## hanning

hanning( QDataSet ds, int len ) → QDataSet

Apply Hanning (Hann) windows to the data to prepare for FFT. The data is reformed into a rank 2 dataset [N,len]. Hanning windows taper the ends of the interval to remove noise caused by the discontinuity. This is deprecated, and windowFunction should be used.

### Parameters

ds - a QDataSet
len - an int

### Returns:

data[N,len] with the hanning window applied.

### See Also:

windowFunction(org.das2.qds.ops.Ops.FFTFilterType, int)
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## hashcodes

hashcodes( QDataSet ds ) → QDataSet

return a rank 1 hashcodes of each record the dataset, with one hashcodes value for each record. The value of hashcodes should repeat if the record repeats. For a rank 1 dataset, the values are returned. NOTE: This is under-implemented and should not be used without understanding the code.

### Parameters

ds - dataset with rank greater than 0.

### Returns:

rank 1 dataset.
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## hilbert

hilbert( QDataSet ds ) → QDataSet

Perform the Hilbert function on the rank 1 dataset, similar to the hilbert function in IDL and Matlab.

### Parameters

ds - rank 1 dataset of length n.

### Returns:

ds[n,2], complex array

### See Also:

hilbert(QDataSet)
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## hilbertSciPy

hilbertSciPy( QDataSet ds ) → QDataSet

Perform the Hilbert function on the rank 1 dataset, similar to the scipy.signal.hilbert function in SciPy. The result is form differently than hilbert.

### Parameters

ds - rank 1 dataset of length n.

### Returns:

ds[n,2], complex array

### See Also:

hilbert(QDataSet)
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## histogram

histogram( QDataSet ds, double min, double max, double binSize ) → QDataSet

returns a rank 1 dataset that is a histogram of the data. Note there will also be in the properties: count, the total number of valid values. nonZeroMin, the smallest non-zero, positive number

### Parameters

ds - rank N dataset
min - the min of the first bin. If min=-1 and max=-1, then automatically set the min and max.
max - the max of the last bin.
binSize - the size of each bin.

### Returns:

a rank 1 dataset with each bin's count. DEPEND_0 indicates the bin locations.
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## histogram

histogram( QDataSet ds, Datum min, Datum max, Datum binsize ) → QDataSet

returns a rank 1 dataset that is a histogram of the data. Note there will also be in the properties: count, the total number of valid values. nonZeroMin, the smallest non-zero, positive number

### Parameters

ds - rank N dataset
min - the center of the first bin. If min=-1 and max=-1, then automatically set the min and max.
max - the center of the last bin.
binsize - the size of each bin.

### Returns:

a rank 1 dataset with each bin's count. DEPEND_0 indicates the bin locations.
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## histogram

histogram( QDataSet ds, String min, String max, String binsize ) → QDataSet

returns rank 1 dataset that is a histogram of the data. This will use the units of ds to interpret min, max, and binsize.

### Parameters

ds - rank N dataset
min - the center of the first bin. If min=-1 and max=-1, then automatically set the min and max.
max - the center of the last bin.
binsize - the size of each bin.

### Returns:

a QDataSet
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## histogram

histogram( QDataSet ds, int binCount ) → QDataSet

returns a histogram of the dataset, based on the extent and scaletype of the data.

### Parameters

ds - a QDataSet
binCount - number of bins

### Returns:

a QDataSet
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## histogram2d

histogram2d( QDataSet x, QDataSet y, int[] bins, QDataSet xrange, QDataSet yrange ) → QDataSet

make a 2-D histogram of the data in x and y. For example

>     x= randn(10000)+1
>     y= randn(10000)+4
>     zz= histogram2d( x,y, [30,30], dataset([0,8]), dataset([-2,6]) )
>     plot( zz )

The result will be a rank 2 dataset with DEPEND_0 and DEPEND_1 indicating the bin locations. If the xrange or yrange is dimensionless, then use the units of x or y.

### Parameters

x - the x values
y - the y values
bins - number of bins in x and y
xrange - a rank 1 2-element bounds dataset, so that Units can be specified.
yrange - a rank 1 2-element bounds dataset, so that Units can be specified.

### Returns:

a rank 2 dataset

### See Also:

histogram(QDataSet, double, double, double)
org.das2.qds.util.Reduction#histogram2D(QDataSet, QDataSet, QDataSet)
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