Upsurge alternatives and similar libraries
Based on the "Math" category.
Alternatively, view Upsurge alternatives based on common mentions on social networks and blogs.
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VectorMath
A Swift library for Mac and iOS that implements common 2D and 3D vector and matrix functions, useful for games or vector-based graphics -
SwiftMath
DISCONTINUED. 📐 A math framework for Swift. Includes: vectors, matrices, complex numbers, quaternions and polynomials. -
Swift-MathEagle
A general math framework to make using math easy. Currently supports function solving and optimisation, matrix and vector algebra, complex numbers, big int, big frac, big rational, graphs and general handy extensions and functions.
InfluxDB - Purpose built for real-time analytics at any scale.
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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README
Upsurge
Upsurge implements multi-dimensional data structures and operations. It brings numpy-like operations to Swift.
Upsurge no longer supports DSP and other linear operations, please use Surge for that. Surge and Upsurge play nice together.
Features
- [x] Tensor and tensor slicing:
tensor.asMatrix(1, 1, 0...4, 0...4)
- [x] Matrix and matrix operations:
let result = A * B′
- [x] ValueArrays with explicit copying and numeric operators:
let result = A • B
Installation
Upsurge supports both CocoaPods (pod 'Upsurge'
) and Carthage (github "aleph7/Upsurge"
). For macOS apps you can use the Swift Package Manager to install Upsurge by adding the proper description to your Package.swift file:
import PackageDescription
let package = Package(
name: "YOUR_PROJECT_NAME",
targets: [],
dependencies: [
.Package(url: "https://github.com/aleph7/Upsurge.git", Version(0,8,.max)),
]
)
Usage
Arrays and vector operations
All of Upsurge's linear (1-dimensional) operations can be performed on anything that conforms to LinearType
. Swift's built-in arrays and array slices conform to LinearType
, of course. But Upsurge also defines the ValueArray
class to store a one-dimensional collection of values. ValueArray
is very similar to Swift's Array
but it is optimized to reduce unnecessary memory allocation. These are the most important differences:
- Its instances have a fixed size defined on creation. When you create a
ValueArray
you can define a capacityvar a = ValueArray<Double>(capacity: 100)
and then append elements up to that capacity. Or you can create it with specific elementsvar a: ValueArray = [1.0, 2.0, 3.0]
but then you can't add any more elements after. - It is a class. That means that creating a new variable will only create a reference and modifying the reference will also modify the original. For instance doing
var a: ValueArray = [1, 2, 3]; var b = a
and thenb[0] = 5
will result ina
being[5, 2, 3]
. If you want to create a copy you need to dovar b = ValueArray(a)
orvar b = a.copy()
. - You can create an uninitialized
ValueArray
by doingvar a = ValueArray<Double>(capacity: n)
orvar a = ValueArray<Doube>(count: n)
. This is good for when you are going to fill up the array yourself. But you can also usevar a = ValueArray(count: n, repeatedValue: 0.0)
if you do want to initialize all the values.
Creating arrays
Create a ValueArray
with specific literal elements when you know ahead of time what the contents are, and you don't need to add more elements at a later time:
let a: ValueArray = [1.0, 3.0, 5.0, 7.0]
Create a ValueArray
with a capacity and then fill it in when you are loading the contents from an external source or have a very large array:
let a = ValueArray<Double>(capacity: 100)
for v in intputSource {
a.append(v)
}
Finally there is a way of initializing both the capacity and the count of a ValueArray
. You should rarely need this but it's there for when you are doing operations on existing arrays using low-level APIs that take pointers:
func operation(a: ValueArray<Double>) {
let N = a.count
let b = ValueArray<Double>(count: N)
// ...
}
Vector arithmetic
You can perform operations on ValueArray
in an intuitive manner:
let a: ValueArray = [1.0, 3.0, 5.0, 7.0]
let b: ValueArray = [2.0, 4.0, 6.0, 8.0]
let addition = a + b // [3.0, 7.0, 11.0, 15.0]
let product = a • b // 100.0
Matrix operations
import Upsurge
let A = Matrix<Double>([
[1, 1],
[1, -1]
])
let C = Matrix<Double>([
[3],
[1]
])
// find B such that A*B=C
let B = inv(A) * C // [2.0, 1.0]′
// Verify result
let r = A*B - C // zero
Tiling
A block Matrix
can be formed by repeating a 1-D ValueArray
or 2-D Matrix
mxn times.
import Upsurge
let a = ValueArray = [1.0, 2.0]
// Tile source array 2 times in each directon,
// returning a 2X4 block matrix
let A = a.tile(2, 2)
let B = Matrix<Double>([
[1.0, 2.0],
[3.0, 4.0]
)]
// Tile source matrix 2 times in each directon,
// returning a 4x4 block matrix
let r = B.tile(2, 2)
Tensors
The Tensor
class makes it easy to manipulate multi-dimensional data. You can easily slice or flatten a tensor to get matrices and vectors that you can operate on.
License
Upsurge is available under the MIT license. See the LICENSE file for more info.
*Note that all licence references and agreements mentioned in the Upsurge README section above
are relevant to that project's source code only.