pyrfu.pyrf.median_bins module#

pyrfu.pyrf.median_bins.median_bins(inp0, inp1, bins: int = 10)[source]#

Computes median of values of y corresponding to bins of x

Parameters:

  • inp0 (xarray.DataArray) – Time series of the quantity of bins.

  • inp1 (xarray.DataArray) – Time series of the quantity to the median.

  • bins (int, Optional) – Number of bins.

Returns:

out –

Dataset with :
  • binsxarray.DataArray

    bin values of the x variable.

  • dataxarray.DataArray

    Median values of y corresponding to each bin of x.

  • sigmaxarray.DataArray

    Standard deviation.

Return type:

xarray.Dataset

Examples

>>> import numpy
>>> from pyrfu import mms, pyrf

Time interval

>>> tint = ["2019-09-14T07:54:00.000", "2019-09-14T08:11:00.000"]

Spacecraft indices

>>> mms_list = numpy.arange(1,5)

Load magnetic field and electric field

>>> r_mms, b_mms = [[] * 4 for _ in range(2)]
>>> for mms_id in range(1, 5):
>>>         r_mms.append(mms.get_data("R_gse", tint, mms_id))
>>>         b_mms.append(mms.get_data("B_gse_fgm_srvy_l2", tint, mms_id))
>>>

Compute current density, etc

>>> j_xyz, _, b_xyz, _, _, _ = pyrf.c_4_j(r_mms, b_mms)

Compute magnitude of B and J

>>> b_mag = pyrf.norm(b_xyz)
>>> j_mag = pyrf.norm(j_xyz)

Median value of J for 10 bins of B

>>> med_b_j = pyrf.mean_bins(b_mag, j_mag)