-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathnnmf0610.m
271 lines (231 loc) · 8.75 KB
/
nnmf0610.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
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
clear
close all
clc
nnmf_init
% all changes of this script will be applied to Synergy field of 'P' Database
%% Settings
load('P.mat')
%% NNMF stage 1
tic
subject =[5];
% test = {[4],[4],[4],[4],[4]};
% trial = {{100 100 100},{100 100 100},{100 100 100},{100 100 100},{100 100 100}};
SYN = 6;
option.type = 'EMG'; % EMG or kin2 or EmgKin
% state='Pre';
option.side = 'Right'; % Right: right side, Left: left side;
option.rep = 1;
for i_sub = subject
% for i_test = test{i_sub}
if strcmp(option.side, 'Right')
TrialNum =length(P(i_sub).Trajectory.Right);
else
TrialNum =length(P(i_sub).Trajectory.Left);
end
% if TrialNum==0
% continue;
% end
% TrialNum=1;
for i_trial = 1:TrialNum
for i_syn = SYN
disp(['sub:',num2str(i_sub),', trial:',num2str(i_trial),', syn:',num2str(i_syn),', ' ])
% M = Pf(i_sub).Test(i_test).Synergy(i_trial).(option.type).mat;
if strcmp(option.type, 'EmgKin')
M=P(i_sub);
else
M=P(i_sub).(option.type);
end
switch option.type
case 'EMG'
[W_best, S_best,W_avg,S_all] = nnmfEMG0524(M,i_syn,option,i_trial);
case 'kin2'
[W_best, S_best,W_avg,S_all] = nnmfKin0524(M,i_syn,option,i_trial);
case 'EmgKin'
[W_best, S_best,W_avg,S_all] = nnmfEMGKin0524(M,i_syn,option,i_trial);
end
P(i_sub).Synergy(i_trial).(option.type).(option.side).syn(i_syn).W_avg = W_avg;
P(i_sub).Synergy(i_trial).(option.type).(option.side).syn(i_syn).W_best = W_best;
P(i_sub).Synergy(i_trial).(option.type).(option.side).syn(i_syn).S_best = S_best;
end
end
end
toc
save('P.mat','P')
disp('nnmf done!')
%% calculate goodness of fits
subject = [1:10];
test=1;
trial=1;
% test = {[4],[4],[4],[4],[4]};
% trial = {{100 100 100},{100 100 100},{100 100 100},{100 100 100},{100 100 100}};
SYN = 4:6;
option.type = 'EMG'; % EMG or kin2 or EmgKin
% state='Pre';
option.side = 'Right'; % Right: right side, Left: left side;
W={};S={};M={};rec={}; name={};
k=1;
for i_sub = subject
W={};S={};M={};rec={}; name={};
k=1;
for i_test = test
if strcmp(option.side, 'Right')
TrialNum =length(P(i_sub).Trajectory.Right);
else
TrialNum =length(P(i_sub).Trajectory.Left);
end
if TrialNum==0
continue;
end
% TrialNum=1;
for i_trial = 1:TrialNum
for i_syn = SYN
disp(['sub:',num2str(i_sub),', trial:',num2str(i_trial),', syn:',num2str(i_syn),', ' ])
% M = Pf(i_sub).Test(i_test).Synergy(i_trial).(option.type).mat;
if strcmp(option.type, 'EmgKin')
M{k}=P(i_sub);
else
M{k}=P(i_sub).(option.type).(option.side)(i_trial).M_R;
end
if strcmp(option.type,'kin2')
M{k}=kinProcess(M{k});
end
name{k} = [num2str(i_sub),num2str(i_test),num2str(i_trial),num2str(i_syn)];
W{k} = P(i_sub).Synergy(i_trial).(option.type).(option.side).syn(i_syn).W_best;
S{k} = P(i_sub).Synergy(i_trial).(option.type).(option.side).syn(i_syn).S_best;
rec{k} = W{k}*S{k};
%
[r2_bootstat_lb(k), r2_bootstat_ub(k)] = myBootStrap(100,95,'@rsq1',M{k},rec{k});
[vaf_bootstat_lb(k), vaf_bootstat_ub(k)] = myBootStrap(100,95,'@vaf1',M{k},rec{k});
VAF(k) = vaf1(rec{k},M{k},0);
RSQ(k) = rsq1(rec{k},M{k},0);
vafLocal = vaf1(rec{k},M{k},1);
[minVal, id] = min(vafLocal);
rsqLocal = rsq1(rec{k},M{k},1);
[minVal, id] = min(rsqLocal);
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).r2_bootstat_lb = r2_bootstat_lb(k);
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).VAF = VAF(k);
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).RSQ = RSQ(k);
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).vafLocal = vafLocal;
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).minVafLocal = min(vafLocal);
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).rsqLocal = rsqLocal;
P(i_sub).Synergy(i_trial).(option.type).Right.syn(i_syn).minRsqLocal = min(rsqLocal);
k=k+1;
end
end
end
end
%% find number of synergies
subject = [1 2 3 5 6 8];
option.type = 'EMG'; % EMG or kin2 or EmgKin
figure; hold on; grid on
xlabel('Number of Subject')
ylabel('Number of Synergy')
title('number of synergy for each trial of subjects')
n={};
meanOfSubject=[];
stdOfSubject=[];
for i_sub=subject
a=[];
for i_trial=1: length(P(i_sub).Trajectory.Right)
n{i_sub}(i_trial)=3+min(find(extractfield(P(i_sub).Synergy(i_trial).(option.type).Right.syn(:),'r2_bootstat_lb')>.8));
plot(i_sub+i_trial*.02,n{i_sub}(i_trial),'k*')
end
% plot(i_sub,mean(a),'b*')
meanOfSubject(i_sub) = mean(n{i_sub});
stdOfSubject(i_sub) = std(n{i_sub});
end
% figure; hold on; grid on
s = bar(meanOfSubject);
alpha(s,.5)
errorbar(meanOfSubject,stdOfSubject,'LineStyle','none')
for i=1:length(n)
end
%% plot goodness of fits
% close all
figure;
hold on;
label = {'RTA','RPL','RSOL','RGC',...
'RRF','RMH','RVL',...
'RIP','RGMAX','RGMED','RAD','RTFL',...
'RIC','RLG','RRA','REO'};
vaf_th=0.75;
rsq_th=0.6;
lineStyle={'--','-'};
VAF=[];
RSQ=[];
for i=1:length(M)
[r2_bootstat_lb(i), r2_bootstat_ub(i)] = myBootStrap(100,95,'@rsq1',M{i},rec{i});
[vaf_bootstat_lb(i), vaf_bootstat_ub(i)] = myBootStrap(100,95,'@vaf1',M{i},rec{i});
VAF(i) = vaf1(rec{i},M{i},0);
RSQ(i) = rsq1(rec{i},M{i},0);
subplot(2,2,3); hold on; title('Local VAF'); grid on
set(gca,'ButtonDownFcn',{@plot_GoF_Click,M,rec,label})
vafLocal = vaf1(rec{i},M{i},1);
[minVal, id] = min(vafLocal);
plot(vafLocal,'linestyle',lineStyle{(minVal>vaf_th)+1},'DisplayName',name{i})
plot(id,minVal,'r*','handlevisibility','off')
legend
xticks(1:length(label))
xtickangle(45)
xticklabels(label)
subplot(2,2,4); hold on; title('Local R-sqaure'); grid on
set(gca,'ButtonDownFcn',{@plot_GoF_Click,M,rec,label})
vafLocal = rsq1(rec{i},M{i},1);
[minVal, id] = min(vafLocal);
plot(vafLocal,'linestyle',lineStyle{(minVal>rsq_th)+1},'DisplayName',name{i})
plot(id,minVal,'r*','handlevisibility','off')
legend
xticks(1:length(label))
xtickangle(45)
xticklabels(label)
end
subplot(2,2,1); hold on; title('Total VAF');grid on
meanVal = (vaf_bootstat_lb+vaf_bootstat_ub)/2;
err = vaf_bootstat_ub-meanVal;
errorbar(meanVal,err)
plot(VAF)
ylim([0.6 1])
% xlim([0 8])
subplot(2,2,2); hold on; title('Total R-sqaure'); grid on
meanVal = (r2_bootstat_lb+r2_bootstat_ub)/2;
err = r2_bootstat_ub-meanVal;
errorbar(meanVal,err)
plot(RSQ)
ylim([0 1])
% xlim([0 8])
%% each muscle activity
close all
subject=[1:10];
musNo=14;
option.type = 'EMG'; % EMG or kin2 or EmgKin
option.side = 'Right'; % Right: right side, Left: left side;
for i_sub = subject
if strcmp(option.side, 'Right')
TrialNum =length(P(i_sub).Trajectory.Right);
else
TrialNum =length(P(i_sub).Trajectory.Left);
end
if TrialNum==0
continue;
end
figure; hold on
for i_mus=1:musNo
subplot(4,4,i_mus); hold on;
title(P(i_sub).(option.type).(option.side)(1).groupName{i_mus});
sig=[];
for i_trial = 1:TrialNum
temp = P(i_sub).(option.type).(option.side)(i_trial).M_R(i_mus,:);
temp2 = P(i_sub).Events.(option.side)(i_trial);
[t,sig(i_trial,:)] = NormS(temp,double(temp2.PurtFrame));
% plot(t,sig(i_trial,:))
end
meanSig = mean(sig);
stdSig = std(sig);
plot([0:1:99],meanSig,'Color','k')
x=[[0:1:99],fliplr([0:1:99])];
y=[meanSig-stdSig,...
fliplr(meanSig+stdSig)];
s=fill(x,y,'k','EdgeColor','none');
alpha(s,.1)
end
end