def objFuncSX(pFit, pFull, pFlag, dFunc, dFlag,
xyo_det, hkls_idx, bMat, vInv, wavelength,
bVec, eVec, omePeriod, simOnly=False):
npts = len(xyo_det)
refineFlag = np.hstack([pFlag, dFlag])
# pFull[refineFlag] = pFit/scl[refineFlag]
pFull[refineFlag] = pFit
dParams = pFull[-len(dFlag):]
xy_unwarped = dFunc(xyo_det[:, :2], dParams)
# detector quantities
rMat_d = xf.makeDetectorRotMat(pFull[:3])
tVec_d = pFull[3:6].reshape(3, 1)
# sample quantities
chi = pFull[6]
tVec_s = pFull[7:10].reshape(3, 1)
# crystal quantities
rMat_c = xf.makeRotMatOfExpMap(pFull[10:13])
tVec_c = pFull[13:16].reshape(3, 1)
gVec_c = np.dot(bMat, hkls_idx)
vMat_s = mutil.vecMVToSymm(vInv) # stretch tensor comp matrix from MV notation in SAMPLE frame
gVec_s = np.dot(vMat_s, np.dot(rMat_c, gVec_c)) # reciprocal lattice vectors in SAMPLE frame
gHat_s = mutil.unitVector(gVec_s) # unit reciprocal lattice vectors in SAMPLE frame
gHat_c = np.dot(rMat_c.T, gHat_s) # unit reciprocal lattice vectors in CRYSTAL frame
match_omes, calc_omes = matchOmegas(xyo_det, hkls_idx, chi, rMat_c, bMat, wavelength,
vInv=vInv, beamVec=bVec, etaVec=eVec, omePeriod=omePeriod)
xy_det = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xf.makeOscillRotMat([chi, calc_omes[i]])
# rMat_s = xf.makeOscillRotMat([chi, meas_omes[i]])
xy_det[i, :] = xf.gvecToDetectorXY(gHat_c[:, i].reshape(3, 1),
rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(xy_det)):
print "infeasible pFull: may want to scale back finite difference step size"
# return values
# retval = np.sum((xy_det - xy_unwarped[:, :2])**2)
if simOnly:
retval = np.hstack([xy_det, calc_omes.reshape(npts, 1)])
else:
# retval = np.sum( (xy_det - xy_unwarped[:, :2])**2, axis=1)
retval = np.sum( (np.hstack([xy_det, calc_omes.reshape(npts, 1)])
- np.hstack([xy_unwarped[:, :2], xyo_det[:, 2].reshape(npts, 1)])
)**2, axis=1)
return retval
[ -3.235616],
[-1050.74026 ] ] )
chi = -0.0011591608938627839
tVec_s = np.array([ [-0.15354144],
[ 0. ],
[-0.23294777] ] )
rMat_c = xf.makeRotMatOfExpMap(np.array( [ [ 0.66931818],
[-0.98578066],
[ 0.73593251] ] ) )
tVec_c = np.array( [ [ 0.07547626],
[ 0.08827523],
[-0.02131205] ] )
rMat_s = xf.makeOscillRotMat([chi, 0.])
# ######################################################################
# Calculate pixel coordinates
#
pvec = 204.8 * np.linspace(-1, 1, 512)
#pvec = 204.8 * np.linspace(-1, 1, 2048)
#pvec = 204.8 * np.linspace(-1, 1, 4096)
#pvec = 204.8 * np.linspace(-1, 1, 8192)
#pvec = 204.8 * np.linspace(-1, 1, 16384)
dcrds = np.meshgrid(pvec, pvec)
XY = np.ascontiguousarray(np.vstack([dcrds[0].flatten(), dcrds[1].flatten()]).T)
# Check the timings
from hexrd.xrd import transforms_CAPI as xfcapi epsf = 2.2e-16 vec = np.array([[random.uniform(-np.pi,np.pi),random.uniform(-np.pi,np.pi),random.uniform(-np.pi,np.pi)]]) vHat1 = xf.unitVector(vec.T) vHat2 = xfcapi.unitRowVector(vec) print "unitVector results match: ",np.linalg.norm(vHat1.T-vHat2)/np.linalg.norm(vHat1) < epsf tAng = np.array([0.0011546340766314521,-0.0040527538387122993,-0.0026221336905160211]) rMat1 = xf.makeDetectorRotMat(tAng) rMat2 = xfcapi.makeDetectorRotMat(tAng) print "makeDetectorRotMat results match: ",np.linalg.norm(rMat1-rMat2)/np.linalg.norm(rMat1) < epsf oAng = np.array([-0.0011591608938627839,0.0011546340766314521]) rMat1 = xf.makeOscillRotMat(oAng) rMat2 = xfcapi.makeOscillRotMat(oAng) print "makeOscillRotMat results match: ",np.linalg.norm(rMat1-rMat2)/np.linalg.norm(rMat1) < epsf eMap = np.array([ 0.66931818,-0.98578066,0.73593251]) rMat1 = xf.makeRotMatOfExpMap(eMap) rMat2 = xfcapi.makeRotMatOfExpMap(eMap) print "makeRotMatOfExpMap results match: ",np.linalg.norm(rMat1-rMat2)/np.linalg.norm(rMat1) < epsf axis = np.array([ 0.66931818,-0.98578066,0.73593251]) rMat1 = xf.makeBinaryRotMat(axis) rMat2 = xfcapi.makeBinaryRotMat(axis) print "makeBinaryRotMat results match: ",np.linalg.norm(rMat1-rMat2)/np.linalg.norm(rMat1) < epsf bHat = np.array([0.0,0.0,-1.0]) eta = np.array([1.0,0.0,0.0])
# input parameters
bVec_ref = xf.bVec_ref
tilt_angles = (0.0011546340766314521, -0.0040527538387122993,
-0.0026221336905160211)
rMat_d = xf.makeDetectorRotMat(tilt_angles)
tVec_d = np.array([[-1.44904], [-3.235616], [-1050.74026]])
chi = -0.0011591608938627839
tVec_s = np.array([[-0.15354144], [0.], [-0.23294777]])
rMat_c = xf.makeRotMatOfExpMap(
np.array([[0.66931818], [-0.98578066], [0.73593251]]))
tVec_c = np.array([[0.07547626], [0.08827523], [-0.02131205]])
rMat_s = xf.makeOscillRotMat([chi, 0.])
# ######################################################################
# Calculate pixel coordinates
#
pvec = 204.8 * np.linspace(-1, 1, 2048)
dcrds = np.meshgrid(pvec, pvec)
XY = np.ascontiguousarray(
np.vstack([dcrds[0].flatten(), dcrds[1].flatten()]).T)
# Check the timings
start1 = time.clock() # time this
dangs1 = xf.detectorXYToGvec(XY,
rMat_d,
rMat_s,
tVec_d,
random.uniform(-np.pi, np.pi)
]])
vHat1 = xf.unitVector(vec.T)
vHat2 = xfcapi.unitRowVector(vec)
print "unitVector results match: ", np.linalg.norm(
vHat1.T - vHat2) / np.linalg.norm(vHat1) < epsf
tAng = np.array(
[0.0011546340766314521, -0.0040527538387122993, -0.0026221336905160211])
rMat1 = xf.makeDetectorRotMat(tAng)
rMat2 = xfcapi.makeDetectorRotMat(tAng)
print "makeDetectorRotMat results match: ", np.linalg.norm(
rMat1 - rMat2) / np.linalg.norm(rMat1) < epsf
oAng = np.array([-0.0011591608938627839, 0.0011546340766314521])
rMat1 = xf.makeOscillRotMat(oAng)
rMat2 = xfcapi.makeOscillRotMat(oAng)
print "makeOscillRotMat results match: ", np.linalg.norm(
rMat1 - rMat2) / np.linalg.norm(rMat1) < epsf
eMap = np.array([0.66931818, -0.98578066, 0.73593251])
rMat1 = xf.makeRotMatOfExpMap(eMap)
rMat2 = xfcapi.makeRotMatOfExpMap(eMap)
print "makeRotMatOfExpMap results match: ", np.linalg.norm(
rMat1 - rMat2) / np.linalg.norm(rMat1) < epsf
axis = np.array([0.66931818, -0.98578066, 0.73593251])
rMat1 = xf.makeBinaryRotMat(axis)
rMat2 = xfcapi.makeBinaryRotMat(axis)
print "makeBinaryRotMat results match: ", np.linalg.norm(
rMat1 - rMat2) / np.linalg.norm(rMat1) < epsf
