[broken] An almost correct diffraction calibration notebook

In [1]:

    

import matplotlib
%matplotlib notebook
import matplotlib.pyplot as plt
from matplotlib.patches import Circle
from matplotlib.colors import LogNorm
from copy import copy


    

In [2]:

    

import skxray
from skxray.core.image import find_ring_center_acorr_1D
from skxray.core.utils import bin_1D, radial_grid, bin_edges_to_centers
from skxray.core.calibration import estimate_d_blind, refine_center
import numpy as np
from pims.tiff_stack import TiffStack_tifffile as TiffStack
import os.path
pixel_size = (.2, .2)


    

In [3]:

    

def estimate_d(img, name, wavelength, pixel_size):
    # find the
    res = find_ring_center_acorr_1D(img)
    res2 = refine_center(img, res, pixel_size, 25, 5, thresh=0.1, window_size=5)
    bins, sums, counts = img_to_relative_xyi(img, res2, radial_grid)

    mask = counts > 10
    bin_centers = bin_edges_to_centers(bins)[mask]
    ring_averages = sums[mask] / counts[mask]

    d_mean, d_std = estimate_d_blind(name,wavelength, bin_centers,
                                     ring_averages, 5, 7, thresh=0.03)
    return d_mean, d_std, res2


def show_rings_on_image(ax, image, ring_radius, center):
    vmin, vmax = np.percentile(image, [80, 100])
    my_cmap = copy(matplotlib.cm.get_cmap('gray'))
    my_cmap.set_bad('k')
    im = ax.imshow(image, cmap=my_cmap, interpolation='none', norm=LogNorm(), vmin=vmin, vmax=vmax)
    for r in ring_radius:
        c = Circle(center[::-1], r , facecolor='none', edgecolor='r', lw=2, linestyle='dashed')
        ax.add_patch(c)
    ax.axhline(center[0], color='r')
    ax.axvline(center[1], color='r')

    ax.set_ylim([center[0] - ring_radius[-1], center[0] + ring_radius[-1]])
    ax.set_xlim([center[1] - ring_radius[-1], center[1] + ring_radius[-1]])


    

In [4]:

    

si_fname = 'Si_STD_d204-00002.tif'
si_name = 'Si'
si_wavelength = 0.1839
si_data = TiffStack(si_fname)


    

In [6]:

    

lab6_fname = 'LaB6_d500-0p72959-2Kx2K_pix200.tif'
lab6_name = 'LaB6'
lab6_wavelength = .72959
lab6_data = TiffStack(lab6_fname)


    

In [7]:

    

calib_si = estimate_d(si_data[0], si_name, si_wavelength, pixel_size)
print("D: {} ± {}".format(calib_si[0], calib_si[1]))
print("center: {}".format(calib_si[2]))


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-7-23f8c796d9eb> in <module>()
----> 1 calib_si = estimate_d(si_data[0], si_name, si_wavelength, pixel_size)
      2 print("D: {} ± {}".format(calib_si[0], calib_si[1]))
      3 print("center: {}".format(calib_si[2]))

<ipython-input-3-5285f337cdcd> in estimate_d(img, name, wavelength, pixel_size)
      3     res = find_ring_center_acorr_1D(img)
      4     res2 = refine_center(img, res, pixel_size, 25, 5, thresh=0.1, window_size=5)
----> 5     bins, sums, counts = img_to_relative_xyi(img, res2, radial_grid)
      6 
      7     mask = counts > 10

NameError: name 'img_to_relative_xyi' is not defined





    




> <ipython-input-3-5285f337cdcd>(5)estimate_d()
      4     res2 = refine_center(img, res, pixel_size, 25, 5, thresh=0.1, window_size=5)
----> 5     bins, sums, counts = img_to_relative_xyi(img, res2, radial_grid)
      6 

ipdb> exit

In [19]:

    

cal_si = skxray.core.calibration.calibration_standards['Si']
si_rings = calib_si[0] * np.tan(cal_si.convert_2theta(si_wavelength)) / .2
fig, ax = plt.subplots()
show_rings_on_image(ax, si_data[0], si_rings, calib_si[2])
plt.show()


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-19-5678e9ce36f3> in <module>()
      1 cal_si = skxray.core.calibration.calibration_standards['Si']
----> 2 si_rings = calib_si[0] * np.tan(cal_si.convert_2theta(si_wavelength)) / .2
      3 fig, ax = plt.subplots()
      4 show_rings_on_image(ax, si_data[0], si_rings, calib_si[2])
      5 plt.show()

NameError: name 'calib_si' is not defined

In [20]:

    

calib_lab6 = estimate_d(lab6_data[0], lab6_name, lab6_wavelength, pixel_size)
print("D: {} ± {}".format(calib_lab6[0], calib_lab6[1]))
print("center: {}".format(calib_lab6[2]))


    

    




---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-20-0b8ac6a41d12> in <module>()
----> 1 calib_lab6 = estimate_d(lab6_data[0], lab6_name, lab6_wavelength, pixel_size)
      2 print("D: {} ± {}".format(calib_lab6[0], calib_lab6[1]))
      3 print("center: {}".format(calib_lab6[2]))

<ipython-input-9-cafae1b71ba8> in estimate_d(img, name, wavelength, pixel_size)
      5     bins, sums, counts = bin_1D(img,
      6                                 res2,
----> 7                                 radial_grid)
      8 
      9     mask = counts > 10

/home/edill/dev/python/scikit-xray/skxray/core/utils.py in bin_1D(x, y, nx, min_x, max_x)
    594 
    595     # use a weighted histogram to get the bin sum
--> 596     bins = np.linspace(start=min_x, stop=max_x, num=nx+1, endpoint=True)
    597     val, _ = np.histogram(a=x, bins=bins, weights=y)
    598     # use an un-weighted histogram to get the counts

TypeError: unsupported operand type(s) for +: 'function' and 'int'

In [ ]:

    

cal_lab6 = nsls2.calibration.calibration_standards['LaB6']\n",
lab6_rings = calib_lab6[0] * np.tan(cal_lab6.convert_2theta(lab6_wavelength)) / .2\n",
fig, ax = plt.subplots()\n",
show_rings_on_image(ax, lab6_data[0], lab6_rings, calib_lab6[2])\n",
ax.set_xlim([0, lab6_data.frame_shape[0]])\n",
ax.set_ylim([0, lab6_data.frame_shape[1]])\n",
plt.show()