Merge pull request #21 from hsma-programme/post_open_day_fixes

Post open day fixes

Introduction.py

@@ -22,7 +22,7 @@
 """
 This is a discrete event simulation playground based on the Monks et al (2022), which is itself an implementation of the Treatment Centre Model from Nelson (2013).
 
-By working through the pages on the left in order, you will 
+By working through the pages on the left in order, you will
 - see how a discrete event simulation builds from simple beginnings up to the point of being able to model a complex system
 - understand the impact of variability and randomness on systems
 - have a go at changing parameters to find the best configuration that balances the average use of resources (like treatment bays or nurses) and the average time a patient will wait at each step of the process.
@@ -38,20 +38,20 @@
     %%{ init: {  'theme': 'base', 'themeVariables': {'lineColor': '#b4b4b4'} } }%%
     flowchart LR
         A[Arrival] --> B{Trauma or non-trauma}
-        B --> B1{Trauma Pathway} 
+        B --> B1{Trauma Pathway}
         B --> B2{Non-Trauma Pathway}
-        
+
         B1 --> C[Stabilisation]
         C --> E[Treatment]
-      
+
         B2 --> D[Registration]
         D --> G[Examination]
 
         G --> H[Treat?]
-        H ----> F 
+        H ----> F
 
         H --> I[Non-Trauma Treatment]
-        I --> F 
+        I --> F
 
         C -.-> Z([Trauma Room\n<b>RESOURCE</b>])
         Z -.-> C
@@ -90,8 +90,8 @@ class I,V ZZ4;
 """
 ## References
 
-1. *Monks.T, Harper.A, Anagnoustou. A, Allen.M, Taylor.S. (2022) Open Science for Computer Simulation*
-2. *Nelson. B.L. (2013). [Foundations and methods of stochastic simulation](https://www.amazon.co.uk/Foundations-Methods-Stochastic-Simulation-International/dp/1461461596/ref=sr_1_1?dchild=1&keywords=foundations+and+methods+of+stochastic+simulation&qid=1617050801&sr=8-1). Springer.* 
+1. *Monks.T, Harper.A, Anagnoustou. A, Allen.M, Taylor.S. (2022) Open Science for Computer Simulation*; [Repository Link](https://github.com/TomMonks/treatment-centre-sim/tree/main)
+2. *Nelson. B.L. (2013). [Foundations and methods of stochastic simulation](https://www.amazon.co.uk/Foundations-Methods-Stochastic-Simulation-International/dp/1461461596/ref=sr_1_1?dchild=1&keywords=foundations+and+methods+of+stochastic+simulation&qid=1617050801&sr=8-1). Springer.*
 3. https://health-data-science-or.github.io/simpy-streamlit-tutorial/
 """
-)
+)

index.html

@@ -47,7 +47,7 @@
 """
 This is a discrete event simulation playground based on the Monks et al (2022), which is itself an implementation of the Treatment Centre Model from Nelson (2013).
 
-By working through the pages on the left in order, you will 
+By working through the pages on the left in order, you will
 - see how a discrete event simulation builds from simple beginnings up to the point of being able to model a complex system
 - understand the impact of variability and randomness on systems
 - have a go at changing parameters to find the best configuration that balances the average use of resources (like treatment bays or nurses) and the average time a patient will wait at each step of the process.
@@ -62,20 +62,20 @@
     %%{ init: {  'theme': 'base', 'themeVariables': {'lineColor': '#b4b4b4'} } }%%
     flowchart LR
         A[Arrival] --> B{Trauma or non-trauma}
-        B --> B1{Trauma Pathway} 
+        B --> B1{Trauma Pathway}
         B --> B2{Non-Trauma Pathway}
-        
+
         B1 --> C[Stabilisation]
         C --> E[Treatment]
-      
+
         B2 --> D[Registration]
         D --> G[Examination]
 
         G --> H[Treat?]
-        H ----> F 
+        H ----> F
 
         H --> I[Non-Trauma Treatment]
-        I --> F 
+        I --> F
 
         C -.-> Z([Trauma Room\n<b>RESOURCE</b>])
         Z -.-> C
@@ -114,10 +114,10 @@
 """
 ## References
 
-1. *Monks.T, Harper.A, Anagnoustou. A, Allen.M, Taylor.S. (2022) Open Science for Computer Simulation*
-2. *Nelson. B.L. (2013). [Foundations and methods of stochastic simulation](https://www.amazon.co.uk/Foundations-Methods-Stochastic-Simulation-International/dp/1461461596/ref=sr_1_1?dchild=1&keywords=foundations+and+methods+of+stochastic+simulation&qid=1617050801&sr=8-1). Springer.* 
+1. *Monks.T, Harper.A, Anagnoustou. A, Allen.M, Taylor.S. (2022) Open Science for Computer Simulation*; [Repository Link](https://github.com/TomMonks/treatment-centre-sim/tree/main)
+2. *Nelson. B.L. (2013). [Foundations and methods of stochastic simulation](https://www.amazon.co.uk/Foundations-Methods-Stochastic-Simulation-International/dp/1461461596/ref=sr_1_1?dchild=1&keywords=foundations+and+methods+of+stochastic+simulation&qid=1617050801&sr=8-1). Springer.*
 3. https://health-data-science-or.github.io/simpy-streamlit-tutorial/
-"""    
+"""
 )
 
 
@@ -144,15 +144,15 @@
 "helper_functions.py": {
         url: "https://raw.githubusercontent.com/hsma-programme/Teaching_DES_Concepts_Streamlit/main/helper_functions.py"
       },
-      
+
 "distribution_classes.py": {
         url: "https://raw.githubusercontent.com/hsma-programme/Teaching_DES_Concepts_Streamlit/main/distribution_classes.py"
       },
-      
+
 "model_classes.py": {
         url: "https://raw.githubusercontent.com/hsma-programme/Teaching_DES_Concepts_Streamlit/main/model_classes.py"
       },
- 
+
 "style.css": {
         url: "https://raw.githubusercontent.com/hsma-programme/Teaching_DES_Concepts_Streamlit/main/style.css"
       },
@@ -176,11 +176,11 @@
 "home/.streamlit/secrets.toml": {
         url: "https://raw.githubusercontent.com/hsma-programme/Teaching_DES_Concepts_Streamlit/main/.streamlit/secrets.toml"
       }
-  
+
     },
   },
   document.getElementById("root")
 );
     </script>
   </body>
-</html>
+</html>