def test_2x2_img_easy():
w = SegGeometryEpix10kaV1(use_wide_pix_center=False)
X, Y = w.get_seg_xy_maps_pix_with_offset()
iX, iY = (X + 0.25).astype(int), (Y + 0.25).astype(int)
img = gg.getImageFromIndexArrays(iY, iX, iX + iY)
gg.plotImageLarge(img, amp_range=(0, 750), figsize=(10, 8))
gg.show()
def example_varsize():
print """Test HSpectrum for variable size bins"""
from time import time
edges = (0, 30, 40, 50, 60, 70, 100) # array of bin edges
mu, sigma = 50, 10 # parameters of random Gaussian distribution of intensities
nevts = 10 # number of events in this test
ashape = (32, 185, 388) # data array shape
spec = HSpectrum(edges, pbits=0377)
for ev in range(nevts):
arr = random_standard_array(ashape, mu, sigma)
t0_sec = time()
spec.fill(arr)
print 'Event:%3d, t = %10.6f sec' % (ev, time() - t0_sec)
if True:
import pyimgalgos.GlobalGraphics as gg
histarr, edges, nbins = spec.spectrum()
#gg.plotImageLarge(arr, amp_range=(vmin,vmax), title='random')
gg.plotImageLarge(histarr[0:500, :],
amp_range=(0, nevts / 3),
title='indexes')
gg.show()
def show():
log( "rmin", rmin)
log( "rmax", rmax)
import pyimgalgos.GlobalGraphics as gg
gg.plotImageLarge(imarr, amp_range=(rmin, rmax), title = title, origin = 'lower')
if show_plot:
gg.show()
def do_main():
""" Main method to do work
"""
from pyimgalgos.FiberIndexing import BinPars
from pyimgalgos.GlobalUtils import create_directory
# h-k space image parameters
hmax = 4
kmax = 6
# recipical space image parameters, bins for 2-d image
bpq = BinPars((-0.25, 0.25), 1200, vtype=np.float32, endpoint=True)
#fname = '/reg/neh/home1/dubrovin/LCLS/rel-mengning/work/peak-idx-cxif5315-r0169-2015-11-13T17:04:37.txt'
#fname = '/reg/neh/home1/dubrovin/LCLS/rel-mengning/work/peak-idx-cxif5315-r0169-2015-12-01T15:44:49.txt'
fname = '/reg/neh/home1/dubrovin/LCLS/rel-mengning/work/peak-idx-cxif5315-r0169-2016-05-12T18:17:57.txt'
rdir = './results-idx'
create_directory(rdir)
sp.prefix = '%s/2016-05-13-v01-idx-res-matched' % rdir # file name prefix for histograms
#sp.prefix = '%s/2016-05-13-v01-idx-res-peak-nm' % rdir # file name prefix for histograms
img_space, img_recip = proc_file(fname, hmax, kmax, bpq)
print_crystal_in_hk_space(img_space, hmax, kmax)
print 'img_recip.shape=', img_recip.shape
if sp.DO_HIST: plot_histograms()
if sp.DO_PLOT:
import pyimgalgos.GlobalGraphics as gg
img = img_space
img_range = (-kmax - 0.5, kmax + 0.5, -hmax - 0.5, hmax + 0.5)
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=(0,1), figsize=(8,6),\
title='Crystal structure in h-k space', origin='upper', window=(0.1, 0.1, 0.9, 0.86))
axim.set_xlabel('k index', fontsize=18)
axim.set_ylabel('h index', fontsize=18)
gg.savefig('%s-%s-crystal-in-hk-space.png' %
(sp.prefix, sp.exp_run)) # sp.tstamp
img = img_recip
ave, rms = img.mean(), img.std()
amin, amax = 0, ave + 5 * rms
img_range = (bpq.vmin, bpq.vmax, bpq.vmin, bpq.vmax)
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=(amin, amax), figsize=(10,8),\
title='Crystal structure in reciprocal space', origin='upper', window=(0.1, 0.1, 0.86, 0.86))
axim.set_xlabel('$q_x$ ($1/\AA$)', fontsize=18)
axim.set_ylabel('$q_y$ ($1/\AA$)', fontsize=18)
gg.savefig('%s-%s-crystal-in-recip-space.png' %
(sp.prefix, sp.exp_run))
gg.show()
def test_2x2_mask(mbits=0o377):
pc2x2 = SegGeometryEpix10kaV1(use_wide_pix_center=False)
X, Y = pc2x2.get_seg_xy_maps_pix_with_offset()
mask = pc2x2.pixel_mask_array(mbits, width=5, wcentral=5)
mask[mask == 0] = 3
iX, iY = (X + 0.25).astype(int), (Y + 0.25).astype(int)
img = gg.getImageFromIndexArrays(iX, iY, mask)
gg.plotImageLarge(img, amp_range=(-1, 2), figsize=(10, 10))
gg.show()
def show():
log("rmin", rmin)
log("rmax", rmax)
import pyimgalgos.GlobalGraphics as gg
gg.plotImageLarge(imarr,
amp_range=(rmin, rmax),
title=title,
origin='lower')
if show_plot:
gg.show()
def test_xyz_maps():
w = SegGeometryEpix10kaV1()
w.print_maps_seg_um()
titles = ['X map', 'Y map']
#for i,arr2d in enumerate([w.x_pix_arr,w.y_pix_arr]) :
for i, arr2d in enumerate(w.get_seg_xy_maps_pix()):
amp_range = (arr2d.min(), arr2d.max())
gg.plotImageLarge(arr2d,
amp_range=amp_range,
figsize=(10, 8),
title=titles[i])
gg.move(200 * i, 100 * i)
gg.show()
def plot_lut_as_omega_vs_qh(list_oq) :
"""Plots content of the lookup table as an image of intensities for omega(deg) vs. hq(1/A)
"""
img = lut_as_image(list_oq)
print_ndarr(img, 'img')
img_range = (bpq.vmin(), bpq.vmax(), bpomega.vmax(), bpomega.vmin())
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Plot reconstructed from look-up table', origin='upper',\
window=(0.06, 0.06, 0.94, 0.92), cmap='gray_r')
axim.set_xlabel('$q_{H}$ ($1/\AA$)', fontsize=18)
axim.set_ylabel('$\omega$ (degree)', fontsize=18)
gg.save('img-lut-prob-omega-vs-qh.png', pbits=1)
gg.show('do not block')
def plot_lut_as_omega_vs_qh(list_oq):
"""Plots content of the lookup table as an image of intensities for omega(deg) vs. hq(1/A)
"""
img = lut_as_image(list_oq)
print_ndarr(img, 'img')
img_range = (bpq.vmin(), bpq.vmax(), bpomega.vmax(), bpomega.vmin())
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Plot reconstructed from look-up table', origin='upper',\
window=(0.06, 0.06, 0.94, 0.92), cmap='gray_r')
axim.set_xlabel('$q_{H}$ ($1/\AA$)', fontsize=18)
axim.set_ylabel('$\omega$ (degree)', fontsize=18)
gg.save('img-lut-prob-omega-vs-qh.png', pbits=1)
gg.show('do not block')
def plot_xy_lattice(list_oq) :
"""Plots image of the crystal lattice, using list of [(omega,<1-d-array-of-intensities-for-omega>)]
"""
img = xy_lattice_image(list_oq)
print_ndarr(img, 'img')
#--- Convolution of image
from scipy.signal import convolve2d
g2d = arr_2d_gauss(2, 1.5)
img = convolve2d(img, g2d, mode='same', boundary='fill', fillvalue=0)
#---
img_range = (bpq.vmin(), bpq.vmax(), bpq.vmin(), bpq.vmax())
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Lattice', origin='upper',\
window=(0.08, 0.06, 0.94, 0.92)) # , cmap='gray_r')
axim.set_xlabel('Reciprocal x ($1/\AA$)', fontsize=18)
axim.set_ylabel('Reciprocal y ($1/\AA$)', fontsize=18)
gg.save('img-lut-lattice-xy.png', pbits=1)
gg.show()
def plot_xy_lattice(list_oq):
"""Plots image of the crystal lattice, using list of [(omega,<1-d-array-of-intensities-for-omega>)]
"""
img = xy_lattice_image(list_oq)
print_ndarr(img, 'img')
#--- Convolution of image
from scipy.signal import convolve2d
g2d = arr_2d_gauss(2, 1.5)
img = convolve2d(img, g2d, mode='same', boundary='fill', fillvalue=0)
#---
img_range = (bpq.vmin(), bpq.vmax(), bpq.vmin(), bpq.vmax())
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Lattice', origin='upper',\
window=(0.08, 0.06, 0.94, 0.92)) # , cmap='gray_r')
axim.set_xlabel('Reciprocal x ($1/\AA$)', fontsize=18)
axim.set_ylabel('Reciprocal y ($1/\AA$)', fontsize=18)
gg.save('img-lut-lattice-xy.png', pbits=1)
gg.show()
def test03(ntest, prefix='fig-v01'):
"""Test for 2-d binning of the restricted rad-phi range of entire image
"""
from time import time
import pyimgalgos.GlobalGraphics as gg
from PSCalib.GeometryAccess import img_from_pixel_arrays
arr, geo = data_geo(ntest)
iX, iY = geo.get_pixel_coord_indexes()
X, Y, Z = geo.get_pixel_coords()
mask = geo.get_pixel_mask(mbits=0377).flatten()
t0_sec = time()
rb = RadialBkgd(X, Y, mask, nradbins=200, nphibins=32, phiedges=(-20, 240), radedges=(10000,80000)) if ntest in (51,52)\
else RadialBkgd(X, Y, mask, nradbins= 5, nphibins= 8, phiedges=(-20, 240), radedges=(10000,80000))
#rb = RadialBkgd(X, Y, mask, nradbins=3, nphibins=8, phiedges=(240, -20), radedges=(80000,10000)) # v3
print 'RadialBkgd initialization time %.3f sec' % (time() - t0_sec)
#print 'npixels_per_bin:', rb.npixels_per_bin()
#print 'intensity_per_bin:', rb.intensity_per_bin(arr)
#print 'average_per_bin:', rb.average_per_bin(arr)
t0_sec = time()
nda, title = arr, None
if ntest == 41: nda, title = arr, 'averaged data'
elif ntest == 42: nda, title = rb.pixel_rad(), 'pixel radius value'
elif ntest == 43: nda, title = rb.pixel_phi(), 'pixel phi value'
elif ntest == 44:
nda, title = rb.pixel_irad() + 2, 'pixel radial bin index'
elif ntest == 45:
nda, title = rb.pixel_iphi() + 2, 'pixel phi bin index'
elif ntest == 46:
nda, title = rb.pixel_iseq(
) + 2, 'pixel sequential (rad and phi) bin index'
elif ntest == 47:
nda, title = mask, 'mask'
elif ntest == 48:
nda, title = rb.pixel_avrg(nda), 'averaged radial background'
elif ntest == 49:
nda, title = rb.subtract_bkgd(nda) * mask, 'background-subtracted data'
elif ntest == 50:
nda, title = rb.bin_avrg_rad_phi(nda), 'r-phi'
elif ntest == 51:
nda, title = rb.pixel_avrg_interpol(
nda), 'averaged radial interpolated background'
elif ntest == 52:
nda, title = rb.subtract_bkgd_interpol(
nda) * mask, 'interpol-background-subtracted data'
else:
print 'Test %d is not implemented' % ntest
return
print 'Get %s n-d array time %.3f sec' % (title, time() - t0_sec)
img = img_from_pixel_arrays(
iX, iY, nda) if not ntest in (50, ) else nda # [100:300,:]
colmap = 'jet' # 'cubehelix' 'cool' 'summer' 'jet' 'winter' 'gray'
da = (nda.min() - 1, nda.max() + 1)
ds = da
if ntest in (41, 48, 49, 50, 51):
ave, rms = nda.mean(), nda.std()
da = ds = (ave - 2 * rms, ave + 3 * rms)
elif ntest in (52, ):
colmap = 'gray'
ds = da = (-20, 20)
gg.plotImageLarge(img,
amp_range=da,
figsize=(14, 12),
title=title,
cmap=colmap)
gg.save('%s-%02d-img.png' % (prefix, ntest))
gg.hist1d(nda, bins=None, amp_range=ds, weights=None, color=None, show_stat=True, log=False, \
figsize=(6,5), axwin=(0.18, 0.12, 0.78, 0.80), \
title=None, xlabel='Pixel value', ylabel='Number of pixels', titwin=title)
gg.save('%s-%02d-his.png' % (prefix, ntest))
gg.show()
print 'End of test for %s' % title
def test01(ntest, prefix='fig-v01'):
"""Test for radial 1-d binning of entire image.
"""
from time import time
import pyimgalgos.GlobalGraphics as gg
from PSCalib.GeometryAccess import img_from_pixel_arrays
arr, geo = data_geo(ntest)
t0_sec = time()
iX, iY = geo.get_pixel_coord_indexes()
X, Y, Z = geo.get_pixel_coords()
mask = geo.get_pixel_mask(mbits=0377).flatten()
print 'Time to retrieve geometry %.3f sec' % (time() - t0_sec)
t0_sec = time()
rb = RadialBkgd(X, Y, mask, nradbins=500, nphibins=1) # v1
print 'RadialBkgd initialization time %.3f sec' % (time() - t0_sec)
t0_sec = time()
nda, title = arr, None
if ntest == 1: nda, title = arr, 'averaged data'
elif ntest == 2: nda, title = rb.pixel_rad(), 'pixel radius value'
elif ntest == 3: nda, title = rb.pixel_phi(), 'pixel phi value'
elif ntest == 4: nda, title = rb.pixel_irad() + 2, 'pixel radial bin index'
elif ntest == 5: nda, title = rb.pixel_iphi() + 2, 'pixel phi bin index'
elif ntest == 6:
nda, title = rb.pixel_iseq(
) + 2, 'pixel sequential (rad and phi) bin index'
elif ntest == 7:
nda, title = mask, 'mask'
elif ntest == 8:
nda, title = rb.pixel_avrg(nda), 'averaged radial background'
elif ntest == 9:
nda, title = rb.subtract_bkgd(nda) * mask, 'background-subtracted data'
else:
t1_sec = time()
pf = polarization_factor(rb.pixel_rad(), rb.pixel_phi(),
94e3) # Z=94mm
print 'Time to evaluate polarization correction factor %.3f sec' % (
time() - t1_sec)
if ntest == 10: nda, title = pf, 'polarization factor'
elif ntest == 11:
nda, title = arr * pf, 'polarization-corrected averaged data'
elif ntest == 12:
nda, title = rb.subtract_bkgd(
arr *
pf) * mask, 'polarization-corrected background subtracted data'
elif ntest == 13:
nda, title = rb.pixel_avrg(
arr * pf), 'polarization-corrected averaged radial background'
elif ntest == 14:
nda, title = rb.pixel_avrg_interpol(
arr * pf
) * mask, 'polarization-corrected interpolated radial background'
elif ntest == 15:
nda, title = rb.subtract_bkgd_interpol(
arr * pf
) * mask, 'polarization-corrected interpolated radial background-subtracted data'
else:
print 'Test %d is not implemented' % ntest
return
print 'Get %s n-d array time %.3f sec' % (title, time() - t0_sec)
img = img_from_pixel_arrays(
iX, iY, nda) if not ntest in (21, ) else nda[100:300, :]
da, ds = None, None
colmap = 'jet' # 'cubehelix' 'cool' 'summer' 'jet' 'winter'
if ntest in (2, 3, 4, 5, 6, 7):
da = ds = (nda.min() - 1., nda.max() + 1.)
if ntest in (12, 15):
ds = da = (-20, 20)
colmap = 'gray'
else:
ave, rms = nda.mean(), nda.std()
da = ds = (ave - 2 * rms, ave + 3 * rms)
gg.plotImageLarge(img,
amp_range=da,
figsize=(14, 12),
title=title,
cmap=colmap)
gg.save('%s-%02d-img.png' % (prefix, ntest))
gg.hist1d(nda, bins=None, amp_range=ds, weights=None, color=None, show_stat=True, log=False, \
figsize=(6,5), axwin=(0.18, 0.12, 0.78, 0.80), \
title=None, xlabel='Pixel value', ylabel='Number of pixels', titwin=title)
gg.save('%s-%02d-his.png' % (prefix, ntest))
gg.show()
print 'End of test for %s' % title
def make_index_table(prefix='./v01-') :
from pyimgalgos.GlobalUtils import str_tstamp
fname = '%s**t-cxif5315-r0169-%s.txt' % (prefix, str_tstamp())
fout = open(fname,'w')
fout.write('# file name: %s\n' % fname)
#------------------------------
# Photon energy
Egamma_eV = 6003.1936 # eV SIOC:SYS0:ML00:AO541
wavelen_nm = wavelength_nm_from_energy_ev(Egamma_eV) # nm
evald_rad = wave_vector_value(Egamma_eV) # 1/A
#-------
sigma_ql = 0.002 * evald_rad
sigma_qt = 0.002 * evald_rad
#-------
rec = '\n# photon energy = %.4f eV' % (Egamma_eV)\
+ '\n# wavelength = %.4f A' % (wavelen_nm*10)\
+ '\n# wave number/Evald radius k = 1/lambda = %.6f 1/A' % (evald_rad)\
+ '\n# sigma_ql = %.6f 1/A (approximately = k * <pixel size>/' % (sigma_ql)\
+ '\n# sigma_qt = %.6f 1/A (approximately = k * <pixel size>/' % (sigma_qt)\
+ '<sample-to-detector distance> = k*100um/100mm)'\
+ '\n# 3*sigma_ql = %.6f 1/A\n' % (3*sigma_ql)\
+ '\n# 3*sigma_qt = %.6f 1/A\n' % (3*sigma_qt)
print rec
fout.write(rec)
#------------------------------
# Lattice parameters
# from previous analysis note:
#a, b, c = 18.36, 26.65, 4.81 # Angstrom
#alpha, beta, gamma = 90, 90, 77.17 # 180 - 102.83 degree
a= 18.55 # Angstrom
b, c = 1.466*a, 0.262*a # Angstrom
alpha, beta, gamma = 90, 90, 78.47 # 180 - 101.53 degree
hmax, kmax, lmax = 4, 6, 0 # size of lattice to consider
#hmin, kmin, lmin =-4,-6, 0 # size of lattice to consider
hmin, kmin, lmin = None, None, None # default [-hmax,hmax], [-kmax,kmax],
a1, a2, a3 = triclinic_primitive_vectors(a, b, c, alpha, beta, gamma)
b1, b2, b3 = reciprocal_from_bravias(a1, a2, a3)
msg1 = '\n# Triclinic crystal cell parameters:'\
+ '\n# a = %.2f A\n# b = %.2f A\n# c = %.2f A' % (a, b, c)\
+ '\n# alpha = %.2f deg\n# beta = %.2f deg\n# gamma = %.2f deg' % (alpha, beta, gamma)
msg2 = '\n# 3-d space primitive vectors:\n# a1 = %s\n# a2 = %s\n# a3 = %s' %\
(str(a1), str(a2), str(a3))
msg3 = '\n# reciprocal space primitive vectors:\n# b1 = %s\n# b2 = %s\n# b3 = %s' %\
(str(b1), str(b2), str(b3))
rec = '%s\n%s\n%s\n' % (msg1, msg2, msg3)
print rec
fout.write(rec)
fout.write('\n# %s\n\n' % (89*'_'))
#for line in triclinic_primitive_vectors.__doc__.split('\n') : fout.write('\n# %s' % line)
test_lattice (b1, b2, b3, hmax, kmax, lmax, np.float32, hmin, kmin, lmin)
lattice_node_radius(b1, b2, b3, hmax, kmax, lmax, np.float32, '%10.6f', hmin, kmin, lmin)
lattice_node_radius(b1, b2, b3, hmax, kmax, 1, np.float32, '%10.6f', hmin, kmin, lmin)
#------------------------------
#return
#------------------------------
# binning for look-up table and plots
# bin parameters for q in units of k = Evald's sphere radius [1/A]
bpq = BinPars((-0.25, 0.25), 1000, vtype=np.float32, endpoint=False)
# bin parameters for omega [degree] - fiber rotation angle around axis
bpomega = BinPars((0., 180.), 360, vtype=np.float32, endpoint=False)
# bin parameters for beta [degree] - fiber axis tilt angle
#bpbeta = BinPars((15., 195.), 2, vtype=np.float32, endpoint=True)
#bpbeta = BinPars((15., 15.), 1, vtype=np.float32, endpoint=False)
#bpbeta = BinPars((5., 25.), 2, vtype=np.float32, endpoint=True)
bpbeta = BinPars((0., 50.), 11, vtype=np.float32, endpoint=True)
bpbeta2 = BinPars((180., 230.), 11, vtype=np.float32, endpoint=True)
str_beta = 'for-beta:%s' % (bpbeta.strrange)
print '\n%s\nIndexing lookup table\n' % (91*'_')
lut = make_lookup_table_v2(b1, b2, b3, hmax, kmax, lmax, np.float32, evald_rad, sigma_ql, sigma_qt, fout, bpq, bpomega, bpbeta, hmin, kmin, lmin)
lut2 = make_lookup_table_v2(b1, b2, b3, hmax, kmax, lmax, np.float32, evald_rad, sigma_ql, sigma_qt, fout, bpq, bpomega, bpbeta2, hmin, kmin, lmin)
fout.close()
print '\nIndexing lookup table is saved in the file: %s' % fname
#------------------------------
# produce and save plots
import pyimgalgos.GlobalGraphics as gg
img = lut # or lut2
img = lut + lut2
img_range = (bpq.vmin, bpq.vmax, bpomega.vmax, bpomega.vmin)
axim = gg.plotImageLarge(lut, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Non-symmetrized for beta', origin='upper', window=(0.05, 0.06, 0.94, 0.94))
axim.set_xlabel('$q_{H}$ ($1/\AA$)', fontsize=18)
axim.set_ylabel('$\omega$ (degree)', fontsize=18)
gg.save('%splot-img-prob-omega-vs-qh-%s.png' % (prefix, str_beta), pbits=1)
axim = gg.plotImageLarge(img, img_range=img_range, amp_range=None, figsize=(15,13),\
title='Symmetrized for beta (beta, beta+pi)', origin='upper', window=(0.05, 0.06, 0.94, 0.94))
axim.set_xlabel('$q_{H}$ ($1/\AA$)', fontsize=18)
axim.set_ylabel('$\omega$ (degree)', fontsize=18)
gg.save('%splot-img-prob-omega-vs-qh-sym-%s.png' % (prefix, str_beta), pbits=1)
arrhi = np.sum(img,0)
fighi, axhi, hi = gg.hist1d(bpq.binedges, bins=bpq.nbins-1, amp_range=(bpq.vmin, bpq.vmax), weights=arrhi,\
color='b', show_stat=True, log=False,\
figsize=(15,5), axwin=(0.05, 0.12, 0.85, 0.80),\
title=None, xlabel='$q_{H}$ ($1/\AA$)', ylabel='Intensity', titwin=None)
gg.show()
gg.save_fig(fighi, '%splot-his-prob-vs-qh-%s.png' % (prefix, str_beta), pbits=1)
qh_weight = zip(bpq.bincenters, arrhi)
fname = '%sarr-qh-weight-%s.npy' % (prefix, str_beta)
print 'Save qh:weigt array in file %s' % fname
np.save(fname, qh_weight)
def plot_image(img, img_range=None, amp_range=None, figsize=(12, 10)):
#import pyimgalgos.GlobalGraphics as gg
axim = gg.plotImageLarge(img, img_range, amp_range, figsize)
gg.show()