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NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]
Diagram of a typical 1D array. A one-dimensional array (or single dimension array) is a type of linear array. Accessing its elements involves a single subscript which can either represent a row or column index. As an example consider the C declaration int anArrayName[10]; which declares a one
The fundamental strategy underlying the raster data model is the tessellation of a plane, into a two-dimensional array of squares, each called a cell or pixel (from "picture element"). In digital photography , the plane is the visual field as projected onto the image sensor ; in computer art , the plane is a virtual canvas; in geographic ...
Dia has special objects to help draw entity-relationship models, Unified Modeling Language (UML) diagrams, flowcharts, network diagrams, and simple electrical circuits. It is also possible to add support for new shapes by writing simple XML files, using a subset of Scalable Vector Graphics (SVG) to draw the shape.
NumPy, a BSD-licensed library that adds support for the manipulation of large, multi-dimensional arrays and matrices; it also includes a large collection of high-level mathematical functions. NumPy serves as the backbone for a number of other numerical libraries, notably SciPy. De facto standard for matrix/tensor operations in Python.
Graphic types include line, bar or point plots in 2D and 3D, including anaglyph plots of 3D surfaces and other 3D plots. Euler has an API to use the open raytracer POV-Ray . Euler handles symbolic computations via Maxima, which is loaded as a separate process, communicating with Euler through pipes.
The Mandelbrot set within a continuously colored environment. The Mandelbrot set (/ ˈ m æ n d əl b r oʊ t,-b r ɒ t /) [1] [2] is a two-dimensional set with a relatively simple definition that exhibits great complexity, especially as it is magnified.