DataMelt example la4j

Create new dense, sparse matrix
Code: "la4j_matrix.py". Programming language: Python DMelt Version 1. Last modified: 07/23/2017. License: Pro
https://datamelt.org/code/cache/la4j_matrix_4421.py
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"""
Lightweight Java sparse/dense matrix library

    See La4j for detail 


      
      The la4j is open source and 100% Java library that provides Linear Algebra primitives (matrices and vectors) and algorithms. The la4j was initially designed to be lightweight and simple tool for passionate Java developers. It has been started as student project and turned into one of the most popular Java packages for matrices and vectors.
       
      
      The key features of the la4j are listed bellow:
      
      
        Great performance allied with beautiful design
        No dependencies and tiny size (~150kb jar)
        Fluent object-oriented/functional API
        Sparse (CRS, CCS) and dense (1D/2D arrays) matrices
        Linear systems solving (Gaussian, Jacobi, Zeidel, Square Root, Sweep and other)
        Matrices decomposition (Eigenvalues/Eigenvectors, SVD, QR, LU, Cholesky and other)
        MatrixMarket/CSV IO formats support for matrices and vectors
      
      

      

"""


from org.la4j.matrix.dense import *
from org.la4j.matrix.sparse import *
from org.la4j.matrix import *

print "Dense matrix"
m=Basic2DMatrix.from2DArray([[1.0, 2.0, 3.0 ],  [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]])
m.multiplyByItsTranspose()
print m

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