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BCVL358C VTU Notes: Problem Solving with Python 2022

BCVL358C VTU Notes : Master computational logic with our BCVL358C Problem Solving with Python notes. Learn data structures, control flows, and file handling specifically tailored for engineering applications under the VTU 2022 Scheme. Also Download BCV358B VTU Notes PDF

Problem Solving with Python

BCVL358C

2022 Scheme

Module 1 : Introduction to Python

Introduction to Python: Installing Python and Python packages, Managing virtual environments with venv module Introduction to NumPy arrays:Array creation, indexing, data types, broadcasting, copies and views, universal functions, I/O with NumPy

Module 2 : Introduction to NumPy and SciPy

Introduction to NumPy and SciPy:NumPy subpackages– linalg, fft, random, polynomials, SciPy subpackages– linalg, fftpack, integrate, interpolate, optimize Introduction to Matplotlib: Plotting 2D graphs with Matplotlib, annotations, legend, saving plots to file, bar and pie charts, line plots

Module 3 : Linear algebra using NumPy and SciPy

Linear algebra using NumPy and SciPy:Solving linear simultaneous equations using NumPy and SciPy using numpy.linalg and scipy.linalg – solve, inverse, determinant, least square solution, Linear algebra using NumPy and SciPy (continued): Decomposition using lu and cholesky. Solving eigenvalue problems using NumPy and SciPy:Using numpy.linalg and scipy.linalg – eig, eigvals.

Module 4 : Solving initial value problems for ODE systems using scipy

Solving initial value problems for ODE systems using scipy.integrate subpackage – solve_ivp, RK45, LSODA. Numerical integration of functions using SciPy:Using scipy.integratesubpackage– Definite integral using Gaussian quadrature – quad and quadrature Numerical integration of fixed samples using scipy.integratesubpackage– Trapezoidal rule trapezoid, Simpson’s 1/3 rule using Simpson, Romberg integration romb.

Module 5 : Determining roots of equations using SciPyusing scipy

Determining roots of equations using SciPyusing scipy.optimizesubpackage– Bisection method bisect, Brent’s method brentq, Newton-Raphson method newton. Symbolic computing using SymPy and solving civil engineering problems using SymPy: Introduction, defining symbols, derivatives, integrals, limits, expression evaluation, expression simplification, solving equations, solving differential equations.