yoshi-seals 1.2

Numeric Calculus python module in the topic of Linear Algebra

Seals - Numeric Calculus

This python package is made for applied Numeric Calculus of Linear Algebra. It is made with the following objectives in mind:

• Scan csv files to make a numpy matrix.

• Write a matrix into a csv file

• Insert user input into a matrix or a vector.

• Use methods to proccess the matrices.

  • Identity Matrix
  • Gauss Elimination
  • Inverse Matrix
  • Cholesky Decomposition
  • LU Decomposition
  • Cramer

Syntax

The function scan has the following syntax scan(path), where path is the path to your directory.

The function solution has the following syntax write(array,path), where array is the matrix that you desire to output and path is the path to your directory.

The python class Insert has a method for matrix and another for vector, and it has the following syntax Insert.method(array), where Insert is the Python Class and method is either a matrix or a vector and array is either a matrix or a vector.

Processes

The python class process has all the methods described in the first session.

To call the method use a syntax like sl = Seals.process(), where sl is an instance and to use a method you have to append the method in front of the instance like: sl.identity(array).

• The method identity returns a numpy identity matrix of the order of the matrix passed into to it, and it has the following syntax sl.identity(array), which array is a square matrix.

• The method gauss returns a numpy vector containing the vector of variables from the augmented matrix. sl.gauss(matrix), which matrix is the augmented matrix.

• The method inverse returns a numpy inverse matrix of the matrix passed into to it, and it has the following syntax sl.inverse(matrix), which matrix is a square matrix.

• The method cholesky returns a numpy vector containing the vector of variables from the coefficient matrix and the constants vector, and it has the following syntax sl.cholesky(A,b), which A is the coefficient matrix and b is the constants vector.

• The method decomposition returns a numpy vector containing the vector of variables from the coefficient matrix and the constants vector, and it has the following syntax sl.cholesky(A,b), which A is the coefficient matrix and b is the constants vector.

• The method cramer returns a numpy vector containing the vector of variables from the coefficient matrix and the constants vector, and it has the following syntax sl.cholesky(A,b), which A is the coefficient matrix and b is the constants vector.

Installation

To install the package from source cd into the directory and run:

pip install .

or run

pip install yoshi-seals