def from_basisgrid(cls, bg, element_type=sensors.Mtrx):
"""
Convert a BasisGrid object to a CompoundCamera.
Parameters
----------
bg : basisgrid.BasisGrid
The basisgrid object to convert.
element_type : sensors.PixelArraySensor
The SensorElement type to populate the camera with.
Returns
-------
cd : CompoundCamera
The compound camera instance.
"""
if not isinstance(bg, basisgrid.BasisGrid):
raise TypeError('`bg` argument must be instance of BasisGrid,'
' got: %s' % type(bg))
cd = cls(type_name='root_frame', id_num=0, parent=None)
for g in range(bg.num_grids):
p, s, f, shape = bg.get_grid(g)
pixel_shape = (np.linalg.norm(s),
np.linalg.norm(f))
# to compute the rotation, find the
us = s / pixel_shape[0] # unit vector
uf = f / pixel_shape[1] # unit vector
n = np.cross(us, uf) # tested for orthog. in next fxn
# remember: in the matrix convention (Mikhail uses), +x is slow
# and +y is fast
ra = moveable._angles_from_rotated_frame(us, uf, n)
# translation is just p
tr = p
pas = element_type(shape,
pixel_shape,
id_num=g,
parent=cd,
rotation_angles=ra,
translation=tr)
return cd
def from_basisgrid(cls, bg, element_type=sensors.Mtrx):
"""
Convert a BasisGrid object to a CompoundCamera.
Parameters
----------
bg : basisgrid.BasisGrid
The basisgrid object to convert.
element_type : sensors.PixelArraySensor
The SensorElement type to populate the camera with.
Returns
-------
cd : CompoundCamera
The compound camera instance.
"""
if not isinstance(bg, basisgrid.BasisGrid):
raise TypeError('`bg` argument must be instance of BasisGrid,'
' got: %s' % type(bg))
cd = cls(type_name='root_frame', id_num=0, parent=None)
for g in range(bg.num_grids):
p, s, f, shape = bg.get_grid(g)
pixel_shape = (np.linalg.norm(s), np.linalg.norm(f))
# to compute the rotation, find the
us = s / pixel_shape[0] # unit vector
uf = f / pixel_shape[1] # unit vector
n = np.cross(us, uf) # tested for orthog. in next fxn
# remember: in the matrix convention (Mikhail uses), +x is slow
# and +y is fast
ra = moveable._angles_from_rotated_frame(us, uf, n)
# translation is just p
tr = p
pas = element_type(shape,
pixel_shape,
id_num=g,
parent=cd,
rotation_angles=ra,
translation=tr)
return cd
def test_angle_retrieval():
for i in range(100):
alpha = np.random.rand() * 180.0
beta = np.random.rand() * 180.0
gamma = np.random.rand() * 180.0
R = moveable._rotation_matrix_from_angles(gamma, beta, alpha)
I = np.eye(3)
Ip = np.dot(R, I)
gp, bp, ap = moveable._angles_from_rotated_frame(Ip[:,0], Ip[:,1], Ip[:,2])
#print np.array([gamma, beta, alpha]), np.array([gp, bp, ap])
# test to make sure they rotate to the same thing
R2 = moveable._rotation_matrix_from_angles(gp, bp, ap)
assert np.sum( np.abs( R - R2 ) ) < 1e-12
def test_angle_retrieval():
for i in range(100):
alpha = np.random.rand() * 180.0
beta = np.random.rand() * 180.0
gamma = np.random.rand() * 180.0
R = moveable._rotation_matrix_from_angles(gamma, beta, alpha)
I = np.eye(3)
Ip = np.dot(R, I)
gp, bp, ap = moveable._angles_from_rotated_frame(
Ip[:, 0], Ip[:, 1], Ip[:, 2])
#print np.array([gamma, beta, alpha]), np.array([gp, bp, ap])
# test to make sure they rotate to the same thing
R2 = moveable._rotation_matrix_from_angles(gp, bp, ap)
assert np.sum(np.abs(R - R2)) < 1e-12
def from_basisgrid(cls, bg):
"""
Convert a BasisGrid object to a Cspad. The BasisGrid must have 64 grids/
panels, one for each CSPAD ASIC.
Parameters
----------
bg : basisgrid.BasisGrid
The basisgrid object to convert.
Returns
-------
cspad : Cspad
The Cspad instance.
"""
cspad = cls(type_name='CSPAD:V1')
if not isinstance(bg, basisgrid.BasisGrid):
raise TypeError('`bg` argument must be instance of BasisGrid,'
' got: %s' % type(bg))
# if the grids are asics, we can strip out every other one and then
# treat them like 2x1s
if bg.num_pixels / bg.num_grids == 185 * 388: # two-by-one grids
stride = 1
elif bg.num_pixels / bg.num_grids == 185 * 194: # asic grids
stride = 2
else:
raise RuntimeError('Could not tell if BasisGrid grid elements are '
'CSPAD 2x1s or ASICs. Pixels per element:'
'%d' % (bg.num_pixels / bg.num_grids,))
for g in range(0, bg.num_grids, stride):
asic_id = (g/stride) # index from 0 to 7
# find the quad geometry
quad_index = asic_id / 8
# we just put the quads in a zero'd frame, no knowledge of absolute
# orientations
quad_rot = np.array([0.0, 0.0, 0.0])
quad_trs = np.array([0.0, 0.0, 0.0])
# add a new quad if necessary
if asic_id % 8 == 0:
quad = CompoundCamera(type_name='QUAD:V1',
id_num=quad_index,
parent=cspad,
rotation_angles=quad_rot,
translation=quad_trs)
p, s, f, shape = bg.get_grid(g)
pixel_shape = (np.linalg.norm(s),
np.linalg.norm(f))
# compute the rotation based on s/f vectors
us = s / pixel_shape[0] # unit vector
uf = f / pixel_shape[1] # unit vector
# BIG WARNING: There is a minus sign on `us` below, which is needed
# to account for the fact that the slow scan is swapped in the
# sensors.Cspad2x1 class
n = np.cross(uf, -us) # tested for orthog. in next fxn
ra = moveable._angles_from_rotated_frame(uf, -us, n)
# translation is center of 2x1, less the quad center
# dont forget the big pixels!
# dont forget p/s/f here is only an ASIC!
# dont forget p points to the middle of a pixel!
tr = p + 184.0/2.0 * 109.92 * us + (192.5 * 109.92 + 274.8) * uf
# construct the 2x1
pas = sensors.Cspad2x1(type_name='SENS2X1:V1',
id_num=int(asic_id % 8),
parent=quad,
rotation_angles=ra,
translation=tr)
# if we skipped a grid (ASIC), we'll check to make sure that
# the p-vector from that grid points to the correct pixel on
# our newly oriented 2x1 -- allow 10 um error in x/y, 200 um in z
if stride == 2:
p_skipped, _, _, _ = bg.get_grid(g + 1)
# be more lenient in z, since some programs are not general
# enough to handle it
if (np.linalg.norm(p_skipped[:2] - pas.xyz[0,194,:2]) > 10.0) or \
(np.abs(p_skipped[2] - pas.xyz[0,194,2]) > 200.0):
print('quad %d / 2x1 %d' % (quad_index, asic_id % 8))
print('grid p-vector: ', p_skipped)
print('pixel (0, 194): ', pas.xyz[0,194,:])
print('')
warnings.warn('The two ASICs making up the %d-th 2x1 on '
'the %d-th quad (grids %d, %d) do not conform'
' to the geometric requirements of a 2x1 '
'unit. Check your geometry! Do not ignore this'
' warning unless you were expecting it!!'
'' % (asic_id % 8, quad_index, g, g+1))
if _STRICT:
raise RuntimeError('_STRICT set, no warnings allowed')
return cspad
def from_basisgrid(cls, bg):
"""
Convert a BasisGrid object to a Cspad. The BasisGrid must have 64 grids/
panels, one for each CSPAD ASIC.
Parameters
----------
bg : basisgrid.BasisGrid
The basisgrid object to convert.
Returns
-------
cspad : Cspad
The Cspad instance.
"""
cspad = cls(type_name='CSPAD:V1')
if not isinstance(bg, basisgrid.BasisGrid):
raise TypeError('`bg` argument must be instance of BasisGrid,'
' got: %s' % type(bg))
# if the grids are asics, we can strip out every other one and then
# treat them like 2x1s
if bg.num_pixels / bg.num_grids == 185 * 388: # two-by-one grids
stride = 1
elif bg.num_pixels / bg.num_grids == 185 * 194: # asic grids
stride = 2
else:
raise RuntimeError('Could not tell if BasisGrid grid elements are '
'CSPAD 2x1s or ASICs. Pixels per element:'
'%d' % (bg.num_pixels / bg.num_grids, ))
for g in range(0, bg.num_grids, stride):
asic_id = (g / stride) # index from 0 to 7
# find the quad geometry
quad_index = asic_id / 8
# we just put the quads in a zero'd frame, no knowledge of absolute
# orientations
quad_rot = np.array([0.0, 0.0, 0.0])
quad_trs = np.array([0.0, 0.0, 0.0])
# add a new quad if necessary
if asic_id % 8 == 0:
quad = CompoundCamera(type_name='QUAD:V1',
id_num=quad_index,
parent=cspad,
rotation_angles=quad_rot,
translation=quad_trs)
p, s, f, shape = bg.get_grid(g)
pixel_shape = (np.linalg.norm(s), np.linalg.norm(f))
# compute the rotation based on s/f vectors
us = s / pixel_shape[0] # unit vector
uf = f / pixel_shape[1] # unit vector
# BIG WARNING: There is a minus sign on `us` below, which is needed
# to account for the fact that the slow scan is swapped in the
# sensors.Cspad2x1 class
n = np.cross(uf, -us) # tested for orthog. in next fxn
ra = moveable._angles_from_rotated_frame(uf, -us, n)
# translation is center of 2x1, less the quad center
# dont forget the big pixels!
# dont forget p/s/f here is only an ASIC!
# dont forget p points to the middle of a pixel!
tr = p + 184.0 / 2.0 * 109.92 * us + (192.5 * 109.92 + 274.8) * uf
# construct the 2x1
pas = sensors.Cspad2x1(type_name='SENS2X1:V1',
id_num=int(asic_id % 8),
parent=quad,
rotation_angles=ra,
translation=tr)
# if we skipped a grid (ASIC), we'll check to make sure that
# the p-vector from that grid points to the correct pixel on
# our newly oriented 2x1 -- allow 10 um error in x/y, 200 um in z
if stride == 2:
p_skipped, _, _, _ = bg.get_grid(g + 1)
# be more lenient in z, since some programs are not general
# enough to handle it
if (np.linalg.norm(p_skipped[:2] - pas.xyz[0,194,:2]) > 10.0) or \
(np.abs(p_skipped[2] - pas.xyz[0,194,2]) > 200.0):
print('quad %d / 2x1 %d' % (quad_index, asic_id % 8))
print('grid p-vector: ', p_skipped)
print('pixel (0, 194): ', pas.xyz[0, 194, :])
print('')
warnings.warn(
'The two ASICs making up the %d-th 2x1 on '
'the %d-th quad (grids %d, %d) do not conform'
' to the geometric requirements of a 2x1 '
'unit. Check your geometry! Do not ignore this'
' warning unless you were expecting it!!'
'' % (asic_id % 8, quad_index, g, g + 1))
if _STRICT:
raise RuntimeError('_STRICT set, no warnings allowed')
return cspad
