numpy-matrix-js
v1.1.5
Published
A numpy-like Matrix/Array module for Node JS and Browser JS
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numpy-matrix-js
A numpy-like Matrix/Array module for Node JS and Browser JS
Installation & Set Up
NPM
In your terminal, type this command to install the module.
npm install numpy-matrix-js
After that, add this following code to the top of your file to import it.
const np = require('numpy-matrix-js')
After this, you can now use the functions available in the module.
Browser
Add this following script tag to your html file.
<script type="module">
import np from "https://unpkg.com/[email protected]/src/html/index.js"
</script>
Documentation
Initializing
np.zeros(rows, cols)
Creates a new matrix/2d array filled with 0 If you only give 1 parameter, it creates a 1d array.
Parameters | What it is | Required -------------|----------------|---------- rows | number of rows in your array | yes cols | number of columns in your array | no
np.random.rand(rows, cols)
Creates a new matrix/2d array of random values
Parameters | What it is | Required -------------|----------------|---------- rows | number of rows in your array | yes cols | number of columns in your array | yes
Math
np.matmul(a, b)
Multiplies 2 matrices together and returns the result.
Note: Like linear algebra, the columns of the first matrix must match the rows of the second matrix.
Parameters | What it is | Required --------------|---------------|---------- a | First matrix | Yes b | Second matrix | Yes
np.add(a,b)
Adds 2 matrices together and returns the result.
Note: Like linear algebra, the dimensions of both matrices needs to match.
Parameters | What it is | Required -------------|---------------|--------- a | First matrix | Yes b | Second matrix | Yes
np.subtract(a,b)
Subtracts 2 matrices and returns the result.
Note: Like linear algebra, the dimensions of both matrices needs to match.
Parameters | What it is | Required -------------|---------------|--------- a | First matrix | Yes b | Second matrix | Yes
np.transpose(a)
Returns the transposed version of the matrix "a".
Parameters | What it is | Required -------------|---------------|--------- a | Input matrix which needs to be transposed | Yes
Built-in Math Functions
Sigmoid
np.sigmoid(x)
Returns the sigmoid value of whatever "x" value you input
Dsigmoid (Derivative of sigmoid)
np.dsigmoid(x)
Returns the dsigmoid value of whatever "x" value you input
Tanh (Hyperbolic Tangent)
np.tanh(x)
Returns the hyperbolic tangent value of whatever "x" value you input
Softmax
np.softmax(inputs)
Applies the softmax function to the inputs array and returns the new result as an array.
Relu
np.relu(x)
Applies the relu function to the value "x" and returns result.
Leaky Relu
np.leakyrelu(x)
Applies the leaky relu function to the value "x" and returns the result.
Debug
Info
let arr = [[0,0,0],[0,0,0]]
arr.info()
Automatically logs the dimensions of the array that you invoke the function on.
Table
let arr = [[0,0,0],[0,0,0]]
arr.table()
Automatically prints the array to the console in a neat format
HasNaN
let arr = [[0,0,0],[0,0,0]]
arr.hasNaN()
Checks if any of the values of the array are "NaN". If there are values with "NaN", it prints "true" to the console.
Versions
Latest Versions: 1.1.3
Stable Versions:
- 1.1.3: Fixed debug glitches. Added relu functions
- 1.1.1: Working browser support via static import