def cut_resolution(self, cycle_number):
def est_resol(xscale_hkl, res_params, plt_out):
iobs = XDS_ASCII(xscale_hkl, i_only=True).i_obs()
est = estimate_resolution_based_on_cc_half(iobs, res_params.cc_one_half_min,
res_params.cc_half_tol,
res_params.n_bins, log_out=self.out)
est.show_plot(False, plt_out)
if None not in (est.d_min, est.cc_at_d_min):
self.out.write("Best resolution cutoff= %.2f A @CC1/2= %.4f\n" % (est.d_min, est.cc_at_d_min))
else:
self.out.write("Can't decide resolution cutoff. No reflections??\n")
return est.d_min
# est_resol()
print >>self.out, "**** Determining resolution cutoff in run_%.2d ****" % cycle_number
last_wd = os.path.join(self.workdir_org, "run_%.2d"%cycle_number)
xscale_hkl = os.path.abspath(os.path.join(last_wd, "xscale.hkl"))
tmpwd = os.path.join(self.workdir_org, "run_%.2d_tmp"%cycle_number)
os.mkdir(tmpwd)
for i, cc_cut in enumerate((self.res_params.cc_one_half_min*.7, self.res_params.cc_one_half_min)):
self.res_params.cc_one_half_min = cc_cut
d_min = est_resol(xscale_hkl, self.res_params,
os.path.join(tmpwd, "ccfit_%d.pdf"%(i+1)))
if d_min is not None and d_min > self.d_min + 0.001:
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(tmpwd, f))
inp_new = os.path.join(tmpwd, "XSCALE.INP")
shutil.copyfile(os.path.join(last_wd, "XSCALE.INP"), inp_new)
modify_xdsinp(inp_new, [make_bin_str(d_min, self.d_max).split("= ")])
try:
xscale.run_xscale(inp_new, cbf_to_dat=True, aniso_analysis=True,
use_tmpdir_if_available=self.xscale_params.use_tmpdir_if_available)
except:
print >>self.out, traceback.format_exc()
xscale_hkl = os.path.abspath(os.path.join(tmpwd, "xscale.hkl"))
if not os.path.isfile(os.path.join(tmpwd, "XSCALE.INP")):
for f in "XSCALE.INP", "XSCALE.LP", "xscale.hkl", "pointless.log", "ccp4":
os.symlink(os.path.relpath(os.path.join(last_wd, f), tmpwd),
os.path.join(tmpwd, f))
if d_min is not None:
self.dmin_est_at_cycles[cycle_number] = d_min
os.rename(tmpwd, os.path.join(self.workdir_org, "run_%.2d_%.2fA"%(cycle_number, d_min)))
def run_dials_sequence(filename_template, prefix, nr_range, wdir, known_xs,
overrides, scan_varying, nproc):
log_out = open(os.path.join(wdir, "dials_sequence.log"), "w")
pointless_log = os.path.join(wdir, "pointless.log")
# Prepare
img_files = find_existing_files_in_template(
filename_template,
nr_range[0],
nr_range[1],
datadir=os.path.dirname(prefix),
check_compressed=True)
if len(img_files) == 0:
mylog.error("No files found for %s %s" % (filename_template, nr_range))
return
nproc_str = "nproc=%d" % nproc
log_out.write("Importing %s range=%s\n" % (img_files, nr_range))
log_out.write(" Overrides: %s\n" % overrides)
log_out.flush()
override_str = "" # TODO support other stuff.. (wavelength, distance, osc_range, rotation_axis,..)
if "orgx" in overrides and "orgy" in overrides:
override_str += "slow_fast_beam_centre=%.2f,%.2f " % (
overrides["orgy"], overrides["orgx"])
if len(img_files) == 1 and img_files[0].endswith(".h5"):
util.call('dials.import "%s" %s image_range=%d,%d' %
(img_files[0], override_str, nr_range[0], nr_range[1]),
wdir=wdir,
stdout=log_out,
expects_out=[os.path.join(wdir, "datablock.json")])
else:
util.call('dials.import %s template="%s" image_range=%d,%d' %
(override_str, filename_template.replace(
"?", "#"), nr_range[0], nr_range[1]),
wdir=wdir,
stdout=log_out,
expects_out=[os.path.join(wdir, "datablock.json")])
util.call(
"dials.find_spots datablock.json filter.d_max=30 %s" %
nproc_str, # global_threshold=200
wdir=wdir,
stdout=log_out,
expects_out=[os.path.join(wdir, "strong.pickle")])
util.call("dials.export strong.pickle format=xds xds.directory=.",
wdir=wdir,
stdout=log_out)
index_ok = False
for index_meth in ("fft3d", "fft1d", "real_space_grid_search"):
for index_assi in ("local", "simple"):
if index_ok: break
cmd = "dials.index datablock.json strong.pickle verbosity=3 "
cmd += "indexing.method=%s index_assignment.method=%s " % (
index_meth, index_assi)
if known_xs is not None: # not in (known.space_group, known.unit_cell):
cmd += "unit_cell=%s space_group=%d " % (
",".join(
map(lambda x: "%.3f" % x,
known_xs.unit_cell().parameters())),
known_xs.space_group().type().number())
elif index_meth == "real_space_grid_search":
continue
log_out.write(
"Trying indexing.method=%s index_assignment.method=%s\n" %
(index_meth, index_assi))
log_out.flush()
util.call(cmd, wdir=wdir, stdout=log_out)
if os.path.isfile(os.path.join(wdir, "experiments.json")):
index_ok = True
else:
for f in ("dials.index.log", "dials.index.debug.log"):
util.rotate_file(os.path.join(wdir, f))
if not index_ok:
return
files_for_integration = "experiments.json indexed.pickle"
if scan_varying:
util.call(
"dials.refine experiments.json indexed.pickle scan_varying=true",
wdir=wdir,
stdout=log_out)
if os.path.isfile(os.path.join(wdir, "refined.pickle")):
files_for_integration = "refined_experiments.json refined.pickle"
else:
log_out.write("dials.refine failed. using intedexed results.\n")
util.call("dials.integrate %s min_spots.per_degree=10 %s" %
(files_for_integration, nproc_str),
wdir=wdir,
stdout=log_out)
util.call(
"dials.export integrated.pickle integrated_experiments.json mtz.hklout=integrated.mtz",
wdir=wdir,
stdout=log_out)
util.call("pointless integrated.mtz hklout pointless.mtz",
wdir=wdir,
stdin="SETTING SYMMETRY-BASED\ntolerance 10\n",
stdout=open(pointless_log, "w"))
util.call(
"dials.export integrated_experiments.json integrated.pickle format=xds_ascii xds_ascii.hklout=DIALS.HKL",
wdir=wdir,
stdout=log_out)
util.call("aimless hklin pointless.mtz hklout aimless.mtz",
wdir=wdir,
stdin="output UNMERGED\n",
stdout=open(os.path.join(wdir, "aimless.log"), "w"))
#job_str += "touch dials_job_finished\n"
ret = calc_merging_stats(os.path.join(wdir, "aimless_unmerged.mtz"))
ret["symm"] = get_most_possible_symmetry(wdir)
pickle.dump(ret, open(os.path.join(wdir, "kamo_dials.pkl"), "w"), -1)
def xds_sequence(root, params):
print
print os.path.relpath(root, params.topdir)
xparm = os.path.join(root, "XPARM.XDS")
gxparm = os.path.join(root, "GXPARM.XDS")
defpix_lp = os.path.join(root, "DEFPIX.LP")
correct_lp = os.path.join(root, "CORRECT.LP")
integrate_hkl = os.path.join(root, "INTEGRATE.HKL")
xac_hkl = os.path.join(root, "XDS_ASCII.HKL")
integrate_lp = os.path.join(root, "INTEGRATE.LP")
spot_xds = os.path.join(root, "SPOT.XDS")
xdsinp = os.path.join(root, "XDS.INP")
assert os.path.isfile(xdsinp)
xdsinp_dict = dict(get_xdsinp_keyword(xdsinp))
decilog = multi_out()
decilog.register("log",
open(os.path.join(root, "decision.log"), "a"),
atexit_send_to=None)
print >> decilog, "xds_sequence started at %s in %s\n" % (
time.strftime("%Y-%m-%d %H:%M:%S"), root)
if params.show_progress:
decilog.register("stdout", sys.stdout)
if params.mode == "initial" and params.resume and os.path.isfile(
correct_lp):
print " Already processed."
return
if params.mode == "recycle" and not os.path.isfile(gxparm):
print "GXPARM.XDS not found. Cannot do recycle."
return
if params.fast_delphi and (params.nproc is None or params.nproc > 1):
delphi = optimal_delphi_by_nproc(xdsinp=xdsinp, nproc=params.nproc)
print " Setting delphi to ", delphi
modify_xdsinp(xdsinp, inp_params=[
("DELPHI", str(delphi)),
])
if params.nproc is not None and params.nproc > 1:
modify_xdsinp(xdsinp,
inp_params=[
("MAXIMUM_NUMBER_OF_PROCESSORS", str(params.nproc)),
])
if params.mode == "initial":
# Peak search
modify_xdsinp(xdsinp, inp_params=[("JOB", "XYCORR INIT COLSPOT")])
run_xds(wdir=root, show_progress=params.show_progress)
if params.auto_frame_exclude_spot_based:
sx = idxreflp.SpotXds(spot_xds)
sx.set_xdsinp(xdsinp)
spots = filter(lambda x: 5 < x[-1] < 30,
sx.collected_spots()) # low-res (5 A)
frame_numbers = numpy.array(map(lambda x: int(x[2]) + 1, spots))
data_range = map(int, xdsinp_dict["DATA_RANGE"].split())
# XXX this assumes SPOT_RANGE equals to DATA_RANGE. Is this guaranteed?
h = numpy.histogram(frame_numbers,
bins=numpy.arange(data_range[0],
data_range[1] + 2,
step=1))
q14 = numpy.percentile(h[0], [25, 75])
iqr = q14[1] - q14[0]
cutoff = max(h[0][h[0] <= iqr * 1.5 + q14[1]]) / 5 # magic number
print "DEBUG:: IQR= %.2f, Q1/4= %s, cutoff= %.2f" % (iqr, q14,
cutoff)
cut_frames = h[1][h[0] < cutoff]
keep_frames = h[1][h[0] >= cutoff]
print "DEBUG:: keep_frames=", keep_frames
print "DEBUG:: cut_frames=", cut_frames
if len(cut_frames) > 0:
cut_ranges = [
[cut_frames[0], cut_frames[0]],
]
for fn in cut_frames:
if fn - cut_ranges[-1][1] <= 1: cut_ranges[-1][1] = fn
else: cut_ranges.append([fn, fn])
# Edit XDS.INP
cut_inp_str = "".join(
map(lambda x: "EXCLUDE_DATA_RANGE= %6d %6d\n" % tuple(x),
cut_ranges))
open(xdsinp, "a").write("\n" + cut_inp_str)
# Edit SPOT.XDS
shutil.copyfile(spot_xds, spot_xds + ".org")
sx.write(open(spot_xds, "w"), frame_selection=set(keep_frames))
# Indexing
modify_xdsinp(xdsinp, inp_params=[("JOB", "IDXREF")])
run_xds(wdir=root, show_progress=params.show_progress)
print # indexing stats like indexed percentage here.
if params.tryhard:
try_indexing_hard(root,
params.show_progress,
decilog,
known_sgnum=params.cell_prior.sgnum,
known_cell=params.cell_prior.cell,
tol_length=params.cell_prior.tol_length,
tol_angle=params.cell_prior.tol_angle)
if not os.path.isfile(xparm):
print >> decilog, " Indexing failed."
return
if params.cell_prior.check and params.cell_prior.sgnum > 0:
xsxds = XPARM(xparm).crystal_symmetry()
xsref = crystal.symmetry(params.cell_prior.cell,
params.cell_prior.sgnum)
cosets = reindex.reindexing_operators(xsref, xsxds,
params.cell_prior.tol_length,
params.cell_prior.tol_angle)
if cosets.double_cosets is None:
print >> decilog, " Incompatible cell. Indexing failed."
return
elif params.mode == "recycle":
print " Start recycle. original ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
for f in xds_files.generated_after_DEFPIX + ("XPARM.XDS",
"plot_integrate.log"):
util.rotate_file(os.path.join(root, f), copy=True)
shutil.copyfile(gxparm + ".1", xparm)
else:
raise "Unknown mode (%s)" % params.mode
# To Integration
modify_xdsinp(xdsinp,
inp_params=[("JOB", "DEFPIX INTEGRATE"),
("INCLUDE_RESOLUTION_RANGE", "50 0")])
run_xds(wdir=root, show_progress=params.show_progress)
if os.path.isfile(integrate_lp):
xds_plot_integrate.run(integrate_lp,
os.path.join(root, "plot_integrate.log"))
if not os.path.isfile(integrate_hkl):
print >> decilog, " Integration failed."
return
# Make _noscale.HKL if needed
if params.no_scaling:
bk_prefix = make_backup(("XDS.INP", ), wdir=root, quiet=True)
xparm_obj = XPARM(xparm)
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "CORRECT"),
("CORRECTIONS", ""),
("NBATCH", "1"),
("MINIMUM_I/SIGMA", "50"),
("REFINE(CORRECT)", ""),
("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x, xparm_obj.unit_cell))),
("SPACE_GROUP_NUMBER", "%d" % xparm_obj.spacegroup),
])
print >> decilog, " running CORRECT without empirical scaling"
run_xds(wdir=root, show_progress=params.show_progress)
for f in xds_files.generated_by_CORRECT + ("XDS.INP", ):
ff = os.path.join(root, f)
if not os.path.isfile(ff): continue
if ff.endswith(".cbf"):
os.remove(ff)
else:
os.rename(ff, ff + "_noscale")
revert_files(("XDS.INP", ), bk_prefix, wdir=root, quiet=True)
# Run pointless
symm_by_integrate = None
if params.use_pointless:
worker = Pointless()
result = worker.run_for_symm(xdsin=integrate_hkl,
logout=os.path.join(
root, "pointless_integrate.log"))
if "symm" in result:
symm = result["symm"]
print >> decilog, " pointless using INTEGRATE.HKL suggested", symm.space_group_info(
)
sgnum = symm.space_group_info().type().number()
cell = " ".join(
map(lambda x: "%.2f" % x,
symm.unit_cell().parameters()))
modify_xdsinp(xdsinp,
inp_params=[("SPACE_GROUP_NUMBER", "%d" % sgnum),
("UNIT_CELL_CONSTANTS", cell)])
symm_by_integrate = symm
else:
print >> decilog, " pointless failed."
# Do Scaling
modify_xdsinp(xdsinp, inp_params=[
("JOB", "CORRECT"),
])
run_xds(wdir=root, show_progress=params.show_progress)
if not os.path.isfile(gxparm):
print >> decilog, " Scaling failed."
return
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(correct_lp,
check_valid=True)
ret = calc_merging_stats(os.path.join(root, "XDS_ASCII.HKL"))
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp,
inp_params=[("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE",
"50 %.2f" % d_min)])
print >> decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"),
os.path.join(root, "CORRECT_fullres.LP"))
os.rename(os.path.join(root, "XDS_ASCII.HKL"),
os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root, show_progress=params.show_progress)
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
print >> decilog, " (Original files are saved as *_fullres.*)"
else:
print >> decilog, "error: Can't decide resolution."
last_ISa = correctlp.get_ISa(correct_lp, check_valid=True)
# Run pointless and (if result is different from INTEGRATE) re-scale.
if params.use_pointless:
worker = Pointless()
result = worker.run_for_symm(xdsin=xac_hkl,
logout=os.path.join(
root, "pointless_correct.log"))
if "symm" in result:
symm = result["symm"]
need_rescale = False
if symm_by_integrate is not None:
if not xtal.is_same_laue_symmetry(
symm_by_integrate.space_group(), symm.space_group()):
print >> decilog, "pointless suggested %s, which is different Laue symmetry from INTEGRATE.HKL (%s)" % (
symm.space_group_info(),
symm_by_integrate.space_group_info())
need_rescale = True
else:
print >> decilog, "pointless using XDS_ASCII.HKL suggested %s" % symm.space_group_info(
)
need_rescale = True
if need_rescale:
# make backup, and do correct and compare ISa
# if ISa got worse, revert the result.
backup_needed = ("XDS.INP", "XDS_ASCII_fullres.HKL",
"CORRECT_fullres.LP", "merging_stats.pkl",
"merging_stats.log")
backup_needed += xds_files.generated_by_CORRECT
bk_prefix = make_backup(backup_needed, wdir=root, quiet=True)
sgnum = symm.space_group_info().type().number()
cell = " ".join(
map(lambda x: "%.2f" % x,
symm.unit_cell().parameters()))
modify_xdsinp(xdsinp,
inp_params=[("JOB", "CORRECT"),
("SPACE_GROUP_NUMBER", "%d" % sgnum),
("UNIT_CELL_CONSTANTS", cell),
("INCLUDE_RESOLUTION_RANGE", "50 0")
])
run_xds(wdir=root, show_progress=params.show_progress)
ret = calc_merging_stats(os.path.join(root, "XDS_ASCII.HKL"))
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp,
inp_params=[("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE",
"50 %.2f" % d_min)])
print >> decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"),
os.path.join(root, "CORRECT_fullres.LP"))
os.rename(os.path.join(root, "XDS_ASCII.HKL"),
os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root, show_progress=params.show_progress)
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
print >> decilog, " (Original files are saved as *_fullres.*)"
else:
print >> decilog, "error: Can't decide resolution."
for f in ("CORRECT_fullres.LP",
"XDS_ASCII_fullres.HKL"):
if os.path.isfile(os.path.join(root, f)):
print >> decilog, "removing", f
os.remove(os.path.join(root, f))
ISa = correctlp.get_ISa(correct_lp, check_valid=True)
if ISa >= last_ISa or last_ISa != last_ISa: # if improved or last_ISa is nan
print >> decilog, "ISa improved= %.2f" % ISa
remove_backups(backup_needed, bk_prefix, wdir=root)
else:
print >> decilog, "ISa got worse= %.2f" % ISa
for f in backup_needed:
if os.path.isfile(os.path.join(root, f)):
os.remove(os.path.join(root, f))
revert_files(backup_needed,
bk_prefix,
wdir=root,
quiet=True)
run_xdsstat(wdir=root)
print
if params.make_report: html_report.make_individual_report(root, root)
print >> decilog, "xds_sequence finished at %s\n" % time.strftime(
"%Y-%m-%d %H:%M:%S")
decilog.close()
def run_cycle(self, xds_ascii_files, reference_idx=None):
if len(xds_ascii_files) == 0:
print >>self.out, "Error: no files given."
return
xscale_inp = os.path.join(self.workdir, "XSCALE.INP")
xscale_lp = os.path.join(self.workdir, "XSCALE.LP")
# Get averaged cell for scaling
sg, cell, lcv, alcv = self.average_cells(xds_ascii_files)
self.cell_info_at_cycles[self.get_last_cycle_number()] = (cell, lcv, alcv)
# Choose directory containing XDS_ASCII.HKL and set space group (but how??)
inp_out = open(xscale_inp, "w")
inp_out.write("MAXIMUM_NUMBER_OF_PROCESSORS= %d\n" % self.nproc)
inp_out.write("SPACE_GROUP_NUMBER= %s\nUNIT_CELL_CONSTANTS= %s\n\n" % (sg, cell))
inp_out.write(self.xscale_inp_head)
for i, xds_ascii in enumerate(xds_ascii_files):
f = self.altfile.get(xds_ascii, xds_ascii)
tmp = min(os.path.relpath(f, self.workdir), f, key=lambda x:len(x))
refstr = "*" if i==reference_idx else " "
inp_out.write(" INPUT_FILE=%s%s\n" % (refstr,tmp))
if len(self.xscale_params.corrections) != 3:
inp_out.write(" CORRECTIONS= %s\n" % " ".join(self.xscale_params.corrections))
if self.xscale_params.frames_per_batch is not None:
frame_range = XDS_ASCII(f, read_data=False).get_frame_range()
nframes = frame_range[1] - frame_range[0]
nbatch = int(numpy.ceil(nframes / self.xscale_params.frames_per_batch))
print >>self.out, "frame range of %s is %d,%d setting NBATCH= %d" % (f, frame_range[0], frame_range[1], nbatch)
inp_out.write(" NBATCH= %d\n" % nbatch)
inp_out.close()
print >>self.out, "DEBUG:: running xscale with %3d files.." % len(xds_ascii_files)
try:
xscale.run_xscale(xscale_inp, cbf_to_dat=True,
use_tmpdir_if_available=self.xscale_params.use_tmpdir_if_available)
except:
print >>self.out, traceback.format_exc()
xscale_log = open(xscale_lp).read()
if "!!! ERROR !!! INSUFFICIENT NUMBER OF COMMON STRONG REFLECTIONS." in xscale_log:
print >>self.out, "DEBUG:: Need to choose files."
# From XDS ver. March 1, 2015, it kindly informs which dataset has no common reflections.
# ..but does not print the table. Sometimes only one dataset is left. Should we make table by ourselves?
# Older versions just print correlation table and stop.
if "CORRELATIONS BETWEEN INPUT DATA SETS AFTER CORRECTIONS" in xscale_log:
G = xscalelp.construct_data_graph(xscale_lp, min_common_refs=10)
#nx.write_dot(G, os.path.join(self.workdir, "common_set_graph.dot"))
cliques = [c for c in nx.find_cliques(G)]
cliques.sort(key=lambda x:len(x))
if self._counter == 1:
max_clique = cliques[-1]
else:
idx_prevfile = 1 if self.reference_file else 0
max_clique = filter(lambda x: idx_prevfile in x, cliques)[-1] # xscale.hkl must be included!
if self.reference_file:
max_clique = [0,] + filter(lambda x: x!=0, max_clique)
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
try_later = map(lambda i: xds_ascii_files[i], filter(lambda x: x not in max_clique, G.nodes()))
print >>self.out, "DEBUG:: %d files can be merged. %d files will be merged later." % (len(max_clique),
len(try_later))
print >>self.out, "DEBUG:: %d files are of no use." % (len(xds_ascii_files)-len(G.nodes()))
for i in filter(lambda j: j not in G.nodes(), xrange(len(xds_ascii_files))):
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "no_common_refls"
self.run_cycle(map(lambda i: xds_ascii_files[i], max_clique))
assert len(try_later) <= 0 # Never be the case with newer xscale!! (if the case, check_remove_list() should be modified to skip_num+=1
if len(try_later) > 0:
print >>self.out, "Trying to merge %d remaining files.." % len(try_later)
next_files = [os.path.join(self.workdir, "xscale.hkl")] + try_later
if self.reference_file: next_files = [self.reference_file,] + next_files
self.workdir = self.request_next_workdir()
self.run_cycle(next_files)
return
else:
bad_idxes = xscalelp.read_no_common_ref_datasets(xscale_lp)
print >>self.out, "DEBUG:: %d files are of no use." % (len(bad_idxes))
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
# XXX Actually, not all datasets need to be thrown.. some of them are useful..
for i in bad_idxes:
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "no_common_refls"
self.run_cycle(map(lambda i: xds_ascii_files[i],
filter(lambda j: j not in bad_idxes, xrange(len(xds_ascii_files)))))
return
elif "!!! ERROR !!! USELESS DATA ON INPUT REFLECTION FILE" in xscale_log:
print >>self.out, "DEBUG:: Need to discard useless data."
unuseful_data = [xscalelp.get_read_data(xscale_lp)[-1]] #filter(lambda x: x[2]==0, xscalelp.get_read_data(xscale_lp))
if len(unuseful_data) == 0:
print >>self.out, "I don't know how to fix it.."
return
remove_idxes = map(lambda x: x[0]-1, unuseful_data)
remove_idxes = self.check_remove_list(remove_idxes)
keep_idxes = filter(lambda x: x not in remove_idxes, xrange(len(xds_ascii_files)))
for i in remove_idxes:
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "useless"
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes))
return
elif "INACCURATE SCALING FACTORS." in xscale_log:
# Actually I don't know how to fix this.. (bug?) but worth proceeding (discarding bad data may solve problem).
print >>self.out, "'INACCURATE SCALING FACTORS' happened.. but ignored."
elif "!!! ERROR !!!" in xscale_log:
print >>self.out, "Unknown error! please check the XSCALE.LP and fix the program."
return
# Re-scale by changing reference
rescale_for = None
if len(self.reject_method) == 0:
rescale_for = self.reference_choice # may be None
elif reference_idx is None:
rescale_for = "bmed"
if rescale_for is not None and len(xds_ascii_files) > 1:
ref_num = xscale.decide_scaling_reference_based_on_bfactor(xscale_lp, rescale_for, return_as="index")
if reference_idx != ref_num:
print >>self.out, "Rescaling with %s" % rescale_for
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(xds_ascii_files, reference_idx=ref_num)
if len(self.reject_method) == 0:
return
# Remove bad data
remove_idxes = []
remove_reasons = {}
if self.reject_method[0] == "framecc":
print >>self.out, "Rejections based on frame CC"
from yamtbx.dataproc.xds.command_line import xscale_cc_against_merged
# list of [frame, n_all, n_common, cc] in the same order
framecc = xscale_cc_against_merged.run(hklin=os.path.join(self.workdir, "xscale.hkl"),
output_dir=self.workdir,
nproc=self.nproc).values()
if self.reject_params.framecc.method == "tukey":
ccs = numpy.array(map(lambda x: x[3], reduce(lambda x,y:x+y,framecc)))
ccs = ccs[ccs==ccs] # Remove nan
q25, q75 = numpy.percentile(ccs, [25, 75])
cc_cutoff = q25 - self.reject_params.framecc.iqr_coeff * (q75 - q25)
print >>self.out, " frameCC cutoff = %.4f (%.2f*IQR)" % (cc_cutoff, self.reject_params.framecc.iqr_coeff)
else:
cc_cutoff = self.reject_params.framecc.abs_cutoff
print >>self.out, " frameCC cutoff = %.4f (value specified)" % cc_cutoff
for i, cclist in enumerate(framecc):
useframes = map(lambda x: x[0], filter(lambda x: x[3] > cc_cutoff, cclist))
if len(useframes) == 0:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("allbadframe")
continue
f = xds_ascii_files[i]
xac = XDS_ASCII(f)
if set(useframes).issuperset(set(range(min(xac.iframe), max(xac.iframe)))):
continue # All useful frames.
sel = xac.iframe == useframes[0]
for x in useframes[1:]: sel |= xac.iframe == x
if sum(sel) < 10: # XXX care I/sigma
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("allbadframe")
continue
print >>self.out, "Extracting frames %s out of %d-%d in %s" % (",".join(map(str,useframes)),
min(xac.iframe), max(xac.iframe),
f)
newf = self.request_file_modify(f)
xac.write_selected(sel, newf)
self.reject_method.pop(0) # Perform only once
elif self.reject_method[0] == "lpstats":
if "bfactor" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on B-factor outliers (%.2f*IQR)" % iqrc
Bs = numpy.array(map(lambda x:x[1], xscalelp.get_k_b(xscale_lp)))
q25, q75 = numpy.percentile(Bs, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, b in enumerate(Bs):
if b < lowlim or b > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_B")
count += 1
print >>self.out, " %4d B-factor outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "em.b" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on error model b outliers (%.2f*IQR)" % iqrc
bs = numpy.array(map(lambda x:x[1], xscalelp.get_ISa(xscale_lp)))
q25, q75 = numpy.percentile(bs, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, b in enumerate(bs):
if b < lowlim or b > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_em.b")
count += 1
print >>self.out, " %4d error model b outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "em.ab" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on error model a*b outliers (%.2f*IQR)" % iqrc
vals = numpy.array(map(lambda x:x[0]*x[1], xscalelp.get_ISa(xscale_lp)))
q25, q75 = numpy.percentile(vals, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, ab in enumerate(vals):
if ab < lowlim or ab > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_em.ab")
count += 1
print >>self.out, " %4d error model a*b outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "rfactor" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on R-factor outliers (%.2f*IQR)" % iqrc
rstats = xscalelp.get_rfactors_for_each(xscale_lp)
vals = numpy.array(map(lambda x:rstats[x][-1][1], rstats)) # Read total R-factor
q25, q75 = numpy.percentile(vals, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, v in enumerate(vals):
if v < lowlim or v > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_R")
count += 1
print >>self.out, " %4d R-factor outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "pairwise_cc" in self.reject_params.lpstats.stats:
corrs = xscalelp.get_pairwise_correlations(xscale_lp)
if self.reject_params.lpstats.pwcc.method == "tukey":
q25, q75 = numpy.percentile(map(lambda x: x[3], corrs), [25, 75])
iqr = q75 - q25
lowlim = q25 - self.reject_params.lpstats.pwcc.iqr_coeff * iqr
print >>self.out, "Rejections based on pairwise_cc < %.4f (IQR=%.2f)" % (lowlim, iqr)
else:
lowlim = self.reject_params.lpstats.pwcc.abs_cutoff
print >>self.out, "Rejections based on pairwise_cc < %.4f" % lowlim
bad_corrs = filter(lambda x: x[3] < lowlim, corrs)
idx_bad = {}
for i, j, common_refs, corr, ratio, bfac in bad_corrs:
idx_bad[i] = idx_bad.get(i, 0) + 1
idx_bad[j] = idx_bad.get(j, 0) + 1
idx_bad = idx_bad.items()
idx_bad.sort(key=lambda x:x[1])
count = 0
for idx, badcount in reversed(idx_bad):
remove_idxes.append(idx-1)
remove_reasons.setdefault(idx-1, []).append("bad_pwcc")
bad_corrs = filter(lambda x: idx not in x[:2], bad_corrs)
if len(bad_corrs) == 0: break
fun_key = lambda x: x[3]
print >>self.out, " Removing idx=%d (CC %.3f..%.3f) remaining %d bad pairs" % (idx,
min(bad_corrs,key=fun_key)[3],
max(bad_corrs,key=fun_key)[3],
len(bad_corrs))
count += 1
print >>self.out, " %4d pairwise CC outliers removed" % count
self.reject_method.pop(0) # Perform only once
elif self.reject_method[0] == "delta_cc1/2":
print >>self.out, "Rejection based on delta_CC1/2 in %s shell" % self.delta_cchalf_bin
table = xscalelp.read_stats_table(xscale_lp)
i_stat = -1 if self.delta_cchalf_bin == "total" else -2
prev_cchalf = table["cc_half"][i_stat]
prev_nuniq = table["nuniq"][i_stat]
# file_name->idx table
remaining_files = collections.OrderedDict(map(lambda x: x[::-1], enumerate(xds_ascii_files)))
# For consistent resolution limit
inp_head = self.xscale_inp_head + "SPACE_GROUP_NUMBER= %s\nUNIT_CELL_CONSTANTS= %s\n\n" % (sg, cell)
count = 0
for i in xrange(len(xds_ascii_files)-1): # if only one file, cannot proceed.
tmpdir = os.path.join(self.workdir, "reject_test_%.3d" % i)
cchalf_list = xscale.calc_cchalf_by_removing(wdir=tmpdir, inp_head=inp_head,
inpfiles=remaining_files.keys(),
stat_bin=self.delta_cchalf_bin,
nproc=self.nproc,
nproc_each=self.nproc_each,
batchjobs=self.batchjobs)
rem_idx, cc_i, nuniq_i = cchalf_list[0] # First (largest) is worst one to remove.
rem_idx_in_org = remaining_files[remaining_files.keys()[rem_idx]]
# Decision making by CC1/2
print >>self.out, "DEBUG:: cycle %.3d remove %3d if %.2f*%d > %.2f*%d" % (i, rem_idx_in_org,
cc_i, nuniq_i,
prev_cchalf, prev_nuniq)
if cc_i*nuniq_i <= prev_cchalf*prev_nuniq: break
print >>self.out, "Removing idx= %3d gained CC1/2 by %.2f" % (rem_idx_in_org, cc_i-prev_cchalf)
prev_cchalf, prev_nuniq = cc_i, nuniq_i
remove_idxes.append(rem_idx_in_org)
remove_reasons.setdefault(rem_idx_in_org, []).append("bad_cchalf")
del remaining_files[remaining_files.keys()[rem_idx]] # remove file from table
count += 1
print >>self.out, " %4d removed by DeltaCC1/2 method" % count
if self.next_delta_cchalf_bin != []:
self.delta_cchalf_bin = self.next_delta_cchalf_bin.pop(0)
else:
self.reject_method.pop(0)
else:
print >>self.out, "ERROR:: Unsupported reject_method (%s)" % reject_method
# Remove duplicates
remove_idxes = list(set(remove_idxes))
remove_idxes = self.check_remove_list(remove_idxes)
if len(remove_idxes) > 0:
print >>self.out, "DEBUG:: Need to remove %d files" % len(remove_idxes)
for i in sorted(remove_idxes):
print >>self.out, " %.3d %s" % (i, xds_ascii_files[i])
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = ",".join(remove_reasons[i])
# Next run
keep_idxes = filter(lambda x: x not in remove_idxes, xrange(len(xds_ascii_files)))
if len(self.reject_method) > 0 or len(remove_idxes) > 0:
self.workdir = self.request_next_workdir()
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes))
elif self.reference_choice is not None and len(keep_idxes) > 1:
# Just re-scale with B reference
ref_num = xscale.decide_scaling_reference_based_on_bfactor(xscale_lp, self.reference_choice, return_as="index")
if reference_idx != ref_num:
print >>self.out, "Rescaling2 with %s" % self.reference_choice
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes), reference_idx=ref_num)
def run(params, xac_files):
if len(xac_files) == 0:
print "No XDS_ASCII.HKL files provided."
return
# Parse
dmin_dict = {}
if params.dmin_lst:
for l in open(params.dmin_lst):
sp = l.split()
if len(sp) != 2: continue
f, dmin = sp
dmin_dict[f] = dmin
xscale_inp_head = "!MINIMUM_I/SIGMA= 3\n\n"
if params.wfac1 is not None:
xscale_inp_head += "WFAC1= %.3f\n" % params.wfac1
if params.nproc:
xscale_inp_head += "MAXIMUM_NUMBER_OF_PROCESSORS= %d\n" % params.nproc
infos = {}
d_max, d_min = 0, 100
cells = []
for xds_ascii in xac_files:
info = get_xac_info(xds_ascii, get_nframes=params.frames_per_batch is not None)
if xds_ascii in dmin_dict:
dmax,dmin = info["resol_range"].split()
info["resol_range_user"] = "******" % (dmax, dmin_dict[xds_ascii])
infos[xds_ascii] = info
resrng = map(float, info["resol_range"].split())
d_max = max(d_max, resrng[0])
d_min = min(d_min, resrng[1])
cells.append(map(float, info["cell"].split()))
if params.d_min is not None:
d_min = max(params.d_min, d_min)
if params.cell == "average":
cell_sum = reduce(lambda x,y: map(lambda a: a[0]+a[1], zip(x,y)), cells)
cell_mean = map(lambda x: x/float(len(cells)), cell_sum)
if params.sgnum is not None: sgnum = str(params.sgnum)
else: sgnum = infos[xac_files[0]]["spgr_num"]
xscale_inp_head += " SPACE_GROUP_NUMBER= %s\n" % sgnum
xscale_inp_head += " UNIT_CELL_CONSTANTS= %s\n" % " ".join(map(lambda x: "%.3f"%x, cell_mean))
xscale_inp_head += make_shells(d_max, d_min, params.nbins) + "\n"
xscale_inp_head += " OUTPUT_FILE= %s\n" % params.output
xscale_inp_head += " FRIEDEL'S_LAW= %s\n\n" % ("FALSE" if params.anomalous else "TRUE")
prep_xscale_inp(params.workdir, xscale_inp_head, xac_files, infos, params.frames_per_batch, params.corrections)
xscale.run_xscale(os.path.join(params.workdir, "XSCALE.INP"),
cbf_to_dat=params.cbf_to_dat,
use_tmpdir_if_available=params.use_tmpdir_if_available)
if params.reference:
print "Choosing reference data (reference=%s)" % params.reference
ref_idx = xscale.decide_scaling_reference_based_on_bfactor(os.path.join(params.workdir, "XSCALE.LP"), params.reference, return_as="index")
if ref_idx != 0:
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(params.workdir, f))
prep_xscale_inp(params.workdir, xscale_inp_head, xac_files, infos, params.frames_per_batch, params.corrections, ref_idx=ref_idx)
xscale.run_xscale(os.path.join(params.workdir, "XSCALE.INP"),
cbf_to_dat=params.cbf_to_dat,
use_tmpdir_if_available=params.use_tmpdir_if_available)
def xds_sequence(root, params):
print
print os.path.relpath(root, params.topdir)
init_lp = os.path.join(root, "INIT.LP")
xparm = os.path.join(root, "XPARM.XDS")
gxparm = os.path.join(root, "GXPARM.XDS")
defpix_lp = os.path.join(root, "DEFPIX.LP")
correct_lp = os.path.join(root, "CORRECT.LP")
integrate_hkl = os.path.join(root, "INTEGRATE.HKL")
xac_hkl = os.path.join(root, "XDS_ASCII.HKL")
integrate_lp = os.path.join(root, "INTEGRATE.LP")
spot_xds = os.path.join(root, "SPOT.XDS")
xdsinp = os.path.join(root, "XDS.INP")
assert os.path.isfile(xdsinp)
if params.cell_prior.force: assert params.cell_prior.check
xdsinp_dict = dict(get_xdsinp_keyword(xdsinp))
if params.cell_prior.sgnum > 0:
xs_prior = crystal.symmetry(params.cell_prior.cell,
params.cell_prior.sgnum)
else:
xs_prior = None
decilog = multi_out()
decilog.register("log",
open(os.path.join(root, "decision.log"), "a"),
atexit_send_to=None)
try:
print >> decilog, "xds_sequence started at %s in %s\n" % (
time.strftime("%Y-%m-%d %H:%M:%S"), root)
if not kamo_test_installation.tst_xds():
print >> decilog, "XDS is not installed or expired!!"
return
if params.show_progress:
decilog.register("stdout", sys.stdout)
if params.mode == "initial" and params.resume and os.path.isfile(
correct_lp):
print >> decilog, " Already processed."
return
if params.mode == "recycle" and not os.path.isfile(gxparm):
print >> decilog, "GXPARM.XDS not found. Cannot do recycle."
return
if params.fast_delphi and (params.nproc is None or params.nproc > 1):
delphi = optimal_delphi_by_nproc(xdsinp=xdsinp, nproc=params.nproc)
print >> decilog, " Setting delphi to ", delphi
modify_xdsinp(xdsinp, inp_params=[
("DELPHI", str(delphi)),
])
if params.nproc is not None and params.nproc > 1:
modify_xdsinp(xdsinp,
inp_params=[
("MAXIMUM_NUMBER_OF_PROCESSORS",
str(params.nproc)),
])
if params.mode == "initial":
modify_xdsinp(xdsinp, inp_params=[("JOB", "XYCORR INIT")])
run_xds(wdir=root, show_progress=params.show_progress)
initlp = InitLp(init_lp)
first_bad = initlp.check_bad_first_frames()
if first_bad:
print >> decilog, " first frames look bad (too weak) exposure:", first_bad
new_data_range = map(
int,
dict(get_xdsinp_keyword(xdsinp))["DATA_RANGE"].split())
new_data_range[0] = first_bad[-1] + 1
print >> decilog, " changing DATA_RANGE= to", new_data_range
modify_xdsinp(xdsinp,
inp_params=[("JOB", "INIT"),
("DATA_RANGE",
"%d %d" % tuple(new_data_range))])
for f in xds_files.generated_by_INIT:
util.rotate_file(os.path.join(root, f), copy=False)
run_xds(wdir=root, show_progress=params.show_progress)
# Peak search
modify_xdsinp(xdsinp, inp_params=[("JOB", "COLSPOT")])
run_xds(wdir=root, show_progress=params.show_progress)
if params.auto_frame_exclude_spot_based:
sx = idxreflp.SpotXds(spot_xds)
sx.set_xdsinp(xdsinp)
spots = filter(lambda x: 5 < x[-1] < 30,
sx.collected_spots()) # low-res (5 A)
frame_numbers = numpy.array(map(lambda x: int(x[2]) + 1,
spots))
data_range = map(
int,
dict(get_xdsinp_keyword(xdsinp))["DATA_RANGE"].split())
# XXX this assumes SPOT_RANGE equals to DATA_RANGE. Is this guaranteed?
h = numpy.histogram(frame_numbers,
bins=numpy.arange(data_range[0],
data_range[1] + 2,
step=1))
q14 = numpy.percentile(h[0], [25, 75])
iqr = q14[1] - q14[0]
cutoff = max(
h[0][h[0] <= iqr * 1.5 + q14[1]]) / 5 # magic number
print >> decilog, "DEBUG:: IQR= %.2f, Q1/4= %s, cutoff= %.2f" % (
iqr, q14, cutoff)
cut_frames = h[1][h[0] < cutoff]
keep_frames = h[1][h[0] >= cutoff]
print >> decilog, "DEBUG:: keep_frames=", keep_frames
print >> decilog, "DEBUG:: cut_frames=", cut_frames
if len(cut_frames) > 0:
cut_ranges = [
[cut_frames[0], cut_frames[0]],
]
for fn in cut_frames:
if fn - cut_ranges[-1][1] <= 1: cut_ranges[-1][1] = fn
else: cut_ranges.append([fn, fn])
# Edit XDS.INP
cut_inp_str = "".join(
map(
lambda x: "EXCLUDE_DATA_RANGE= %6d %6d\n" % tuple(
x), cut_ranges))
open(xdsinp, "a").write("\n" + cut_inp_str)
# Edit SPOT.XDS
shutil.copyfile(spot_xds, spot_xds + ".org")
sx.write(open(spot_xds, "w"),
frame_selection=set(keep_frames))
# Indexing
if params.cell_prior.method == "use_first":
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "IDXREF"),
("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x,
params.cell_prior.cell))),
("SPACE_GROUP_NUMBER",
"%d" % params.cell_prior.sgnum),
])
else:
modify_xdsinp(xdsinp, inp_params=[("JOB", "IDXREF")])
run_xds(wdir=root, show_progress=params.show_progress)
print >> decilog, "" # TODO indexing stats like indexed percentage here.
if params.tryhard:
try_indexing_hard(root,
params.show_progress,
decilog,
known_sgnum=params.cell_prior.sgnum,
known_cell=params.cell_prior.cell,
tol_length=params.cell_prior.tol_length,
tol_angle=params.cell_prior.tol_angle)
if not os.path.isfile(xparm):
print >> decilog, " Indexing failed."
return
if params.cell_prior.sgnum > 0:
# Check anyway
xsxds = XPARM(xparm).crystal_symmetry()
cosets = reindex.reindexing_operators(
xs_prior, xsxds, params.cell_prior.tol_length,
params.cell_prior.tol_angle)
if cosets.double_cosets is None:
if params.cell_prior.check:
print >> decilog, " Incompatible cell. Indexing failed."
return
else:
print >> decilog, " Warning: Incompatible cell."
elif params.cell_prior.method == "symm_constraint_only":
cell = xsxds.unit_cell().change_basis(
cosets.combined_cb_ops()[0])
print >> decilog, " Trying symmetry-constrained cell parameter:", cell
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "IDXREF"),
("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x,
cell.parameters()))),
("SPACE_GROUP_NUMBER",
"%d" % params.cell_prior.sgnum),
])
for f in xds_files.generated_by_IDXREF:
util.rotate_file(os.path.join(root, f),
copy=(f == "SPOT.XDS"))
run_xds(wdir=root, show_progress=params.show_progress)
if not os.path.isfile(xparm):
print >> decilog, " Indexing failed."
return
# Check again
xsxds = XPARM(xparm).crystal_symmetry()
if not xsxds.unit_cell().is_similar_to(
xs_prior.unit_cell(), params.cell_prior.tol_length,
params.cell_prior.tol_angle):
print >> decilog, " Resulted in different cell. Indexing failed."
return
elif params.mode == "recycle":
print >> decilog, " Start recycle. original ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
for f in xds_files.generated_after_DEFPIX + ("XPARM.XDS",
"plot_integrate.log"):
util.rotate_file(os.path.join(root, f), copy=True)
shutil.copyfile(gxparm + ".1", xparm)
else:
raise "Unknown mode (%s)" % params.mode
# To Integration
modify_xdsinp(xdsinp,
inp_params=[("JOB", "DEFPIX INTEGRATE"),
("INCLUDE_RESOLUTION_RANGE", "50 0")])
run_xds(wdir=root, show_progress=params.show_progress)
if os.path.isfile(integrate_lp):
xds_plot_integrate.run(integrate_lp,
os.path.join(root, "plot_integrate.log"))
if not os.path.isfile(integrate_hkl):
print >> decilog, " Integration failed."
return
# Make _noscale.HKL if needed
if params.no_scaling:
bk_prefix = make_backup(("XDS.INP", ), wdir=root, quiet=True)
xparm_obj = XPARM(xparm)
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "CORRECT"),
("CORRECTIONS", ""),
("NBATCH", "1"),
("MINIMUM_I/SIGMA", "50"),
("REFINE(CORRECT)", ""),
("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x,
xparm_obj.unit_cell))),
("SPACE_GROUP_NUMBER",
"%d" % xparm_obj.spacegroup),
])
print >> decilog, " running CORRECT without empirical scaling"
run_xds(wdir=root, show_progress=params.show_progress)
for f in xds_files.generated_by_CORRECT + ("XDS.INP", ):
ff = os.path.join(root, f)
if not os.path.isfile(ff): continue
if ff.endswith(".cbf"):
os.remove(ff)
else:
os.rename(ff, ff + "_noscale")
revert_files(("XDS.INP", ), bk_prefix, wdir=root, quiet=True)
# Run pointless
pointless_integrate = {}
if params.use_pointless:
worker = Pointless()
pointless_integrate = worker.run_for_symm(
xdsin=integrate_hkl,
logout=os.path.join(root, "pointless_integrate.log"))
if "symm" in pointless_integrate:
symm = pointless_integrate["symm"]
print >> decilog, " pointless using INTEGRATE.HKL suggested", symm.space_group_info(
)
if xs_prior:
if xtal.is_same_space_group_ignoring_enantiomorph(
symm.space_group(), xs_prior.space_group()):
print >> decilog, " which is consistent with given symmetry."
elif xtal.is_same_laue_symmetry(symm.space_group(),
xs_prior.space_group()):
print >> decilog, " which has consistent Laue symmetry with given symmetry."
else:
print >> decilog, " which is inconsistent with given symmetry."
sgnum = symm.space_group_info().type().number()
cell = " ".join(
map(lambda x: "%.2f" % x,
symm.unit_cell().parameters()))
modify_xdsinp(xdsinp,
inp_params=[("SPACE_GROUP_NUMBER", "%d" % sgnum),
("UNIT_CELL_CONSTANTS", cell)])
else:
print >> decilog, " pointless failed."
flag_do_not_change_symm = False
if xs_prior and params.cell_prior.force:
modify_xdsinp(xdsinp,
inp_params=[("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x,
params.cell_prior.cell))),
("SPACE_GROUP_NUMBER",
"%d" % params.cell_prior.sgnum)])
flag_do_not_change_symm = True
elif params.cell_prior.method == "correct_only":
xsxds = XPARM(xparm).crystal_symmetry()
cosets = reindex.reindexing_operators(xs_prior, xsxds,
params.cell_prior.tol_length,
params.cell_prior.tol_angle)
if cosets.double_cosets is not None:
cell = xsxds.unit_cell().change_basis(
cosets.combined_cb_ops()[0])
print >> decilog, " Using given symmetry in CORRECT with symmetry constraints:", cell
modify_xdsinp(xdsinp,
inp_params=[
("UNIT_CELL_CONSTANTS", " ".join(
map(lambda x: "%.3f" % x,
cell.parameters()))),
("SPACE_GROUP_NUMBER",
"%d" % params.cell_prior.sgnum),
])
flag_do_not_change_symm = True
else:
print >> decilog, " Tried to use given symmetry in CORRECT, but cell in integration is incompatible."
# Do Scaling
modify_xdsinp(xdsinp, inp_params=[
("JOB", "CORRECT"),
])
run_xds(wdir=root, show_progress=params.show_progress)
if not os.path.isfile(xac_hkl):
print >> decilog, " CORRECT failed."
return
if not os.path.isfile(gxparm):
print >> decilog, " Refinement in CORRECT failed."
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
ret = calc_merging_stats(xac_hkl)
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp,
inp_params=[("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE",
"50 %.2f" % d_min)])
print >> decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"),
os.path.join(root, "CORRECT_fullres.LP"))
os.rename(xac_hkl, os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root, show_progress=params.show_progress)
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
print >> decilog, " (Original files are saved as *_fullres.*)"
else:
print >> decilog, "error: Can't decide resolution."
last_ISa = correctlp.get_ISa(correct_lp, check_valid=True)
# Run pointless and (if result is different from INTEGRATE) re-scale.
if params.use_pointless:
worker = Pointless()
pointless_correct = worker.run_for_symm(
xdsin=xac_hkl,
logout=os.path.join(root, "pointless_correct.log"))
pointless_best_symm = None
if "symm" in pointless_correct:
symm = pointless_correct["symm"]
need_rescale = False
if pointless_integrate.get("symm"):
symm_by_integrate = pointless_integrate["symm"]
if not xtal.is_same_laue_symmetry(
symm_by_integrate.space_group(),
symm.space_group()):
print >> decilog, "pointless suggested %s, which is different Laue symmetry from INTEGRATE.HKL (%s)" % (
symm.space_group_info(),
symm_by_integrate.space_group_info())
prob_integrate = pointless_integrate.get(
"laue_prob", float("nan"))
prob_correct = pointless_correct.get(
"laue_prob", float("nan"))
print >> decilog, " Prob(%s |INTEGRATE), Prob(%s |CORRECT) = %.4f, %.4f." % (
symm_by_integrate.space_group_info(),
symm.space_group_info(), prob_integrate,
prob_correct)
if prob_correct > prob_integrate:
need_rescale = True
pointless_best_symm = symm
else:
pointless_best_symm = symm_by_integrate
else:
need_rescale = True
pointless_best_symm = symm
print >> decilog, "pointless using XDS_ASCII.HKL suggested %s" % symm.space_group_info(
)
if xs_prior:
if xtal.is_same_space_group_ignoring_enantiomorph(
symm.space_group(), xs_prior.space_group()):
print >> decilog, " which is consistent with given symmetry."
elif xtal.is_same_laue_symmetry(
symm.space_group(), xs_prior.space_group()):
print >> decilog, " which has consistent Laue symmetry with given symmetry."
else:
print >> decilog, " which is inconsistent with given symmetry."
if need_rescale and not flag_do_not_change_symm:
sgnum = symm.space_group_info().type().number()
cell = " ".join(
map(lambda x: "%.2f" % x,
symm.unit_cell().parameters()))
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "CORRECT"),
("SPACE_GROUP_NUMBER", "%d" % sgnum),
("UNIT_CELL_CONSTANTS", cell),
("INCLUDE_RESOLUTION_RANGE", "50 0")
])
run_xds(wdir=root, show_progress=params.show_progress)
ret = calc_merging_stats(xac_hkl)
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE",
"50 %.2f" % d_min)
])
print >> decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"),
os.path.join(root, "CORRECT_fullres.LP"))
os.rename(
xac_hkl,
os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root,
show_progress=params.show_progress)
print >> decilog, " OK. ISa= %.2f" % correctlp.get_ISa(
correct_lp, check_valid=True)
print >> decilog, " (Original files are saved as *_fullres.*)"
else:
print >> decilog, "error: Can't decide resolution."
for f in ("CORRECT_fullres.LP",
"XDS_ASCII_fullres.HKL"):
if os.path.isfile(os.path.join(root, f)):
print >> decilog, "removing", f
os.remove(os.path.join(root, f))
ISa = correctlp.get_ISa(correct_lp, check_valid=True)
if ISa >= last_ISa or last_ISa != last_ISa: # if improved or last_ISa is nan
print >> decilog, "ISa improved= %.2f" % ISa
else:
print >> decilog, "ISa got worse= %.2f" % ISa
if pointless_best_symm:
xac_symm = XDS_ASCII(xac_hkl, read_data=False).symm
if not xtal.is_same_space_group_ignoring_enantiomorph(
xac_symm.space_group(),
pointless_best_symm.space_group()):
if xtal.is_same_laue_symmetry(
xac_symm.space_group(),
pointless_best_symm.space_group()):
tmp = "same Laue symmetry"
else:
tmp = "different Laue symmetry"
print >> decilog, "WARNING: symmetry in scaling is different from Pointless result (%s)." % tmp
run_xdsstat(wdir=root)
print
if params.make_report: html_report.make_individual_report(root, root)
except:
print >> decilog, traceback.format_exc()
finally:
print >> decilog, "\nxds_sequence finished at %s" % time.strftime(
"%Y-%m-%d %H:%M:%S")
decilog.close()
def try_indexing_hard(wdir,
show_progress,
decilog,
known_sgnum=None,
known_cell=None,
tol_length=None,
tol_angle=None):
idxref_lp = os.path.join(wdir, "IDXREF.LP")
xdsinp = os.path.join(wdir, "XDS.INP")
lp_org = idxreflp.IdxrefLp(idxref_lp)
if lp_org.is_cell_maybe_half():
backup_needed = ("XDS.INP", ) + xds_files.generated_by_IDXREF
print >> decilog, " !! Cell may be halved. Trying doubled cell."
bk_prefix = make_backup(backup_needed, wdir=wdir, quiet=True)
cell = lp_org.deduce_correct_cell_based_on_integerness()
cell = " ".join(map(lambda x: "%.2f" % x, cell.parameters()))
modify_xdsinp(xdsinp,
inp_params=[("JOB", "IDXREF"),
("SPACE_GROUP_NUMBER", "1"),
("UNIT_CELL_CONSTANTS", cell)])
for f in xds_files.generated_by_IDXREF:
util.rotate_file(os.path.join(wdir, f), copy=(f == "SPOT.XDS"))
run_xds(wdir=wdir, show_progress=show_progress)
if idxreflp.IdxrefLp(idxref_lp).is_cell_maybe_half():
revert_files(backup_needed, bk_prefix, wdir=wdir, quiet=True)
print >> decilog, " .. not solved. Next, try decreasing SEPMIN= and CLUSTER_RADIUS=."
bk_prefix = make_backup(backup_needed, wdir=wdir, quiet=True)
modify_xdsinp(xdsinp,
inp_params=[("JOB", "IDXREF"), ("SEPMIN", "4"),
("CLUSTER_RADIUS", "2")])
for f in xds_files.generated_by_IDXREF:
util.rotate_file(os.path.join(wdir, f), copy=(f == "SPOT.XDS"))
run_xds(wdir=wdir, show_progress=show_progress)
if idxreflp.IdxrefLp(idxref_lp).is_cell_maybe_half():
print >> decilog, " .. not solved. Give up."
revert_files(backup_needed, bk_prefix, wdir=wdir, quiet=True)
else:
print >> decilog, " Now OK."
remove_backups(backup_needed, bk_prefix, wdir=wdir)
modify_xdsinp(xdsinp, inp_params=[
("SPACE_GROUP_NUMBER", "0"),
])
# If Cell hint exists, try to use it..
if known_sgnum > 0:
flag_try_cell_hint = False
xparm = os.path.join(wdir, "XPARM.XDS")
if not os.path.isfile(xparm):
flag_try_cell_hint = True
else:
xsxds = XPARM(xparm).crystal_symmetry()
xsref = crystal.symmetry(known_cell, known_sgnum)
cosets = reindex.reindexing_operators(xsref, xsxds, tol_length,
tol_angle)
if cosets.double_cosets is None: flag_try_cell_hint = True
if flag_try_cell_hint:
print >> decilog, " Worth trying to use prior cell for indexing."
modify_xdsinp(xdsinp,
inp_params=[
("JOB", "IDXREF"),
("UNIT_CELL_CONSTANTS",
" ".join(map(lambda x: "%.3f" % x,
known_cell))),
("SPACE_GROUP_NUMBER", "%d" % known_sgnum),
])
for f in xds_files.generated_by_IDXREF:
util.rotate_file(os.path.join(wdir, f), copy=(f == "SPOT.XDS"))
run_xds(wdir=wdir, show_progress=False)
modify_xdsinp(xdsinp, inp_params=[
("SPACE_GROUP_NUMBER", "0"),
])
def find_spots(img_file, params):
"""
Use XDS to locate spots.
If params.xds.do_defpix is true, DEFPIX will be run. For DEFPIX, dummy XPARM.XDS is needed. Thanks to DEFPIX, we can mask beam stop shadow and remove areas outside the resolution range.
If false, we need to set TRUSTED_REGION to exclude regions outside resolution range, but it is independent of beam center. Maybe we should remove spots outside the resolution range after XDS run?
"""
# Test if ramdisk available
if os.path.isdir("/dev/shm"):
work_dir = tempfile.mkdtemp(
prefix="shika_x_" +
os.path.splitext(os.path.basename(img_file))[0],
dir="/dev/shm")
else:
work_dir = os.path.join(
params.work_dir,
"xds_" + os.path.splitext(os.path.basename(img_file))[0])
xdsinp = os.path.join(work_dir, "XDS.INP")
spot_xds = os.path.join(work_dir, "SPOT.XDS")
if not os.path.exists(work_dir):
os.mkdir(work_dir)
template_str, min_frame, max_frame = dataset.group_img_files_template(
[img_file])[0]
im = XIO.Image(img_file)
# Remove lines if None (means to use default)
params_maps = [
("strong_pixel", "STRONG_PIXEL="),
("minimum_number_of_pixels_in_a_spot",
"MINIMUM_NUMBER_OF_PIXELS_IN_A_SPOT="),
("background_pixel", "BACKGROUND_PIXEL="),
("maximum_number_of_strong_pixels",
"MAXIMUM_NUMBER_OF_STRONG_PIXELS="),
("spot_maximum_centroid", "SPOT_MAXIMUM-CENTROID="),
("reflecting_range", "REFLECTING_RANGE="),
("value_range_for_trusted_detector_pixels",
"VALUE_RANGE_FOR_TRUSTED_DETECTOR_PIXELS="),
]
tmp = xds_inp_template.splitlines()
for p, x in params_maps:
if getattr(params.xds, p) is None:
tmp = filter(lambda s: not s.startswith(x), tmp)
inp_template = "\n".join(tmp)
# Prepare XDS.INP
inp_str = inp_template % dict(
template=os.path.relpath(template_str, work_dir),
framenum=min_frame,
orgx=im.header["BeamX"] / im.header["PixelX"],
orgy=im.header["BeamY"] / im.header["PixelY"],
distance=im.header["Distance"],
osc_range=im.header["PhiWidth"],
wavelength=im.header["Wavelength"],
strong_pixel=params.xds.strong_pixel,
min_pixels=params.xds.minimum_number_of_pixels_in_a_spot,
background_pixel=params.xds.background_pixel,
max_strong_pixels=params.xds.maximum_number_of_strong_pixels,
spot_maximum_centroid=params.xds.spot_maximum_centroid,
reflecting_range=params.xds.reflecting_range,
nx=im.header["Width"],
ny=im.header["Height"],
qx=im.header["PixelX"],
qy=im.header["PixelY"],
defpix_trusted1=params.xds.value_range_for_trusted_detector_pixels[0],
defpix_trusted2=params.xds.value_range_for_trusted_detector_pixels[1])
open(xdsinp, "w").write(inp_str)
if params.xds.do_defpix:
xp = xparm.XPARM()
xp.set_info_from_xdsinp(xdsinp)
open(os.path.join(work_dir, "XPARM.XDS"), "w").write(xp.xparm_str())
modify_xdsinp(xdsinp,
inp_params=[("JOB", "XYCORR INIT DEFPIX"),
("INCLUDE_RESOLUTION_RANGE",
res_range_for_xds(params.distl.res.outer,
params.distl.res.inner))])
call("xds",
wdir=work_dir,
stdout=open(os.path.join(work_dir, "xds.log"), "w"))
shutil.copy(os.path.join(work_dir, "BKGPIX.cbf"),
os.path.join(work_dir, "BKGINIT.cbf"))
modify_xdsinp(xdsinp, inp_params=[("JOB", "COLSPOT")])
else:
modify_xdsinp(xdsinp,
inp_params=[
("TRUSTED_REGION",
res_range_to_trusted_region(params.distl.res.outer,
params.distl.res.inner,
im.header))
])
open(os.path.join(work_dir, "xds.log"), "w").write("")
# Run XDS
rotate_file(spot_xds)
call("xds",
wdir=work_dir,
stdout=open(os.path.join(work_dir, "xds.log"), "a"))
# Extract results
spots = [] # (x, y, d, intensity)
if os.path.isfile(spot_xds):
for l in open(spot_xds):
x, y, z, intensity = map(lambda x: float(x), l.strip().split())
d = coord_to_resol(x, y, im.header)
spots.append((x, y, d, intensity))
# Delete dir
shutil.rmtree(work_dir)
return spots
def run(params, xac_files):
if len(xac_files) == 0:
print "No XDS_ASCII.HKL files provided."
return
# Parse
dmin_dict = {}
if params.dmin_lst:
for l in open(params.dmin_lst):
sp = l.split()
if len(sp) != 2: continue
f, dmin = sp
dmin_dict[f] = dmin
xscale_inp_head = "!SNRC= 3 ! was MINIMUM_I/SIGMA= before BUILT=20191015\n\n"
if params.wfac1 is not None:
xscale_inp_head += "WFAC1= %.3f\n" % params.wfac1
if params.nproc:
xscale_inp_head += "MAXIMUM_NUMBER_OF_PROCESSORS= %d\n" % params.nproc
infos = {}
d_max, d_min = 0, 100
cells = []
for xds_ascii in xac_files:
info = get_xac_info(xds_ascii,
get_nframes=params.frames_per_batch is not None)
if xds_ascii in dmin_dict:
dmax, dmin = info["resol_range"].split()
info["resol_range_user"] = "******" % (dmax, dmin_dict[xds_ascii])
infos[xds_ascii] = info
resrng = map(float, info["resol_range"].split())
d_max = max(d_max, resrng[0])
d_min = min(d_min, resrng[1])
cells.append(map(float, info["cell"].split()))
if params.d_min is not None:
d_min = max(params.d_min, d_min)
if params.cell == "average":
cell_sum = reduce(lambda x, y: map(lambda a: a[0] + a[1], zip(x, y)),
cells)
cell_mean = map(lambda x: x / float(len(cells)), cell_sum)
if params.sgnum is not None: sgnum = str(params.sgnum)
else: sgnum = infos[xac_files[0]]["spgr_num"]
xscale_inp_head += " SPACE_GROUP_NUMBER= %s\n" % sgnum
xscale_inp_head += " UNIT_CELL_CONSTANTS= %s\n" % " ".join(
map(lambda x: "%.3f" % x, cell_mean))
xscale_inp_head += make_shells(d_max, d_min, params.nbins) + "\n"
xscale_inp_head += " OUTPUT_FILE= %s\n" % params.output
xscale_inp_head += " FRIEDEL'S_LAW= %s\n\n" % ("FALSE" if params.anomalous
else "TRUE")
prep_xscale_inp(params.workdir, xscale_inp_head, xac_files, infos,
params.frames_per_batch, params.corrections)
xscale.run_xscale(os.path.join(params.workdir, "XSCALE.INP"),
cbf_to_dat=params.cbf_to_dat,
use_tmpdir_if_available=params.use_tmpdir_if_available)
if params.reference:
print "Choosing reference data (reference=%s)" % params.reference
ref_idx = xscale.decide_scaling_reference_based_on_bfactor(
os.path.join(params.workdir, "XSCALE.LP"),
params.reference,
return_as="index")
if ref_idx != 0:
for f in "XSCALE.INP", "XSCALE.LP":
util.rotate_file(os.path.join(params.workdir, f))
prep_xscale_inp(params.workdir,
xscale_inp_head,
xac_files,
infos,
params.frames_per_batch,
params.corrections,
ref_idx=ref_idx)
xscale.run_xscale(
os.path.join(params.workdir, "XSCALE.INP"),
cbf_to_dat=params.cbf_to_dat,
use_tmpdir_if_available=params.use_tmpdir_if_available)
def find_spots(img_file, params):
"""
Use XDS to locate spots.
If params.xds.do_defpix is true, DEFPIX will be run. For DEFPIX, dummy XPARM.XDS is needed. Thanks to DEFPIX, we can mask beam stop shadow and remove areas outside the resolution range.
If false, we need to set TRUSTED_REGION to exclude regions outside resolution range, but it is independent of beam center. Maybe we should remove spots outside the resolution range after XDS run?
"""
# Test if ramdisk available
if os.path.isdir("/dev/shm"):
work_dir = tempfile.mkdtemp(prefix="shika_x_"+os.path.splitext(os.path.basename(img_file))[0], dir="/dev/shm")
else:
work_dir = os.path.join(params.work_dir, "xds_"+os.path.splitext(os.path.basename(img_file))[0])
xdsinp = os.path.join(work_dir, "XDS.INP")
spot_xds = os.path.join(work_dir, "SPOT.XDS")
if not os.path.exists(work_dir):
os.mkdir(work_dir)
template_str, min_frame, max_frame = dataset.group_img_files_template([img_file])[0]
im = XIO.Image(img_file)
# Remove lines if None (means to use default)
params_maps = [("strong_pixel", "STRONG_PIXEL="),
("minimum_number_of_pixels_in_a_spot", "MINIMUM_NUMBER_OF_PIXELS_IN_A_SPOT="),
("background_pixel", "BACKGROUND_PIXEL="),
("maximum_number_of_strong_pixels", "MAXIMUM_NUMBER_OF_STRONG_PIXELS="),
("spot_maximum_centroid", "SPOT_MAXIMUM-CENTROID="),
("reflecting_range", "REFLECTING_RANGE="),
("value_range_for_trusted_detector_pixels", "VALUE_RANGE_FOR_TRUSTED_DETECTOR_PIXELS="),
]
tmp = xds_inp_template.splitlines()
for p, x in params_maps:
if getattr(params.xds, p) is None:
tmp = filter(lambda s:not s.startswith(x), tmp)
inp_template = "\n".join(tmp)
# Prepare XDS.INP
inp_str = inp_template%dict(template=os.path.relpath(template_str, work_dir),
framenum=min_frame,
orgx=im.header["BeamX"]/im.header["PixelX"],
orgy=im.header["BeamY"]/im.header["PixelY"],
distance=im.header["Distance"],
osc_range=im.header["PhiWidth"],
wavelength=im.header["Wavelength"],
strong_pixel=params.xds.strong_pixel,
min_pixels=params.xds.minimum_number_of_pixels_in_a_spot,
background_pixel=params.xds.background_pixel,
max_strong_pixels=params.xds.maximum_number_of_strong_pixels,
spot_maximum_centroid=params.xds.spot_maximum_centroid,
reflecting_range=params.xds.reflecting_range,
nx=im.header["Width"], ny=im.header["Height"],
qx=im.header["PixelX"], qy=im.header["PixelY"],
defpix_trusted1=params.xds.value_range_for_trusted_detector_pixels[0],
defpix_trusted2=params.xds.value_range_for_trusted_detector_pixels[1]
)
open(xdsinp, "w").write(inp_str)
if params.xds.do_defpix:
xp = xparm.XPARM()
xp.set_info_from_xdsinp(xdsinp)
open(os.path.join(work_dir, "XPARM.XDS"), "w").write(xp.xparm_str())
modify_xdsinp(xdsinp, inp_params=[("JOB", "XYCORR INIT DEFPIX"),
("INCLUDE_RESOLUTION_RANGE", res_range_for_xds(params.distl.res.outer, params.distl.res.inner))
])
call("xds", wdir=work_dir, stdout=open(os.path.join(work_dir, "xds.log"), "w"))
shutil.copy(os.path.join(work_dir, "BKGPIX.cbf"), os.path.join(work_dir, "BKGINIT.cbf"))
modify_xdsinp(xdsinp, inp_params=[("JOB","COLSPOT")])
else:
modify_xdsinp(xdsinp, inp_params=[("TRUSTED_REGION", res_range_to_trusted_region(params.distl.res.outer, params.distl.res.inner, im.header))
])
open(os.path.join(work_dir, "xds.log"), "w").write("")
# Run XDS
rotate_file(spot_xds)
call("xds", wdir=work_dir, stdout=open(os.path.join(work_dir, "xds.log"), "a"))
# Extract results
spots = [] # (x, y, d, intensity)
if os.path.isfile(spot_xds):
for l in open(spot_xds):
x, y, z, intensity = map(lambda x:float(x), l.strip().split())
d = coord_to_resol(x, y, im.header)
spots.append((x, y, d, intensity))
# Delete dir
shutil.rmtree(work_dir)
return spots
def run_cycle(self, xds_ascii_files, reference_idx=None):
if len(xds_ascii_files) == 0:
print >>self.out, "Error: no files given."
return
xscale_inp = os.path.join(self.workdir, "XSCALE.INP")
xscale_lp = os.path.join(self.workdir, "XSCALE.LP")
# Get averaged cell for scaling
sg, cell = self.average_cells(xds_ascii_files)
# Choose directory containing XDS_ASCII.HKL and set space group (but how??)
inp_out = open(xscale_inp, "w")
inp_out.write("MAXIMUM_NUMBER_OF_PROCESSORS= %d\n" % self.nproc)
inp_out.write("SPACE_GROUP_NUMBER= %s\nUNIT_CELL_CONSTANTS= %s\n\n" % (sg, cell))
inp_out.write(self.xscale_inp_head)
for i, xds_ascii in enumerate(xds_ascii_files):
f = self.altfile.get(xds_ascii, xds_ascii)
tmp = min(os.path.relpath(f, self.workdir), f, key=lambda x:len(x))
refstr = "*" if i==reference_idx else " "
inp_out.write(" INPUT_FILE=%s%s\n" % (refstr,tmp))
if len(self.xscale_params.corrections) != 3:
inp_out.write(" CORRECTIONS= %s\n" % " ".join(self.xscale_params.corrections))
if self.xscale_params.frames_per_batch is not None:
frame_range = XDS_ASCII(f, read_data=False).get_frame_range()
nframes = frame_range[1] - frame_range[0]
nbatch = int(numpy.ceil(nframes / self.xscale_params.frames_per_batch))
print >>self.out, "frame range of %s is %d,%d setting NBATCH= %d" % (f, frame_range[0], frame_range[1], nbatch)
inp_out.write(" NBATCH= %d\n" % nbatch)
inp_out.close()
print >>self.out, "DEBUG:: running xscale with %3d files.." % len(xds_ascii_files)
xscale.run_xscale(xscale_inp)
#util.call(xscale_comm, wdir=self.workdir)
cbfouts = glob.glob(os.path.join(self.workdir, "*.cbf"))
if len(cbfouts) > 0:
# This doesn't affect anything, so I don't want program to stop if this failed
try:
xscalelp.cbf_to_dat(xscale_lp)
for f in cbfouts: os.remove(f)
except:
print >>self.out, traceback.format_exc()
xscale_log = open(xscale_lp).read()
if "!!! ERROR !!! INSUFFICIENT NUMBER OF COMMON STRONG REFLECTIONS." in xscale_log:
print >>self.out, "DEBUG:: Need to choose files."
# From XDS ver. March 1, 2015, it kindly informs which dataset has no common reflections.
# ..but does not print the table. Sometimes only one dataset is left. Should we make table by ourselves?
# Older versions just print correlation table and stop.
if "CORRELATIONS BETWEEN INPUT DATA SETS AFTER CORRECTIONS" in xscale_log:
G = xscalelp.construct_data_graph(xscale_lp, min_common_refs=10)
#nx.write_dot(G, os.path.join(self.workdir, "common_set_graph.dot"))
cliques = [c for c in nx.find_cliques(G)]
cliques.sort(key=lambda x:len(x))
if self._counter == 1:
max_clique = cliques[-1]
else:
idx_prevfile = 1 if self.reference_file else 0
max_clique = filter(lambda x: idx_prevfile in x, cliques)[-1] # xscale.hkl must be included!
if self.reference_file:
max_clique = [0,] + filter(lambda x: x!=0, max_clique)
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
try_later = map(lambda i: xds_ascii_files[i], filter(lambda x: x not in max_clique, G.nodes()))
print >>self.out, "DEBUG:: %d files can be merged. %d files will be merged later." % (len(max_clique),
len(try_later))
print >>self.out, "DEBUG:: %d files are of no use." % (len(xds_ascii_files)-len(G.nodes()))
for i in filter(lambda j: j not in G.nodes(), xrange(len(xds_ascii_files))):
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "no_common_refls"
self.run_cycle(map(lambda i: xds_ascii_files[i], max_clique))
assert len(try_later) <= 0 # Never be the case with newer xscale!! (if the case, check_remove_list() should be modified to skip_num+=1
if len(try_later) > 0:
print >>self.out, "Trying to merge %d remaining files.." % len(try_later)
next_files = [os.path.join(self.workdir, "xscale.hkl")] + try_later
if self.reference_file: next_files = [self.reference_file,] + next_files
self.workdir = self.request_next_workdir()
self.run_cycle(next_files)
return
else:
bad_idxes = xscalelp.read_no_common_ref_datasets(xscale_lp)
print >>self.out, "DEBUG:: %d files are of no use." % (len(bad_idxes))
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
# XXX Actually, not all datasets need to be thrown.. some of them are useful..
for i in bad_idxes:
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "no_common_refls"
self.run_cycle(map(lambda i: xds_ascii_files[i],
filter(lambda j: j not in bad_idxes, xrange(len(xds_ascii_files)))))
return
elif "!!! ERROR !!! USELESS DATA ON INPUT REFLECTION FILE" in xscale_log:
print >>self.out, "DEBUG:: Need to discard useless data."
unuseful_data = [xscalelp.get_read_data(xscale_lp)[-1]] #filter(lambda x: x[2]==0, xscalelp.get_read_data(xscale_lp))
if len(unuseful_data) == 0:
print >>self.out, "I don't know how to fix it.."
return
remove_idxes = map(lambda x: x[0]-1, unuseful_data)
remove_idxes = self.check_remove_list(remove_idxes)
keep_idxes = filter(lambda x: x not in remove_idxes, xrange(len(xds_ascii_files)))
for i in remove_idxes:
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = "useless"
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes))
return
elif "INACCURATE SCALING FACTORS." in xscale_log:
# Actually I don't know how to fix this.. (bug?) but worth proceeding (discarding bad data may solve problem).
print >>self.out, "'INACCURATE SCALING FACTORS' happened.. but ignored."
elif "!!! ERROR !!!" in xscale_log:
print >>self.out, "Unknown error! please check the XSCALE.LP and fix the program."
return
# Re-scale by changing reference
rescale_for = None
if len(self.reject_method) == 0:
rescale_for = self.reference_choice # may be None
elif reference_idx is None:
rescale_for = "bmed"
if rescale_for is not None and len(xds_ascii_files) > 1:
ref_num = xscale.decide_scaling_reference_based_on_bfactor(xscale_lp, rescale_for, return_as="index")
if reference_idx != ref_num:
print >>self.out, "Rescaling with %s" % rescale_for
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(xds_ascii_files, reference_idx=ref_num)
if len(self.reject_method) == 0:
return
# Remove bad data
remove_idxes = []
remove_reasons = {}
if self.reject_method[0] == "framecc":
print >>self.out, "Rejections based on frame CC"
from yamtbx.dataproc.xds.command_line import xscale_cc_against_merged
# list of [frame, n_all, n_common, cc] in the same order
framecc = xscale_cc_against_merged.run(hklin=os.path.join(self.workdir, "xscale.hkl"),
output_dir=self.workdir,
nproc=self.nproc).values()
if self.reject_params.framecc.method == "tukey":
ccs = numpy.array(map(lambda x: x[3], reduce(lambda x,y:x+y,framecc)))
q25, q75 = numpy.percentile(ccs, [25, 75])
cc_cutoff = q25 - self.reject_params.framecc.iqr_coeff * (q75 - q25)
print >>self.out, " frameCC cutoff = %.4f (%.2f*IQR)" % (cc_cutoff, self.reject_params.framecc.iqr_coeff)
else:
cc_cutoff = self.reject_params.framecc.abs_cutoff
print >>self.out, " frameCC cutoff = %.4f (value specified)" % cc_cutoff
for i, cclist in enumerate(framecc):
useframes = map(lambda x: x[0], filter(lambda x: x[3] > cc_cutoff, cclist))
if len(useframes) == 0:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("allbadframe")
continue
f = xds_ascii_files[i]
xac = XDS_ASCII(f)
if set(useframes).issuperset(set(range(min(xac.iframe), max(xac.iframe)))):
continue # All useful frames.
sel = xac.iframe == useframes[0]
for x in useframes[1:]: sel |= xac.iframe == x
if sum(sel) < 10: # XXX care I/sigma
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("allbadframe")
continue
print >>self.out, "Extracting frames %s out of %d-%d in %s" % (",".join(map(str,useframes)),
min(xac.iframe), max(xac.iframe),
f)
newf = self.request_file_modify(f)
xac.write_selected(sel, newf)
self.reject_method.pop(0) # Perform only once
elif self.reject_method[0] == "lpstats":
if "bfactor" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on B-factor outliers (%.2f*IQR)" % iqrc
Bs = numpy.array(map(lambda x:x[1], xscalelp.get_k_b(xscale_lp)))
q25, q75 = numpy.percentile(Bs, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, b in enumerate(Bs):
if b < lowlim or b > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_B")
count += 1
print >>self.out, " %4d B-factor outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "em.b" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on error model b outliers (%.2f*IQR)" % iqrc
bs = numpy.array(map(lambda x:x[1], xscalelp.get_ISa(xscale_lp)))
q25, q75 = numpy.percentile(bs, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, b in enumerate(bs):
if b < lowlim or b > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_em.b")
count += 1
print >>self.out, " %4d error model b outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "em.ab" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on error model a*b outliers (%.2f*IQR)" % iqrc
vals = numpy.array(map(lambda x:x[0]*x[1], xscalelp.get_ISa(xscale_lp)))
q25, q75 = numpy.percentile(vals, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, ab in enumerate(vals):
if ab < lowlim or ab > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_em.ab")
count += 1
print >>self.out, " %4d error model a*b outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "rfactor" in self.reject_params.lpstats.stats:
iqrc = self.reject_params.lpstats.iqr_coeff
print >>self.out, "Rejections based on R-factor outliers (%.2f*IQR)" % iqrc
rstats = xscalelp.get_rfactors_for_each(xscale_lp)
vals = numpy.array(map(lambda x:rstats[x][-1][1], rstats)) # Read total R-factor
q25, q75 = numpy.percentile(vals, [25, 75])
iqr = q75 - q25
lowlim, highlim = q25 - iqrc*iqr, q75 + iqrc*iqr
count = 0
for i, v in enumerate(vals):
if v < lowlim or v > highlim:
remove_idxes.append(i)
remove_reasons.setdefault(i, []).append("bad_R")
count += 1
print >>self.out, " %4d R-factor outliers (<%.2f, >%.2f) removed"% (count, lowlim, highlim)
if "pairwise_cc" in self.reject_params.lpstats.stats:
corrs = xscalelp.get_pairwise_correlations(xscale_lp)
if self.reject_params.lpstats.pwcc.method == "tukey":
q25, q75 = numpy.percentile(map(lambda x: x[3], corrs), [25, 75])
iqr = q75 - q25
lowlim = q25 - self.reject_params.lpstats.pwcc.iqr_coeff * iqr
print >>self.out, "Rejections based on pairwise_cc < %.4f (IQR=%.2f)" % (lowlim, iqr)
else:
lowlim = self.reject_params.lpstats.pwcc.abs_cutoff
print >>self.out, "Rejections based on pairwise_cc < %.4f" % lowlim
bad_corrs = filter(lambda x: x[3] < lowlim, corrs)
idx_bad = {}
for i, j, common_refs, corr, ratio, bfac in bad_corrs:
idx_bad[i] = idx_bad.get(i, 0) + 1
idx_bad[j] = idx_bad.get(j, 0) + 1
idx_bad = idx_bad.items()
idx_bad.sort(key=lambda x:x[1])
count = 0
for idx, badcount in reversed(idx_bad):
remove_idxes.append(idx-1)
remove_reasons.setdefault(idx-1, []).append("bad_pwcc")
bad_corrs = filter(lambda x: idx not in x[:2], bad_corrs)
if len(bad_corrs) == 0: break
fun_key = lambda x: x[3]
print >>self.out, " Removing idx=%d (CC %.3f..%.3f) remaining %d bad pairs" % (idx,
min(bad_corrs,key=fun_key)[3],
max(bad_corrs,key=fun_key)[3],
len(bad_corrs))
count += 1
print >>self.out, " %4d pairwise CC outliers removed" % count
self.reject_method.pop(0) # Perform only once
elif self.reject_method[0] == "delta_cc1/2":
print >>self.out, "Rejection based on delta_CC1/2 in %s shell" % self.delta_cchalf_bin
table = xscalelp.read_stats_table(xscale_lp)
i_stat = -1 if self.delta_cchalf_bin == "total" else -2
prev_cchalf = table["cc_half"][i_stat]
prev_nuniq = table["nuniq"][i_stat]
# file_name->idx table
remaining_files = collections.OrderedDict(map(lambda x: x[::-1], enumerate(xds_ascii_files)))
# For consistent resolution limit
inp_head = self.xscale_inp_head + "SPACE_GROUP_NUMBER= %s\nUNIT_CELL_CONSTANTS= %s\n\n" % (sg, cell)
count = 0
for i in xrange(len(xds_ascii_files)-1): # if only one file, cannot proceed.
tmpdir = os.path.join(self.workdir, "reject_test_%.3d" % i)
cchalf_list = xscale.calc_cchalf_by_removing(wdir=tmpdir, inp_head=inp_head,
inpfiles=remaining_files.keys(),
stat_bin=self.delta_cchalf_bin,
nproc=self.nproc,
nproc_each=self.nproc_each,
batchjobs=self.batchjobs)
rem_idx, cc_i, nuniq_i = cchalf_list[0] # First (largest) is worst one to remove.
rem_idx_in_org = remaining_files[remaining_files.keys()[rem_idx]]
# Decision making by CC1/2
print >>self.out, "DEBUG:: cycle %.3d remove %3d if %.2f*%d > %.2f*%d" % (i, rem_idx_in_org,
cc_i, nuniq_i,
prev_cchalf, prev_nuniq)
if cc_i*nuniq_i <= prev_cchalf*prev_nuniq: break
print >>self.out, "Removing idx= %3d gained CC1/2 by %.2f" % (rem_idx_in_org, cc_i-prev_cchalf)
prev_cchalf, prev_nuniq = cc_i, nuniq_i
remove_idxes.append(rem_idx_in_org)
remove_reasons.setdefault(rem_idx_in_org, []).append("bad_cchalf")
del remaining_files[remaining_files.keys()[rem_idx]] # remove file from table
count += 1
print >>self.out, " %4d removed by DeltaCC1/2 method" % count
if self.next_delta_cchalf_bin != []:
self.delta_cchalf_bin = self.next_delta_cchalf_bin.pop(0)
else:
self.reject_method.pop(0)
else:
print >>self.out, "ERROR:: Unsupported reject_method (%s)" % reject_method
# Remove duplicates
remove_idxes = list(set(remove_idxes))
remove_idxes = self.check_remove_list(remove_idxes)
if len(remove_idxes) > 0:
print >>self.out, "DEBUG:: Need to remove %d files" % len(remove_idxes)
for i in sorted(remove_idxes):
print >>self.out, " %.3d %s" % (i, xds_ascii_files[i])
self.removed_files.append(xds_ascii_files[i])
self.removed_reason[xds_ascii_files[i]] = ",".join(remove_reasons[i])
# Next run
keep_idxes = filter(lambda x: x not in remove_idxes, xrange(len(xds_ascii_files)))
if len(self.reject_method) > 0 or len(remove_idxes) > 0:
self.workdir = self.request_next_workdir()
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes))
elif self.reference_choice is not None and len(keep_idxes) > 1:
# Just re-scale with B reference
ref_num = xscale.decide_scaling_reference_based_on_bfactor(xscale_lp, self.reference_choice, return_as="index")
if reference_idx != ref_num:
print >>self.out, "Rescaling2 with %s" % self.reference_choice
for f in "XSCALE.INP", "XSCALE.LP": util.rotate_file(os.path.join(self.workdir, f))
self.run_cycle(map(lambda i: xds_ascii_files[i], keep_idxes), reference_idx=ref_num)
def xds_sequence(root, params):
print
print os.path.relpath(root, params.topdir)
xparm = os.path.join(root, "XPARM.XDS")
gxparm = os.path.join(root, "GXPARM.XDS")
defpix_lp = os.path.join(root, "DEFPIX.LP")
correct_lp = os.path.join(root, "CORRECT.LP")
integrate_hkl = os.path.join(root, "INTEGRATE.HKL")
xac_hkl = os.path.join(root, "XDS_ASCII.HKL")
integrate_lp = os.path.join(root, "INTEGRATE.LP")
xdsinp = os.path.join(root, "XDS.INP")
assert os.path.isfile(xdsinp)
decilog = multi_out()
decilog.register("log", open(os.path.join(root, "decision.log"), "a"), atexit_send_to=None)
print >>decilog, "xds_sequence started at %s in %s\n" % (time.strftime("%Y-%m-%d %H:%M:%S"), root)
if params.show_progress:
decilog.register("stdout", sys.stdout)
if params.mode=="initial" and params.resume and os.path.isfile(correct_lp):
print " Already processed."
return
if params.mode == "recycle" and not os.path.isfile(gxparm):
print "GXPARM.XDS not found. Cannot do recycle."
return
if params.fast_delphi and (params.nproc is None or params.nproc > 1):
delphi = optimal_delphi_by_nproc(xdsinp=xdsinp, nproc=params.nproc)
print " Setting delphi to ", delphi
modify_xdsinp(xdsinp, inp_params=[("DELPHI", str(delphi)),
])
if params.nproc is not None and params.nproc > 1:
modify_xdsinp(xdsinp, inp_params=[("MAXIMUM_NUMBER_OF_PROCESSORS", str(params.nproc)),
])
if params.mode == "initial":
# To Indexing
modify_xdsinp(xdsinp, inp_params=[("JOB", "XYCORR INIT COLSPOT IDXREF")])
run_xds(wdir=root, show_progress=params.show_progress)
print # indexing stats like indexed percentage here.
if params.tryhard:
try_indexing_hard(root, params.show_progress, decilog,
known_sgnum=params.cell_prior.sgnum,
known_cell=params.cell_prior.cell,
tol_length=params.cell_prior.tol_length,
tol_angle=params.cell_prior.tol_angle)
if not os.path.isfile(xparm):
print >>decilog, " Indexing failed."
return
if params.cell_prior.check and params.cell_prior.sgnum > 0:
xsxds = XPARM(xparm).crystal_symmetry()
xsref = crystal.symmetry(params.cell_prior.cell, params.cell_prior.sgnum)
cosets = reindex.reindexing_operators(xsref, xsxds,
params.cell_prior.tol_length, params.cell_prior.tol_angle)
if cosets.double_cosets is None:
print >>decilog, " Incompatible cell. Indexing failed."
return
elif params.mode == "recycle":
print " Start recycle. original ISa= %.2f" % correctlp.get_ISa(correct_lp, check_valid=True)
for f in xds_files.generated_after_DEFPIX + ("XPARM.XDS", "plot_integrate.log"):
util.rotate_file(os.path.join(root, f), copy=True)
shutil.copyfile(gxparm+".1", xparm)
else:
raise "Unknown mode (%s)" % params.mode
# To Integration
modify_xdsinp(xdsinp, inp_params=[("JOB", "DEFPIX INTEGRATE"),
("INCLUDE_RESOLUTION_RANGE", "50 0")])
run_xds(wdir=root, show_progress=params.show_progress)
if os.path.isfile(integrate_lp):
xds_plot_integrate.run(integrate_lp, os.path.join(root, "plot_integrate.log"))
if not os.path.isfile(integrate_hkl):
print >>decilog, " Integration failed."
return
# Make _noscale.HKL if needed
if params.no_scaling:
bk_prefix = make_backup(("XDS.INP",), wdir=root, quiet=True)
xparm_obj = XPARM(xparm)
modify_xdsinp(xdsinp, inp_params=[("JOB", "CORRECT"),
("CORRECTIONS", ""),
("NBATCH", "1"),
("MINIMUM_I/SIGMA", "50"),
("REFINE(CORRECT)", ""),
("UNIT_CELL_CONSTANTS", " ".join(map(lambda x:"%.3f"%x, xparm_obj.unit_cell))),
("SPACE_GROUP_NUMBER", "%d"%xparm_obj.spacegroup),])
print >>decilog, " running CORRECT without empirical scaling"
run_xds(wdir=root, show_progress=params.show_progress)
for f in xds_files.generated_by_CORRECT + ("XDS.INP",):
ff = os.path.join(root, f)
if not os.path.isfile(ff): continue
if ff.endswith(".cbf"):
os.remove(ff)
else:
os.rename(ff, ff+"_noscale")
revert_files(("XDS.INP",), bk_prefix, wdir=root, quiet=True)
# Run pointless
symm_by_integrate = None
if params.use_pointless:
worker = Pointless()
result = worker.run_for_symm(xdsin=integrate_hkl,
logout=os.path.join(root, "pointless_integrate.log"))
if "symm" in result:
symm = result["symm"]
print >>decilog, " pointless using INTEGRATE.HKL suggested", symm.space_group_info()
sgnum = symm.space_group_info().type().number()
cell = " ".join(map(lambda x:"%.2f"%x, symm.unit_cell().parameters()))
modify_xdsinp(xdsinp, inp_params=[("SPACE_GROUP_NUMBER", "%d"%sgnum),
("UNIT_CELL_CONSTANTS", cell)])
symm_by_integrate = symm
else:
print >>decilog, " pointless failed."
# Do Scaling
modify_xdsinp(xdsinp, inp_params=[("JOB", "CORRECT"),])
run_xds(wdir=root, show_progress=params.show_progress)
if not os.path.isfile(gxparm):
print >>decilog, " Scaling failed."
return
print >>decilog, " OK. ISa= %.2f" % correctlp.get_ISa(correct_lp, check_valid=True)
ret = calc_merging_stats(os.path.join(root, "XDS_ASCII.HKL"))
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp, inp_params=[("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE", "50 %.2f"%d_min)])
print >>decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"), os.path.join(root, "CORRECT_fullres.LP"))
os.rename(os.path.join(root, "XDS_ASCII.HKL"), os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root, show_progress=params.show_progress)
print >>decilog, " OK. ISa= %.2f" % correctlp.get_ISa(correct_lp, check_valid=True)
print >>decilog, " (Original files are saved as *_fullres.*)"
else:
print >>decilog, "error: Can't decide resolution."
last_ISa = correctlp.get_ISa(correct_lp, check_valid=True)
# Run pointless and (if result is different from INTEGRATE) re-scale.
if params.use_pointless:
worker = Pointless()
result = worker.run_for_symm(xdsin=xac_hkl,
logout=os.path.join(root, "pointless_correct.log"))
if "symm" in result:
symm = result["symm"]
need_rescale = False
if symm_by_integrate is not None:
if not xtal.is_same_laue_symmetry(symm_by_integrate.space_group(), symm.space_group()):
print >>decilog, "pointless suggested %s, which is different Laue symmetry from INTEGRATE.HKL (%s)" % (symm.space_group_info(), symm_by_integrate.space_group_info())
need_rescale = True
else:
print >>decilog, "pointless using XDS_ASCII.HKL suggested %s" % symm.space_group_info()
need_rescale = True
if need_rescale:
# make backup, and do correct and compare ISa
# if ISa got worse, revert the result.
backup_needed = ("XDS.INP", "XDS_ASCII_fullres.HKL","CORRECT_fullres.LP",
"merging_stats.pkl","merging_stats.log")
backup_needed += xds_files.generated_by_CORRECT
bk_prefix = make_backup(backup_needed, wdir=root, quiet=True)
sgnum = symm.space_group_info().type().number()
cell = " ".join(map(lambda x:"%.2f"%x, symm.unit_cell().parameters()))
modify_xdsinp(xdsinp, inp_params=[("JOB", "CORRECT"),
("SPACE_GROUP_NUMBER", "%d"%sgnum),
("UNIT_CELL_CONSTANTS", cell),
("INCLUDE_RESOLUTION_RANGE", "50 0")])
run_xds(wdir=root, show_progress=params.show_progress)
ret = calc_merging_stats(os.path.join(root, "XDS_ASCII.HKL"))
if params.cut_resolution:
if ret is not None and ret[0] is not None:
d_min = ret[0]
modify_xdsinp(xdsinp, inp_params=[("JOB", "CORRECT"),
("INCLUDE_RESOLUTION_RANGE", "50 %.2f"%d_min)])
print >>decilog, " Re-scale at %.2f A" % d_min
os.rename(os.path.join(root, "CORRECT.LP"), os.path.join(root, "CORRECT_fullres.LP"))
os.rename(os.path.join(root, "XDS_ASCII.HKL"), os.path.join(root, "XDS_ASCII_fullres.HKL"))
run_xds(wdir=root, show_progress=params.show_progress)
print >>decilog, " OK. ISa= %.2f" % correctlp.get_ISa(correct_lp, check_valid=True)
print >>decilog, " (Original files are saved as *_fullres.*)"
else:
print >>decilog, "error: Can't decide resolution."
for f in ("CORRECT_fullres.LP", "XDS_ASCII_fullres.HKL"):
if os.path.isfile(os.path.join(root, f)):
print >>decilog, "removing", f
os.remove(os.path.join(root, f))
ISa = correctlp.get_ISa(correct_lp, check_valid=True)
if ISa >= last_ISa or last_ISa!=last_ISa: # if improved or last_ISa is nan
print >>decilog, "ISa improved= %.2f" % ISa
remove_backups(backup_needed, bk_prefix, wdir=root)
else:
print >>decilog, "ISa got worse= %.2f" % ISa
for f in backup_needed:
if os.path.isfile(os.path.join(root, f)): os.remove(os.path.join(root, f))
revert_files(backup_needed, bk_prefix, wdir=root, quiet=True)
run_xdsstat(wdir=root)
print
if params.make_report: html_report.make_individual_report(root, root)
print >>decilog, "xds_sequence finished at %s\n" % time.strftime("%Y-%m-%d %H:%M:%S")
decilog.close()
def prepare_plot(plot_data, f, kind, wdir, rotate=False, plot_grid=True):
def normalize_max(v, maximum=400.):
max_v = max(v)
f = maximum / max_v if max_v > 0 else 1.
return map(
lambda x: f * x + 1.,
v) # add 1 to make zero-value pickable # XXX when max_v is Inf?
# normalize_max()
scan_prefix = f[:f.index(" ")] if " (phi=" in f else f
pngout = os.path.join(wdir, "plot_%s%s.png" % (scan_prefix, kind))
if rotate:
rotate_file(pngout)
xs, ys, ds, imgfs = [], [], [], []
zero_xs, zero_ys = [], [] # For values of zero
for imgf, stat in plot_data[f]:
gc = stat.grid_coord
if gc is None:
continue
x, y = gc
x *= 1000.
y *= 1000.
d = stat.stats[("n_spots", "total_integrated_signal",
"median_integrated_signal").index(kind)]
xs.append(x)
ys.append(y)
ds.append(d)
imgfs.append(imgf)
if d == 0:
zero_xs.append(x)
zero_ys.append(y)
if len(xs) == 0:
return "", ""
win = (max(xs) - min(xs) + 1000) / 1000 * 400 / 80 * 1.7 # ad-hoc scale
hin = (max(ys) - min(ys) + 1000) / 1000 * 400 / 80
fig = matplotlib.figure.Figure(figsize=(win, hin),
dpi=80) # figsize in inches
ax = fig.add_subplot(111)
#p = ax.scatter(xs, ys, s=normalize_max(ds), c=ds, alpha=0.5) # s in points^2
scaninfo = plot_data[f][0][1].scan_info
if plot_grid:
p = plot_heatmap(ax, xs, ys, ds, scaninfo)
else:
p, _ = plot_circles(ax, xs, ys, ds, zero_xs, zero_ys)
if max(ds) - min(ds) > 1e-5:
fig.colorbar(p)
ax.scatter(zero_xs,
zero_ys,
s=50,
marker="x",
c=[0] * len(zero_xs),
alpha=0.5)
ax.set_xlabel("horizontal [um]")
ax.set_ylabel("vertical [um]")
if scaninfo is not None:
vp, hp = scaninfo.vpoints, scaninfo.hpoints
vs, hs = scaninfo.vstep * 1000., scaninfo.hstep * 1000.
if 1 in (vp, hp) or len(plot_data[f]) <= hp:
ax.set_aspect("auto")
else:
ax.set_aspect("equal")
if vp == hp == 1:
ax.set_xlim(-10, 10)
ax.set_ylim(-10, 10)
elif vp == 1:
ax.set_xlim(min(xs) - hs, max(xs) + hs)
ax.set_ylim(-10, 10)
elif hp == 1:
ax.set_xlim(-10, 10)
ax.set_ylim(min(ys) - vs, max(ys) + vs)
else:
ax.set_xlim(min(xs) - hs, max(xs) + hs)
ax.set_ylim(min(ys) - vs, max(ys) + vs)
else:
# Should never reach here.. but should we set limit here?
vs, hs = 5, 5
canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(fig)
canvas.print_figure(pngout + ".tmp", dpi=80, format="png")
img_width = fig.get_figwidth() * 80
img_height = fig.get_figheight() * 80
map_str = '<map name="%smap">\n' % scan_prefix
for x, y, imgf in zip(xs, ys, imgfs):
if plot_grid:
tx1, ty1 = ax.transData.transform((x - hs / 2., y - vs / 2.))
tx2, ty2 = ax.transData.transform((x + hs / 2., y + vs / 2.))
map_str += ' <area shape="rect" coords="%.2f,%.2f,%.2f,%.2f" title="%s" onClick=\'plotClick("%s", "%s")\'>\n' % (
tx1, img_height - ty1, tx2, img_height - ty2,
os.path.basename(imgf), scan_prefix, os.path.basename(imgf))
else:
tx, ty = ax.transData.transform((x, y))
map_str += ' <area shape="circle" coords="%.2f,%.2f,10" title="%s" onClick=\'plotClick("%s", "%s")\'>\n' % (
tx, img_height - ty, os.path.basename(imgf), scan_prefix,
os.path.basename(imgf))
map_str += "</map>"
return pngout, map_str
def make_html_report(current_stats,
wdir,
htmlout,
zoo_mode,
rotate=False,
plot_grid=True):
#plot_data = self.plotFrame.data
shikalog.info("Making HTML report for %s" % wdir)
startt = time.time()
plot_data = collections.OrderedDict()
for f, stat in current_stats.items():
if stat is None: continue
fpref = decide_fpref(f, stat.scan_info)
plot_data.setdefault(fpref, []).append((f, stat))
#if gui_params.mode == "zoo": htmlout = os.path.join(wdir, "report_zoo.html")
#else: htmlout = os.path.join(wdir, "report.html")
if rotate: rotate_file(htmlout)
if zoo_mode: assert len(plot_data) <= 1
kinds = ("total_integrated_signal", "median_integrated_signal", "n_spots")
plots = ""
pngs = []
for f in plot_data:
scan_prefix = f[:f.index(" ")] if " (phi=" in f else f
info = plot_data[f][0][1].scan_info
if info is None: info = bl_logfiles.ScanInfo() # Empty info
plots += '<table border=0 style="margin-bottom:0px">\n <tr><td>\n'
if zoo_mode:
try:
im = Image.open(os.path.join(wdir, "../../../before.ppm"))
im.save(os.path.join(wdir, "loop_before.jpg"))
except:
import traceback
print "Can't convert loop image"
print traceback.format_exc()
plots += ' Loop image</td><td><img src="loop_before.jpg" /></td></tr>\n'
plots += ' <tr><td>\n'
plots += ' <table class="info"><tr><th>scan</th><td>%s</td></tr>\n' % scan_prefix
plots += ' <tr><th>date</th><td>%s</td></tr>\n' % (
info.date.strftime("%Y/%m/%d %H:%M:%S")
if info.date != 0 else "??")
if info.is_shutterless():
plots += ' <tr><th>fixed spindle</th><td>%.2f°</td></tr>\n' % info.fixed_spindle
plots += ' <tr><th>frame rate</th><td>%.2f [Hz]</td></tr>\n' % info.frame_rate
else:
plots += ' <tr><th>osc. start</th><td>%.2f°</td></tr>\n' % info.osc_start
plots += ' <tr><th>osc. step</th><td>%.2f°</td></tr>\n' % info.osc_step
plots += ' <tr><th>exp. time</th><td>%.2f [sec]</td></tr>\n' % info.exp_time
plots += ' <tr><th>beam size</th><td>h= %.1f, v= %.1f [μm]</td></tr>\n' % (
info.beam_hsize, info.beam_vsize)
plots += ' <tr><th>attenuator</th><td>%s %.1f [μm]</td></tr>\n' % info.attenuator
plots += ' <tr><th>distance</th><td>%.2f [mm]</td></tr>\n' % info.distance
plots += ' <tr><th>wavelength</th><td>%.4f [Å]</td></tr>\n' % info.wavelength
plots += ' <tr><th>scan points</th><td>v=%d, h=%d</td></tr>\n' % (
info.vpoints, info.hpoints)
plots += ' <tr><th>scan steps</th><td>v=%.2f, h=%.2f [μm]</td></tr>\n' % (
info.vstep * 1000., info.hstep * 1000.)
plots += ' </table>\n'
for i, kind in enumerate(kinds):
pngout, mapstr = prepare_plot(plot_data, f, kind, wdir, rotate,
plot_grid)
pngs.append(pngout) # rename later
adds = ""
if i == 0:
plots += ' <td><img name="%s" src="%s" usemap="#%smap" /><br />\n' % (
scan_prefix, os.path.basename(pngout), scan_prefix)
plots += '<form>\n'
adds = ' checked="checked"'
plots += '<input type="radio" name="spot_mode" value="%s" onClick="changeplot(this, \'%s\')"%s />%s<br />\n' % (
kind, scan_prefix, adds, kind)
plots += '</form>%s</td></tr></table><br>\n\n' % mapstr # The last mapstr is used. This is dirty way, though.
plots += '<table border=0 style="margin-bottom:20px">\n <tr><td>\n'
plots += '<td style="border:solid 1px #999"><canvas id="%scanvas" width=600 height=600></canvas>\n' % scan_prefix
plots += '<td id="%sinfo" valign="top"></tr></table>\n\n' % scan_prefix
result = current_stats.items()
if len(result) == 0:
shikalog.warning("No results found. Exiting. %s" % wdir)
return
dbfile = os.path.join(wdir, "shika.db")
con = sqlite3.connect(dbfile, timeout=10, isolation_level=None)
con.execute('pragma query_only = ON;')
print "Reading data from DB for making report html."
c = con.execute("select filename,spots from spots")
dbspots = dict(
map(lambda x: (str(x[0]), pickle.loads(str(x[1]))), c.fetchall()))
spot_data = "var spot_data = {"
for i, (f, stat) in enumerate(result):
if stat is None: continue
bf = os.path.basename(f)
spots = dbspots[bf]["spots"]
thumb_posmag = dbspots[bf]["thumb_posmag"]
r = re.search("^(.*)_([0-9]+)\.[^0-9]+$", bf)
prefix, num = r.group(1), int(r.group(2))
spot_data += '"%s":[[' % bf
for y, x, snr, d in spots:
#x, y = spot.max_pxl_y(), spot.max_pxl_x()
pos = thumb_posmag[0:2]
mag = thumb_posmag[2]
x, y = (x - pos[0]) * mag, (y - pos[1]) * mag
spot_data += "[%d,%d]," % (x, y)
spot_data += "], %.1f, %.1f, %d, %d]," % (stat.stats[1], stat.stats[2],
stat.stats[0], num)
spot_data += "};"
spot_data = spot_data.replace("inf,", "Infinity,").replace("nan,", "NaN,")
con.close()
# Determine img picture extension
img_ext = ".png" if os.path.exists(
os.path.join(wdir,
os.path.basename(result[0][0]) + ".png")) else ".jpg"
jpg_dirs = "var jpg_dirs = {"
flag_tiled_jpg = False
if glob.glob(os.path.join(wdir, "thumb_*")):
for res in result:
r = re.search("^(.*)_([0-9]+)\.[^0-9]+$", os.path.basename(res[0]))
prefix, num = r.group(1), int(r.group(2))
jd = os.path.join("thumb_%s_%.3d" % (prefix, num // 1000))
if not os.path.exists(jd):
flag_tiled_jpg = True # THIS MAY CAUSE A PROBLEM..
jpg_dirs += '"%s":"%s",' % (os.path.basename(res[0]), jd)
else:
for res in result:
jpg_dirs += '"%s":".",' % os.path.basename(res[0])
jpg_dirs += "};"
ofs = open(htmlout, "w")
ofs.write("""\
<!DOCTYPE html>
<html>
<head>
<meta charset="UTF-8" />
<title>SHIKA report</title>
<script type="text/javascript">
<!--
function changeplot(obj, name){
document.images[name].src = "plot_"+name+obj.value+".png";
}
%(spot_data)s
%(jpg_dirs)s
""" % dict(spot_data=spot_data,
jpg_dirs=jpg_dirs if not flag_tiled_jpg else ""))
if flag_tiled_jpg: # FOR TILED JPEG
ofs.write("""\
function plotClick(scanprefix, imgfile) {
var f = imgfile;
var data = spot_data[f];
var img = new Image();
var idx = Math.floor((data[4]-1)/100);
var n1 = idx*100+1;
var n2 = (idx+1)*100;
img.src = "thumb_" + scanprefix.slice(0,-1) + "/" + scanprefix + ("00000"+n1).slice(-6) + "-" + ("00000"+n2).slice(-6) + ".jpg"; // prefix ends with _
var idx2 = (data[4]-1)%%100;
var sx = idx2%%10;
var sy = Math.floor(idx2/10);
img.onload = (function(fn){
return function(){
var td = document.getElementById(scanprefix+"info");
td.innerHTML = "<table border=0><tr><td>File name: <td>" + imgfile + "<tr><td>total signal: <td>" + data[1] + "<tr><td>median signal: <td>" + data[2] + "<tr><td>N_spots: <td>" + data[3] + "</table>";
var t = data[0];
var canvas = document.getElementById(scanprefix+"canvas");
var ctx = canvas.getContext('2d');
ctx.clearRect(0,0,canvas.width,canvas.height);
ctx.drawImage(this, sx*600, sy*600, 600, 600, 0, 0, 600, 600);
""" % dict(img_ext=img_ext))
else: # FOR SINGLE JPEGs
ofs.write("""\
function plotClick(scanprefix, imgfile) {
var f = imgfile;
var data = spot_data[f];
var img = new Image();
img.src = jpg_dirs[f] + "/" + f + "%(img_ext)s";
img.onload = (function(fn){
return function(){
var td = document.getElementById(scanprefix+"info");
td.innerHTML = "<table border=0><tr><td>File name: <td>" + imgfile + "<tr><td>total signal: <td>" + data[1] + "<tr><td>median signal: <td>" + data[2] + "<tr><td>N_spots: <td>" + data[3] + "</table>";
var t = data[0];
var canvas = document.getElementById(scanprefix+"canvas");
var ctx = canvas.getContext('2d');
ctx.clearRect(0,0,canvas.width,canvas.height);
ctx.drawImage(this, 0, 0);
""" % dict(img_ext=img_ext))
# Common parts
ofs.write("""\
for (var i = 0; i < t.length; i++) {
ctx.rect(t[i][0]-6, t[i][1]-6, 12, 12);
}
ctx.strokeStyle = "red";
ctx.lineWidth = 1;
ctx.stroke();
var center = [300,300];
ctx.beginPath();
ctx.strokeStyle = "blue";
ctx.moveTo(center[0]-10, center[1]);
ctx.lineTo(center[0]+10, center[1]);
ctx.moveTo(center[0], center[1]-10);
ctx.lineTo(center[0], center[1]+10);
ctx.stroke();
}
}(f));
}
//-->
</script>
<style type="text/css">
<!--
table.info {
border-collapse: separate;
border-spacing: 7px;
}
table.info th {
text-align: left;
}
table.images {
border-collapse: collapse;
border: solid 1px #999;
}
table.images caption {
margin-top: 1em;
text-align: left;
}
table.images th,
table.images td {
border: solid 1px #999;
}
table.images th {
background: #E6E6E6;
text-align: center;
white-space: nowrap;
}
-->
</style>
</head>
<body>
<h1>SHIKA report</h1>
<div align="right">
Created on %(date)s<br>
Original directory: %(wdir)s
</div>
<hr style="height: 1px;border: none;border-top: 1px #000000 dotted;" />
%(plots)s
</body>
</html>
""" % dict(
plots=plots,
date=datetime.datetime.today().strftime("%Y/%m/%d %H:%M:%S"),
wdir=wdir,
))
shikalog.debug("Renaming png files in %s" % wdir)
for png in pngs:
os.rename(png + ".tmp", png)
delt = time.time() - startt
shikalog.info("HTML making Done (took %f s). Open? firefox %s" %
(delt, htmlout))