Easily step through discrete time intervals, calling functions as you go!
> The TimeScrubber component provides a UI for playing back and scrubbing through a number of discrete time steps. It's primarily used to scrub through map layers.
Encodings that map abstract data to visual representation.
Tiny O(1) discrete time scheduler
It’s a website that lets you design small Discrete-Time Markov Chains and interact with it
javascript implementation of Dunning's T-Digest for streaming quantile approximation
minimal discrete time simulation in javascript
Scales and color schemes for visual encoding.
Sequential, diverging and categorical color schemes.
Discrete uniform distributed pseudorandom numbers.
Simuli.JS is an open source framework for modeling and simulating systems in discrete time. It designed to build and simulate complex interactive systems while monitoring the internal flow of information and internal system states. The framework provides
Find how many values of a discrete periodic function are contained in an interval.
Find the nearest value of a discrete periodic function, given a point.
Create an array containing pseudorandom numbers drawn from a discrete uniform distribution.
Graphical primitives for visualization, such as lines and areas.
A Discrete Wavelet Transform (DWT) library for the web.
Vue-component including graph settings interface and resulting rendered graph. For using graph only (creating picture without user interface) use [miplots4](https://github.com/milaboratory/miplots4).
A frame-synced render loop for JavaScript
Generate pseudorandom numbers drawn from a discrete uniform distribution.
Manage a cluster of child processes
Utils for collecting telemetry data from Sanity CLI and Sanity Studio
Experimental implementation of a new declarative API for gesture handling in react-native
Format validation for Ajv v7+
TypeScript definitions for d3-time
surge synthesizer -- create filter coefficients for various filter types
surge synthesizer -- handle for managing the sample rate
A discrete-time events simulation framework inspired by Simpy
Baseband is a discrete-time signals and systems processor
Compositional discrete-time state machines, after MIT 6.01 chapter 4.
The perfect smoother: A discrete-time version of spline smoothing for equally spaced data.
surge synthesizer -- nonlinear feedback filter
DARE, LQR, gramians, and pole placement for nabled Physical AI control
High-performance block-circulant tensor operations using FFT
Dead simple implementation of Discrete Kalman filter for object tracking purposes
An efficient implementation of Allen's interval relations for Rust's range types.
surge synthesizer -- dual delay effect
Use to simulate discrete time models. See the examples directory for examples.
Iterate over time ranges in discrete chunks.
A library for time conversion and intercomparison of multiple time series data in the case of handling time series data of the type that specifies the time using indexes of time steps since origin time. It handles time units notation like 'hours since 2001-01-01 00:00:00', which is originate from udunits library and also is used in CF-convension of NetCDF. The main purpose of this library is to describe the time axis when dealing with time series of observational data and climate data.
bins x, y data into discrete bins using constant time binning. Useful.
For representing Numerical Sequences, especially Discret-Time signals
* http://rubysideshow.rubyforge.org/irb_callbacks == DESCRIPTION: This gem adds callbacks to irb, intended for you to override at your discretion. == FEATURES: irb's control flow looks like this: loop: * prompt * eval * output This gem adds three callbacks to each phase. module IRB: * self.before_prompt * self.around_prompt (call yield) * self.after_prompt * self.before_eval * self.around_eval (call yield) * self.after_eval * self.before_output * self.around_output (call yield) * self.after_output == SYNOPSIS: # Here's my ~/.irbrc file (which is run at irb startup) require 'rubygems' require 'irb_callbacks' require 'benchmark' # This little snippet will time each command run via the console. module IRB def self.around_eval(&block) @timing = Benchmark.realtime do block.call end end def self.after_output puts "=> #{'%.3f' % @timing} seconds" end end # And a sample irb session: $ irb irb(main):001:0> 1_000_000.times { |x| x + 1 } => 1000000 => 0.330 seconds == CAVEATS: The three around_* callbacks all require you to call the block that's passed in. If you don't do it, undefined behavior may occur. == INSTALL: * sudo gem install irb_callbacks == LICENSE: (The MIT License) Copyright (c) 2008 Mike Judge Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the 'Software'), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED 'AS IS', WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
YPetri is a DSL (domain-specific language) for modelling of dynamical systems. It is biologically inspired, but concerns of biology and chemistry have been purposely separated away from it. YPetri caters solely to the two main concerns of modelling, model specification and simulation, and it excels in the first one. Dynamical systems are described under a Petri net paradigm. YPetri implements a universal Petri net abstraction that integrates discrete/continous, timed/timeless and stoichiometric/nonstoichiometric dichotomies of the extended Petri nets, and allows efficient specification of any kind of dynamical system. Like Petri nets themselves, YPetri was inspired by problems from the domain of chemistry (biochemical pathway modelling), but is not specific to it. Other gems, YChem and YCell are planned to cater to the concerns specific to chemistry and cell biochemistry. A lower-level extension of YPetri is currently under development under the name YNelson. Its usage is practically identical to YPetri, so any YPetri user can now consider using YNelson instead. YNelson covers additional concerns: it allows relations among nodes and parameters to be specified under a zz structure paradigm (developed by Ted Nelson) and it is also aimed towards providing a higher level of abstraction in Petri net specification by providing commands that create more than one Petri net node per command. YPetri documentation is avalable online, but due to formatting issues, you may prefer to generate the documentation on your own by running rdoc in the gem directory. As for the user manuals, there are currently 3 documents applicable for both YPetri and YNelson, whose master copies are stored in the YNelson source directory: 1. Introduction to YNelson and YPetri (hands-on tutorial), 2. Object model of YNelson and YPetri, 3. Introduction to Ruby for YNelson users. These manuals are written to allow beginners, including those unfamiliar with Ruby, to start working with YPetri and/or YNelson. For an example of how YPetri can be used to model complex dynamical systems, see the eukaryotic cell cycle model which I released as "cell_cycle" gem.
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