def CC(self, beam_center, rotmat=None):
detector = self.image.get_detector()
angle = [0, 3, 2, 1][self.i_quad] #
asic = self.image.get_raw_data()[list(detector.get_names()).index(
self.panel.get_name())].matrix_rot90(angle)
p_w, p_h = self.panel.get_image_size()
b = [
self.panel.get_pixel_lab_coord((0, 0)),
self.panel.get_pixel_lab_coord((p_w - 1, 0)),
self.panel.get_pixel_lab_coord((p_w - 1, p_h - 1)),
self.panel.get_pixel_lab_coord((0, p_h - 1))
]
asic_origin = col(
self.panel.millimeter_to_pixel(
(min([p[0] for p in b]), min([p[1] for p in b]))))
if rotmat is None:
rot45 = sqr(
(sin(pi / 3.), -cos(pi / 3.), cos(pi / 3.), sin(pi / 3.)))
else:
rot45 = rotmat
from xfel.metrology.legacy_scale import quadrant_self_correlation
min_value = self.image.get_detector()[0].get_trusted_range()[0]
REF, ROT = quadrant_self_correlation(asic.as_double(), asic_origin,
beam_center, rot45, min_value)
CCRR = flex.linear_correlation(REF, ROT)
return CCRR.coefficient()
def CC(self, beam_center):
quad = self.tiling[4*self.sensor[0]:4+4*self.sensor[0]]
asic = self.image.linearintdata.matrix_copy_block(quad[0],quad[1],
quad[2]-quad[0],quad[3]-quad[1])
#npy = asic.as_numpy_array()
#from matplotlib import pyplot as plt
#plt.imshow(npy, cmap="hot")
#plt.show()
asci_origin = col((float(quad[0]),float(quad[1])))
rot45 = sqr((sin(pi/4.),-cos(pi/4.),cos(pi/4.),sin(pi/4.)))
from xfel.metrology.legacy_scale import quadrant_self_correlation
min_value = self.image.get_detector()[0].get_trusted_range()[0]
REF,ROT = quadrant_self_correlation(asic,asci_origin,beam_center,rot45,min_value)
CCRR = flex.linear_correlation(REF,ROT)
"""initial python implementation
#rot_asic = flex.double(asic.accessor())
F0,F1 = asic.focus()
ref_data = flex.double()
rot_data = flex.double()
constant = rot45*(asci_origin - beam_center) +beam_center - asci_origin
for xcoord in range(quad[2]-quad[0]):
for ycoord in range(quad[3]-quad[1]):
acoord = col((float(xcoord),float(ycoord)))
#prime = rot45*(acoord + asci_origin - beam_center) + beam_center - asci_origin
prime = rot45*acoord + constant
prime = (int(round(prime[0],0)),int(round(prime[1],0)))
if 0<=prime[0]<F0 and 0<=prime[1]<F1:
#rot_asic[(xcoord,ycoord)]=asic[prime]
ref_data.append(asic[(xcoord,ycoord)])
rot_data.append(asic[prime])
CC = flex.linear_correlation(ref_data,rot_data)
print "Correlation_coefficient %7.4f %7.4f"%(CC.coefficient(),CCRR.coefficient())
"""
return CCRR.coefficient()
def CC(self, beam_center):
quad = self.tiling[4*self.sensor[0]:4+4*self.sensor[0]]
asic = self.image.linearintdata.matrix_copy_block(quad[0],quad[1],
quad[2]-quad[0],quad[3]-quad[1])
#npy = asic.as_numpy_array()
#from matplotlib import pyplot as plt
#plt.imshow(npy, cmap="hot")
#plt.show()
asci_origin = col((float(quad[0]),float(quad[1])))
rot45 = sqr((sin(pi/4.),-cos(pi/4.),cos(pi/4.),sin(pi/4.)))
from xfel.metrology.legacy_scale import quadrant_self_correlation
min_value = self.image.get_detector()[0].get_trusted_range()[0]
REF,ROT = quadrant_self_correlation(asic,asci_origin,beam_center,rot45,min_value)
CCRR = flex.linear_correlation(REF,ROT)
"""initial python implementation
#rot_asic = flex.double(asic.accessor())
F0,F1 = asic.focus()
ref_data = flex.double()
rot_data = flex.double()
constant = rot45*(asci_origin - beam_center) +beam_center - asci_origin
for xcoord in xrange(quad[2]-quad[0]):
for ycoord in xrange(quad[3]-quad[1]):
acoord = col((float(xcoord),float(ycoord)))
#prime = rot45*(acoord + asci_origin - beam_center) + beam_center - asci_origin
prime = rot45*acoord + constant
prime = (int(round(prime[0],0)),int(round(prime[1],0)))
if 0<=prime[0]<F0 and 0<=prime[1]<F1:
#rot_asic[(xcoord,ycoord)]=asic[prime]
ref_data.append(asic[(xcoord,ycoord)])
rot_data.append(asic[prime])
CC = flex.linear_correlation(ref_data,rot_data)
print "Correlation_coefficient %7.4f %7.4f"%(CC.coefficient(),CCRR.coefficient())
"""
return CCRR.coefficient()
def CC(self, beam_center):
detector = self.image.get_detector()
angle = [0,3,2,1][self.i_quad] #
asic = self.image.get_raw_data()[list(detector.get_names()).index(self.panel.get_name())].matrix_rot90(angle)
p_w, p_h = self.panel.get_image_size()
b = [self.panel.get_pixel_lab_coord((0 ,0 )),
self.panel.get_pixel_lab_coord((p_w-1,0 )),
self.panel.get_pixel_lab_coord((p_w-1,p_h-1)),
self.panel.get_pixel_lab_coord((0 ,p_h-1))]
asic_origin = col(self.panel.millimeter_to_pixel((min([p[0] for p in b]),
min([p[1] for p in b]))))
rot45 = sqr((sin(pi/4.),-cos(pi/4.),cos(pi/4.),sin(pi/4.)))
from xfel.metrology.legacy_scale import quadrant_self_correlation
min_value = self.image.get_detector()[0].get_trusted_range()[0]
REF,ROT = quadrant_self_correlation(asic.as_double(),asic_origin,beam_center,rot45,min_value)
CCRR = flex.linear_correlation(REF,ROT)
return CCRR.coefficient()
if params.show_plots:
from matplotlib import pyplot as plt
plt.imshow(data.as_numpy_array())
plt.show()
grid_radius = 20
mapp = flex.double(flex.grid(2*grid_radius+1, 2*grid_radius+1))
print mapp.focus()
gmax = 0.0
coordmax = (0,0)
for xi in range(-grid_radius, grid_radius+1):
for yi in range(-grid_radius, grid_radius+1):
test_bc = beam_center + col((xi,yi))
print "Testing beam center", test_bc.elems,
REF,ROT = quadrant_self_correlation(data,panel_origin,test_bc,rot45,trusted_min)
CCRR = flex.linear_correlation(REF,ROT)
VV = CCRR.coefficient()
if VV>gmax:
gmax = VV
coordmax = col((xi,yi))
mapp[(xi+grid_radius,yi+grid_radius)]=VV
print VV
print "max cc %7.4F is at "%gmax, (beam_center + coordmax).elems, "(slow, fast). Delta:", coordmax.elems
if params.show_plots:
npy = mapp.as_numpy_array()
from matplotlib import pyplot as plt
plt.imshow(npy, cmap="hot")
plt.plot([coordmax[1]+grid_radius],[coordmax[0]+grid_radius],"k.")
plt.show()
