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 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 draw_times(ax, wf, wt):
#wf -= wf[0:1000].mean()
edges = find_edges(wf, BASE, THR, CFR, DEADTIME, LEADINGEDGE)
# pairs of (amplitude,sampleNumber)
print 'MCP edges'
print edges
for (amp, ind) in edges:
x0 = wt[int(ind)]
xarr = (x0, x0)
yarr = (amp, -amp)
gg.drawLine(ax, xarr, yarr, s=10, linewidth=1, color='k')
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 draw_times(ax, wf, wt):
#extrema = 0.1* wf_extremas(ax, wf, wt, rank=10)
#gg.drawLine(ax, wt, extrema, s=10, linewidth=1, color='k')
#return
#wf -= wf[0:1000].mean()
#edges = find_edges(wf, BASE, THR, CFR, DEADTIME, LEADINGEDGE)
edges = wf_extremas(ax, wf, wt, rank=10)
# pairs of (amplitude,sampleNumber)
print ' nhits:', edges.shape[0],
print ' edges:', edges
for (amp, ind) in edges:
x0 = wt[int(ind)]
xarr = (x0, x0)
yarr = (amp, -amp)
gg.drawLine(ax, xarr, yarr, s=10, linewidth=1, color='k')
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_lattice(b1 = (1.,0.,0.), b2 = (0.,1.,0.), b3 = (0.,0.,1.),\
hmax=3, kmax=2, lmax=1, cdtype=np.float32,\
evald_rad=0.5, qtol=0.01, prefix='', do_movie=False, delay=400,\
hmin=None, kmin=None, lmin=None, title_add='') :
"""Plots 2-d reciprocal space lattice, evald sphere,
generates series of plots for rotated lattice and movie from these plots.
- do_movie = True/False - on/off production of movie
- delay - is a time in msec between movie frames.
"""
import matplotlib.pyplot as plt
import pyimgalgos.GlobalGraphics as gg
print '\nIn %s' % sys._getframe().f_code.co_name
print '%s\nTest lattice with default parameters' % (80*'_')
x, y, z, r, h, k, l = lattice(b1, b2, b3, hmax, kmax, lmax, cdtype, hmin, kmin, lmin)
x.shape = (x.size,)
y.shape = (y.size,)
z.shape = (z.size,)
xlimits = ylimits = (-0.3, 0.3) # plot limits in (1/A)
#ylimits = (-0.4, 0.4) # plot limits in (1/A)
#xlimits = (-0.5, 0.3) # plot limits in (1/A)
fig, ax = gg.plotGraph(x,y, figsize=(8,7.5), window=(0.17, 0.10, 0.78, 0.84), pfmt='bo')
ax.set_xlim(xlimits)
ax.set_ylim(ylimits)
ax.set_xlabel('Reciprocal x ($1/\AA$)', fontsize=18)
ax.set_ylabel('Reciprocal y ($1/\AA$)', fontsize=18)
gg.save_fig(fig, '%sreciprocal-space-lattice.png' % prefix, pbits=1)
lst_omega = range(0,180,2) if do_movie else range(0,11,10)
#lst_omega = range(0,180,5) if do_movie else range(0,13,11)
#lst_omega = range(0,180,45) if do_movie else range(0,13,11)
beta_deg = 0
for omega_deg in lst_omega :
xrot1, yrot1 = rotation(x, y, omega_deg)
xrot2, zrot2 = rotation(xrot1, z, beta_deg)
dr, qv, qh, qt, ql = q_components(xrot2, yrot1, zrot2, evald_rad)
xhit = [xr for dq,xr in zip(dr.flatten(), xrot2.flatten()) if math.fabs(dq)<qtol]
yhit = [yr for dq,yr in zip(dr.flatten(), yrot1.flatten()) if math.fabs(dq)<qtol]
#fig, ax = gg.plotGraph(xrot2, yrot1, figsize=(8,7.5), window=(0.15, 0.10, 0.78, 0.84), pfmt='bo')
ax.cla()
ax.set_xlim(xlimits)
ax.set_ylim(ylimits)
ax.plot(xrot1, yrot1, 'yo')
if len(xhit)>0 and len(yhit)>0 : ax.plot(xhit, yhit, 'bo')
tit = 'beta=%.0f omega=%.0f' % (beta_deg, omega_deg)
if title_add : tit += ' %s' % (title_add)
ax.set_title(tit, color='k', fontsize=12)
ax.set_xlabel('Reciprocal x ($1/\AA$)', fontsize=18)
ax.set_ylabel('Reciprocal y ($1/\AA$)', fontsize=18)
gg.drawCenter(ax, (-evald_rad,0), s=0.04, linewidth=2, color='k')
gg.drawCircle(ax, (-evald_rad,0), evald_rad, linewidth=1, color='k', fill=False)
fig.canvas.draw()
gg.show('Do not hold!')
gg.save_fig(fig, '%slattice-rotated-beta%03d-omega%03d.png'%\
(prefix, int(beta_deg), int(omega_deg)), pbits=1)
if do_movie :
import os
#dir_movie = 'movie'
#os.system('mkdir %s'% dir_movie)
cmd = 'convert -delay %f %slattice-rotated-beta*.png movie.gif' % (delay, prefix)
print 'Wait for completion of the command: %s' % cmd
os.system(cmd)
print 'DONE!'
gg.show()
Rum.shape = Phi.shape = shape_cspad
#addhdr = ' Evnum Reg Seg Row Col Npix Amax Atot rcent ccent '+\
# 'rsigma csigma rmin rmax cmin cmax bkgd rms son imrow imcol x[um] y[um] r[um] phi[deg]'
addhdr = ' Evnum Reg Seg Row Col Npix Amax Atot rcent ccent '+\
'rsigma csigma bkgd rms son imrow imcol x[um] y[um] r[um] phi[deg]'
fmt = '%7d %3s %3d %4d %4d %4d %8.1f %8.1f %6.1f %6.1f %6.2f %6.2f'+\
' %6.2f %6.2f %6.2f'+\
' %6d %6d %8.0f %8.0f %8.0f %8.2f'
pstore = PeakStore(env, runnum, prefix='peaks', add_header=addhdr, pbits=1)
pstore.print_attrs()
##-----------------------------
fig, axim, axcb = gg.fig_axes() if DO_PLOT else (None, None, None)
fighi, axhi = None, None
if DO_SPEC :
fighi = gr.figure(figsize=(6,5), title='Spectrum of pixel intensities', move=(800,0))
axhi = gr.add_axes(fighi, (0.17, 0.12, 0.78, 0.78))
##-----------------------------
def geo_pars(s,r,c) :
inds = (s,r,c)
return imRow[inds], imCol[inds], Xum[inds], Yum[inds], Rum[inds], Phi[inds]
##-----------------------------
t0_sec_evloop = time()
def test_pf(tname):
##-----------------------------
PF = V3 # default
if tname == '1': PF = V1
if tname == '2': PF = V2
if tname == '3': PF = V3
if tname == '4': PF = V4
SKIP = 0
EVTMAX = 5 + SKIP
DO_PLOT_IMAGE = True
DO_PLOT_CONNECED_PIXELS = True if PF in (V2, V3, V4) else False
DO_PLOT_LOCAL_MAXIMUMS = True if PF in (V3, V4) else False
DO_PLOT_LOCAL_MINIMUMS = True if PF == V3 else False
shape = (500, 500)
mask = np.ones(shape, dtype=np.uint16)
# Pixel image indexes
#arr3d = np.array((1,shape[0],shape[1]))
INDS = np.indices((1, shape[0], shape[1]), dtype=np.int64)
imRow, imCol = INDS[1, :], INDS[2, :]
#iX = np.array(det.indexes_x(evt), dtype=np.int64) #- xoffset
#iY = np.array(det.indexes_y(evt), dtype=np.int64) #- yoffset
fs = (8, 7) # (11,10)
##-----------------------------
fig5, axim5, axcb5, imsh5 = gg.fig_axim_axcb_imsh(
figsize=fs) if DO_PLOT_LOCAL_MINIMUMS else (None, None, None, None)
fig4, axim4, axcb4, imsh4 = gg.fig_axim_axcb_imsh(
figsize=fs) if DO_PLOT_LOCAL_MAXIMUMS else (None, None, None, None)
fig3, axim3, axcb3, imsh3 = gg.fig_axim_axcb_imsh(
figsize=fs) if DO_PLOT_CONNECED_PIXELS else (None, None, None, None)
fig1, axim1, axcb1, imsh1 = gg.fig_axim_axcb_imsh(
figsize=fs) if DO_PLOT_IMAGE else (None, None, None, None)
##-----------------------------
#alg = PyAlgos(windows=None, mask=None, pbits=10) # 0177777)
alg = psalgos.peak_finder_algos(seg=0, pbits=0)
if PF == V1:
alg.set_peak_selection_parameters(npix_min=0,
npix_max=1e6,
amax_thr=0,
atot_thr=0,
son_min=6)
elif PF == V2:
alg.set_peak_selection_parameters(npix_min=0,
npix_max=1e6,
amax_thr=0,
atot_thr=0,
son_min=6)
elif PF == V3:
alg.set_peak_selection_parameters(npix_min=1,
npix_max=1e6,
amax_thr=0,
atot_thr=0,
son_min=8)
elif PF == V4:
alg.set_peak_selection_parameters(npix_min=1,
npix_max=1e6,
amax_thr=0,
atot_thr=0,
son_min=4)
alg.print_attributes()
for ev in range(EVTMAX):
ev1 = ev + 1
if ev < SKIP: continue
#if ev>=EVTMAX : break
print 50 * '_', '\nEvent %04d' % ev1
add_water_ring = False if PF == V4 else True
img, peaks_sim = image_with_random_peaks(shape, add_water_ring)
# --- for debugging
#np.save('xxx-image', img)
#np.save('xxx-peaks', np.array(peaks_sim))
#img = np.load('xxx-image-crash.npy')
#peaks_sim = np.load('xxx-peaks-crash.npy')
# ---
peaks_gen = [(0, r, c, a, a * s, 9 * s * s)
for r, c, a, s in peaks_sim]
t0_sec = time()
peaks = alg.peak_finder_v3r3_d2(img, mask, rank=4, r0=6, dr=3, nsigm=3) if PF == V3 else\
alg.peak_finder_v4r3_d2(img, mask, thr_low=20, thr_high=40, rank=4, r0=5, dr=3)
#peaks = alg.list_of_peaks_selected()
#peaks_tot = alg.list_of_peaks()
# peaks = alg.peak_finder_v1(img, thr_low=20, thr_high=40, radius=6, dr=2) if PF == V1 else\
# alg.peak_finder_v2r1(img, thr=30, r0=7, dr=2) if PF == V2 else\
# alg.peak_finder_v3r2(img, rank=5, r0=7, dr=2, nsigm=3) if PF == V3 else\
# alg.peak_finder_v4r2(img, thr_low=20, thr_high=40, rank=6, r0=7, dr=2)
# #alg.peak_finder_v4r2(img, thr_low=20, thr_high=40, rank=6, r0=3.3, dr=0)
print 'Time consumed by the peak_finder = %10.6f(sec) number of simulated/found peaks: %d/%d'%\
(time()-t0_sec, len(peaks_sim), len(peaks))
#map3 = reshape_to_2d(alg.maps_of_connected_pixels()) if DO_PLOT_CONNECED_PIXELS else None # np.zeros((10,10))
#map4 = reshape_to_2d(alg.maps_of_local_maximums()) if DO_PLOT_LOCAL_MAXIMUMS else None # np.zeros((10,10))
#map5 = reshape_to_2d(alg.maps_of_local_minimums()) if DO_PLOT_LOCAL_MINIMUMS else None # np.zeros((10,10))
map3 = reshape_to_2d(alg.connected_pixels(
)) if DO_PLOT_CONNECED_PIXELS else None # np.zeros((10,10))
map4 = reshape_to_2d(alg.local_maxima(
)) if DO_PLOT_LOCAL_MAXIMUMS else None # np.zeros((10,10))
map5 = reshape_to_2d(alg.local_minima(
)) if DO_PLOT_LOCAL_MINIMUMS else None # np.zeros((10,10))
#print_arr(map3, 'map_of_connected_pixels')
#maps.shape = shape
#for i, (r0, c0, a0, sigma) in enumerate(peaks_sim) :
# print ' %04d row=%6.1f col=%6.1f amp=%6.1f sigma=%6.3f' % (i, r0, c0, a0, sigma)
#plot_image(img)
#print 'Found peaks:'
#print hdr
reg = 'IMG'
peaks_rec = []
if False:
for pk in peaks:
seg,row,col,npix,amax,atot,rcent,ccent,rsigma,csigma,\
rmin,rmax,cmin,cmax,bkgd,rms,son = pk.parameters()
#rmin,rmax,cmin,cmax,bkgd,rms,son = pk[0:17]
rec = fmt % (ev, reg, seg, row, col, npix, amax, atot, rcent, ccent, rsigma, csigma,\
rmin, rmax, cmin, cmax, bkgd, rms, son) #,\
#imrow, imcol, xum, yum, rum, phi)
peaks_rec.append((seg, row, col, amax, atot, npix))
print rec
#peaks_gen = [(0, r, c, a, a*s, 9*s*s) for r,c,a,s in peaks_sim]
#peaks_rec = [(p.seg, p.row, p.col, p.amp_max, p.amp_tot, p.npix) for p in peaks]
#s, r, c, amax, atot, npix = rec[0:6]
if DO_PLOT_CONNECED_PIXELS:
cmin, cmax = (map3.min(),
map3.max()) if map3 is not None else (None, None)
#print 'Connected pixel groups min/max:', cmin, cmax
gg.plot_imgcb(fig3,
axim3,
axcb3,
imsh3,
map3,
amin=cmin,
amax=cmax,
title='Connected pixel groups, ev: %04d' % ev1)
gg.move_fig(fig3, x0=100, y0=30)
if DO_PLOT_LOCAL_MAXIMUMS:
gg.plot_imgcb(fig4,
axim4,
axcb4,
imsh4,
map4,
amin=0,
amax=10,
title='Local maximums, ev: %04d' % ev1)
gg.move_fig(fig4, x0=200, y0=30)
if DO_PLOT_LOCAL_MINIMUMS:
gg.plot_imgcb(fig5,
axim5,
axcb5,
imsh5,
map5,
amin=0,
amax=10,
title='Local minimums, ev: %04d' % ev1)
gg.move_fig(fig5, x0=300, y0=30)
if DO_PLOT_IMAGE:
#nda = maps_of_conpix_arc
#nda = maps_of_conpix_equ
#img = det.image(evt, nda)[xoffset:xoffset+xsize,yoffset:yoffset+ysize]
#img = det.image(evt, mask_img*nda)[xoffset:xoffset+xsize,yoffset:yoffset+ysize]
#img = det.image(evt, maps_of_conpix_equ)[xoffset:xoffset+xsize,yoffset:yoffset+ysize]
ave, rms = img.mean(), img.std()
amin, amax = ave - 1 * rms, ave + 8 * rms
axim1.clear()
if imsh1 is not None: del imsh1
imsh1 = None
gg.plot_imgcb(fig1,
axim1,
axcb1,
imsh1,
img,
amin=amin,
amax=amax,
title='Image, ev: %04d' % ev1)
gg.move_fig(fig1, x0=400, y0=30)
gg.plot_peaks_on_img(peaks_gen,
axim1,
imRow,
imCol,
color='g',
lw=2) #, pbits=3)
gg.plot_peaks_on_img(peaks_rec, axim1, imRow, imCol,
color='w') #, pbits=3)
fig1.canvas.draw() # re-draw figure content
#gg.plotHistogram(nda, amp_range=(-100,100), bins=200, title='Event %d' % i)
gg.show(mode='do not hold')
gg.show()
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()
imCol = np.select([iY < yoffset], [0], default=iY - yoffset)
# Pixel coordinates [um] (transformed as needed)
Xum = det.coords_y(runnum)
Yum = -det.coords_x(runnum)
# Derived pixel raduius in [um] and angle phi[degree]
Rum = np.sqrt(Xum * Xum + Yum * Yum)
Phi = np.arctan2(Yum, Xum) * 180 / np.pi
imRow.shape = imCol.shape = \
Xum.shape = Yum.shape = \
Rum.shape = Phi.shape = det.shape()
#------------------------------
fig1, axim1, axcb1, imsh1 = gg.fig_axim_axcb_imsh(figsize=(12, 11))
#------------------------------
t0_sec_evloop = time()
nda = None
peaks = None
# loop over events in data set
myrun = next(ds.runs())
for evnum, evt in enumerate(myrun.events()):
if evnum % 100 == 0: print 'Event %d' % (evnum)
if evnum < SKIP: continue
if evnum >= EVTMAX: break
