26171438601

Committed 20 May 2026 02:07AM UTC coverage: 90.571% (+0.01%) from 90.557%

Build # 26171438601

Build Type

push

github

Committed by

jameswilburlewis

Commit Message

Fix crash when a spectrogram is plotted with Y axis interpolation is enabled and Y scaling is linear.
Add regression test for y_interp bug.

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0 of 4 new or added lines in 2 files covered. (0.0%)

17831 existing lines in 383 files now uncovered.

44379 of 48999 relevant lines covered (90.57%)

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94.12

/pyspedas/tplot_tools/tplot_math/subtract_average.py


import logging
import pyspedas
from pyspedas.tplot_tools import tnames, tplot_copy
import numpy


def subtract_average(
        names,
        newname=None,
        suffix=None,
        overwrite=None,
        median=None
):
    """
    Subtracts the average or median from data.

    Parameters
    ----------
    names: str/list of str
        List of tplot variable names to process (wildcards accepted)
    newname: str/list of str, optional
        List of new names for tplot variables.
        Default: None. If not given, then a suffix is applied.
    suffix: str, optional
        A suffix to apply.
        Default: '-d'.
    overwrite: bool, optional
        If set, then tplot variables are replaced.
        Default: None
    median: float, optional
        If it is 0 or not set, then it computes the mean.
        Otherwise, it computes the median.
        Default: None.

    Returns
    -------
    list of str
        List of new tplot variables created

    Examples
    --------
        >>> pyspedas.store_data('a', data={'x':[0,4,8,12,16], 'y':[1,2,3,4,5]})
        >>> pyspedas.subtract_average('a')
        >>> pyspedas.tplot(['a','a-d'])

    """

    old_names = tnames(names)

    if len(old_names) == 0:
        return
    elif len(old_names) < 1:
        logging.error('Subtract Average error: No tplot names were provided.')
        return

    if suffix is None:
        if median:
            suffix = '-m'
        else:
            suffix = '-d'

    if overwrite is not None:
        n_names = old_names
    elif newname is None:
        n_names = [s + suffix for s in old_names]
    else:
        n_names = newname

    if isinstance(n_names, str):
        n_names = [n_names]

    if len(n_names) != len(old_names):
        n_names = [s + suffix for s in old_names]

    old_names = tnames(names)

    for old_idx, old in enumerate(old_names):
        new = n_names[old_idx]

        if new != old:
            tplot_copy(old, new)

        data = pyspedas.tplot_tools.data_quants[new].values
        # Subtracting the average will fail if data is not a floating point type
        if data.dtype.kind != 'f':
            data=numpy.float64(data)
        dim = data.shape
        if median:
            if len(dim) == 1:
                if not numpy.isnan(data).all():
                        data -= numpy.nanmedian(data, axis=0)
            else:
                for i in range(dim[1]):
                    if not numpy.isnan(data[:, i]).all():
                        data[:, i] -= numpy.nanmedian(data[:, i], axis=0)
            ptype = 'Median'
        else:
            if len(dim) == 1:
                if not numpy.isnan(data).all():
                    data -= numpy.nanmean(data, axis=0)
            else:
                for i in range(dim[1]):
                    if not numpy.isnan(data[:, i]).all():
                        data[:, i] -= numpy.nanmean(data[:, i], axis=0)
            ptype = 'Mean'

        pyspedas.tplot_tools.data_quants[new].values = data

        logging.info('Subtract ' + ptype + ' was applied to: ' + new)

    return n_names

1
2	import logging	2✔
3	import pyspedas	2✔
4	from pyspedas.tplot_tools import tnames, tplot_copy	2✔
5	import numpy	2✔
6
7
8	def subtract_average(	2✔
9	names,
10	newname=None,
11	suffix=None,
12	overwrite=None,
13	median=None
14	):
15	"""
16	Subtracts the average or median from data.
17
18	Parameters
19	----------
20	names: str/list of str
21	List of tplot variable names to process (wildcards accepted)
22	newname: str/list of str, optional
23	List of new names for tplot variables.
24	Default: None. If not given, then a suffix is applied.
25	suffix: str, optional
26	A suffix to apply.
27	Default: '-d'.
28	overwrite: bool, optional
29	If set, then tplot variables are replaced.
30	Default: None
31	median: float, optional
32	If it is 0 or not set, then it computes the mean.
33	Otherwise, it computes the median.
34	Default: None.
35
36	Returns
37	-------
38	list of str
39	List of new tplot variables created
40
41	Examples
42	--------
43	>>> pyspedas.store_data('a', data={'x':[0,4,8,12,16], 'y':[1,2,3,4,5]})
44	>>> pyspedas.subtract_average('a')
45	>>> pyspedas.tplot(['a','a-d'])
46
47	"""
48
UNCOV 49	old_names = tnames(names)	1✔
50
UNCOV 51	if len(old_names) == 0:	1✔
UNCOV 52	return	1✔
UNCOV 53	elif len(old_names) < 1:	1✔
54	logging.error('Subtract Average error: No tplot names were provided.')	×
55	return	×
56
UNCOV 57	if suffix is None:	1✔
UNCOV 58	if median:	1✔
UNCOV 59	suffix = '-m'	1✔
60	else:
UNCOV 61	suffix = '-d'	1✔
62
UNCOV 63	if overwrite is not None:	1✔
UNCOV 64	n_names = old_names	1✔
UNCOV 65	elif newname is None:	1✔
UNCOV 66	n_names = [s + suffix for s in old_names]	1✔
67	else:
UNCOV 68	n_names = newname	1✔
69
UNCOV 70	if isinstance(n_names, str):	1✔
UNCOV 71	n_names = [n_names]	1✔
72
UNCOV 73	if len(n_names) != len(old_names):	1✔
UNCOV 74	n_names = [s + suffix for s in old_names]	1✔
75
UNCOV 76	old_names = tnames(names)	1✔
77
UNCOV 78	for old_idx, old in enumerate(old_names):	1✔
UNCOV 79	new = n_names[old_idx]	1✔
80
UNCOV 81	if new != old:	1✔
UNCOV 82	tplot_copy(old, new)	1✔
83
UNCOV 84	data = pyspedas.tplot_tools.data_quants[new].values	1✔
85	# Subtracting the average will fail if data is not a floating point type
UNCOV 86	if data.dtype.kind != 'f':	1✔
87	data=numpy.float64(data)	×
UNCOV 88	dim = data.shape	1✔
UNCOV 89	if median:	1✔
UNCOV 90	if len(dim) == 1:	1✔
UNCOV 91	if not numpy.isnan(data).all():	1✔
UNCOV 92	data -= numpy.nanmedian(data, axis=0)	1✔
93	else:
UNCOV 94	for i in range(dim[1]):	1✔
UNCOV 95	if not numpy.isnan(data[:, i]).all():	1✔
UNCOV 96	data[:, i] -= numpy.nanmedian(data[:, i], axis=0)	1✔
UNCOV 97	ptype = 'Median'	1✔
98	else:
UNCOV 99	if len(dim) == 1:	1✔
UNCOV 100	if not numpy.isnan(data).all():	1✔
UNCOV 101	data -= numpy.nanmean(data, axis=0)	1✔
102	else:
UNCOV 103	for i in range(dim[1]):	1✔
UNCOV 104	if not numpy.isnan(data[:, i]).all():	1✔
UNCOV 105	data[:, i] -= numpy.nanmean(data[:, i], axis=0)	1✔
UNCOV 106	ptype = 'Mean'	1✔
107
UNCOV 108	pyspedas.tplot_tools.data_quants[new].values = data	1✔
109
UNCOV 110	logging.info('Subtract ' + ptype + ' was applied to: ' + new)	1✔
111
UNCOV 112	return n_names	1✔

spedas / pyspedas / 26171438601

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