circmoment¶
-
astropy.stats.
circmoment
(data, p=1.0, centered=False, axis=None, weights=None)[source] [edit on github]¶ Computes the
p
-th trigonometric circular moment for an array of circular data.Parameters: - data : numpy.ndarray or Quantity
Array of circular (directional) data, which is assumed to be in radians whenever
data
isnumpy.ndarray
.- p : float, optional
Order of the circular moment.
- centered : Boolean, optional
If
True
, central circular moments are computed. Default value isFalse
.- axis : int, optional
Axis along which circular moments are computed. The default is to compute the circular moment of the flattened array.
- weights : numpy.ndarray, optional
In case of grouped data, the i-th element of
weights
represents a weighting factor for each group such thatsum(weights, axis)
equals the number of observations. See [1], remark 1.4, page 22, for detailed explanation.
Returns: - circmoment : numpy.ndarray or Quantity
The first and second elements correspond to the direction and length of the
p
-th circular moment, respectively.
References
[1] (1, 2) S. R. Jammalamadaka, A. SenGupta. “Topics in Circular Statistics”. Series on Multivariate Analysis, Vol. 5, 2001. [2] C. Agostinelli, U. Lund. “Circular Statistics from ‘Topics in Circular Statistics (2001)’”. 2015. <https://cran.r-project.org/web/packages/CircStats/CircStats.pdf> Examples
>>> import numpy as np >>> from astropy.stats import circmoment >>> from astropy import units as u >>> data = np.array([51, 67, 40, 109, 31, 358])*u.deg >>> circmoment(data, p=2) # doctest: +FLOAT_CMP (<Quantity 90.99263082432564 deg>, <Quantity 0.48004283892950717>)