Manipulating KP Data¶
Resample¶
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pydivide.
resample
(kp, time, sc_only=False)[source]¶ Modifies KP structure index to user specified time via interpolation.
Parameters: - kp – struct KP insitu data structure read from file(s).
- time – list Specifies subset of insitu KP data for resampling. time must be expressed in the format ‘YYYY-MM-DD HH:MM:SS’.
Examples
>>> # Resample insitu time to 2016-06-20 coarse survey 3D file time. >>> swi_cdf = cdflib.CDF('<dir_path>/mvn_swi_l2_coarsesvy3d_20160620_v01_r00.cdf') >>> newtime = swi_cdf.varget('time_unix') >>> insitu_resampled = pydivide.resample(insitu, newtime)
>>> # Resamples an entire day of data to just 3 points >>> import pytplot >>>insitu, iuvs = pydivide.read(input_time=['2016-02-18', '2016-02-19']) >>> x = pydivide.resample(insitu, [pytplot.tplot_utilities.str_to_int('2016-02-18T05:00:00'), >>> pytplot.tplot_utilities.str_to_int('2016-02-18T10:00:00'), >>> pytplot.tplot_utilities.str_to_int('2016-02-18T15:00:00')])
Bin¶
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pydivide.
bin
(kp, parameter=None, bin_by=None, mins=None, maxs=None, binsize=None, std=False, avg=False, density=False, median=False, unittest=False)[source]¶ Bins insitu Key Parameters by up to 8 different parameters, specified within the data structure. Necessary that at least one of avg, std, median, or density be specified.
Parameters: - kp – struct KP insitu data structure read from file(s).
- parameter – str Key Parameter to be binned. Only one may be binned at a time.
- bin_by – int, str Parameters (index or name) by which to bin the specified Key Parameter.
- binsize – int, list
- size for each binning dimension. Number of elements must be equal to those in bin_by. (Bin) –
- mins – int, list Minimum value(s) for each binning scheme. Number of elements must be equal to those in bin_by.
- maxs – int, list 7 Maximum value(s) for each binning scheme. Number of elements must be equal to those in bin_by.
- avg – bool Calculate average per bin.
- std – bool Calculate standard deviation per bin.
- density – bool Returns number of items in each bin.
- median – bool Calculate median per bin.
Returns: This procedures outputs up to 4 arrays to user-defined variables, corresponding to avg, std, median, and density.
Examples: >>> # Bin STATIC O+ characteristic energy by spacecraft latitude (1° resolution) and longitude (2° resolution). >>> output_avg = pydivide.bin(insitu, parameter=’static.oplus_char_energy’, bin_by=[‘spacecraft.geo_latitude’, ‘spacecraft.geo_longitude’], avg=True,binsize=[2,1])
>>> # Bin SWIA H+ density by spacecraft altitude (10km resolution), return average value and standard deviation for each bin. >>> output_avg,output_std = pydivide.bin(insitu, parameter='swia.hplus_density', bin_by='spacecraft.altitude', binsize=10,avg=True,std=True)