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author | Bryan Newbold <bnewbold@archive.org> | 2021-09-12 00:44:07 -0700 |
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committer | Bryan Newbold <bnewbold@archive.org> | 2021-09-12 00:44:07 -0700 |
commit | 0fbccacc129182e58fc940d41930980af23c1500 (patch) | |
tree | dac1f3fa16f2f5a3d1dbe1e6cbc89457f6874d5c | |
parent | c953b1967ba67bb012b1aa890b6741715be0f4cd (diff) | |
download | modelthought-0fbccacc129182e58fc940d41930980af23c1500.tar.gz modelthought-0fbccacc129182e58fc940d41930980af23c1500.zip |
recent notes and CAS thoughts
-rw-r--r-- | 2021/08/homes_and_funding.md | 37 | ||||
-rw-r--r-- | 2021/08/models_to_model.md | 7 | ||||
-rw-r--r-- | 2021/09/2021-09-11_reading.md | 88 | ||||
-rw-r--r-- | 2021/09/learning_cas.md | 38 |
4 files changed, 170 insertions, 0 deletions
diff --git a/2021/08/homes_and_funding.md b/2021/08/homes_and_funding.md new file mode 100644 index 0000000..c7154b3 --- /dev/null +++ b/2021/08/homes_and_funding.md @@ -0,0 +1,37 @@ + +## Academia + + +## Research Institutions + +NIST + +Simons Foundation (NYC) + + +## Large Funders + +(whoever funds Julia) + + +## Indie Support + +Mozilla Science Labs (and other fellowships/grants) + +Recurse Center + +Code for Science and Society + + +## Companies + +hash.ai + + +## Adjacent Projects + +Julia modeling project + +biomedical symbolic modeling + +modelica diff --git a/2021/08/models_to_model.md b/2021/08/models_to_model.md new file mode 100644 index 0000000..44038e0 --- /dev/null +++ b/2021/08/models_to_model.md @@ -0,0 +1,7 @@ + +ride share driver economics vs. taxi economics +=> with adjustments, etc +=> "can uber ever deiver" blog series https://www.nakedcapitalism.com/2016/11/can-uber-ever-deliver-part-one-understanding-ubers-bleak-operating-economics.html + + +COVID-19 epi models? at country level? diff --git a/2021/09/2021-09-11_reading.md b/2021/09/2021-09-11_reading.md new file mode 100644 index 0000000..5359dce --- /dev/null +++ b/2021/09/2021-09-11_reading.md @@ -0,0 +1,88 @@ + +## "Computer Algebra Systems" section of wpi.edu History of Calculus + +This is the clearest short overview of CAS implementation I have seen. It is a +bit out of date, and doesn't go very deep, but mentions what appear to be the +fundamentals: multiple representations (eg, expressions vs. polynomials), +canonical forms, and term re-writing. + +References "Computer Algebra: Systems and Algorithms for Algebraic +Computations" (1988) by Davenport several times. + +Didn't learn anything new, but good reference and resource. + + +## SciML Julia Project + +<https://sciml.ai/> + +Bunch of folks doing things around ML and modeling using Julia. Julia Computing +(the company) has a "JuliaSim" product; bunch of pharma folks using these +tools; etc. + +Related stuff: + +- https://juliasymbolics.org/ and Symbolics.jl +- https://github.com/SciML/DataDrivenDiffEq.jl +- https://discourse.julialang.org/c/domain/models/21 +- https://www.reddit.com/r/SciML/ +- https://sebastiancallh.github.io/post/neural-ode-weather-forecast/ +- https://sciml.ai/news/2021/08/16/juliacon2021/ +- https://juliacomputing.com/products/juliasim/ +- https://sciml.ai/news/2021/08/26/expansion/ +- https://sciml.ai/roadmap/ +- https://sciml.ai/showcase/ +- https://github.com/ModiaSim/Modia.jl + +## "Computer Algebra" (1988) by Davenport + +"Computer Algebra: Systems and Algorithms for Algebraic Computations" + +Copy on IA: <https://archive.org/details/computeralgebras0000dave> + +A bit old at this point, but from the table of contents seems to go reasonably +deep. I think this is basically an overview of how to implement a system like +Macsyma; not sure how Macsyma-specific it is. Maybe goes a bit deeper and more +implementation specific than the Cohn books? Eg, more specifics about +canonicalization and term sorting. + +## Cohn Book + +Continues to be pretty good. Will probably want to flip/skim through the paired +book as well. + + +## Other Notes + +### Sage Math Symbolics + +Sage used to use Maxima, but the external call overhead was too high. Ended up +switching to GiNaC, which is a C++ library CAS implementation. They actually +forked as Pynac, a bit confusingly; they want to keep numeric execution +internal to Sage/python. + +### Optimization Model Languages (eg, AMPL) + +In the world of optimization problems (eg, in business modeling), there are +langages like AMPL ("A Mathematical Programming Language") to describe models. +Not too disimilar from Modelica etc. + +The term for these seems to be "Algebraic modeling language", for use in +mathematical optimization. + +<https://en.wikipedia.org/wiki/AMPL#A_sample_model> + +### NineML Modeling Languages + +For neuroscience: <http://incf.github.io/nineml-spec/> + +### Macsyma / Maxima Stuff + +"Macsyma’s General Simplifier: Philosophy and Operation" (1979, Richard Fateman) + +Maxima can output Fortran, LaTeX, and MathML. The fortan output is very crude +though, just single expressions, and supports very little. + +### insect.sh + +Web-based scientific calculator. Syntax/grammar might be interesting to study. diff --git a/2021/09/learning_cas.md b/2021/09/learning_cas.md new file mode 100644 index 0000000..a482be5 --- /dev/null +++ b/2021/09/learning_cas.md @@ -0,0 +1,38 @@ + +Started reading "Computer Algebra and Symbolic Computation: Elementary +Algorithms" by Joel Cohen (2002). This is the somewhat more applied/language +oriented of two books in a series (the other, "Mathematical Methods", +apparently dives deeper in to some simplification and manipulation processes). + +Currently thinking that implementing a basic schema/s-expr computer algebra +system would be a good learning exersize, building knowledge and familiarity +with expression manipulation. + +Found [expreduce](https://github.com/corywalker/expreduce), a simple golang +computer algebra system. Also [mmaclone](https://github.com/jyh1/mmaclone). +[Blog post](https://corywalker.me/2018/06/03/introduction-to-computer-algebra.html) +about expreduce, and some documentation of functions which have been +implemented. Uses syntax, and I assume conventions, of Mathematica. + +Via expreduce, found the 'Rubi' integration rule corpus (and basic CAS system) +by Albert Rich (<http://www.apmaths.uwo.ca/~arich/>). Rich previously worked on +the CAS built-in to TI-83 calculators! + +----- + +Specific things learned from CASC:EA book so far: + +Internal representations of expressions often involve a stage of simplification +after parsing an expression. For example, in product expressions, can simplify +with constraint that none of the members are themselves product expressions, +and that there is only one rational number member, and it is the first member. +Division and subtraction are substituded for product-and-negative-power and +sum-and-negative-product. Presumably additional data structures can be used for +polynomials, etc. + +This initial simplification stage, as part of evaluation, reminds me a bit of +the tokenization vs. grammar parsing stages of compilation. Eg, where does +tokenization end and parsing begin. + +The 'procedure' definition blocks seem similar to Modelica: Input, Output, +Local Variables, Begin End. |