def rotate_image(self,data,angle_deg,sigma=1.0):
# we take an image, rotate, interpolate it back onto a regular grid and return it
#
# There is however the problem that some pixels will never be seen. those pixels will be filled up by interpolation
data = data*self.mask
cost = smath.cos( angle_deg*smath.pi/180.0 )
sint = smath.sin( angle_deg*smath.pi/180.0 )
new_image = flex.double(self.grid,0)
visited = flex.bool(self.grid,False)
nx_array = flex.double()
ny_array = flex.double()
val_array = flex.double()
for ix in range(self.np):
for iy in range(self.np):
x = ix - self.ox
y = iy - self.oy
nx = cost*x - sint*y
ny = sint*x + cost*y
jx = int(nx+self.ox+0.5)
jy = int(ny+self.oy+0.5)
if jx >= self.np : jx = self.np-1
if jy >= self.np : jy = self.np-1
if jx<0: jx=0
if jy<0: jy=0
new_image[ (jx,jy) ] = data[ (ix,iy) ]
visited[ (jx,jy) ] = True
nx_array.append( nx+self.ox )
ny_array.append( ny+self.oy )
val_array.append( data[ (ix,iy) ] )
assert nx_array.size() == self.mask.size()
not_visited = ~visited
not_visited = not_visited.iselection()
# now we need to loop over all non-visited pixel values
for pixel in not_visited:
#for ix in range(self.np):
# for iy in range(self.np):
nv = 0
if self.mask[(ix,iy)]>-0.1:
nv = -9
index = n_dim_index_from_one_dim(pixel, [self.np,self.np] )
nvx = index[1]
nvy = index[0]
dx = nx_array-nvx
dy = ny_array-nvy
dd = (dx*dx+dy*dy)
ss = flex.exp( -dd/(sigma*sigma) )*self.mask
nv = flex.sum(ss*val_array)/(1e-12+flex.sum(ss))
new_image[ (ix,iy) ] = nv
new_image = new_image*self.mask
return new_image
def enlarge(data,factor,sigma=0.1,full=False):
n,n = data.focus()
m = int(n*factor)
x = flex.double()
y = flex.double()
vals = flex.double()
sigma=sigma*factor
new_data = flex.double( flex.grid(m,m), -9 )
visited = flex.bool( flex.grid(m,m), False )
oo = n/2.0
for ii in range(n):
for jj in range(n):
dd = smath.sqrt( (ii-oo)**2.0 + (jj-oo)**2.0 )
if dd <= oo:
nx = ii*factor
ny = jj*factor
x.append( nx )
y.append( ny )
vals.append( data[ (ii,jj) ] )
new_data[ (int(nx), int(ny)) ] = data[ (ii,jj) ]
if not full:
visited[ (int(nx), int(ny)) ] = True
not_visited = ~visited
not_visited = not_visited.iselection()
# now we need to loop over all non-visited pixel values
for pixel in not_visited:
nv = -9
index = n_dim_index_from_one_dim(pixel, [m,m] )
nvx = index[1]
nvy = index[0]
dx = x-nvx
dy = y-nvy
dd = (dx*dx+dy*dy)
ss = flex.exp( -dd/(sigma*sigma) )
nv = flex.sum(ss*vals)/(1e-12+flex.sum(ss))
new_data[ (nvx,nvy) ] = nv
visited[ (nvx,nvy) ] = True
#print nvx, nvy, nv
not_visited = ~visited
not_visited = not_visited.iselection()
#print not_visited.size()
return new_data
oo=m/2.0
for ii in range(m):
for jj in range(m):
dd = smath.sqrt( (ii-oo)**2.0 + (jj-oo)**2.0 )
new_data[ (ii,jj) ] = new_data[ (ii,jj) ]/(1+smath.sqrt(dd))
return new_data
def exercise(space_group_info, redundancy_counter=0):
n_real = (12,12,12)
miller_max = (2,2,2)
gt = maptbx.grid_tags(n_real)
uc = space_group_info.any_compatible_unit_cell(volume=1000)
fl = sgtbx.search_symmetry_flags(use_space_group_symmetry=True)
gt.build(space_group_info.type(), fl)
fft = fftpack.real_to_complex_3d(n_real)
map0 = flex.double(flex.grid(fft.m_real()).set_focus(fft.n_real()), 0)
weight_map = map0.deep_copy()
map = map0.deep_copy()
ta = gt.tag_array()
order_z = space_group_info.group().order_z()
problems_expected = (redundancy_counter != 0)
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
xyz = [i/n for i,n in zip(ijk, n_real)]
ss = sgtbx.site_symmetry(
unit_cell=uc,
space_group=space_group_info.group(),
original_site=xyz,
min_distance_sym_equiv=1e-5)
m = space_group_info.group().multiplicity(
site=boost.rational.vector(ijk, n_real))
assert m == ss.multiplicity()
w = m / order_z
weight_map[ijk] = w
map[ijk] = w
elif (redundancy_counter != 0):
redundancy_counter -= 1
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
map[ijk] = map[ijk_asu]
sf_map = fft.forward(map)
del map
mi = miller.index_generator(
space_group_info.type(), False, miller_max).to_array()
assert mi.size() != 0
from_map = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map,
conjugate_flag=True)
sf = [iround(abs(f)) for f in from_map.data()]
if (sf != [0]*len(sf)):
assert problems_expected
return
else:
not problems_expected
#
map_p1 = map0.deep_copy()
map_sw = map0.deep_copy()
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
v = random.random()*2-1
map_p1[ijk] = v
map_sw[ijk] = v * weight_map[ijk]
else:
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
assert map_p1[ijk_asu] != 0
map_p1[ijk] = map_p1[ijk_asu]
#
# fft followed by symmetry summation in reciprocal space
sf_map_sw = fft.forward(map_sw)
del map_sw
sf_sw = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_sw,
conjugate_flag=True).data()
del sf_map_sw
#
# symmetry expansion in real space (done above already) followed fft
sf_map_p1 = fft.forward(map_p1)
del map_p1
sf_p1 = maptbx.structure_factors.from_map(
space_group=sgtbx.space_group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_p1,
conjugate_flag=True).data()
del sf_map_p1
#
corr = flex.linear_correlation(x=flex.abs(sf_sw), y=flex.abs(sf_p1))
assert corr.is_well_defined
assert approx_equal(corr.coefficient(), 1)
def exercise(space_group_info, redundancy_counter=0):
n_real = (12, 12, 12)
miller_max = (2, 2, 2)
gt = maptbx.grid_tags(n_real)
uc = space_group_info.any_compatible_unit_cell(volume=1000)
fl = sgtbx.search_symmetry_flags(use_space_group_symmetry=True)
gt.build(space_group_info.type(), fl)
fft = fftpack.real_to_complex_3d(n_real)
map0 = flex.double(flex.grid(fft.m_real()).set_focus(fft.n_real()), 0)
weight_map = map0.deep_copy()
map = map0.deep_copy()
ta = gt.tag_array()
order_z = space_group_info.group().order_z()
problems_expected = (redundancy_counter != 0)
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
xyz = [i / n for i, n in zip(ijk, n_real)]
ss = sgtbx.site_symmetry(unit_cell=uc,
space_group=space_group_info.group(),
original_site=xyz,
min_distance_sym_equiv=1e-5)
m = space_group_info.group().multiplicity(
site=boost.rational.vector(ijk, n_real))
assert m == ss.multiplicity()
w = m / order_z
weight_map[ijk] = w
map[ijk] = w
elif (redundancy_counter != 0):
redundancy_counter -= 1
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
map[ijk] = map[ijk_asu]
sf_map = fft.forward(map)
del map
mi = miller.index_generator(space_group_info.type(), False,
miller_max).to_array()
assert mi.size() != 0
from_map = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map,
conjugate_flag=True)
sf = [iround(abs(f)) for f in from_map.data()]
if (sf != [0] * len(sf)):
assert problems_expected
return
else:
not problems_expected
#
map_p1 = map0.deep_copy()
map_sw = map0.deep_copy()
for ijk in flex.nested_loop(n_real):
t = ta[ijk]
if (t < 0):
v = random.random() * 2 - 1
map_p1[ijk] = v
map_sw[ijk] = v * weight_map[ijk]
else:
ijk_asu = n_dim_index_from_one_dim(i1d=t, sizes=n_real)
assert ta.accessor()(ijk_asu) == t
assert map_p1[ijk_asu] != 0
map_p1[ijk] = map_p1[ijk_asu]
#
# fft followed by symmetry summation in reciprocal space
sf_map_sw = fft.forward(map_sw)
del map_sw
sf_sw = maptbx.structure_factors.from_map(
space_group=space_group_info.group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_sw,
conjugate_flag=True).data()
del sf_map_sw
#
# symmetry expansion in real space (done above already) followed fft
sf_map_p1 = fft.forward(map_p1)
del map_p1
sf_p1 = maptbx.structure_factors.from_map(space_group=sgtbx.space_group(),
anomalous_flag=False,
miller_indices=mi,
complex_map=sf_map_p1,
conjugate_flag=True).data()
del sf_map_p1
#
corr = flex.linear_correlation(x=flex.abs(sf_sw), y=flex.abs(sf_p1))
assert corr.is_well_defined
assert approx_equal(corr.coefficient(), 1)
def exercise_grid_indices_around_sites():
unit_cell = uctbx.unit_cell((5,5,5))
fft_n_real = (5,5,5)
fft_m_real = (5,5,5)
site_radii = flex.double([0.5*3**0.5+1e-6])
def get():
grid_indices = maptbx.grid_indices_around_sites(
unit_cell=unit_cell, fft_n_real=fft_n_real, fft_m_real=fft_m_real,
sites_cart=sites_cart, site_radii=site_radii)
return list(grid_indices)
sites_cart = flex.vec3_double([(0.5,0.5,0.5)])
assert get() == [0, 1, 5, 6, 25, 26, 30, 31]
sites_cart = flex.vec3_double([(1.5,1.5,1.5)])
assert get() == [31, 32, 36, 37, 56, 57, 61, 62]
def sample():
for i in xrange(-2,7):
for j in xrange(-2,7):
for k in xrange(-2,7):
sites_cart = flex.vec3_double([(i+.5,j+.5,k+.5)])
assert len(get()) == 8
sample()
#
unit_cell = uctbx.unit_cell((5,6,7))
fft_n_real = (5,6,7)
fft_m_real = (5,6,7)
sites_cart = flex.vec3_double([(0.5,0.5,0.5)])
assert get() == [0, 1, 7, 8, 42, 43, 49, 50]
fft_m_real = (5,6,8)
assert get() == [0, 1, 8, 9, 48, 49, 56, 57]
fft_m_real = (5,7,8)
assert get() == [0, 1, 8, 9, 56, 57, 64, 65]
sample()
#
site_radii = flex.double([2])
assert len(get()) == 8 + 6*4
site_radii = flex.double([1000])
assert len(get()) == 5*6*7
#
unit_cell = uctbx.unit_cell((18,26,27))
fft_n_real = (18,26,27)
fft_m_real = (18,27,28)
for ish in xrange(5):
x = 2*ish+.5
sites_cart = flex.vec3_double([[x]*3])
sh = 3**0.5*(ish+0.5)
site_radii = flex.double([sh-1e-6])
s1 = set(get())
site_radii = flex.double([sh+1e-6])
s2 = set(get())
for gi in sorted(s2-s1):
i,j,k = n_dim_index_from_one_dim(gi, fft_m_real)
assert approx_equal(abs(matrix.col((i-x,j-x,k-x))), sh)
assert len(s1) == [0, 56, 304, 912, 1904][ish]
assert len(s2) == [8, 88, 360, 968, 2008][ish]
#
unit_cell = uctbx.unit_cell((8,9,7,80,100,110))
fft_n_real = (11,13,15)
fft_m_real = (18,26,19)
sites_cart = flex.vec3_double([(3,11,5)])
ls = []
prev = 0
for r in itertools.count(1):
site_radii = flex.double([r])
l = len(get())
assert l > prev
ls.append(l)
if (l == 11*13*15):
break
assert r < 7
prev = l
assert ls == [18, 155, 524, 1225, 1940, 2139, 2145]
#
fft_m_real = (1073741824, 1073741824, 1073741824)
try:
maptbx.grid_indices_around_sites(
unit_cell=unit_cell, fft_n_real=fft_n_real, fft_m_real=fft_m_real,
sites_cart=sites_cart, site_radii=site_radii)
except RuntimeError, e:
assert str(e).startswith("product of fft_m_real")