pyrfu.pyrf.histogram2d module#

pyrfu.pyrf.histogram2d.histogram2d(inp1, inp2, bins=100, y_range=None, weights=None, density=True)[source]#

Computes 2d histogram of inp2 vs inp1 with nbins number of bins.

Parameters:

  • inp1 (xarray.DataArray) – Time series of the x coordinates of the points to be histogrammed.

  • inp2 (xarray.DataArray) – Time series of the y coordinates of the points to be histogrammed.

  • bins (str or int or tuple, Optional) – Number of bins. Default is bins=100.

  • y_range (array_like, shape(2,2), Optional) – The leftmost and rightmost edges of the bins along each dimension (if not specified explicitly in the bins parameters): [[xmin, xmax], [ymin, ymax]]. All values outside of this range will be considered outliers and not tallied in the histogram.

  • weights (array_like, shape(N,), Optional) – An array of values w_i weighing each sample (x_i, y_i). Weights are normalized to 1 if normed is True. If normed is False, the values of the returned histogram are equal to the sum of the weights belonging to the samples falling into each bin.

  • density (bool, Optional) – If False, the default, returns the number of samples in each bin. If True, returns the probability density function at the bin, bin_count / sample_count / bin_area.

Returns:

out – 2D map of the density of inp2 vs inp1.

Return type:

xarray.DataArray

Examples

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

Time interval

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

Spacecraft indices

>>> mms_id = np.arange(1, 5)

Load magnetic field and electric field

>>> r_mms = [mms.get_data("r_gse", tint, i) for i in mms_id]
>>> b_mms = [mms.get_data("b_gse_fgm_srvy_l2", tint, i) for i in 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)

Histogram of J vs B

>>> h2d_b_j = pyrf.histogram2d(b_mag, j_mag)