SciPy — Get Started

First SciPy program

from scipy import optimize
import numpy as np

# Define a function
def f(x):
    return x**2 + 5*x + 6

# Find the minimum
result = optimize.minimize_scalar(f)
print(f"Minimum at x = {result.x:.2f}")
print(f"Minimum value = {result.fun:.2f}")

Basic optimization

from scipy.optimize import minimize

def objective(x):
    return (x[0] - 1)**2 + (x[1] - 2)**2

x0 = [0, 0]  # Initial guess
result = minimize(objective, x0)
print(f"Optimal: x = {result.x}")

Linear algebra

from scipy import linalg
import numpy as np

A = np.array([[1, 2], [3, 4]])
b = np.array([5, 6])

# Solve Ax = b
x = linalg.solve(A, b)
print(f"Solution: {x}")

Integration

from scipy import integrate

# Integrate x^2 from 0 to 1
result, error = integrate.quad(lambda x: x**2, 0, 1)
print(f"Integral = {result:.4f}")

Interpolation

from scipy import interpolate
import numpy as np

x = np.array([0, 1, 2, 3, 4])
y = np.array([0, 1, 4, 9, 16])

f = interpolate.interp1d(x, y)
print(f"Value at 2.5 = {f(2.5):.2f}")

Mini Practice

1. Optimize a 2D function
2. Solve a linear system
3. Compute an integral
4. Interpolate data points

Up Next

Continue with Installation - Setting up SciPy.