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VTK - The Visualization Toolkit

VTK - The Visualization Toolkit

News CEI-EnSight Python Wrapping - KitwarePublic From KitwarePublic This section describes how to wrap ITK classes for being used from Python. Python will need to be installed along with the Python development headers (Python.h). If you need to specify a specific Python version or a custom location of the headers, the following CMake configuration variables can be modified: Step 2: Turn on Python wrapping in the ITK configuration Turn ON the CMake configuration ITK_WRAP_PYTHON. Step 3: Select the pixel types and dimensions to build You can choose what pixel types and dimensions to build into the wrapped interface. For the dimensions to support, set the CMake configuration variable ITK_WRAP_DIMS. The pixel types to support are boolean variables in the pattern ITK_WRAP_<pixel type>. ITK_WRAP_float ITK_WRAP_rgb_unsigned_char ITK_WRAP_vector_double ITK_WRAP_complex_double

Signal and Image Processing Library The Signal and Image Processing Library is a free collection of general-purpose, optimized C++ routines and classes for signal and image processing along with utility classes to aid image and video file manipulation. These routines are typically used in computationally intensive real-time applications, where optimal execution speed is critical. The library also provides efficient implementations for the most common datatypes used in signal and image processing applications. Function Categories in the Library Pointwise operations Pointwise transformation, normalization and thresholding Spectral processing Spectral processing based on the Fast Fourier Transform (FFT) and inverse FFT Linear filtering Convolution, correlation, FIR and IIR filtering Nonlinear filtering Minimum, maximum, median, alpha trimmed mean, OS filtering Binary morphology Erosion, dilation, opening, closing, hit-and-miss, convex hull, skeleton, hole filling, pruning, thickening, thinning, object reconstruction, object shifting

VPython OpenGL Pandore What is Pandore? Pandore is a standardized library of image processing operators. The current version contains image processing operators that operate on grayscale, color and multispectral, 1D, 2D and 3D images. The library provides: a set of executable operators; a C++ programming environment. Who is concerned with Pandore? Pandore is mainly dedicated to image processing experts because the use of the library needs skills on image processing operations and on the way to combine them to perform real world image processing applications. How does Pandore work? The library is a set of executable programs performing directly on image files. Permission to use, copy, modify, and distribute code and its documentation for any purpose, without fee, and without a written agreement is hereby granted. Systems: WINDOWS 95/97/NT/XP/2000/VISTA, UNIX, LINUX, MACOS X, CYGWINLanguage: C++ Download area: Sources and binaries.

PyQtGraph - Scientific Graphics and GUI Library for Python Model Builder plotexplorer_gui 0.3.2 Package Index > plotexplorer_gui > 0.3.2 Not Logged In plotexplorer_gui 0.3.2 Downloads ↓ A wxpython/matplotlib script for plotting and contrasting a collection of graphs This script creates a matplotlib window next to the sortable list of checkboxes from which graphs can be selected. This script depends upon wxpython and matplotlib. Downloads (All Versions): 7 downloads in the last day 84 downloads in the last week 555 downloads in the last month Website maintained by the Python community Real-time CDN by Fastly / hosting by Rackspace / design by Tim Parkin

Monte - machine learning in Python Overview — SimPy 3.0.2 documentation Event discrete simulation for Python. News | PyPI | Bitbucket | Issues | Mailing list >>> import simpy>>>>>> def clock(env, name, tick):... while True:... print(name, yield env.timeout(tick)...>>> env = simpy.Environment()>>> env.process(clock(env, 'fast', 0.5))<Process(clock) object at 0x...>>>> env.process(clock(env, 'slow', 1))<Process(clock) object at 0x...>>>> 0slow 0fast 0.5slow 1fast 1.0fast 1.5 SimPy is a process-based discrete-event simulation framework based on standard Python. Its event dispatcher is based on Python’s generators and can also be used for asynchronous networking or to implement multi-agent systems (with both, simulated and real communication). Processes in SimPy are simple Python generator functions and are used to model active components like customers, vehicles or agents. Simulations can be performed “as fast as possible”, in real time (wall clock time) or by manually stepping through the events.