## org.das2.qds.util.BinAverage

utility class providing methods for bin averaging.

## binAverage

binAverage( QDataSet ds, QDataSet newTags0 ) → org.das2.qds.DDataSet

returns a dataset with tags specified by newTags0. Data from `ds` are averaged together when they fall into the same bin. Note the result will have the property WEIGHTS.

### Parameters

ds - a rank 1 dataset, no fill
newTags0 - a rank 1 tags dataset, that must be MONOTONIC.

### Returns:

rank 1 dataset with DEPEND_0 = newTags.

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
binAverage(QDataSet, QDataSet )
binAverage(QDataSet, QDataSet, QDataSet )
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## binAverage

binAverage( QDataSet ds, QDataSet newTags0, QDataSet newTags1 ) → org.das2.qds.DDataSet

returns a dataset with tags specified by newTags.

### Parameters

ds - a rank 2 dataset. If it's a bundle, then rebinBundle is called.
newTags0 - rank 1 monotonic dataset
newTags1 - rank 1 monotonic dataset

### Returns:

rank 2 dataset with newTags0 for the DEPEND_0 tags, newTags1 for the DEPEND_1 tags. WEIGHTS property contains the weights.

### See Also:

rebin(QDataSet, int, int)
rebinBundle(QDataSet, QDataSet, QDataSet)
binAverage(QDataSet, QDataSet)
binAverage(QDataSet )
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## binAverageBundle

binAverageBundle( QDataSet ds, QDataSet dep0, QDataSet dep1, QDataSet dep2 ) → org.das2.qds.DDataSet

takes rank 2 bundle (x,y,z,f) and averages it into rank 3 qube f(x,y,z). This is similar to what happens in the spectrogram routine.

### Parameters

ds - rank 2 bundle(x,y,z,f)
dep0 - the rank 1 depend0 for the result, which must be uniformly spaced.
dep1 - the rank 1 depend1 for the result, which must be uniformly spaced.
dep2 - the rank 1 depend2 for the result, which must be uniformly spaced.

### Returns:

rank 3 dataset of z averages with depend_0, depend_1, and depend_2. WEIGHTS contains the total weight for each bin.

### See Also:

rebinBundle(QDataSet, QDataSet, QDataSet)
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## binAverageBundle

binAverageBundle( QDataSet ds, QDataSet dep0, QDataSet dep1 ) → org.das2.qds.DDataSet

takes rank 2 bundle (x,y,z) and averages it into table z(x,y). This is similar to what happens in the spectrogram routine.

### Parameters

ds - rank 2 bundle(x,y,z)
dep0 - the rank 1 depend0 for the result, which must be uniformly spaced.
dep1 - the rank 1 depend1 for the result, which must be uniformly spaced.

### Returns:

rank 2 dataset of z averages with depend_0 and depend_1. WEIGHTS contains the total weight for each bin.

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
rebinBundle(QDataSet, QDataSet, QDataSet, QDataSet)
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## binMeanAverageDeviation

binMeanAverageDeviation( QDataSet ads, QDataSet ds ) → org.das2.qds.DDataSet

takes rank 2 bundle (x,y,z) and averages in table z(x,y) and computes the mean average deviation in each bin.

### Parameters

ads - rank 2 grid of averages
ds - rank 2 bundle(x,y,z)

### Returns:

rank 2 dataset of z averages with depend_0 and depend_1. WEIGHTS contains the total weight for each bin.

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
rebinBundle(QDataSet, QDataSet, QDataSet, QDataSet)
Ops#meanAverageDeviation(QDataSet)
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## boxcar

boxcar( QDataSet ds, int size ) → org.das2.qds.DDataSet

run boxcar average over the dataset, returning a dataset of same geometry. Points near the edge are simply copied from the source dataset. The result dataset contains a property "weights" that is the weights for each point.

### Parameters

ds - a rank 1 dataset of size N
size - the number of adjacent bins to average

### Returns:

rank 1 dataset of size N
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## rebin

rebin( QDataSet ds, QDataSet newTags0 ) → org.das2.qds.DDataSet

returns a dataset with tags specified by newTags0. Data from `ds` are averaged together when they fall into the same bin. Note the result will have the property WEIGHTS.

### Parameters

ds - a rank 1 dataset, no fill
newTags0 - a rank 1 tags dataset, that must be MONOTONIC.

### Returns:

rank 1 dataset with DEPEND_0 = newTags.

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
binAverage(QDataSet, QDataSet )
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## rebin

Deprecated: see binAverage

## rebin

rebin( QDataSet ds, int n0 ) → QDataSet

reduce the rank 1 dataset by averaging blocks of bins together

### Parameters

ds - rank 1 dataset with N points
n0 - number of bins in the result.

### Returns:

rank 1 dataset with n0 points. Weights plane added.

### See Also:

rebin(QDataSet, int, int)
rebin(QDataSet, int, int, int)
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## rebin

rebin( QDataSet ds, int n0, int n1 ) → QDataSet

reduce the rank 2 dataset by averaging blocks of bins together. depend datasets reduced as well.

### Parameters

ds - rank 2 dataset with M by N points
n0 - the number of bins in the result. Note this changed in v2013a_6 from earlier versions of this routine.
n1 - the number of bins in the result.

### Returns:

rank 2 dataset with n0 by n1 points, with a weights plane.

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
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## rebin

rebin( QDataSet ds, int n0, int n1, int n2 ) → QDataSet

reduce the rank 3 dataset by averaging blocks of bins together. depend datasets reduced as well.

### Parameters

ds - rank 3 dataset
n0 - the number of bins in the result.
n1 - the number of bins in the result.
n2 - the number of bins in the result.

### Returns:

rank 3 dataset ds[n0,n1,n2]

### See Also:

rebin(QDataSet, QDataSet, QDataSet)
rebin(QDataSet, int)
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## rebinBundle

Deprecated: see binAverageBundle

## rebinBundle

Deprecated: see binAverageBundle

## residuals

residuals( QDataSet ds, int boxcarSize ) → QDataSet

returns number of stddev from adjacent data.

### Parameters

ds - a QDataSet
boxcarSize - an int

### Returns:

QDataSet
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