164 lines
4.5 KiB
Python
164 lines
4.5 KiB
Python
#!/usr/bin/env python
|
|
# -*- coding: utf-8 -*-
|
|
#
|
|
# Determine mean detector shift based on prediction refinement results
|
|
#
|
|
# Copyright © 2015-2020 Deutsches Elektronen-Synchrotron DESY,
|
|
# a research centre of the Helmholtz Association.
|
|
#
|
|
# Author:
|
|
# 2015-2018 Thomas White <taw@physics.org>
|
|
# 2016 Mamoru Suzuki <mamoru.suzuki@protein.osaka-u.ac.jp>
|
|
# 2018 Chun Hong Yoon
|
|
#
|
|
|
|
import sys
|
|
import os
|
|
import re
|
|
import numpy as np
|
|
import matplotlib.pyplot as plt
|
|
|
|
if sys.argv[1] == "-":
|
|
f = sys.stdin
|
|
else:
|
|
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()
|
|
|
|
mean_x = sum(x_shifts) / len(x_shifts)
|
|
mean_y = sum(y_shifts) / len(y_shifts)
|
|
print('Mean shifts: dx = {:.2} mm, dy = {:.2} mm'.format(mean_x,mean_y))
|
|
print('Shifts will be applied to geometry file when you close the graph window')
|
|
print('Click anywhere on the graph to override the detector shift')
|
|
|
|
def plotNewCentre(x, y):
|
|
circle1 = plt.Circle((x,y),.1,color='r',fill=False)
|
|
fig.gca().add_artist(circle1)
|
|
plt.plot(x, y, 'b8', color='m')
|
|
plt.grid(True)
|
|
|
|
def onclick(event):
|
|
print('New shifts: dx = {:.2} mm, dy = {:.2} mm'.format(event.xdata, event.ydata))
|
|
print('Shifts will be applied to geometry file when you close the graph window')
|
|
mean_x = event.xdata
|
|
mean_y = event.ydata
|
|
plotNewCentre(mean_x, mean_y)
|
|
|
|
nbins = 200
|
|
H, xedges, yedges = np.histogram2d(x_shifts,y_shifts,bins=nbins)
|
|
H = np.rot90(H)
|
|
H = np.flipud(H)
|
|
Hmasked = np.ma.masked_where(H==0,H)
|
|
|
|
# Plot 2D histogram using pcolor
|
|
plt.ion()
|
|
fig2 = plt.figure()
|
|
cid = fig2.canvas.mpl_connect('button_press_event', onclick)
|
|
plt.pcolormesh(xedges,yedges,Hmasked)
|
|
plt.title('Detector shifts according to prediction refinement')
|
|
plt.xlabel('x shift / mm')
|
|
plt.ylabel('y shift / mm')
|
|
plt.plot(0, 0, 'bH', color='c')
|
|
fig = plt.gcf()
|
|
cbar = plt.colorbar()
|
|
cbar.ax.set_ylabel('Counts')
|
|
plotNewCentre(mean_x, mean_y)
|
|
plt.show(block=True)
|
|
|
|
# Apply shifts to geometry
|
|
if have_geom:
|
|
|
|
out = os.path.splitext(geom)[0]+'-predrefine.geom'
|
|
print('Applying corrections to {}, output filename {}'.format(geom,out))
|
|
g = open(geom, 'r')
|
|
h = open(out, 'w')
|
|
panel_resolutions = {}
|
|
|
|
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))
|
|
h.write(fline)
|
|
continue
|
|
|
|
match = prog2.match(fline)
|
|
if match:
|
|
panel = match.group(1)
|
|
panel_res = float(match.group(2))
|
|
default_res = panel_res
|
|
panel_resolutions[panel] = panel_res
|
|
h.write(fline)
|
|
continue
|
|
|
|
match = prog3.match(fline)
|
|
if match:
|
|
panel = match.group(1)
|
|
panel_cnx = float(match.group(2))
|
|
if panel in panel_resolutions:
|
|
res = panel_resolutions[panel]
|
|
else:
|
|
res = default_res
|
|
print('Using default resolution ({} px/m) for panel {}'.format(res, panel))
|
|
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))
|
|
if panel in panel_resolutions:
|
|
res = panel_resolutions[panel]
|
|
else:
|
|
res = default_res
|
|
print('Using default resolution ({} px/m) for panel {}'.format(res, panel))
|
|
h.write('%s/corner_y = %f\n' % (panel,panel_cny+(mean_y*res*1e-3)))
|
|
continue
|
|
|
|
h.write(fline)
|
|
|
|
g.close()
|
|
h.close()
|
|
|