first commit for total score calculation

application/src/app.rs

@@ -1,3 +1,4 @@
+#![feature(diagnostic_namespace)]
 use crate::error_template::{AppError, ErrorTemplate};
 use leptos::*;
 use leptos_meta::*;

application/src/main.rs

@@ -1,3 +1,4 @@
+#![feature(diagnostic_namespace)]
 #[cfg(feature = "ssr")]
 #[tokio::main]
 async fn main() {

application/src/pages/groups.rs

@@ -1,5 +1,6 @@
-use crate::components;
+use crate::components::{self, participant};
 use crate::util::surrealdb::schemas;
+use futures::stream::ForEach;
 use leptos::*;
 
 /// Renders the home page of your application.
@@ -22,6 +23,7 @@ pub fn Groups() -> impl IntoView {
 
     let (participants_lifesaver, participants_hindernis, participants_popduiken) =
         sort_by_events(participants_filtered);
+    let total_score_participants = sort_by_total_score(participants_filtered);
 
     view! {
         <h2>"Groups"</h2>
@@ -43,7 +45,7 @@ pub fn Groups() -> impl IntoView {
             </div>
         </div>
         <h3>"Algemene score"</h3>
-        <components::participants::Participants participants=participants_filtered.into() show_group=false />
+        <components::participants::Participants participants=total_score_participants.into() show_group=false />
         <div class="events-container">
             <div>
                 <h3>"Lifesaver"</h3>
@@ -61,6 +63,71 @@ pub fn Groups() -> impl IntoView {
     }
 }
 
+fn sort_by_total_score(
+    participants_filtered: Memo<Vec<schemas::ParticipantSignal>>,
+) -> Memo<Vec<schemas::ParticipantSignal>> {
+    let total_score_participants: Memo<Vec<schemas::ParticipantSignal>> = create_memo(move |_| {
+        let mut all_participants: Vec<(usize, schemas::ParticipantSignal)> = participants_filtered
+            .get()
+            .into_iter()
+            .enumerate()
+            .collect();
+
+        let mut lifesaver_best = 6_000_000;
+        let mut popduiken_best = 6_000_000;
+        let mut hindernis_best = 6_000_000;
+
+        for val in all_participants.clone().into_iter() {
+            if val.1.value.get().events == None {
+                continue;
+            }
+            let person = val.1.value.get().events.unwrap();
+            let person_lifesaver = person.lifesaver.unwrap_or(6_000_000);
+            let person_popduiken = person.popduiken.unwrap_or(6_000_000);
+            let person_hindernis = person.hindernis.unwrap_or(6_000_000);
+
+            if person_lifesaver < lifesaver_best {
+                lifesaver_best = person_lifesaver;
+            }
+            if person_popduiken < popduiken_best {
+                popduiken_best = person_popduiken;
+            }
+            if person_hindernis < hindernis_best {
+                hindernis_best = person_hindernis;
+            }
+        }
+
+        all_participants.sort_by(|(_, a), (_, b)| {
+            let part_a = match a.value.get().events {
+                Some(events) => {
+                    (((events.lifesaver.unwrap_or(6_000_000) * 100) / lifesaver_best)
+                        + ((events.hindernis.unwrap_or(6_000_000) * 100) / hindernis_best)
+                        + ((events.popduiken.unwrap_or(6_000_000) * 100) / popduiken_best))
+                        / 3
+                }
+                None => 36_000_000,
+            };
+            let part_b = match b.value.get().events {
+                Some(events) => {
+                    (((events.lifesaver.unwrap_or(6_000_000) * 100) / lifesaver_best)
+                        + ((events.hindernis.unwrap_or(6_000_000) * 100) / hindernis_best)
+                        + ((events.popduiken.unwrap_or(6_000_000) * 100) / popduiken_best))
+                        / 3
+                }
+                None => 36_000_000,
+            };
+
+            part_a.cmp(&part_b)
+        });
+
+        all_participants
+            .into_iter()
+            .map(|(_, value)| value)
+            .collect()
+    });
+    total_score_participants
+}
+
 fn sort_by_events(
     participants_filtered: Memo<Vec<schemas::ParticipantSignal>>,
 ) -> (