#!/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 # 2014-2016 Thomas Grant # # 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 . 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()