Search Results for "matplotlib"

...Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them. Behind the scenes, seaborn uses matplotlib to draw its plots. For interactive work, it’s recommended to use a Jupyter/IPython interface in matplotlib mode, or else you’ll have to call matplotlib.pyplot.show() when you want to see the plot.

Euler is a powerful all-in-one numerical software and includes Maxima for seamless symbolic computations. Euler supports Latex for math display, Povray for photo-realistic 3D scenes, Python, Matplotlib and C for scripting, and contains a full programming language. Features include libraries for numerical algorithms, optimization, plotting in 2D and 3D, graphics export, a complete help system, tutorials and examples. Euler runs in Windows natively, or in Linux via Wine. It is completely free of royalties. The source is licensed under GPL.

...PhaseSpace allows you to plot the phase space of the dynamical system you are studying, its critical points and the curves of slope zero and infinite.It can also plot the solutions of the system and it's vector field. To use PhaseSpace you'll need to have Python installed along with Matplotlib and Numpy.

... - Implemented a 3d surface plot (GLSurface) based on OpenGL (ScienPlot v1.3.2 and above) - ColorMap surface, trisurface, Pie, Polar plots, and 3D height field, 3dBar, scatter plots (under developing), and more - Column by column plotting/calculation - LaTex commands enclosed by $ symbols can be used for the labels in Graph - Accept txt(Text) and csv(Comma separated values) formatted data - Save, copy, print Graph - Use spread sheets to display data - Textboard to organize the results - Graphs in a publishable quality - Source codes based on: Python Numpy Scipy Matplotlib WxPython Visvis etc. - Special functions - Drag and drop data files - Python console is back (since v1.3.3), capable of reusing column data - Debye and Guinier models for SANS / SAX data - More apps in our Web below

...You need to install Python, NumPy/SciPy and CVXOPT ( FFTW enabled) to use this software. The test.py program demonstrates a simple application in Compressive Sensing and shows how to use l1min module. You need to install matplotlib to plot diagrams. Note: pyL1min can handle complex as well as real vectors.

...The program runs on any Python-enabled platform, including GNU/Linux and MS\Windows OSs. To run the program you will need a python interpreter ver. 2.x and compatible versions of numpy, scipy and matplotlib libraries. See screenshot for usage reference.

PyParticles is an opensource particles simulation tool box entirely written in python. It support the most popular integrations methods and the most relevant forces model. It also offer a nice looking OpneGL interface or at your preference a Matplotlib based GUI. PyParticles as a forces models implements Gravity, spring, constant force and electrostatic and the user defined vector field force. As a integrations method it includes Euler, Midpoint, Runge Kutta, Störmer Verlet and Leap frog.

A small simulator for Mendelian genetics, genetic drift, natural selection and random mutations, built on matplotlib and wxpython. A graph will be generated that traces the distribution of genotypes at successive generations.

PyMaTi is a simple and easy to use GUI for numerical and scientific computing in Python. It surrounds well know packages NumPy and Matplotlib and provides possibility to immediately play with numerical python from intuitive user interface.

...With the back-end built using the numpy and scikit-learn libraries, as a toolkit, ExoPlanet couples fast and well tested algorithms, a UI designed over the Qt4 framework, and graphs rendered using Matplotlib to provide the user with a rich interface, rapid analytics and interactive visuals. ExoPlanet is designed to have a minimal learning curve, allowing researchers to focus on the applicative aspect of Machine Learning rather than their implementation details. It provides algorithms for unsupervised and supervised learning, which may be done with continuous or discrete labels. ...