def write_fit_group(f, label, group):
if (label == "h_sds"): # retro-fitted
group = list(reversed(group))
id = identifier(label)
s = "D %s_s[] = {" % id
for fit in group:
s += " " + str(fit.stol) + ","
s = s[:-1] + " };"
print(s, file=f)
print("D %s_e[] = {" % id, file=f)
if (label == "h_sds"): # retro-fitted
from cctbx.eltbx.development.hydrogen_plots import fit_input
from scitbx.array_family import flex
fi = fit_input()
for fit in group:
sel = fi.stols <= fit.stol + 1.e-6
if (label == "h_sds"): # retro-fitted
gaussian_fit = scitbx.math.gaussian.fit(
fi.stols.select(sel),
fi.data.select(sel),
fi.sigmas.select(sel),
fit)
s = str(flex.max(gaussian_fit.significant_relative_errors()))
else:
s = str(fit.max_error)
if (fit is not group[-1]): s += ","
print(s, file=f)
print("};", file=f)
labels = []
for fit_unsorted in group:
fit = fit_unsorted.sort()
lbl = "%s_%d" % (id, fit.n_terms())
if (fit.use_c()): lbl += "c"
print("D %s[] = {" % lbl, file=f)
labels.append(lbl)
buf = []
for a,b in zip(fit.array_of_a(), fit.array_of_b()):
buf.append("%s, %s," % (str(a), str(b)))
if (fit.use_c()):
buf.append(str(fit.c()))
else:
buf[-1] = buf[-1][:-1]
for s in buf: print(s, file=f)
print("};", file=f)
print("D* %s_c[] = { %s };" % (id, ", ".join(labels)), file=f)
print(file=f)
return
print("""\
""", file=f)
def write_fit_group(f, label, group):
if (label == "h_sds"): # retro-fitted
group = list(reversed(group))
id = identifier(label)
s = "D %s_s[] = {" % id
for fit in group:
s += " " + str(fit.stol) + ","
s = s[:-1] + " };"
print >> f, s
print >> f, "D %s_e[] = {" % id
if (label == "h_sds"): # retro-fitted
from cctbx.eltbx.development.hydrogen_plots import fit_input
from scitbx.array_family import flex
fi = fit_input()
for fit in group:
sel = fi.stols <= fit.stol + 1.e-6
if (label == "h_sds"): # retro-fitted
gaussian_fit = scitbx.math.gaussian.fit(
fi.stols.select(sel),
fi.data.select(sel),
fi.sigmas.select(sel),
fit)
s = str(flex.max(gaussian_fit.significant_relative_errors()))
else:
s = str(fit.max_error)
if (fit is not group[-1]): s += ","
print >> f, s
print >> f, "};"
labels = []
for fit_unsorted in group:
fit = fit_unsorted.sort()
lbl = "%s_%d" % (id, fit.n_terms())
if (fit.use_c()): lbl += "c"
print >> f, "D %s[] = {" % lbl
labels.append(lbl)
buf = []
for a,b in zip(fit.array_of_a(), fit.array_of_b()):
buf.append("%s, %s," % (str(a), str(b)))
if (fit.use_c()):
buf.append(str(fit.c()))
else:
buf[-1] = buf[-1][:-1]
for s in buf: print >> f, s
print >> f, "};"
print >> f, "D* %s_c[] = { %s };" % (id, ", ".join(labels))
print >> f
return
print >> f, """\
def run(file_name,
args,
cutoff,
params,
zig_zag=False,
six_term=False,
full_fits=None,
plots_dir="itvc_fits_plots",
verbose=0):
tab = itvc_section61_io.read_table6111(file_name)
chunk_n = 1
chunk_i = 0
if (len(args) > 0 and len(args[0].split(",")) == 2):
chunk_n, chunk_i = [int(i) for i in args[0].split(",")]
args = args[1:]
if (not six_term and not zig_zag):
if (not os.path.isdir(plots_dir)):
print("No plots because target directory does not exist (mkdir %s)." % \
plots_dir)
plots_dir = None
if (chunk_n > 1):
assert plots_dir is not None
stols_more = cctbx.eltbx.gaussian_fit.international_tables_stols
sel = stols_more <= cutoff + 1.e-6
stols = stols_more.select(sel)
i_chunk = 0
for element in tab.elements + ["O2-", "SDS"]:
if (len(args) > 0 and element not in args): continue
flag = i_chunk % chunk_n == chunk_i
i_chunk += 1
if (not flag):
continue
results = {}
results["fit_parameters"] = params
if (element == "SDS"):
wrk_lbl = element
from cctbx.eltbx.development.hydrogen_plots import fit_input
fi = fit_input()
sel = fi.stols <= cutoff + 1.e-6
null_fit = scitbx.math.gaussian.fit(
fi.stols.select(sel), fi.data.select(sel),
fi.sigmas.select(sel), xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
fi.stols, fi.data, fi.sigmas,
xray_scattering.gaussian(0, False))
else:
wrk_lbl = xray_scattering.wk1995(element, True)
if (element != "O2-"):
entry = tab.entries[element]
null_fit = scitbx.math.gaussian.fit(
stols, entry.table_y[:stols.size()],
entry.table_sigmas[:stols.size()],
xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
stols_more, entry.table_y[:stols_more.size()],
entry.table_sigmas[:stols_more.size()],
xray_scattering.gaussian(0, False))
else:
rrg_stols_more = rez_rez_grant.table_2_stol
sel = rrg_stols_more <= cutoff + 1.e-6
rrg_stols = rrg_stols_more.select(sel)
null_fit = scitbx.math.gaussian.fit(
rrg_stols,
rez_rez_grant.table_2_o2minus[:rrg_stols.size()],
rez_rez_grant.table_2_sigmas[:rrg_stols.size()],
xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
rrg_stols_more,
rez_rez_grant.table_2_o2minus[:rrg_stols_more.size()],
rez_rez_grant.table_2_sigmas[:rrg_stols_more.size()],
xray_scattering.gaussian(0, False))
if (zig_zag):
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.zig_zag_fits(
label=wrk_lbl,
null_fit=null_fit,
null_fit_more=null_fit_more,
params=params)
elif (full_fits is not None):
assert len(full_fits.all[wrk_lbl]) == 1
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.decremental_fits(
label=wrk_lbl,
null_fit=null_fit,
full_fit=full_fits.all[wrk_lbl][0],
params=params,
plots_dir=plots_dir,
verbose=verbose)
elif (not six_term):
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.incremental_fits(
label=wrk_lbl,
null_fit=null_fit,
params=params,
plots_dir=plots_dir,
verbose=verbose)
else:
best_min = scitbx.math.gaussian_fit.fit_with_golay_starts(
label=wrk_lbl,
null_fit=null_fit,
null_fit_more=null_fit_more,
params=params)
g = best_min.final_gaussian_fit
results[wrk_lbl] = [
xray_scattering.fitted_gaussian(stol=g.table_x()[-1],
gaussian_sum=g)
]
sys.stdout.flush()
pickle_file_name = "%s_fits.pickle" % identifier(wrk_lbl)
easy_pickle.dump(pickle_file_name, results)
def run(file_name, args, cutoff, params,
zig_zag=False, six_term=False, full_fits=None,
plots_dir="itvc_fits_plots", verbose=0):
tab = itvc_section61_io.read_table6111(file_name)
chunk_n = 1
chunk_i = 0
if (len(args) > 0 and len(args[0].split(",")) == 2):
chunk_n, chunk_i = [int(i) for i in args[0].split(",")]
args = args[1:]
if (not six_term and not zig_zag):
if (not os.path.isdir(plots_dir)):
print "No plots because target directory does not exist (mkdir %s)." % \
plots_dir
plots_dir = None
if (chunk_n > 1):
assert plots_dir is not None
stols_more = cctbx.eltbx.gaussian_fit.international_tables_stols
sel = stols_more <= cutoff + 1.e-6
stols = stols_more.select(sel)
i_chunk = 0
for element in tab.elements + ["O2-", "SDS"]:
if (len(args) > 0 and element not in args): continue
flag = i_chunk % chunk_n == chunk_i
i_chunk += 1
if (not flag):
continue
results = {}
results["fit_parameters"] = params
if (element == "SDS"):
wrk_lbl = element
from cctbx.eltbx.development.hydrogen_plots import fit_input
fi = fit_input()
sel = fi.stols <= cutoff + 1.e-6
null_fit = scitbx.math.gaussian.fit(
fi.stols.select(sel),
fi.data.select(sel),
fi.sigmas.select(sel),
xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
fi.stols,
fi.data,
fi.sigmas,
xray_scattering.gaussian(0, False))
else:
wrk_lbl = xray_scattering.wk1995(element, True)
if (element != "O2-"):
entry = tab.entries[element]
null_fit = scitbx.math.gaussian.fit(
stols,
entry.table_y[:stols.size()],
entry.table_sigmas[:stols.size()],
xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
stols_more,
entry.table_y[:stols_more.size()],
entry.table_sigmas[:stols_more.size()],
xray_scattering.gaussian(0, False))
else:
rrg_stols_more = rez_rez_grant.table_2_stol
sel = rrg_stols_more <= cutoff + 1.e-6
rrg_stols = rrg_stols_more.select(sel)
null_fit = scitbx.math.gaussian.fit(
rrg_stols,
rez_rez_grant.table_2_o2minus[:rrg_stols.size()],
rez_rez_grant.table_2_sigmas[:rrg_stols.size()],
xray_scattering.gaussian(0, False))
null_fit_more = scitbx.math.gaussian.fit(
rrg_stols_more,
rez_rez_grant.table_2_o2minus[:rrg_stols_more.size()],
rez_rez_grant.table_2_sigmas[:rrg_stols_more.size()],
xray_scattering.gaussian(0, False))
if (zig_zag):
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.zig_zag_fits(
label=wrk_lbl,
null_fit=null_fit,
null_fit_more=null_fit_more,
params=params)
elif (full_fits is not None):
assert len(full_fits.all[wrk_lbl]) == 1
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.decremental_fits(
label=wrk_lbl,
null_fit=null_fit,
full_fit=full_fits.all[wrk_lbl][0],
params=params,
plots_dir=plots_dir,
verbose=verbose)
elif (not six_term):
results[wrk_lbl] = cctbx.eltbx.gaussian_fit.incremental_fits(
label=wrk_lbl,
null_fit=null_fit,
params=params,
plots_dir=plots_dir,
verbose=verbose)
else:
best_min = scitbx.math.gaussian_fit.fit_with_golay_starts(
label=wrk_lbl,
null_fit=null_fit,
null_fit_more=null_fit_more,
params=params)
g = best_min.final_gaussian_fit
results[wrk_lbl] = [xray_scattering.fitted_gaussian(
stol=g.table_x()[-1], gaussian_sum=g)]
sys.stdout.flush()
pickle_file_name = "%s_fits.pickle" % identifier(wrk_lbl)
easy_pickle.dump(pickle_file_name, results)
