-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathcreate_data_matrixes_v1v2.m
128 lines (109 loc) · 5.84 KB
/
create_data_matrixes_v1v2.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
function create_data_matrixes_v1v2(icsdir, normalicsdir, output)
%This function edits the original measurements to create a bigger matrix of
%data containing just the values of the indexes at the end of the occlusion
%and just the 9 original leads of the database. It also creates the
%necessary groups variables and the matrix of data ready to export to spss
lista=char('002','003','006','007','008','009','010','011','013','014','015','016','017','018','019','020','021','022','023','025','026','029','030','031','032','037','039','040','041','046','047','048','049','050','051','052','053','054','055','056','057','058','059','061','062','063','065','066','068','069','070','071','072','073','074','075','077','079','080','081','082','083','084','085','086','087','088','090','091','092','094','095','096','097','098','099','100','101','102','104','105','106','107');
arteries = loadarteriesclassif();
data_matrix_delta.vars = zeros(83,45);
data_matrix_ICS.vars = zeros(83,45);
mkdir(output)
for h = 1:83
load([normalicsdir 'ics' lista(h,:)])
load([normalicsdir 'delta_indexes' lista(h,:)])
for g = 1:10
if (g<7)
data_matrix_delta.vars(h,(g-1)*5+1) = delt_st(g,end);
data_matrix_delta.vars(h,(g-1)*5+2) = delt_qt(g,end);
data_matrix_delta.vars(h,(g-1)*5+3) = delt_qd(g,end);
data_matrix_delta.vars(h,(g-1)*5+4) = delt_ta(g,end);
data_matrix_delta.vars(h,(g-1)*5+5) = delt_tp(g,end);
data_matrix_ICS.vars(h,(g-1)*5+1) = fa_st(g,end);
data_matrix_ICS.vars(h,(g-1)*5+2) = fa_qt(g,end);
data_matrix_ICS.vars(h,(g-1)*5+3) = fa_qd(g,end);
data_matrix_ICS.vars(h,(g-1)*5+4) = fa_ta(g,end);
data_matrix_ICS.vars(h,(g-1)*5+5) = fa_tp(g,end);
elseif (g == 7)
data_matrix_delta.vars(h,(g-1)*5+1) = delt_st(8,end);
data_matrix_delta.vars(h,(g-1)*5+2) = delt_qt(8,end);
data_matrix_delta.vars(h,(g-1)*5+3) = delt_qd(8,end);
data_matrix_delta.vars(h,(g-1)*5+4) = delt_ta(8,end);
data_matrix_delta.vars(h,(g-1)*5+5) = delt_tp(8,end);
data_matrix_ICS.vars(h,(g-1)*5+1) = fa_st(8,end);
data_matrix_ICS.vars(h,(g-1)*5+2) = fa_qt(8,end);
data_matrix_ICS.vars(h,(g-1)*5+3) = fa_qd(8,end);
data_matrix_ICS.vars(h,(g-1)*5+4) = fa_ta(8,end);
data_matrix_ICS.vars(h,(g-1)*5+5) = fa_tp(8,end);
elseif (g == 8)
data_matrix_delta.vars(h,(g-1)*5+1) = delt_st(10,end);
data_matrix_delta.vars(h,(g-1)*5+2) = delt_qt(10,end);
data_matrix_delta.vars(h,(g-1)*5+3) = delt_qd(10,end);
data_matrix_delta.vars(h,(g-1)*5+4) = delt_ta(10,end);
data_matrix_delta.vars(h,(g-1)*5+5) = delt_tp(10,end);
data_matrix_ICS.vars(h,(g-1)*5+1) = fa_st(10,end);
data_matrix_ICS.vars(h,(g-1)*5+2) = fa_qt(10,end);
data_matrix_ICS.vars(h,(g-1)*5+3) = fa_qd(10,end);
data_matrix_ICS.vars(h,(g-1)*5+4) = fa_ta(10,end);
data_matrix_ICS.vars(h,(g-1)*5+5) = fa_tp(10,end);
elseif (g == 9)
data_matrix_delta.vars(h,(g-1)*5+1) = delt_st(12,end);
data_matrix_delta.vars(h,(g-1)*5+2) = delt_qt(12,end);
data_matrix_delta.vars(h,(g-1)*5+3) = delt_qd(12,end);
data_matrix_delta.vars(h,(g-1)*5+4) = delt_ta(12,end);
data_matrix_delta.vars(h,(g-1)*5+5) = delt_tp(12,end);
data_matrix_ICS.vars(h,(g-1)*5+1) = fa_st(12,end);
data_matrix_ICS.vars(h,(g-1)*5+2) = fa_qt(12,end);
data_matrix_ICS.vars(h,(g-1)*5+3) = fa_qd(12,end);
data_matrix_ICS.vars(h,(g-1)*5+4) = fa_ta(12,end);
data_matrix_ICS.vars(h,(g-1)*5+5) = fa_tp(12,end);
elseif (g == 10)
load([icsdir 'ics' lista(h,:)])
load([icsdir 'delta_indexes' lista(h,:)])
data_matrix_delta.vars(h,(g-1)*5+1) = delt_st(12,end);
data_matrix_delta.vars(h,(g-1)*5+2) = delt_qt(1,end);
data_matrix_delta.vars(h,(g-1)*5+3) = delt_qd(1,end);
data_matrix_delta.vars(h,(g-1)*5+4) = delt_ta(1,end);
data_matrix_delta.vars(h,(g-1)*5+5) = delt_tp(1,end);
data_matrix_ICS.vars(h,(g-1)*5+1) = fa_st(1,end);
data_matrix_ICS.vars(h,(g-1)*5+2) = fa_qt(1,end);
data_matrix_ICS.vars(h,(g-1)*5+3) = fa_qd(1,end);
data_matrix_ICS.vars(h,(g-1)*5+4) = fa_ta(1,end);
data_matrix_ICS.vars(h,(g-1)*5+5) = fa_tp(1,end);
end
end
end
for i=1:83
data_matrix_delta.patient{i} = lista(i,:);
data_matrix_ICS.patient{i} = lista(i,:);
for j=1:length(arteries.fields)
for k = 1:length(arteries.(arteries.fields(j)))
if lista(i,:) == arteries.(arteries.fields(j))(k,1:end-1)
data_matrix_delta.artery{i} = arteries.fields(j);
data_matrix_ICS.artery{i} = arteries.fields(j);
end
end
end
end
%%Preparing groups variable as string and numbers
groups = [];
for j = 1:83
ar = data_matrix_ICS.artery{j};
groups = [groups; ar];
end
save ('var_dependencies\groups_str', 'groups')
a = (groups=="lad")*1;
b = (groups=="rca")*2;
c = (groups=="cir")*3;
groups = a+b+c;
save('var_dependencies\groups_num', 'groups')
%%Creating data for using spss program of statistics
load('var_dependencies\leaflet10')
prepared_data_spss_ics = [leafletvar "groups"; data_matrix_ICS.vars groups];
prepared_data_spss_delta = [leafletvar "groups"; data_matrix_delta.vars groups];
xlswrite([output 'data_spss_ics.xlsx'], prepared_data_spss_ics);
xlswrite([output 'data_spss_delta.xlsx'],prepared_data_spss_delta);
%%Saving the local variables in mat format
save([output 'data_matrix_delta'],'data_matrix_delta');
save([output 'data_matrix_ICS'],'data_matrix_ICS');
fclose('all');
end