src.canns.analyzer.experimental_data.cann1d

Attributes

HAS_NUMBA
data

Exceptions

AnimationError	Raised when animation creation fails.
CANN1DError	Base exception for CANN1D analysis errors.
FittingError	Raised when bump fitting fails.

Classes

AnimationConfig	Configuration for 1D CANN bump animation.
BumpFitsConfig	Configuration for CANN1D bump fitting.
CANN1DPlotConfig	Specialized PlotConfig for CANN1D visualizations.
Constants	Constants used throughout CANN1D analysis.
SiteBump

Functions

bump_fits(data[, config, save_path])	Fit CANN1D bumps to data using MCMC optimization.
create_1d_bump_animation(fits_data[, config, save_path])	Create 1D CANN bump animation using vectorized operations.

Module Contents

exception src.canns.analyzer.experimental_data.cann1d.AnimationError

Bases: CANN1DError

Raised when animation creation fails.

Initialize self. See help(type(self)) for accurate signature.

exception src.canns.analyzer.experimental_data.cann1d.CANN1DError

Bases: Exception

Base exception for CANN1D analysis errors.

Initialize self. See help(type(self)) for accurate signature.

exception src.canns.analyzer.experimental_data.cann1d.FittingError

Bases: CANN1DError

Raised when bump fitting fails.

Initialize self. See help(type(self)) for accurate signature.

class src.canns.analyzer.experimental_data.cann1d.AnimationConfig

Configuration for 1D CANN bump animation.

bump_selection: str = 'strongest'

fps: int = 5

max_height_value: float = 0.5

max_width_range: int = 40

nframes: int | None = None

npoints: int = 300

repeat: bool = False

show: bool = False

show_progress_bar: bool = True

title: str = '1D CANN Bump Animation'

class src.canns.analyzer.experimental_data.cann1d.BumpFitsConfig

Configuration for CANN1D bump fitting.

ampli_min: float = 2.0

beta: float = 5.0

jc: float = 1.8

kappa_mean: float = 2.5

n_bump_max: int = 4

n_roi: int = 16

n_steps: int = 20000

penbump: float = 0.4

random_seed: int | None = None

sig2: float = 1.0

sigma_diff: float = 0.5

class src.canns.analyzer.experimental_data.cann1d.CANN1DPlotConfig

Bases: src.canns.analyzer.plotting.PlotConfig

Specialized PlotConfig for CANN1D visualizations.

classmethod for_bump_animation(**kwargs)

Create configuration for 1D CANN bump animation.

bump_selection: str = 'strongest'

max_height_value: float = 0.5

max_width_range: int = 40

nframes: int | None = None

npoints: int = 300

class src.canns.analyzer.experimental_data.cann1d.Constants

Constants used throughout CANN1D analysis.

BASE_RADIUS = 1.0

DEFAULT_DPI = 100

DEFAULT_FIGSIZE = (4, 4)

MAX_KERNEL_SIZE = 60

NUMBA_THRESHOLD = 64

class src.canns.analyzer.experimental_data.cann1d.SiteBump

clone()

ampli = []

kappa = []

logl = 0.0

nbump = 0

pos = []

src.canns.analyzer.experimental_data.cann1d.bump_fits(data, config=None, save_path=None, **kwargs)

Fit CANN1D bumps to data using MCMC optimization.

Parameters:

• data – numpy.ndarray Input data for bump fitting

• config (BumpFitsConfig | None) – BumpFitsConfig, optional Configuration object with all fitting parameters

• save_path – str, optional Path to save the results

• **kwargs – backward compatibility parameters

Returns:

list

List of fitted bump objects

fits_arraynumpy.ndarray

Array of fitted bump parameters

nbump_arraynumpy.ndarray

Array of bump counts and reconstructed signals

centrbump_arraynumpy.ndarray

Array of centered bump data

Return type:

bumps

src.canns.analyzer.experimental_data.cann1d.create_1d_bump_animation(fits_data, config=None, save_path=None, **kwargs)

Create 1D CANN bump animation using vectorized operations.

Parameters:

• fits_data – numpy.ndarray Shape (n_fits, 4) array with columns [time, position, amplitude, kappa]

• config (CANN1DPlotConfig | None) – AnimationConfig, optional Configuration object with all animation parameters

• save_path – str, optional Output path for the generated GIF

• **kwargs – backward compatibility parameters

Returns:

matplotlib.animation.FuncAnimation

The animation object

src.canns.analyzer.experimental_data.cann1d.HAS_NUMBA = True

src.canns.analyzer.experimental_data.cann1d.data = None