Add links to hosted Streamlit app in README and relevant modules for easier access

Author: Daniel Precioso

README.md

@@ -4,6 +4,8 @@ Welcome to the Applied Math Lab! This repository contains the materials for the
 
 You can see the [online version of the course materials here](https://daniprec.github.io/BAM-Applied-Math-Lab/).
 
+You can explore the hosted Streamlit app here: [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
+
 ## Repository Structure
 
 At a high level:
@@ -37,6 +39,7 @@ Brief explanation:
 - **modules/**: Guided learning modules written in Quarto (notes, explanations, exercises).
 - **references/**: External reference materials (e.g., NetworkX tutorial notebooks, datasets).
 - **streamlit/**: Streamlit app(s) used for interactive demonstrations and student exploration.
+- **Hosted Streamlit app**: [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
 - **tex/**: LaTeX assets and builds (style files, bibliography, generated PDFs/aux files).
 
 ## How to Use This Repository
@@ -93,6 +96,8 @@ quarto render modules/cellular-automata/cellular-1d.qmd
 
 ## Running Streamlit
 
+If you only want to explore the live app, use the hosted version: [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
+
 Some scripts in this repository use Streamlit, a library included in the `requirements.txt` file. When you run a script with Streamlit, you might see the following warning:
 
 ```bash

modules/pde-1d/gierer-meinhardt-1d.qmd

@@ -8,6 +8,8 @@ The Gierer-Meinhardt model is a classical activator-inhibitor system that produc
 
 In the ODE sessions, the state was a short vector and `solve_ivp()` took care of the time integration. Here the state is a **field** sampled on a grid, so we must build the update rule ourselves. The logic is still familiar: define the right-hand side, choose parameters, advance in time, and visualize the result.
 
+You can also explore the hosted Streamlit version of this app at [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
+
 The model reads
 
 $$
@@ -389,4 +391,6 @@ You now have a working 1D solver. The next question is theoretical: for which pa
 
 ::: {.callout-tip}
 Reference code is available in [amlab/pdes/gierer_meinhardt_1d.py](https://github.com/daniprec/BAM-Applied-Math-Lab/blob/main/amlab/pdes/gierer_meinhardt_1d.py).
+
+The hosted Streamlit version is available at [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
 :::

modules/pde-1d/index.qmd

@@ -26,6 +26,8 @@ We will build this session in layers.
 
 First, we start with the **Gierer-Meinhardt model in 1D**. This is the cleanest place to learn the PDE workflow: grid, Laplacian, Euler update, boundary conditions, and animation.
 
+If you want to explore the interactive version directly, open the hosted Streamlit app at [bam-applied-math-lab.streamlit.app](https://bam-applied-math-lab.streamlit.app/).
+
 [Gierer-Meinhardt 1D](gierer-meinhardt-1d.qmd){.btn .btn-primary}
 
 Then we ask the theoretical question: **when should patterns appear at all?** That is where Turing instability enters, through steady states, Jacobians, spatial modes, and the mode matrices that define Turing space.