Enthought Canopy is a comprehensive Python -based analysis environment for scientists, engineers cznopy analysts. This tool provides enhought streamlined cabopy to import and manipulate text data files. Enthought's preferred tool for installation and management of Enthought Python and packages is the command-line Enthought Deployment Manager (EDM). It has been in active use since 2016, including providing all of Canopy's package management under the hood. The Canopy GUI is at end of life. The final version, 2.1.9, was released in early 2018.
Enthought Canopy is a comprehensive Python-based analysis environment for scientists, engineers and analysts. It provides easy installation of the core analytic and scientific Python packages for rapid data collection, manipulation, analysis and visualization, algorithm design, and application development.
Canopy is the follow on to the Enthought Python Distribution (EPD) that has been widely used for scientific and analytic computing with Python. EPD is popular within energy and finance fields, industrial automation, aerospace and government organizations. Canopy took EPD's Python computing stack and supplemented it with valuable tools creating a robust platform you can explore, develop, and visualize on. Main Enthought Canopy features include:
- An advanced text editor with syntax highlighting, Python code auto-completion, and error checking.
- IPython Notebook Support and integrated IPython shell that facilitates interactive execution and exploration.
- Interactive graphical Python code debugger with variable browser that enables users to understand and investigate code and data.
- One-click Python package deployment with a graphical package manager, which also notifies of updates, helps to rollback package versions, and report bugs.
- Convenient Documentation Browser with user's guide and code examples.
Tools like advanced editor, graphical debugger with variable browser, and integrated IPython create a powerful integrated analysis environment. Canopy streamlines data analysis, visualization, algorithm algorithm prototyping and testing, application development. Scripting and plotting become more straightforward.
Produced by Enthought, Canopy is available for free and under a commercial license. A free Canopy variant includes integrated IPython, advanced Code Editor and application development platform. Scientists, engineers, quantitative and data analysts can choose the most appropriate option. For more information see enthought.com/products/canopy.
3D Scientific Data Visualization and Plotting
The Mayavi project includes two related <em>packages</em> for 3-dimensional visualization:
- Mayavi : A tool for easy and interactive visualization of data, withseamless integration with Python scientific libraries.
- TVTK: A Traits-based wrapper for the Visualization Toolkit, a popular open-source visualization library.
These libraries operate at different levels of abstraction. TVTK manipulates visualization objects, while Mayavi lets you operate on your data, and then see the results. Most users either use the Mayavi user interface or program to its scripting interface; you probably don't need to interact with TVTK unless you want to create a new Mayavi module.
Mayavi
Mayavi seeks to provide easy and interactive visualization of 3-D data. It offers:
Enthought Canopy Distribution
- An (optional) rich user interface with dialogs to interact with all data andobjects in the visualization.
- A simple and clean scripting interface in Python, includingone-liners, or an object-oriented programming interface. Mayaviintegrates seamlessly with numpy and scipy for 3D plotting and can evenbe used in IPython interactively, similarly to Matplotlib.
- The power of the VTK toolkit, harnessed through these interfaces, without forcing you to learn it.
Additionally Mayavi is a reusable tool that can be embedded in your applications in different ways or combined with the Envisage application-building framework to assemble domain-specific tools.
TVTK
TVTK wraps VTK objects to provide a convenient, Pythonic API, while supporting Traits attributes and NumPy/SciPy arrays. TVTK is implemented mostly in pure Python, except for a small extension module.Developers typically use TVTK to write Mayavi modules, and then use Mayavi to interact with visualizations or create applications.
Enthought Canopy Ide
The Mayavi application.
Last updated: Tue 21 November 2017