def _parse_statistics(stats: ProcStats, report):
with open(report, "r", encoding="utf-8") as r:
log = r.readlines()
for n, line in enumerate(log):
if "Unit cell and space group:" in line:
parts = line.split()
stats.space_group = "".join(parts[11:]).replace("'", "")
(
stats.unit_cell_a,
stats.unit_cell_b,
stats.unit_cell_c,
stats.unit_cell_alpha,
stats.unit_cell_beta,
stats.unit_cell_gamma,
) = parts[5:11]
if "Low resolution limit " in line:
stats.low_resolution_average, stats.low_resolution_out = (
line.split()[3],
line.split()[5],
)
if "High resolution limit " in line:
stats.high_resolution_out, stats.high_resolution_average = (
line.split()[3],
line.split()[5],
)
if "Total number of observations " in line:
stats.reflections = line.split()[-3]
if "Total number unique " in line:
stats.unique_reflections = line.split()[-3]
if "Multiplicity " in line:
stats.multiplicity = line.split()[1]
if "Mean(I)/sd(I)" in line:
stats.i_sig_average = line.split()[1]
stats.i_sig_out = line.split()[-1]
if "Completeness (ellipsoidal)" in line or "Completeness (spherical)" in line:
stats.completeness_average = line.split()[2]
stats.completeness_out = line.split()[-1]
if "Rmeas (all I+ & I-)" in line:
stats.r_meas_average = line.split()[-3]
stats.r_meas_out = line.split()[-1]
elif "Rmeas" in line:
stats.r_meas_average = line.split()[-3]
stats.r_meas_out = line.split()[-1]
if "CRYSTAL MOSAICITY (DEGREES)" in line:
stats.mosaicity = line.split()[-1]
if "ISa (" in line:
stats.isa = log[n + 1].split()[-1]
return stats
def _parse_statistics(project: Project, edna_dir: Path, dataset, stats: ProcStats):
log_file = Path(edna_dir, f"ep_{dataset.name}_aimless_anom.log")
with open(log_file, "r", encoding="utf-8") as r:
log = r.readlines()
for line in log:
if "Space group:" in line:
stats.space_group = "".join(line.split()[2:])
if "Number of unique reflections" in line:
stats.unique_reflections = line.split()[-1]
if "Total number of observations" in line:
stats.reflections = line.split()[-3]
if "Low resolution limit" in line:
stats.low_resolution_average = line.split()[3]
stats.low_resolution_out = line.split()[-1]
if "High resolution limit" in line:
stats.high_resolution_average = line.split()[3]
stats.high_resolution_out = line.split()[-1]
if line.startswith(UNIT_CELL):
(
stats.unit_cell_a,
stats.unit_cell_b,
stats.unit_cell_c,
stats.unit_cell_alpha,
stats.unit_cell_beta,
stats.unit_cell_gamma,
) = line[len(UNIT_CELL) :].split()
if "Multiplicity" in line:
stats.multiplicity = line.split()[1]
if "Mean((I)/sd(I))" in line:
stats.i_sig_average = line.split()[1]
stats.i_sig_out = line.split()[-1]
if "Rmeas (all I+ & I-)" in line:
stats.r_meas_average = line.split()[5]
stats.r_meas_out = line.split()[-1]
if "completeness" in line:
stats.completeness_average = line.split()[-3]
stats.completeness_out = line.split()[-1]
if "mosaicity" in line:
stats.mosaicity = line.split()[-1]
return stats
def _parse_xia2_html(project: Project, xia2_html: Path, stats: ProcStats):
for line in read_text_lines(project, xia2_html):
if "High resolution limit " in line:
stats.high_resolution_average = line.split()[-3]
stats.high_resolution_out = line.split()[-1]
if "Low resolution limit " in line:
stats.low_resolution_average = line.split()[-3]
stats.low_resolution_out = line.split()[-1]
if "Completeness " in line:
stats.completeness_average = line.split()[-3]
stats.completeness_out = line.split()[-1]
if "Multiplicity " in line:
stats.multiplicity = line.split()[-3]
if "Rmeas(I+/-) " in line:
stats.r_meas_average = line.split()[-3]
stats.r_meas_out = line.split()[-1]
if "Total unique" in line:
stats.unique_reflections = line.split()[-3]
if "Total observations" in line:
stats.reflections = line.split()[-3]
if "Mosaic spread" in line:
stats.mosaicity = line.split()[-1]
if "I/sigma " in line:
stats.i_sig_average = line.split()[-3]
stats.i_sig_out = line.split()[-1]
if "Space group: " in line:
stats.space_group = "".join(line.split()[2:])
if "Unit cell: " in line:
vals = line.split(":")[1].strip()
(
stats.unit_cell_a,
stats.unit_cell_b,
stats.unit_cell_c,
stats.unit_cell_alpha,
stats.unit_cell_beta,
stats.unit_cell_gamma,
) = vals.split(", ")