def _plot_cal_sample(self, index):
"""
Plots a single calibration sample.
"""
self._axL.cla()
self._axR.cla()
if (index < 0) or (index >= self.num_samples):
print "Cannot access sample: %d" % index
print "Total %d samples available" % self.num_samples
return
print
print "Plotting calibration sample: %d" % index
print " (may take a moment)"
# load up the calibration sample requested
fn = self.calibration_samples[index]['filename']
d = self.calibration_samples[index]['distance'] + self.distance_offset
print " distance: %.2f mm" % d
# -- plot left panel, the assemled image with ring predictions overlaid
img = read.load_raw_image(fn)
plot.imshow_cspad( self.cspad(img), vmin=0, ax=self._axL )
# plot circles on the image, over where the powder rings should be
# note that (1000,1000) is where the center is in pixel units
# for our fxn imshow_cspads
real_expected = self.real_space(self.expected, d) / 0.10992
for r in real_expected:
blob_circ = plt_patches.Circle((1000,1000), r, fill=False, lw=1, ec='white')
self._axL.add_patch(blob_circ)
# plot beam center
beam_center = plt_patches.Circle((1000,1000), 2, fill=True, lw=1, color='r')
self._axL.add_patch(beam_center)
# --- plot the right image
n_bins = 800
bin_centers, a = self.cspad.intensity_profile(img, n_bins=n_bins)
q_bin_centers = self.reciprocal(bin_centers, d)
self._axR.plot(q_bin_centers, a / a.max(), color='orange', lw=4)
for i in range(4):
bin_centers, a = self.cspad.intensity_profile(img, n_bins=n_bins, quad=i)
a /= a.max()
a += 1.0 * i + 1.0
q_bin_centers = self.reciprocal(bin_centers, d)
self._axR.plot(q_bin_centers, a, color=plot.quad_colors[i], lw=2)
self._axR.text(0.5, -0.2, 'All Quads')
self._axR.text(0.5, 0.8, 'Quad 0')
self._axR.text(0.5, 1.8, 'Quad 1')
self._axR.text(0.5, 2.8, 'Quad 2')
self._axR.text(0.5, 3.8, 'Quad 3')
self._axR.set_ylim([-0.3, 5.3])
self._axR.vlines(self.expected, 0, a.max()*1.2, color='k', linestyles='dashed')
# self._axR.vlines(self.observed[index,:], 0, a.max(), color='r', linestyles='dashed')
self._axR.set_xlabel(r'q ($\AA^{-1}$)')
self._axR.set_ylabel('Intensity')
plt.show()
print
return
#!/usr/bin/local/python
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as plt_patches
from pypad import cspad
from pypad import utils
from pypad import read
from pypad import plot
cs1 = cspad.CSPad.load("examples/my_cspad.cspad")
cs2 = cspad.CSPad.default()
cs3 = cspad.CSPad.default()
cs3.quad_rotation[0] = 10.
cs3.quad_rotation[1] = 0.
cs3.quad_rotation[2] = 2.
cs3.quad_rotation[3] = -10.
raw_image = read.load_raw_image("examples/gold-minus490mm.h5")
fig = plt.figure()
ax = plt.subplot(121)
plot.imshow_cspad(cs3(raw_image), ax=ax, scrollable=True)
ax = plt.subplot(122)
plot.sketch_2x1s(cs3.pixel_positions, ax)
plt.show()
def _plot_cal_sample(self, index):
"""
Plots a single calibration sample.
"""
self._axL.cla()
self._axR.cla()
if (index < 0) or (index >= self.num_samples):
print "Cannot access sample: %d" % index
print "Total %d samples available" % self.num_samples
return
print
print "Plotting calibration sample: %d" % index
print " (may take a moment)"
# load up the calibration sample requested
fn = self.calibration_samples[index]['filename']
d = self.calibration_samples[index]['distance'] + self.distance_offset
print " distance: %.2f mm" % d
# -- plot left panel, the assemled image with ring predictions overlaid
img = read.load_raw_image(fn)
plot.imshow_cspad(self.cspad(img), vmin=0, ax=self._axL)
# plot circles on the image, over where the powder rings should be
# note that (1000,1000) is where the center is in pixel units
# for our fxn imshow_cspads
real_expected = self.real_space(self.expected, d) / 0.10992
for r in real_expected:
blob_circ = plt_patches.Circle((1000, 1000),
r,
fill=False,
lw=1,
ec='white')
self._axL.add_patch(blob_circ)
# plot beam center
beam_center = plt_patches.Circle((1000, 1000),
2,
fill=True,
lw=1,
color='r')
self._axL.add_patch(beam_center)
# --- plot the right image
n_bins = 800
bin_centers, a = self.cspad.intensity_profile(img, n_bins=n_bins)
q_bin_centers = self.reciprocal(bin_centers, d)
self._axR.plot(q_bin_centers, a / a.max(), color='orange', lw=4)
for i in range(4):
bin_centers, a = self.cspad.intensity_profile(img,
n_bins=n_bins,
quad=i)
a /= a.max()
a += 1.0 * i + 1.0
q_bin_centers = self.reciprocal(bin_centers, d)
self._axR.plot(q_bin_centers, a, color=plot.quad_colors[i], lw=2)
self._axR.text(0.5, -0.2, 'All Quads')
self._axR.text(0.5, 0.8, 'Quad 0')
self._axR.text(0.5, 1.8, 'Quad 1')
self._axR.text(0.5, 2.8, 'Quad 2')
self._axR.text(0.5, 3.8, 'Quad 3')
self._axR.set_ylim([-0.3, 5.3])
self._axR.vlines(self.expected,
0,
a.max() * 1.2,
color='k',
linestyles='dashed')
# self._axR.vlines(self.observed[index,:], 0, a.max(), color='r', linestyles='dashed')
self._axR.set_xlabel(r'q ($\AA^{-1}$)')
self._axR.set_ylabel('Intensity')
plt.show()
print
return
