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spedas / pyspedas / 25194239086

26 Apr 2026 08:07PM UTC coverage: 61.697% (-28.8%) from 90.54%
25194239086

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github

jameswilburlewis
Added test for loading Cluster CODIF differential energy flux

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
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31.58
/pyspedas/tplot_tools/tplot_math/divide.py
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# Copyright 2020 Regents of the University of Colorado. All Rights Reserved.
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# Released under the MIT license.
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# This software was developed at the University of Colorado's Laboratory for Atmospheric and Space Physics.
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# Verify current version before use at: https://github.com/MAVENSDC/Pytplot
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import pyspedas
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from pyspedas.tplot_tools import store_data, tinterp
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import numpy as np
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import copy
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import logging
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def divide(tvar1,tvar2,newname=None):
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    """
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    Divides two tplot variables.  Will interpolate if the two are not on the same time cadence.
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    Parameters
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    ----------
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        tvar1 : str
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            Name of first tplot variable.
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        tvar2 : int/float
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            Name of second tplot variable
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        newname : str
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            Name of new tvar for divided data.  If not set, then the data in tvar1 is replaced.
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    Returns
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    -------
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        None
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    Examples
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    --------
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        >>> pyspedas.store_data('a', data={'x':[0,4,8,12,16], 'y':[1,2,3,4,5]})
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        >>> pyspedas.store_data('c', data={'x':[0,4,8,12,16,19,21], 'y':[1,4,1,7,1,9,1]})
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        >>> pyspedas.divide('a','c','a_over_c')
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        """
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    # interpolate tvars
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    tv2 = tinterp(tvar1, tvar2)
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    # separate and divide data
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    data1 = pyspedas.tplot_tools.data_quants[tvar1].values
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    data2 = pyspedas.tplot_tools.data_quants[tv2].values
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    data = data1 / data2
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    # store divided data
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    if newname is None:
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        pyspedas.tplot_tools.data_quants[tvar1].values = data
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        return tvar1
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    if 'spec_bins' in pyspedas.tplot_tools.data_quants[tvar1].coords:
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        store_data(newname, data={'x': pyspedas.tplot_tools.data_quants[tvar1].coords['time'].values, 'y': data,
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                                           'v': pyspedas.tplot_tools.data_quants[tvar1].coords['spec_bins'].values})
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        pyspedas.tplot_tools.data_quants[newname].attrs = copy.deepcopy(pyspedas.tplot_tools.data_quants[tvar1].attrs)
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    else:
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       store_data(newname, data={'x':pyspedas.tplot_tools.data_quants[tvar1].coords['time'].values, 'y': data})
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       pyspedas.tplot_tools.data_quants[newname].attrs = copy.deepcopy(pyspedas.tplot_tools.data_quants[tvar1].attrs)
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    return newname
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