update

Author: MartinPdeS

README.rst

@@ -60,15 +60,19 @@ Simulate a simple flow cytometer experiment:
 
 ..  code-block:: python
 
+    # %%
+    # Step 0: Global Settings and Imports
+    # -----------------------------------
+    import numpy as np
     from TypedUnit import ureg
-    import os
-    dir_path = os.path.dirname(os.path.realpath(__file__))
 
     # %%
     # Step 1: Define Flow Cell and Fluidics
     # -------------------------------------
-    from FlowCyPy.flow_cell import FlowCell
-    from FlowCyPy.fluidics import Fluidics, ScattererCollection, distribution, population
+    from FlowCyPy.fluidics import FlowCell
+    from FlowCyPy.fluidics import Fluidics, ScattererCollection, population
+    from FlowCyPy.sampling_method import GammaModel, ExplicitModel
+    from FlowCyPy.fluidics import distributions
 
     flow_cell = FlowCell(
         sample_volume_flow=80 * ureg.microliter / ureg.minute,
@@ -77,25 +81,54 @@ Simulate a simple flow cytometer experiment:
         height=100 * ureg.micrometer,
     )
 
-    scatterer_collection = ScattererCollection(medium_refractive_index=1.33 * ureg.RIU)
+    scatterer_collection = ScattererCollection()
+
+    medium_refractive_index = distributions.Delta(1.33 * ureg.RIU)
+
+    diameter_dist = distributions.RosinRammler(
+        shape=150 * ureg.nanometer,
+        scale=50 * ureg.nanometer,
+        low_cutoff=50.0 * ureg.nanometer,
+    )
+
+    ri_dist = distributions.Normal(
+        mean=1.44 * ureg.RIU,
+        standard_deviation=0.002 * ureg.RIU,
+        low_cutoff=1.33 * ureg.RIU,
+    )
 
     population_0 = population.Sphere(
         name="Pop 0",
-        particle_count=5e9 * ureg.particle / ureg.milliliter,
-        diameter=distribution.RosinRammler(150 * ureg.nanometer, spread=30),
-        refractive_index=distribution.Normal(1.44 * ureg.RIU, std_dev=0.002 * ureg.RIU),
+        medium_refractive_index=medium_refractive_index,
+        concentration=5e10 * ureg.particle / ureg.milliliter,
+        diameter=diameter_dist,
+        refractive_index=ri_dist,
+    )
+
+
+    diameter_dist = distributions.RosinRammler(
+        shape=50 * ureg.nanometer,
+        scale=50 * ureg.nanometer,
+    )
+
+    ri_dist = distributions.Normal(
+        mean=1.44 * ureg.RIU,
+        standard_deviation=0.002 * ureg.RIU,
+        low_cutoff=1.33 * ureg.RIU,
     )
 
     population_1 = population.Sphere(
         name="Pop 1",
-        particle_count=5e9 * ureg.particle / ureg.milliliter,
-        diameter=distribution.RosinRammler(200 * ureg.nanometer, spread=30),
-        refractive_index=distribution.Normal(1.44 * ureg.RIU, std_dev=0.002 * ureg.RIU),
+        medium_refractive_index=medium_refractive_index,
+        concentration=5e17 * ureg.particle / ureg.milliliter,
+        diameter=diameter_dist,
+        refractive_index=ri_dist,
+        sampling_method=GammaModel(mc_samples=10_000),
     )
 
-    scatterer_collection.add_population(population_0, population_1)
+    scatterer_collection.add_population(population_0)
 
-    scatterer_collection.dilute(factor=30)
+    scatterer_collection.dilute(factor=280)
 
     fluidics = Fluidics(scatterer_collection=scatterer_collection, flow_cell=flow_cell)
 
@@ -111,21 +144,21 @@ Simulate a simple flow cytometer experiment:
 
     source = source.GaussianBeam(
         numerical_aperture=0.1 * ureg.AU,
-        wavelength=450 * ureg.nanometer,
+        wavelength=405 * ureg.nanometer,
         optical_power=200 * ureg.milliwatt,
-        RIN=-140,
+        RIN=-180,
     )
 
     detectors = [
         Detector(
-            name="forward",
-            phi_angle=0 * ureg.degree,
+            name="side",
+            phi_angle=90 * ureg.degree,
             numerical_aperture=0.3 * ureg.AU,
             responsivity=1 * ureg.ampere / ureg.watt,
         ),
         Detector(
-            name="side",
-            phi_angle=90 * ureg.degree,
+            name="forward",
+            phi_angle=0 * ureg.degree,
             numerical_aperture=0.3 * ureg.AU,
             responsivity=1 * ureg.ampere / ureg.watt,
         ),
@@ -165,7 +198,7 @@ Simulate a simple flow cytometer experiment:
 
     triggering = triggering_system.DynamicWindow(
         trigger_detector_name="forward",
-        threshold=10 * ureg.microvolt,
+        threshold="4sigma",
         pre_buffer=20,
         post_buffer=20,
         max_triggers=-1,
@@ -192,18 +225,50 @@ Simulate a simple flow cytometer experiment:
         background_power=0.001 * ureg.milliwatt,
     )
 
-    run_record = cytometer.run(run_time=1.5 * ureg.millisecond)
+    run_record = cytometer.run(run_time=3 * ureg.millisecond)
+
+    _ = run_record.event_collection.plot(x="Diameter")
 
     # %%
     # Step 5: Plot Events and Raw Analog Signals
     # ------------------------------------------
-    _ = run_record.events.plot(
-        x="Diameter",
-        y="RefractiveIndex",
-        show=False,
-        save_as=f"{dir_path}/../images/readme_events.png",
+    _ = run_record.event_collection.plot(x="forward")
+
+
+    # %%
+    # Plot raw analog signals
+    # -----------------------
+    _ = run_record.plot_analog(figure_size=(12, 8))
+
+
+    # %%
+    # Step 6: Plot Triggered Analog Segments
+    # --------------------------------------
+    _ = run_record.plot_digital(figure_size=(12, 8))
+
+
+    # %%
+    # Step 7: Plot Peak Features
+    # --------------------------
+    _ = run_record.peaks.plot(x=("forward", "Height"))
+
+
+    # %%
+    # Step 8: Classify Events from Peak Features
+    # ------------------------------------------
+    from FlowCyPy.classifier import KmeansClassifier
+
+    classifier = KmeansClassifier(number_of_clusters=2)
+
+    classified = classifier.run(
+        dataframe=run_record.peaks.unstack("Detector"),
+        features=["Height"],
+        detectors=["side", "forward"],
     )
 
+    _ = classified.plot(x=("side", "Height"), y=("forward", "Height"))
+
+
 |readme_events|
 
 

docs/examples/tutorials/workflow.py

@@ -32,10 +32,6 @@
 SimulationSettings.assume_perfect_hydrodynamic_focusing = True
 SimulationSettings.population_cutoff_bypass = False
 
-np.random.seed(3)
-
-from TypedUnit import RefractiveIndex
-
 # %%
 # Step 1: Define Flow Cell and Fluidics
 # -------------------------------------