71 lines
4.2 KiB
Plaintext
71 lines
4.2 KiB
Plaintext
Metadata-Version: 2.1
|
|
Name: yoshi-seals
|
|
Version: 1.3.3
|
|
Summary: Numeric Calculus python module in the topic of Linear Algebra
|
|
Home-page: https://github.com/HideyoshiNakazone/Seals-NumericCalculus.git
|
|
Author: Vitor Hideyoshi
|
|
Author-email: vitor.h.n.batista@gmail.com
|
|
License: UNKNOWN
|
|
Description: # Seals - Numeric Calculus
|
|
|
|
This python namespace 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.
|
|
|
|
* Calculate Eigen Values
|
|
|
|
* Use methods to proccess the matrices.
|
|
* Identity Matrix
|
|
* Gauss Elimination
|
|
* Inverse Matrix
|
|
* Cholesky Decomposition
|
|
* LU Decomposition
|
|
* Cramer
|
|
|
|
## Syntax
|
|
|
|
To call the package *scan* use the syntax: `from Seals import scan`. The package also has a function for *Numpy* arrays and *Pandas* dataframes, and used the following syntax `scan.np(path)` for *Numpy* and `scan.pd(path)` for *Pandas*, where `path` is the path to your directory.
|
|
|
|
To call the package *write* use the syntax: `from Seals import write`. The package also has a function for *Numpy* arrays and *Pandas* dataframes, and uses the following syntax `write.np(array,path)` for *Numpy*, where `array` is the matrix that you desire to output and `path` is the path to your directory, and `write.pd(df,path)` for *Pandas*, where `df` is the matrix that you desire to output and `path` is the path to your directory.
|
|
|
|
To call the package *insert* use the syntax: `from Seals import insert`. The package also has a function for *matrix* and another for *vector*, and it has the following syntax `insert.function(array)`, where `insert` is the *Python Module* and `function` is either a `matrix` or a `vector` and `array` is either a *matrix* or a *vector*.
|
|
|
|
There is also a function that given a matrix it return all real eigen values
|
|
|
|
### Processes
|
|
|
|
To call the module `process` use the syntax: `from Seals import process as sl`, where `sl` is an instance and to use a function you have to append the desired function in front of the instance like: `sl.identity(array)`.
|
|
|
|
* The function *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 function *gauss* returns a *numpy* vector containing the vector of variables from the augmented matrix. `sl.gauss(matrix)`, which `matrix` is the augmented matrix.
|
|
|
|
* The function *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 function *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 function *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 function *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`
|
|
|
|
Platform: UNKNOWN
|
|
Classifier: Programming Language :: Python :: 3
|
|
Classifier: License :: OSI Approved :: GNU General Public License v2 (GPLv2)
|
|
Classifier: Operating System :: OS Independent
|
|
Requires-Python: >=3.6
|
|
Description-Content-Type: text/markdown
|