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Evince VS NumPy

Compare Evince VS NumPy and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Evince logo Evince

Evince is a document viewer for multiple document formats: PDF, Postscript, djvu, tiff, dvi, XPS...

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Evince Landing page
    Landing page //
    2021-07-26
  • NumPy Landing page
    Landing page //
    2023-05-13

Evince features and specs

  • Open Source
    Evince is free and open-source software, allowing users to use, modify, and distribute it without cost.
  • Lightweight
    Evince is designed to be simple and resource-efficient, making it ideal for use on machines with limited resources.
  • Multi-format Support
    Evince supports a variety of document formats including PDF, PostScript, TIFF, DjVu, and DVI.
  • User-Friendly Interface
    Evince features a clean and intuitive interface that is easy to navigate, even for users who are not tech-savvy.
  • Integration with GNOME
    As part of the GNOME project, Evince integrates smoothly with the GNOME desktop environment, offering a cohesive user experience.
  • Annotation Support
    Evince provides features for adding and managing annotations in PDF files, which is useful for reviewing and editing documents.

Possible disadvantages of Evince

  • Limited Advanced Features
    Evince lacks some advanced features found in other PDF viewers, such as extensive editing capabilities and form filling.
  • Occasional Compatibility Issues
    While Evince supports multiple document formats, there can be occasional issues with rendering complex documents accurately.
  • Geared Towards GNOME
    Evince is optimized for the GNOME desktop, which might lead to a less seamless experience on other desktop environments.
  • No Mobile Version
    Evince does not have an official mobile version, thus limiting its accessibility on smartphones and tablets.
  • Limited Customization
    There are fewer customization options in Evince compared to other PDF viewers, which might be a drawback for power users.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Analysis of Evince

Overall verdict

  • Evince is a good choice for users who are looking for a straightforward and reliable document viewer, especially those who are using a GNOME-based Linux distribution. It meets the needs of users who want a no-frills application that performs well and supports various document formats.

Why this product is good

  • Evince is a document viewer developed by the GNOME Project. It is designed to be simple yet powerful, supporting a wide range of document formats, including PDF, PostScript, DjVu, TIFF, XPS, and DVI. Its simplicity and integration with the GNOME desktop make it a popular choice for users who prefer a lightweight and efficient application for viewing documents. Moreover, it comes with features like text selection, search capabilities, and a clean, user-friendly interface.

Recommended for

    Evince is recommended for GNOME users, Linux users seeking a simple and intuitive document viewer, and anyone who needs to open and view multiple types of document formats without requiring advanced editing or annotation features.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Evince videos

+ Add

Evince Learning - Draw with JAZZA review

More videos:

  • Review - Incredible 97% Project Success Ratio | Clients' Review | EvinceDev

NumPy videos

+ Add

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Category Popularity

0-100% (relative to Evince and NumPy)

Evince

NumPy

PDF Editor
100 100%
PDF Editor
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
PDF Tools
100 100%
PDF Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Evince and NumPy

Evince Reviews

Top 10 Adobe Reader Alternatives for Windows
Evince is a free and open source (FOSS) document viewer that is available on Windows, Linux and Unix-like operating systems. It is included as the default PDF viewer in Fedora, Debian and Ubuntu. The program was originally designed for the GNOME desktop environment and, support a multitude of file formats, including PDF, PostScrip, DjVu, TIFF, XPS and DVI.
Source: beebom.com

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
Source: www.analyticsvidhya.com
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. It has been mentiond 122 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Evince mentions (0)

We have not tracked any mentions of Evince yet. Tracking of Evince recommendations started around Mar 2021.

NumPy mentions (122)

View more

What are some alternatives?

When comparing Evince and NumPy, you can also consider the following products

Okular - Okular is a universal document viewer based developed by KDE.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

Sumatra PDF - Sumatra PDF is a slim PDF/DjVu/EPUB/XPS/CHM/CBR/CBZ/MOBI viewer for Windows.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Atril - Atril is a simple multi-page document viewer. Atril is a fork of Evince.

OpenCV - OpenCV is the world's biggest computer vision library

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