Signal parameters

I will enrich rampy with new functions to calculate the characteristics/parameters of signals. This is not urgent as scipy.signal allows us to do many things already (e.g. with find_peaks…), and there is no need to reinvent the wheel. One function is often useful and that is not in scipy.signal:

class rampy.spectranization.centroid(x: ndarray, y: ndarray, smoothing: bool = False, **kwargs)

Bases:

Calculates the centroid of y signal(s).

The centroid is calculated as ( ext{centroid} = sum(y / sum(y) cdot x) ).

Parameters:

  • x (np.ndarray) – A 2D array of shape (m values, n samples) containing the x-axis values.

  • y (np.ndarray) – A 2D array of shape (m values, n samples) containing the y-axis values.

  • smoothing (bool) – Whether to smooth the signals before calculating centroids. If True, smoothing is applied using rampy.smooth with additional arguments passed via kwargs.

Returns:

A 1D array of centroids for each sample in y.

Return type:

np.ndarray

Example

>>> import numpy as np
>>> import rampy as rp
>>> x = np.linspace(0, 10, 100).reshape(-1, 1)
>>> y = rp.gaussian(x, 10., 50., 2.0)
>>> centroids = rp.centroid(x, y)