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Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
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 two programs can exchange variables and ...
MATLAB (an abbreviation of "MATrix LABoratory" [22]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.
This page is a subsection of the list of sequence alignment software. Multiple alignment visualization tools typically serve four purposes: Aid general understanding of large-scale DNA or protein alignments; Visualize alignments for figures and publication; Manually edit and curate automatically generated alignments; Analysis in depth
Asymptote is also notable for having a graphical interface coded in Python (and the Tk widget set), xasy.py – this allows an inexperienced user to quickly draw up objects and save them as .asy source code which can then be examined or edited by hand. The program's syntax was originally described by using a Yacc compatible grammar.
Interactive geometry software (IGS) or dynamic geometry environments (DGEs) are computer programs which allow one to create and then manipulate geometric constructions, primarily in plane geometry. In most IGS, one starts construction by putting a few points and using them to define new objects such as lines , circles or other points.
The algorithm has already been explained to a large extent, but there are further optimizations. The new presented method [4] gets along with only 5 arithmetic operations per step (for 8 pixels) and is thus best suitable for low-performate systems.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.