mathpad 2.1.0

Simplified interface to Sympy for solving physics, engineering and maths problems

mathpad

mathpad is a robust Computer Algebra System (CAS) library built on top of SymPy, providing a simple and intuitive way to solve engineering, science, and math problems using Python.

Quickstart

1. Install using package manager of choice. For example, pip:

pip install mathpad

2. Import and use the library in python:

Code	Display
from mathpad import * v = 5 * m / s mph = "mph" * miles / hour eqn = mph == v.eval()

Documentation

Currently the only in-depth documentation is Walkthrough.ipynb. You can access it on the JupyterLite Sandbox Site here.

Showcase

Feature	Example	Display
Units	m m / s ** 2 feet.in_units(cm) (V * A).in_units(watt)
Values	v = 2.5 * m / s c = m(5)
Symbols	t = "t" * seconds y = "\\hat{y}_1" * volts
Symbolic Functions	a = "a(t)" * m / s ** 2
Equations	eqn = (v == a * t)
Solving	sln, = solve([eqn], solve_for=[a]) sln[a]
Algebra	simplify(e ** (1j * pi)) expand((t + 1)(t + 2)) factor(t**2 + 3 * t * s + 2) subs((t + 1)(t + 2), { t: 5 })
Calculus	diff(a, wrt=t, order=1) integral(a, wrt=t, between=(0, 10))
Vectors	O = R3("O") # 3D frame of reference v1 = O[1, 2, 3] x, y, z = ("x", "y", "z") * m v2 = O[x, y, z] v3 = "v_3" @ O v2.cross(v3)
Matrices	O2 = R2("O2") A = Mat[O, O2]( [1, 2], [3, 4], [5, 6] ) v2_wrt_O2 = v2 @ A B = Mat[O2, O]("B") I = Mat[O2, O2].I
Numpy Compatibility	y = sin(t) y_fn = as_numpy_func(y) y_fn({ t: [1, 2, 3] }) import numpy as np y_fn({ t: np.arange( start=0, stop=2 * np.pi, step=np.pi / 12 ) })	array([0.84147098, 0.90929743, 0.14112001]) array([0. , 0.25881905, 0.5 , 0.70710678, 0.8660254 , 0.96592583, 1. , 0.96592583, 0.8660254 , 0.70710678, 0.5 , 0.25881905])
Code Generation	generate_c_code(theta, [t])

Credits

This package was created with Cookiecutter and the browniebroke/cookiecutter-pypackage project template.