Search Results for "factor"

ReactiveMP.jl is a Julia package that provides an efficient reactive message passing based Bayesian inference engine on a factor graph. The package is a part of the bigger and user-friendly ecosystem for automatic Bayesian inference called RxInfer. While ReactiveMP.jl exports only the inference engine, RxInfer provides convenient tools for model and inference constraints specification as well as routines for running efficient inference both for static and real-time datasets.

...Here we take a simple boxplot of fuel consumption as a function of cylinders and let it transition between the number of gears available in the cars. As this is a discrete split (gear being best described as an ordered factor) we use transition_states and provide a relative length to use for transition and state view. As not all combinations of data are present there are states missing a box. We define that when a box appears it should fade into view, whereas it should shrink away when it disappears. Lastly, we decide to use a sinusoidal easing for all our aesthetics (here, only y is changing) gganimate is available on CRAN and can be installed with install.packages('gganimate').

...The msno.matrix nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion. At a glance, date, time, the distribution of injuries, and the contribution factor of the first vehicle appear to be completely populated, while geographic information seems mostly complete, but spottier. The sparkline at right summarizes the general shape of the data completeness and points out the rows with the maximum and minimum nullity in the dataset. This visualization will comfortably accommodate up to 50 labelled variables.

...However if you have a large number of images (several hundrets or more than thousand) and control points, PTOptimizer typically needs much time (up to several days) for the optimization of the parameters. fastPTOptimizer decreases the processing time for large panoramas (a speedup factor of 100 or more can be achieved). This is possible by exploiting the sparseness of the mathematical optimization problem. The original PTOptimizer uses the well proven Levenberg Marquardt optimizer lmdif from the minpack software. fastPTOptimizer uses a "sparse" optimizer lmdif_sparse that uses the SuiteSparse library.

We present an improved ball and stick representation called HyperBalls. This type of depiction is particularly useful to represent dynamic phenomena, such as the evolution of non covalent bonds and takes advantage of GPU capabilities. HyperBalls are now fully integrated into the UnityMol software and are actively developed in that context. You will find the most up-to-date versions of the shaders in the http://unitymol.sourceforge.net project.