manujajay / scipy-starter

SciPy Starter

This repository offers a beginner's guide to SciPy, a Python library used for scientific and technical computing. It includes examples of how to use SciPy for optimization, integration, interpolation, and solving algebraic equations.

Prerequisites

• Python installed on your machine
• Basic knowledge of Python and mathematics

Installation

Install SciPy

1. Install SciPy using pip:

   pip install scipy

Basic Usage Examples

1. Optimization

• Using SciPy's optimization module to find the minimum of a function:

  from scipy.optimize import minimize
  
  def objective(x):
      return x**2
  
  result = minimize(objective, x0=2)
  print("Minimum:", result.x)

2. Integration

• Calculating the integral of a function:

  from scipy.integrate import quad
  
  def integrand(x):
      return x**2
  
  result, _ = quad(integrand, 0, 1)
  print("Integral:", result)

3. Interpolation

• Interpolating data points:

  from scipy.interpolate import interp1d
  import numpy as np
  
  x = np.arange(0, 10)
  y = np.sin(x)
  interpolator = interp1d(x, y, kind='cubic')
  
  xnew = np.arange(0, 9, 0.1)
  ynew = interpolator(xnew)

4. Solving Linear Systems

• Solving a system of linear equations:

  from scipy.linalg import solve
  
  a = [[3, 1], [1, 2]]
  b = [9, 8]
  x = solve(a, b)
  print("Solution:", x)

Contributing

Contributions that enhance the examples, improve the documentation, or expand the repository with new features are welcome. Please fork the repository, make your changes, and submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for more details.