pogona.SensorEmpirical
- class pogona.SensorEmpirical[source]
Bases:
Sensor
Sensor based on empirical measurements of susceptibility variations within a susceptometer.
For this, we shall assume that molecules pass through the sensor in positive (object-local!) z direction and that the sensor (i.e., the boundary) is 25 mm long! So remember to rotate this sensor via the transformation accordingly if your particles aren’t moving from -z to +z.
Attributes
Default distribution parameters for known sensors.
Unique name of this component, unless it is "Generic component".
Distribution parameters obtained from curve fitting, for now applied to a logistic function by default.
The file sensor[<component name>].csv will be created in here.
Shape of this sensor.
Use distribution parameters obtained for known sensors in previous experiments.
Methods
__init__
()finalize
(simulation_kernel)initialize
(simulation_kernel, init_stage)Use
InitStages
to initialize this Component instance.is_inside_sensor_zone
(position_global)Override this method for your sensing algorithm.
Called before updating the position of a particle within a time step.
process_new_time_step
(simulation_kernel, ...)set_arguments
(**kwargs)Read arguments as key value pairs and set this component's member variables accordingly.
- finalize(simulation_kernel: SimulationKernel)[source]
- initialize(simulation_kernel: SimulationKernel, init_stage: InitStages)[source]
Use
InitStages
to initialize this Component instance.
- is_inside_sensor_zone(position_global: ndarray)
- process_molecule_moving_after(simulation_kernel: SimulationKernel, molecule: Molecule)[source]
Override this method for your sensing algorithm. The sensor manager will use this method to notify you of all molecule movement inside of the sensor zone. However, it may also notify you of molecule movement outside of your sensor zone! So make sure you additionally check the molecule position yourself. See SensorCounting for a simple reference implementation.
- Parameters
simulation_kernel – The single simulation kernel
molecule – Which molecule has moved, with the new position
- process_molecule_moving_before(simulation_kernel: SimulationKernel, molecule: Molecule)
Called before updating the position of a particle within a time step. Useful for SensorTeleporting, for example, which should consider the position of particles right after they have been spawned.
- Parameters
simulation_kernel –
molecule –
- Returns
- process_new_time_step(simulation_kernel: SimulationKernel, notification_stage: NotificationStages)[source]
- set_arguments(**kwargs)
Read arguments as key value pairs and set this component’s member variables accordingly. Validity of the argument values will be checked in
initialize()
.
- DEFAULT_FCT_PARAMS = {<KnownSensors.MS2G_BARTINGTON: 2>: [1.1710899115768234, 0.012806480117364473, 0.0017908368596852163], <KnownSensors.ERLANGEN_20200310: 3>: [1.1521874852663174, 0.017531424609419782, 0.003804701283874202]}
Default distribution parameters for known sensors. Values determined using curve fitting for the logistic function.
- component_name = 'Generic component'
Unique name of this component, unless it is “Generic component”.
- distribution_params = []
Distribution parameters obtained from curve fitting, for now applied to a logistic function by default. Alternatively, use use_known_sensor.
- id
Unique integer component ID
- log_folder = 'sensor_data'
The file sensor[<component name>].csv will be created in here.
- rotation = [0, 0, 0]
- scale = [1, 1, 1]
- sensor_id: int
Unique integer sensor ID. Set by the sensor manager.
- shape = 'NONE'
Shape of this sensor. Valid shapes are defined in the
pogona.Shapes
enum.
- property transformation: Transformation
- translation = [0, 0, 0]
- use_known_sensor = 'MS2G_BARTINGTON'
Use distribution parameters obtained for known sensors in previous experiments.
Default: MS2G_BARTINGTON