Gridap Talks

In this repos you can find some material we have recently develop for presenting the Gridap library.

[July 30th, 2020] You can find here the presentation of Gridap in JuliaCon2020.
[April 21st, 2020] You can also find the slides of UNSW Online Computational Mathematics Seminar, Melbourne-Sydney, April 21st 2020 here, together with the video recording of the online seminar that you can download from here.
[February 14th, 2020] You can find the slides of the Monash Workshop on Numerical Differential Equations with Applications, Melbourne, February 14th 2020, here.

Jupyter Notebooks

[April 21st, 2020] You can also find a jupyter notebook in which we have created a very simple example of a lazy ummutable matrix implementation in Julia, which we consider provides a nice overview of the Julia capabilities, its multiple dispatching paradigm, the importance of interfaces and group by actions, not attributes. we think it can be useful for people that come from object-oriented backgrounds. This example also provides some insight about how we have been able to implement our numerical PDE solvers in Gridap, as @santiagobadia explains in the video.

To install the jupyter notebooks, do the following

$ git clone https://github.com/gridap/Tutorials.git

Move into the folder and open a Julia REPL setting the current folder as the project environment

$ cd Gridap-presentation/lazy-matrix-notebook/
$ julia

In the Julia REPL

julia>

type ] to enter in pkg mode, activate the project

(@v1.4) pkg> activate .

and instantiate the environment

(lazy-matrix-notebook) pkg> instantiate

Open the notebook using these commands

julia> using IJulia
julia> notebook(dir=pwd())

Enjoy!