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rtemis - Schema-Driven Machine Learning and Visualization

Machine learning and visualization package with an 'S7' backend featuring comprehensive type checking and validation, observable runs, and auditable outputs. The functional API provides one-call access to supervised and unsupervised learning through train(), cluster(), and decomp(). All configuration steps are performed using setup functions and validated. A single call to train() can handle preprocessing, decomposition, hyperparameter tuning, model stacking, and testing with nested resampling. Supports 'data.frame', 'data.table', and 'tibble' inputs and parallel execution. Plot methods for trained and resampled supervised models draw interactive figures through 'rtemis.draw'. Includes native implementations of SuperLearner, RuleFit, and Linear Additive Trees, and supports conformal prediction. The package first appeared in E.D. Gennatas (2017) <https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Last updated

data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization

8.36 score 150 stars 2 dependents 53 scripts 431 downloads

rtemis - Schema-Driven Machine Learning and Visualization

Machine learning and visualization package with an 'S7' backend featuring comprehensive type checking and validation, observable runs, and auditable outputs. The functional API provides one-call access to supervised and unsupervised learning through train(), cluster(), and decomp(). All configuration steps are performed using setup functions and validated. A single call to train() can handle preprocessing, decomposition, hyperparameter tuning, model stacking, and testing with nested resampling. Supports 'data.frame', 'data.table', and 'tibble' inputs and parallel execution. Plot methods for trained and resampled supervised models draw interactive figures through 'rtemis.draw'. Includes native implementations of SuperLearner, RuleFit, and Linear Additive Trees, and supports conformal prediction. The package first appeared in E.D. Gennatas (2017) <https://repository.upenn.edu/entities/publication/d81892ea-3087-4b71-a6f5-739c58626d64>.

Last updated

data-sciencedata-visualizationmachine-learningmachine-learning-libraryvisualization

8.36 score 150 stars 2 dependents 53 scripts 431 downloads

music - Learn and Experiment with Music Theory

An aid for learning and using music theory. You can build chords, scales, and chord progressions using 12-note equal temperament tuning (12-ET) or user-defined tuning. Includes functions to visualize notes on a piano using ASCII plots in the console and to plot waveforms using base graphics. It allows simple playback of notes and chords using the 'audio' package.

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music

5.78 score 51 stars 1.2k scripts 267 downloads

rtemis.core - Core Utilities for the 'rtemis' Ecosystem

Utilities used across packages of the 'rtemis' ecosystem. Includes the msg() messaging system and the fmt() formatting system. Provides a library of 'S7' properties, test_* functions that return logical values, check_* functions that throw informative errors, and clean_* functions that return validated and coerced values. This code began as part of the 'rtemis' package (<doi:10.32614/CRAN.package.rtemis>).

Last updated

5.51 score 2 stars 6 dependents 1 scripts 302 downloads

rtemis.draw - Schema-Driven Interactive Charts, Network Graphs, and Maps

Create interactive statistical charts, network graphs, and choropleth maps. Charts are rendered with the 'ECharts' 'JavaScript' library, networks with 'Sigma.js' and maps with 'MapLibre GL JS'. A high-level interface of plotting functions builds a complete visualization from data in a single call, while a low-level interface gives full control over every option. Both are based on the same type-checked and validated 'S7' configuration objects. Configurations can be saved to and restored from 'JSON' files, and each chart type has a published 'JSON Schema' that other interfaces can implement. Visualizations display as 'htmlwidgets' that automatically adapt to light and dark themes, work in 'R Markdown', 'Quarto' and 'shiny', and can be exported to Scalable Vector Graphics (SVG) files using 'Node.js'.

Last updated

4.24 score 3 stars 3 dependents 9 scripts

rtemis.llm - Large Language Models and Agentic AI

Unified interface for creating LLM and Agent objects, generating responses and performing batch inference based on a type-checked and validated 'S7' backend. Features reasoning, structured output, image input, memory management, and tool use. Supports 'Ollama' <https://docs.ollama.com/api>, 'OpenAI'-compatible <https://developers.openai.com/api/reference/overview>, and 'Anthropic'-compatible <https://platform.claude.com/docs/en/api/getting-started> endpoints. Runs Apple's on-device 'Foundation Models' through the 'rtemis-afm' bridge <https://github.com/rtemis-org/rtemis-afm>. Fills closed schemas and answers typed questions with decision models served by 'Ollama' and 'OpenRouter' <https://openrouter.ai>.

Last updated

4.15 score 2 stars 2 scripts 285 downloads

rtemis.a3 - Amino Acid Annotation (A3) Format

Implements the Amino Acid Annotation (A3) format using 'S7' classes. The A3 format is a structured schema for annotating amino acid sequences with site, region, post-translational modification (PTM), processing event, and variant information. Provides functions to create, read, and write A3 objects, and to import annotations from 'UniProt', 'AlphaFold', 'PDBe', 'ClinVar', and 'Ensembl'.

Last updated

3.95 score 2 stars 2 scripts 290 downloads

rtemis.server - 'rtemis' Server

Create a websocket server to run 'rtemis' functions from an 'rtemislive' client.

Last updated

2.70 score 1 stars

infoveillance - 'infoveillance' Package

Utilities to collect web-based data to track public health trends, behaviors, and disease outbreaks in real time.

Last updated

2.00 score 1 stars 2 scripts

rtemis.draw - Schema-Driven Interactive Charts, Network Graphs, and Maps

Create interactive statistical charts, network graphs and choropleth maps. Charts are rendered with the 'ECharts' 'JavaScript' library, networks with 'Sigma.js' and maps with 'MapLibre GL JS'. A high-level interface of plotting functions builds a complete visualization from data in a single call, while a low-level interface gives full control over every option. Both are based on the same type-checked and validated 'S7' configuration objects. Configurations can be saved to and restored from 'JSON' files, and each chart type has a published 'JSON Schema' that other interfaces can implement. Visualizations display as 'htmlwidgets' that automatically adapt to light and dark themes, work in 'R Markdown', 'Quarto' and 'shiny', and can be exported to Scalable Vector Graphics (SVG) files using 'Node.js'.

Last updated

1.95 score 3 dependents 9 scripts

rtemis.dplot3 - Interactive 'plotly' Graphics for the 'rtemis' Ecosystem

Interactive 'plotly', 'networkD3', 'threejs' and 'leaflet' graphics: scatter, 3D scatter, bar, box, density, heatmap, pie, calibration, confusion matrix, ROC, survival, time series, spectrogram, volcano, protein annotation, network, map and table plots, with 'rtemis' themes and palettes. These functions began as part of the 'rtemis' package (<doi:10.32614/CRAN.package.rtemis>); 'rtemis.draw' provides their successors.

Last updated

1.70 score 1 stars

rtemisalpha - Machine Learning and Visualization

Advanced Machine Learning and Visualization. Unsupervised Learning (Clustering, Decomposition), Supervised Learning (Classification, Regression), Cross-Decomposition, Bagging, Boosting, Meta-models. Static and interactive graphics.

Last updated

1.70 score