Matplotlib is a 2D graphics package used for Python for application development, interactive scripting,and publication-quality image generation across user interfaces and operating systems
Computing in Science & Engineering Template
Write in a clean editor, then format for Computing in Science & Engineering in one click — DocuGuru applies the official IEEE template with numbered references and exports a submission-ready PDF plus the editable LaTeX source. Free to start.
About the Computing in Science & Engineering format
Computing in Science & Engineering is a peer-reviewed journal published by IEEE, covering Scientific Computing and Data Management, Distributed and Parallel Computing Systems, Diverse Scientific and Economic Studies. Over its lifetime it has published 3,373 papers, which have received 111,806 citations.
| Publisher | IEEE |
|---|---|
| Reference style | Numbered (IEEE) Numbered — [1], [2] in the text [1] A. Smith, B. Jones, and C. Lee, "A representative article title," Computing in Science & Engineering, vol. 12, no. 3, pp. 45–58, 2023.
Formats any DOI in Computing in Science & Engineering style. No sign-up. |
| Publishes research in | Scientific Computing and Data Management Distributed and Parallel Computing Systems Diverse Scientific and Economic Studies Human auditory perception and evaluation Parallel Computing and Optimization Techniques |
| ISSN | 1521-9615 |
| Citation impact (2-yr) | 1.32 |
| h-index | 97 |
| i10-index | 781 |
| Top institutions publishing here | Argonne National Laboratory |
| Journal website | books.google.com |
| You get | A submission-ready PDF and the editable LaTeX source — ready to submit. |
Papers published in Computing in Science & Engineering per year
Citation impact of Computing in Science & Engineering by publication year
Citations each year’s papers have accumulated so far — the most recent years are still building up.
Most-cited papers in Computing in Science & Engineering
In the Python world, NumPy arrays are the standard representation for numerical data and enable efficient implementation of numerical computations in a high-level language. As this effort shows, NumPy performance can be improved through three techniques: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts.
Python offers basic facilities for interactive work and a comprehensive library on top of which more sophisticated systems can be built. The IPython project provides on enhanced interactive environment that includes, among other features, support for data visualization and facilities for distributed and parallel computation
Python is an excellent "steering" language for scientific codes written in other languages. However, with additional basic tools, Python transforms into a high-level language suited for scientific and engineering code that's often fast enough to be immediately useful but also flexible enough to be sped up with additional extensions.
Computing in science and engineering is now ubiquitous: digital technologies underpin, accelerate, and enable new, even transformational, research in all domains. Access to an array of integrated and well-supported high-end digital services is critical for the advancement of knowledge. Driven by community needs, the Extreme Science and Engineering Discovery Environment (XSEDE) project substantially enhances the…