Treffer: Fortran Programming with NumPy Arrays.
Weitere Informationen
Python loops over large array structures are known to run slowly. Tests with class Grid2D from Chapter 4.3.5 show that filling a two-dimensional array of size 1100 × 1100 with nested loops in Python may require about 150 times longer execution time than using Fortran 77 for the same purpose. With Numerical Python (NumPy) and vectorized expressions (from Chapter 4.2) one can speed up the code by a factor of about 50, which gives decent performance. [ABSTRACT FROM AUTHOR]
Copyright of Python Scripting for Computational Science (978-3-540-73915-9) is the property of Springer eBooks and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)