25194239086

Committed 26 Apr 2026 08:07PM UTC coverage: 61.697% (-28.8%) from 90.54%

Build # 25194239086

Build Type

push

github

Committed by

jameswilburlewis

Commit Message

Added test for loading Cluster CODIF differential energy flux

Coverage Stats

0 of 7 new or added lines in 1 file covered. (0.0%)

19460 existing lines in 418 files now uncovered.

30204 of 48955 relevant lines covered (61.7%)

1.44 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

11.54

/pyspedas/tplot_tools/tplot_math/add_across.py

# Copyright 2018 Regents of the University of Colorado. All Rights Reserved.
# Released under the MIT license.
# This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics.
# Verify current version before use at: https://github.com/MAVENSDC/Pytplot

import pyspedas
import numpy as np
import copy
import logging
from pyspedas.tplot_tools import convert_tplotxarray_to_pandas_dataframe, store_data

def add_across(tvar,column_range=None,newname=None):
    """
    Adds across columns in the tplot variable

    .. note::
        This analysis routine assumes the data is no more than 2 dimensions.  If there are more, they may become flattened!

    Parameters
    ----------
        tvar : str
            Name of tplot variable.
        column_range: list of ints
            The columns to add together.  For example, if [1,4] is given here, columns 1, 2, 3, and 4 will be added together.
            If not set, then every column is added.
        newname : str
            Name of new tvar for averaged data.  If not set, then the variable is replaced

    Returns
    -------
        None

    Examples
    --------

        >>> #Add across every column in the data
        >>> pyspedas.store_data('d', data={'x':[2,5,8,11,14,17,21], 'y':[[1,1,50],[2,2,3],[100,4,47],[4,90,5],[5,5,99],[6,6,25],[7,7,-5]]})
        >>> pyspedas.add_across('d',newname='d_aa')


        >>> #Add across specific columns in the data
        >>> pyspedas.store_data('b', data={'x':[2,5,8,11,14,17,20], 'y':[[1,1,1,1,1,1],[2,2,5,4,1,1],[100,100,3,50,1,1],[4,4,8,58,1,1],[5,5,9,21,1,1],[6,6,2,2,1,1],[7,7,1,6,1,1]]})
        >>> pyspedas.add_across('b',column_range=[[1,2],[3,4]],newname='b_aap')

    """

    # separate and add data

    if 'spec_bins' in pyspedas.tplot_tools.data_quants[tvar].coords:
        d, s = convert_tplotxarray_to_pandas_dataframe(tvar)
    else:
        d = convert_tplotxarray_to_pandas_dataframe(tvar, no_spec_bins=True)
        s = None

    time = d.index.copy()
    data1 = d.copy()
    if s is not None:
        data2 = s.copy()
    else:
        data2=None
    data = []
    spec_data = []

    if column_range is None:
        column_range = [0, len(d.columns)-1]

    #grab column data
    if len(column_range)==2 and isinstance(column_range[0],int):
        range_start = column_range[0]
        range_end = column_range[1]
        add_col = list(range(range_start,range_end+1))
        datasum = data1[add_col].sum(axis=1)
        data = data + [list(datasum)]
    else:
        for i in column_range:
            #if not a list
            if type(i) == int:
                data = data + [list(data1[i])]
            #sum across listed column range
            else:
                range_start = i[0]
                range_end = i[1]
                add_col = list(range(range_start,range_end+1))
                datasum = data1[add_col].sum(axis=1)
                data = data + [list(datasum)]

    if data2 is not None:
        if len(column_range) == 2 and isinstance(column_range[0], int):
            range_start = column_range[0]
            range_end = column_range[1]
            add_col = list(range(range_start, range_end + 1))
            datasum = data2[add_col].mean(axis=1)
            spec_data = spec_data + [list(datasum)]
        else:
            for i in column_range:
                # if not a list
                if type(i) == int:
                    spec_data = spec_data + [list(data2[i])]
                # sum across listed column range
                else:
                    range_start = i[0]
                    range_end = i[1]
                    add_col = list(range(range_start, range_end + 1))
                    datasum = data2[add_col].mean(axis=1)
                    spec_data = spec_data + [list(datasum)]

    #store added data
    if s is None:
        store_data(newname,data={'x':time, 'y':np.transpose(data)})
    else:
        store_data(newname, data={'x': time, 'y':np.transpose(data), 'v': np.transpose(spec_data)})

    #pyspedas.tplot_tools.data_quants[newname].attrs = copy.deepcopy(pyspedas.tplot_tools.data_quants[tvar].attrs)

    return


1	# Copyright 2018 Regents of the University of Colorado. All Rights Reserved.
2	# Released under the MIT license.
3	# This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics.
4	# Verify current version before use at: https://github.com/MAVENSDC/Pytplot
5
6	import pyspedas	3✔
7	import numpy as np	3✔
8	import copy	3✔
9	import logging	3✔
10	from pyspedas.tplot_tools import convert_tplotxarray_to_pandas_dataframe, store_data	3✔
11
12	def add_across(tvar,column_range=None,newname=None):	3✔
13	"""
14	Adds across columns in the tplot variable
15
16	.. note::
17	This analysis routine assumes the data is no more than 2 dimensions. If there are more, they may become flattened!
18
19	Parameters
20	----------
21	tvar : str
22	Name of tplot variable.
23	column_range: list of ints
24	The columns to add together. For example, if [1,4] is given here, columns 1, 2, 3, and 4 will be added together.
25	If not set, then every column is added.
26	newname : str
27	Name of new tvar for averaged data. If not set, then the variable is replaced
28
29	Returns
30	-------
31	None
32
33	Examples
34	--------
35
36	>>> #Add across every column in the data
37	>>> pyspedas.store_data('d', data={'x':[2,5,8,11,14,17,21], 'y':[[1,1,50],[2,2,3],[100,4,47],[4,90,5],[5,5,99],[6,6,25],[7,7,-5]]})
38	>>> pyspedas.add_across('d',newname='d_aa')
39
40
41	>>> #Add across specific columns in the data
42	>>> pyspedas.store_data('b', data={'x':[2,5,8,11,14,17,20], 'y':[[1,1,1,1,1,1],[2,2,5,4,1,1],[100,100,3,50,1,1],[4,4,8,58,1,1],[5,5,9,21,1,1],[6,6,2,2,1,1],[7,7,1,6,1,1]]})
43	>>> pyspedas.add_across('b',column_range=[[1,2],[3,4]],newname='b_aap')
44
45	"""
46
47	# separate and add data
48
UNCOV 49	if 'spec_bins' in pyspedas.tplot_tools.data_quants[tvar].coords:	×
50	d, s = convert_tplotxarray_to_pandas_dataframe(tvar)	×
51	else:
UNCOV 52	d = convert_tplotxarray_to_pandas_dataframe(tvar, no_spec_bins=True)	×
UNCOV 53	s = None	×
54
UNCOV 55	time = d.index.copy()	×
UNCOV 56	data1 = d.copy()	×
UNCOV 57	if s is not None:	×
58	data2 = s.copy()	×
59	else:
UNCOV 60	data2=None	×
UNCOV 61	data = []	×
UNCOV 62	spec_data = []	×
63
UNCOV 64	if column_range is None:	×
UNCOV 65	column_range = [0, len(d.columns)-1]	×
66
67	#grab column data
UNCOV 68	if len(column_range)==2 and isinstance(column_range[0],int):	×
UNCOV 69	range_start = column_range[0]	×
UNCOV 70	range_end = column_range[1]	×
UNCOV 71	add_col = list(range(range_start,range_end+1))	×
UNCOV 72	datasum = data1[add_col].sum(axis=1)	×
UNCOV 73	data = data + [list(datasum)]	×
74	else:
UNCOV 75	for i in column_range:	×
76	#if not a list
UNCOV 77	if type(i) == int:	×
78	data = data + [list(data1[i])]	×
79	#sum across listed column range
80	else:
UNCOV 81	range_start = i[0]	×
UNCOV 82	range_end = i[1]	×
UNCOV 83	add_col = list(range(range_start,range_end+1))	×
UNCOV 84	datasum = data1[add_col].sum(axis=1)	×
UNCOV 85	data = data + [list(datasum)]	×
86
UNCOV 87	if data2 is not None:	×
88	if len(column_range) == 2 and isinstance(column_range[0], int):	×
89	range_start = column_range[0]	×
90	range_end = column_range[1]	×
91	add_col = list(range(range_start, range_end + 1))	×
92	datasum = data2[add_col].mean(axis=1)	×
93	spec_data = spec_data + [list(datasum)]	×
94	else:
95	for i in column_range:	×
96	# if not a list
97	if type(i) == int:	×
98	spec_data = spec_data + [list(data2[i])]	×
99	# sum across listed column range
100	else:
101	range_start = i[0]	×
102	range_end = i[1]	×
103	add_col = list(range(range_start, range_end + 1))	×
104	datasum = data2[add_col].mean(axis=1)	×
105	spec_data = spec_data + [list(datasum)]	×
106
107	#store added data
UNCOV 108	if s is None:	×
UNCOV 109	store_data(newname,data={'x':time, 'y':np.transpose(data)})	×
110	else:
111	store_data(newname, data={'x': time, 'y':np.transpose(data), 'v': np.transpose(spec_data)})	×
112
113	#pyspedas.tplot_tools.data_quants[newname].attrs = copy.deepcopy(pyspedas.tplot_tools.data_quants[tvar].attrs)
114
UNCOV 115	return	×
116

spedas / pyspedas / 25194239086

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous