def objFuncSX(pFit, pFull, pFlag, dFunc, dFlag,
xyo_det, hkls_idx, bMat, vInv, wavelength,
bVec, eVec, omePeriod,
simOnly=False, returnScalarValue=returnScalarValue):
"""
"""
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)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
print "infeasible pFull: may want to scale back finite difference step size"
# return values
if simOnly:
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
diff_vecs_xy = calc_xy - xy_unwarped[:, :2]
diff_ome = xf.angularDifference( calc_omes, xyo_det[:, 2] )
retval = np.hstack([diff_vecs_xy,
diff_ome.reshape(npts, 1)
]).flatten()
if returnScalarValue:
retval = sum( retval )
return retval
def objFuncSX(pFit, pFull, pFlag, dFunc, dFlag,
xyo_det, hkls_idx, bMat, vInv, wavelength,
bVec, eVec, omePeriod,
simOnly=False, returnScalarValue=returnScalarValue):
"""
"""
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)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
print "infeasible pFull: may want to scale back finite difference step size"
# return values
if simOnly:
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
diff_vecs_xy = calc_xy - xy_unwarped[:, :2]
diff_ome = xf.angularDifference( calc_omes, xyo_det[:, 2] )
retval = np.hstack([diff_vecs_xy,
diff_ome.reshape(npts, 1)
]).flatten()
if returnScalarValue:
retval = sum( retval )
return retval
def xy_of_angs(self, angs):
"""
Cartesion coordinates of vstacked (tth, eta) pairs
*) wrapper for transforms.anglesToGVec
"""
gVec_l = xf.anglesToGVec(angs, self.bVec, self.eVec,
rMat_s=None, rMat_c=None)
xy = xf.gvecToDetectorXY(gVec_l,
self.rMat, I3, I3,
self.tVec, self.tVec_s, self.tVec_c,
distortion=self.distortion,
beamVec=self.bVec,
etaVec=self.eVec)
return xy
def angles_to_cart(self, tth_eta):
"""
TODO: distortion
"""
rmat_s = rmat_c = ct.identity_3x3
tvec_s = tvec_c = ct.zeros_3
angs = np.hstack([tth_eta, np.zeros((len(tth_eta), 1))])
xy_det = gvecToDetectorXY(
anglesToGVec(angs, bHat_l=self.bvec, eHat_l=self.evec),
self.rmat, rmat_s, rmat_c,
self.tvec, tvec_s, tvec_c,
beamVec=self.bvec)
return xy_det
def angles_to_cart(self, tth_eta):
"""
TODO: distortion
"""
rmat_s = rmat_c = ct.identity_3x3
tvec_s = tvec_c = ct.zeros_3
angs = np.hstack([tth_eta, np.zeros((len(tth_eta), 1))])
xy_det = gvecToDetectorXY(anglesToGVec(angs,
bHat_l=self.bvec,
eHat_l=self.evec),
self.rmat,
rmat_s,
rmat_c,
self.tvec,
tvec_s,
tvec_c,
beamVec=self.bvec)
return xy_det
def xy_of_angs(self, angs):
"""
Cartesion coordinates of vstacked (tth, eta) pairs
*) wrapper for transforms.anglesToGVec
"""
gVec_l = xf.anglesToGVec(angs,
self.bVec,
self.eVec,
rMat_s=None,
rMat_c=None)
xy = xf.gvecToDetectorXY(gVec_l,
self.rMat,
I3,
I3,
self.tVec,
self.tVec_s,
self.tVec_c,
distortion=self.distortion,
beamVec=self.bVec,
etaVec=self.eVec)
return xy
def make_reflection_patches(
instr_cfg,
tth_eta,
ang_pixel_size,
omega=None,
tth_tol=0.2,
eta_tol=1.0,
rMat_c=np.eye(3),
tVec_c=np.c_[0.0, 0.0, 0.0].T,
distortion=distortion,
npdiv=1,
quiet=False,
compute_areas_func=compute_areas,
):
"""
prototype function for making angular patches on a detector
panel_dims are [(xmin, ymin), (xmax, ymax)] in mm
pixel_pitch is [row_size, column_size] in mm
DISTORTION HANDING IS STILL A KLUDGE
patches are:
delta tth
d ------------- ... -------------
e | x | x | x | ... | x | x | x |
l ------------- ... -------------
t .
a .
.
e ------------- ... -------------
t | x | x | x | ... | x | x | x |
a ------------- ... -------------
"""
npts = len(tth_eta)
# detector frame
rMat_d = xfcapi.makeDetectorRotMat(instr_cfg["detector"]["transform"]["tilt_angles"])
tVec_d = np.r_[instr_cfg["detector"]["transform"]["t_vec_d"]]
pixel_size = instr_cfg["detector"]["pixels"]["size"]
frame_nrows = instr_cfg["detector"]["pixels"]["rows"]
frame_ncols = instr_cfg["detector"]["pixels"]["columns"]
panel_dims = (
-0.5 * np.r_[frame_ncols * pixel_size[1], frame_nrows * pixel_size[0]],
0.5 * np.r_[frame_ncols * pixel_size[1], frame_nrows * pixel_size[0]],
)
row_edges = np.arange(frame_nrows + 1)[::-1] * pixel_size[1] + panel_dims[0][1]
col_edges = np.arange(frame_ncols + 1) * pixel_size[0] + panel_dims[0][0]
# sample frame
chi = instr_cfg["oscillation_stage"]["chi"]
tVec_s = np.r_[instr_cfg["oscillation_stage"]["t_vec_s"]]
# data to loop
# ...WOULD IT BE CHEAPER TO CARRY ZEROS OR USE CONDITIONAL?
if omega is None:
full_angs = np.hstack([tth_eta, np.zeros((npts, 1))])
else:
full_angs = np.hstack([tth_eta, omega.reshape(npts, 1)])
patches = []
for angs, pix in zip(full_angs, ang_pixel_size):
# need to get angular pixel size
rMat_s = xfcapi.makeOscillRotMat([chi, angs[2]])
ndiv_tth = npdiv * np.ceil(tth_tol / np.degrees(pix[0]))
ndiv_eta = npdiv * np.ceil(eta_tol / np.degrees(pix[1]))
tth_del = np.arange(0, ndiv_tth + 1) * tth_tol / float(ndiv_tth) - 0.5 * tth_tol
eta_del = np.arange(0, ndiv_eta + 1) * eta_tol / float(ndiv_eta) - 0.5 * eta_tol
# store dimensions for convenience
# * etas and tths are bin vertices, ome is already centers
sdims = [len(eta_del) - 1, len(tth_del) - 1]
# meshgrid args are (cols, rows), a.k.a (fast, slow)
m_tth, m_eta = np.meshgrid(tth_del, eta_del)
npts_patch = m_tth.size
# calculate the patch XY coords from the (tth, eta) angles
# * will CHEAT and ignore the small perturbation the different
# omega angle values causes and simply use the central value
gVec_angs_vtx = np.tile(angs, (npts_patch, 1)) + np.radians(
np.vstack([m_tth.flatten(), m_eta.flatten(), np.zeros(npts_patch)]).T
)
# will need this later
rMat_s = xfcapi.makeOscillRotMat([chi, angs[2]])
# FOR ANGULAR MESH
conn = gutil.cellConnectivity(sdims[0], sdims[1], origin="ll")
gVec_c = xf.anglesToGVec(gVec_angs_vtx, xf.bVec_ref, xf.eta_ref, rMat_s=rMat_s, rMat_c=rMat_c)
xy_eval_vtx = xfcapi.gvecToDetectorXY(gVec_c.T, rMat_d, rMat_s, rMat_c, tVec_d, tVec_s, tVec_c)
if distortion is not None and len(distortion) == 2:
xy_eval_vtx = distortion[0](xy_eval_vtx, distortion[1], invert=True)
pass
areas = compute_areas_func(xy_eval_vtx, conn)
# EVALUATION POINTS
# * for lack of a better option will use centroids
tth_eta_cen = gutil.cellCentroids(np.atleast_2d(gVec_angs_vtx[:, :2]), conn)
gVec_angs = np.hstack([tth_eta_cen, np.tile(angs[2], (len(tth_eta_cen), 1))])
gVec_c = xf.anglesToGVec(gVec_angs, xf.bVec_ref, xf.eta_ref, rMat_s=rMat_s, rMat_c=rMat_c)
xy_eval = xfcapi.gvecToDetectorXY(gVec_c.T, rMat_d, rMat_s, rMat_c, tVec_d, tVec_s, tVec_c)
if distortion is not None and len(distortion) == 2:
xy_eval = distortion[0](xy_eval, distortion[1], invert=True)
pass
row_indices = gutil.cellIndices(row_edges, xy_eval[:, 1])
col_indices = gutil.cellIndices(col_edges, xy_eval[:, 0])
patches.append(
(
(gVec_angs_vtx[:, 0].reshape(m_tth.shape), gVec_angs_vtx[:, 1].reshape(m_tth.shape)),
(xy_eval_vtx[:, 0].reshape(m_tth.shape), xy_eval_vtx[:, 1].reshape(m_tth.shape)),
conn,
areas.reshape(sdims[0], sdims[1]),
(row_indices.reshape(sdims[0], sdims[1]), col_indices.reshape(sdims[0], sdims[1])),
)
)
pass
return patches
def objFuncFitGrain(gFit, gFull, gFlag,
detectorParams,
xyo_det, hkls_idx, bMat, wavelength,
bVec, eVec,
dFunc, dParams,
omePeriod,
simOnly=False, returnScalarValue=returnScalarValue):
"""
gFull[0] = expMap_c[0]
gFull[1] = expMap_c[1]
gFull[2] = expMap_c[2]
gFull[3] = tVec_c[0]
gFull[4] = tVec_c[1]
gFull[5] = tVec_c[2]
gFull[6] = vInv_MV[0]
gFull[7] = vInv_MV[1]
gFull[8] = vInv_MV[2]
gFull[9] = vInv_MV[3]
gFull[10] = vInv_MV[4]
gFull[11] = vInv_MV[5]
detectorParams[0] = tiltAngles[0]
detectorParams[1] = tiltAngles[1]
detectorParams[2] = tiltAngles[2]
detectorParams[3] = tVec_d[0]
detectorParams[4] = tVec_d[1]
detectorParams[5] = tVec_d[2]
detectorParams[6] = chi
detectorParams[7] = tVec_s[0]
detectorParams[8] = tVec_s[1]
detectorParams[9] = tVec_s[2]
"""
npts = len(xyo_det)
gFull[gFlag] = gFit
xy_unwarped = dFunc(xyo_det[:, :2], dParams)
rMat_d = xfcapi.makeDetectorRotMat(detectorParams[:3])
tVec_d = detectorParams[3:6].reshape(3, 1)
chi = detectorParams[6]
tVec_s = detectorParams[7:10].reshape(3, 1)
rMat_c = xfcapi.makeRotMatOfExpMap(gFull[:3])
tVec_c = gFull[3:6].reshape(3, 1)
vInv_s = gFull[6:]
vMat_s = mutil.vecMVToSymm(vInv_s) # NOTE: Inverse of V from F = V * R
gVec_c = np.dot(bMat, hkls_idx) # gVecs with magnitudes in CRYSTAL frame
gVec_s = np.dot(vMat_s, np.dot(rMat_c, gVec_c)) # stretched gVecs in SAMPLE frame
gHat_c = mutil.unitVector(
np.dot(rMat_c.T, gVec_s)) # unit reciprocal lattice vectors in CRYSTAL frame
match_omes, calc_omes = matchOmegas(xyo_det, hkls_idx, chi, rMat_c, bMat, wavelength,
vInv=vInv_s, beamVec=bVec, etaVec=eVec,
omePeriod=omePeriod)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
print "infeasible pFull"
# return values
if simOnly:
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
diff_vecs_xy = calc_xy - xy_unwarped[:, :2]
diff_ome = xf.angularDifference( calc_omes, xyo_det[:, 2] )
retval = mutil.rowNorm(
np.hstack([diff_vecs_xy,
diff_ome.reshape(npts, 1)
]) ).flatten()
if returnScalarValue:
retval = sum( retval )
return retval
def pull_spots(self, plane_data, grain_params,
imgser_dict,
tth_tol=0.25, eta_tol=1., ome_tol=1.,
npdiv=2, threshold=10,
eta_ranges=[(-np.pi, np.pi), ],
ome_period=(-np.pi, np.pi),
dirname='results', filename=None, output_format='text',
save_spot_list=False,
quiet=True, check_only=False,
interp='nearest'):
"""
Exctract reflection info from a rotation series encoded as an
OmegaImageseries object
"""
# grain parameters
rMat_c = makeRotMatOfExpMap(grain_params[:3])
tVec_c = grain_params[3:6]
# grab omega ranges from first imageseries
#
# WARNING: all imageseries AND all wedges within are assumed to have
# the same omega values; put in a check that they are all the same???
oims0 = imgser_dict[imgser_dict.keys()[0]]
ome_ranges = [np.radians([i['ostart'], i['ostop']])
for i in oims0.omegawedges.wedges]
# delta omega in DEGREES grabbed from first imageseries in the dict
delta_ome = oims0.omega[0, 1] - oims0.omega[0, 0]
# make omega grid for frame expansion around reference frame
# in DEGREES
ndiv_ome, ome_del = make_tolerance_grid(
delta_ome, ome_tol, 1, adjust_window=True,
)
# generate structuring element for connected component labeling
if ndiv_ome == 1:
label_struct = ndimage.generate_binary_structure(2, 2)
else:
label_struct = ndimage.generate_binary_structure(3, 3)
# simulate rotation series
sim_results = self.simulate_rotation_series(
plane_data, [grain_params, ],
eta_ranges=eta_ranges,
ome_ranges=ome_ranges,
ome_period=ome_period)
# patch vertex generator (global for instrument)
tol_vec = 0.5*np.radians(
[-tth_tol, -eta_tol,
-tth_tol, eta_tol,
tth_tol, eta_tol,
tth_tol, -eta_tol])
# prepare output if requested
if filename is not None and output_format.lower() == 'hdf5':
this_filename = os.path.join(dirname, filename)
writer = io.GrainDataWriter_h5(
os.path.join(dirname, filename),
self.write_config(), grain_params)
# =====================================================================
# LOOP OVER PANELS
# =====================================================================
iRefl = 0
compl = []
output = dict.fromkeys(self.detectors)
for detector_id in self.detectors:
# initialize text-based output writer
if filename is not None and output_format.lower() == 'text':
output_dir = os.path.join(
dirname, detector_id
)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
this_filename = os.path.join(
output_dir, filename
)
writer = io.PatchDataWriter(this_filename)
# grab panel
panel = self.detectors[detector_id]
instr_cfg = panel.config_dict(self.chi, self.tvec)
native_area = panel.pixel_area # pixel ref area
# pull out the OmegaImageSeries for this panel from input dict
ome_imgser = imgser_dict[detector_id]
# extract simulation results
sim_results_p = sim_results[detector_id]
hkl_ids = sim_results_p[0][0]
hkls_p = sim_results_p[1][0]
ang_centers = sim_results_p[2][0]
xy_centers = sim_results_p[3][0]
ang_pixel_size = sim_results_p[4][0]
# now verify that full patch falls on detector...
# ???: strictly necessary?
#
# patch vertex array from sim
nangs = len(ang_centers)
patch_vertices = (
np.tile(ang_centers[:, :2], (1, 4)) +
np.tile(tol_vec, (nangs, 1))
).reshape(4*nangs, 2)
ome_dupl = np.tile(
ang_centers[:, 2], (4, 1)
).T.reshape(len(patch_vertices), 1)
# find vertices that all fall on the panel
det_xy, _ = xrdutil._project_on_detector_plane(
np.hstack([patch_vertices, ome_dupl]),
panel.rmat, rMat_c, self.chi,
panel.tvec, tVec_c, self.tvec,
panel.distortion)
_, on_panel = panel.clip_to_panel(det_xy, buffer_edges=True)
# all vertices must be on...
patch_is_on = np.all(on_panel.reshape(nangs, 4), axis=1)
patch_xys = det_xy.reshape(nangs, 4, 2)[patch_is_on]
# re-filter...
hkl_ids = hkl_ids[patch_is_on]
hkls_p = hkls_p[patch_is_on, :]
ang_centers = ang_centers[patch_is_on, :]
xy_centers = xy_centers[patch_is_on, :]
ang_pixel_size = ang_pixel_size[patch_is_on, :]
# TODO: add polygon testing right here!
# done <JVB 06/21/16>
if check_only:
patch_output = []
for i_pt, angs in enumerate(ang_centers):
# the evaluation omegas;
# expand about the central value using tol vector
ome_eval = np.degrees(angs[2]) + ome_del
# ...vectorize the omega_to_frame function to avoid loop?
frame_indices = [
ome_imgser.omega_to_frame(ome)[0] for ome in ome_eval
]
if -1 in frame_indices:
if not quiet:
msg = """
window for (%d%d%d) falls outside omega range
""" % tuple(hkls_p[i_pt, :])
print(msg)
continue
else:
these_vertices = patch_xys[i_pt]
ijs = panel.cartToPixel(these_vertices)
ii, jj = polygon(ijs[:, 0], ijs[:, 1])
contains_signal = False
for i_frame in frame_indices:
contains_signal = contains_signal or np.any(
ome_imgser[i_frame][ii, jj] > threshold
)
compl.append(contains_signal)
patch_output.append((ii, jj, frame_indices))
else:
# make the tth,eta patches for interpolation
patches = xrdutil.make_reflection_patches(
instr_cfg, ang_centers[:, :2], ang_pixel_size,
omega=ang_centers[:, 2],
tth_tol=tth_tol, eta_tol=eta_tol,
rMat_c=rMat_c, tVec_c=tVec_c,
distortion=panel.distortion,
npdiv=npdiv, quiet=True,
beamVec=self.beam_vector)
# GRAND LOOP over reflections for this panel
patch_output = []
for i_pt, patch in enumerate(patches):
# strip relevant objects out of current patch
vtx_angs, vtx_xy, conn, areas, xy_eval, ijs = patch
prows, pcols = areas.shape
nrm_fac = areas/float(native_area)
nrm_fac = nrm_fac / np.min(nrm_fac)
# grab hkl info
hkl = hkls_p[i_pt, :]
hkl_id = hkl_ids[i_pt]
# edge arrays
tth_edges = vtx_angs[0][0, :]
delta_tth = tth_edges[1] - tth_edges[0]
eta_edges = vtx_angs[1][:, 0]
delta_eta = eta_edges[1] - eta_edges[0]
# need to reshape eval pts for interpolation
xy_eval = np.vstack([xy_eval[0].flatten(),
xy_eval[1].flatten()]).T
# the evaluation omegas;
# expand about the central value using tol vector
ome_eval = np.degrees(ang_centers[i_pt, 2]) + ome_del
# ???: vectorize the omega_to_frame function to avoid loop?
frame_indices = [
ome_imgser.omega_to_frame(ome)[0] for ome in ome_eval
]
if -1 in frame_indices:
if not quiet:
msg = """
window for (%d%d%d) falls outside omega range
""" % tuple(hkl)
print(msg)
continue
else:
# initialize spot data parameters
# !!! maybe change these to nan to not f**k up writer
peak_id = -999
sum_int = None
max_int = None
meas_angs = None
meas_xy = None
# quick check for intensity
contains_signal = False
patch_data_raw = []
for i_frame in frame_indices:
tmp = ome_imgser[i_frame][ijs[0], ijs[1]]
contains_signal = contains_signal or np.any(
tmp > threshold
)
patch_data_raw.append(tmp)
pass
patch_data_raw = np.stack(patch_data_raw, axis=0)
compl.append(contains_signal)
if contains_signal:
# initialize patch data array for intensities
if interp.lower() == 'bilinear':
patch_data = np.zeros(
(len(frame_indices), prows, pcols))
for i, i_frame in enumerate(frame_indices):
patch_data[i] = \
panel.interpolate_bilinear(
xy_eval,
ome_imgser[i_frame],
pad_with_nans=False
).reshape(prows, pcols) # * nrm_fac
elif interp.lower() == 'nearest':
patch_data = patch_data_raw # * nrm_fac
else:
msg = "interpolation option " + \
"'%s' not understood"
raise(RuntimeError, msg % interp)
# now have interpolated patch data...
labels, num_peaks = ndimage.label(
patch_data > threshold, structure=label_struct
)
slabels = np.arange(1, num_peaks + 1)
if num_peaks > 0:
peak_id = iRefl
coms = np.array(
ndimage.center_of_mass(
patch_data,
labels=labels,
index=slabels
)
)
if num_peaks > 1:
center = np.r_[patch_data.shape]*0.5
center_t = np.tile(center, (num_peaks, 1))
com_diff = coms - center_t
closest_peak_idx = np.argmin(
np.sum(com_diff**2, axis=1)
)
else:
closest_peak_idx = 0
pass # end multipeak conditional
coms = coms[closest_peak_idx]
# meas_omes = \
# ome_edges[0] + (0.5 + coms[0])*delta_ome
meas_omes = \
ome_eval[0] + coms[0]*delta_ome
meas_angs = np.hstack(
[tth_edges[0] + (0.5 + coms[2])*delta_tth,
eta_edges[0] + (0.5 + coms[1])*delta_eta,
mapAngle(
np.radians(meas_omes), ome_period
)
]
)
# intensities
# - summed is 'integrated' over interpolated
# data
# - max is max of raw input data
sum_int = np.sum(
patch_data[
labels == slabels[closest_peak_idx]
]
)
max_int = np.max(
patch_data_raw[
labels == slabels[closest_peak_idx]
]
)
# ???: Should this only use labeled pixels?
# Those are segmented from interpolated data,
# not raw; likely ok in most cases.
# need MEASURED xy coords
gvec_c = anglesToGVec(
meas_angs,
chi=self.chi,
rMat_c=rMat_c,
bHat_l=self.beam_vector)
rMat_s = makeOscillRotMat(
[self.chi, meas_angs[2]]
)
meas_xy = gvecToDetectorXY(
gvec_c,
panel.rmat, rMat_s, rMat_c,
panel.tvec, self.tvec, tVec_c,
beamVec=self.beam_vector)
if panel.distortion is not None:
# FIXME: distortion handling
meas_xy = panel.distortion[0](
np.atleast_2d(meas_xy),
panel.distortion[1],
invert=True).flatten()
pass
# FIXME: why is this suddenly necessary???
meas_xy = meas_xy.squeeze()
pass # end num_peaks > 0
else:
patch_data = patch_data_raw
pass # end contains_signal
# write output
if filename is not None:
if output_format.lower() == 'text':
writer.dump_patch(
peak_id, hkl_id, hkl, sum_int, max_int,
ang_centers[i_pt], meas_angs,
xy_centers[i_pt], meas_xy)
elif output_format.lower() == 'hdf5':
xyc_arr = xy_eval.reshape(
prows, pcols, 2
).transpose(2, 0, 1)
writer.dump_patch(
detector_id, iRefl, peak_id, hkl_id, hkl,
tth_edges, eta_edges, np.radians(ome_eval),
xyc_arr, ijs, frame_indices, patch_data,
ang_centers[i_pt], xy_centers[i_pt],
meas_angs, meas_xy)
pass # end conditional on write output
pass # end conditional on check only
patch_output.append([
peak_id, hkl_id, hkl, sum_int, max_int,
ang_centers[i_pt], meas_angs, meas_xy,
])
iRefl += 1
pass # end patch conditional
pass # end patch loop
output[detector_id] = patch_output
if filename is not None and output_format.lower() == 'text':
writer.close()
pass # end detector loop
if filename is not None and output_format.lower() == 'hdf5':
writer.close()
return compl, output
def objFuncSX(pFit, pFull, pFlag, dFunc, dFlag,
xyo_det, hkls_idx, bMat, vInv,
bVec, eVec, omePeriod,
simOnly=False, return_value_flag=return_value_flag):
"""
"""
npts = len(xyo_det)
refineFlag = np.array(np.hstack([pFlag, dFlag]), dtype=bool)
print refineFlag
# pFull[refineFlag] = pFit/scl[refineFlag]
pFull[refineFlag] = pFit
if dFunc is not None:
dParams = pFull[-len(dFlag):]
xys = dFunc(xyo_det[:, :2], dParams)
else:
xys = xyo_det[:, :2]
# detector quantities
wavelength = pFull[0]
rMat_d = xf.makeDetectorRotMat(pFull[1:4])
tVec_d = pFull[4:7].reshape(3, 1)
# sample quantities
chi = pFull[7]
tVec_s = pFull[8:11].reshape(3, 1)
# crystal quantities
rMat_c = xf.makeRotMatOfExpMap(pFull[11:14])
tVec_c = pFull[14:17].reshape(3, 1)
# stretch tensor comp matrix from MV notation in SAMPLE frame
vMat_s = mutil.vecMVToSymm(vInv)
# g-vectors:
# 1. calculate full g-vector components in CRYSTAL frame from B
# 2. rotate into SAMPLE frame and apply stretch
# 3. rotate back into CRYSTAL frame and normalize to unit magnitude
# IDEA: make a function for this sequence of operations with option for
# choosing ouput frame (i.e. CRYSTAL vs SAMPLE vs LAB)
gVec_c = np.dot(bMat, hkls_idx)
gVec_s = np.dot(vMat_s, np.dot(rMat_c, gVec_c))
gHat_c = mutil.unitVector(np.dot(rMat_c.T, gVec_s))
match_omes, calc_omes = matchOmegas(
xyo_det, hkls_idx, chi, rMat_c, bMat, wavelength,
vInv=vInv, beamVec=bVec, etaVec=eVec, omePeriod=omePeriod)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
raise RuntimeError(
"infeasible pFull: may want to scale" +
"back finite difference step size")
# return values
if simOnly:
# return simulated values
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
# return residual vector
# IDEA: try angles instead of xys?
diff_vecs_xy = calc_xy - xys[:, :2]
diff_ome = xf.angularDifference(calc_omes, xyo_det[:, 2])
retval = np.hstack([diff_vecs_xy,
diff_ome.reshape(npts, 1)
]).flatten()
if return_value_flag == 1:
# return scalar sum of squared residuals
retval = sum(abs(retval))
elif return_value_flag == 2:
# return DOF-normalized chisq
# TODO: check this calculation
denom = npts - len(pFit) - 1.
if denom != 0:
nu_fac = 1. / denom
else:
nu_fac = 1.
nu_fac = 1 / (npts - len(pFit) - 1.)
retval = nu_fac * sum(retval**2)
return retval
tth_vec = tth_size * (np.arange(ntth) - 0.5 * ntth - 1) + tth0
eta_vec = eta_size * (np.arange(neta) - 0.5 * neta - 1) + eta0
angpts = np.meshgrid(eta_vec, tth_vec, indexing='ij')
gpts = xfc.anglesToGVec(np.vstack([
np.radians(angpts[1].flatten()),
np.radians(angpts[0].flatten()),
np.zeros(neta * ntth)
]).T,
bHat_l=d.bvec)
xypts = xfc.gvecToDetectorXY(gpts,
d.rmat,
np.eye(3),
np.eye(3),
d.tvec,
np.zeros(3),
np.zeros(3),
beamVec=d.bvec)
img2 = d.interpolate_bilinear(xypts, average_frame).reshape(neta, ntth)
img3 = copy.deepcopy(img2)
borders = np.isnan(img2)
img2[borders] = 0.
img3[borders] = 0.
img3 += np.min(img3) + 1
img3 = np.log(img3)
img3[borders] = np.nan
extent = (np.min(angpts[1]), np.max(angpts[1]), np.min(angpts[0]),
np.max(angpts[0]))
except (KeyError):
distortion = None
# for defining patches
delta_eta = 0.5
neta = int(360 / float(delta_eta))
eta = np.radians(delta_eta * np.linspace(0, neta - 1, num=neta))
angs = [
np.vstack([i * np.ones(neta), eta, np.zeros(neta)]) for i in pd.getTTh()
]
# need xy coords and pixel sizes
gVec_ring_l = xf.anglesToGVec(angs[0].T, xf.bVec_ref, xf.eta_ref)
xydet_ring = xfcapi.gvecToDetectorXY(gVec_ring_l.T, rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c)
if distortion is not None:
det_xy = distortion[0](xydet_ring, distortion[1], invert=True)
ang_ps = angularPixelSize(det_xy,
pixel_pitch,
rMat_d,
rMat_s,
tVec_d,
tVec_s,
tVec_c,
distortion=distortion)
def compute_areas(xy_eval_vtx, conn):
areas = np.zeros(len(conn))
def simulate_laue_pattern(self,
crystal_data,
minEnergy=5.,
maxEnergy=35.,
rmat_s=None,
tvec_s=None,
grain_params=None,
beam_vec=None):
"""
"""
if isinstance(crystal_data, PlaneData):
plane_data = crystal_data
# grab the expanded list of hkls from plane_data
hkls = np.hstack(plane_data.getSymHKLs())
# and the unit plane normals (G-vectors) in CRYSTAL FRAME
gvec_c = np.dot(plane_data.latVecOps['B'], hkls)
elif len(crystal_data) == 2:
# !!! should clean this up
hkls = np.array(crystal_data[0])
bmat = crystal_data[1]
gvec_c = np.dot(bmat, hkls)
else:
raise (RuntimeError, 'argument list not understood')
nhkls_tot = hkls.shape[1]
# parse energy ranges
# TODO: allow for spectrum parsing
multipleEnergyRanges = False
if hasattr(maxEnergy, '__len__'):
assert len(maxEnergy) == len(minEnergy), \
'energy cutoff ranges must have the same length'
multipleEnergyRanges = True
lmin = []
lmax = []
for i in range(len(maxEnergy)):
lmin.append(ct.keVToAngstrom(maxEnergy[i]))
lmax.append(ct.keVToAngstrom(minEnergy[i]))
else:
lmin = ct.keVToAngstrom(maxEnergy)
lmax = ct.keVToAngstrom(minEnergy)
# parse grain parameters kwarg
if grain_params is None:
grain_params = np.atleast_2d(
np.hstack([np.zeros(6), ct.identity_6x1]))
n_grains = len(grain_params)
# sample rotation
if rmat_s is None:
rmat_s = ct.identity_3x3
# dummy translation vector... make input
if tvec_s is None:
tvec_s = ct.zeros_3
# beam vector
if beam_vec is None:
beam_vec = ct.beam_vec
# =========================================================================
# LOOP OVER GRAINS
# =========================================================================
# pre-allocate output arrays
xy_det = np.nan * np.ones((n_grains, nhkls_tot, 2))
hkls_in = np.nan * np.ones((n_grains, 3, nhkls_tot))
angles = np.nan * np.ones((n_grains, nhkls_tot, 2))
dspacing = np.nan * np.ones((n_grains, nhkls_tot))
energy = np.nan * np.ones((n_grains, nhkls_tot))
for iG, gp in enumerate(grain_params):
rmat_c = makeRotMatOfExpMap(gp[:3])
tvec_c = gp[3:6].reshape(3, 1)
vInv_s = mutil.vecMVToSymm(gp[6:].reshape(6, 1))
# stretch them: V^(-1) * R * Gc
gvec_s_str = np.dot(vInv_s, np.dot(rmat_c, gvec_c))
ghat_c_str = mutil.unitVector(np.dot(rmat_c.T, gvec_s_str))
# project
dpts = gvecToDetectorXY(ghat_c_str.T,
self.rmat,
rmat_s,
rmat_c,
self.tvec,
tvec_s,
tvec_c,
beamVec=beam_vec)
# check intersections with detector plane
canIntersect = ~np.isnan(dpts[:, 0])
npts_in = sum(canIntersect)
if np.any(canIntersect):
dpts = dpts[canIntersect, :].reshape(npts_in, 2)
dhkl = hkls[:, canIntersect].reshape(3, npts_in)
# back to angles
tth_eta, gvec_l = detectorXYToGvec(dpts,
self.rmat,
rmat_s,
self.tvec,
tvec_s,
tvec_c,
beamVec=beam_vec)
tth_eta = np.vstack(tth_eta).T
# warp measured points
if self.distortion is not None:
if len(self.distortion) == 2:
dpts = self.distortion[0](dpts,
self.distortion[1],
invert=True)
else:
raise (RuntimeError,
"something is wrong with the distortion")
# plane spacings and energies
dsp = 1. / rowNorm(gvec_s_str[:, canIntersect].T)
wlen = 2 * dsp * np.sin(0.5 * tth_eta[:, 0])
# clip to detector panel
_, on_panel = self.clip_to_panel(dpts, buffer_edges=True)
if multipleEnergyRanges:
validEnergy = np.zeros(len(wlen), dtype=bool)
for i in range(len(lmin)):
in_energy_range = np.logical_and(
wlen >= lmin[i], wlen <= lmax[i])
validEnergy = validEnergy | in_energy_range
pass
else:
validEnergy = np.logical_and(wlen >= lmin, wlen <= lmax)
pass
# index for valid reflections
keepers = np.where(np.logical_and(on_panel, validEnergy))[0]
# assign output arrays
xy_det[iG][keepers, :] = dpts[keepers, :]
hkls_in[iG][:, keepers] = dhkl[:, keepers]
angles[iG][keepers, :] = tth_eta[keepers, :]
dspacing[iG, keepers] = dsp[keepers]
energy[iG, keepers] = ct.keVToAngstrom(wlen[keepers])
pass # close conditional on valids
pass # close loop on grains
return xy_det, hkls_in, angles, dspacing, energy
dparams = instr_cfg["detector"]["distortion"]["parameters"]
distortion = (xf.dFunc_ref, dparams)
except (KeyError):
distortion = None
# for defining patches
delta_eta = 0.5
neta = int(360 / float(delta_eta))
eta = np.radians(delta_eta * np.linspace(0, neta - 1, num=neta))
angs = [np.vstack([i * np.ones(neta), eta, np.zeros(neta)]) for i in pd.getTTh()]
# need xy coords and pixel sizes
gVec_ring_l = xf.anglesToGVec(angs[0].T, xf.bVec_ref, xf.eta_ref)
xydet_ring = xfcapi.gvecToDetectorXY(gVec_ring_l.T, rMat_d, rMat_s, rMat_c, tVec_d, tVec_s, tVec_c)
if distortion is not None:
det_xy = distortion[0](xydet_ring, distortion[1], invert=True)
ang_ps = angularPixelSize(det_xy, pixel_pitch, rMat_d, rMat_s, tVec_d, tVec_s, tVec_c, distortion=distortion)
def compute_areas(xy_eval_vtx, conn):
areas = np.zeros(len(conn))
for i in range(len(conn)):
polygon = [[xy_eval_vtx[conn[i, j], 0], xy_eval_vtx[conn[i, j], 1]] for j in range(4)]
areas[i] = gutil.computeArea(polygon)
return areas
@numba.jit
def simulate_laue_pattern(self, crystal_data,
minEnergy=5., maxEnergy=35.,
rmat_s=None, tvec_s=None,
grain_params=None,
beam_vec=None):
"""
"""
if isinstance(crystal_data, PlaneData):
plane_data = crystal_data
# grab the expanded list of hkls from plane_data
hkls = np.hstack(plane_data.getSymHKLs())
# and the unit plane normals (G-vectors) in CRYSTAL FRAME
gvec_c = np.dot(plane_data.latVecOps['B'], hkls)
elif len(crystal_data) == 2:
# !!! should clean this up
hkls = np.array(crystal_data[0])
bmat = crystal_data[1]
gvec_c = np.dot(bmat, hkls)
else:
raise(RuntimeError, 'argument list not understood')
nhkls_tot = hkls.shape[1]
# parse energy ranges
# TODO: allow for spectrum parsing
multipleEnergyRanges = False
if hasattr(maxEnergy, '__len__'):
assert len(maxEnergy) == len(minEnergy), \
'energy cutoff ranges must have the same length'
multipleEnergyRanges = True
lmin = []
lmax = []
for i in range(len(maxEnergy)):
lmin.append(ct.keVToAngstrom(maxEnergy[i]))
lmax.append(ct.keVToAngstrom(minEnergy[i]))
else:
lmin = ct.keVToAngstrom(maxEnergy)
lmax = ct.keVToAngstrom(minEnergy)
# parse grain parameters kwarg
if grain_params is None:
grain_params = np.atleast_2d(
np.hstack([np.zeros(6), ct.identity_6x1])
)
n_grains = len(grain_params)
# sample rotation
if rmat_s is None:
rmat_s = ct.identity_3x3
# dummy translation vector... make input
if tvec_s is None:
tvec_s = ct.zeros_3
# beam vector
if beam_vec is None:
beam_vec = ct.beam_vec
# =========================================================================
# LOOP OVER GRAINS
# =========================================================================
# pre-allocate output arrays
xy_det = np.nan*np.ones((n_grains, nhkls_tot, 2))
hkls_in = np.nan*np.ones((n_grains, 3, nhkls_tot))
angles = np.nan*np.ones((n_grains, nhkls_tot, 2))
dspacing = np.nan*np.ones((n_grains, nhkls_tot))
energy = np.nan*np.ones((n_grains, nhkls_tot))
for iG, gp in enumerate(grain_params):
rmat_c = makeRotMatOfExpMap(gp[:3])
tvec_c = gp[3:6].reshape(3, 1)
vInv_s = mutil.vecMVToSymm(gp[6:].reshape(6, 1))
# stretch them: V^(-1) * R * Gc
gvec_s_str = np.dot(vInv_s, np.dot(rmat_c, gvec_c))
ghat_c_str = mutil.unitVector(np.dot(rmat_c.T, gvec_s_str))
# project
dpts = gvecToDetectorXY(ghat_c_str.T,
self.rmat, rmat_s, rmat_c,
self.tvec, tvec_s, tvec_c,
beamVec=beam_vec)
# check intersections with detector plane
canIntersect = ~np.isnan(dpts[:, 0])
npts_in = sum(canIntersect)
if np.any(canIntersect):
dpts = dpts[canIntersect, :].reshape(npts_in, 2)
dhkl = hkls[:, canIntersect].reshape(3, npts_in)
# back to angles
tth_eta, gvec_l = detectorXYToGvec(
dpts,
self.rmat, rmat_s,
self.tvec, tvec_s, tvec_c,
beamVec=beam_vec)
tth_eta = np.vstack(tth_eta).T
# warp measured points
if self.distortion is not None:
if len(self.distortion) == 2:
dpts = self.distortion[0](
dpts, self.distortion[1],
invert=True)
else:
raise(RuntimeError,
"something is wrong with the distortion")
# plane spacings and energies
dsp = 1. / rowNorm(gvec_s_str[:, canIntersect].T)
wlen = 2*dsp*np.sin(0.5*tth_eta[:, 0])
# clip to detector panel
_, on_panel = self.clip_to_panel(dpts, buffer_edges=True)
if multipleEnergyRanges:
validEnergy = np.zeros(len(wlen), dtype=bool)
for i in range(len(lmin)):
in_energy_range = np.logical_and(
wlen >= lmin[i],
wlen <= lmax[i])
validEnergy = validEnergy | in_energy_range
pass
else:
validEnergy = np.logical_and(wlen >= lmin, wlen <= lmax)
pass
# index for valid reflections
keepers = np.where(np.logical_and(on_panel, validEnergy))[0]
# assign output arrays
xy_det[iG][keepers, :] = dpts[keepers, :]
hkls_in[iG][:, keepers] = dhkl[:, keepers]
angles[iG][keepers, :] = tth_eta[keepers, :]
dspacing[iG, keepers] = dsp[keepers]
energy[iG, keepers] = ct.keVToAngstrom(wlen[keepers])
pass # close conditional on valids
pass # close loop on grains
return xy_det, hkls_in, angles, dspacing, energy
def make_powder_rings(
self, pd, merge_hkls=False, delta_tth=None,
delta_eta=10., eta_period=None,
rmat_s=ct.identity_3x3, tvec_s=ct.zeros_3,
tvec_c=ct.zeros_3, full_output=False):
"""
"""
# in case you want to give it tth angles directly
if hasattr(pd, '__len__'):
tth = np.array(pd).flatten()
if delta_tth is None:
raise RuntimeError(
"If supplying a 2theta list as first arg, "
+ "must supply a delta_tth")
sector_vertices = np.tile(
0.5*np.radians([-delta_tth, -delta_eta,
-delta_tth, delta_eta,
delta_tth, delta_eta,
delta_tth, -delta_eta,
0.0, 0.0]), (len(tth), 1)
)
else:
# Okay, we have a PlaneData object
pd = PlaneData.makeNew(pd) # make a copy to munge
if delta_tth is not None:
pd.tThWidth = np.radians(delta_tth)
else:
delta_tth = np.degrees(pd.tThWidth)
# conversions, meh...
del_eta = np.radians(delta_eta)
# do merging if asked
if merge_hkls:
_, tth_ranges = pd.getMergedRanges()
tth = np.array([0.5*sum(i) for i in tth_ranges])
else:
tth_ranges = pd.getTThRanges()
tth = pd.getTTh()
tth_pm = tth_ranges - np.tile(tth, (2, 1)).T
sector_vertices = np.vstack(
[[i[0], -del_eta,
i[0], del_eta,
i[1], del_eta,
i[1], -del_eta,
0.0, 0.0]
for i in tth_pm])
# for generating rings
if eta_period is None:
eta_period = (-np.pi, np.pi)
neta = int(360./float(delta_eta))
eta = mapAngle(
np.radians(delta_eta*(np.linspace(0, neta - 1, num=neta) + 0.5)) +
eta_period[0], eta_period
)
angs = [np.vstack([i*np.ones(neta), eta, np.zeros(neta)]) for i in tth]
# need xy coords and pixel sizes
valid_ang = []
valid_xy = []
map_indices = []
npp = 5 # [ll, ul, ur, lr, center]
for i_ring in range(len(angs)):
# expand angles to patch vertices
these_angs = angs[i_ring].T
patch_vertices = (
np.tile(these_angs[:, :2], (1, npp))
+ np.tile(sector_vertices[i_ring], (neta, 1))
).reshape(npp*neta, 2)
# duplicate ome array
ome_dupl = np.tile(
these_angs[:, 2], (npp, 1)
).T.reshape(npp*neta, 1)
# find vertices that all fall on the panel
gVec_ring_l = anglesToGVec(
np.hstack([patch_vertices, ome_dupl]),
bHat_l=self.bvec)
all_xy = gvecToDetectorXY(
gVec_ring_l,
self.rmat, rmat_s, ct.identity_3x3,
self.tvec, tvec_s, tvec_c,
beamVec=self.bvec)
_, on_panel = self.clip_to_panel(all_xy)
# all vertices must be on...
patch_is_on = np.all(on_panel.reshape(neta, npp), axis=1)
patch_xys = all_xy.reshape(neta, 5, 2)[patch_is_on]
idx = np.where(patch_is_on)[0]
valid_ang.append(these_angs[patch_is_on, :2])
valid_xy.append(patch_xys[:, -1, :].squeeze())
map_indices.append(idx)
pass
# ??? is this option necessary?
if full_output:
return valid_ang, valid_xy, map_indices, eta
else:
return valid_ang, valid_xy
def objFuncFitGrain(gFit,
gFull,
gFlag,
detectorParams,
xyo_det,
hkls_idx,
bMat,
wavelength,
bVec,
eVec,
dFunc,
dParams,
omePeriod,
simOnly=False,
returnScalarValue=returnScalarValue):
"""
gFull[0] = expMap_c[0]
gFull[1] = expMap_c[1]
gFull[2] = expMap_c[2]
gFull[3] = tVec_c[0]
gFull[4] = tVec_c[1]
gFull[5] = tVec_c[2]
gFull[6] = vInv_MV[0]
gFull[7] = vInv_MV[1]
gFull[8] = vInv_MV[2]
gFull[9] = vInv_MV[3]
gFull[10] = vInv_MV[4]
gFull[11] = vInv_MV[5]
detectorParams[0] = tiltAngles[0]
detectorParams[1] = tiltAngles[1]
detectorParams[2] = tiltAngles[2]
detectorParams[3] = tVec_d[0]
detectorParams[4] = tVec_d[1]
detectorParams[5] = tVec_d[2]
detectorParams[6] = chi
detectorParams[7] = tVec_s[0]
detectorParams[8] = tVec_s[1]
detectorParams[9] = tVec_s[2]
"""
npts = len(xyo_det)
gFull[gFlag] = gFit
xy_unwarped = dFunc(xyo_det[:, :2], dParams)
rMat_d = xfcapi.makeDetectorRotMat(detectorParams[:3])
tVec_d = detectorParams[3:6].reshape(3, 1)
chi = detectorParams[6]
tVec_s = detectorParams[7:10].reshape(3, 1)
rMat_c = xfcapi.makeRotMatOfExpMap(gFull[:3])
tVec_c = gFull[3:6].reshape(3, 1)
vInv_s = gFull[6:]
vMat_s = mutil.vecMVToSymm(vInv_s) # NOTE: Inverse of V from F = V * R
gVec_c = np.dot(bMat, hkls_idx) # gVecs with magnitudes in CRYSTAL frame
gVec_s = np.dot(vMat_s, np.dot(rMat_c,
gVec_c)) # stretched gVecs in SAMPLE frame
gHat_c = mutil.unitVector(np.dot(
rMat_c.T, gVec_s)) # unit reciprocal lattice vectors in CRYSTAL frame
match_omes, calc_omes = matchOmegas(xyo_det,
hkls_idx,
chi,
rMat_c,
bMat,
wavelength,
vInv=vInv_s,
beamVec=bVec,
etaVec=eVec,
omePeriod=omePeriod)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d,
rMat_s,
rMat_c,
tVec_d,
tVec_s,
tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
print "infeasible pFull"
# return values
if simOnly:
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
diff_vecs_xy = calc_xy - xy_unwarped[:, :2]
diff_ome = xf.angularDifference(calc_omes, xyo_det[:, 2])
retval = np.hstack([diff_vecs_xy, diff_ome.reshape(npts, 1)]).flatten()
if returnScalarValue:
retval = sum(retval)
return retval
def pull_spots(self,
plane_data,
grain_params,
imgser_dict,
tth_tol=0.25,
eta_tol=1.,
ome_tol=1.,
npdiv=2,
threshold=10,
eta_ranges=[
(-np.pi, np.pi),
],
ome_period=(-np.pi, np.pi),
dirname='results',
filename=None,
output_format='text',
save_spot_list=False,
quiet=True,
check_only=False,
interp='nearest'):
"""
Exctract reflection info from a rotation series encoded as an
OmegaImageseries object
"""
# grain parameters
rMat_c = makeRotMatOfExpMap(grain_params[:3])
tVec_c = grain_params[3:6]
# grab omega ranges from first imageseries
#
# WARNING: all imageseries AND all wedges within are assumed to have
# the same omega values; put in a check that they are all the same???
oims0 = imgser_dict[imgser_dict.keys()[0]]
ome_ranges = [
np.radians([i['ostart'], i['ostop']])
for i in oims0.omegawedges.wedges
]
# delta omega in DEGREES grabbed from first imageseries in the dict
delta_ome = oims0.omega[0, 1] - oims0.omega[0, 0]
# make omega grid for frame expansion around reference frame
# in DEGREES
ndiv_ome, ome_del = make_tolerance_grid(
delta_ome,
ome_tol,
1,
adjust_window=True,
)
# generate structuring element for connected component labeling
if ndiv_ome == 1:
label_struct = ndimage.generate_binary_structure(2, 2)
else:
label_struct = ndimage.generate_binary_structure(3, 3)
# simulate rotation series
sim_results = self.simulate_rotation_series(plane_data, [
grain_params,
],
eta_ranges=eta_ranges,
ome_ranges=ome_ranges,
ome_period=ome_period)
# patch vertex generator (global for instrument)
tol_vec = 0.5 * np.radians([
-tth_tol, -eta_tol, -tth_tol, eta_tol, tth_tol, eta_tol, tth_tol,
-eta_tol
])
# prepare output if requested
if filename is not None and output_format.lower() == 'hdf5':
this_filename = os.path.join(dirname, filename)
writer = io.GrainDataWriter_h5(os.path.join(dirname, filename),
self.write_config(), grain_params)
# =====================================================================
# LOOP OVER PANELS
# =====================================================================
iRefl = 0
compl = []
output = dict.fromkeys(self.detectors)
for detector_id in self.detectors:
# initialize text-based output writer
if filename is not None and output_format.lower() == 'text':
output_dir = os.path.join(dirname, detector_id)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
this_filename = os.path.join(output_dir, filename)
writer = io.PatchDataWriter(this_filename)
# grab panel
panel = self.detectors[detector_id]
instr_cfg = panel.config_dict(self.chi, self.tvec)
native_area = panel.pixel_area # pixel ref area
# pull out the OmegaImageSeries for this panel from input dict
ome_imgser = imgser_dict[detector_id]
# extract simulation results
sim_results_p = sim_results[detector_id]
hkl_ids = sim_results_p[0][0]
hkls_p = sim_results_p[1][0]
ang_centers = sim_results_p[2][0]
xy_centers = sim_results_p[3][0]
ang_pixel_size = sim_results_p[4][0]
# now verify that full patch falls on detector...
# ???: strictly necessary?
#
# patch vertex array from sim
nangs = len(ang_centers)
patch_vertices = (np.tile(ang_centers[:, :2],
(1, 4)) + np.tile(tol_vec,
(nangs, 1))).reshape(
4 * nangs, 2)
ome_dupl = np.tile(ang_centers[:, 2],
(4, 1)).T.reshape(len(patch_vertices), 1)
# find vertices that all fall on the panel
det_xy, _ = xrdutil._project_on_detector_plane(
np.hstack([patch_vertices, ome_dupl]), panel.rmat, rMat_c,
self.chi, panel.tvec, tVec_c, self.tvec, panel.distortion)
_, on_panel = panel.clip_to_panel(det_xy, buffer_edges=True)
# all vertices must be on...
patch_is_on = np.all(on_panel.reshape(nangs, 4), axis=1)
patch_xys = det_xy.reshape(nangs, 4, 2)[patch_is_on]
# re-filter...
hkl_ids = hkl_ids[patch_is_on]
hkls_p = hkls_p[patch_is_on, :]
ang_centers = ang_centers[patch_is_on, :]
xy_centers = xy_centers[patch_is_on, :]
ang_pixel_size = ang_pixel_size[patch_is_on, :]
# TODO: add polygon testing right here!
# done <JVB 06/21/16>
if check_only:
patch_output = []
for i_pt, angs in enumerate(ang_centers):
# the evaluation omegas;
# expand about the central value using tol vector
ome_eval = np.degrees(angs[2]) + ome_del
# ...vectorize the omega_to_frame function to avoid loop?
frame_indices = [
ome_imgser.omega_to_frame(ome)[0] for ome in ome_eval
]
if -1 in frame_indices:
if not quiet:
msg = """
window for (%d%d%d) falls outside omega range
""" % tuple(hkls_p[i_pt, :])
print(msg)
continue
else:
these_vertices = patch_xys[i_pt]
ijs = panel.cartToPixel(these_vertices)
ii, jj = polygon(ijs[:, 0], ijs[:, 1])
contains_signal = False
for i_frame in frame_indices:
contains_signal = contains_signal or np.any(
ome_imgser[i_frame][ii, jj] > threshold)
compl.append(contains_signal)
patch_output.append((ii, jj, frame_indices))
else:
# make the tth,eta patches for interpolation
patches = xrdutil.make_reflection_patches(
instr_cfg,
ang_centers[:, :2],
ang_pixel_size,
omega=ang_centers[:, 2],
tth_tol=tth_tol,
eta_tol=eta_tol,
rMat_c=rMat_c,
tVec_c=tVec_c,
distortion=panel.distortion,
npdiv=npdiv,
quiet=True,
beamVec=self.beam_vector)
# GRAND LOOP over reflections for this panel
patch_output = []
for i_pt, patch in enumerate(patches):
# strip relevant objects out of current patch
vtx_angs, vtx_xy, conn, areas, xy_eval, ijs = patch
prows, pcols = areas.shape
nrm_fac = areas / float(native_area)
nrm_fac = nrm_fac / np.min(nrm_fac)
# grab hkl info
hkl = hkls_p[i_pt, :]
hkl_id = hkl_ids[i_pt]
# edge arrays
tth_edges = vtx_angs[0][0, :]
delta_tth = tth_edges[1] - tth_edges[0]
eta_edges = vtx_angs[1][:, 0]
delta_eta = eta_edges[1] - eta_edges[0]
# need to reshape eval pts for interpolation
xy_eval = np.vstack(
[xy_eval[0].flatten(), xy_eval[1].flatten()]).T
# the evaluation omegas;
# expand about the central value using tol vector
ome_eval = np.degrees(ang_centers[i_pt, 2]) + ome_del
# ???: vectorize the omega_to_frame function to avoid loop?
frame_indices = [
ome_imgser.omega_to_frame(ome)[0] for ome in ome_eval
]
if -1 in frame_indices:
if not quiet:
msg = """
window for (%d%d%d) falls outside omega range
""" % tuple(hkl)
print(msg)
continue
else:
# initialize spot data parameters
# !!! maybe change these to nan to not f**k up writer
peak_id = -999
sum_int = None
max_int = None
meas_angs = None
meas_xy = None
# quick check for intensity
contains_signal = False
patch_data_raw = []
for i_frame in frame_indices:
tmp = ome_imgser[i_frame][ijs[0], ijs[1]]
contains_signal = contains_signal or np.any(
tmp > threshold)
patch_data_raw.append(tmp)
pass
patch_data_raw = np.stack(patch_data_raw, axis=0)
compl.append(contains_signal)
if contains_signal:
# initialize patch data array for intensities
if interp.lower() == 'bilinear':
patch_data = np.zeros(
(len(frame_indices), prows, pcols))
for i, i_frame in enumerate(frame_indices):
patch_data[i] = \
panel.interpolate_bilinear(
xy_eval,
ome_imgser[i_frame],
pad_with_nans=False
).reshape(prows, pcols) # * nrm_fac
elif interp.lower() == 'nearest':
patch_data = patch_data_raw # * nrm_fac
else:
msg = "interpolation option " + \
"'%s' not understood"
raise (RuntimeError, msg % interp)
# now have interpolated patch data...
labels, num_peaks = ndimage.label(
patch_data > threshold, structure=label_struct)
slabels = np.arange(1, num_peaks + 1)
if num_peaks > 0:
peak_id = iRefl
coms = np.array(
ndimage.center_of_mass(patch_data,
labels=labels,
index=slabels))
if num_peaks > 1:
center = np.r_[patch_data.shape] * 0.5
center_t = np.tile(center, (num_peaks, 1))
com_diff = coms - center_t
closest_peak_idx = np.argmin(
np.sum(com_diff**2, axis=1))
else:
closest_peak_idx = 0
pass # end multipeak conditional
coms = coms[closest_peak_idx]
# meas_omes = \
# ome_edges[0] + (0.5 + coms[0])*delta_ome
meas_omes = \
ome_eval[0] + coms[0]*delta_ome
meas_angs = np.hstack([
tth_edges[0] + (0.5 + coms[2]) * delta_tth,
eta_edges[0] + (0.5 + coms[1]) * delta_eta,
mapAngle(np.radians(meas_omes), ome_period)
])
# intensities
# - summed is 'integrated' over interpolated
# data
# - max is max of raw input data
sum_int = np.sum(patch_data[
labels == slabels[closest_peak_idx]])
max_int = np.max(patch_data_raw[
labels == slabels[closest_peak_idx]])
# ???: Should this only use labeled pixels?
# Those are segmented from interpolated data,
# not raw; likely ok in most cases.
# need MEASURED xy coords
gvec_c = anglesToGVec(meas_angs,
chi=self.chi,
rMat_c=rMat_c,
bHat_l=self.beam_vector)
rMat_s = makeOscillRotMat(
[self.chi, meas_angs[2]])
meas_xy = gvecToDetectorXY(
gvec_c,
panel.rmat,
rMat_s,
rMat_c,
panel.tvec,
self.tvec,
tVec_c,
beamVec=self.beam_vector)
if panel.distortion is not None:
# FIXME: distortion handling
meas_xy = panel.distortion[0](
np.atleast_2d(meas_xy),
panel.distortion[1],
invert=True).flatten()
pass
# FIXME: why is this suddenly necessary???
meas_xy = meas_xy.squeeze()
pass # end num_peaks > 0
else:
patch_data = patch_data_raw
pass # end contains_signal
# write output
if filename is not None:
if output_format.lower() == 'text':
writer.dump_patch(peak_id, hkl_id, hkl,
sum_int, max_int,
ang_centers[i_pt], meas_angs,
xy_centers[i_pt], meas_xy)
elif output_format.lower() == 'hdf5':
xyc_arr = xy_eval.reshape(prows, pcols,
2).transpose(
2, 0, 1)
writer.dump_patch(
detector_id, iRefl, peak_id, hkl_id,
hkl, tth_edges, eta_edges,
np.radians(ome_eval), xyc_arr, ijs,
frame_indices, patch_data,
ang_centers[i_pt], xy_centers[i_pt],
meas_angs, meas_xy)
pass # end conditional on write output
pass # end conditional on check only
patch_output.append([
peak_id,
hkl_id,
hkl,
sum_int,
max_int,
ang_centers[i_pt],
meas_angs,
meas_xy,
])
iRefl += 1
pass # end patch conditional
pass # end patch loop
output[detector_id] = patch_output
if filename is not None and output_format.lower() == 'text':
writer.close()
pass # end detector loop
if filename is not None and output_format.lower() == 'hdf5':
writer.close()
return compl, output
def make_powder_rings(self,
pd,
merge_hkls=False,
delta_tth=None,
delta_eta=10.,
eta_period=None,
rmat_s=ct.identity_3x3,
tvec_s=ct.zeros_3,
tvec_c=ct.zeros_3,
full_output=False):
"""
"""
# in case you want to give it tth angles directly
if hasattr(pd, '__len__'):
tth = np.array(pd).flatten()
if delta_tth is None:
raise RuntimeError(
"If supplying a 2theta list as first arg, " +
"must supply a delta_tth")
sector_vertices = np.tile(
0.5 * np.radians([
-delta_tth, -delta_eta, -delta_tth, delta_eta, delta_tth,
delta_eta, delta_tth, -delta_eta, 0.0, 0.0
]), (len(tth), 1))
else:
# Okay, we have a PlaneData object
pd = PlaneData.makeNew(pd) # make a copy to munge
if delta_tth is not None:
pd.tThWidth = np.radians(delta_tth)
else:
delta_tth = np.degrees(pd.tThWidth)
# conversions, meh...
del_eta = np.radians(delta_eta)
# do merging if asked
if merge_hkls:
_, tth_ranges = pd.getMergedRanges()
tth = np.array([0.5 * sum(i) for i in tth_ranges])
else:
tth_ranges = pd.getTThRanges()
tth = pd.getTTh()
tth_pm = tth_ranges - np.tile(tth, (2, 1)).T
sector_vertices = np.vstack([[
i[0], -del_eta, i[0], del_eta, i[1], del_eta, i[1], -del_eta,
0.0, 0.0
] for i in tth_pm])
# for generating rings
if eta_period is None:
eta_period = (-np.pi, np.pi)
neta = int(360. / float(delta_eta))
eta = mapAngle(
np.radians(delta_eta *
(np.linspace(0, neta - 1, num=neta) + 0.5)) +
eta_period[0], eta_period)
angs = [
np.vstack([i * np.ones(neta), eta,
np.zeros(neta)]) for i in tth
]
# need xy coords and pixel sizes
valid_ang = []
valid_xy = []
map_indices = []
npp = 5 # [ll, ul, ur, lr, center]
for i_ring in range(len(angs)):
# expand angles to patch vertices
these_angs = angs[i_ring].T
patch_vertices = (np.tile(these_angs[:, :2], (1, npp)) +
np.tile(sector_vertices[i_ring],
(neta, 1))).reshape(npp * neta, 2)
# duplicate ome array
ome_dupl = np.tile(these_angs[:, 2],
(npp, 1)).T.reshape(npp * neta, 1)
# find vertices that all fall on the panel
gVec_ring_l = anglesToGVec(np.hstack([patch_vertices, ome_dupl]),
bHat_l=self.bvec)
all_xy = gvecToDetectorXY(gVec_ring_l,
self.rmat,
rmat_s,
ct.identity_3x3,
self.tvec,
tvec_s,
tvec_c,
beamVec=self.bvec)
_, on_panel = self.clip_to_panel(all_xy)
# all vertices must be on...
patch_is_on = np.all(on_panel.reshape(neta, npp), axis=1)
patch_xys = all_xy.reshape(neta, 5, 2)[patch_is_on]
idx = np.where(patch_is_on)[0]
valid_ang.append(these_angs[patch_is_on, :2])
valid_xy.append(patch_xys[:, -1, :].squeeze())
map_indices.append(idx)
pass
# ??? is this option necessary?
if full_output:
return valid_ang, valid_xy, map_indices, eta
else:
return valid_ang, valid_xy
def objFuncSX(pFit,
pFull,
pFlag,
dFunc,
dFlag,
xyo_det,
hkls_idx,
bMat,
vInv,
bVec,
eVec,
omePeriod,
simOnly=False,
return_value_flag=return_value_flag):
"""
"""
npts = len(xyo_det)
refineFlag = np.array(np.hstack([pFlag, dFlag]), dtype=bool)
print refineFlag
# pFull[refineFlag] = pFit/scl[refineFlag]
pFull[refineFlag] = pFit
if dFunc is not None:
dParams = pFull[-len(dFlag):]
xys = dFunc(xyo_det[:, :2], dParams)
else:
xys = xyo_det[:, :2]
# detector quantities
wavelength = pFull[0]
rMat_d = xf.makeDetectorRotMat(pFull[1:4])
tVec_d = pFull[4:7].reshape(3, 1)
# sample quantities
chi = pFull[7]
tVec_s = pFull[8:11].reshape(3, 1)
# crystal quantities
rMat_c = xf.makeRotMatOfExpMap(pFull[11:14])
tVec_c = pFull[14:17].reshape(3, 1)
# stretch tensor comp matrix from MV notation in SAMPLE frame
vMat_s = mutil.vecMVToSymm(vInv)
# g-vectors:
# 1. calculate full g-vector components in CRYSTAL frame from B
# 2. rotate into SAMPLE frame and apply stretch
# 3. rotate back into CRYSTAL frame and normalize to unit magnitude
# IDEA: make a function for this sequence of operations with option for
# choosing ouput frame (i.e. CRYSTAL vs SAMPLE vs LAB)
gVec_c = np.dot(bMat, hkls_idx)
gVec_s = np.dot(vMat_s, np.dot(rMat_c, gVec_c))
gHat_c = mutil.unitVector(np.dot(rMat_c.T, gVec_s))
match_omes, calc_omes = matchOmegas(xyo_det,
hkls_idx,
chi,
rMat_c,
bMat,
wavelength,
vInv=vInv,
beamVec=bVec,
etaVec=eVec,
omePeriod=omePeriod)
calc_xy = np.zeros((npts, 2))
for i in range(npts):
rMat_s = xfcapi.makeOscillRotMat([chi, calc_omes[i]])
calc_xy[i, :] = xfcapi.gvecToDetectorXY(gHat_c[:, i],
rMat_d,
rMat_s,
rMat_c,
tVec_d,
tVec_s,
tVec_c,
beamVec=bVec).flatten()
pass
if np.any(np.isnan(calc_xy)):
raise RuntimeError("infeasible pFull: may want to scale" +
"back finite difference step size")
# return values
if simOnly:
# return simulated values
retval = np.hstack([calc_xy, calc_omes.reshape(npts, 1)])
else:
# return residual vector
# IDEA: try angles instead of xys?
diff_vecs_xy = calc_xy - xys[:, :2]
diff_ome = xf.angularDifference(calc_omes, xyo_det[:, 2])
retval = np.hstack([diff_vecs_xy, diff_ome.reshape(npts, 1)]).flatten()
if return_value_flag == 1:
# return scalar sum of squared residuals
retval = sum(abs(retval))
elif return_value_flag == 2:
# return DOF-normalized chisq
# TODO: check this calculation
denom = npts - len(pFit) - 1.
if denom != 0:
nu_fac = 1. / denom
else:
nu_fac = 1.
nu_fac = 1 / (npts - len(pFit) - 1.)
retval = nu_fac * sum(retval**2)
return retval
## print "Maximum disagreement in eta: %f"%maxDiff_eta # maxDiff_gVec = np.linalg.norm(np.sqrt(np.sum(np.asarray(gVec_l1.T-gVec_l2)**2,1)),np.inf) # print "Maximum disagreement in gVec: %f"%maxDiff_gVec gVec_c1 = np.dot(rMat_c.T,np.dot(rMat_s.T,gVec_l1)) gVec_c2 = np.ascontiguousarray(np.dot(rMat_c.T,np.dot(rMat_s.T,gVec_l2.T)).T) start3 = timer() # time this xy1 = xf.gvecToDetectorXY(gVec_c1,rMat_d,rMat_s,rMat_c,tVec_d,tVec_s,tVec_c,beamVec=bVec_ref) elapsed3 = (timer() - start3) print "Time for Python gvecToDetectorXY: %f"%(elapsed3) start4 = timer() # time this xy2 = xfcapi.gvecToDetectorXY(gVec_c2,rMat_d,rMat_s,rMat_c,tVec_d,tVec_s,tVec_c,beamVec=bVec_ref) elapsed4 = (timer() - start4) print "Time for CAPI gvecToDetectorXY: %f"%(elapsed4) print 'cudadevice: ', numba.cuda.get_current_device().name # setup or numba version # should be able to run in nopython mode bHat_l = np.zeros(3) nVec_l = np.zeros(3) P0_l = np.zeros(3) P2_l = np.zeros(3) P2_d = np.zeros(3) P3_l = np.zeros(3)
neta = int(eta_range/eta_size)
tth_vec = tth_size*(np.arange(ntth) - 0.5*ntth - 1) + tth0
eta_vec = eta_size*(np.arange(neta) - 0.5*neta - 1) + eta0
angpts = np.meshgrid(eta_vec, tth_vec, indexing='ij')
gpts = xfc.anglesToGVec(
np.vstack([
np.radians(angpts[1].flatten()),
np.radians(angpts[0].flatten()),
np.zeros(neta*ntth)
]).T, bHat_l=d.bvec)
xypts = xfc.gvecToDetectorXY(
gpts,
d.rmat, np.eye(3), np.eye(3),
d.tvec, np.zeros(3), np.zeros(3),
beamVec=d.bvec)
img2 = d.interpolate_bilinear(xypts, average_frame).reshape(neta, ntth)
img3 = copy.deepcopy(img2)
borders = np.isnan(img2)
img2[borders] = 0.
img3[borders] = 0.
img3 += np.min(img3) + 1
img3 = np.log(img3)
img3[borders] = np.nan
extent = (
np.min(angpts[1]), np.max(angpts[1]),
np.min(angpts[0]), np.max(angpts[0])
def make_reflection_patches(instr_cfg,
tth_eta,
ang_pixel_size,
omega=None,
tth_tol=0.2,
eta_tol=1.0,
rMat_c=np.eye(3),
tVec_c=np.c_[0., 0., 0.].T,
distortion=distortion,
npdiv=1,
quiet=False,
compute_areas_func=compute_areas):
"""
prototype function for making angular patches on a detector
panel_dims are [(xmin, ymin), (xmax, ymax)] in mm
pixel_pitch is [row_size, column_size] in mm
DISTORTION HANDING IS STILL A KLUDGE
patches are:
delta tth
d ------------- ... -------------
e | x | x | x | ... | x | x | x |
l ------------- ... -------------
t .
a .
.
e ------------- ... -------------
t | x | x | x | ... | x | x | x |
a ------------- ... -------------
"""
npts = len(tth_eta)
# detector frame
rMat_d = xfcapi.makeDetectorRotMat(
instr_cfg['detector']['transform']['tilt_angles'])
tVec_d = np.r_[instr_cfg['detector']['transform']['t_vec_d']]
pixel_size = instr_cfg['detector']['pixels']['size']
frame_nrows = instr_cfg['detector']['pixels']['rows']
frame_ncols = instr_cfg['detector']['pixels']['columns']
panel_dims = (
-0.5 * np.r_[frame_ncols * pixel_size[1], frame_nrows * pixel_size[0]],
0.5 * np.r_[frame_ncols * pixel_size[1], frame_nrows * pixel_size[0]])
row_edges = np.arange(frame_nrows +
1)[::-1] * pixel_size[1] + panel_dims[0][1]
col_edges = np.arange(frame_ncols + 1) * pixel_size[0] + panel_dims[0][0]
# sample frame
chi = instr_cfg['oscillation_stage']['chi']
tVec_s = np.r_[instr_cfg['oscillation_stage']['t_vec_s']]
# data to loop
# ...WOULD IT BE CHEAPER TO CARRY ZEROS OR USE CONDITIONAL?
if omega is None:
full_angs = np.hstack([tth_eta, np.zeros((npts, 1))])
else:
full_angs = np.hstack([tth_eta, omega.reshape(npts, 1)])
patches = []
for angs, pix in zip(full_angs, ang_pixel_size):
# need to get angular pixel size
rMat_s = xfcapi.makeOscillRotMat([chi, angs[2]])
ndiv_tth = npdiv * np.ceil(tth_tol / np.degrees(pix[0]))
ndiv_eta = npdiv * np.ceil(eta_tol / np.degrees(pix[1]))
tth_del = np.arange(
0, ndiv_tth + 1) * tth_tol / float(ndiv_tth) - 0.5 * tth_tol
eta_del = np.arange(
0, ndiv_eta + 1) * eta_tol / float(ndiv_eta) - 0.5 * eta_tol
# store dimensions for convenience
# * etas and tths are bin vertices, ome is already centers
sdims = [len(eta_del) - 1, len(tth_del) - 1]
# meshgrid args are (cols, rows), a.k.a (fast, slow)
m_tth, m_eta = np.meshgrid(tth_del, eta_del)
npts_patch = m_tth.size
# calculate the patch XY coords from the (tth, eta) angles
# * will CHEAT and ignore the small perturbation the different
# omega angle values causes and simply use the central value
gVec_angs_vtx = np.tile(angs, (npts_patch, 1)) \
+ np.radians(
np.vstack([m_tth.flatten(),
m_eta.flatten(),
np.zeros(npts_patch)
]).T
)
# will need this later
rMat_s = xfcapi.makeOscillRotMat([chi, angs[2]])
# FOR ANGULAR MESH
conn = gutil.cellConnectivity(sdims[0], sdims[1], origin='ll')
gVec_c = xf.anglesToGVec(gVec_angs_vtx,
xf.bVec_ref,
xf.eta_ref,
rMat_s=rMat_s,
rMat_c=rMat_c)
xy_eval_vtx = xfcapi.gvecToDetectorXY(gVec_c.T, rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c)
if distortion is not None and len(distortion) == 2:
xy_eval_vtx = distortion[0](xy_eval_vtx,
distortion[1],
invert=True)
pass
areas = compute_areas_func(xy_eval_vtx, conn)
# EVALUATION POINTS
# * for lack of a better option will use centroids
tth_eta_cen = gutil.cellCentroids(np.atleast_2d(gVec_angs_vtx[:, :2]),
conn)
gVec_angs = np.hstack(
[tth_eta_cen, np.tile(angs[2], (len(tth_eta_cen), 1))])
gVec_c = xf.anglesToGVec(gVec_angs,
xf.bVec_ref,
xf.eta_ref,
rMat_s=rMat_s,
rMat_c=rMat_c)
xy_eval = xfcapi.gvecToDetectorXY(gVec_c.T, rMat_d, rMat_s, rMat_c,
tVec_d, tVec_s, tVec_c)
if distortion is not None and len(distortion) == 2:
xy_eval = distortion[0](xy_eval, distortion[1], invert=True)
pass
row_indices = gutil.cellIndices(row_edges, xy_eval[:, 1])
col_indices = gutil.cellIndices(col_edges, xy_eval[:, 0])
patches.append(
((gVec_angs_vtx[:, 0].reshape(m_tth.shape),
gVec_angs_vtx[:, 1].reshape(m_tth.shape)),
(xy_eval_vtx[:, 0].reshape(m_tth.shape),
xy_eval_vtx[:, 1].reshape(m_tth.shape)), conn,
areas.reshape(sdims[0],
sdims[1]), (row_indices.reshape(sdims[0], sdims[1]),
col_indices.reshape(sdims[0],
sdims[1]))))
pass
return patches
eta_d2 = dangs2[0][1] gVec_l2 = dangs2[1] elapsed2 = (time.clock() - start2) print "Time for CAPI detectorXYToGvec: %f"%(elapsed2) maxDiff_tTh = np.linalg.norm(tTh_d1-tTh_d2,np.inf) print "Maximum disagreement in tTh: %f"%maxDiff_tTh maxDiff_eta = np.linalg.norm(eta_d1-eta_d2,np.inf) print "Maximum disagreement in eta: %f"%maxDiff_eta maxDiff_gVec = np.linalg.norm(np.sqrt(np.sum(np.asarray(gVec_l1.T-gVec_l2)**2,1)),np.inf) print "Maximum disagreement in gVec: %f"%maxDiff_gVec gVec_c1 = np.dot(rMat_c.T,np.dot(rMat_s.T,gVec_l1)) gVec_c2 = np.ascontiguousarray(np.dot(rMat_c.T,np.dot(rMat_s.T,gVec_l2.T)).T) start3 = time.clock() # time this xy1 = xf.gvecToDetectorXY(gVec_c1,rMat_d,rMat_s,rMat_c,tVec_d,tVec_s,tVec_c,beamVec=bVec_ref) elapsed3 = (time.clock() - start3) print "Time for Python gvecToDetectorXY: %f"%(elapsed3) maxDiff_xy = np.linalg.norm(np.sqrt(np.sum(np.asarray(XY-xy1)**2,1)),np.inf) print "Maximum disagreement in gVec: %f"%maxDiff_xy start4 = time.clock() # time this xy2 = xfcapi.gvecToDetectorXY(gVec_c2,rMat_d,rMat_s,rMat_c,tVec_d,tVec_s,tVec_c,beamVec=bVec_ref) elapsed4 = (time.clock() - start4) print "Time for CAPI gvecToDetectorXY: %f"%(elapsed4) maxDiff_xy = np.linalg.norm(np.sqrt(np.sum(np.asarray(XY-xy2)**2,1)),np.inf) print "Maximum disagreement in gVec: %f"%maxDiff_xy
