circmoment#
- astropy.stats.circstats.circmoment(data: NDArray | Quantity, p: float | None = 1.0, centered: bool | None = False, axis: int | None = None, weights: NDArray | None = None) NDArray | Quantity [source]#
Computes the
p
-th trigonometric circular moment for an array of circular data.- Parameters:
- data
ndarray
orQuantity
Array of circular (directional) data, which is assumed to be in radians whenever
data
isnumpy.ndarray
.- p
float
, optional Order of the circular moment.
- centeredbool, 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.
- data
- Returns:
References
[1]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) (<Quantity 90.99263082432564 deg>, <Quantity 0.48004283892950717>)