K Estimator Validation — Fixed Illumination, Variable Bead Size

This example demonstrates how to estimate the K parameter, which characterizes how the absolute signal noise (Robust STD) scales with the square root of the median signal when varying bead size under fixed illumination power.

Setup and configuration

import numpy as np
from FlowCyPy.fluidics import Fluidics, FlowCell, ScattererCollection
from FlowCyPy.opto_electronics import OptoElectronics, source, TransimpedanceAmplifier, Detector
from FlowCyPy.signal_processing import SignalProcessing, Digitizer
from FlowCyPy import FlowCytometer, SimulationSettings, units
from FlowCyPy.calibration import KEstimator

Configure simulation-level noise assumptions

SimulationSettings.include_noises = True
SimulationSettings.include_shot_noise = True
SimulationSettings.include_dark_current_noise = False
SimulationSettings.include_source_noise = False
SimulationSettings.include_amplifier_noise = False
SimulationSettings.assume_perfect_hydrodynamic_focusing = True
SimulationSettings.assume_amplifier_bandwidth_is_infinite = True
SimulationSettings.assume_perfect_digitizer = True
SimulationSettings.evenly_spaced_events = True

np.random.seed(3)  # Reproducibility

Construct simulation components

flow_cell = FlowCell(
    sample_volume_flow=80 * units.microliter / units.minute,
    sheath_volume_flow=1 * units.milliliter / units.minute,
    width=400 * units.micrometer,
    height=400 * units.micrometer,
)

scatterer_collection = ScattererCollection(medium_refractive_index=1.33 * units.RIU)

fluidics = Fluidics(
    scatterer_collection=scatterer_collection,
    flow_cell=flow_cell
)

_source = source.GaussianBeam(
    numerical_aperture=0.2 * units.AU,
    wavelength=450 * units.nanometer,
    optical_power=150 * units.milliwatt  # Fixed illumination power
)

digitizer = Digitizer(
    bit_depth='16bit',
    saturation_levels=(0 * units.volt, 2 * units.volt),
    sampling_rate=60 * units.megahertz,
)

amplifier = TransimpedanceAmplifier(
    gain=10 * units.volt / units.ampere,
    bandwidth=60 * units.megahertz,
)

detector_0 = Detector(
    name='default',
    phi_angle=0 * units.degree,
    numerical_aperture=0.2 * units.AU,
    cache_numerical_aperture=0.0 * units.AU,
    responsivity=1 * units.ampere / units.watt,
)

opto_electronics = OptoElectronics(
    detectors=[detector_0],
    source=_source,
    amplifier=amplifier
)

signal_processing = SignalProcessing(
    digitizer=digitizer,
    analog_processing=[],
)

flow_cytometer = FlowCytometer(
    opto_electronics=opto_electronics,
    fluidics=fluidics,
    signal_processing=signal_processing,
    background_power=_source.optical_power * 0.001
)

Run K Estimation Simulation

k_estimator = KEstimator(debug_mode=False)

k_estimator.add_batch(
    bead_diameters=np.linspace(300, 900, 15) * units.nanometer,
    illumination_power=_source.optical_power,
    flow_cytometer=flow_cytometer,
    particle_count=50 * units.particle
)

[INFO] Simulating bead 1/15: 300.0 nm
[INFO] Simulating bead 2/15: 342.85714285714283 nm
[INFO] Simulating bead 3/15: 385.7142857142857 nm
[INFO] Simulating bead 4/15: 428.57142857142856 nm
[INFO] Simulating bead 5/15: 471.42857142857144 nm
[INFO] Simulating bead 6/15: 514.2857142857142 nm
[INFO] Simulating bead 7/15: 557.1428571428571 nm
[INFO] Simulating bead 8/15: 600.0 nm
[INFO] Simulating bead 9/15: 642.8571428571429 nm
[INFO] Simulating bead 10/15: 685.7142857142857 nm
[INFO] Simulating bead 11/15: 728.5714285714286 nm
[INFO] Simulating bead 12/15: 771.4285714285713 nm
[INFO] Simulating bead 13/15: 814.2857142857142 nm
[INFO] Simulating bead 14/15: 857.1428571428571 nm
[INFO] Simulating bead 15/15: 900.0 nm

Plot estimation

k_estimator.plot()

Plot relevant statistics

k_estimator.plot_statistics()