amep.utils.average_func

amep.utils.average_func(func: callable, data: list | ndarray, skip: float = 0.0, nr: int = 10, indices: bool = False, **kwargs)

Compute the average of a certain function.

Parameters:

• func (func) – function that has to be averaged

• data (list/np.ndarray) – list/array of data for each time step (input for func)

• skip (float, default=0.0) – fraction of the whole trajectory that is skipped at the beginning of the trajectory for the calculation of the time average (float between 0.0 and 1.0)

• nr (int, default=10) – maximum number of frames to average over

• indices (bool, default=False) – If True, the list indices that the averaging function used are returned as last output!

• **kwargs (Keyword Arguments) – keyword arguments that are put to func

Returns:

• list – list of func results for each time step

• various – time-averaged value of func for given trajectory

Examples

>>> import amep
>>> import numpy as np
>>> def function(x):
...     return x**2
>>> x = np.linspace(0,100,1000)
>>> y = np.sin(x)
>>> function_yvalues, average = amep.utils.average_func(
...     function, y, nr=20
... )
>>> function_xvalues, _ = amep.utils.average_func(
...     lambda x:x, x, nr=20
... )
>>> fig, axs = amep.plot.new()
>>> axs.plot(
...     function_xvalues, function_yvalues,
...     label='data'
... )
>>> axs.axhline(average, label='average', ls='--')
>>> axs.legend()
>>> axs.set_xlabel(r'$x$')
>>> axs.set_ylabel(r'$y$')
>>> fig.savefig('./figures/utils/utils-average_func.png')
>>>