unbundle
unbundle( QDataSet ds, String name ) → QDataSet
Extract the named bundled dataset. For example, extract B_x from bundle of components.
Parameters
ds - the bundle of datasets, often rank 2 with BUNDLE_1 property
name - the name of the bundled dataset, or "ch_<i>" where i is the dataset number
Returns:
the named dataset
See Also:
unbundle(QDataSet, int)
DataSetOps#bundleNames(QDataSet)
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unbundle( QDataSet ds, int i ) → QDataSet
unbundleBins
unbundleBins( QDataSet ds, int i ) → QDataSet
convenient method for getting the times from an events dataset, this
unbundles the startTimes at i and the stopTimes at i+1 to a bins dataset.
The second column can be durations as well.
Parameters
ds - the bundle.
i - the index, 0 for a canonical events dataset.
Returns:
rank 2 bins dataset.
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uniq
uniq( QDataSet ds ) → QDataSet
Return the unique indices from the rank 1 dataset. If the
set is not monotonic, then return unique indices from the monotonic
portions.
Parameters
ds - rank 1 dataset, sorted, or mostly sorted.
Returns:
the element indices.
See Also:
sort(java.lang.Object)
uniq(QDataSet, QDataSet)
uniqValues(QDataSet, QDataSet)
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uniq( QDataSet ds, QDataSet sort ) → QDataSet
uniqValues
uniqValues( QDataSet ds, QDataSet sort ) → QDataSet
return the unique elements from the dataset. If sort is null, then
the dataset is assumed to be monotonic, and only repeating values are
coalesced. If sort is non-null, then it is the result of the function
"sort" and should be a rank 1 list of indices that sort the data.
renamed uniqValues from uniq to avoid confusion with the IDL command.
This needs example code and should not be used for now. See VirboAutoplot/src/scripts/test/testUniq.jy
Parameters
ds - rank 1 dataset, sorted, or mostly sorted.
sort - null, or the rank 1 dataset of indices
Returns:
the subset of the data which is uniq.
See Also:
uniq uniq, which returns the indices. uniq, which returns the indices.
uniq(QDataSet, QDataSet)
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unwrap
unwrap( QDataSet ds, double discont ) → QDataSet
SciPy's unwrap function, used in demo of hilbertSciPy, which unwraps
a function that exists in a modulo space so that the differences are
minimal.
Parameters
ds - rank 1 dataset, containing values from 0 to discont
discont - the discont, such as PI, TAU, 24, 60, 360, etc.
Returns:
a QDataSet
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