fluopy.fcs
==========

.. py:module:: fluopy.fcs

.. autoapi-nested-parse::

   Fluorescence correlation spectroscopy.



Classes
-------

.. autoapisummary::

   fluopy.fcs.FCS


Module Contents
---------------

.. py:class:: FCS(emissions: fluopy.emissions.Emissions)

   Container of FCS-associated attributes and methods.

   :ivar emissions: Container for emission-associated attributes.
   :vartype emissions: fluopy.emissions.Emissions
   :ivar autocorrelation: Autocorrelation values.
   :vartype autocorrelation: npt.NDArray[np.float64]
   :ivar tau: Time differences (i.e., τ, lag times).

   :vartype tau: npt.NDArray[np.float64]


   .. py:attribute:: emissions


   .. py:attribute:: autocorrelation
      :value: None



   .. py:attribute:: tau
      :value: None



   .. py:method:: autocorrelate_time_points(exp_min: int = -8, exp_max: int = 2, points_per_base: int = 4, base: int = 10, normalize: bool = True) -> Self

      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.

      :param exp_min: Exponent of the minimum value.
      :param exp_max: Exponent of the maximum value.
      :param points_per_base: Number of points per base.
      :param base: The base of the exponentiation.
      :param normalize: Whether to normalize the autocorrelation.

      :rtype: Self



   .. py:method:: autocorrelate_time_series(log: bool = True, m: int = 4, normalize: bool = True) -> Self

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

      :param 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.
      :param 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.
      :param normalize: Whether to normalize the autocorrelation.

      :rtype: Self



   .. py:method:: plot_matplotlib(normalize_to: int | None = None, unit: str = 's', ax: matplotlib.axes.Axes | None = None, **kwargs: Any) -> matplotlib.axes.Axes

      Plot FCS data.

      :param normalize_to: Index of datapoint to which the data is normalized.
      :param unit: One of 's', 'ms', 'us'. Influences the unit of the x-axis.
      :param ax: Axis to plot on.
      :param kwargs: Other parameters passed to :func:`matplotlib.pyplot.plot`.

      :returns: Axes object with the plot.
      :rtype: matplotlib.axes.Axes



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

      Plot FCS data.

      :param normalize_to: Index of datapoint to which the data is normalized.
      :param unit: One of 's', 'ms', 'us'. Influences the unit of the x-axis.
      :param kwargs: fluopy.figure.universal_figure arguments

      :returns: Contains matplotlib.axes._subplots.AxesSubplots.
      :rtype: npt.NDArray[mplAxes]