachment><fileType>Graph")
fout.write("</fileType><fileName>%s</fileName>" %
os.path.split(str(merging_stats_json))[-1])
fout.write("<filePath>%s</filePath>" %
sanitize(str(log_directory)))
fout.write("</AutoProcProgramAttachment>\n")
# add the xia2.txt file...
fout.write("<AutoProcProgramAttachment><fileType>Log")
fout.write("</fileType><fileName>xia2.txt</fileName>")
fout.write("<filePath>%s</filePath>" % sanitize(os.getcwd()))
fout.write("</AutoProcProgramAttachment>\n")
fout.write("</AutoProcProgramContainer>")
fout.write("</AutoProcContainer>\n")
fout.close()
def write_xml(self, file):
fout = open(file, 'w')
fout.write('<?xml version="1.0"?>')
fout.write('<AutoProcContainer>\n')
for crystal in sorted(self._crystals):
xcrystal = self._crystals[crystal]
cell = xcrystal.get_cell()
spacegroup = xcrystal.get_likely_spacegroups()[0]
fout.write('<AutoProc><spaceGroup>%s</spaceGroup>' % spacegroup)
self.write_refined_cell(fout, cell)
fout.write('</AutoProc>')
fout.write('<AutoProcScalingContainer>')
fout.write('<AutoProcScaling>')
self.write_date(fout)
fout.write('</AutoProcScaling>')
statistics_all = xcrystal.get_statistics()
reflection_files = xcrystal.get_scaled_merged_reflections()
wavelength_names = xcrystal.get_wavelength_names()
for key in statistics_all.keys():
pname, xname, dname = key
# FIXME should assert that the dname is a
# valid wavelength name
available = statistics_all[key].keys()
stats = []
keys = [
'High resolution limit',
'Low resolution limit',
'Completeness',
'Multiplicity',
'I/sigma',
'Rmerge(I+/I-)',
'CC half',
'Anomalous completeness',
'Anomalous correlation',
'Anomalous multiplicity',
'Total observations',
'Total unique',
'Rmeas(I)',
'Rmeas(I+,-)',
'Rpim(I)',
'Rpim(I+/-)',
'Partial Bias'
]
for k in keys:
if k in available:
stats.append(k)
xwavelength = xcrystal.get_xwavelength(dname)
sweeps = xwavelength.get_sweeps()
for j, name in enumerate(
['overall', 'innerShell', 'outerShell']):
statistics_cache = { }
for s in stats:
if type(statistics_all[key][s]) == type([]):
statistics_cache[s] = statistics_all[key][s][j]
elif type(statistics_all[key][s]) == type(()):
statistics_cache[s] = statistics_all[key][s][j]
# send these to be written out
self.write_scaling_statistics(fout, name,
statistics_cache)
for sweep in sweeps:
fout.write('<AutoProcIntegrationContainer>\n')
image_name = sweep.get_all_image_names()[0]
fout.write('<Image><fileName>%s</fileName>' % \
os.path.split(image_name)[-1])
fout.write('<fileLocation>%s</fileLocation></Image>' %
sanitize(os.path.split(image_name)[0]))
fout.write('<AutoProcIntegration>\n')
cell = sweep.get_integrater_cell()
self.write_cell(fout, cell)
# FIXME this is naughty
intgr = sweep._get_integrater()
start, end = intgr.get_integrater_wedge()
fout.write('<startImageNumber>%d</startImageNumber>' % \
start)
fout.write('<endImageNumber>%d</endImageNumber>' % \
end)
# FIXME this is naughty
indxr = sweep._get_indexer()
fout.write(
'<refinedDetectorDistance>%f</refinedDetectorDistance>' % \
indxr.get_indexer_distance())
beam = indxr.get_indexer_beam_centre()
fout.write('<refinedXBeam>%f</refinedXBeam>' % beam[0])
fout.write('<refinedYBeam>%f</refinedYBeam>' % beam[1])
fout.write('</AutoProcIntegration>\n')
fout.write('</AutoProcIntegrationContainer>\n')
fout.write('</AutoProcScalingContainer>')
# file unpacking nonsense
from xia2.Handlers.CommandLine import CommandLine
fout.write('<AutoProcProgramContainer><AutoProcProgram>')
fout.write('<processingCommandLine>%s</processingCommandLine>' \
% sanitize(CommandLine.get_command_line()))
fout.write('<processingPrograms>xia2</processingPrograms>')
fout.write('</AutoProcProgram>')
for k in reflection_files:
reflection_file = reflection_files[k]
if not type(reflection_file) == type(''):
continue
reflection_file = FileHandler.get_data_file(reflection_file)
fout.write(
'<AutoProcProgramAttachment><fileType>Result')
fout.write('</fileType><fileName>%s</fileName>' % \
os.path.split(reflection_file)[-1])
fout.write('<filePath>%s</filePath>' % \
sanitize(os.path.split(reflection_file)[0]))
fout.write('</AutoProcProgramAttachment>\n')
# add the xia2.txt file...
fout.write('<AutoProcProgramAttachment><fileType>Log')
fout.write('</fileType><fileName>xia2.txt</fileName>')
fout.write('<filePath>%s</filePath>' % sanitize(os.getcwd()))
fout.write('</AutoProcProgramAttachment>\n')
fout.write('</AutoProcProgramContainer>')
fout.write('</AutoProcContainer>\n')
fout.close()
return
def get_output(self):
result = 'Crystal: %s\n' % self._name
if self._aa_sequence:
result += 'Sequence: %s\n' % self._aa_sequence.get_sequence()
for wavelength in self._wavelengths.keys():
result += self._wavelengths[wavelength].get_output()
scaler = self._get_scaler()
if scaler.get_scaler_finish_done():
for wname, xwav in self._wavelengths.iteritems():
for xsweep in xwav.get_sweeps():
idxr = xsweep._get_indexer()
if PhilIndex.params.xia2.settings.show_template:
result += '%s\n' %banner('Autoindexing %s (%s)' %(
idxr.get_indexer_sweep_name(), idxr.get_template()))
else:
result += '%s\n' %banner(
'Autoindexing %s' %idxr.get_indexer_sweep_name())
result += '%s\n' %idxr.show_indexer_solutions()
intgr = xsweep._get_integrater()
if PhilIndex.params.xia2.settings.show_template:
result += '%s\n' %banner('Integrating %s (%s)' %(
intgr.get_integrater_sweep_name(), intgr.get_template()))
else:
result += '%s\n' %banner(
'Integrating %s' %intgr.get_integrater_sweep_name())
result += '%s\n' % intgr.show_per_image_statistics()
result += '%s\n' %banner('Scaling %s' %self.get_name())
for (dname, sname), (limit, suggested) in scaler.get_scaler_resolution_limits().iteritems():
if suggested is None or limit == suggested:
result += 'Resolution limit for %s/%s: %5.2f\n' %(dname, sname, limit)
else:
result += 'Resolution limit for %s/%s: %5.2f (%5.2f suggested)\n' %(dname, sname, limit, suggested)
# this is now deprecated - be explicit in what you are
# asking for...
reflections_all = self.get_scaled_merged_reflections()
statistics_all = self._get_scaler().get_scaler_statistics()
# print some of these statistics, perhaps?
for key in statistics_all.keys():
result += format_statistics(statistics_all[key], caption='For %s/%s/%s' % key)
# then print out some "derived" information based on the
# scaling - this is presented through the Scaler interface
# explicitly...
cell = self._get_scaler().get_scaler_cell()
cell_esd = self._get_scaler().get_scaler_cell_esd()
spacegroups = self._get_scaler().get_scaler_likely_spacegroups()
spacegroup = spacegroups[0]
resolution = self._get_scaler().get_scaler_highest_resolution()
from cctbx import sgtbx
sg = sgtbx.space_group_type(str(spacegroup))
spacegroup = sg.lookup_symbol()
CIF.set_spacegroup(sg)
mmCIF.set_spacegroup(sg)
if len(self._wavelengths) == 1:
CIF.set_wavelengths([w.get_wavelength() for w in self._wavelengths.itervalues()])
mmCIF.set_wavelengths([w.get_wavelength() for w in self._wavelengths.itervalues()])
else:
for wavelength in self._wavelengths.keys():
full_wave_name = '%s_%s_%s' % (self._project._name, self._name, wavelength)
CIF.get_block(full_wave_name)['_diffrn_radiation_wavelength'] = \
self._wavelengths[wavelength].get_wavelength()
mmCIF.get_block(full_wave_name)['_diffrn_radiation_wavelength'] = \
self._wavelengths[wavelength].get_wavelength()
CIF.set_wavelengths({name: wave.get_wavelength() for name, wave in self._wavelengths.iteritems()})
mmCIF.set_wavelengths({name: wave.get_wavelength() for name, wave in self._wavelengths.iteritems()})
result += 'Assuming spacegroup: %s\n' % spacegroup
if len(spacegroups) > 1:
result += 'Other likely alternatives are:\n'
for sg in spacegroups[1:]:
result += '%s\n' % sg
if cell_esd:
from libtbx.utils import format_float_with_standard_uncertainty
def match_formatting(dimA, dimB):
def conditional_split(s):
return (s[:s.index('.')],s[s.index('.'):]) if '.' in s else (s, '')
A, B = conditional_split(dimA), conditional_split(dimB)
maxlen = (max(len(A[0]), len(B[0])), max(len(A[1]), len(B[1])))
return (
A[0].rjust(maxlen[0])+A[1].ljust(maxlen[1]),
B[0].rjust(maxlen[0])+B[1].ljust(maxlen[1])
)
formatted_cell_esds = tuple(format_float_with_standard_uncertainty(v, sd) for v, sd in zip(cell, cell_esd))
formatted_rows = (formatted_cell_esds[0:3], formatted_cell_esds[3:6])
formatted_rows = zip(*(match_formatting(l, a) for l, a in zip(*formatted_rows)))
result += 'Unit cell (with estimated std devs):\n'
result += '%s %s %s\n%s %s %s\n' % (formatted_rows[0] + formatted_rows[1])
else:
result += 'Unit cell:\n'
result += '%7.3f %7.3f %7.3f\n%7.3f %7.3f %7.3f\n' % tuple(cell)
# now, use this information and the sequence (if provided)
# and also matthews_coef (should I be using this directly, here?)
# to compute a likely number of molecules in the ASU and also
# the solvent content...
if self._aa_sequence:
residues = self._aa_sequence.get_sequence()
if residues:
nres = len(residues)
# first compute the number of molecules using the K&R
# method
nmol = compute_nmol(cell[0], cell[1], cell[2],
cell[3], cell[4], cell[5],
spacegroup, resolution, nres)
# then compute the solvent fraction
solvent = compute_solvent(cell[0], cell[1], cell[2],
cell[3], cell[4], cell[5],
spacegroup, nmol, nres)
result += 'Likely number of molecules in ASU: %d\n' % nmol
result += 'Giving solvent fraction: %4.2f\n' % solvent
self._nmol = nmol
if type(reflections_all) == type({}):
for format in reflections_all.keys():
result += '%s format:\n' % format
reflections = reflections_all[format]
if type(reflections) == type({}):
for wavelength in reflections.keys():
target = FileHandler.get_data_file(
reflections[wavelength])
result += 'Scaled reflections (%s): %s\n' % \
(wavelength, target)
else:
target = FileHandler.get_data_file(
reflections)
result += 'Scaled reflections: %s\n' % target
CIF.write_cif()
mmCIF.write_cif()
return result
