-
Notifications
You must be signed in to change notification settings - Fork 14
Expand file tree
/
Copy pathexpSynData.m
More file actions
179 lines (158 loc) · 4.35 KB
/
expSynData.m
File metadata and controls
179 lines (158 loc) · 4.35 KB
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
%% Exprimenet on synthetic data.
% Generate data.
clear all
expTimes = 1;
dataSize = 900;
noiseLevel = 0.0;
bandNum = 5;
emNum = 6;
HTrue = zeros(emNum, bandNum);
HI = zeros(emNum, bandNum);
HMdc = zeros(emNum, bandNum);
WTrue = zeros(dataSize, emNum);
WI = zeros(dataSize, emNum);
WMdc = zeros(dataSize, emNum);
HTrue = abs( randn( emNum, bandNum ) );
[V, W_true] = create4(dataSize, HTrue);
figure;
scatter(V(:,1), V(:,2));
xlabel('band 1');
ylabel('band 2');
% Run VCA
vca_ = false;
if vca_
HVca = hyperVca(V', emNum);
end
% Run Nfindr
indxNfindr = nFindr(V, emNum);
HNfindr = V(indxNfindr, :);
sadNfindr = sadEms(HTrue, HNfindr, emNum);
sadSet = sadNfindr;
legendBar = { 'N-Findr' };
% Run nmfAbundance to find initial well-conditioned abundance.
HI = HNfindr;
alpha = 1;
tol = 0.1;
maxIter = 5000;
[WI, EI] = nmfAbundance(V, emNum, HI,...
alpha, tol, maxIter);
% Run hyperNmfMDC.
mdc_ = true;
if mdc_
[ WMdc, HMdc, HRcMDC, EMDC] = ...
hyperNmfMDC(...
V, emNum, WI, HI, ...
0.0002, 4,...
0.01, 30000 );
sadMdc = sadEms(HTrue, HMdc, emNum);
sadSet = [sadSet, sadMdc];
legendBar{ length(legendBar)+1 } = 'MDC';
end
% Run hyperNmfMVC
mvc_ = true;
if mvc_
[UU, SS, WW] = svd(V');
prinComp = pca(V);
meanData = mean(HTrue, 1);
[HMvc, WMvc] = hyperNmfMVC(V', HI', WI', ...
HI', UU, prinComp, meanData, ...
0.015, 0.001, 100, ...
0, 2, 1);
sadMvc = sadEms(HTrue, HMvc', emNum);
sadSet = [sadSet, sadMvc];
legendBar{ length(legendBar)+1 } = 'ICE';
end
% Run hyperNmfASCL1_2
spl1_2_ = false;
if spl1_2_
[ WASCL1_2, HASCL1_2, HRcL1_2, errRcL1_2, objRcL1] = ...
hyperNmfASCL1_2(...
V', HI', WI',...
0.001,... % tolObj
20000,... % maxIter
20 ... %fDelta
);
sadASCL1_2 = sadEms(HTrue, HASCL1_2, emNum);
sadSet = [sadSet, sadASCL1_2];
legendBar{ length(legendBar) } = 'ASCL_{1/2}';
end
% Run hyperNmfASCL1
spl1_ = false;
if spl1_
[ WASCL1, HASCL1, HRcL1, errRcL1, objRcL1] = ...
hyperNmfASCL1(...
V', HI', WI',...
0.001,... % tolObj
20000,... % maxIter
20 ... %fDelta
);
sadASCL1 = sadEms(HASCL1, HASCL1_2, emNum);
sadSet = [sadSet, sadASCL1];
legendBar{ length(legendBar) } = 'ASCL_1';
end
% Visualize result
figure;
hold on
% true data
scatter(V(:,1), V(:,2), 'm+');
hTrue = scatter(HTrue(:, 1), HTrue(:, 2), 100, 'filled', 'r');
handlesScatter = hTrue;
legendScatter = {'True'};
% VCA
if vca_
hVCA = scatter(HVca(1,:), HVca(2,:), 100, 'filled', 'o');
handlesScatter = [handlesScatter, hVCA];
legendScatter{ length(legendScatter)+1 } = 'VCA';
end
% Nfindr
hNfindr = scatter(HNfindr(:, 1), HNfindr(:, 2), 100, 'filled', 'm');
handlesScatter = [handlesScatter, hNfindr];
legendScatter{ length(legendScatter)+1 } = 'N-Findr';
% MDC
if mdc_
bandIndx1 = 1;
bandIndx2 = 2;
hMDC = scatter( HMdc(:,bandIndx1), HMdc(:,bandIndx2) , 100, 'filled','k');
for i=1:bandNum
plot(HRcMDC(i, :,bandIndx1), HRcMDC(i, :,bandIndx2), 'm-', 'MarkerSize', 5);
end
VMdc = WMdc * HMdc;
scatter(VMdc(:,1), VMdc(:,2), 'o');
handlesScatter = [handlesScatter, hMDC];
legendScatter{ length(legendScatter)+1 } = 'MDC';
end
% MVC
if mvc_
hMVC = scatter( HMvc(bandIndx1,:), HMvc(bandIndx2,:) , 100, 'filled','b');
handlesScatter = [handlesScatter, hMVC];
legendScatter{ length(legendScatter)+1 } = 'ICE';
end
% ASCL1_2
if spl1_2_
hASCL1_2 = scatter( HASCL1_2(bandIndx1, :), HASCL1_2(bandIndx2,:) , 100, 'filled','c');
for i = 1:emNum
plot(HRcL1_2(i, :,bandIndx1), HRcL1_2(i, :,bandIndx2), 'r-.', 'MarkerSize', 5);
end
handlesScatter = [handlesScatter, hASCL1_2];
legendScatter{ length(legendScatter)+1 } = 'ASCL_{1/2}';
end
% ASCL1
if spl1_
hASCL1 = scatter( HASCL1(bandIndx1, :), HASCL1(bandIndx2,:) , 100, 'filled','g');
for i = 1:emNum
plot(HRcL1(i, :,bandIndx1), HRcL1(i, :,bandIndx2), 'r-.', 'MarkerSize', 5);
end
handlesScatter = [handlesScatter, hASCL1];
legendScatter{ length(legendScatter)+1 } = 'ASCL_1';
end
legend(handlesScatter, legendScatter)
% Computer reconstruction error.
alpha = 1;
tol = 0.1;
maxIter = 5000;
figure;
hold on
hBar = bar(sadSet);
xlabel('endmember', 'FontSize', 15, 'FontWeight', 'bold')
ylabel('SAD', 'FontSize', 15, 'FontWeight', 'bold')
legend(hBar, legendBar)