/
denss.py
executable file
·187 lines (158 loc) · 6.49 KB
/
denss.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
#!/usr/bin/env python
#
# denss.py
# DENSS: DENsity from Solution Scattering
# A tool for calculating an electron density map from solution scattering data
#
# Tested using Anaconda / Python 2.7
#
# Author: Thomas D. Grant
# Email: <tgrant@hwi.buffalo.edu>
# Copyright 2017 The Research Foundation for SUNY
#
# This program 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.
#
# This program 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 this program. If not, see <http://www.gnu.org/licenses/>.
#
from __future__ import print_function
from saxstats._version import __version__
import saxstats.saxstats as saxs
import saxstats.denssopts as dopts
import numpy as np
import sys, argparse, os
import logging
parser = argparse.ArgumentParser(description="DENSS: DENsity from Solution Scattering.\n A tool for calculating an electron density map from solution scattering data", formatter_class=argparse.RawTextHelpFormatter)
args = dopts.parse_arguments(parser)
if __name__ == "__main__":
__spec__ = None
my_logger = logging.getLogger()
my_logger.setLevel(logging.DEBUG)
formatter = logging.Formatter('%(asctime)s %(message)s', '%Y-%m-%d %I:%M:%S %p')
# h1 = logging.StreamHandler(sys.stdout)
# h1.setLevel(logging.INFO)
# h1.setFormatter(formatter)
h2 = logging.FileHandler(os.path.join('.', args.output+'.log'), mode='w')
h2.setLevel(logging.INFO)
h2.setFormatter(formatter)
# my_logger.addHandler(h1)
my_logger.addHandler(h2)
my_logger.info('BEGIN')
my_logger.info('Command: %s', ' '.join(sys.argv))
my_logger.info('DENSS Version: %s', __version__)
my_logger.info('Data filename: %s', args.file)
my_logger.info('Output prefix: %s', args.output)
my_logger.info('Mode: %s', args.mode)
qdata, Idata, sigqdata, qbinsc, Imean, chis, rg, supportV, rho, side, fit, final_chi2 = saxs.denss(
q=args.q,
I=args.I,
sigq=args.sigq,
dmax=args.dmax,
qraw=args.qraw,
Iraw=args.Iraw,
sigqraw=args.sigqraw,
ne=args.ne,
voxel=args.voxel,
oversampling=args.oversampling,
recenter=args.recenter,
recenter_steps=args.recenter_steps,
recenter_mode=args.recenter_mode,
positivity=args.positivity,
positivity_steps=args.positivity_steps,
extrapolate=args.extrapolate,
output=args.output,
steps=args.steps,
ncs=args.ncs,
ncs_steps=args.ncs_steps,
ncs_axis=args.ncs_axis,
ncs_type=args.ncs_type,
seed=args.seed,
support_start=args.support_start,
shrinkwrap=args.shrinkwrap,
shrinkwrap_old_method=args.shrinkwrap_old_method,
shrinkwrap_sigma_start=args.shrinkwrap_sigma_start,
shrinkwrap_sigma_end=args.shrinkwrap_sigma_end,
shrinkwrap_sigma_decay=args.shrinkwrap_sigma_decay,
shrinkwrap_threshold_fraction=args.shrinkwrap_threshold_fraction,
shrinkwrap_iter=args.shrinkwrap_iter,
shrinkwrap_minstep=args.shrinkwrap_minstep,
chi_end_fraction=args.chi_end_fraction,
write_xplor_format=args.write_xplor_format,
write_freq=args.write_freq,
enforce_connectivity=args.enforce_connectivity,
enforce_connectivity_steps=args.enforce_connectivity_steps,
enforce_connectivity_max_features=args.enforce_connectivity_max_features,
cutout=args.cutout,
quiet=args.quiet,
DENSS_GPU=args.DENSS_GPU,
my_logger=my_logger)
print("\n%s"%args.output)
if args.plot:
import matplotlib.pyplot as plt
from matplotlib.colors import colorConverter as cc
import matplotlib.gridspec as gridspec
qraw = args.qraw
Iraw = args.Iraw
q = args.q
I = args.I
sigq = args.sigq
f = plt.figure(figsize=[6,6])
gs = gridspec.GridSpec(2, 1, height_ratios=[3,1])
ax0 = plt.subplot(gs[0])
ax0.errorbar(fit[:,0], fit[:,1], fmt='k.', yerr=fit[:,2], mec='none', mew=0, ms=5, alpha=0.3, capsize=0, elinewidth=0.1, ecolor=cc.to_rgba('0',alpha=0.5),label='Supplied Data',zorder=-1)
ax0.plot(fit[:,0],fit[:,3],'r-',label=r'DENSS Map $\chi^2 = %.2f$'%final_chi2)
handles,labels = ax0.get_legend_handles_labels()
handles = [handles[1], handles[0] ]
labels = [labels[1], labels[0] ]
ax0.legend(handles,labels)
ax0.semilogy()
ax0.set_ylabel('I(q)')
ax1 = plt.subplot(gs[1])
ax1.plot(fit[:,0], fit[:,0]*0, 'k--')
residuals = (fit[:,1]-fit[:,3])/fit[:,2]
ax1.plot(fit[:,0], residuals, 'r.')
ylim = ax1.get_ylim()
ymax = np.max(np.abs(ylim))
ymax = np.max(np.abs(residuals))
ax1.set_ylim([-ymax,ymax])
ax1.yaxis.major.locator.set_params(nbins=5)
xlim = ax0.get_xlim()
ax1.set_xlim(xlim)
ax1.set_ylabel(r'$\Delta{I}/\sigma$')
ax1.set_xlabel(r'q ($\mathrm{\AA^{-1}}$)')
plt.tight_layout()
plt.savefig(args.output+'_fit.png',dpi=150)
plt.close()
fig, host = plt.subplots(nrows=1, ncols=1)
par1 = host.twinx()
par2 = host.twinx()
host.set_xlabel('Step')
host.set_ylabel('$\chi^2$')
par1.set_ylabel('Rg')
par2.set_ylabel('Support Volume')
color1 = plt.cm.viridis(0)
color2 = plt.cm.viridis(0.5)
color3 = plt.cm.viridis(.9)
p1, = host.plot(chis[chis>0], color=color1,label="$\chi^2$")
p2, = par1.plot(rg[rg!=0], color=color2, label="Rg")
p3, = par2.plot(supportV[supportV>0], color=color3, label="Support Volume")
host.semilogy()
par2.semilogy()
lns = [p1, p2, p3]
host.legend(handles=lns, loc='best')
# right, left, top, bottom
par2.spines['right'].set_position(('outward', 60))
host.yaxis.label.set_color(p1.get_color())
par1.yaxis.label.set_color(p2.get_color())
par2.yaxis.label.set_color(p3.get_color())
plt.savefig(args.output+'_stats_by_step.png', bbox_inches='tight',dpi=150)
plt.close()
logging.info('END')