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Add Math/Scientific category (#61)

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* Add Math/Scientific category

* Add ordered-float library

* Move num-trait recomendation to Math section

* Add ndarray
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Nico Burns 2023-01-04 20:50:58 +00:00 committed by GitHub
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@ -313,13 +313,6 @@
"notes": "Concatenating and manipulating identifiers"
}]
},
{
"name": "Abstracting over different number types",
"recommendations": [{
"name": "num",
"notes": "Traits like Number, Add, etc that allow you write functions that are generic over the specific numeric type"
}]
},
{
"name": "Safe type casts",
"recommendations": [{
@ -375,6 +368,53 @@
}
]
},
{
"slug": "math-scientific",
"name": "Math / Scientific",
"description": "The <a href=\"https://lib.rs/crates/num\">num</a> crate is trusted and has a variety of numberical functionality that is missing from the standard library.",
"subgroups": [],
"purposes": [
{
"name": "Abstracting over different number types",
"recommendations": [{
"name": "num-traits",
"notes": "Traits like Number, Add, etc that allow you write functions that are generic over the specific numeric type"
}]
},
{
"name": "Big Integers",
"recommendations": [
{ "name": "num-bigint", "notes": "It's not the fastest, but it's part of the trusted num library." },
{ "name": "rug", "notes": "LGPL licensed. Wrapper for GMP. Much faster than num-bigint." }
]
},
{
"name": "Big Decimals",
"recommendations": [
{ "name": "rust_decimal", "notes": "The binary representation consists of a 96 bit integer number, a scaling factor used to specify the decimal fraction and a 1 bit sign." }
]
},
{
"name": "Sortable Floats",
"recommendations": [
{ "name": "ordered-float", "notes": "Float types that don't allow NaN and are therefore orderable. You can also use the <code>total_cmp</code> method from the standard library like <code>.sort_by(|a, b| a.total_cmp(&b))</code>." }
]
},
{
"name": "Linear Algebra",
"recommendations": [
{ "name": "nalgebra", "notes": "General-purpose linear algebra library with transformations and statically-sized or dynamically-sized matrices. However it supports only vectors (1d) and matrices (2d) and not higher-dimensional tensors." },
{ "name": "ndarray", "notes": "Less featureful than nalgebra but supports arbitrarily dimensioned arrays" }
]
},
{
"name": "DataFrames",
"recommendations": [
{ "name": "polars", "notes": "Similar to the Pandas library in Python but in pure Rust. Uses the Apache Arrow Columnar Format as the memory model." }
]
}
]
},
{
"slug": "ffi",
"name": "FFI / Interop",