v1.3.3-1 - Fixed Eigen function

yoshi-seals1.3.3-1/yoshi_seals.egg-info/PKG-INFO

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+Metadata-Version: 2.1
+Name: yoshi-seals
+Version: 1.3.3.post1
+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 Eigenvalues and his Eigenvectors.
+        
+        * 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 eigenvalues and all real eigenvectors, this function uses the power method to find the eigenvalues and inverse power method for the eigenvector.
+        
+        ### 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

yoshi-seals1.3.3-1/yoshi_seals.egg-info/SOURCES.txt

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+README.md
+setup.py
+Seals/__init__.py
+Seals/eigen/__init__.py
+Seals/eigen/eigen.py
+Seals/insert/__init__.py
+Seals/insert/insert.py
+Seals/process/__init__.py
+Seals/process/process.py
+Seals/scan/__init__.py
+Seals/scan/scan.py
+Seals/write/__init__.py
+Seals/write/write.py
+yoshi_seals.egg-info/PKG-INFO
+yoshi_seals.egg-info/SOURCES.txt
+yoshi_seals.egg-info/dependency_links.txt
+yoshi_seals.egg-info/requires.txt
+yoshi_seals.egg-info/top_level.txt

yoshi-seals1.3.3-1/yoshi_seals.egg-info/dependency_links.txt

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+

yoshi-seals1.3.3-1/yoshi_seals.egg-info/requires.txt

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+numpy
+pandas

yoshi-seals1.3.3-1/yoshi_seals.egg-info/top_level.txt

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+Seals