def zero_below_threshold(self, m):
maptbx.reset(
data = m,
substitute_value = 0.0,
less_than_threshold = 0.24,
greater_than_threshold = -9999,
use_and = True)
def randomize_completeness2(map_coeffs, crystal_gridding, n_cycles=10):
map_filter = None
from mmtbx.maps import fem
for cycle in xrange(n_cycles):
if (cycle > 0):
mc = map_coeffs.select(flex.random_bool(map_coeffs.size(), 0.99))
else:
mc = map_coeffs.deep_copy()
m = get_map(map_coeffs=mc, crystal_gridding=crystal_gridding)
maptbx.reset(data=m,
substitute_value=0.0,
less_than_threshold=0.5,
greater_than_threshold=-9999,
use_and=True)
m = maptbx.volume_scale(map=m, n_bins=10000).map_data()
if (map_filter is not None):
map_filter = maptbx.volume_scale(map=map_filter,
n_bins=10000).map_data()
map_filter = fem.intersection(m1=map_filter,
m2=m,
thresholds=flex.double(
[i / 100. for i in range(0, 55, 5)]),
average=True)
#map_filter = map_filter.set_selected(map_filter< 0.5, 0)
#map_filter = map_filter.set_selected(map_filter>=0.5, 1)
return map_filter
def randomize_completeness2(map_coeffs, crystal_gridding, n_cycles=10):
map_filter = None
from mmtbx.maps import fem
for cycle in xrange(n_cycles):
if(cycle>0):
mc = map_coeffs.select(flex.random_bool(map_coeffs.size(), 0.99))
else:
mc = map_coeffs.deep_copy()
m = get_map(map_coeffs=mc, crystal_gridding=crystal_gridding)
maptbx.reset(
data=m,
substitute_value=0.0,
less_than_threshold=0.5,
greater_than_threshold=-9999,
use_and=True)
m = maptbx.volume_scale(map = m, n_bins = 10000).map_data()
if(map_filter is not None):
map_filter = maptbx.volume_scale(map = map_filter, n_bins = 10000).map_data()
map_filter = fem.intersection(m1=map_filter, m2=m,
thresholds=flex.double([i/100. for i in range(0,55,5)]),
average=True)
#map_filter = map_filter.set_selected(map_filter< 0.5, 0)
#map_filter = map_filter.set_selected(map_filter>=0.5, 1)
return map_filter