def import_geometry(xds_inp=None, dials_json=None):
assert (xds_inp, dials_json).count(None) == 1
geom_kwds = set([
"DIRECTION_OF_DETECTOR_X-AXIS",
"DIRECTION_OF_DETECTOR_Y-AXIS",
"DETECTOR_DISTANCE",
"ORGX",
"ORGY",
"ROTATION_AXIS", # "X-RAY_WAVELENGTH",
"INCIDENT_BEAM_DIRECTION",
"SEGMENT",
"DIRECTION_OF_SEGMENT_X-AXIS",
"DIRECTION_OF_SEGMENT_Y-AXIS",
"SEGMENT_DISTANCE",
"SEGMENT_ORGX",
"SEGMENT_ORGY"
])
# FIXME in case of multi-segment detector..
if xds_inp:
inp = get_xdsinp_keyword(xds_inp)
inp = filter(lambda x: x[0] in geom_kwds, inp)
return map(lambda x: "%s= %s" % x, inp)
elif dials_json:
import dxtbx.imageset
from dxtbx.serialize.load import _decode_dict
from dxtbx.model import BeamFactory
from dxtbx.model import DetectorFactory
from dxtbx.model import GoniometerFactory
from dxtbx.model import ScanFactory
from dxtbx.serialize.xds import to_xds
j = json.loads(open(dials_json).read(), object_hook=_decode_dict)
# dummy
sweep = dxtbx.imageset.ImageSetFactory.from_template(
"####", image_range=[1, 1], check_format=False)[0]
sweep.set_detector(DetectorFactory.from_dict(j["detector"][0]))
sweep.set_beam(BeamFactory.from_dict(j["beam"][0]))
sweep.set_goniometer(GoniometerFactory.from_dict(j["goniometer"][0]))
sweep.set_scan(
ScanFactory.make_scan(image_range=[1, 1],
exposure_times=[1],
oscillation=[1, 2],
epochs=[0])) # dummy
sio = cStringIO.StringIO()
to_xds(sweep).XDS_INP(sio)
inp = get_xdsinp_keyword(inp_str=sio.getvalue())
inp = filter(lambda x: x[0] in geom_kwds, inp)
return map(lambda x: "%s= %s" % x, inp)
return []
def set_info_from_xdsinp(self, xdsinp):
# XXX x, y, z axes
table = [
("STARTING_FRAME", "starting_frame", lambda x: int(x)),
("STARTING_ANGLE", "starting_angle", lambda x: float(x)),
("OSCILLATION_RANGE", "osc_range", lambda x: float(x)),
("ROTATION_AXIS", "rotation_axis", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
("X-RAY_WAVELENGTH", "wavelength", lambda x: float(x)),
("INCIDENT_BEAM_DIRECTION", "incident_beam", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
("NX", "nx", lambda x: int(x)),
("NY", "ny", lambda x: int(x)),
("QX", "qx", lambda x: float(x)),
("QY", "qy", lambda x: float(x)),
("DETECTOR_DISTANCE", "distance", lambda x: float(x)),
("SPACE_GROUP_NUMBER", "spacegroup", lambda x: int(x)),
("UNIT_CELL_CONSTANTS", "unit_cell", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
("UNIT_CELL_A-AXIS", "a_axis", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
("UNIT_CELL_B-AXIS", "b_axis", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
("UNIT_CELL_C-AXIS", "c_axis", lambda x: numpy.array(map(lambda y: float(y), x.split()))),
]
inp = dict(get_xdsinp_keyword(xdsinp)) # I believe dict() removes duplicated parameters and keeps last.
for k, at, f in table:
if k in inp and inp[k].strip() != "":
setattr(self, at, f(inp[k]))
if "ORGX" in inp:
self.origin[0] = float(inp["ORGX"])
if "ORGY" in inp:
self.origin[1] = float(inp["ORGY"])
def run(xscale_inp):
inp_dir = os.path.dirname(xscale_inp)
files = map(lambda y: y[1].replace("*",""), filter(lambda x: x[0]=="INPUT_FILE", get_xdsinp_keyword(xscale_inp)))
files = map(lambda x: os.path.join(inp_dir, x) if not os.path.isabs(x) else x, files)
symms = map(lambda x: XDS_ASCII(x,read_data=False).symm, files)
cells = numpy.array(map(lambda x: x.unit_cell().parameters(), symms))
sgs = map(lambda x: str(x.space_group_info()), symms)
laues = map(lambda x: str(x.space_group().build_derived_reflection_intensity_group(False).info()), symms)
median_cell = map(lambda i: numpy.median(cells[:,i]), xrange(6))
mean_cell = map(lambda i: cells[:,i].mean(), xrange(6))
cell_sd = map(lambda i: numpy.std(cells[:,i]), xrange(6))
print "%4d files loaded" % len(files)
print "Space groups:", ", ".join(map(lambda x: "%s (%d files)"%(x,sgs.count(x)), set(sgs)))
print " Laue groups:", ", ".join(map(lambda x: "%s (%d files)"%(x,laues.count(x)), set(laues)))
print " Median cell:", " ".join(map(lambda x: "%7.3f"%x, median_cell))
print " Mean cell:", " ".join(map(lambda x: "%7.3f"%x, mean_cell))
print " SD:", " ".join(map(lambda x: "%7.1e"%x, cell_sd))
# for BLEND $CCP4/share/blend/R/blend0.R
# names(macropar) <- c("cn","a","b","c","alpha","beta","gamma","mosa","ctoddist","wlength")
ofs = open("forR_macropar.dat", "w")
for i, cell in enumerate(cells):
print >>ofs, "%4d" % (i+1),
print >>ofs, " ".join(map(lambda x: "%7.3f"%x, cell)),
print >>ofs, " 0 0 0"
ofs.close()
shutil.copyfile("forR_macropar.dat", "forR_macropar.dat.bak")
print
print "Run BLEND?"
print "Rscript $CCP4/share/blend/R/blend0.R"
def set_info_from_xdsinp(self, xdsinp):
# XXX x, y, z axes
table = [("STARTING_FRAME", "starting_frame", lambda x: int(x)),
("STARTING_ANGLE", "starting_angle", lambda x: float(x)),
("OSCILLATION_RANGE", "osc_range", lambda x: float(x)),
("ROTATION_AXIS", "rotation_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()))),
("X-RAY_WAVELENGTH", "wavelength", lambda x: float(x)),
("INCIDENT_BEAM_DIRECTION", "incident_beam", lambda x: numpy.array(map(lambda y:float(y), x.split()))),
("NX", "nx", lambda x: int(x)),
("NY", "ny", lambda x: int(x)),
("QX", "qx", lambda x: float(x)),
("QY", "qy", lambda x: float(x)),
("DETECTOR_DISTANCE", "distance", lambda x: float(x)),
("SPACE_GROUP_NUMBER", "spacegroup", lambda x: int(x)),
("UNIT_CELL_CONSTANTS", "unit_cell", lambda x: numpy.array(map(lambda y:float(y), x.split()))),
("UNIT_CELL_A-AXIS", "a_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()))),
("UNIT_CELL_B-AXIS", "b_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()))),
("UNIT_CELL_C-AXIS", "c_axis", lambda x: numpy.array(map(lambda y:float(y), x.split())))
]
inp = dict(get_xdsinp_keyword(xdsinp)) # I believe dict() removes duplicated parameters and keeps last.
for k, at, f in table:
if k in inp and inp[k].strip() != "":
setattr(self, at, f(inp[k]))
if "ORGX" in inp:
self.origin[0] = float(inp["ORGX"])
if "ORGY" in inp:
self.origin[1] = float(inp["ORGY"])
def set_xdsinp(self, xdsinp):
inp = dict(get_xdsinp_keyword(xdsinp))
wavelength = float(inp["X-RAY_WAVELENGTH"])
orgx, orgy = map(float, (inp["ORGX"], inp["ORGY"]))
qx = float(inp["QX"])
distance = abs(float(inp["DETECTOR_DISTANCE"]))
self.calc_d = lambda x, y: wavelength/2./math.sin(0.5*math.atan(math.sqrt((x-orgx)**2+(y-orgy)**2)*qx/distance))
def set_info_from_xdsinp_or_inpstr(self, xdsinp=None, inpstr=None):
assert (xdsinp,inpstr).count(None) == 1
t1 = lambda x: x.split()[0] # may have units that should be removed (if read from INTEGRATE.LP header)
table = [("STARTING_FRAME", "starting_frame", lambda x: int(t1(x))),
("STARTING_ANGLE", "starting_angle", lambda x: float(t1(x))),
("OSCILLATION_RANGE", "osc_range", lambda x: float(t1(x))),
("ROTATION_AXIS", "rotation_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("DIRECTION_OF_DETECTOR_X-AXIS", "X_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("DIRECTION_OF_DETECTOR_Y-AXIS", "Y_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("X-RAY_WAVELENGTH", "wavelength", lambda x: float(t1(x))),
("INCIDENT_BEAM_DIRECTION", "incident_beam", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("NX", "nx", lambda x: int(t1(x))),
("NY", "ny", lambda x: int(t1(x))),
("QX", "qx", lambda x: float(t1(x))),
("QY", "qy", lambda x: float(t1(x))),
("DETECTOR_DISTANCE", "distance", lambda x: float(t1(x))),
("SPACE_GROUP_NUMBER", "spacegroup", lambda x: int(t1(x))),
("UNIT_CELL_CONSTANTS", "unit_cell", lambda x: numpy.array(map(lambda y:float(y), x.split()[:6]))),
("UNIT_CELL_A-AXIS", "a_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("UNIT_CELL_B-AXIS", "b_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3]))),
("UNIT_CELL_C-AXIS", "c_axis", lambda x: numpy.array(map(lambda y:float(y), x.split()[:3])))
]
inp_raw = get_xdsinp_keyword(xdsinp=xdsinp, inp_str=inpstr)
inp = dict(inp_raw)# I believe dict() removes duplicated parameters and keeps last.
for k, at, f in table:
if k in inp and inp[k].strip() != "":
setattr(self, at, f(inp[k]))
if "ORGX" in inp:
self.origin[0] = float(inp["ORGX"])
if "ORGY" in inp:
self.origin[1] = float(inp["ORGY"])
if "DIRECTION_OF_DETECTOR_X-AXIS" in inp:
self.Z_axis = numpy.cross(self.X_axis, self.Y_axis)
self.Z_axis /= numpy.linalg.norm(self.Z_axis)
# Segment
for k, v in inp_raw:
if k == "SEGMENT":
sp = map(int, v.split())
self.segments.append(Segment())
self.segments[-1].x1 = sp[0]
self.segments[-1].x2 = sp[1]
self.segments[-1].y1 = sp[2]
self.segments[-1].y2 = sp[3]
elif k == "SEGMENT_ORGX":
self.segments[-1].orgxs = float(v)
elif k == "SEGMENT_ORGY":
self.segments[-1].orgys = float(v)
elif k == "SEGMENT_DISTANCE":
self.segments[-1].fs = float(v)
elif k == "DIRECTION_OF_SEGMENT_X-AXIS":
self.segments[-1].eds_x = numpy.array(map(float, v.split()))
elif k == "DIRECTION_OF_SEGMENT_Y-AXIS":
self.segments[-1].eds_y = numpy.array(map(float, v.split()))
def set_xdsinp(self, xdsinp):
inp = dict(get_xdsinp_keyword(xdsinp))
wavelength = float(inp["X-RAY_WAVELENGTH"])
orgx, orgy = map(float, (inp["ORGX"], inp["ORGY"]))
qx = float(inp["QX"])
distance = abs(float(inp["DETECTOR_DISTANCE"]))
# XXX no support for non-normal incident beam or multipanel detector
self.calc_d = lambda x, y: wavelength/2./math.sin(0.5*math.atan(math.sqrt((x-orgx)**2+(y-orgy)**2)*qx/distance))
def run_xds_sequence(root, params):
tmpdir = None
if params.use_tmpdir_if_available:
tmpdir = util.get_temp_local_dir("xdskamo", min_gb=2) # TODO guess required tempdir size
if tmpdir is None:
print "Can't get temp dir with sufficient size."
# If tmpdir is not used
if tmpdir is None:
return xds_sequence(root, params)
print "Using %s as temp dir.." % tmpdir
# If tempdir is used
for f in glob.glob(os.path.join(root, "*")): shutil.copy2(f, tmpdir)
xdsinp = os.path.join(tmpdir, "XDS.INP")
xdsinp_dict = dict(get_xdsinp_keyword(xdsinp))
# Make a link to data dir
org_data_template = xdsinp_dict["NAME_TEMPLATE_OF_DATA_FRAMES"]
ord_data_dir = os.path.dirname(org_data_template)
if not os.path.isabs(ord_data_dir): ord_data_dir = os.path.join(root, ord_data_dir)
datadir_lns = os.path.join(tmpdir, "data_loc")
os.symlink(ord_data_dir, datadir_lns)
# Modify XDS.INP
modify_xdsinp(xdsinp, inp_params=[("NAME_TEMPLATE_OF_DATA_FRAMES",
os.path.join("data_loc", os.path.basename(org_data_template)))])
try:
ret = xds_sequence(tmpdir, params)
finally:
# Revert XDS.INP
modify_xdsinp(xdsinp, inp_params=[("NAME_TEMPLATE_OF_DATA_FRAMES", org_data_template)])
# Remove link
os.remove(datadir_lns)
# Move to original directory
for f in glob.glob(os.path.join(tmpdir, "*")):
f_dest = os.path.join(root, os.path.relpath(f, tmpdir))
if os.path.isfile(f_dest):
# Copy only if newer
if os.stat(f).st_mtime > os.stat(f_dest).st_mtime:
shutil.copy2(f, root)
else:
print "%s already exists and not modified. skip." % f
os.remove(f)
else:
shutil.move(f, root)
# Remove tmpdir
shutil.rmtree(tmpdir)
return ret
def set_xdsinp(self, xdsinp):
inp = dict(get_xdsinp_keyword(xdsinp))
wavelength = float(inp["X-RAY_WAVELENGTH"])
orgx, orgy = map(float, (inp["ORGX"], inp["ORGY"]))
qx = float(inp["QX"])
distance = abs(float(inp["DETECTOR_DISTANCE"]))
# XXX no support for non-normal incident beam or multipanel detector
self.calc_d = lambda x, y: wavelength / 2. / math.sin(0.5 * math.atan(
math.sqrt((x - orgx)**2 + (y - orgy)**2) * qx / distance))
def run(xscale_inp):
inp_dir = os.path.dirname(xscale_inp)
files = map(
lambda y: y[1].replace("*", ""),
filter(lambda x: x[0] == "INPUT_FILE", get_xdsinp_keyword(xscale_inp)))
files = map(
lambda x: os.path.join(inp_dir, x)
if not os.path.isabs(x) else x, files)
symms = map(lambda x: XDS_ASCII(x, read_data=False).symm, files)
cells = numpy.array(map(lambda x: x.unit_cell().parameters(), symms))
sgs = map(lambda x: str(x.space_group_info()), symms)
laues = map(
lambda x: str(x.space_group().build_derived_reflection_intensity_group(
False).info()), symms)
median_cell = map(lambda i: numpy.median(cells[:, i]), xrange(6))
mean_cell = map(lambda i: cells[:, i].mean(), xrange(6))
cell_sd = map(lambda i: numpy.std(cells[:, i]), xrange(6))
print "%4d files loaded" % len(files)
print "Space groups:", ", ".join(
map(lambda x: "%s (%d files)" % (x, sgs.count(x)), set(sgs)))
print " Laue groups:", ", ".join(
map(lambda x: "%s (%d files)" % (x, laues.count(x)), set(laues)))
print " Median cell:", " ".join(map(lambda x: "%7.3f" % x, median_cell))
print " Mean cell:", " ".join(map(lambda x: "%7.3f" % x, mean_cell))
print " SD:", " ".join(map(lambda x: "%7.1e" % x, cell_sd))
# for BLEND $CCP4/share/blend/R/blend0.R
# names(macropar) <- c("cn","a","b","c","alpha","beta","gamma","mosa","ctoddist","wlength")
ofs = open("forR_macropar.dat", "w")
for i, cell in enumerate(cells):
print >> ofs, "%4d" % (i + 1),
print >> ofs, " ".join(map(lambda x: "%7.3f" % x, cell)),
print >> ofs, " 0 0 0"
ofs.close()
shutil.copyfile("forR_macropar.dat", "forR_macropar.dat.bak")
print
print "Run BLEND?"
print "Rscript $CCP4/share/blend/R/blend0.R"
def read_geometry_using_dxtbx(img_file):
import dxtbx.datablock
import dxtbx.serialize.xds
geom_kwds = set([
"DIRECTION_OF_DETECTOR_X-AXIS", "DIRECTION_OF_DETECTOR_Y-AXIS",
"DETECTOR_DISTANCE", "ORGX", "ORGY", "ROTATION_AXIS",
"X-RAY_WAVELENGTH", "DETECTOR", "MINIMUM_VALID_PIXEL_VALUE",
"OVERLOAD", "SENSOR_THICKNESS", "NX", "NY", "QX", "QY",
"STARTING_ANGLE", "OSCILLATION_RANGE", "FRACTION_OF_POLARIZATION",
"POLARIZATION_PLANE_NORMAL", "INCIDENT_BEAM_DIRECTION", "SEGMENT",
"DIRECTION_OF_SEGMENT_X-AXIS", "DIRECTION_OF_SEGMENT_Y-AXIS",
"SEGMENT_DISTANCE", "SEGMENT_ORGX", "SEGMENT_ORGY"
])
datablocks = dxtbx.datablock.DataBlockFactory.from_filenames([img_file])
to_xds = dxtbx.serialize.xds.to_xds(datablocks[0].extract_sweeps()[0])
inp = get_xdsinp_keyword(inp_str=to_xds.XDS_INP())
inp = filter(lambda x: x[0] in geom_kwds, inp)
return to_xds, map(lambda x: " %s= %s" % x, inp)
def run(params):
xds_inp = os.path.join(params.xds_dir, "XDS.INP")
spot_xds = os.path.join(params.xds_dir, "SPOT.XDS")
spots = idxreflp.SpotXds(
spot_xds).indexed_and_unindexed_by_frame_on_detector()
inputs = get_xdsinp_keyword(xds_inp)
filename_template = dict(inputs).get("NAME_TEMPLATE_OF_DATA_FRAMES", "")
if filename_template == "":
print "Error! Can't find filename from XDS.INP"
return
# Start adxv
adxv = Adxv(params.adxv_bin)
adxv.start(params.xds_dir)
type_indexed = adxv.define_spot("blue")
type_unindexed = adxv.define_spot("red")
num = params.image
while True:
print "Showing image %d" % num
img_file = dataset.template_to_filenames(filename_template, num,
num)[0]
adxv.open_image(img_file)
uninds = map(lambda x: [x[0], x[1], type_unindexed],
spots["unindexed"].get(num, []))
inds = map(lambda x: [x[0], x[1], type_indexed],
spots["indexed"].get(num, []))
print "Showing %d Indexed spots (blue)" % len(inds)
print "Showing %d Unindexed spots (red)" % len(uninds)
adxv.load_spots(inds + uninds)
time.sleep(1) # wait until adxv finishes process..
num = int(raw_input("Next image number?: "))
def run(params):
xdsinp = "XDS.INP"
kwds = dict(get_xdsinp_keyword(xdsinp))
orgx_org, orgy_org = map(float, (kwds["ORGX"], kwds["ORGY"]))
dx, dy = params.dx, params.dy
if params.unit == "mm":
assert "QX" in kwds
assert "QY" in kwds
dx /= float(kwds["QX"])
dy /= float(kwds["QY"])
backup_needed = files.generated_by_IDXREF + ("XDS.INP",)
bk_prefix = make_backup(backup_needed)
try:
results = []
for i in xrange(-params.nx, params.nx+1):
for j in xrange(-params.ny, params.ny+1):
work_name = "bs_x%+.2d_y%+.2d" % (i, j)
orgx = orgx_org + i * dx
orgy = orgy_org + j * dy
print "Trying", orgx, orgy
modify_xdsinp(xdsinp, inp_params=[("JOB", "IDXREF"),
("ORGX", orgx),
("ORGY", orgy),
])
call("xds")
make_backup(backup_needed, work_name+"_")
results.append([work_name, orgx, orgy])
for ret in results:
print ret,
analyze_result(ret[0]+"_IDXREF.LP")
finally:
revert_files(backup_needed, bk_prefix)
def run(params):
xdsinp = "XDS.INP"
kwds = dict(get_xdsinp_keyword(xdsinp))
orgx_org, orgy_org = map(float, (kwds["ORGX"], kwds["ORGY"]))
dx, dy = params.dx, params.dy
if params.unit == "mm":
assert "QX" in kwds
assert "QY" in kwds
dx /= float(kwds["QX"])
dy /= float(kwds["QY"])
#backup_needed = files.generated_by_IDXREF + ("XDS.INP",)
#bk_prefix = make_backup(backup_needed)
orgxy_list = []
for i in xrange(-params.nx, params.nx+1):
for j in xrange(-params.ny, params.ny+1):
orgxy_list.append((orgx_org + i * dx, orgy_org + j * dy))
easy_mp.pool_map(fixed_func=lambda x: work(os.path.abspath(params.workdir), os.path.abspath(xdsinp), x),
args=orgxy_list,
processes=params.nproc)
def run(params):
xds_inp = os.path.join(params.xds_dir, "XDS.INP")
spot_xds = os.path.join(params.xds_dir, "SPOT.XDS")
spots = idxreflp.SpotXds(spot_xds).indexed_and_unindexed_by_frame_on_detector()
inputs = get_xdsinp_keyword(xds_inp)
filename_template = dict(inputs).get("NAME_TEMPLATE_OF_DATA_FRAMES", "")
if filename_template == "":
print "Error! Can't find filename from XDS.INP"
return
# Start adxv
adxv = Adxv(params.adxv_bin)
adxv.start(params.xds_dir)
type_indexed = adxv.define_spot("blue")
type_unindexed = adxv.define_spot("red")
num = params.image
while True:
print "Showing image %d" % num
img_file = dataset.template_to_filenames(filename_template, num, num)[0]
adxv.open_image(img_file)
uninds = map(lambda x: [x[0], x[1], type_unindexed], spots["unindexed"].get(num, []))
inds = map(lambda x: [x[0], x[1], type_indexed], spots["indexed"].get(num, []))
print "Showing %d Indexed spots (blue)" % len(inds)
print "Showing %d Unindexed spots (red)" % len(uninds)
adxv.load_spots(inds+uninds)
time.sleep(1) # wait until adxv finishes process..
num = int(raw_input("Next image number?: "))
def run(params):
xdsinp = "XDS.INP"
kwds = dict(get_xdsinp_keyword(xdsinp))
orgx_org, orgy_org = map(float, (kwds["ORGX"], kwds["ORGY"]))
dx, dy = params.dx, params.dy
if params.unit == "mm":
assert "QX" in kwds
assert "QY" in kwds
dx /= float(kwds["QX"])
dy /= float(kwds["QY"])
#backup_needed = files.generated_by_IDXREF + ("XDS.INP",)
#bk_prefix = make_backup(backup_needed)
orgxy_list = []
for i in xrange(-params.nx, params.nx + 1):
for j in xrange(-params.ny, params.ny + 1):
orgxy_list.append((orgx_org + i * dx, orgy_org + j * dy))
easy_mp.pool_map(fixed_func=lambda x: work(os.path.abspath(params.workdir),
os.path.abspath(xdsinp), x),
args=orgxy_list,
processes=params.nproc)
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 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 total_deg_from_xds_inp(xdsinp):
kwds = dict(get_xdsinp_keyword(xdsinp))
dr = map(int, kwds["DATA_RANGE"].split())
osc = float(kwds["OSCILLATION_RANGE"])
return (dr[1] - dr[0] + 1) * osc