Search Results for "note-taking"

...You can change to the legacy color scheme by toggling the variable _MENU_THEME between default and legacy. You can set variable _GIT_LIMIT for limited output. It will affect the "changelogs" and "branch tree" options. You can also exclude files from the stats. Note that it works with any alphanumeric, glob, or regex that git respects.

...Thanks to ROOT, it is easily scriptable in CINT (c++ like syntax) and Python. Is is available both for Unix and Windows platforms (a dedicated platform archive is available on request). Note : if you have downloaded version 3.12 before the 8th of february, a patch exists for a minor bug on TOutputFileKey file, don't hesitate to ask us.

...The data is held in spreadsheets which are referred to as tables with column-based data (typically X and Y values for 2D plots) or matrices (for 3D plots). The spreadsheets as well as graphs and note windows are gathered in a project and can be organized using folders. The built-in analysis operations include column/row statistics, (de)convolution, FFT and FFT-based filters. Scripting Console support in-place evaluation of mathematical expressions and scrtipting interface to ECMAScript like dynamic scripting language(java script). ...

... * PubMed ID: 29562348 * DOI: 10.1093/nar/gky175 -> PLEASE MOVE OR MAKE A COPY OF 'DATA' FOLDER INTO YOUR INTENSIVE TEST FOLDER (I.E. LINUX, MAC OR WINDOWS SPECIFIED FOLDER) TO ALLOW THE PROGRAM TO FIND THE PREDESIGNED DATA. * UPDATE NOTE: -> Sep-1-2020: add an update for Ubuntu-20.04. You will need Boost library installed (sudo apt-get install libboost-all-dev) -> Mar-7-2018: revise header terms in the output file

Multi-categorization Recommendation Adjusting (MRA) is to optimize the results of recommendation based on traditional(basic) recommendation models, through introducing objective category information and taking use of the feature that users always get the habits of preferring certain categories. Besides this, there are two advantages of this improved model: 1) it can be easily applied to any kind of existing recommendation models. And 2) a controller is set in this improved model to provide controllable adjustment range, which thereby makes it possible to provide optional modes of recommendation aiming different kinds of users.

A MATLAB package to simulate sample paths of the solution of a Itô or Stratonovich stochastic differential equation (SDE), compute statistics and estimate the parameters from data. A note of caution: SDE Toolbox is no more developed but it's still downloadable. Its inferential capabilities can be considered surpassed (at best). Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and non-parametric Monte Carlo likelihood methods were chosen for their ability to treat both one-dimensional and multivariate SDE systems, although the quality of the inferential results can't match those obtained using more advanced techniques. ...