cleanup/pylint police (90712129) · Commits · Zolnierczuk, Piotr / pysen

pysen/echo/init.py

+3 −3

Original line number	Diff line number	Diff line
		@@ -3,5 +3,5 @@ echo fit/plot module
		"""

		from .fit import fit_echo_current, Spectrum # NOQA
		from .reduce import get_symmetry_phase, reduce_echo # NOQA
		from .reduce import get_symmetry_phase, get_phase_indices # NOQA
		from .phase_table import make_phase_table # NOQA

pysen/echo/phase_table.py

+2 −4

Original line number	Diff line number	Diff line
		@@ -101,10 +101,8 @@ def make_phase_table(phtab, polyfit=0, ncur=10, nphi=11, pos='p2', threshold=0.2
		ph_int = brute_force_interpolation(phase_table, yphi, xi00, theta0, maincur)
		ph_dif = ph_int-ph_fit
		ph_rel = 100*ph_dif/ph_fit
		if abs(ph_dif) > max_abs:
		max_abs = abs(ph_dif)
		if abs(ph_rel) > max_rel:
		max_rel = abs(ph_rel)
		max_abs = max(max_abs, abs(ph_dif))
		max_rel = max(max_rel, abs(ph_rel))
		log.info("i00=%9.5f phi=%9.5f, i5_fit=%8.5f i5_tab=%8.5f i5_int=%8.5f diff=(%+.4fA, %+.3f%%)",
		maincur, theta0, ph_fit, ph_tab, ph_int, ph_dif, ph_rel)
		log.info("max(diff)=(%.4fA,%.3f%%)", max_abs, max_rel)

pysen/echo/reduce.py

+189 −183

Original line number	Diff line number	Diff line
		#!/usr/bin/env python
		"reduce echo data"

		import time
		import logging
		import numpy as np

		from .. import config, get_q, dictionary_hash
		from ..constants import NANOSECOND, ANGSTROM
		#from .. import config, get_q, dictionary_hash
		#from ..constants import NANOSECOND, ANGSTROM
		from .fit import Spectrum, fit_echo_current


		def get_phase_indices(hdfile):
		"get phase indices"
		idx = {'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		n_phases = idx['dn']
		return n_phases, idx

		def get_symmetry_phase(hdfile, iecho=None, **kwargs):
		"get the symmetry phase (for phase tables)"
		#
		@@ -19,17 +27,14 @@ def get_symmetry_phase(hdfile, iecho=None, **kwargs):
		ypix1 = kwargs.pop('ypix1', 0)
		ypix2 = kwargs.pop('ypix2', None)


		#if kwargs.get('center_only'):
		# tbin1, tbin2 = 4, -4
		# xpix1, xpix2 = 5, -5
		# ypix1, ypix2 = 5, -5

		log = logging.getLogger()

		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nph = n_idx['dn']
		nph, _ = get_phase_indices(hdfile)

		results = []
		for echo in list(hdfile['/data'].values()):
		@@ -54,22 +59,23 @@ def get_symmetry_phase(hdfile, iecho=None, **kwargs):

		phasesens = float(params['phaseangle'].attrs['sensitivities'][0])

		cur = phase['phase_current'][:, 0] # actual value
		det = phase['detector'][...]

		pcha = phase['proton_charge'][...]
		cur = phase['phase_current'][:, 0] # actual value
		pcha0 = np.average(pcha)
		pcha = pcha[:,np.newaxis,np.newaxis,np.newaxis]/float(pcha0)
		pcha = pcha/float(np.average(pcha))
		pcha = pcha[:,np.newaxis,np.newaxis,np.newaxis]
		#
		det = det/pcha
		wlen = np.sum(det, axis=(0,1,2)) # all but TOF axis
		#
		pha = det[:,ypix1:ypix2,xpix1:xpix2,tbin1:tbin2]
		epha = np.sqrt(np.sum(pha[:nph], axis=(1,2,3)))
		pha = np.sum(pha[:nph], axis=(1,2,3))
		det = det[:,ypix1:ypix2,xpix1:xpix2,tbin1:tbin2]
		edet = np.sqrt(np.sum(det[:nph], axis=(1,2,3)))
		det = np.sum(det[:nph], axis=(1,2,3))


		spectrum = Spectrum(lam=lmax[tbin1:tbin2], dlam=dlam[tbin1:tbin2], flux=wlen[tbin1:tbin2])
		(phase_ef, _), _, _ = fit_echo_current(cur[:nph], (pha, epha), spectrum,
		(phase_ef, _), _, _ = fit_echo_current(cur[:nph], (det, edet),
		Spectrum(lam=lmax[tbin1:tbin2], dlam=dlam[tbin1:tbin2], flux=wlen[tbin1:tbin2]),
		lam0=lam0, phase0=phase0, phasesens=phasesens)
		log.info("i00=%9.5f phi=%9.5f, i5_fit=%8.5f i5_set=%8.5f",
		maincur, theta0, phase_ef, phase0)
		@@ -86,170 +92,170 @@ def write_pixel(grp, name, attrs, **kwargs):
		pixel.create_dataset(key, data=val)


		def reduce_echo(hdfile, **kwargs):
		"reduce echo file"
		# reduction parameters
		rpar = {}
		rpar['npix'] = kwargs.get('npix', 4) # pix
		# default TOF range
		rpar['tbin1'] = kwargs.get('tbin1', 0)
		rpar['tbin2'] = kwargs.get('tbin2', None)
		# default center patch
		rpar['xpix1'] = kwargs.get('xpix1', 10)
		rpar['xpix2'] = kwargs.get('xpix2', 22)
		rpar['ypix1'] = kwargs.get('ypix1', 10)
		rpar['ypix2'] = kwargs.get('ypix2', 22)
		#def reduce_echo(hdfile, **kwargs):
		# "reduce echo file"
		# # reduction parameters
		# rpar = {}
		# rpar['npix'] = kwargs.get('npix', 4) # pix
		# # default TOF range
		# rpar['tbin1'] = kwargs.get('tbin1', 0)
		# rpar['tbin2'] = kwargs.get('tbin2', None)
		# # default center patch
		# rpar['xpix1'] = kwargs.get('xpix1', 10)
		# rpar['xpix2'] = kwargs.get('xpix2', 22)
		# rpar['ypix1'] = kwargs.get('ypix1', 10)
		# rpar['ypix2'] = kwargs.get('ypix2', 22)
		# #
		#

		# misc
		rpar['incoherent'] = kwargs.get('incoherent', False)
		# # misc
		# rpar['incoherent'] = kwargs.get('incoherent', False)
		# #
		# log = logging.getLogger()
		# #
		# n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		# 'up': hdfile['/'].attrs['point_to_up'] ,
		# 'nphases': hdfile['/'].attrs['no_of_phases'] }
		# nt = hdfile['/detector'].attrs['no_t_channels']
		# ny = hdfile['/detector'].attrs['no_y_channels']
		# nx = hdfile['/detector'].attrs['no_x_channels']
		# nph = n_idx['dn']
		# #
		# rpar['tbin2'] = rpar['tbin2'] or nt
		# if kwargs.get('whole_detector'):
		# rpar['xpix1'], rpar['xpix2'] = 0, nx
		# rpar['ypix1'], rpar['ypix2'] = 0, ny
		# #
		# tbin1, tbin2 = rpar['tbin1'], rpar['tbin2']
		# xpix1, xpix2 = rpar['xpix1'], rpar['xpix2']
		# ypix1, ypix2 = rpar['ypix1'], rpar['ypix2']
		#
		log = logging.getLogger()
		# rhash = dictionary_hash(rpar)
		# reduction_parameters = hdfile.require_group("reduction")
		# if reduction_parameters.attrs.get('hash') == rhash:
		# log.info('data already reduced with the same parameters')
		# return hdfile
		#
		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nt = hdfile['/detector'].attrs['no_t_channels']
		ny = hdfile['/detector'].attrs['no_y_channels']
		nx = hdfile['/detector'].attrs['no_x_channels']
		nph = n_idx['dn']
		#
		rpar['tbin2'] = rpar['tbin2'] or nt
		if kwargs.get('whole_detector'):
		rpar['xpix1'], rpar['xpix2'] = 0, nx
		rpar['ypix1'], rpar['ypix2'] = 0, ny
		#
		tbin1, tbin2 = rpar['tbin1'], rpar['tbin2']
		xpix1, xpix2 = rpar['xpix1'], rpar['xpix2']
		ypix1, ypix2 = rpar['ypix1'], rpar['ypix2']

		rhash = dictionary_hash(rpar)
		reduction_parameters = hdfile.require_group("reduction")
		if reduction_parameters.attrs.get('hash') == rhash:
		log.info('data already reduced with the same parameters')
		return hdfile

		for itau, echo in hdfile['/data'].items():
		try:
		del echo['reduced']
		except KeyError:
		pass
		reduced_data = echo.require_group('reduced')

		phase = echo['phase']
		physics = echo['phys']
		params = echo['params']
		tech = echo['tech']

		tau0 = physics.attrs['fouriertime']/NANOSECOND
		lam0 = physics.attrs['lambda']
		phase0 = float(tech.attrs['i5'][0])
		theta0 = float(tech.attrs['mophi'][0])

		try:
		lmax = params['lambdatable']
		except KeyError:
		lmax = params['lambdaTable']
		phasesens = float(params['phaseangle'].attrs['sensitivities'][0])

		lmax = np.array(lmax).flatten()
		dlam = np.ones_like(lmax)*(lmax[1]-lmax[0])
		avlam = lmax - dlam/2

		det = phase['detector'][...]*1.0
		pcha = phase['proton_charge'][...]
		cur = phase['phase_current'][:, 0] # actual value

		pcha = pcha/np.average(pcha)
		wlen = np.sum(det, axis=(0,1,2))

		YY, XX, TT = np.mgrid[ypix1:ypix2, xpix1:xpix2, tbin1:tbin2]
		theta, _ = config.pixel_angle(XX, YY, np.radians(theta0)) # theta,phi
		alam = avlam[TT]
		q_pix = get_q(alam, theta)*ANGSTROM
		tau_pix = (alam/lam0)*3tau0

		flux = np.tile(wlen[tbin1:tbin2], q_pix.shape[:-1]).reshape(q_pix.shape)
		qave = np.average(q_pix, weights=flux)
		qvar = np.sqrt(np.average((q_pix-qave)**2, weights=flux))
		tave = np.average(tau_pix, weights=flux)
		tvar = np.sqrt(np.average((tau_pix-tave)**2, weights=flux))

		spectrum = Spectrum(lam=lmax[tbin1:tbin2], dlam=dlam[tbin1:tbin2], flux=wlen[tbin1:tbin2])
		y = np.sum(det[:,xpix1:xpix2,ypix1:ypix2,tbin1:tbin2], axis=(1,2,3))
		ey = np.sqrt(y)
		y = y/pcha
		ey = ey/pcha
		#
		dn = y[nph:n_idx['up']]
		up = y[n_idx['up']:]

		(phase_ef0, phase_err) , (xef,yef), res = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,
		lam0=lam0, phase0=phase0, phasesens=phasesens,
		incoherent=rpar['incoherent'], global_fit=False)
		atari = np.sum(det, axis=(1,2))
		upave = np.average(up)
		dnave = np.average(dn)
		res['q'] = qave, qvar
		res['tau'] = tave, tvar
		res['up'] = upave, np.sqrt(np.sum(up)/len(up))
		res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))
		res['current0'] = (phase_ef0, phase_err)
		res['tbins'] = (tbin1, tbin2 or -1)
		res['pixels'] = ((xpix1, ypix1), (xpix2, ypix2))
		res['R'] = (2*res['amplitude'][0]/( upave - dnave),0) # TODO error estimate

		write_pixel(reduced_data, 'center', res,
		echo=np.vstack((cur, y, ey)), fit=np.vstack((xef, yef)),
		spectrum=spectrum, atari=atari)

		_, nx, ny, nt = det.shape
		npix = rpar['npix']
		nyy = ny//npix
		nxx = nx//npix

		reduced_data.attrs['nxpix'] = nxx
		reduced_data.attrs['nypix'] = nyy
		reduced_data.attrs['tbins'] = (tbin1, tbin2)

		pha = det.reshape(-1, nyy, npix, nxx, npix, nt)
		pha = pha.sum(axis=(2, 4)) # pixel rebin
		pha = np.sum(pha[:,:,:,tbin1:tbin2],axis=-1) # tof summation

		for j in range(nyy):
		for i in range(nxx):
		y = pha[:,i,j]
		ey = np.where(y>0, np.sqrt(y), 1) # no counts has non-zero error bar
		y = y/pcha
		ey = ey/pcha
		#
		dn = y[nph:n_idx['up']]
		up = y[n_idx['up']:]

		upave = np.average(up)
		dnave = np.average(dn)

		_ = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,
		lam0=lam0, phase0=phase_ef0,
		phasesens=phasesens, phase_pf=phase_ef0,
		incoherent=rpar['incoherent'])
		(phase_ef, phase_err) , (xef, yef), res = _
		res['current0'] = phase_ef, phase_err
		res['up'] = upave, np.sqrt(np.sum(up)/len(up))
		res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))
		res['tbins'] = tbin1, tbin2 or -1
		res['pixels'] = i+1,j+1
		res['R'] = 2*res['amplitude'][0]/( upave - dnave),0 # TODO error estimate
		write_pixel(reduced_data, 'pix-%d-%d' % (i+1,j+1), attrs=res,
		echo=np.vstack((cur, y, ey)), fit=np.vstack((xef, yef)),
		spectrum=spectrum)
		log.debug('pixel %d-%d done', i+1,j+1)
		log.info('tau=%s reduced', itau)

		#
		reduction_parameters.attrs['hash'] = rhash
		reduction_parameters.attrs['date'] = time.ctime()
		for key, value in rpar.items():
		reduction_parameters.attrs[key] = value

		return hdfile
		# for itau, echo in hdfile['/data'].items():
		# try:
		# del echo['reduced']
		# except KeyError:
		# pass
		# reduced_data = echo.require_group('reduced')
		#
		# phase = echo['phase']
		# physics = echo['phys']
		# params = echo['params']
		# tech = echo['tech']
		#
		# tau0 = physics.attrs['fouriertime']/NANOSECOND
		# lam0 = physics.attrs['lambda']
		# phase0 = float(tech.attrs['i5'][0])
		# theta0 = float(tech.attrs['mophi'][0])
		#
		# try:
		# lmax = params['lambdatable']
		# except KeyError:
		# lmax = params['lambdaTable']
		# phasesens = float(params['phaseangle'].attrs['sensitivities'][0])
		#
		# lmax = np.array(lmax).flatten()
		# dlam = np.ones_like(lmax)*(lmax[1]-lmax[0])
		# avlam = lmax - dlam/2
		#
		# det = phase['detector'][...]*1.0
		# pcha = phase['proton_charge'][...]
		# cur = phase['phase_current'][:, 0] # actual value
		#
		# pcha = pcha/np.average(pcha)
		# wlen = np.sum(det, axis=(0,1,2))
		#
		# YY, XX, TT = np.mgrid[ypix1:ypix2, xpix1:xpix2, tbin1:tbin2]
		# theta, _ = config.pixel_angle(XX, YY, np.radians(theta0)) # theta,phi
		# alam = avlam[TT]
		# q_pix = get_q(alam, theta)*ANGSTROM
		# tau_pix = (alam/lam0)*3tau0
		#
		# flux = np.tile(wlen[tbin1:tbin2], q_pix.shape[:-1]).reshape(q_pix.shape)
		# qave = np.average(q_pix, weights=flux)
		# qvar = np.sqrt(np.average((q_pix-qave)**2, weights=flux))
		# tave = np.average(tau_pix, weights=flux)
		# tvar = np.sqrt(np.average((tau_pix-tave)**2, weights=flux))
		#
		# spectrum = Spectrum(lam=lmax[tbin1:tbin2], dlam=dlam[tbin1:tbin2], flux=wlen[tbin1:tbin2])
		# y = np.sum(det[:,xpix1:xpix2,ypix1:ypix2,tbin1:tbin2], axis=(1,2,3))
		# ey = np.sqrt(y)
		# y = y/pcha
		# ey = ey/pcha
		# #
		# dn = y[nph:n_idx['up']]
		# up = y[n_idx['up']:]
		#
		# (phase_ef0, phase_err) , (xef,yef), res = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,
		# lam0=lam0, phase0=phase0, phasesens=phasesens,
		# incoherent=rpar['incoherent'], global_fit=False)
		# atari = np.sum(det, axis=(1,2))
		# upave = np.average(up)
		# dnave = np.average(dn)
		# res['q'] = qave, qvar
		# res['tau'] = tave, tvar
		# res['up'] = upave, np.sqrt(np.sum(up)/len(up))
		# res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))
		# res['current0'] = (phase_ef0, phase_err)
		# res['tbins'] = (tbin1, tbin2 or -1)
		# res['pixels'] = ((xpix1, ypix1), (xpix2, ypix2))
		# res['R'] = (2*res['amplitude'][0]/( upave - dnave),0) # TODO error estimate
		#
		# write_pixel(reduced_data, 'center', res,
		# echo=np.vstack((cur, y, ey)), fit=np.vstack((xef, yef)),
		# spectrum=spectrum, atari=atari)
		#
		# _, nx, ny, nt = det.shape
		# npix = rpar['npix']
		# nyy = ny//npix
		# nxx = nx//npix
		#
		# reduced_data.attrs['nxpix'] = nxx
		# reduced_data.attrs['nypix'] = nyy
		# reduced_data.attrs['tbins'] = (tbin1, tbin2)
		#
		# pha = det.reshape(-1, nyy, npix, nxx, npix, nt)
		# pha = pha.sum(axis=(2, 4)) # pixel rebin
		# pha = np.sum(pha[:,:,:,tbin1:tbin2],axis=-1) # tof summation
		#
		# for j in range(nyy):
		# for i in range(nxx):
		# y = pha[:,i,j]
		# ey = np.where(y>0, np.sqrt(y), 1) # no counts has non-zero error bar
		# y = y/pcha
		# ey = ey/pcha
		# #
		# dn = y[nph:n_idx['up']]
		# up = y[n_idx['up']:]
		#
		# upave = np.average(up)
		# dnave = np.average(dn)
		#
		# _ = fit_echo_current(cur[:nph], (y[:nph], ey[:nph]), spectrum,
		# lam0=lam0, phase0=phase_ef0,
		# phasesens=phasesens, phase_pf=phase_ef0,
		# incoherent=rpar['incoherent'])
		# (phase_ef, phase_err) , (xef, yef), res = _
		# res['current0'] = phase_ef, phase_err
		# res['up'] = upave, np.sqrt(np.sum(up)/len(up))
		# res['dn'] = dnave, np.sqrt(np.sum(dn)/len(dn))
		# res['tbins'] = tbin1, tbin2 or -1
		# res['pixels'] = i+1,j+1
		# res['R'] = 2*res['amplitude'][0]/( upave - dnave),0 # TODO error estimate
		# write_pixel(reduced_data, 'pix-%d-%d' % (i+1,j+1), attrs=res,
		# echo=np.vstack((cur, y, ey)), fit=np.vstack((xef, yef)),
		# spectrum=spectrum)
		# log.debug('pixel %d-%d done', i+1,j+1)
		# log.info('tau=%s reduced', itau)
		#
		# #
		# reduction_parameters.attrs['hash'] = rhash
		# reduction_parameters.attrs['date'] = time.ctime()
		# for key, value in rpar.items():
		# reduction_parameters.attrs[key] = value
		#
		# return hdfile

pysen/plot/echo.py

+7 −21

Original line number	Diff line number	Diff line
		@@ -9,6 +9,7 @@ import matplotlib.pyplot as plt
		from matplotlib import colors

		from ..constants import ANGSTROM, NANOSECOND
		from ..echo import get_phase_indices
		from .plotutil import get_nsubplots

		def plot_single_echo(ax, data, nptr, **kwargs):
		@@ -61,10 +62,7 @@ def plot_center_echo(hdfile, **kwargs):
		comment = hdfile.attrs['master_comment']
		sample = comment.split()[0]

		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nph = n_idx['dn']
		nph, n_idx = get_phase_indices(hdfile)
		miny, maxy = np.inf, 0

		fig0 = plt.figure(figsize=(8,8))
		@@ -159,10 +157,7 @@ def plot_echo_portrait(hdfile, iecho=0, **kwargs):
		comment = hdfile.attrs['master_comment']
		sample = comment.split()[0]

		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nph = n_idx['dn']
		nph, n_idx = get_phase_indices(hdfile)
		#miny, maxy = np.inf, 0

		itau = 0
		@@ -221,10 +216,7 @@ def atari_plot(hdfile, iecho=0, **kwargs):
		vmin = kwargs.pop('vmin', 0)
		vmax = kwargs.pop('vmax', None)
		#
		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nph = n_idx['dn']
		nph, n_idx = get_phase_indices(hdfile)

		log = logging.getLogger()
		log.info('plotting')
		@@ -274,17 +266,11 @@ def atari_plot(hdfile, iecho=0, **kwargs):
		img = np.sum(det[:,:,:,:], axis=(0,-1))
		if logz:
		norm = colors.LogNorm(max(1,vmin), vmax)
		im = ax.imshow(img , aspect='equal', norm=norm)
		else:
		norm = colors.Normalize(vmin, vmax)

		im = ax.imshow(img , aspect='equal', norm=norm)
		im = ax.imshow(img , aspect='equal')
		fig.colorbar(im, ax=ax)
		#ax.axvline(xpix1, color='gray')
		#ax.axhline(ypix1, color='gray')
		#ax.axvline(xpix2-1, color='gray')
		#ax.axhline(ypix2-1, color='gray')


		ax = axes[1,1]
		p = ax.errorbar(cur[:nph], edat[1,:nph], yerr=edat[2,:nph], fmt='.', lw=1)

pysen/plot/nseplotlib.py

+7 −21

Original line number	Diff line number	Diff line
		@@ -12,10 +12,10 @@ from matplotlib import colors

		from .. import config, get_q
		from ..constants import ANGSTROM, NANOSECOND, GAUSS, MICRO, OMEGA_N
		from ..echo import fit_echo_current, Spectrum
		from ..echo import fit_echo_current, Spectrum, get_phase_indices
		from ..mathutil import linear_fit
		from .plotutil import get_nsubplots, norm_pix, get_pix
		from .echo import plot_single_echo
		from .echo import plot_single_echo, get_phase_indices


		MAX_CHI2_DEFAULT_BFIELD = 1e-2 # TODO: explain the meaning of this
		@@ -29,13 +29,6 @@ def _get_lambda(params):
		lmax = params['lambdaTable']
		return np.asarray(lmax).flatten()

		#def _get_echo_phase_indices(hfile):
		# " "
		# n_idx = { 'dn': hfile['/'].attrs['point_to_down'],
		# 'up': hfile['/'].attrs['point_to_up'] ,
		# 'nphases': hfile['/'].attrs['no_of_phases'] }
		# nph = n_idx['dn']
		#
		#def _get_detector_dims(hfile):
		# " "
		# nt = hfile['/detector'].attrs['no_t_channels']
		@@ -158,14 +151,10 @@ def plot_atari(hdfile, iecho=None, **kwargs):
		#ntaus = hdfile.attrs['scan_length']
		#print(hdfile.filename)
		base = os.path.splitext(os.path.basename(hdfile.filename))[0]
		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		#ctime = hdfile['/'].attrs['preset']
		nt = hdfile['/detector'].attrs['no_t_channels']
		ny = hdfile['/detector'].attrs['no_y_channels']
		nx = hdfile['/detector'].attrs['no_x_channels']
		nph = n_idx['dn']
		nph, n_idx = get_phase_indices(hdfile)
		comment = hdfile.attrs['master_comment']

		tbin1, tbin2 = pix['tbin1'], pix['tbin2']
		@@ -244,10 +233,10 @@ def plot_atari(hdfile, iecho=None, **kwargs):
		img = np.sum(det[:,:,:,tbin1:tbin2], axis=(0,-1))
		if logz:
		norm = colors.LogNorm(max(1,vmin), vmax)
		im = ax.imshow(img , aspect='equal', norm=norm)
		else:
		norm = colors.Normalize(vmin, vmax)
		im = ax.imshow(img , aspect='equal', norm=norm)

		fig.colorbar(im, ax=ax)
		ax.axvline(xpix1, color='gray')
		ax.axhline(ypix1, color='gray')
		@@ -359,14 +348,11 @@ def plot_map(hdfile, iecho=None, **kwargs):
		#comment = hdfile.attrs['master_comment']
		#sample = comment.split()[0]

		n_idx = { 'dn': hdfile['/'].attrs['point_to_down'],
		'up': hdfile['/'].attrs['point_to_up'] ,
		'nphases': hdfile['/'].attrs['no_of_phases'] }
		nt = hdfile['/detector'].attrs['no_t_channels']
		ny = hdfile['/detector'].attrs['no_y_channels']
		nx = hdfile['/detector'].attrs['no_x_channels']
		nph = n_idx['dn']
		#miny, maxy = np.inf, 0

		nph, n_idx = get_phase_indices(hdfile)

		log.warning('maps under development')