def __init__(self, reflections, av_callback=flex.mean, debug=False):
# flags to indicate at what level the analysis has been performed
self._average_residuals = False
self._spectral_analysis = False
self._av_callback = av_callback
# Remove invalid reflections
reflections = reflections.select(~(reflections["miller_index"] ==
(0, 0, 0)))
# FIXME - better way to recognise non-predictions. Can't rely on flags
# in e.g. indexed.refl I think.
x, y, z = reflections["xyzcal.mm"].parts()
sel = (x == 0) & (y == 0)
reflections = reflections.select(~sel)
self._nexp = flex.max(reflections["id"]) + 1
# Ensure required keys are present
if not all(k in reflections
for k in ["x_resid", "y_resid", "phi_resid"]):
x_obs, y_obs, phi_obs = reflections["xyzobs.mm.value"].parts()
x_cal, y_cal, phi_cal = reflections["xyzcal.mm"].parts()
# do not wrap around multiples of 2*pi; keep the full rotation
# from zero to differentiate repeat observations.
TWO_PI = 2.0 * math.pi
resid = phi_cal - (flex.fmod_positive(phi_obs, TWO_PI))
# ensure this is the smaller of two possibilities
resid = flex.fmod_positive((resid + math.pi), TWO_PI) - math.pi
phi_cal = phi_obs + resid
reflections["x_resid"] = x_cal - x_obs
reflections["y_resid"] = y_cal - y_obs
reflections["phi_resid"] = phi_cal - phi_obs
# create empty results list
self._results = []
# first, just determine a suitable block size for analysis
for iexp in range(self._nexp):
ref_this_exp = reflections.select(reflections["id"] == iexp)
if len(ref_this_exp) == 0:
# can't do anything, just keep an empty dictionary
self._results.append({})
continue
phi_obs_deg = ref_this_exp["xyzobs.mm.value"].parts()[2] * RAD2DEG
phi_range = flex.min(phi_obs_deg), flex.max(phi_obs_deg)
phi_width = phi_range[1] - phi_range[0]
ideal_block_size = 1.0
old_nblocks = 0
while True:
nblocks = int(phi_width // ideal_block_size)
if nblocks == old_nblocks:
nblocks -= 1
nblocks = max(nblocks, 1)
block_size = phi_width / nblocks
nr = flex.int()
for i in range(nblocks - 1):
blk_start = phi_range[0] + i * block_size
blk_end = blk_start + block_size
sel = (phi_obs_deg >= blk_start) & (phi_obs_deg < blk_end)
nref_in_block = sel.count(True)
nr.append(nref_in_block)
# include max phi in the final block
blk_start = phi_range[0] + (nblocks - 1) * block_size
blk_end = phi_range[1]
sel = (phi_obs_deg >= blk_start) & (phi_obs_deg <= blk_end)
nref_in_block = sel.count(True)
nr.append(nref_in_block)
# Break if there are enough reflections, otherwise increase block size,
# unless only one block remains
if nblocks == 1:
break
min_nr = flex.min(nr)
if min_nr >= 50:
break
if min_nr < 5:
fac = 2
else:
fac = 50 / min_nr
ideal_block_size *= fac
old_nblocks = nblocks
# collect the basic data for this experiment
self._results.append({
"block_size": block_size,
"nref_per_block": nr,
"nblocks": nblocks,
"phi_range": phi_range,
})
# keep reflections for analysis
self._reflections = reflections
# for debugging, write out reflections used
if debug:
self._reflections.as_file("centroid_analysis.refl")
def __init__(self, reflections, av_callback=flex.mean):
# flags to indicate at what level the analysis has been performed
self._average_residuals = False
self._spectral_analysis = False
self._av_callback = av_callback
# Remove invalid reflections
reflections = reflections.select(~(reflections['miller_index'] == (0,0,0)))
# FIXME - better way to recognise non-predictions. Can't rely on flags
# in e.g. indexed.pickle I think.
x, y, z = reflections['xyzcal.mm'].parts()
sel = (x == 0) & (y == 0)
reflections = reflections.select(~sel)
self._nexp = flex.max(reflections['id']) + 1
# Ensure required keys are present
if not all([k in reflections for k in ['x_resid', 'y_resid', 'phi_resid']]):
x_obs, y_obs, phi_obs = reflections['xyzobs.mm.value'].parts()
x_cal, y_cal, phi_cal = reflections['xyzcal.mm'].parts()
# do not wrap around multiples of 2*pi; keep the full rotation
# from zero to differentiate repeat observations.
from math import pi
TWO_PI = 2.0 * pi
resid = phi_cal - (flex.fmod_positive(phi_obs, TWO_PI))
# ensure this is the smaller of two possibilities
resid = flex.fmod_positive((resid + pi), TWO_PI) - pi
phi_cal = phi_obs + resid
reflections['x_resid'] = x_cal - x_obs
reflections['y_resid'] = y_cal - y_obs
reflections['phi_resid'] = phi_cal - phi_obs
# create empty results list
self._results = []
# first, just determine a suitable block size for analysis
for iexp in range(self._nexp):
ref_this_exp = reflections.select(reflections['id'] == iexp)
if len(ref_this_exp) == 0:
# can't do anything, just keep an empty dictionary
self._results.append({})
continue
phi_obs_deg = ref_this_exp['xyzobs.mm.value'].parts()[2] * RAD2DEG
phi_range = flex.min(phi_obs_deg), flex.max(phi_obs_deg)
phi_width = phi_range[1] - phi_range[0]
ideal_block_size = 1.0
old_nblocks = 0
while True:
nblocks = int(phi_width // ideal_block_size)
if nblocks == old_nblocks: nblocks -= 1
nblocks = max(nblocks, 1)
block_size = phi_width / nblocks
nr = flex.int()
for i in range(nblocks - 1):
blk_start = phi_range[0] + i * block_size
blk_end = blk_start + block_size
sel = (phi_obs_deg >= blk_start) & (phi_obs_deg < blk_end)
nref_in_block = sel.count(True)
nr.append(nref_in_block)
# include max phi in the final block
blk_start = phi_range[0] + (nblocks - 1) * block_size
blk_end = phi_range[1]
sel = (phi_obs_deg >= blk_start) & (phi_obs_deg <= blk_end)
nref_in_block = sel.count(True)
nr.append(nref_in_block)
# Break if there are enough reflections, otherwise increase block size,
# unless only one block remains
if nblocks == 1: break
min_nr = flex.min(nr)
if min_nr >= 50: break
if min_nr < 5:
fac = 2
else:
fac = 50 / min_nr
ideal_block_size *= fac
old_nblocks = nblocks
# collect the basic data for this experiment
self._results.append({'block_size':block_size,
'nref_per_block':nr,
'nblocks':nblocks,
'phi_range':phi_range})
# keep reflections for analysis
self._reflections = reflections