fluopy.fcs

Fluorescence correlation spectroscopy.

Classes

FCS

Container of FCS-associated attributes and methods.

Module Contents

class fluopy.fcs.FCS(emissions: fluopy.emissions.Emissions)[source]

Container of FCS-associated attributes and methods.

Variables:

  • emissions (fluopy.emissions.Emissions) – Container for emission-associated attributes.

  • autocorrelation (npt.NDArray[np.float64]) – Autocorrelation values.

  • tau (npt.NDArray[np.float64]) – Time differences (i.e., τ, lag times).

emissions
autocorrelation = None
tau = None
autocorrelate_time_points(exp_min: int = -8, exp_max: int = 2, points_per_base: int = 4, base: int = 10, normalize: bool = True) → Self[source]

Autocorrelation of emissions.event_time_points. Generally much faster than autocorrelation based on emissions.event_time_series. Based on https://opg.optica.org/ol/abstract.cfm?uri=ol-31-6-829.

Parameters:

  • exp_min – Exponent of the minimum value.

  • exp_max – Exponent of the maximum value.

  • points_per_base – Number of points per base.

  • base – The base of the exponentiation.

  • normalize – Whether to normalize the autocorrelation.

Return type:

Self

autocorrelate_time_series(log: bool = True, m: int = 4, normalize: bool = True) → Self[source]

Autocorrelation of emissions.event_time_series. The minimum lag time is equal to sampling interval of series.

Parameters:

  • log – Whether to compute the autocorrelation on a logarithmic scale. As time steps increase, correlation signals are getting noisier, fluctuating around 0. Hence, log should usually be True.

  • m – Defines the number of points on each log level. E.g., m=4 leads to |1, 2, 3, 4| |2, 4, 6, 8| |4, 8, 12, 16| …, hence |1, 2, 3, 4, 6, 8, 12, 16, ...|. Only used if log is True.

  • normalize – Whether to normalize the autocorrelation.

Return type:

Self

plot_matplotlib(normalize_to: int | None = None, unit: str = 's', ax: matplotlib.axes.Axes | None = None, **kwargs: Any) → matplotlib.axes.Axes[source]

Plot FCS data.

Parameters:

  • normalize_to – Index of datapoint to which the data is normalized.

  • unit – One of ‘s’, ‘ms’, ‘us’. Influences the unit of the x-axis.

  • ax – Axis to plot on.

  • kwargs – Other parameters passed to matplotlib.pyplot.plot().

Returns:

Axes object with the plot.

Return type:

matplotlib.axes.Axes

plot(normalize_to: int | None = None, unit: str = 's', **kwargs: Any) → numpy.typing.NDArray[matplotlib.axes.Axes][source]

Plot FCS data.

Parameters:

  • normalize_to – Index of datapoint to which the data is normalized.

  • unit – One of ‘s’, ‘ms’, ‘us’. Influences the unit of the x-axis.

  • kwargs – fluopy.figure.universal_figure arguments

Returns:

Contains matplotlib.axes._subplots.AxesSubplots.

Return type:

npt.NDArray[mplAxes]