#!/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()

mean_x = sum(x_shifts) / len(x_shifts)
mean_y = sum(y_shifts) / len(y_shifts)
print 'Mean shifts: dx = %.2f mm,  dy = %.2f mm' % (mean_x,mean_y)

# 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.plot(x_shifts, y_shifts, 'rx')
plt.plot(0, 0, 'bo')
plt.axis([-2,2,-2,2])
plt.title('Detector shifts according to prediction refinement')
plt.xlabel('x shift / mm')
plt.ylabel('y shift / mm')
plt.grid(True)
plt.show()