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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Check a stream for saturation
#
# Copyright © 2016-2020 Deutsches Elektronen-Synchrotron DESY,
# a research centre of the Helmholtz Association.
# Copyright © 2016 The Research Foundation for SUNY
#
# Authors:
# 2016-2017 Thomas White <taw@physics.org>
# 2014-2016 Thomas Grant <tgrant@hwi.buffalo.edu>
#
# This file is part of CrystFEL.
#
# CrystFEL is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# CrystFEL is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with CrystFEL. If not, see <http://www.gnu.org/licenses/>.
import sys
import argparse
import math as m
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm
def c2(a):
return m.cos(a) * m.cos(a)
def s2(a):
return m.sin(a) * m.sin(a)
# Return 1/d for hkl in cell, in 1/Angstroms
def resolution(scell, shkl):
a = float(scell[0])*10.0
b = float(scell[1])*10.0
c = float(scell[2])*10.0 # nm -> Angstroms
al = m.radians(float(scell[3]))
be = m.radians(float(scell[4]))
ga = m.radians(float(scell[5])) # in degrees
h = int(shkl[0])
k = int(shkl[1])
l = int(shkl[2])
pf = 1.0 - c2(al) - c2(be) - c2(ga) + 2.0*m.cos(al)*m.cos(be)*m.cos(ga)
n1 = h*h*s2(al)/(a*a) + k*k*s2(be)/(b*b) + l*l*s2(ga)/(c*c)
n2a = 2.0*k*l*(m.cos(be)*m.cos(ga) - m.cos(al))/(b*c)
n2b = 2.0*l*h*(m.cos(ga)*m.cos(al) - m.cos(be))/(c*a)
n2c = 2.0*h*k*(m.cos(al)*m.cos(be) - m.cos(ga))/(a*b)
return m.sqrt((n1 + n2a + n2b + n2c) / pf)
parser = argparse.ArgumentParser()
parser.add_argument("-i", action="append", required=True, help="stream filename")
parser.add_argument("-l", action="store_true", help="log scale y-axis")
parser.add_argument("--rmin", type=float, help="minimum resolution cutoff (1/d in Angstroms^-1)")
parser.add_argument("--rmax", type=float, help="maximum resolution cutoff (1/d in Angstroms^-1)")
parser.add_argument("--imin", type=float, help="minimum peak intensity cutoff")
parser.add_argument("--imax", type=float, help="maximum peak intensity cutoff")
parser.add_argument("--nmax", default=np.inf, type=int, help="maximum number of peaks to read")
parser.add_argument("-o", default="peakogram", help="output file prefix")
args = parser.parse_args()
data = []
n=0
in_list = 0
cell = []
for file in args.i:
if file == "-":
f = sys.stdin
else:
f = open(file)
for line in f:
if line.find("Cell parameters") != -1:
cell[0:3] = line.split()[2:5]
cell[3:6] = line.split()[6:9]
continue
if line.find("Reflections measured after indexing") != -1:
in_list = 1
continue
if line.find("End of reflections") != -1:
in_list = 0
if in_list == 1:
in_list = 2
continue
elif in_list != 2:
continue
# From here, we are definitely handling a reflection line
# Add reflection to list
columns = line.split()
n += 1
try:
data.append([resolution(cell, columns[0:3]),columns[5]])
except:
print("Error with line: "+line.rstrip("\r\n"))
print("Cell: "+str(cell))
if n%1000==0:
sys.stdout.write("\r%i predicted reflections found" % n)
sys.stdout.flush()
if n >= args.nmax:
break
f.close()
data = np.asarray(data,dtype=float)
sys.stdout.write("\r%i predicted reflections found" % n)
sys.stdout.flush()
print("")
x = data[:,0]
y = data[:,1]
xmin = np.min(x[x>0])
xmax = np.max(x)
ymin = np.min(y[y>0])
ymax = np.max(y)
if args.rmin is not None:
xmin = args.rmin
if args.rmax is not None:
xmax = args.rmax
if args.imin is not None:
ymin = args.imin
if args.imax is not None:
ymax = args.imax
keepers = np.where((x>=xmin) & (x<=xmax) & (y>=ymin) & (y<=ymax))
x = x[keepers]
y = y[keepers]
if args.l:
y = np.log10(y)
ymin = np.log10(ymin)
ymax = np.log10(ymax)
bins=300
H,xedges,yedges = np.histogram2d(y,x,bins=bins)
fig = plt.figure()
ax1 = plt.subplot(111)
plot = ax1.pcolormesh(yedges,xedges,H, norm=LogNorm())
cbar = plt.colorbar(plot)
plt.xlim([xmin,xmax])
plt.ylim([ymin,ymax])
plt.xlabel("1/d (A^-1)")
if args.l:
plt.ylabel("Log(Reflection max intensity)")
else:
plt.ylabel("Reflection max intensity")
plt.title(args.i)
plt.show()
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