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test: update variance tests to use accessors
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‎lib/node_modules/@stdlib/stats/base/nanvariancech/test/test.main.js

Lines changed: 128 additions & 30 deletions
Original file line numberDiff line numberDiff line change
@@ -94,115 +94,115 @@ tape( 'the function calculates the population variance of a strided array (ignor
9494
t.end();
9595
});
9696

97-
tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', function test( t ) {
97+
tape( 'the function calculates the population variance of a strided array (ignoring `NaN` values) (accessors)', function test( t ) {
9898
var x;
9999
var v;
100100
var i;
101101

102102
x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ];
103103

104-
v = nanvariancech( x.length, 1, x, 1 );
105-
t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' );
104+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
105+
t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
106106

107107
x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ];
108108

109-
v = nanvariancech( x.length, 1, x, 1 );
110-
t.strictEqual( v, 53.5/(x.length-7), 'returns expected value' );
109+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
110+
t.strictEqual( v, 53.5/(x.length-6), 'returns expected value' );
111111

112112
x = [ -4.0, NaN ];
113113

114-
v = nanvariancech( x.length, 1, x, 1 );
115-
t.strictEqual( isnan( v ), true, 'returns expected value' );
114+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
115+
t.strictEqual( v, 0.0, 'returns expected value' );
116116

117117
x = [ NaN, NaN ];
118118

119-
v = nanvariancech( x.length, 1, x, 1 );
119+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
120120
t.strictEqual( isnan( v ), true, 'returns expected value' );
121121

122122
x = [ NaN ];
123-
v = nanvariancech( x.length, 1, x, 1 );
123+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
124124
t.strictEqual( isnan( v ), true, 'returns expected value' );
125125

126126
x = [ 4.0 ];
127-
v = nanvariancech( x.length, 1, x, 1 );
128-
t.strictEqual( isnan( v ), true, 'returns expected value' );
127+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
128+
t.strictEqual( v, 0.0, 'returns expected value' );
129129

130130
x = [];
131131
for ( i = 0; i < 1e3; i++ ) {
132132
x.push( 100.0 );
133133
}
134-
v = nanvariancech( x.length, 1, x, 1 );
134+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
135135
t.strictEqual( v, 0.0, 'returns expected value' );
136136

137137
x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ];
138-
v = nanvariancech( x.length, 1, x, 1 );
138+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
139139
t.strictEqual( isnan( v ), true, 'returns expected value' );
140140

141141
x = [];
142142
for ( i = 0; i < 1e3; i++ ) {
143143
x.push( NaN );
144144
}
145-
v = nanvariancech( x.length, 1, x, 1 );
145+
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
146146
t.strictEqual( isnan( v ), true, 'returns expected value' );
147147

148148
t.end();
149149
});
150150

151-
tape( 'the function calculates the population variance of a strided array (accessors) (ignoring `NaN` values)', function test( t ) {
151+
tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values)', function test( t ) {
152152
var x;
153153
var v;
154154
var i;
155155

156156
x = [ 1.0, -2.0, -4.0, 5.0, NaN, 0.0, 3.0 ];
157157

158-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
159-
t.strictEqual( v, 53.5/(x.length-1), 'returns expected value' );
158+
v = nanvariancech( x.length, 1, x, 1 );
159+
t.strictEqual( v, 53.5/(x.length-2), 'returns expected value' );
160160

161161
x = [ 1.0, NaN, NaN, -2.0, NaN, -4.0, NaN, 5.0, NaN, 0.0, 3.0, NaN ];
162162

163-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
164-
t.strictEqual( v, 53.5/(x.length-6), 'returns expected value' );
163+
v = nanvariancech( x.length, 1, x, 1 );
164+
t.strictEqual( v, 53.5/(x.length-7), 'returns expected value' );
165165

166166
x = [ -4.0, NaN ];
167167

168-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
169-
t.strictEqual( v, 0.0, 'returns expected value' );
168+
v = nanvariancech( x.length, 1, x, 1 );
169+
t.strictEqual( isnan( v ), true, 'returns expected value' );
170170

171171
x = [ NaN, NaN ];
172172

173-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
173+
v = nanvariancech( x.length, 1, x, 1 );
174174
t.strictEqual( isnan( v ), true, 'returns expected value' );
175175

176176
x = [ NaN ];
177-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
177+
v = nanvariancech( x.length, 1, x, 1 );
178178
t.strictEqual( isnan( v ), true, 'returns expected value' );
179179

180180
x = [ 4.0 ];
181-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
182-
t.strictEqual( v, 0.0, 'returns expected value' );
181+
v = nanvariancech( x.length, 1, x, 1 );
182+
t.strictEqual( isnan( v ), true, 'returns expected value' );
183183

184184
x = [];
185185
for ( i = 0; i < 1e3; i++ ) {
186186
x.push( 100.0 );
187187
}
188-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
188+
v = nanvariancech( x.length, 1, x, 1 );
189189
t.strictEqual( v, 0.0, 'returns expected value' );
190190

191191
x = [ NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN, NaN ];
192-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
192+
v = nanvariancech( x.length, 1, x, 1 );
193193
t.strictEqual( isnan( v ), true, 'returns expected value' );
194194

195195
x = [];
196196
for ( i = 0; i < 1e3; i++ ) {
197197
x.push( NaN );
198198
}
199-
v = nanvariancech( x.length, 0, toAccessorArray( x ), 1 );
199+
v = nanvariancech( x.length, 1, x, 1 );
200200
t.strictEqual( isnan( v ), true, 'returns expected value' );
201201

202202
t.end();
203203
});
204204

205-
tape( 'the function calculates the sample variance of a strided array (accessors) (ignoring `NaN` values)', function test( t ) {
205+
tape( 'the function calculates the sample variance of a strided array (ignoring `NaN` values) (accessors)', function test( t ) {
206206
var x;
207207
var v;
208208
var i;
@@ -271,7 +271,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
271271
t.end();
272272
});
273273

274-
tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN`', function test( t ) {
274+
tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
275275
var x;
276276
var v;
277277

@@ -303,6 +303,23 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a populat
303303
t.end();
304304
});
305305

306+
tape( 'if provided an `N` parameter equal to `1`, the function returns a population variance of `0` provided the first element is not `NaN` (accessors)', function test( t ) {
307+
var x;
308+
var v;
309+
310+
x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
311+
312+
v = nanvariancech( 1, 0, toAccessorArray( x ), 1 );
313+
t.strictEqual( v, 0.0, 'returns expected value' );
314+
315+
x = [ NaN, 1.0, -2.0, -4.0, 5.0, 3.0 ];
316+
317+
v = nanvariancech( 1, 0, toAccessorArray( x ), 1 );
318+
t.strictEqual( isnan( v ), true, 'returns expected value' );
319+
320+
t.end();
321+
});
322+
306323
tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN`', function test( t ) {
307324
var x;
308325
var v;
@@ -320,6 +337,23 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns a sample
320337
t.end();
321338
});
322339

340+
tape( 'if provided an `N` parameter equal to `1`, the function returns a sample variance equal to `NaN` (accessors)', function test( t ) {
341+
var x;
342+
var v;
343+
344+
x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
345+
346+
v = nanvariancech( 1, 1, toAccessorArray( x ), 1 );
347+
t.strictEqual( isnan( v ), true, 'returns expected value' );
348+
349+
x = [ NaN, 1.0, -2.0, -4.0, 5.0, 3.0 ];
350+
351+
v = nanvariancech( 1, 1, toAccessorArray( x ), 1 );
352+
t.strictEqual( isnan( v ), true, 'returns expected value' );
353+
354+
t.end();
355+
});
356+
323357
tape( 'if provided a `correction` parameter yielding a correction term less than or equal to `0`, the function returns `NaN`', function test( t ) {
324358
var x;
325359
var v;
@@ -335,6 +369,21 @@ tape( 'if provided a `correction` parameter yielding a correction term less than
335369
t.end();
336370
});
337371

372+
tape( 'if provided a `correction` parameter yielding a correction term less than or equal to `0`, the function returns `NaN` (accessors)', function test( t ) {
373+
var x;
374+
var v;
375+
376+
x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
377+
378+
v = nanvariancech( x.length, x.length, toAccessorArray( x ), 1 );
379+
t.strictEqual( isnan( v ), true, 'returns expected value' );
380+
381+
v = nanvariancech( x.length, x.length+1, toAccessorArray( x ), 1 );
382+
t.strictEqual( isnan( v ), true, 'returns expected value' );
383+
384+
t.end();
385+
});
386+
338387
tape( 'the function supports a `stride` parameter', function test( t ) {
339388
var x;
340389
var v;
@@ -465,6 +514,28 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` p
465514
t.end();
466515
});
467516

517+
tape( 'if provided a `stride` parameter equal to `0`, the function returns `0` provided the correction term is not less than `0` and the first element is not `NaN` (accessors)', function test( t ) {
518+
var x;
519+
var v;
520+
521+
x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
522+
523+
v = nanvariancech( x.length, 1, toAccessorArray( x ), 0 );
524+
t.strictEqual( v, 0.0, 'returns expected value' );
525+
526+
x = [ NaN, 1.0, -2.0, -4.0, 5.0, 3.0 ];
527+
528+
v = nanvariancech( x.length, 1, toAccessorArray( x ), 0 );
529+
t.strictEqual( isnan( v ), true, 'returns expected value' );
530+
531+
x = [ 1.0, -2.0, -4.0, 5.0, 3.0 ];
532+
533+
v = nanvariancech( x.length, x.length, toAccessorArray( x ), 0 );
534+
t.strictEqual( isnan( v ), true, 'returns expected value' );
535+
536+
t.end();
537+
});
538+
468539
tape( 'the function supports view offsets', function test( t ) {
469540
var x0;
470541
var x1;
@@ -491,3 +562,30 @@ tape( 'the function supports view offsets', function test( t ) {
491562

492563
t.end();
493564
});
565+
566+
tape( 'the function supports view offsets (accessors)', function test( t ) {
567+
var x0;
568+
var x1;
569+
var v;
570+
571+
x0 = new Float64Array([
572+
2.0,
573+
1.0, // 0
574+
2.0,
575+
-2.0, // 1
576+
-2.0,
577+
2.0, // 2
578+
3.0,
579+
4.0, // 3
580+
6.0,
581+
NaN, // 4
582+
NaN
583+
]);
584+
585+
x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
586+
587+
v = nanvariancech( 5, 1, toAccessorArray( x1 ), 2 );
588+
t.strictEqual( v, 6.25, 'returns expected value' );
589+
590+
t.end();
591+
});

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