This repository has been archived by the owner on Feb 20, 2018. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 11
/
plot_plusminus_comparison.m
190 lines (171 loc) · 9.83 KB
/
plot_plusminus_comparison.m
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
186
187
188
189
190
% Copyright (C) 2010-2017, Raytheon BBN Technologies and contributors listed
% in the AUTHORS file in TASBE analytics package distribution's top directory.
%
% This file is part of the TASBE analytics package, and is distributed
% under the terms of the GNU General Public License, with a linking
% exception, as described in the file LICENSE in the TASBE analytics
% package distribution's top directory.
function plot_plusminus_comparison(pm_results,outputsettings)
step = outputsettings.PlotEveryN;
ticks = outputsettings.PlotTickMarks;
variable = getInducerLevelsToFiles(getExperiment(pm_results.PlusResults),1);
n_var = numel(variable);
AP = getAnalysisParameters(pm_results.PlusResults);
hues = (1:n_var)./n_var;
bin_centers = get_bin_centers(getBins(AP));
in_units = getChannelUnits(AP,'input');
out_units = getChannelUnits(AP,'output');
cfp_units = getChannelUnits(AP,'constitutive');
legendentries = cell(n_var,1);
for i=1:n_var, legendentries{i} = num2str(variable(i)); end;
if n_var == 1,
pmlegendentries{1} = 'Plus';
else
pmlegendentries = legendentries;
end
% set tick marks, if any
if ticks, ptick = '+'; ntick = 'o';
else ptick = []; ntick = [];
end
%%% I/O plots:
% Plain I/O plot:
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1),[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2),[ntick '--'],'Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1).*pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1)./pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2).*pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2)./pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
end;
xlabel(['IFP ' in_units]); ylabel(['OFP ' out_units]);
set(gca,'XScale','log'); set(gca,'YScale','log');
legend('Location','Best',legendentries);
if(outputsettings.FixedInputAxis), xlim(outputsettings.FixedInputAxis); end;
if(outputsettings.FixedOutputAxis), ylim(outputsettings.FixedOutputAxis); end;
title(['Raw ',outputsettings.StemName,' transfer curves']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-mean'],outputsettings.Directory);
% normalized I/O plot
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1)./bin_centers(which)',[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2)./bin_centers(which)',[ntick '--'],'Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1)./bin_centers(which)'.*pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,1),pm_results.OutMeans(which,i,1)./bin_centers(which)'./pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2)./bin_centers(which)'.*pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(pm_results.InMeans(which,i,2),pm_results.OutMeans(which,i,2)./bin_centers(which)'./pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
end;
xlabel(['IFP ' in_units]); ylabel(['OFP ' out_units ' / CFP ' cfp_units]);
set(gca,'XScale','log'); set(gca,'YScale','log');
legend('Location','Best',legendentries);
if(outputsettings.FixedInputAxis), xlim(outputsettings.FixedInputAxis); end;
if(outputsettings.FixedOutputAxis), ylim(outputsettings.FixedOutputAxis); end;
title([outputsettings.StemName,' transfer curves normalized by CFP']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-mean-norm'],outputsettings.Directory);
% OFP vs. CFP
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(bin_centers(which),pm_results.OutMeans(which,i,1),[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(bin_centers(which),pm_results.OutMeans(which,i,2),[ntick '--'],'Color',hsv2rgb([hues(i) 1 0.9]));
loglog(bin_centers(which),pm_results.OutMeans(which,i,1).*pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(bin_centers(which),pm_results.OutMeans(which,i,1)./pm_results.OutStandardDevs(which,i,1),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(bin_centers(which),pm_results.OutMeans(which,i,2).*pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
loglog(bin_centers(which),pm_results.OutMeans(which,i,2)./pm_results.OutStandardDevs(which,i,2),':','Color',hsv2rgb([hues(i) 1 0.9]));
end;
xlabel(['CFP ' cfp_units]); ylabel(['OFP ' out_units]);
set(gca,'XScale','log'); set(gca,'YScale','log');
legend('Location','Best',pmlegendentries,'Minus');
if(outputsettings.FixedInputAxis), xlim(outputsettings.FixedInputAxis); end;
if(outputsettings.FixedOutputAxis), ylim(outputsettings.FixedOutputAxis); end;
title([outputsettings.StemName,' OFP vs. CFP']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-v-cfp'],outputsettings.Directory);
% Relative change in OFP vs. CFP
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = find(pm_results.Valid(1:(end-1),i,1) & pm_results.Valid(1:(end-1),i,2) & ...
pm_results.Valid(2:end,i,1) & pm_results.Valid(2:end,i,2));
marginal_centers = (bin_centers(which) + bin_centers(which+1)) / 2;
p_ofp_difference = pm_results.OutMeans(which+1,i,1) ./ pm_results.OutMeans(which,i,1);
m_ofp_difference = pm_results.OutMeans(which+1,i,2) ./ pm_results.OutMeans(which,i,2);
cfp_difference = (bin_centers(which+1) ./ bin_centers(which));
semilogx(marginal_centers,p_ofp_difference./cfp_difference',[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end
for i=1:step:n_var
which = find(pm_results.Valid(1:(end-1),i,1) & pm_results.Valid(1:(end-1),i,2) & ...
pm_results.Valid(2:end,i,1) & pm_results.Valid(2:end,i,2));
marginal_centers = (bin_centers(which) + bin_centers(which+1)) / 2;
p_ofp_difference = pm_results.OutMeans(which+1,i,1) ./ pm_results.OutMeans(which,i,1);
m_ofp_difference = pm_results.OutMeans(which+1,i,2) ./ pm_results.OutMeans(which,i,2);
cfp_difference = (bin_centers(which+1) ./ bin_centers(which));
semilogx(marginal_centers,m_ofp_difference./cfp_difference',[ntick '--'],'Color',hsv2rgb([hues(i) 1 0.9]));
end;
xlabel(['CFP ' cfp_units]); ylabel(['OFP ' out_units ' / CFP ' cfp_units]);
set(gca,'XScale','log'); set(gca,'YScale','linear');
legend('Location','Best',pmlegendentries,'Minus');
if(outputsettings.FixedInputAxis), xlim(outputsettings.FixedInputAxis); end;
if(outputsettings.FixedOutputAxis), ylim(outputsettings.FixedOutputAxis); end;
title([outputsettings.StemName,' marginal change in OFP vs. CFP']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-marginal-ofp'],outputsettings.Directory);
% ratio plot
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
semilogx(bin_centers(which),pm_results.Ratios(which,i),'-','Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
xlabel(['CFP ' cfp_units]); ylabel('Fold Activation');
set(gca,'XScale','log'); set(gca,'YScale','linear');
legend('Location','Best',legendentries);
if(outputsettings.FixedInputAxis), xlim(outputsettings.FixedInputAxis); end;
if(outputsettings.FixedOutputAxis), ylim(outputsettings.FixedOutputAxis); end;
title(['+/- Ratios for ',outputsettings.StemName]);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-ratios'],outputsettings.Directory);
% SNR plots
if n_var == 1,
pmlegendentries{1} = 'Output SNR';
end
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
semilogx(bin_centers(which),pm_results.OutputSNR(which,i),[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
loglog(bin_centers(which),pm_results.InputSNR(which,i),[ntick '--'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
xlabel(['CFP ' cfp_units]); ylabel('SNR (db)');
set(gca,'XScale','log');
legend('Location','Best',pmlegendentries,'Input SNR');
title([outputsettings.StemName,' SNR vs. CFP']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-SNR'],outputsettings.Directory);
if n_var == 1,
pmlegendentries{1} = '\Delta SNR';
end
h = figure('PaperPosition',[1 1 5 3.66]);
set(h,'visible','off');
for i=1:step:n_var
which = pm_results.Valid(:,i,1) & pm_results.Valid(:,i,2);
semilogx(bin_centers(which),pm_results.OutputSNR(which,i)-pm_results.InputSNR(which,i),[ptick '-'],'Color',hsv2rgb([hues(i) 1 0.9])); hold on;
end;
xlabel(['CFP ' cfp_units]); ylabel('\Delta SNR (db)');
set(gca,'XScale','log');
legend('Location','Best',pmlegendentries);
title([outputsettings.StemName,'\Delta SNR vs. CFP']);
outputfig(h,[outputsettings.StemName,'-',outputsettings.DeviceName,'-dSNR'],outputsettings.Directory);