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This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic...

Bayesian statistics is an approach to inferential statistics based on Bayes' theorem, where available knowledge about parameters in a statistical model is updated with the information in observed data. The background knowledge is expressed as a prior distribution and combined with observational data in the form of a likelihood function to determine the posterior distribution. The posterior can also be used for making predictions about future events. Bayesian statistics is a departure from...

ATTENTION: Cumulative update 2.5.0 has been released!! The update works for any previous 2.x.x version. If upgrading from version v1.x.x, please download and install v2.0.0 first. IMPORTANT FIXES in respect to base v2.0.0 version: v.2.5.0 introduces the Differential Attenuation and Cube Viewer utilities, and migrates user database to *.json files v2.4.3 fixes a with K element in the fit-approx method v2.4.3 fixes and issue where saving plots with fit-approx or a auto-wizard could...

Software oscilloscope using Python and tkinter. Supports multiple sources: socket, file, audio, USB. Displays data by samples, time or frequency. Scales the input automatically or manually.

Software oscilloscope using Python and tkinter. Supports multiple sources: socket, file, audio, USB. Displays data by samples, time or frequency. Scales the input automatically or manually. It has been renamed "pdatascope" to avoid a name-clash with Pyscope, a scoping package on PyPi. See https://sourceforge.net/p/pydatascope/ for the latest code.