rand

randn

return a rank 0 dataset of random numbers of a Gaussian (normal) distribution.

Returns:

randomSeed

restart the random sequence used by randu and randn. Note if there if there are multiple threads using random functions, this becomes unpredictable.

Returns:

randomn

returns a rank 0 dataset of random numbers of a Gaussian (normal) distribution. System.currentTimeMillis() may be used for the seed. Note this is unlike the IDL randomn function because the seed is not modified. (Any long parameter in Jython and Java is read-only.) System.currentTimeMillis() may be used for the seed.

Parameters

Returns:

randomu

returns a rank 0 dataset of random numbers of a uniform distribution. System.currentTimeMillis() may be used for the seed. Note this is unlike the IDL randomn function because the seed is not modified. (Any long parameter in Jython and Java is read-only.)

Parameters

Returns:

randu

returns a rank 0 dataset of random uniform numbers from 0 to 1 but not including 1.

Returns:

rebundle

unbundle the names from the bundle, and rebundle them in the order specified.

Parameters

Returns:

See Also:

reduceBins

reduce each bin to its center. If the spacing is log, then geometric centers are used.

Parameters

Returns:

reduceMax

reduce the dataset's rank by reporting the max of all the elements along a dimension. Only QUBEs are supported presently.

Parameters

Returns:

reduceMean

reduce the dataset's rank by reporting the mean of all the elements along a dimension. Only QUBEs are supported presently. Note this does not contain code that would remove large offsets from zero when making the average, so the number of points is limited.

Parameters

Returns:

reduceMedian

reduce the dataset's rank by reporting the median of all the elements along a dimension. Only QUBEs are supported presently. Note the weights reported are the totals of the data going in to each median, typically the number of measurements compared (when all weights are 0 or 1).

Parameters

Returns:

reduceMin

reduce the dataset's rank by reporting the min of all the elements along a dimension. Only QUBEs are supported presently.

Parameters

Returns:

reduceSum

reduce the dataset's rank by reporting the sum of all the valid elements along a dimension. The property "WEIGHTS" will contain the sum of the weights. Only QUBEs are supported presently. This is like the function "total," but skips invalid values.

Parameters

Returns:

See Also:

reform

Reshape the dataset to remove the first dimension with length 1, reducing its rank by 1. Dependencies are also preserved. If no indices are found, then the dataset is returned.

Parameters

Returns:

removeFill

remove the fill values from the rank 1 dataset, returning a smaller dataset. This was introduced to support the mash-up dialog.

Parameters

Returns:

removeIndeces

remove the data at the indices from the rank 1 dataset. This can be used for example like so:

 
 ds= ripples(20)
 ds= removeIndeces( ds, where( valid(ds).eq(0) ) )
 print ds.length()
 
 

Parameters

Returns:

See Also:

removeValues

put fill data for these indices

Parameters

Returns:

See Also:

removeValuesGreaterThan

remove values in the dataset which are greater than the value. This is a convenient method for the common case where we want to filter data by values within the data, introduced to support the data mash up dialog.

Parameters

Returns:

removeValuesLessThan

remove values in the dataset which are less than the value. This is a convenient method for the common case where we want to filter data by values within the data, introduced to support the data mash up dialog. Note that this inserts fill where data is to be removed.

Parameters

Returns:

replicate

returns rank 1 dataset with value

Parameters

Returns:

rescale

calculate the range of data, then rescale it so that the smallest values becomes min and the largest values becomes max.

Parameters

Returns:

rescaleRange

returns rank 1 QDataSet range relative to range "dr", where 0. is the minimum, and 1. is the maximum. For example rescaleRange(ds,1,2) is scanNext, rescaleRange(ds,0.5,1.5) is zoomOut. This is similar to the DatumRange rescale functions.

Parameters

Returns:

rescaleRangeLogLin

like rescaleRange, but look at log/lin flag.

Parameters

Returns:

See Also:

reverse

returns the reverse of the rank 1 dataset.

Parameters

Returns:

rgbColorDataset

create a dataset of RGB colors. The output is int(red)*256*256 + int(green)*256 + int(blue) with the units of Units.rgbColor

Parameters

Returns:

See Also:

ripples

rank 1 dataset for demos and testing.

Parameters

Returns:

ripplesJoinSpectrogramTimeSeries

return fake position data for testing result is rank 3 bundle [3,len/3,27*]

Parameters

Returns:

See Also:

ripplesPitchAngleDistribution

return an example of a QDataSet containing a pitch angle distribution. This is a rank 2 dataset with angle in radians for DEPEND_0 and radius for DEPEND_1.

Returns:

ripplesSpectrogramTimeSeries

return fake position data for testing result is rank 2 bundle [len,27]

Parameters

Returns:

ripplesTimeSeries

return fake rank 1 data timeseries for testing

Parameters

Returns:

ripplesVectorTimeSeries

return fake position data for testing. result is rank 2 bundle [len,3]

Parameters

Returns:

ripplesWaveformTimeSeries

return fake waveform data for testing result is rank 2 bundle [len,512]

Parameters

Returns:

round

element-wise round function. 0.5 is round up.

Parameters

Returns: