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Welcome! cachai (Custom Axes and CHarts Advanced Interface) is a fully customizable Python
visualization toolkit designed to deliver polished, publication-ready plots built on top of
Matplotlib. Currently, the package includes the ChordDiagram module as its primary feature.
For details on the toolkit’s capabilities, motivations and future projections, refer to
this paper .
To contribute or report bugs, please visit the issues page.
Fun fact
“Cachai” (/kɑːˈtʃaɪ/) is a slang word from Chilean informal speech, similar to saying “ya know?” or “get it?” in English. Don’t know how to pronounce it? Think of “kah-CHAI” (like “cut” + “chai” tea, with stress on “CHAI”).
About cachai
From “CACHAI’s first module: a fully customizable chord diagram for astronomy and beyond”” (Beltrán, D. & Dantas, M. L. L., 2025):
Effective data visualization turns complex relationships into intuitive insights, accelerating scientific progress across disciplines (e.g. C. Wilke 2019). In astronomy, where high-dimensional data are common, the choice of visualization tools directly affects both interpretation and communication. Chord diagrams are particularly valuable for illustrating weighted, non-directional connections — such as (anti-)correlations — between variables (M. Krzywinski et al. 2009), but existing implementations often lack the flexibility.
In Python, support for chord diagrams is limited. Plotly offers interactive diagrams but minimal stylistic control (Plotly Technologies Inc. 2015), while Matplotlib lacks native support (J. D. Hunter 2007). In contrast, R packages like Circlize (Z. Gu et al. 2014) and astronomy-focused tools like Amada (R. S. de Souza & B. Ciardi 2015) provide more options, but often omit key features such as link styling, node gradients, or precise label control.
The ChordDiagram module in cachai addresses this gap, combining immediate usability with
room for future expansion. It is shaped by both astronomical and general visualization needs and
principles (e.g. N. P. Rougier et al. 2014, and references therein), bridging exploratory
analysis and polished presentation.
Future modules will expand its capabilities beyond chord diagrams. A more complete description is expected to follow in a forthcoming publication.