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
|
// =============================================================================
// Scilab ( http://www.scilab.org/ ) - This file is part of Scilab
// Copyright (C) 2014 - Scilab Enterprises - Pierre-Aime Agnel
//
// This file is distributed under the same license as the Scilab package.
// =============================================================================
// <-- CLI SHELL MODE -->
// <-- unit test for samplef.sci-->
//
//==============================================================================
// Checking error messages
//==============================================================================
fname = "samplef";
err_msg_negative = msprintf(_("%s: Wrong value for input argument #%d: Non-negative values expected.\n"), fname, 3);
err_msg_size_glob = msprintf(_("%s: Wrong size for input argument #%d and #%d: Same size expected.\n"), fname, 2, 3);
err_msg_size_row = msprintf(_("%s: Wrong size for input argument #%d: Same number of rows of the second input argument expected.\n"), fname, 3);
err_msg_size_col = msprintf(_("%s: Wrong size for input argument #%d: Same number of columns of the second input argument expected.\n"), fname, 3);
//========================================
// Error if sum of frequency is negative
n = 100;
X = 1:10;
f = [-10:-1];
func_str = "samplef(n, X, f)";
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
assert_checkerror(func_str, err_msg_negative);
//========================================
// Error if frequency is not the same size af the
X = 1:10;
f = [1:12];
func_str = "samplef(n, X, f)";
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
assert_checkerror(func_str, err_msg_size_glob);
//========================================
// Error if row mode on and size of f does not match the number of rows
X = [1 2 3; 4 5 6];
f = [5 10 15];
func_str = "samplef(n, X, f, ""r"")";
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
assert_checkerror(func_str, err_msg_size_row);
//========================================
// Error if column mode on and size of f does not match the number of columns
X = [1 2 3; 4 5 6];
f = [5 10];
func_str = "samplef(n, X, f, ""c"")";
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
assert_checkerror(func_str, err_msg_size_col);
//==============================================================================
// Checking Normal behaviours for complete size '*'
//==============================================================================
//========================================
// Tests normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3];
f = [0.5 0.3 0.2];
samples = samplef(10, X, f);
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_star = samplef(10, X, f, "*");
//Check both results are identical
assert_checkequal(samples, samples_star);
//========================================
// Tests non normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
f = f * 10;
samples = samplef(10, X, f);
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_star = samplef(10, X, f, "*");
//Check both results are identical
assert_checkequal(samples, samples_star);
//========================================
// Checks 0 frequency value is not taken
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
f = ones(1, 10);
f(4) = 0;
X = 1:10;
samples = samplef(10000, X, f, "*");
assert_checktrue(isempty(find(samples == 4)));
grand("setsd", 0);
f = zeros(1,10);
f(4) = 1;
samples = samplef(10000, X, f, "*");
assert_checkalmostequal(samples, 4 .* ones(1,10000));
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
f = ones(1, 10);
f(4) = 0;
X = 1:10;
X = matrix(X, 2, 5);
//No crash for X matrix and f correct size
samples = samplef(100, X, f, "*");
assert_checktrue(isempty(find(samples == 4)));
//========================================
// Checks consistency of size when called without "orient" options
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
f = [0.1 0.2 0.3; 0.2 0.1 0.1];
X = ["a", "b", "c"; "d", "e", "f"];
samples = samplef(100, X, f);
assert_checkequal(size(samples, 'r'), 1);
assert_checkequal(size(samples, 'c'), 100);
//==============================================================================
// Checking Normal behaviours for row size 'r'
//==============================================================================
//========================================
// Test normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [0.1 0.9];
samples_r_n = samplef(10, X, f, "r");
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_one_n = samplef(10, X, f, 1);
//Check both results are identical
assert_checkequal(samples_r_n, samples_one_n);
//========================================
// Test non normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [1000 9000];
samples_r = samplef(10, X, f, "r");
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_one = samplef(10, X, f, 1);
//Check both results are identical
assert_checkequal(samples_r, samples_one);
//Normalized and non normalized should have the same behaviour
assert_checkequal(samples_r_n, samples_r);
//========================================
// Checks 0 frequency value is not taken
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [1 0];
samples = samplef(1000, X, f, 1);
assert_checkalmostequal(samples, repmat([1 2 3], 1000, 1));
//==============================================================================
// Checking Normal behaviours for column size 'c'
//==============================================================================
//========================================
// Test normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [0.1 0.7 0.2];
samples_c_n = samplef(10, X, f, "c");
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_two_n = samplef(10, X, f, 2);
//Check both results are identical
assert_checkequal(samples_c_n, samples_two_n);
//========================================
// Test non normalized frequencies
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [100 700 200];
samples_c = samplef(10, X, f, "c");
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
samples_two = samplef(10, X, f, 2);
//Check both results are identical
assert_checkequal(samples_c, samples_two);
//Normalized and non normalized should have the same behaviour
assert_checkequal(samples_c_n, samples_c);
//========================================
// Checks 0 frequency value is not taken
grand("setsd", 0); //Sets the randum number to seed 0 for reproductibility
X = [1 2 3; 4 5 6];
f = [1 0 1];
samples = samplef(10000, X, f, "c");
assert_checktrue(isempty(find(samples == 2 | samples == 5)));
|
