Search Results for "complex function plotter"
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Showing 14 open source projects for "complex function plotter"
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1
Tree
tree is a library for working with nested data structures
Tree (dm-tree) is a lightweight Python library developed by Google DeepMind for manipulating nested data structures (also called pytrees). It generalizes Python’s built-in map function to operate over arbitrarily nested collections — including lists, tuples, dicts, and custom container types — while preserving their structure. This makes it particularly useful in machine learning pipelines and JAX-based workflows, where complex parameter trees or hierarchical state representations are common. The library provides efficient operations such as flatten, unflatten, and map_structure, enabling users to apply functions to all leaves of a nested structure seamlessly. ... -
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Go Jsonnet
This an implementation of Jsonnet in pure Go
go-jsonnet is a pure Go implementation of the Jsonnet data templating language, which extends JSON with variables, functions, imports, and a standard library so you can generate complex configuration safely. Instead of hand-maintaining massive JSON files, you write concise, reusable templates that evaluate to JSON or YAML, with deterministic semantics and rich error messages. The repository ships both an embeddable VM for Go programs and a command-line interpreter, making it easy to... -
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Symfony ExpressionLanguage
Provides an engine that can compile and evaluate expressions
Symfony ExpressionLanguage is a powerful component that evaluates expressions written in a simple language. It allows developers to write dynamic expressions that can be evaluated at runtime, making it useful for configuration, validation, and business rule processing. ExpressionLanguage is versatile and integrates seamlessly with other Symfony components, enhancing the flexibility of complex applications. -
4
Measurements.jl
Error propagation calculator and library for physical measurements
Error propagation calculator and library for physical measurements. It supports real and complex numbers with uncertainty, arbitrary precision calculations, operations with arrays, and numerical integration. Physical measures are typically reported with an error, a quantification of the uncertainty of the accuracy of the measurement. Whenever you perform mathematical operations involving these quantities you have also to propagate the uncertainty, so that the resulting number will also have... -
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5
plotly
An interactive graphing library for R
This part of the book teaches you how to leverage the plotly R package to create a variety of interactive graphics. There are two main ways to creating a plotly object: either by transforming a ggplot2 object (via ggplotly()) into a plotly object or by directly initializing a plotly object with plot_ly()/plot_geo()/plot_mapbox(). Both approaches have somewhat complementary strengths and weaknesses, so it can pay off to learn both approaches. Moreover, both approaches are an implementation of... -
6
WS2812FX
WS2812 FX library for Arduino and ESP8266
...It is meant to be a drop-in replacement for the Adafruit NeoPixel library with additional features. You can search for WS2812FX in the Arduino IDE Library Manager or install the latest (or development) version manually. More complex effects can be created by dividing your string of LEDs into segments (up to ten) and programming each segment independently. Use the segment() function to program each segment's mode, color, speed, and direction (normal or reverse). Note, some effects make use of more than one color (up to three) and are programmed by specifying an array of colors. ... -
7
Redux
A Predictable State Container for JavaScript apps
...Unlike Flux (from which Redux was inspired), Redux only has a single store for the object tree where the whole state of your app is stored. This store has a single root reducing function. As your app grows, instead of adding stores you split the root reducer into smaller ones that work independently on different parts of the state tree. This architecture allows for scaling well to large and complex apps, and also enables very powerful developer tools. -
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Neural Tangents
Fast and Easy Infinite Neural Networks in Python
Neural Tangents is a high-level neural network API for specifying complex, hierarchical models at both finite and infinite width, built in Python on top of JAX and XLA. It lets researchers define architectures from familiar building blocks—convolutions, pooling, residual connections, and nonlinearities—and obtain not only the finite network but also the corresponding Gaussian Process (GP) kernel of its infinite-width limit. With a single specification, you can compute NNGP and NTK kernels,... -
9
OpenAI-Java
OpenAI Api Client in Java
...For complex use cases (e.g. structured outputs, function calling), it provides schema support, JSON annotations, and schema validation. -
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10
Pure Bash Bible
A collection of pure bash alternatives to external processes
pure-bash-bible is a collection of pure Bash scripting techniques that demonstrate how to accomplish common and complex tasks using only built-in Bash features. Its goal is to reduce reliance on external tools like sed, awk, or grep, which can slow down scripts and add unnecessary dependencies. The project is organized as a reference book of function-based code snippets, each showcasing practical solutions for string manipulation, text processing, file operations, and more. ... -
11
xorm
xorm is a simple and powerful Go language ORM library
xorm is a simple and powerful Go language ORM library, through which database operations can be made very easy. This library is a customized and enhanced version based on the original xorm, which provides xorm with ibatis-like configuration files and dynamic SQL support, and supports ActiveRecord operations. This library is based on the customized and enhanced version of the original xorm. Since this customized version has third-party library dependencies (the original version of xorm does... -
12
AdaAutoDiff
C++ Templates and Ada Package for Automatic Differentiation
Operators are overloaded so that a normal looking function definition provides access to not only evaluations of itself, but to evaluations of any of its analytic derivatives. Automatic differentiation means the user does not need to define the analytic expressions for all the various partial derivatives. It also means that those complex expressions are essentially calculated at compile time, and merely evaluated at runtime. -
13
Grenade
Deep Learning in Haskell
...To perform back propagation, one can call the eponymous function which takes a network, appropriate input, and target data, and returns the back propagated gradients for the network. The shapes of the gradients are appropriate for each layer and may be trivial for layers like Relu which have no learnable parameters. -
14
PdfPageCounter
C++ code to count the number pages in a given PDF file.
This C++ library contains the 'PdfPageCount' class that performs the single task of finding the number of pages in a given PDF document. While the PdfPageCount class is very simple to use, the contained code is complex because the page count can be hidden in any number of places, quite often within compressed data.
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