NeuroMath
NeuroMath is a lightweight symbolic mathematical DSL (Domain Specific Language) built on top of SymPy.
It provides a clean notebook-style computation experience with both CLI and Streamlit GUI support.
✨ Features
- Symbolic computation
- Variable assignment
- Function definitions
- Differentiation
- Expression evaluation
- Built-in constants (
pi,e) - CLI interface
- Notebook-style Streamlit GUI
- Lightweight and easy to extend
📦 Installation
Install from PyPI:
pip install neuromath
# MathScript Language Reference 📚
A comprehensive guide to built-in functions and operations in MathScript.
## Table of Contents
- [Built-in Functions](#built-in-functions)
- [Math Functions](#math-functions)
- [Symbolic Functions](#symbolic-functions)
---
## Built-in Functions
### Basic Operations
| Function | Description |
|----------|-------------|
| `print(value)` | Print output to console |
| `typeof(value)` | Get type of value |
| `shape(matrix)` | Get matrix dimensions |
| `det(matrix)` | Calculate matrix determinant |
| `trans(matrix)` | Transpose matrix |
| `inv(matrix)` | Calculate matrix inverse |
### Matrix Operations
| Function | Description |
|----------|-------------|
| `identity(n)` | Create n×n identity matrix |
| `zeroes(rows, cols)` | Create matrix filled with zeros |
| `dot(v1, v2)` | Dot product of vectors |
| `cross(v1, v2)` | Cross product of vectors |
| `norm(v)` | Vector norm/magnitude |
| `unit(v)` | Convert to unit vector |
### Linear Algebra Functions
| Function | Description |
|----------|-------------|
| `eigenval(matrix)` | Calculate eigenvalues |
| `eigenvec(matrix)` | Calculate eigenvectors |
| `solve_linear(A, b)` | Solve linear system Ax = b |
### Visualization
| Function | Description |
|----------|-------------|
| `plot(f(x), x, start, end)` | Create 2D function plot |
| `plot_surface(f(x,y), x, y, x_start, x_end, y_start, y_end)` | Create 3D surface plot |
---
## Math Functions
### 📐 Trigonometric Functions
| Function | Description |
|----------|-------------|
| `sin(x)` | Sine of angle x |
| `cos(x)` | Cosine of angle x |
| `tan(x)` | Tangent of angle x |
| `arcsin(x)` | Inverse sine (arcsine) |
| `arccos(x)` | Inverse cosine (arccosine) |
| `arctan(x)` | Inverse tangent (arctangent) |
### Exponential & Logarithmic Functions
| Function | Description |
|----------|-------------|
| `exp(x)` | Exponential (e^x) |
| `log(x)` or `ln(x)` | Natural logarithm |
| `sqrt(x)` | Square root |
| `abs(x)` | Absolute value |
| `pow(x, y)` | Power (x^y) |
---
## Symbolic Functions
### Calculus & Algebra
| Function | Description |
|----------|-------------|
| `integrate(f(x), x)` | Perform symbolic integration |
| `diff(f(x), x)` | Perform symbolic differentiation |
| `limit(f(x), x, point)` | Calculate limit at a point |
| `solve(equation, variable)` | Solve algebraic equations |
| `summation(expr, (var, start, end))` | Compute series summation |
| `simplify(expr)` | Simplify mathematical expressions |
| `factor(expr)` | Factor algebraic expressions |
---
## Quick Examples
```mathscript
// Matrix operations
A = identity(3)
B = zeroes(2, 3)
det_A = det(A)
// Calculus
f(x) = x^2 + 3x + 2
derivative = diff(f(x), x)
integral = integrate(f(x), x)
// Visualization
plot(sin(x), x, 0, 2π)
Metadata
Release files for neuromath 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| neuromath-0.2.0.tar.gz | 20.9 kB | Without provenance | Details for neuromath-0.2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| neuromath-0.2.0-py3-none-any.whl | Python 3 | none | any | Details for neuromath-0.2.0-py3-none-any.whl |
Total release size: 42.5 kB
Release files / neuromath-0.2.0.tar.gz
| Download URL | neuromath-0.2.0.tar.gz |
|---|---|
| Size | 20.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
3d6d3f310789304135bfa00a3dd61166a673ddc0391730cd13b39ea9ffe8ec0b
|
|
BLAKE2b-256 checksum How to use checksums |
25b026ca22a05b0da4098886669602ad1934f46cecd7eebd9b2f9326b211b7a4
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.11
|
Release files / neuromath-0.2.0-py3-none-any.whl
| Download URL | neuromath-0.2.0-py3-none-any.whl |
|---|---|
| Size | 21.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
025641a9cd3dcc3a8aee030c0b9b74400943d4a59a5b1179d9ee22df1a343618
|
|
BLAKE2b-256 checksum How to use checksums |
c229681cc4c73dc168e7b0412e185599ee081786c40cc5286e69dea2f8f90e86
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.10.11
|
Security for neuromath 0.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.