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nei_beam_parameters.py
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nei_beam_parameters.py
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from near_edge_imaging import *
import math
import scipy.constants as C
def nei_beam_parameters(beam_files, setup, detector, fix_vertical_motion=False,
clip=False, no_fit=False, Verbose=False, poly_degree=5):
'''
Unit of exy in the returned parameters: keV
:param sub_dir:
:param setup:
:param detector:
:param fix_vertical_motion:
:param clip:
:param no_fit:
:param Verbose:
:param poly_degree:
:return:
'''
hkl = setup.hkl
chi_degrees = setup.chi_degrees
energy = setup.energy # edge energy
dist_fd = setup.dist_fd
diffraction_plane = setup.diffaction_plane
e_range = setup.energy_range
pixel = detector.pixel
pct_max = detector.pct_max
############### physics in the crystal #################
chi = math.radians(chi_degrees)
a0 = 5.4305 # Unit: Angstroms ##silicon crystal unit cell length at 300K.
# This is usually used as the internal standard for silicon
e_edge = energy
d_hkl = a0 / math.sqrt((np.array(hkl) ** 2).sum())
# C.c: speed of light, C.h: planck constant, C.eV: eV to Joer
lamb = (C.c * C.h / C.eV) / (e_edge * 1000) * (10 ** 10) # WaveLength, Unit: Angstroms
theta_b = math.asin(lamb / (2 * d_hkl)) # lambda = 2d*sin(theta)
print('(nei_beam_parameters) Bragg angle in degree:\n'
' ', round(theta_b * 180 / math.pi, 3))
####### Get beam_files ################################
flat = beam_files.flat
dark = beam_files.dark
edge = beam_files.edge
beam_shape = flat.shape
ny = beam_shape[0]
nx = beam_shape[1]
x_range = np.arange(nx)
y_range = np.arange(ny)
edge_dark = edge - dark # dark corrected edge
flat_dark = flat - dark # dark corrected flat
########## Determine the beam size we want to keep ################################
thresh = pct_max / 100.0
print('(nei_beam_parameters) Running "beam_edges"')
beam_position = beam_edges(flat_dark, thresh, no_fit=no_fit, poly_deg=poly_degree)
beam = beam_position.beam # 2D array (image), trimmed top and bottom to remove the darker part vertically
beam_top = beam_position.top
beam_bot = beam_position.bot
beam_peak = beam_position.peak
if diffraction_plane.lower() == 'horizontal':
raise Exception('"Diffraction plane: horizontal" has '
'not been set up for nei_beam_parameters. Come back in future.')
################ Find absorption edge y_positions ############################
r = edge_dark / flat_dark
mu_t = -np.log(r)
mu_t_median = np.median(mu_t, axis=1)
deriv_med = abs(np.gradient(mu_t_median))
deriv_med = beam.mean(axis=1)*deriv_med # get rid of part of the beam with weak signal, to fix issue with finding the peak (2020-03-15T13:15:22-06:00)
mu_t_smooth = median_filter(mu_t, [10, 5])
deriv_all = abs(np.gradient(mu_t_smooth, axis=0))
deriv_fwhm = mp.fwhm(np.arange(ny), deriv_med)
conv_filter = deriv_med[deriv_fwhm[1]:deriv_fwhm[2]] # fwhm[1]: left side of fwhm; fwhm[2]: right side of fwhm
if Verbose:
plt.plot(conv_filter)
deriv_conv = []
def do_convolve(x, deriv_all, conv_filter):
deriv_x = deriv_all[:, x]
conv = np.convolve(deriv_x, conv_filter, 'same') # Convolution filter used here. See Notes for details.
return conv
for x in range(nx):
try:
conv = do_convolve(x,deriv_all,conv_filter)
except:
conv = do_convolve(x-1,deriv_all,conv_filter)
deriv_conv.append(conv)
deriv_conv = np.array(deriv_conv).T
edge_positions_origin = deriv_conv.argmax(axis=0)
###### polynomial fit for edge_positions
edge_positions = mp.polyfit(np.arange(nx), median_filter(edge_positions_origin, 3), degree=5)
edge_positions = np.round(edge_positions).astype(int)
############## flat beam as filter to amplify center#############
# mu_t = -np.log(r*beam+(1.0-beam))
# deriv_mut = []
# for i in range(nx):
# top_value = mu_t[beam_top[i], i]
# bot_value = mu_t[beam_bot[i], i]
# mu_t[0:beam_bot[i], i] = bot_value
# mu_t[beam_top[i]:, i] = top_value
# deriv = median_filter(np.abs(np.gradient(mu_t[:, i])), 5)
# deriv = np.array(deriv) * filter # beam center amplified here
# deriv_mut.append(deriv)
# deriv_mut = np.array(deriv_mut).T
# deriv_mut = median_filter(deriv_mut, [5, 20])
# edge_positions = deriv_mut.argmax(axis=0)
##################################################################
if Verbose == True:
plt.plot(deriv_all[:, 0], label='One spectrum derivative')
plt.plot(deriv_med, label='Median derivative')
plt.title('nei_beam_parameters: $\mu t$ & derivatives')
plt.twinx()
plt.plot(mu_t[:, 0], color='y', alpha=0.4, label='$\mu t$')
plt.show()
plt.figure()
plt.imshow(mu_t)
plt.plot(edge_positions, label='edge_positions')
plt.show()
################ Find fwhm and then gaussian with as the edge width##
################ To be fixed not sure what is the best way to get the correct real values
# get edge_widths by calculating fwhm for derivative of each spectrum
# It could have false values on left and right end when noise is too much
# fwhms = []
# for i in range(nx):
# fwhms.append(mp.fwhm(np.arange(ny),deriv_mut[:,i])[0])
# fwhms = np.array(fwhms)
# edge_widths = fwhms/(2*np.sqrt(2*np.log(2)))
# get gaussian_edge_width by calculating the median fwhm for the whole mu_t image
fw = mp.fwhm(np.arange(ny), deriv_med)[0]
edge_width = fw / (2 * np.sqrt(2 * np.log(2)))
# fit the edge and peak with a 1st order polynomial to get slope of beam
# for chi and bragg angle corrections.
# If it is bad, we cannot change it in software(maybe we can??), we have to change the hardware
# setting on the beamline. So that these variable are only useful during the experiment
edge_slope = np.polyfit(x_range, edge_positions, deg=1)[0] # K-Edge y values
peak_slope = np.polyfit(x_range, beam_peak, deg=1)[0] # Peak of beam y values
# get mean values for edge and peak
edge_mean = edge_positions.mean()
peak_mean = beam_peak.mean()
######### align pixel with energy values ####################
'''
edge_positions-y_index: get the relative position to edge. Use matrix to do it
exy is the energy(keV) at every [y,x] location
10**10 is used to line up the unit to Angstrom
'''
y_relative = edge_positions - y_range.reshape((ny, 1))
exy = (C.h * C.c / C.eV) * 10 ** 10 / (2 * d_hkl * np.sin(theta_b + 0.5 * np.arctan(y_relative * pixel / dist_fd)))
exy = exy / 1000 # change the unit to keV
########### If e_range is set, use the set values #################
if (type(e_range) == list) & (e_range[0] >= 0) & (e_range[1] > e_range[0]):
# if e_range is set with reasonable number, then use the e_range to define beam top and bottom
print('(nei_beam_parameters) Selected energy range is limited to: \n'
' ', e_range,'keV')
beam[:, :] = 0.0
range_index = np.where((exy >= (e_range[0])) & (exy <= (e_range[1])))
if len(range_index) > 0:
beam[range_index] = 1.0
top = []
bot = []
for x in x_range:
beam_inrange = np.where(beam[:, x] > 0)[0]
top.append(beam_inrange.max())
bot.append(beam_inrange.min())
beam_top = np.array(top)
beam_bot = np.array(bot)
else:
raise ValueError('(nei_beam_parameters) The wanted energy range is not available. '
'Please change to a reasonable range, or reset range to [0,0] '
'to use the whole available energy range')
############ calculate gaussian width in terms of Energy #############
# energy at the absorption edge
edge_energies = np.array([exy[edge_positions[i], i] for i in x_range])
# energy of one pixel away from edge
edge1_energies = np.array([exy[edge_positions[i] + 1, i] for i in x_range])
e_per_pixel = abs(edge_energies - edge1_energies).mean()
e_width = edge_width * e_per_pixel # gaussian edge width in terms of ENERGY
# In IDL, we also had the std from gaussian width
print('(nei_beam_parameters) Gaussian Width measured from Edge Images: ')
print(' Energy Width(eV) = ', round(e_width * 1000, 2))
print(' Pixel Width = ', round(edge_width, 2))
####################### Todo: Fix Vertical Motion ############################
'''
;since beam seems to move vertically, a non-vertical motion affected flat can be created if keyword FIX_VERTICAL_MOTION is set
; this flat is used to I/Io correct the data
if keyword_set( FIX_VERTICAL_MOTION ) then flt = find_best_average_flat(flat_path, dark)
;'''
##################### wrap up things to return #########################
class Edges:
def __init__(self, beam_top, beam_bot, beam_peak, edge_positions):
self.top = beam_top
self.bot = beam_bot
self.peak = beam_peak
self.edge = edge_positions
edges = Edges(beam_top, beam_bot, beam_peak, edge_positions)
class Parameters:
def __init__(self, beam_files, beam, edges, mu_t, edge_width, edge_slope, peak_slope, exy,
e_per_pixel, e_width):
self.beam_files = beam_files
self.beam = beam
self.edges = edges
self.mu_t = mu_t
self.pixel_edge_width = edge_width
self.e_per_pixel = e_per_pixel
self.e_width = e_width
self.edge_slope = edge_slope
self.peak_slope = peak_slope
self.exy = exy
beam_parameters = Parameters(beam_files, beam, edges, mu_t, edge_width, edge_slope, peak_slope, exy,
e_per_pixel, e_width)
print('(nei_beam_parameters) Finished "nei_beam_parameters"')
return beam_parameters
def get_beam_parameters(path='', e_range=0, Verbose=False):
"""
This function is used to quickly obtain beam parameters.
:param path:
:param e_range:
:param Verbose:
:return: beam_parameters
"""
############## get Path for experiment data file ################
if path == '':
path = choose_path()
print("Data directory: ", path)
path = Path(path)
############# get system setup info from arrangement.dat ##########
setup = nei_get_arrangement(path=path,arrangement_type='file')
detector = setup.detector
# redefine energy_range if needed
if e_range != 0: setup.energy_range = e_range
######## get beam files: averaged flat, dark, and edge ############
beam_files = get_beam_files(path=path, Verbose=Verbose)
######## get beam parameters ####################################
beam_parameters = nei_beam_parameters(beam_files=beam_files,
setup=setup, detector=detector,
fix_vertical_motion=False,
clip=False, Verbose=Verbose)
return beam_parameters