Source code for pyrfu.pyrf.calc_agyro
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 3rd party imports
import numpy as np
import xarray as xr
# Local imports
from .ts_scalar import ts_scalar
__author__ = "Louis Richard"
__email__ = "louisr@irfu.se"
__copyright__ = "Copyright 2020-2023"
__license__ = "MIT"
__version__ = "2.4.2"
__status__ = "Prototype"
[docs]def calc_agyro(p_xyz):
r"""Computes agyrotropy coefficient as
.. math::
A\Phi = \frac{|P_{\perp 1} - P_{\perp 2}|}{P_{\perp 1}
+ P_{\perp 2}}
Parameters
----------
p_xyz : xarray.DataArray
Time series of the pressure tensor
Returns
-------
agyro : xarray.DataArray
Time series of the agyrotropy coefficient of the specie.
Examples
--------
>>> from pyrfu import mms, pyrf
Time interval
>>> tint = ["2019-09-14T07:54:00.000","2019-09-14T08:11:00.000"]
Spacecraft index
>>> ic = 1
Load magnetic field and electron pressure tensor
>>> b_xyz = mms.get_data("b_gse_fgm_srvy_l2", tint, 1)
>>> p_xyz_e = mms.get_data("pe_gse_fpi_fast_l2", tint, 1)
Rotate electron pressure tensor to field aligned coordinates
>>> p_fac_e_qq = mms.rotate_tensor(p_xyz_e, "fac", b_xyz, "qq")
Compute agyrotropy coefficient
>>> agyro_e = pyrf.calc_agyro(p_fac_e_qq)
"""
# Check input type
assert isinstance(p_xyz, xr.DataArray), "p_xyz must be a xarray.DataArray"
# Check import shape
message = "p_xyz must be a time series of a tensor"
assert p_xyz.data.ndim == 3 and p_xyz.shape[1] == 3 and p_xyz.shape[2] == 3, message
# Parallel and perpendicular components
p_perp_1, p_perp_2 = [p_xyz.data[:, 1, 1], p_xyz.data[:, 2, 2]]
agyrotropy = np.abs(p_perp_1 - p_perp_2) / (p_perp_1 + p_perp_2)
agyrotropy = ts_scalar(p_xyz.time.data, agyrotropy)
return agyrotropy