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Older Versions/yoshi-seals1.2/README.md

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+# 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`