def _set_rad_bins(self, radedges, nradbins):
rmin = math.floor(np.amin(
self.rad)) if radedges is None else radedges[0]
rmax = math.ceil(np.amax(
self.rad)) if radedges is None else radedges[-1]
if rmin < 1: rmin = 1
self.rb = HBins((rmin, rmax), nradbins)
def test_hbins():
print('In pyalgos.test_hbins')
from psana.pyalgos.generic.HBins import HBins
o = HBins((1, 6), 5)
print(' binedges():', o.binedges())
assert (np.array_equal(o.binedges(),
np.array((1, 2, 3, 4, 5, 6), dtype=np.float)))
def set_histogram_from_arr(self, arr, nbins=1000, amin=None, amax=None, frmin=0.001, frmax=0.999, edgemode=0, update_hblimits=True):
#if np.array_equal(arr, self.arr_old): return
if arr is self.arr_old: return
self.arr_old = arr
if arr.size<1: return
aravel = arr.ravel()
vmin, vmax = self.hbins.limits() if self.hbins is not None else (None, None)
if self.hbins is None or update_hblimits:
vmin = amin if amin is not None else\
aravel.min() if frmin in (0,None) else\
np.quantile(aravel, frmin, axis=0, interpolation='lower')
vmax = amax if amax is not None else\
aravel.max() if frmax in (1,None) else\
np.quantile(aravel, frmax, axis=0, interpolation='higher')
if not vmin<vmax: vmax=vmin+1
hb = HBins((vmin,vmax), nbins=nbins)
hb.set_bin_data_from_array(aravel, dtype=np.float64, edgemode=edgemode)
hmin, hmax = 0, hb.bin_data_max()
#logger.debug('set_histogram_from_arr %s\n vmin(%.5f%%):%.3f vmax(%.5f%%):%.3f hmin: %.3f hmax: %.3f'%\
# (info_ndarr(aravel, 'arr.ravel'), frmin,vmin,frmax,vmax,hmin,hmax))
hgap = 0.05*(hmax-hmin)
rs0 = self.scene().sceneRect()
rsy, rsh = (hb.vmin(), hb.vmax()-hb.vmin()) if update_hblimits else (rs0.y(), rs0.height())
rs = QRectF(hmin-hgap, rsy, hmax-hmin+2*hgap, rsh)
self.set_rect_scene(rs, set_def=update_hblimits)
self.update_my_scene(hbins=hb)
self.hbins = hb
def test_histogram():
import psana.pyalgos.generic.NDArrGenerators as ag
from psana.pyalgos.generic.HBins import HBins
nbins = 1000
arr = ag.random_standard((nbins,), mu=50, sigma=10, dtype=ag.np.float64)
hb = HBins((0,nbins), nbins=nbins)
hb.set_bin_data(arr, dtype=ag.np.float64)
return hb
def _set_phi_bins(self, phiedges, nphibins):
if phiedges[-1] > phiedges[0]+360\
or phiedges[-1] < phiedges[0]-360:
raise ValueError('Difference between angular edges should not exceed 360 degree;'\
' phiedges: %.0f, %.0f' % (phiedges[0], phiedges[-1]))
self.pb = HBins(phiedges, nphibins)
phi1, phi2 = self.pb.limits()
self.is360 = math.fabs(math.fabs(phi2 - phi1) - 360) < 1e-3
def proc_waveforms(self, wfs, wts) :
"""
"""
# if waveforms are already processed
if wfs is self._wfs_old : return
self._init_arrays()
#print_ndarr(wfs, ' waveforms : ', last=4)
assert (self.NUM_CHANNELS==wfs.shape[0]),\
'expected number of channels in not consistent with waveforms array shape'
if self.VERSION == 2 : std = wfs[:,self.IOFFSETBEG:self.IOFFSETEND].std(axis=1)
if self.VERSION == 4:
self.wfsprep = wfs[:,self.WFBINBEG:self.WFBINEND]
else:
offsets = wfs[:,self.IOFFSETBEG:self.IOFFSETEND].mean(axis=1)
#print(' XXX offsets: %s' % str(offsets))
self.wfsprep = wfs[:,self.WFBINBEG:self.WFBINEND] - offsets.reshape(-1, 1) # subtract wf-offset
self.wtsprep = wts[:,self.WFBINBEG:self.WFBINEND] # sec
for ch in range(self.NUM_CHANNELS) :
wf = self.wfsprep[ch,:]
wt = self.wtsprep[ch,:]
npeaks = None
if self.VERSION == 3 :
npeaks, self.wfgi, self.wff, self.wfg, self.thrg, self.edges =\
peak_finder_v3(wf, self.SIGMABINS, self.BASEBINS, self.NSTDTHR, self.GAPBINS, self.DEADBINS,\
self._pkvals[ch,:], self._pkinds[ch,:])
elif self.VERSION == 2 :
self.THR = self.NSTDTHR*std[ch]
npeaks = peak_finder_v2(wf, self.SIGMABINS, self.THR, self.DEADBINS,\
self._pkvals[ch,:], self._pkinds[ch,:])
elif self.VERSION == 4 :
t_list = self.PyCFDs[ch].CFD(wf,wt)
npeaks = self._pkinds[ch,:].size if self._pkinds[ch,:].size<=len(t_list) else len(t_list)
# need it in V4 to convert _pktsec to _pkinds and _pkvals
if self.tbins is None :
from psana.pyalgos.generic.HBins import HBins
self.tbins = HBins(list(wt))
else : # self.VERSION == 1
npeaks = wfpkfinder_cfd(wf, self.BASE, self.THR, self.CFR, self.DEADTIME, self.LEADINGEDGE,\
self._pkvals[ch,:], self._pkinds[ch,:])
#print(' npeaks:', npeaks)
#assert (npeaks<self.NUM_HITS), 'number of found peaks exceeds reserved array shape'
if npeaks>=self.NUM_HITS : npeaks = self.NUM_HITS
self._number_of_hits[ch] = npeaks
if self.VERSION == 4 :
self._pktsec[ch, :npeaks] = np.array(t_list)[:npeaks]
else:
self._pktsec[ch, :npeaks] = wt[self._pkinds[ch, :npeaks]] #sec
self._wfs_old = wfs
def do_work():
prefix = './%s-figs-ti_vs_tj' % gu.str_tstamp(
fmt='%Y-%m-%d', time_sec=None) # '%Y-%m-%dT%H:%M:%S%z'
gu.create_directory(prefix, mode=0o775)
path = os.path.abspath(os.path.dirname(__file__))
print('path to npy flies dir:', path)
ti_vs_tj = np.load('%s/ti_vs_tj.npy' % path)
t_all = np.load('%s/t_all.npy' % path)
trange = (1400., 2900.)
print_ndarr(ti_vs_tj, 'ti_vs_tj:\n')
print_ndarr(t_all, 't_all:\n')
sum_bkg = t_all.sum()
sum_cor = ti_vs_tj.sum()
print('sum_bkg:', sum_bkg)
print('sum_cor:', sum_cor)
imrange = trange + trange # (1400., 2900., 1400., 2900.)
axim = gr.plotImageLarge(ti_vs_tj, img_range=imrange, amp_range=(0,500), figsize=(11,10),\
title='ti_vs_tj', origin='lower', window=(0.10, 0.08, 0.88, 0.88), cmap='inferno')
gr.save('%s/fig-ti_vs_tj.png' % prefix)
bkg = np.outer(t_all, t_all) / sum_bkg
print_ndarr(bkg, 'bkg:\n')
axim = gr.plotImageLarge(bkg, img_range=imrange, amp_range=(0,500), figsize=(11,10),\
title='bkg', origin='lower', window=(0.10, 0.08, 0.88, 0.88), cmap='inferno')
gr.save('%s/fig-ti_vs_tj-bkg.png' % prefix)
harr = t_all
nbins = harr.size
ht = HBins(trange, nbins, vtype=np.float32) # ht.binedges()
fig, axhi, hi = gr.hist1d(ht.bincenters(), bins=nbins, amp_range=ht.limits(), weights=harr, color='b', show_stat=True,\
log=True, figsize=(7,6), axwin=(0.10, 0.10, 0.88, 0.85), title='1-d bkg',\
xlabel='time of all hits (ns)', ylabel='number of hits', titwin='1-d bkg')
gr.save('%s/fig-time-hits.png' % prefix)
gr.show()
def __init__(self, proc, **kwargs):
self.proc = proc
logger.info('In set_parameters, **kwargs: %s' % str(kwargs))
self.STAT_NHITS = kwargs.get('STAT_NHITS', True)
self.STAT_TIME_CH = kwargs.get('STAT_TIME_CH', True)
self.STAT_UVW = kwargs.get('STAT_UVW', True)
self.STAT_TIME_SUMS = kwargs.get('STAT_TIME_SUMS', True)
self.STAT_CORRELATIONS = kwargs.get('STAT_CORRELATIONS', True)
self.STAT_XY_COMPONENTS = kwargs.get('STAT_XY_COMPONENTS', True)
self.STAT_XY_2D = kwargs.get('STAT_XY_2D', True)
self.STAT_MISC = kwargs.get('STAT_MISC', True)
self.STAT_REFLECTIONS = kwargs.get('STAT_REFLECTIONS', True)
self.STAT_PHYSICS = kwargs.get('STAT_PHYSICS', True)
self.STAT_XY_RESOLUTION = kwargs.get('STAT_XY_RESOLUTION',
False) # not available for QUAD
if self.STAT_TIME_CH:
self.lst_u1 = []
self.lst_u2 = []
self.lst_v1 = []
self.lst_v2 = []
self.lst_w1 = []
self.lst_w2 = []
self.lst_mcp = []
if self.STAT_NHITS:
self.lst_nhits_u1 = []
self.lst_nhits_u2 = []
self.lst_nhits_v1 = []
self.lst_nhits_v2 = []
self.lst_nhits_w1 = []
self.lst_nhits_w2 = []
self.lst_nhits_mcp = []
self.lst_nparts = []
if self.STAT_UVW or self.STAT_CORRELATIONS:
self.lst_u_ns = []
self.lst_v_ns = []
self.lst_w_ns = []
self.lst_u = []
self.lst_v = []
self.lst_w = []
if self.STAT_TIME_SUMS or self.STAT_CORRELATIONS:
self.lst_time_sum_u = []
self.lst_time_sum_v = []
self.lst_time_sum_w = []
self.lst_time_sum_u_corr = []
self.lst_time_sum_v_corr = []
self.lst_time_sum_w_corr = []
if self.STAT_XY_COMPONENTS:
self.lst_Xuv = []
self.lst_Xuw = []
self.lst_Xvw = []
self.lst_Yuv = []
self.lst_Yuw = []
self.lst_Yvw = []
if self.STAT_MISC:
self.list_dr = []
self.lst_consist_indicator = []
self.lst_rec_method = []
if self.STAT_XY_RESOLUTION:
self.lst_binx = []
self.lst_biny = []
self.lst_resol_fwhm = []
if self.STAT_REFLECTIONS:
self.lst_refl_u1 = []
self.lst_refl_u2 = []
self.lst_refl_v1 = []
self.lst_refl_v2 = []
self.lst_refl_w1 = []
self.lst_refl_w2 = []
if self.STAT_XY_2D:
# images
nbins = 360
self.img_x_bins = HBins((-45., 45.), nbins, vtype=np.float32)
self.img_y_bins = HBins((-45., 45.), nbins, vtype=np.float32)
self.img_xy_uv = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_uw = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_vw = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_1 = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_2 = np.zeros((nbins, nbins), dtype=np.float32)
if self.STAT_PHYSICS:
t_ns_nbins = 300
self.t_ns_bins = HBins((1400., 2900.),
t_ns_nbins,
vtype=np.float32)
#self.t1_vs_t0 = np.zeros((t_ns_nbins, t_ns_nbins), dtype=np.float32)
self.ti_vs_tj = np.zeros((t_ns_nbins, t_ns_nbins),
dtype=np.float32)
self.t_all = np.zeros((t_ns_nbins, ), dtype=np.float32)
self.lst_t_all = []
x_mm_nbins = 200
y_mm_nbins = 200
r_mm_nbins = 200
self.x_mm_bins = HBins((-50., 50.), x_mm_nbins, vtype=np.float32)
self.y_mm_bins = HBins((-50., 50.), y_mm_nbins, vtype=np.float32)
self.r_mm_bins = HBins((-50., 50.), r_mm_nbins, vtype=np.float32)
#self.x_vs_t0 = np.zeros((x_mm_nbins, t_ns_nbins), dtype=np.float32)
#self.y_vs_t0 = np.zeros((y_mm_nbins, t_ns_nbins), dtype=np.float32)
self.rsx_vs_t = np.zeros((r_mm_nbins, t_ns_nbins),
dtype=np.float32)
self.rsy_vs_t = np.zeros((r_mm_nbins, t_ns_nbins),
dtype=np.float32)
def __init__(self):
# set default parameters
self.set_parameters()
if self.PLOT_TIME_CH:
self.lst_u1 = []
self.lst_u2 = []
self.lst_v1 = []
self.lst_v2 = []
self.lst_w1 = []
self.lst_w2 = []
self.lst_mcp = []
if self.PLOT_NHITS:
self.lst_nhits_u1 = []
self.lst_nhits_u2 = []
self.lst_nhits_v1 = []
self.lst_nhits_v2 = []
self.lst_nhits_w1 = []
self.lst_nhits_w2 = []
self.lst_nhits_mcp = []
self.lst_nparts = []
if self.PLOT_UVW or self.PLOT_CORRELATIONS:
self.lst_u_ns = []
self.lst_v_ns = []
self.lst_w_ns = []
self.lst_u = []
self.lst_v = []
self.lst_w = []
if self.PLOT_TIME_SUMS or self.PLOT_CORRELATIONS:
self.lst_time_sum_u = []
self.lst_time_sum_v = []
self.lst_time_sum_w = []
self.lst_time_sum_u_corr = []
self.lst_time_sum_v_corr = []
self.lst_time_sum_w_corr = []
if self.PLOT_XY_COMPONENTS:
self.lst_Xuv = []
self.lst_Xuw = []
self.lst_Xvw = []
self.lst_Yuv = []
self.lst_Yuw = []
self.lst_Yvw = []
if self.PLOT_MISC:
self.list_dr = []
self.lst_consist_indicator = []
self.lst_rec_method = []
#if self.PLOT_XY_RESOLUTION :
# self.lst_binx = []
# self.lst_biny = []
# self.lst_resol_fwhm = []
if self.PLOT_REFLECTIONS:
self.lst_refl_u1 = []
self.lst_refl_u2 = []
self.lst_refl_v1 = []
self.lst_refl_v2 = []
self.lst_refl_w1 = []
self.lst_refl_w2 = []
if self.PLOT_XY_2D:
# images
nbins = 360
self.img_x_bins = HBins((-45., 45.), nbins, vtype=np.float32)
self.img_y_bins = HBins((-45., 45.), nbins, vtype=np.float32)
self.img_xy_uv = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_uw = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_vw = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_1 = np.zeros((nbins, nbins), dtype=np.float32)
self.img_xy_2 = np.zeros((nbins, nbins), dtype=np.float32)
if self.PLOT_PHYSICS:
t_ns_nbins = 300
self.t_ns_bins = HBins((1400., 2900.),
t_ns_nbins,
vtype=np.float32)
#self.t1_vs_t0 = np.zeros((t_ns_nbins, t_ns_nbins), dtype=np.float32)
self.ti_vs_tj = np.zeros((t_ns_nbins, t_ns_nbins),
dtype=np.float32)
self.t_all = np.zeros((t_ns_nbins, ), dtype=np.float32)
self.lst_t_all = []
x_mm_nbins = 200
y_mm_nbins = 200
r_mm_nbins = 200
self.x_mm_bins = HBins((-50., 50.), x_mm_nbins, vtype=np.float32)
self.y_mm_bins = HBins((-50., 50.), y_mm_nbins, vtype=np.float32)
self.r_mm_bins = HBins((-50., 50.), r_mm_nbins, vtype=np.float32)
#self.x_vs_t0 = np.zeros((x_mm_nbins, t_ns_nbins), dtype=np.float32)
#self.y_vs_t0 = np.zeros((y_mm_nbins, t_ns_nbins), dtype=np.float32)
self.rsx_vs_t = np.zeros((r_mm_nbins, t_ns_nbins),
dtype=np.float32)
self.rsy_vs_t = np.zeros((r_mm_nbins, t_ns_nbins),
dtype=np.float32)
