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

78.57

/pyspedas/tplot_tools/tplot_math/split_vec.py

"""
Splits up 2D data into many 1D tplot variables.

Notes
-----
Similar to split_vec.pro in IDL SPEDAS.

"""

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

def split_vec(
        tvar,
        polar=False,
        newname=None,
        new_name=None,
        columns='all',
        suffix=None
):
    """
    Splits up 2D data into many 1D tplot variables. Takes a stored tplot vector like Vp
    and stores tplot variables Vp_x, Vp_y, Vp_z

    Parameters
    ----------
        tvar : str
            Name of tplot variable to split up
        polar : bool, optional
            If True, the input data is in polar coordinates.
            Suffix will be set to ['_mag', '_th', '_phi'].
            Default: False
        new_name : int/list, optional (Deprecated)
            The names of the new tplot variables.
            This must be the same length as the number of variables created.
        newname : int/list, optional
            The names of the new tplot variables.
            This must be the same length as the number of variables created.
            Default: None
        columns : list of ints, optional
            The specific column numbers to grab from the data.
            Default: 'all' (splits all columns)
        suffix: str
            Suffix str to be added to end of tplot variable name
            Default: None

    Returns
    -------
    list[str]
        List of variables created

    Examples
    --------
        >>> 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.split_vec('b')



    """
    # new_name is deprecated in favor of newname
    if new_name is not None:
        logging.info("split_vec: The new_name parameter is deprecated. Please use newname instead.")
        newname = new_name

    # Make sure the tvar is found
    if tvar not in pyspedas.tplot_tools.data_quants:
        logging.error(f"Error: {tvar} not found in memory.")
        return None

    # Give a default to the new name
    if newname is None:
        newname = tvar

    # Gather data from the tvar
    alldata = get_data(tvar)
    time = alldata[0]
    data = alldata[1]
    dim = data.shape
    metadata = get_data(tvar, metadata=True)

    has_v = False
    combined_v = None
    time_varying_v = False

    # If already size one, simply return
    if len(dim) == 1:
        return [tvar]
    # Is there depend_1 data to split?
    elif len(dim) == 2:
        if len(alldata) == 3:
            has_v = True
            combined_v = alldata[2]
            if len(combined_v.shape) == 1:
                time_varying_v = False
            else:
                time_varying_v = True

    elif len(dim) > 2:
        logging.error(f"split_vec:data array for {tvar} has {len(dim)} dimensions, too many to split")
        return None


    vec_length = dim[1]

    # Determine what the suffix list will be
    if suffix is not None:
        if vec_length > len(suffix):
            logging.error(f"split_vec error: number of columns ({vec_length}) is greater than the number of suffix entered")
    else:
        if vec_length == 3:
            if polar:
                suffix = ['_mag', '_th', '_phi']
            else:
                suffix = ["_x", "_y", "_z"]
        else:
            suffix = []
            for i in range(vec_length):
                suffix.append("_"+str(i))

    created_variables = []

    # grab column data
    if columns == 'all':
        columns = range(vec_length)

    v_idx = 0
    for i in columns:
        # if not a list
        if isinstance(i, list):
            range_start = i[0]
            range_end = i[1]
        else:
            range_start = i
            range_end = i
        split_col = list(range(range_start, range_end+1))
        split_name = newname + suffix[i]
        created_variables = created_variables + [split_name]

        if has_v and time_varying_v:
            data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze(), 'v': combined_v[:,v_idx]}
        elif has_v and not time_varying_v:
            data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze(), 'v': np.array([combined_v[v_idx]])}
        else:
            data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze()}

        plot_options = metadata.get('plot_options', {})
        yaxis_opt = plot_options.get('yaxis_opt', {})
        labels = yaxis_opt.get('legend_names', None)
        if labels is None:
            cdf = metadata.get('CDF', {})
            labels = cdf.get('LABELS', None)

        if labels is None:
            attrs = metadata
        else:
            # Make a deep copy to avoid modifying original metadata
            attrs = copy.deepcopy(metadata)
            if 'plot_options' not in attrs:
                attrs['plot_options'] = {}
            if 'yaxis_opt' not in attrs['plot_options']:
                attrs['plot_options']['yaxis_opt'] = {}
            attrs['plot_options']['yaxis_opt']['legend_names'] = []

            if v_idx < len(labels):
                attrs['plot_options']['yaxis_opt']['legend_names'].append(labels[v_idx])

        if not store_data(split_name, data=data_for_tplot, attr_dict=attrs):
            raise Exception(f"Failed to store {split_name} in pyspedas.")
        v_idx += 1

    return created_variables

1	"""
2	Splits up 2D data into many 1D tplot variables.
3
4	Notes
5	-----
6	Similar to split_vec.pro in IDL SPEDAS.
7
8	"""
9
10	import copy	3✔
11	import logging	3✔
12	import pyspedas	3✔
13	from pyspedas.tplot_tools import store_data, get_data	3✔
14	import numpy as np	3✔
15	import logging	3✔
16
17	def split_vec(	3✔
18	tvar,
19	polar=False,
20	newname=None,
21	new_name=None,
22	columns='all',
23	suffix=None
24	):
25	"""
26	Splits up 2D data into many 1D tplot variables. Takes a stored tplot vector like Vp
27	and stores tplot variables Vp_x, Vp_y, Vp_z
28
29	Parameters
30	----------
31	tvar : str
32	Name of tplot variable to split up
33	polar : bool, optional
34	If True, the input data is in polar coordinates.
35	Suffix will be set to ['_mag', '_th', '_phi'].
36	Default: False
37	new_name : int/list, optional (Deprecated)
38	The names of the new tplot variables.
39	This must be the same length as the number of variables created.
40	newname : int/list, optional
41	The names of the new tplot variables.
42	This must be the same length as the number of variables created.
43	Default: None
44	columns : list of ints, optional
45	The specific column numbers to grab from the data.
46	Default: 'all' (splits all columns)
47	suffix: str
48	Suffix str to be added to end of tplot variable name
49	Default: None
50
51	Returns
52	-------
53	list[str]
54	List of variables created
55
56	Examples
57	--------
58	>>> 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]]})
59	>>> pyspedas.split_vec('b')
60
61
62
63	"""
64	# new_name is deprecated in favor of newname
UNCOV 65	if new_name is not None:	2✔
66	logging.info("split_vec: The new_name parameter is deprecated. Please use newname instead.")	×
67	newname = new_name	×
68
69	# Make sure the tvar is found
UNCOV 70	if tvar not in pyspedas.tplot_tools.data_quants:	2✔
71	logging.error(f"Error: {tvar} not found in memory.")	×
72	return None	×
73
74	# Give a default to the new name
UNCOV 75	if newname is None:	2✔
UNCOV 76	newname = tvar	2✔
77
78	# Gather data from the tvar
UNCOV 79	alldata = get_data(tvar)	2✔
UNCOV 80	time = alldata[0]	2✔
UNCOV 81	data = alldata[1]	2✔
UNCOV 82	dim = data.shape	2✔
UNCOV 83	metadata = get_data(tvar, metadata=True)	2✔
84
UNCOV 85	has_v = False	2✔
UNCOV 86	combined_v = None	2✔
UNCOV 87	time_varying_v = False	2✔
88
89	# If already size one, simply return
UNCOV 90	if len(dim) == 1:	2✔
UNCOV 91	return [tvar]	1✔
92	# Is there depend_1 data to split?
UNCOV 93	elif len(dim) == 2:	2✔
UNCOV 94	if len(alldata) == 3:	2✔
UNCOV 95	has_v = True	1✔
UNCOV 96	combined_v = alldata[2]	1✔
UNCOV 97	if len(combined_v.shape) == 1:	1✔
UNCOV 98	time_varying_v = False	1✔
99	else:
UNCOV 100	time_varying_v = True	1✔
101
102	elif len(dim) > 2:	×
103	logging.error(f"split_vec:data array for {tvar} has {len(dim)} dimensions, too many to split")	×
104	return None	×
105
106
UNCOV 107	vec_length = dim[1]	2✔
108
109	# Determine what the suffix list will be
UNCOV 110	if suffix is not None:	2✔
111	if vec_length > len(suffix):	×
112	logging.error(f"split_vec error: number of columns ({vec_length}) is greater than the number of suffix entered")	×
113	else:
UNCOV 114	if vec_length == 3:	2✔
UNCOV 115	if polar:	2✔
116	suffix = ['_mag', '_th', '_phi']	×
117	else:
UNCOV 118	suffix = ["_x", "_y", "_z"]	2✔
119	else:
120	suffix = []	×
121	for i in range(vec_length):	×
122	suffix.append("_"+str(i))	×
123
UNCOV 124	created_variables = []	2✔
125
126	# grab column data
UNCOV 127	if columns == 'all':	2✔
UNCOV 128	columns = range(vec_length)	2✔
129
UNCOV 130	v_idx = 0	2✔
UNCOV 131	for i in columns:	2✔
132	# if not a list
UNCOV 133	if isinstance(i, list):	2✔
134	range_start = i[0]	×
135	range_end = i[1]	×
136	else:
UNCOV 137	range_start = i	2✔
UNCOV 138	range_end = i	2✔
UNCOV 139	split_col = list(range(range_start, range_end+1))	2✔
UNCOV 140	split_name = newname + suffix[i]	2✔
UNCOV 141	created_variables = created_variables + [split_name]	2✔
142
UNCOV 143	if has_v and time_varying_v:	2✔
UNCOV 144	data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze(), 'v': combined_v[:,v_idx]}	1✔
UNCOV 145	elif has_v and not time_varying_v:	2✔
UNCOV 146	data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze(), 'v': np.array([combined_v[v_idx]])}	1✔
147	else:
UNCOV 148	data_for_tplot = {'x': time, 'y': data[:, split_col].squeeze()}	1✔
149
UNCOV 150	plot_options = metadata.get('plot_options', {})	2✔
UNCOV 151	yaxis_opt = plot_options.get('yaxis_opt', {})	2✔
UNCOV 152	labels = yaxis_opt.get('legend_names', None)	2✔
UNCOV 153	if labels is None:	2✔
UNCOV 154	cdf = metadata.get('CDF', {})	1✔
UNCOV 155	labels = cdf.get('LABELS', None)	1✔
156
UNCOV 157	if labels is None:	2✔
UNCOV 158	attrs = metadata	1✔
159	else:
160	# Make a deep copy to avoid modifying original metadata
UNCOV 161	attrs = copy.deepcopy(metadata)	1✔
UNCOV 162	if 'plot_options' not in attrs:	1✔
163	attrs['plot_options'] = {}	×
UNCOV 164	if 'yaxis_opt' not in attrs['plot_options']:	1✔
165	attrs['plot_options']['yaxis_opt'] = {}	×
UNCOV 166	attrs['plot_options']['yaxis_opt']['legend_names'] = []	1✔
167
UNCOV 168	if v_idx < len(labels):	1✔
UNCOV 169	attrs['plot_options']['yaxis_opt']['legend_names'].append(labels[v_idx])	1✔
170
UNCOV 171	if not store_data(split_name, data=data_for_tplot, attr_dict=attrs):	2✔
172	raise Exception(f"Failed to store {split_name} in pyspedas.")	×
UNCOV 173	v_idx += 1	2✔
174
UNCOV 175	return created_variables	2✔

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