calpy.rqa package

Submodules

calpy.rqa.rqa module

calpy.rqa.rqa.cross_recurrence_matrix(xps, yps)[source]

Cross reccurence matrix.

Args:
xps (numpy.array): yps (numpy.array):
Returns:
numpy.array : A 2D numpy array.
calpy.rqa.rqa.determinism(AA)[source]

Calculates percentage of recurrence points which form diagonal lines.

Args:
AA (numpy.array): A reccurence matrix.
Returns:
float: The determinism.
calpy.rqa.rqa.divergence(AA)[source]

Divergence

Args:
AA (numpy.array): A numpy array.
Returns:
numpy.array: The answer.
calpy.rqa.rqa.entropy(AA)[source]

Entropy

Args:
AA (numpy.array): A numpy array.
Returns:
numpy.array: The answer.
calpy.rqa.rqa.joint_recurrence_matrix(xps, yps)[source]

Joint reccurence matrix.

Args:
xps (numpy.array): yps (numpy.array):
Returns:
numpy.array : A 2D numpy array.
calpy.rqa.rqa.laminarity(AA)[source]

Laminarity. Calculates percentage of recurrence points which form verticle lines.

This function calculates Trapping as a side effect.

Args:
AA (numpy.array(float)): A 2D matrix.
Returns:
float: The laminarity
class calpy.rqa.rqa.phase_space(xs, tau=1, m=2, eps=0.001)[source]

Bases: object

Phase space class.

calpy.rqa.rqa.pred(AA)[source]

Pred

Args:
AA (numpy.array): A numpy array.
Returns:
numpy.array: The answer.
calpy.rqa.rqa.recurrence_matrix(xps, yps=None, joint=False)[source]

Computes cross-reccurence matrix when two inputs are given and self-reccurence otherwise.

Args:
xps (numpy.array): Phase_space object(s). yps (numpy.array, optional): Phase_space object for cross reccurence. Defaults to none. joint (bool, optional): Should joint reccurence be calculated? Defaults to False.
Returns:
numpy.array : A 2D numpy matrix.
calpy.rqa.rqa.recurrence_rate(AA)[source]

Computes reccurence-rate from reccurence matrix.

Args:
AA (numpy.array): A reccurence matrix.
Returns:
numpy.array : A numpy array.
calpy.rqa.rqa.trapping(AA)[source]

Trapping. Calculates ...

This function calculates Laminiarity as a side effect.

Args:
AA (numpy.array(float)): A 2D matrix.
Returns:
float: The trapping
calpy.rqa.rqa.trend(AA, longterm=False)[source]

Calculate the TREND of a give 1d numpy array R.

Args:
AA (numpy.array(float)): A 2D matrix. longterm (bool, optional): Should long-term trend be calculate? Defaults to False.
Returns:
float: The medium and long range trends a float tuple (Med, Long)