17192022881

Committed 24 Aug 2025 06:00PM UTC coverage: 89.279% (+0.09%) from 89.194%

Build # 17192022881

Build Type

push

github

Committed by

jameswilburlewis

Commit Message

Remove references to obsolete 'new_tvar' parameter

Run Details

11 of 11 new or added lines in 10 files covered. (100.0%)

29 existing lines in 6 files now uncovered.

40356 of 45202 relevant lines covered (89.28%)

0.89 hits per line

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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	1✔
3	import pyspedas	1✔
4	from pyspedas.tplot_tools import tnames, tplot_copy	1✔
5	import numpy	1✔
6
7
8	def subtract_average(	1✔
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
49	old_names = tnames(names)	1✔
50
51	if len(old_names) == 0:	1✔
52	return	1✔
53	elif len(old_names) < 1:	1✔
UNCOV 54	logging.error('Subtract Average error: No tplot names were provided.')	×
UNCOV 55	return	×
56
57	if suffix is None:	1✔
58	if median:	1✔
59	suffix = '-m'	1✔
60	else:
61	suffix = '-d'	1✔
62
63	if overwrite is not None:	1✔
64	n_names = old_names	1✔
65	elif newname is None:	1✔
66	n_names = [s + suffix for s in old_names]	1✔
67	else:
68	n_names = newname	1✔
69
70	if isinstance(n_names, str):	1✔
71	n_names = [n_names]	1✔
72
73	if len(n_names) != len(old_names):	1✔
74	n_names = [s + suffix for s in old_names]	1✔
75
76	old_names = tnames(names)	1✔
77
78	for old_idx, old in enumerate(old_names):	1✔
79	new = n_names[old_idx]	1✔
80
81	if new != old:	1✔
82	tplot_copy(old, new)	1✔
83
84	data = pyspedas.tplot_tools.data_quants[new].values	1✔
85	# Subtracting the average will fail if data is not a floating point type
86	if data.dtype.kind != 'f':	1✔
UNCOV 87	data=numpy.float64(data)	×
88	dim = data.shape	1✔
89	if median:	1✔
90	if len(dim) == 1:	1✔
91	if not numpy.isnan(data).all():	1✔
92	data -= numpy.nanmedian(data, axis=0)	1✔
93	else:
94	for i in range(dim[1]):	1✔
95	if not numpy.isnan(data[:, i]).all():	1✔
96	data[:, i] -= numpy.nanmedian(data[:, i], axis=0)	1✔
97	ptype = 'Median'	1✔
98	else:
99	if len(dim) == 1:	1✔
100	if not numpy.isnan(data).all():	1✔
101	data -= numpy.nanmean(data, axis=0)	1✔
102	else:
103	for i in range(dim[1]):	1✔
104	if not numpy.isnan(data[:, i]).all():	1✔
105	data[:, i] -= numpy.nanmean(data[:, i], axis=0)	1✔
106	ptype = 'Mean'	1✔
107
108	pyspedas.tplot_tools.data_quants[new].values = data	1✔
109
110	logging.info('Subtract ' + ptype + ' was applied to: ' + new)	1✔
111
112	return n_names	1✔

spedas / pyspedas / 17192022881

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