Type-hinted, simplified interface to `sympy` for solving engineering, science and maths problems.
MIT License
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.
pip
:pip install mathpad
python
:from mathpad import *
v = 5 * m / s
mph = "mph" * miles / hour
eqn = mph == v.eval()
Currently the only in-depth documentation is Walkthrough.ipynb
. You can access it on the JupyterLite Sandbox Site here.
m
m / s ** 2
feet.in_units(cm)
(V * A).in_units(watt)
v = 2.5 * m / s
c = m(5)
t = "t" * seconds
y = "\\hat{y}_1" * volts
a = "a(t)" * m / s ** 2
eqn = (v == a * t)
sln, = solve([eqn], solve_for=[a])
sln[a]
simplify(e ** (1j * pi))
expand((t + 1)(t + 2))
factor(t**2 + 3 * t * s + 2)
subs((t + 1)(t + 2), { t: 5 })
diff(a, wrt=t, order=1)
integral(a, wrt=t, between=(0, 10))
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)
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
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])
generate_c_code(theta, [t])
This package was created with Cookiecutter and the browniebroke/cookiecutter-pypackage project template.