Numerical Methods for Life123 #19
BrainAnnex
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A promising 2020 book that has come to my attention is "A Gentle Introduction To Numerical Simulations With Python", by S. Linge, H. P. Langtangen, 2nd edn |
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UPDATE: this thread will be about GENERAL numerical methods; a separate thread will focus on "finite element methods" for solving the diffusion equation.
A definite source of complexity for Life123 are the complex boundary conditions. From early on - probably starting in a couple of Beta releases from now - an integral part of Life123 will be membranes and sub-cellular compartments... as well as the varying dimensions of the simulated cells.
Life123 will strive for a dual approach of helping non-experts feel more at ease, as well as trying to recruit contributors with deep expertise in the field.
The Diffusion page on the site has expanded a lot over time, and will take on an increasingly prominent role.
I've been reviewing the literature on numerical methods and PDEs (Partial Differential Equations): for the latter, see the separate thread
One 2022 ebook that I like is "Practical Numerical Computing Using Python", by Mahendra Verma (on Amazon)
![Capture](https://user-images.githubusercontent.com/41893046/179426431-97c00500-6685-43cf-8795-802ea9778245.PNG)
It's pretty general, and covers tons of topics. It also lightly covers "Solving PDEs using Finite Difference Method" (chapter 16)
It pointed me to the Numpy Gradient method - which I wasn't aware of - to compute some of numerical differences that are used in Finite Difference Methods
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