class StillsReflectionManager(ReflectionManager):
"""Overloads for a Reflection Manager that does not exclude
reflections too close to the spindle, and reports only information
about X, Y, DelPsi residuals"""
_weighting_strategy = weighting_strategies.StillsWeightingStrategy()
experiment_type = "stills"
def _id_refs_to_keep(self, obs_data):
"""Create a selection of observations that pass certain conditions.
Stills-specific version removes checks relevant only to experiments
with a rotation axis."""
# first exclude reflections with miller index set to 0,0,0
sel1 = obs_data["miller_index"] != (0, 0, 0)
# exclude reflections with overloads, as these have worse centroids
sel2 = ~obs_data.get_flags(obs_data.flags.overloaded)
# combine selections
sel = sel1 & sel2
inc = flex.size_t_range(len(obs_data)).select(sel)
return inc
def print_stats_on_matches(self):
"""Print some basic statistics on the matches"""
l = self.get_matches()
nref = len(l)
if nref == 0:
logger.warning(
"Unable to calculate summary statistics for zero observations"
)
return
from scitbx.math import five_number_summary
try:
x_resid = l["x_resid"]
y_resid = l["y_resid"]
delpsi = l["delpsical.rad"]
w_x, w_y, _ = l["xyzobs.mm.weights"].parts()
w_delpsi = l["delpsical.weights"]
except KeyError:
return
header = ["", "Min", "Q1", "Med", "Q3", "Max"]
rows = []
row_data = five_number_summary(x_resid)
rows.append(["Xc - Xo (mm)"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(y_resid)
rows.append(["Yc - Yo (mm)"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(delpsi)
rows.append(["DeltaPsi (deg)"] + ["%.4g" % (e * RAD2DEG) for e in row_data])
row_data = five_number_summary(w_x)
rows.append(["X weights"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(w_y)
rows.append(["Y weights"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(w_delpsi)
rows.append(
["DeltaPsi weights"] + ["%.4g" % (e * DEG2RAD ** 2) for e in row_data]
)
msg = (
"\nSummary statistics for {} observations".format(nref)
+ " matched to predictions:"
)
logger.info(msg)
logger.info(dials.util.tabulate(rows, header) + "\n")
class StillsReflectionManager(ReflectionManager):
"""Overloads for a Reflection Manager that does not exclude
reflections too close to the spindle, and reports only information
about X, Y, DelPsi residuals"""
_weighting_strategy = weighting_strategies.StillsWeightingStrategy()
def print_stats_on_matches(self):
"""Print some basic statistics on the matches"""
l = self.get_matches()
nref = len(l)
from libtbx.table_utils import simple_table
from scitbx.math import five_number_summary
x_resid = l['x_resid']
y_resid = l['y_resid']
delpsi = l['delpsical.rad']
w_x, w_y, _ = l['xyzobs.mm.weights'].parts()
w_delpsi = l['delpsical.weights']
msg = "\nSummary statistics for {0} observations".format(nref) +\
" matched to predictions:"
header = ["", "Min", "Q1", "Med", "Q3", "Max"]
rows = []
try:
row_data = five_number_summary(x_resid)
rows.append(["Xc - Xo (mm)"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(y_resid)
rows.append(["Yc - Yo (mm)"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(delpsi)
rows.append(["DeltaPsi (deg)"] +
["%.4g" % (e * RAD2DEG) for e in row_data])
row_data = five_number_summary(w_x)
rows.append(["X weights"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(w_y)
rows.append(["Y weights"] + ["%.4g" % e for e in row_data])
row_data = five_number_summary(w_delpsi)
rows.append(["DeltaPsi weights"] +
["%.4g" % (e * DEG2RAD**2) for e in row_data])
except IndexError:
# zero length reflection list
logger.warning(
"Unable to calculate summary statistics for zero observations")
return
logger.info(msg)
st = simple_table(rows, header)
logger.info(st.format())
logger.info("")
# sorting is expensive and the following table is only of interest in
# special cases, so return now if verbosity is not high
if self._verbosity < 3: return
if nref < 20:
logger.debug("Fewer than 20 reflections matched!")
return
sl = self._sort_obs_by_residual(l)
logger.debug("Reflections with the worst 20 positional residuals:")
header = [
'Miller index', 'x_resid', 'y_resid', 'pnl', 'x_obs', 'y_obs',
'x_obs\nweight', 'y_obs\nweight'
]
rows = []
for i in xrange(20):
e = sl[i]
x_obs, y_obs, _ = e['xyzobs.mm.value']
rows.append([
'% 3d, % 3d, % 3d' % e['miller_index'],
'%5.3f' % e['x_resid'],
'%5.3f' % e['y_resid'],
'%d' % e['panel'],
'%5.3f' % x_obs,
'%5.3f' % y_obs,
'%5.3f' % e['xyzobs.mm.weights'][0],
'%5.3f' % e['xyzobs.mm.weights'][1]
])
logger.debug(simple_table(rows, header).format())
logger.debug("")
return