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chore: minor clean-up
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‎lib/node_modules/@stdlib/blas/ext/base/snansumkbn2/docs/repl.txt

+2-2
Original file line numberDiff line numberDiff line change
@@ -4,8 +4,8 @@
44
ignoring `NaN` values and using a second-order iterative Kahan–Babuška
55
algorithm.
66

7-
The `N` and stride parameters determine which elements in the strided
8-
array are accessed at runtime.
7+
The `N` and stride parameters determine which elements in the strided array
8+
are accessed at runtime.
99

1010
Indexing is relative to the first index. To introduce an offset,
1111
use a typed array view.

‎lib/node_modules/@stdlib/blas/ext/base/snansumkbn2/manifest.json

+19-19
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@@ -1,8 +1,8 @@
11
{
2-
"options": {
2+
"options": {
33
"task": "build"
44
},
5-
"fields": [
5+
"fields": [
66
{
77
"field": "src",
88
"resolve": true,
@@ -23,28 +23,28 @@
2323
"resolve": true,
2424
"relative": false
2525
}
26-
],
27-
"confs": [
28-
{
26+
],
27+
"confs": [
28+
{
2929
"task": "build",
30-
"src": [
31-
"./src/snansumkbn2.c"
32-
],
33-
"include": [
34-
"./include"
35-
],
36-
"libraries": [
37-
"-lm"
38-
],
39-
"libpath": [],
40-
"dependencies": [
30+
"src": [
31+
"./src/snansumkbn2.c"
32+
],
33+
"include": [
34+
"./include"
35+
],
36+
"libraries": [
37+
"-lm"
38+
],
39+
"libpath": [],
40+
"dependencies": [
4141
"@stdlib/math/base/assert/is-nanf",
4242
"@stdlib/napi/export",
4343
"@stdlib/napi/argv",
4444
"@stdlib/napi/argv-int64",
4545
"@stdlib/napi/argv-strided-float32array"
46-
]
47-
},
46+
]
47+
},
4848
{
4949
"task": "benchmark",
5050
"src": [
@@ -77,5 +77,5 @@
7777
"@stdlib/math/base/assert/is-nanf"
7878
]
7979
}
80-
]
80+
]
8181
}

‎lib/node_modules/@stdlib/stats/base/dists/gamma/README.md

+15-15
Original file line numberDiff line numberDiff line change
@@ -133,20 +133,20 @@ var gammaCDF = gamma.cdf.factory( alpha, beta );
133133
var cdf = filledarrayby( x.length, 'float64', gammaCDF );
134134

135135
// Output the PDF and CDF values:
136-
console.log( 'x values:', x );
137-
console.log( 'PDF values:', pdf );
138-
console.log( 'CDF values:', cdf );
136+
console.log( 'x values: %s', x );
137+
console.log( 'PDF values: %s', pdf );
138+
console.log( 'CDF values: %s', cdf );
139139

140140
// Compute statistical properties:
141141
var theoreticalMean = gamma.mean( alpha, beta );
142142
var theoreticalVariance = gamma.variance( alpha, beta );
143143
var theoreticalSkewness = gamma.skewness( alpha, beta );
144144
var theoreticalKurtosis = gamma.kurtosis( alpha, beta );
145145

146-
console.log( 'Theoretical Mean:', theoreticalMean );
147-
console.log( 'Theoretical Variance:', theoreticalVariance );
148-
console.log( 'Skewness:', theoreticalSkewness );
149-
console.log( 'Kurtosis:', theoreticalKurtosis );
146+
console.log( 'Theoretical Mean: %s', theoreticalMean );
147+
console.log( 'Theoretical Variance: %s', theoreticalVariance );
148+
console.log( 'Skewness: %s', theoreticalSkewness );
149+
console.log( 'Kurtosis: %s', theoreticalKurtosis );
150150

151151
// Generate random samples from the gamma distribution:
152152
var rgamma = gammaRandomFactory( alpha, beta );
@@ -157,12 +157,12 @@ var samples = filledarrayby( n, 'float64', rgamma );
157157
var sampleMean = mean( n, samples, 1 );
158158
var sampleVariance = variance( n, 1, samples, 1 );
159159

160-
console.log( 'Sample Mean:', sampleMean );
161-
console.log( 'Sample Variance:', sampleVariance );
160+
console.log( 'Sample Mean: %s', sampleMean );
161+
console.log( 'Sample Variance: %s', sampleVariance );
162162

163163
// Compare sample statistics to theoretical values:
164-
console.log( 'Difference in Mean:', abs( theoreticalMean - sampleMean ) );
165-
console.log( 'Difference in Variance:', abs( theoreticalVariance - sampleVariance ) );
164+
console.log( 'Difference in Mean: %s', abs( theoreticalMean - sampleMean ) );
165+
console.log( 'Difference in Variance: %s', abs( theoreticalVariance - sampleVariance ) );
166166

167167
// Demonstrate that the sum of `k` gamma variables is a gamma-distributed sum of `k` gamma(α, β) variables with same β is `gamma(k*α, β)`:
168168
var k = 5;
@@ -184,15 +184,15 @@ var sumAlpha = k * alpha;
184184
var sumMean = gamma.mean( sumAlpha, beta );
185185
var sumVariance = gamma.variance( sumAlpha, beta );
186186

187-
console.log( 'Sum Theoretical Mean:', sumMean );
188-
console.log( 'Sum Theoretical Variance:', sumVariance );
187+
console.log( 'Sum Theoretical Mean: %s', sumMean );
188+
console.log( 'Sum Theoretical Variance: %s', sumVariance );
189189

190190
// Compute sample mean and variance for the sum:
191191
var sumSampleMean = mean( sumSamples.length, sumSamples, 1 );
192192
var sumSampleVariance = variance( sumSamples.length, 1, sumSamples, 1 );
193193

194-
console.log( 'Sum Sample Mean:', sumSampleMean );
195-
console.log( 'Sum Sample Variance:', sumSampleVariance );
194+
console.log( 'Sum Sample Mean: %s', sumSampleMean );
195+
console.log( 'Sum Sample Variance: %s', sumSampleVariance );
196196
```
197197

198198
</section>

‎lib/node_modules/@stdlib/stats/base/dists/gamma/examples/index.js

+15-15
Original file line numberDiff line numberDiff line change
@@ -43,20 +43,20 @@ var gammaCDF = gamma.cdf.factory( alpha, beta );
4343
var cdf = filledarrayby( x.length, 'float64', gammaCDF );
4444

4545
// Output the PDF and CDF values:
46-
console.log( 'x values:', x );
47-
console.log( 'PDF values:', pdf );
48-
console.log( 'CDF values:', cdf );
46+
console.log( 'x values: %s', x );
47+
console.log( 'PDF values: %s', pdf );
48+
console.log( 'CDF values: %s', cdf );
4949

5050
// Compute statistical properties:
5151
var theoreticalMean = gamma.mean( alpha, beta );
5252
var theoreticalVariance = gamma.variance( alpha, beta );
5353
var theoreticalSkewness = gamma.skewness( alpha, beta );
5454
var theoreticalKurtosis = gamma.kurtosis( alpha, beta );
5555

56-
console.log( 'Theoretical Mean:', theoreticalMean );
57-
console.log( 'Theoretical Variance:', theoreticalVariance );
58-
console.log( 'Skewness:', theoreticalSkewness );
59-
console.log( 'Kurtosis:', theoreticalKurtosis );
56+
console.log( 'Theoretical Mean: %s', theoreticalMean );
57+
console.log( 'Theoretical Variance: %s', theoreticalVariance );
58+
console.log( 'Skewness: %s', theoreticalSkewness );
59+
console.log( 'Kurtosis: %s', theoreticalKurtosis );
6060

6161
// Generate random samples from the gamma distribution:
6262
var rgamma = gammaRandomFactory( alpha, beta );
@@ -67,12 +67,12 @@ var samples = filledarrayby( n, 'float64', rgamma );
6767
var sampleMean = mean( n, samples, 1 );
6868
var sampleVariance = variance( n, 1, samples, 1 );
6969

70-
console.log( 'Sample Mean:', sampleMean );
71-
console.log( 'Sample Variance:', sampleVariance );
70+
console.log( 'Sample Mean: %s', sampleMean );
71+
console.log( 'Sample Variance: %s', sampleVariance );
7272

7373
// Compare sample statistics to theoretical values:
74-
console.log( 'Difference in Mean:', abs( theoreticalMean - sampleMean ) );
75-
console.log( 'Difference in Variance:', abs( theoreticalVariance - sampleVariance ) );
74+
console.log( 'Difference in Mean: %s', abs( theoreticalMean - sampleMean ) );
75+
console.log( 'Difference in Variance: %s', abs( theoreticalVariance - sampleVariance ) );
7676

7777
// Demonstrate that the sum of `k` gamma variables is a gamma-distributed sum of `k` gamma(α, β) variables with same β is `gamma(k*α, β)`:
7878
var k = 5;
@@ -94,12 +94,12 @@ var sumAlpha = k * alpha;
9494
var sumMean = gamma.mean( sumAlpha, beta );
9595
var sumVariance = gamma.variance( sumAlpha, beta );
9696

97-
console.log( 'Sum Theoretical Mean:', sumMean );
98-
console.log( 'Sum Theoretical Variance:', sumVariance );
97+
console.log( 'Sum Theoretical Mean: %s', sumMean );
98+
console.log( 'Sum Theoretical Variance: %s', sumVariance );
9999

100100
// Compute sample mean and variance for the sum:
101101
var sumSampleMean = mean( sumSamples.length, sumSamples, 1 );
102102
var sumSampleVariance = variance( sumSamples.length, 1, sumSamples, 1 );
103103

104-
console.log( 'Sum Sample Mean:', sumSampleMean );
105-
console.log( 'Sum Sample Variance:', sumSampleVariance );
104+
console.log( 'Sum Sample Mean: %s', sumSampleMean );
105+
console.log( 'Sum Sample Variance: %s', sumSampleVariance );

‎lib/node_modules/@stdlib/stats/base/dists/invgamma/README.md

+14-16
Original file line numberDiff line numberDiff line change
@@ -101,8 +101,6 @@ var y = dist.cdf( 0.5 );
101101

102102
## Examples
103103

104-
<!-- TODO: better examples -->
105-
106104
<!-- eslint no-undef: "error" -->
107105

108106
```javascript
@@ -131,20 +129,20 @@ var invgammaCDF = invgamma.cdf.factory( alpha, beta );
131129
var cdf = filledarrayBy( x.length, 'float64', invgammaCDF );
132130

133131
// Output the PDF and CDF values:
134-
console.log( 'x values:', x );
135-
console.log( 'PDF values:', pdf );
136-
console.log( 'CDF values:', cdf );
132+
console.log( 'x values: %s', x );
133+
console.log( 'PDF values: %s', pdf );
134+
console.log( 'CDF values: %s', cdf );
137135

138136
// Compute statistical properties:
139137
var theoreticalMean = invgamma.mean( alpha, beta );
140138
var theoreticalVariance = invgamma.variance( alpha, beta );
141139
var theoreticalSkewness = invgamma.skewness( alpha, beta );
142140
var theoreticalKurtosis = invgamma.kurtosis( alpha, beta );
143141

144-
console.log( 'Theoretical Mean:', theoreticalMean );
145-
console.log( 'Theoretical Variance:', theoreticalVariance );
146-
console.log( 'Skewness:', theoreticalSkewness );
147-
console.log( 'Kurtosis:', theoreticalKurtosis );
142+
console.log( 'Theoretical Mean: %s', theoreticalMean );
143+
console.log( 'Theoretical Variance: %s', theoreticalVariance );
144+
console.log( 'Skewness: %s', theoreticalSkewness );
145+
console.log( 'Kurtosis: %s', theoreticalKurtosis );
148146

149147
// Generate random samples from the inverse gamma distribution:
150148
var rinvGamma = invgammaRandomFactory( alpha, beta );
@@ -155,21 +153,21 @@ var samples = filledarrayBy( n, 'float64', rinvGamma );
155153
var sampleMean = mean( n, samples, 1 );
156154
var sampleVariance = variance( n, 1, samples, 1 );
157155

158-
console.log( 'Sample Mean:', sampleMean );
159-
console.log( 'Sample Variance:', sampleVariance );
156+
console.log( 'Sample Mean: %s', sampleMean );
157+
console.log( 'Sample Variance: %s', sampleVariance );
160158

161159
// Compare sample statistics to theoretical values:
162-
console.log( 'Difference in Mean:', abs( mean - sampleMean ) );
163-
console.log( 'Difference in Variance:', abs( variance - sampleVariance ) );
160+
console.log( 'Difference in Mean: %s', abs( theoreticalMean - sampleMean ) );
161+
console.log( 'Difference in Variance: %s', abs( theoreticalVariance - sampleVariance ) );
164162

165163
// Demonstrate the relationship between inverse gamma and gamma distributions:
166164
var y = 0.5;
167165
var invGammaCDF = invgamma.cdf( y, alpha, beta );
168166
var gammaCDF = 1.0 - gamma.cdf( 1.0 / y, alpha, 1.0 / beta );
169167

170-
console.log( 'Inverse Gamma CDF at y =', y, ':', invGammaCDF );
171-
console.log( '1 - Gamma CDF at 1/y =', 1 / y, ':', gammaCDF );
172-
console.log( 'Difference:', abs( invGammaCDF - gammaCDF ) );
168+
console.log( 'Inverse Gamma CDF at y = %s: %s', y, invGammaCDF );
169+
console.log( '1 - Gamma CDF at 1/y = %s: %s', 1 / y, gammaCDF );
170+
console.log( 'Difference: %s', abs( invGammaCDF - gammaCDF ) );
173171
```
174172

175173
</section>

‎lib/node_modules/@stdlib/stats/base/dists/invgamma/examples/index.js

+14-14
Original file line numberDiff line numberDiff line change
@@ -43,20 +43,20 @@ var invgammaCDF = invgamma.cdf.factory( alpha, beta );
4343
var cdf = filledarrayBy( x.length, 'float64', invgammaCDF );
4444

4545
// Output the PDF and CDF values:
46-
console.log( 'x values:', x );
47-
console.log( 'PDF values:', pdf );
48-
console.log( 'CDF values:', cdf );
46+
console.log( 'x values: %s', x );
47+
console.log( 'PDF values: %s', pdf );
48+
console.log( 'CDF values: %s', cdf );
4949

5050
// Compute statistical properties:
5151
var theoreticalMean = invgamma.mean( alpha, beta );
5252
var theoreticalVariance = invgamma.variance( alpha, beta );
5353
var theoreticalSkewness = invgamma.skewness( alpha, beta );
5454
var theoreticalKurtosis = invgamma.kurtosis( alpha, beta );
5555

56-
console.log( 'Theoretical Mean:', theoreticalMean );
57-
console.log( 'Theoretical Variance:', theoreticalVariance );
58-
console.log( 'Skewness:', theoreticalSkewness );
59-
console.log( 'Kurtosis:', theoreticalKurtosis );
56+
console.log( 'Theoretical Mean: %s', theoreticalMean );
57+
console.log( 'Theoretical Variance: %s', theoreticalVariance );
58+
console.log( 'Skewness: %s', theoreticalSkewness );
59+
console.log( 'Kurtosis: %s', theoreticalKurtosis );
6060

6161
// Generate random samples from the inverse gamma distribution:
6262
var rinvGamma = invgammaRandomFactory( alpha, beta );
@@ -67,18 +67,18 @@ var samples = filledarrayBy( n, 'float64', rinvGamma );
6767
var sampleMean = mean( n, samples, 1 );
6868
var sampleVariance = variance( n, 1, samples, 1 );
6969

70-
console.log( 'Sample Mean:', sampleMean );
71-
console.log( 'Sample Variance:', sampleVariance );
70+
console.log( 'Sample Mean: %s', sampleMean );
71+
console.log( 'Sample Variance: %s', sampleVariance );
7272

7373
// Compare sample statistics to theoretical values:
74-
console.log( 'Difference in Mean:', abs( mean - sampleMean ) );
75-
console.log( 'Difference in Variance:', abs( variance - sampleVariance ) );
74+
console.log( 'Difference in Mean: %s', abs( theoreticalMean - sampleMean ) );
75+
console.log( 'Difference in Variance: %s', abs( theoreticalVariance - sampleVariance ) );
7676

7777
// Demonstrate the relationship between inverse gamma and gamma distributions:
7878
var y = 0.5;
7979
var invGammaCDF = invgamma.cdf( y, alpha, beta );
8080
var gammaCDF = 1.0 - gamma.cdf( 1.0 / y, alpha, 1.0 / beta );
8181

82-
console.log( 'Inverse Gamma CDF at y =', y, ':', invGammaCDF );
83-
console.log( '1 - Gamma CDF at 1/y =', 1 / y, ':', gammaCDF );
84-
console.log( 'Difference:', abs( invGammaCDF - gammaCDF ) );
82+
console.log( 'Inverse Gamma CDF at y = %s: %s', y, invGammaCDF );
83+
console.log( '1 - Gamma CDF at 1/y = %s: %s', 1 / y, gammaCDF );
84+
console.log( 'Difference: %s', abs( invGammaCDF - gammaCDF ) );

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