Search Results for "math function graph" - Page 7

Function graph drawing/rendering application for use with audio applications. Exports .wav files. Dependencies: wxPython & Numeric(not in 1.10)

iS-DOS Math is a set of mathematical programs for ZX-Spectrum home computer running iS-DOS operating system. Includes calculator, graph plotter and symbolic formula processor for engineering calculations.

ctCalc engine: VB6 function that calculates a math term (string) and returns the result (string); ctCalc GUI: 1. Simple text-calculator 2. Graphs 3. Custom scripts

Disparate set of java utility functions used in numerous Aepryus projects. Includes a math package with vector objects and function parsers. A utility package contains loggers, a handy profiler and assorted helper methods for String and Date classes.

Not yet playable. jadab is a Dots and Boxes playing program. It uses modern algorithms and graph theory to play the twin game, Strings and Coins. It is being done as a research project in math, game theory, and computer science at Dalhousie University

A VB class which provides mathematic functionality on Hex or Decimal numbers of any length (yes, it'll add 2 numbers of 1 million digits - but it might take a while)

An efficient 2D Simple Graphing program for windows, perfect for plotting collected data incorporating features of cricket graph which allow you to apply a function to all your data. Regression Lines for data.

Vofce is a simple GUI driven graph plotting tool mainly for math students.

Draw & analysis math function graph in a free way!

This tool converts the output of gprof to a format processible by the DOT tool, to generate a nice graphical function call graph.

Functrace is a tracing facility, similar to ltrace/strace, that can be used for tracing the dynamic call graph internal to a running program (i.e. a trace of function calls).

Interval chart plots horizontal intervals on a graph. Edit chart's values. File I/O. Output to printer.png. Adjust scale. No hashmap function. Uses Java ScreenResSelector. Sometimes called Tornado Plot. Font hard coded.

...It pairs a 3.4B-parameter language model with a 0.4B-parameter vision encoder, enabling it to understand both text and image inputs. This reasoning-tuned variant is optimized for tasks like math, coding, and other STEM-related problem solving, making it suitable for applications that require logical reasoning, analysis, or structured thinking. Despite its modest size, the model is designed for edge deployment and can run locally, fitting in ~16 GB of VRAM in BF16 or under 8 GB of RAM/VRAM when quantized. It supports dozens of languages, allowing it to function across global and multilingual contexts. ...

...It combines an 8.4B-parameter language model with a 0.4B vision encoder, enabling it to process both text and images for advanced reasoning tasks. This version is specifically post-trained for reasoning, making it well-suited for math, coding, and STEM applications requiring multi-step logic and problem-solving. Despite its reasoning-focused training, the model remains edge-optimized and can run locally on a single 24GB GPU in BF16, or under 12GB when quantized. It supports dozens of languages, adheres reliably to system prompts, and provides native function calling and structured JSON output—key capabilities for agentic and automation workflows. ...

...It pairs a 13.5B-parameter language model with a 0.4B vision encoder, enabling strong multimodal reasoning across both text and images. This version is specifically post-trained for reasoning tasks, making it highly effective for math, coding, STEM workloads, and complex multi-step problem-solving. Despite its scale, the model is engineered for practical deployment and can run locally on 32GB of VRAM in BF16 or under 24GB when quantized. It maintains robust system-prompt adherence, supports dozens of languages, and provides native function calling with clean JSON output for agentic workflows. ...

...It introduces a hybrid reasoning mode with explicit <think> segments, enabling the model to deliberate deeply when needed and switch to faster responses when desired. Post-training improvements include a vastly expanded corpus with ~60B tokens, boosting performance across math, code, STEM, logic, creativity, and structured outputs. The model is designed for schema adherence, producing valid JSON and repairing malformed outputs, making it highly suitable for tool use and function calling. Hermes 4 is engineered for superior steerability with reduced refusal rates, aligning responses to user values while preserving assistant quality. ...

This utility is to construct the interactive function call graph.