File: test.factory.js

package info (click to toggle)
node-stdlib 0.0.96%2Bds1%2B~cs0.0.429-2
  • links: PTS, VCS
  • area: main
  • in suites: sid, trixie
  • size: 421,476 kB
  • sloc: javascript: 1,562,831; ansic: 109,702; lisp: 49,823; cpp: 27,224; python: 7,871; sh: 6,807; makefile: 6,089; fortran: 3,102; awk: 387
file content (222 lines) | stat: -rw-r--r-- 5,773 bytes parent folder | download
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
/**
* @license Apache-2.0
*
* Copyright (c) 2018 The Stdlib Authors.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
*    http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

'use strict';

// MODULES //

var tape = require( 'tape' );
var isnan = require( '@stdlib/math/base/assert/is-nan' );
var abs = require( '@stdlib/math/base/special/abs' );
var exp = require( '@stdlib/math/base/special/exp' );
var PINF = require( '@stdlib/constants/float64/pinf' );
var NINF = require( '@stdlib/constants/float64/ninf' );
var EPS = require( '@stdlib/constants/float64/eps' );
var factory = require( './../lib/factory.js' );


// FIXTURES //

var positiveMean = require( './fixtures/julia/positive_mean.json' );
var negativeMean = require( './fixtures/julia/negative_mean.json' );
var largeVariance = require( './fixtures/julia/large_variance.json' );


// TESTS //

tape( 'main export is a function', function test( t ) {
	t.ok( true, __filename );
	t.equal( typeof factory, 'function', 'main export is a function' );
	t.end();
});

tape( 'the function returns a function', function test( t ) {
	var mgf = factory( 0.0, 1.0 );
	t.equal( typeof mgf, 'function', 'returns a function' );
	t.end();
});

tape( 'if provided `NaN` for any parameter, the created function returns `NaN`', function test( t ) {
	var mgf;
	var y;

	mgf = factory( 0.0, 1.0 );
	y = mgf( NaN );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( NaN, 1.0 );
	y = mgf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( 1.0, NaN );
	y = mgf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( NaN, NaN );
	y = mgf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( NaN, NaN );
	y = mgf( NaN );
	t.equal( isnan( y ), true, 'returns NaN' );

	t.end();
});

tape( 'if provided a negative `s`, the created function always returns `NaN`', function test( t ) {
	var mgf;
	var y;

	mgf = factory( 0.0, -1.0 );

	y = mgf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	y = mgf( 0.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( 0.0, NINF );
	y = mgf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( PINF, NINF );
	y = mgf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( NINF, NINF );
	y = mgf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	mgf = factory( NaN, NINF );
	y = mgf( 2.0 );
	t.equal( isnan( y ), true, 'returns NaN' );

	t.end();
});

tape( 'if provided `s = 0`, the created function evaluates the MGF of the degenerate distribution', function test( t ) {
	var mgf;
	var y;

	mgf = factory( 0.0, 0.0 );

	y = mgf( 0.5 );
	t.equal( y, 1.0, 'returns exp( 0.0 * 0.5 )' );

	mgf = factory( 2.0, 0.0 );
	y = mgf( 0.5 );
	t.equal( y, exp( 1.0 ), 'returns exp( 2.0 * 0.5 )' );

	y = mgf( 2.0 );
	t.equal( y, exp( 4.0 ), 'returns exp( 2.0 * 2.0 )' );

	t.end();
});

tape( 'the created function evaluates the MGF for `x` given positive `mu`', function test( t ) {
	var expected;
	var delta;
	var mgf;
	var tol;
	var mu;
	var s;
	var x;
	var y;
	var i;

	expected = positiveMean.expected;
	x = positiveMean.x;
	mu = positiveMean.mu;
	s = positiveMean.s;
	for ( i = 0; i < x.length; i++ ) {
		mgf = factory( mu[i], s[i] );
		y = mgf( x[i] );
		if ( expected[i] !== null ) {
			if ( y === expected[i] ) {
				t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
			} else {
				delta = abs( y - expected[ i ] );
				tol = 2.0 * EPS * abs( expected[ i ] );
				t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
			}
		}
	}
	t.end();
});

tape( 'the created function evaluates the MGF for `x` given negative `mu`', function test( t ) {
	var expected;
	var delta;
	var mgf;
	var tol;
	var mu;
	var s;
	var x;
	var y;
	var i;

	expected = negativeMean.expected;
	x = negativeMean.x;
	mu = negativeMean.mu;
	s = negativeMean.s;
	for ( i = 0; i < x.length; i++ ) {
		mgf = factory( mu[i], s[i] );
		y = mgf( x[i] );
		if ( expected[i] !== null ) {
			if ( y === expected[i] ) {
				t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
			} else {
				delta = abs( y - expected[ i ] );
				tol = 2.0 * EPS * abs( expected[ i ] );
				t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
			}
		}
	}
	t.end();
});

tape( 'the created function evaluates the MGF for `x` given large variance ( = large `s`)', function test( t ) {
	var expected;
	var delta;
	var mgf;
	var tol;
	var mu;
	var s;
	var x;
	var y;
	var i;

	expected = largeVariance.expected;
	x = largeVariance.x;
	mu = largeVariance.mu;
	s = largeVariance.s;
	for ( i = 0; i < x.length; i++ ) {
		mgf = factory( mu[i], s[i] );
		y = mgf( x[i] );
		if ( expected[i] !== null ) {
			if ( y === expected[i] ) {
				t.equal( y, expected[i], 'x: '+x[i]+', mu: '+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
			} else {
				delta = abs( y - expected[ i ] );
				tol = 2.0 * EPS * abs( expected[ i ] );
				t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
			}
		}
	}
	t.end();
});