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#!/usr/bin/env python
#
# Determine mean detector shift based on prediction refinement results
#
# Copyright (c) 2015 Deutsches Elektronen-Synchrotron DESY,
# a research centre of the Helmholtz Association.
#
# Author:
# 2015 Thomas White <taw@physics.org>
#
import sys
import os
import re
import matplotlib.pyplot as plt
f = open(sys.argv[1], 'r')
if len(sys.argv) > 2:
geom = sys.argv[2]
have_geom = 1
else:
have_geom = 0
# Determine the mean shifts
x_shifts = []
y_shifts = []
z_shifts = []
prog1 = re.compile("^predict_refine/det_shift\sx\s=\s([0-9\.\-]+)\sy\s=\s([0-9\.\-]+)\smm$")
prog2 = re.compile("^predict_refine/clen_shift\s=\s([0-9\.\-]+)\smm$")
while True:
fline = f.readline()
if not fline:
break
match = prog1.match(fline)
if match:
xshift = float(match.group(1))
yshift = float(match.group(2))
x_shifts.append(xshift)
y_shifts.append(yshift)
match = prog2.match(fline)
if match:
zshift = float(match.group(1))
z_shifts.append(zshift)
f.close()
if len(x_shifts) != len(z_shifts):
print 'Warning: number of xy shifts not equal to number of z shifts'
n = len(z_shifts)
z_shifts = [t for t in z_shifts if abs(t) < 2.0]
if len(z_shifts) < n:
print 'Warning: %i camera length shifts of more than 2 mm ignored' \
% (n-len(z_shifts))
mean_x = sum(x_shifts) / len(x_shifts)
mean_y = sum(y_shifts) / len(y_shifts)
mean_z = sum(z_shifts) / len(z_shifts)
print 'From %i measurements:' % len(x_shifts)
print 'Mean shifts: dx = %.2f mm, dy = %.2f mm; dz = %.2f mm' \
% (mean_x,mean_y,mean_z)
# Apply shifts to geometry
if have_geom:
out = os.path.splitext(geom)[0]+'-predrefine.geom'
print 'Applying corrections to %s, output filename %s' % (geom,out)
g = open(geom, 'r')
h = open(out, 'w')
prog1 = re.compile("^\s*res\s+=\s+([0-9\.]+)\s")
prog2 = re.compile("^\s*(.*)\/res\s+=\s+([0-9\.]+)\s")
prog3 = re.compile("^\s*(.*)\/corner_x\s+=\s+([0-9\.\-]+)\s")
prog4 = re.compile("^\s*(.*)\/corner_y\s+=\s+([0-9\.\-]+)\s")
default_res = 0
while True:
fline = g.readline()
if not fline:
break
match = prog1.match(fline)
if match:
default_res = float(match.group(1))
print 'default res %f' % (default_res)
h.write(fline)
continue
match = prog2.match(fline)
if match:
panel = match.group(1)
panel_res = float(match.group(2))
print 'panel res %s / %f' % (panel, panel_res)
h.write(fline)
continue
match = prog3.match(fline)
if match:
panel = match.group(1)
panel_cnx = float(match.group(2))
res = default_res # FIXME!
h.write('%s/corner_x = %f\n' % (panel,panel_cnx+(mean_x*res*1e-3)))
continue
match = prog4.match(fline)
if match:
panel = match.group(1)
panel_cny = float(match.group(2))
res = default_res # FIXME!
h.write('%s/corner_y = %f\n' % (panel,panel_cny+(mean_y*res*1e-3)))
continue
h.write(fline)
g.close()
h.close()
plt.suptitle('Detector shifts according to prediction refinement')
plt.subplot(121, autoscale_on=False, aspect='equal')
plt.plot(x_shifts, y_shifts, 'rx')
plt.plot(0, 0, 'bo')
plt.axis([-2,2,-2,2])
plt.title('In-plane')
plt.xlabel('x shift / mm')
plt.ylabel('y shift / mm')
plt.grid(True)
plt.subplot(122)
plt.hist(z_shifts,bins=30,range=[-2,2])
plt.title('Camera length')
plt.xlabel('z shift / mm')
plt.ylabel('Frequency')
plt.grid(True)
plt.show()
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