class saspt.StateArrayParameters(pixel_size_um: float, frame_interval: float)
__init__(pixel_size_um: float, frame_interval: float, focal_depth: float = np.inf, splitsize: int = DEFAULT_SPLITSIZE, sample_size: int = DEFAULT_SAMPLE_SIZE, start_frame: int = DEFAULT_START_FRAME, max_iter: int = DEFAULT_MAX_ITER, conc_param: float = DEFAULT_CONC_PARAM, progress_bar: bool = False, num_workers: int = 1)
  • pixel_size_um (float) – camera pixel size after magnification in microns

  • frame_interval (float) – delay between frames in seconds

  • splitsize (int) – maximum length of trajectories in frames. Trajectories longer than splitsize are split into smaller pieces.

  • sample_size (int) – maximum number of trajectories to consider per state array. SPT experiments that exceed this number are subsampled.

  • start_frame (int) – disregard detections before this frame. Useful to restrict analysis to later frames with lower detection density.

  • max_iter (int) – maximum number of iterations of variational Bayesian inference to run when inferring the posterior distribution

  • conc_param (float) – concentration parameter of the Dirichlet prior over state occupations. A conc_param of 1.0 is a naive prior; values less than 1.0 favor more states and values greater than 1.0 favor fewer states. Default value is 1.0.

  • progress_bar (bool) – show progress and be a little verbose, where relevant

  • num_workers (int) – number of parallel processes to use. Recommended not to set this higher than the number of CPUs.


new instance of StateArrayParameters

property parameters: Tuple[str]

Names of all parameters that directly impact the state array algorithm. Does not include parameters that determine implementation or display, such as progress_bar or num_workers

property units: dict

Physical units in which each parameter is defined

__eq__(self, other: StateArrayParameters) bool

Check for equivalence of two StateArrayParameter objects

__repr__(self) str

String representation of this StateArrayParameters object