stdlib-js/stdlib

✨ Standard library for JavaScript and Node.js. ✨

stdlib's Issues

Implement `asind`

Compute the arcsine of x, where the output is in degrees. @stdlib/math/base/special/asind.

RFC: add `j1`, the Bessel function of order 1

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Bessel functions find frequent application in areas of scientific computing. This RFC proposes to add the Bessel function of order 1. Package name: @stdlib/math/base/special/j1.

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Reference implementations:

• SciPy

Implement `parse-csv`

Comma-separated values. @stdlib/utils/parse-csv.

This is a special case of @stdlib/utils/parse-dsv and should just be a wrapper.

Implement `logit`

Logit function. @stdlib/math/base/special/logit.

RFC: add `j0`, the Bessel function of order 0

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Bessel functions find frequent application in areas of scientific computing. This RFC proposes to add the Bessel function of order 0. Package name: @stdlib/math/base/special/j0.

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Reference implementations:

• SciPy

Implement `increwmean`

Incremental exponentially weighted mean. @stdlib/math/statistics/incr/ewmean.

See reference literature.

Floating point precision - does/ will this library support this?

@kgryte Thanks for the quick merge earlier!

I have a question - is it the intent of this library's math section to provide a means to solve the floating point precision problems in JS?

A concise demonstration of what I'm referring to:

$ node 
> 0.3
0.3
> 0.1 + 0.2
0.30000000000000004

I came across this lib linked from this article and while reading it, this came to mind immediately.

For many common application tasks, minor deviations in precision are unlikely to have a significant effect. However, for numeric computing and applications requiring high precision, poor precision does have a significant effect due to accumulated error. Especially since the built-in Math functions are frequently used by higher-order functions, small deviations compounded many times can lead to significant drift from the "true" value.

... and that paragraph implied that you have solved (or are aiming to solve) this very problem, which I believe is an baseline factor that tends to affect precision in any non-integer math in JS. I've tried looking for references to this specific issue in this lib (and its FAQ), but have not been able to find reference to it yet.

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Does this lib provide a means to solve this?

$ node 
> 0.3
0.3
> 0.1 + 0.2
0.30000000000000004

Related Issues

Does this issue (or feature request) have any related issues?

None.

Questions

Any questions for reviewers?

Yes, see above.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Demo

If relevant, provide a link to a live demo.

Not applicable.

Reproduction

If this issue is a bug report, what steps are required to reproduce the unexpected output? (If this is a feature request, remove this section.)

Not applicable.

Expected Results

What are the expected results? (If this is a feature request, remove this section.)

The following results are expected:

(insert expected results here)

Actual Results

What are the actual results? (If this is a feature request, remove this section.)

The following are the actual results:

$ node 
> 0.3
0.3
> 0.1 + 0.2
0.30000000000000004
> stdlib.math.add([0.1, 0.2])
0.3

Environments

If this issue is a bug report, what environments are affected; e.g., Node v0.4.x, Chrome, IE 11? (If this is a feature request, remove this section.)

v8, likely all JS engine implementations

Implement `acosd`

Compute the arccosine of x where the output is in degrees. @stdlib/math/base/special/acosd.

Implement `incrgmean`

Incremental geometric mean. See @stdlib/math/statistics/incr/mean.

Implement `incrmwstdev`

Incremental moving weighted standard deviation. @stdlib/math/statistics/incr/mwstdev.

Two use cases:

1. Fixed window weights. In which case, should provide a factory method to set the weights beforehand.
2. Weights which accompany each value: accumulator( x, weight ).

[RFC]: add `stats/incr/mskewness`

Moving incremental skewness. See also @stdlib/stats/incr/skewness for the non-moving version.

For similar packages, see https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr.

Implement `incrhmean`

Incremental harmonic mean. See @stdlib/math/statistics/incr/mean.

Implement `parse-tsv`

Tab-separated values. @stdlib/utils/parse-tsv.

This is a special case of @stdlib/utils/parse-dsv and should just be a wrapper.

Implement `incrmwvariance`

Incremental moving weighted variance. @stdlib/math/statistics/incr/mwvariance.

Two use cases:

1. Fixed window weights. In which case, should provide a factory method to set the weights beforehand.
2. Weights which accompany each value: accumulator( x, weight ).

[RFC]: add `stats/incr/wstdev`

Incremental weighted standard deviation. @stdlib/stats/incr/wstdev.

See also an algorithm for computing an incremental weighted variance.

[RFC]: add `stats/incr/wvariance`

Incremental weighted sample variance.

Package: @stdlib/stats/incr/wvariance
Alias: incrwvariance

See @stdlib/math/generics/statistics/incrvariance for the non-weighted package.

See https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr for similar packages.

See reference literature.

Implement `incrmgmean`

Moving incremental geometric mean. See @stdlib/math/statistics/incr/mmean.

Implement `homedir`

See utils-homedir. @stdlib/utils/homedir.

Implement `incrmpcorr`

Moving incremental Pearson Correlation. See @stdlib/math/statistics/incr/mvariance.

Implement `tand`

Compute the tangent of x where x is in degrees. @stdlib/math/base/special/tand.

Implement `parse-dsv`

Delimiter-separated values. @stdlib/utils/parse-dsv.

Note that this package is not simple. The implementation should adhere as best as possible to the various CSV RFCs and pass standard CSV parsing tests.

Ideally, this implementation should be portable and/or share a code base with a streaming variant.

Implement `incrpcorr`

Incremental Pearson Correlation. See @stdlib/math/statistics/incr/variance.

Implement `read-xlsx`

Read XLSX files. @stdlib/fs/read-xlsx.

This package should only focus on xlsx files. Other file formats should be addressed in separate packages.

Implement `asecd`

Compute the inverse secant of x where the output is in degrees. @stdlib/math/base/special/asecd.

RFC: add `y0`, the Bessel function of the second kind of order 0

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Bessel functions find frequent application in areas of scientific computing. This RFC proposes to add the Bessel function of the second kind of order 0. Package name: @stdlib/math/base/special/y0.

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Reference implementations:

• SciPy

Implement `incrcov`

Incremental covariance. See @stdlib/math/statistics/incr/variance.

[RFC]: add `stats/incr/mkurtosis`

Moving incremental kurtosis. See also @stdlib/stats/incr/kurtosis for the non-moving version.

For similar packages, see https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/incr.

RFC: add the inverse logit function

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

This RFC proposes adding support for computing the inverse logit function. The implementation is straightforward:

/**
* @param {number} x - input value
* @returns {number} function result
*/
function expit( x ) {
    return 1.0 / ( 1.0 + exp( -x ) );
}

Package: @stdlib/math/base/special/expit
Alias: base.expit

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Reference implementations:

• SciPy [1][2]

See also @stdlib/math/base/special/logit.

Implement `cosd`

Compute the cosine of x where x is in degrees. @stdlib/math/base/special/cosd.

Implement `read-tsv`

Read a file containing tab-separated values. @stdlib/fs/read-tsv.

This package should leverage parse-tsv. Additionally, a readStream variant is desirable.

Implement `read-dsv`

Read a file containing delimiter-separated values. @stdlib/fs/read-dsv.

This package should leverage parse-dsv. Additionally, a readStream variant is desirable.

Implement `acscd`

Compute the inverse cosecant of x where the output is in degrees. @stdlib/math/base/special/acscd.

Implement `error-to-json`

See utils-error-to-json. @stdlib/utils/error-to-json.

Implement `cotd`

Compute the cotangent of x where x is in degrees. @stdlib/math/base/special/cotd.

Implement `read-csv`

Read a file containing comma-separated values. @stdlib/fs/read-csv.

This package should leverage parse-csv. Additionally, a readStream variant is desirable.

Implement `incrmcov`

Moving incremental covariance. See @stdlib/math/statistics/incr/mvariance.

Implement `tmpdir`

See tmpdir. @stdlib/utils/tmpdir.

Implement `cscd`

Compute the cosecant of x where x is in degrees. @stdlib/math/base/special/cscd.

Implement double factorial

Double factorial. @stdlib/math/base/special/double-factorial.

Implement `incrmwmean`

Incremental moving weighted mean. @stdlib/math/statistics/incr/mwmean.

Two use cases:

1. Fixed window weights. In which case, should provide a factory method to set the weights beforehand.
2. Weights which accompany each value: accumulator( x, weight ).

Implement `secd`

Compute the secant of x where x is in degrees. @stdlib/math/base/special/asecd.

Implement `incrmhmean`

Moving incremental harmonic mean. See @stdlib/math/statistics/incr/hmean.

RFC: add `sind`

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Compute the sine of x where x is in degrees.

Package: @stdlib/math/base/special/sind
Alias: base.sind

For a reference implementation, see Julia.

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

No.

Implement `configdir`

See utils-configdir. @stdlib/utils/configdir.

Implement `atand`

Compute the arctangent of x where the output is in degrees. @stdlib/math/base/special/atand.

Implement `incrprod`

Incremental product. See @stdlib/math/statistics/incr/sum.

RFC: add `y1`, the Bessel function of the second kind of order 1

Checklist

Please ensure the following tasks are completed before filing an issue.

• Read and understood the Code of Conduct.
• Searched for existing issues and pull requests.
• If this is a general question, searched the FAQ for an existing answer.
• If this is a feature request, the issue name begins with RFC: .

Description

Description of the issue (or feature request).

Bessel functions find frequent application in areas of scientific computing. This RFC proposes to add the Bessel function of the second kind of order 1. Package name: @stdlib/math/base/special/y1.

Related Issues

Does this issue (or feature request) have any related issues?

No.

Questions

Any questions for reviewers?

No.

Other

Any other information relevant to this issue (or feature request)? This may include screenshots, references, stack traces, sample output, and/or implementation notes.

Reference implementations:

• SciPy

Implement `incrmprod`

Incremental moving product. See @stdlib/math/statistics/incr/msum.

Implement `incrwmean`

Incremental weighted mean. @stdlib/math/statistics/incr/wmean. See @stdlib/math/statistics/incr/mean.

See also an algorithm for computing a weighted incremental variance.

Implement `acotd`

Compute the inverse cotangent of x where the output is in degrees. @stdlib/math/base/special/acotd.