diff --git a/content/Week_2_2/PA/README.md b/content/Week_2_2/PA/README.md index 43d0874bde2c5f652589338e486e61d394077d19..7e55eab62c6136de69c932039e8ec62e762330a1 100644 --- a/content/Week_2_2/PA/README.md +++ b/content/Week_2_2/PA/README.md @@ -1,6 +1,7 @@ # PA 2.2: Love is Sparse *[CEGM1000 MUDE](http://mude.citg.tudelft.nl/): Week 2.2. Due: before Friday, November 22nd, 2024.* +_You can access this assignment with the following link: [classroom.github.com/a/yyIrSrxc](https://classroom.github.com/a/yyIrSrxc)._ This assignment will introduce you to the concept of sparse matrices in Python and how they can be useful to speed up computations and reduce file sizes. This is especially important when using the numerical schemes we are learning about (FDM, FVM, FEM) to solve problems with a lot of unknowns at each time step. To accomplish this, we will be using the `scipy.sparse` library. diff --git a/src/students/Week_2_2/README.html b/src/students/Week_2_2/README.html index fbbb5968879d663d50d8962649bcdf262631f726..6028c470b0cd33cf10da590542757f2f8b3a91ba 100644 --- a/src/students/Week_2_2/README.html +++ b/src/students/Week_2_2/README.html @@ -366,8 +366,8 @@ code { }); </script> <h1 id="pa-22-love-is-sparse">PA 2.2: Love is Sparse</h1> -<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 2.2. Due: before Friday, November 22nd, 2024.</em></p> -<p><em>You can access this assignment with the following link: <a href="https://classroom.github.com/a/yyIrSrxc">classroom.github.com/a/yyIrSrxc</a>.</em></p> +<p><em><a href="http://mude.citg.tudelft.nl/">CEGM1000 MUDE</a>: Week 2.2. Due: before Friday, November 22nd, 2024.</em> +<em>You can access this assignment with the following link: <a href="https://classroom.github.com/a/yyIrSrxc">classroom.github.com/a/yyIrSrxc</a>.</em></p> <p>This assignment will introduce you to the concept of sparse matrices in Python and how they can be useful to speed up computations and reduce file sizes. This is especially important when using the numerical schemes we are learning about (FDM, FVM, FEM) to solve problems with a lot of unknowns at each time step. To accomplish this, we will be using the <code>scipy.sparse</code> library.</p> <p>The instructions and technical content for this PA are included in the attached notebook file. Enjoy!</p> <h2 id="grading-criteria">Grading Criteria</h2>