Substance and Style: domain-specific languages for mathematical diagrams
Creating mathematical diagrams is essential for both developing one’s intuition and conveying it to others. However, formalizing diagrams in most general-purpose tools requires painstaking low-level manipulation of shapes and positions. We report on early work on PENROSE, a system we are building to automatically visualize mathematics from notation. PENROSE comprises two languages: Substance, a domain-specific language that mimics the declarativeness of mathematical notation, and Style, a styling language that concisely specifies the visual semantics of the notation. Our system can automatically visualize set theory expressions with user-defined styles, and it can visualize abstract definitions of functions by producing concrete examples. We plan to extend the system to more domains of mathematics.
(dsldi-penrose.pdf) | 6.57MiB |
(dsldi17-final13.pdf) | 2.4MiB |
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10:30 - 10:52 Talk | Substance and Style: domain-specific languages for mathematical diagrams DSLDI Wode NiColumbia University, Katherine Ye, Joshua SunshineCarnegie Mellon University, Jonathan AldrichCarnegie Mellon University, Keenan CraneCarnegie Mellon University File Attached | ||
10:52 - 11:15 Talk | Debugging Domain-Specific Languages Defined with Macros DSLDI File Attached | ||
11:15 - 11:37 Talk | DSL Design for Reinforcement Learning Agents DSLDI Christopher SimpkinsGeorgia Institute of Technology, Spencer RugaberGeorgia Institute of Technology, Charles Isbell, Jr.Georgia Institute of Technology File Attached | ||
11:37 - 12:00 Talk | Tangent: automatic differentiation using source code transformation in Python DSLDI File Attached |