Add additional example animations

Author: Bergam0t

_extensions/whitphx/stlite/stlite.js

@@ -4,6 +4,7 @@ window.addEventListener("load", function(event) {
     minHeight: 140,
     sizeWidth: true,
     maxWidth: 800,
+    maxHeight: 675,
     widthCalculationMethod: 'rightMostElement' // Or 'bodyOffset'
   }, ".stlite");
 });

animation_examples/background_files/sinks.drawio.png

@@ -0,0 +1,28 @@
+<mxfile host="app.diagrams.net" agent="Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:139.0) Gecko/20100101 Firefox/139.0" version="27.1.3">
+  <diagram name="Page-1" id="RVeoq7JkO4piARM7jQIV">
+    <mxGraphModel dx="1489" dy="941" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="1100" pageHeight="600" math="0" shadow="0">
+      <root>
+        <mxCell id="0" />
+        <mxCell id="1" parent="0" />
+        <mxCell id="8jv0vOWLXyXSIXB2e-R--5" value="" style="rounded=0;whiteSpace=wrap;html=1;sketch=1;curveFitting=1;jiggle=2;fillColor=#b1ddf0;strokeColor=#10739e;" vertex="1" parent="1">
+          <mxGeometry x="10" y="8" width="1080" height="272" as="geometry" />
+        </mxCell>
+        <mxCell id="8jv0vOWLXyXSIXB2e-R--3" value="" style="rounded=0;whiteSpace=wrap;html=1;sketch=1;curveFitting=1;jiggle=2;fillColor=#fad9d5;strokeColor=#ae4132;" vertex="1" parent="1">
+          <mxGeometry x="10" y="280" width="1080" height="300" as="geometry" />
+        </mxCell>
+        <mxCell id="8jv0vOWLXyXSIXB2e-R--4" value="Sinks" style="rounded=0;whiteSpace=wrap;html=1;sketch=1;curveFitting=1;jiggle=2;fontStyle=0;fontFamily=Caveat;fontSource=https%3A%2F%2Ffonts.googleapis.com%2Fcss%3Ffamily%3DCaveat;fontSize=29;" vertex="1" parent="1">
+          <mxGeometry x="350" y="280" width="370" height="60" as="geometry" />
+        </mxCell>
+        <mxCell id="8jv0vOWLXyXSIXB2e-R--2" value="Pathway" style="rounded=0;whiteSpace=wrap;html=1;sketch=1;curveFitting=1;jiggle=2;fontStyle=0;fontFamily=Caveat;fontSource=https%3A%2F%2Ffonts.googleapis.com%2Fcss%3Ffamily%3DCaveat;fontSize=29;" vertex="1" parent="1">
+          <mxGeometry x="350" y="220" width="370" height="60" as="geometry" />
+        </mxCell>
+        <mxCell id="8jv0vOWLXyXSIXB2e-R--1" value="" style="endArrow=none;html=1;rounded=0;strokeWidth=6;sketch=1;curveFitting=1;jiggle=2;" edge="1" parent="1">
+          <mxGeometry width="50" height="50" relative="1" as="geometry">
+            <mxPoint x="40" y="280" as="sourcePoint" />
+            <mxPoint x="1070" y="280" as="targetPoint" />
+          </mxGeometry>
+        </mxCell>
+      </root>
+    </mxGraphModel>
+  </diagram>
+</mxfile>

animation_examples/background_files/source/sinks.drawio

@@ -0,0 +1,82 @@
+from vidigi.logging import EventLogger
+from vidigi.utils import EventPosition, create_event_position_df
+from vidigi.animation import animate_activity_log
+import simpy
+import numpy as np
+
+class Patient:
+    def __init__(self, p_id):
+        self.id = p_id
+
+class SimpleActivityModelThreeSequentialActivities:
+    def __init__(self, master_seed=42):
+        self.env = simpy.Environment()
+        self.patient_counter = 0
+        self.patient_inter = 4
+        self.logger = EventLogger(env=self.env)
+
+        # Seed setup using numpy's SeedSequence
+        self.master_seed = master_seed
+        self.seed_seq = np.random.SeedSequence(master_seed)
+        self.rng = np.random.default_rng(self.seed_seq)
+
+    def generate_arrivals(self):
+        while True:
+            self.patient_counter += 1
+
+            p = Patient(self.patient_counter)
+
+            self.logger.log_arrival(entity_id=p.id)
+            self.env.process(self.patient_journey(p))
+            sampled_inter = self.rng.exponential(scale=self.patient_inter)
+            yield self.env.timeout(sampled_inter)
+
+    def patient_journey(self, patient):
+
+      self.logger.log_queue(entity_id=patient.id, event="wait_here_receptionist")
+
+      yield self.env.timeout(abs(self.rng.normal(loc=3, scale=1)))
+
+      self.logger.log_queue(entity_id=patient.id, event="wait_here_blood_test")
+
+      yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+
+      self.logger.log_queue(entity_id=patient.id, event="wait_here_doctor_consult")
+
+      yield self.env.timeout(abs(self.rng.normal(loc=8, scale=2)))
+
+      self.logger.log_departure(entity_id=patient.id)
+
+    def run(self):
+        self.env.process(self.generate_arrivals())
+        self.env.run(until=180)
+
+model = SimpleActivityModelThreeSequentialActivities()
+model.run()
+event_log = model.logger.to_dataframe()
+# event_log.to_csv("test_log.csv")
+
+animate_activity_log(
+  event_log = event_log,
+  event_position_df = create_event_position_df([
+    EventPosition(event="wait_here_receptionist", x=50 , y=25 , label="Registering<br>with receptionist"),
+    EventPosition(event="wait_here_blood_test", x=125 , y=125 , label="Having a<br>blood test"),
+    EventPosition(event="wait_here_doctor_consult", x=200 , y=225 , label="Seeing<br>a doctor"),
+    EventPosition(event="depart", x=400, y=125, label="Exit")
+    ]),
+  every_x_time_units=1,
+  limit_duration=60,
+  override_x_max=300,
+  override_y_max=275,
+  plotly_height=600,
+  plotly_width=1100,
+  display_stage_labels=True,
+  # time_display_units="%M minutes",
+  gap_between_entities=15,
+  wrap_queues_at=5,
+  entity_icon_size=30,
+  simulation_time_unit="minutes",
+  debug_write_intermediate_objects=True
+).update_layout(
+        plot_bgcolor='white',
+    )

animation_examples/entity_sequential_paths.py

@@ -0,0 +1,119 @@
+from vidigi.logging import EventLogger
+from vidigi.utils import EventPosition, create_event_position_df
+from vidigi.animation import animate_activity_log
+import simpy
+import numpy as np
+
+class Patient:
+    def __init__(self, p_id):
+        self.id = p_id
+
+class SimpleActivityModelSequentialActivitiesSinks:
+    def __init__(self, master_seed=42):
+        self.env = simpy.Environment()
+        self.patient_counter = 0
+        self.patient_inter = 4
+        self.logger = EventLogger(env=self.env)
+
+        # Seed setup using numpy's SeedSequence
+        self.master_seed = master_seed
+        self.seed_seq = np.random.SeedSequence(master_seed)
+        self.rng = np.random.default_rng(self.seed_seq)
+
+    def generate_arrivals(self):
+        while True:
+            self.patient_counter += 1
+
+            p = Patient(self.patient_counter)
+
+            self.logger.log_arrival(entity_id=p.id)
+            self.env.process(self.patient_journey(p))
+            sampled_inter = self.rng.exponential(scale=self.patient_inter)
+            yield self.env.timeout(sampled_inter)
+
+    def patient_journey(self, patient):
+
+      self.logger.log_queue(entity_id=patient.id, event="wait_here_triage")
+
+      yield self.env.timeout(abs(self.rng.normal(loc=3, scale=1)))
+
+      if self.rng.uniform(low=0.0, high=1.0) < 0.2:
+          self.logger.log_queue(entity_id=patient.id, event="died")
+          yield self.env.timeout(2)
+          self.logger.log_departure(entity_id=patient.id)
+
+      else:
+        self.logger.log_queue(entity_id=patient.id, event="wait_here_stabilisation")
+        yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+
+        if self.rng.uniform(low=0.0, high=1.0) < 0.1:
+          self.logger.log_queue(entity_id=patient.id, event="died")
+          yield self.env.timeout(2)
+          self.logger.log_departure(entity_id=patient.id)
+        elif self.rng.uniform(low=0.0, high=1.0) < 0.2:
+            self.logger.log_queue(entity_id=patient.id, event="transferred")
+            yield self.env.timeout(2)
+            self.logger.log_departure(entity_id=patient.id)
+        elif self.rng.uniform(low=0.0, high=1.0) < 0.5:
+            self.logger.log_queue(entity_id=patient.id, event="ward")
+            yield self.env.timeout(2)
+            self.logger.log_departure(entity_id=patient.id)
+        else:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_treatment")
+          yield self.env.timeout(abs(self.rng.normal(loc=8, scale=2)))
+
+          if self.rng.uniform(low=0.0, high=1.0) < 0.2:
+              self.logger.log_queue(entity_id=patient.id, event="transferred")
+              yield self.env.timeout(2)
+              self.logger.log_departure(entity_id=patient.id)
+          elif self.rng.uniform(low=0.0, high=1.0) < 0.7:
+              self.logger.log_queue(entity_id=patient.id, event="ward")
+              yield self.env.timeout(2)
+              self.logger.log_departure(entity_id=patient.id)
+          else:
+              self.logger.log_queue(entity_id=patient.id, event="home")
+              yield self.env.timeout(2)
+              self.logger.log_departure(entity_id=patient.id)
+
+    def run(self):
+        self.env.process(self.generate_arrivals())
+        self.env.run(until=180)
+
+model = SimpleActivityModelSequentialActivitiesSinks()
+model.run()
+event_log = model.logger.to_dataframe()
+# event_log.to_csv("test_log.csv")
+
+animate_activity_log(
+  event_log = event_log,
+  event_position_df = create_event_position_df([
+    EventPosition(event="wait_here_triage", x=50 , y=225 , label="Arrived<br>in ED"),
+    EventPosition(event="wait_here_stabilisation", x=150 , y=225 , label="Being<br>Stabilised"),
+    EventPosition(event="wait_here_treatment", x=250 , y=225 , label="Being<br>Treated"),
+
+
+    EventPosition(event="died", x=40 , y=50 , label="Died"),
+    EventPosition(event="transferred", x=100 , y=50 , label="Transferred<br>to other<br>Hospital"),
+    EventPosition(event="ward", x=160 , y=50 , label="Admitted<br>to Ward"),
+    EventPosition(event="home", x=220 , y=50 , label="Discharged<br>home"),
+
+
+    EventPosition(event="depart", x=150, y=-30, label="Exit")
+    ]),
+  every_x_time_units=1,
+  limit_duration=60,
+  override_x_max=300,
+  override_y_max=275,
+  plotly_height=600,
+  plotly_width=1100,
+  display_stage_labels=True,
+  # time_display_units="%M minutes",
+  gap_between_entities=15,
+  wrap_queues_at=5,
+  entity_icon_size=30,
+  simulation_time_unit="minutes",
+  debug_write_intermediate_objects=True,
+  add_background_image="animation_examples/background_files/sinks.drawio.png"
+).update_layout(
+        plot_bgcolor='white',
+    )

animation_examples/entity_sequential_paths_sinks.py

@@ -0,0 +1,130 @@
+from vidigi.logging import EventLogger
+from vidigi.utils import EventPosition, create_event_position_df
+from vidigi.animation import animate_activity_log
+import simpy
+import numpy as np
+
+class Patient:
+    def __init__(self, p_id):
+        self.id = p_id
+
+class SimpleActivityModelThreeSequentialActivities:
+    def __init__(self, master_seed=42):
+        self.env = simpy.Environment()
+        self.patient_counter = 0
+        self.patient_inter = 3
+        self.logger = EventLogger(env=self.env)
+
+        # Seed setup using numpy's SeedSequence
+        self.master_seed = master_seed
+        self.seed_seq = np.random.SeedSequence(master_seed)
+        self.rng = np.random.default_rng(self.seed_seq)
+
+    def generate_arrivals(self):
+        while True:
+            self.patient_counter += 1
+
+            p = Patient(self.patient_counter)
+
+            self.logger.log_arrival(entity_id=p.id)
+
+            if self.rng.uniform(low=0.0, high=1.0) < 0.4:
+                self.env.process(self.patient_journey_1(p))
+            else:
+               self.env.process(self.patient_journey_2(p))
+            sampled_inter = self.rng.exponential(scale=self.patient_inter)
+            yield self.env.timeout(sampled_inter)
+
+    def patient_journey_1(self, patient):
+
+      if self.rng.uniform(low=0.0, high=1.0) < 0.4:
+        self.logger.log_queue(entity_id=patient.id, event="wait_here_receptionist")
+        yield self.env.timeout(abs(self.rng.normal(loc=3, scale=1)))
+      else:
+        self.logger.log_queue(entity_id=patient.id, event="wait_here_self_register")
+        yield self.env.timeout(abs(self.rng.normal(loc=2, scale=1)))
+
+      # 50% of patients in this pathway have a blood test before their appointment
+      if self.rng.uniform(low=0.0, high=1.0) < 0.5:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_blood_test")
+          yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+
+      self.logger.log_queue(entity_id=patient.id, event="wait_here_doctor_consult")
+
+      yield self.env.timeout(abs(self.rng.normal(loc=8, scale=2)))
+
+      self.logger.log_departure(entity_id=patient.id)
+
+    def patient_journey_2(self, patient):
+      if self.rng.uniform(low=0.0, high=1.0) < 0.7:
+        self.logger.log_queue(entity_id=patient.id, event="wait_here_app")
+        yield self.env.timeout(abs(self.rng.normal(loc=3, scale=1)))
+      else:
+        self.logger.log_queue(entity_id=patient.id, event="wait_here_self_register")
+        yield self.env.timeout(abs(self.rng.normal(loc=3, scale=1)))
+
+      # 20% of patients in this pathway have a blood test before their appointment
+      if self.rng.uniform(low=0.0, high=1.0) < 0.2:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_blood_test")
+          yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+      # Another 60% have a health check with a nurse
+      elif self.rng.uniform(low=0.0, high=1.0) < 0.8:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_health_check")
+          yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+          # And some proportion of those also then have a blood test
+          if self.rng.uniform(low=0.0, high=1.0) < 0.7:
+              self.logger.log_queue(entity_id=patient.id, event="wait_here_blood_test")
+              yield self.env.timeout(abs(self.rng.normal(loc=14, scale=3)))
+      # And the remaining 20% go straight to the doctor
+      if self.rng.uniform(low=0.0, high=1.0) < 0.7:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_doctor_consult")
+          yield self.env.timeout(abs(self.rng.normal(loc=8, scale=2)))
+
+      # some then return to the receptionist to book another appointment
+      if self.rng.uniform(low=0.0, high=1.0) < 0.4:
+          self.logger.log_queue(entity_id=patient.id, event="wait_here_receptionist")
+          yield self.env.timeout(abs(self.rng.normal(loc=8, scale=2)))
+
+    def run(self):
+        self.env.process(self.generate_arrivals())
+        self.env.run(until=180)
+
+
+model = SimpleActivityModelThreeSequentialActivities()
+model.run()
+event_log = model.logger.to_dataframe()
+# event_log.to_csv("test_log.csv")
+
+animate_activity_log(
+  event_log = event_log,
+  event_position_df = create_event_position_df([
+
+    EventPosition(event="wait_here_receptionist", x=75 , y=25 , label="Speaking<br>with receptionist"),
+    EventPosition(event="wait_here_self_register", x=75 , y=125 , label="Registering<br>via machine"),
+    EventPosition(event="wait_here_app", x=75 , y=225 , label="Checked in<br>via app"),
+
+
+    EventPosition(event="wait_here_blood_test", x=175 , y=125 , label="Having a<br>blood test"),
+    EventPosition(event="wait_here_health_check", x=175 , y=225 , label="Having a<br>health check"),
+
+    EventPosition(event="wait_here_doctor_consult", x=275 , y=225 , label="Seeing<br>a<br>doctor"),
+
+    EventPosition(event="depart", x=400, y=125, label="Exit")
+    ]),
+  every_x_time_units=1,
+  limit_duration=60,
+  override_x_max=300,
+  override_y_max=325,
+  plotly_height=600,
+  plotly_width=1100,
+  display_stage_labels=True,
+  # time_display_units="%M minutes",
+  gap_between_entities=10,
+  wrap_queues_at=5,
+  entity_icon_size=20,
+  text_size=15,
+  simulation_time_unit="minutes",
+  debug_write_intermediate_objects=True
+).update_layout(
+        plot_bgcolor='white',
+    )