Schemes

java.lang.Object
- org.das2.qds.examples.Schemes

```
public class Schemes
extends java.lang.Object
```
For the various QDataSet schemes, show examples and documentation for each. This was motivated when trying to describe the output of org.das2.graph.ContoursRenderer.doAutorange() Note all QDataSets are "duck-typed," meaning if they happen to meet the requirements of an interface then they are an instance of the interface. All schemes can be executed using reflection, looking for methods starting with "is". This Jython code scans through the class looking for all the methods which make a dataset:
```
 mm= dir( Schemes )
 i=0
 for m in mm:
 if ( m[0:2]=='is' ):
     continue
 else:
     i=i+1
 
```
See Also:

https://github.com/autoplot/dev/blob/master/bugs/2022/20220125/showAllRanks.md

Constructor Summary

Constructors
Constructor and Description

Schemes()

Constructors
Constructor and Description
`Schemes()`

Method Summary

All Methods Static Methods Concrete Methods
Modifier and Type	Method and Description
`static QDataSet`	`angleDistribution()` return example angle distribution.
`static QDataSet`	`angleDistribution(int i)` return example angle distribution.
`static QDataSet`	`arrayOfBoundingBox()` array of bounding boxes, joined by the zeroth dimension.
`static QDataSet`	`boundingBox()` return a bounding box for the data.
`static QDataSet`	`bundleDataSet()` return an example bundle dataset that bundles timetags, a rank 1 dataset and a rank 1 dataset.
`static QDataSet`	`bundleDescriptor()` return data that describes the columns of another dataset.
`static QDataSet`	`complexBundleDataSet()` return bundle with Time, Density, Speed, and Flux, to demonstrate a bundle of datasets with differing rank.
`static QDataSet`	`complexBundleDataSet2()` A complexBundleDataSet is a set of datasets which have different rank.
`static QDataSet`	`complexCoordinateSystemDepend()` returns the QDataSet used to identify the columns of a complex coordinate frame.
`static QDataSet`	`compositeImage()` return an example of a compositeImage.
`static QDataSet`	`eventsList()` return example events list.
`static QDataSet`	`irregularJoin()` return a rank 3 irregular join of three datasets, the first is 13 records of 27 energies, the second is 13 records of 20 energies, and the third is 14 records of 24 energies.
`static boolean`	`isAngleDistribution(QDataSet ds)` return true if the data is an angle distribution.
`static boolean`	`isArrayOfBoundingBox(QDataSet ds)` return true if the data is a rank 3 array of bounding boxes.
`static boolean`	`isBoundingBox(QDataSet ds)` return true if the data is a boundingBox.
`static boolean`	`isBundleDataSet(QDataSet ds)` return true if the data is a bundle dataset
`static boolean`	`isBundleDescriptor(QDataSet bds)` return true if the data describes the columns of another dataset.
`static boolean`	`isComplexCoordinateSystemDepend(QDataSet dep)` return true if the data is length 2, rank 1, and has "ComplexNumber" as the COORDINATE_FRAME.
`static boolean`	`isComplexNumbers(QDataSet ds1)` return true if the data represents an array of complex numbers, containing the property COORDINATE_FRAME on the last DEPEND, which is equal to "ComplexNumber"
`static boolean`	`isCompositeImage(QDataSet ds)` return true if the dataset is a composite image, and is plottable with the RGBImageRenderer
`static boolean`	`isEventsList(QDataSet ds)` return true if the data is an events list.
`static boolean`	`isIrregularJoin(QDataSet ds)` return true if the data is a join of datasets of different cadences or lengths.
`static boolean`	`isLegacyXYZScatter(QDataSet zds)` Many of Autoplot's codes use the "legacyXYZScatter" QDataSet scheme, where the X tags are in DEPEND_0, the Y tags are the QDataSet, and PLANE_0 contains the Z values.
`static boolean`	`isPolyMesh(QDataSet ds)` return true if the data can be used as a triangulation or tessalation of 4-point rectangles.
`static boolean`	`isRank1AlongTrajectory(QDataSet ds)` return true if the data is rank 1 along a trajectory
`static boolean`	`isRank1AtXYScatter(QDataSet ds)` is a Z that is a function of X and Y of a xyScatter.
`static boolean`	`isRank2Bins(QDataSet dep)` return true if the data is a rank 2 list of M bins.
`static boolean`	`isRank2Waveform(QDataSet ds)` return true if the data is a rank 2 waveform.
`static boolean`	`isRank2WaveformRank2Offsets(QDataSet ds)` return true if the data is a rank 2 waveform with rank 2 offsets.
`static boolean`	`isRank3Waveform(QDataSet ds)` return true if the data is a rank 3 join of rank 2 waveforms.
`static boolean`	`isScalarSeriesWithErrors(QDataSet ds)` return true is the data is a simple series of scalars with errors.
`static boolean`	`isScalarTimeSeries(QDataSet ds)` return true if the data is a simple time series of scalars.
`static boolean`	`isSimpleSpectrogram(QDataSet ds)` return true if the data is a simple spectrogram, which is rank 2, and not a small bundle.
`static boolean`	`isSimpleSpectrogramTimeSeries(QDataSet ds)` return true if the data is a simple spectrogram.
`static boolean`	`isTimeSeries(QDataSet ds)` returns true if the dataset is a time series.
`static boolean`	`isTrajectory(QDataSet ds)` return true is the data is a trajectory
`static boolean`	`isUniformCadence(QDataSet ds)` return true of the data has a uniform cadence.
`static boolean`	`isUniformRatiometricCadence(QDataSet ds)` return true of the data has a uniform cadence in log space.
`static boolean`	`isVectorTimeSeries(QDataSet ds)` return true if the data is a vector time series.
`static boolean`	`isXYScatter(QDataSet ds)` is a xyScatter data set.
`static boolean`	`isXYZScatter(QDataSet zds)`
`static QDataSet`	`legacyXYZScatter()` Many code use this form of data to represent Z(X,Y).
`static QDataSet`	`polyMesh()` set of 2-d or 3-d points and the triangles connecting them.
`static QDataSet`	`rank1AlongTrajectory()` return a rank 1 dataset that depends on a trajectory through a space, which is not supported currently.
`static QDataSet`	`rank1AtXYScatter()` Here there is a Z that is a function of X and Y of a xyScatter.
`static QDataSet`	`rank2Bins()` return a rank 2 dataset that is a list of bins.
`static QDataSet`	`rank2ComplexNumbers()` return a complex rank 2 dataset, N by 2, which can be thought of as a 1-D array of N complex numbers
`static QDataSet`	`rank2Waveform()` return a rank 2 waveform, where the waveform is stored in packets.
`static QDataSet`	`rank2WaveformRank2Offsets()` return a rank 2 waveform, but DEPEND_1 which contains the offsets is also rank 2.
`static QDataSet`	`rank3Waveform()` return a join of rank 2 waveforms, also called a rank 3 waveform.
`static QDataSet`	`scalarSeriesWithErrors()` return a rank 1 scalar series with errors.
`static QDataSet`	`scalarTimeSeries()` return a rank 1 scalar time series.
`static QDataSet`	`simpleSpectrogram()` return a rank 2 simple spectrogram, which has two indeces.
`static QDataSet`	`simpleSpectrogramTimeSeries()` return a rank 2 simple spectrogram, which has two indeces and is a TimeSeries.
`static QDataSet`	`trajectory()` return a trajectory through a space
`static QDataSet`	`uniformCadence()` uniform cadence is when each tag is the same distance apart, within a reasonable threshold.
`static QDataSet`	`uniformRatiometricCadence()` uniform ratiometric cadence is when the tags are uniform in log space.
`static QDataSet`	`vectorTimeSeries()` return a rank 2 vectorTimeSeries, which is a bundle of m rank 1 measurements.
`static QDataSet`	`xyScatter()` "scatter" is meant to indicate there is no connection between successive points, and that there is no dependence indicates no clean relation between the bundled datasets.
`static QDataSet`	`xyzScatter()` This will be the preferred way to represent X,Y → Z.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - Schemes
```
public Schemes()
```
- Method Detail
  - boundingBox
```
public static QDataSet boundingBox()
```
    return a bounding box for the data. This is a rank 2 dataset where ds[0,:] shows the bounds for the first dimension and ds[1,:] shows the bounds for the second dimension. Therefor ds[0,0] is the minumum extent of the first dimension, and ds[0,1] is the maximum. Note this can be extended to any number of dimensions (cube or hypercube). Note,
    from org.das2.qds.examples import Schemes ds= Schemes.boundingBox() print asDatumRange(ds.slice(0))
    Returns:
    
    a bounding box for the data.
    
    See Also:
    
    DataSetUtil.asDatumRange(org.das2.qds.QDataSet), arrayOfBoundingBox()
  - isBoundingBox
```
public static boolean isBoundingBox(QDataSet ds)
```
    return true if the data is a boundingBox. A bounding box is rank 2 and has length 2. ds[0,:] is typically the horizontal direction, and ds[1,:] is the vertical.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the dataset is a bounding box.
  - arrayOfBoundingBox
```
public static QDataSet arrayOfBoundingBox()
```
    array of bounding boxes, joined by the zeroth dimension.
    
    Returns:
    
    array of bounding boxes
    
    See Also:
    
    boundingBox()
  - isArrayOfBoundingBox
```
public static boolean isArrayOfBoundingBox(QDataSet ds)
```
    return true if the data is a rank 3 array of bounding boxes. Presently only 2-D bounding boxes are allowed. The zeroth dimension is the number of boxes, and each slice is a bounding box.
    
    Parameters:
    
    ds -
    
    Returns:
    
    true if the data is a rank 3 array of bounding boxes.
  - rank2Waveform
```
public static QDataSet rank2Waveform()
```
    return a rank 2 waveform, where the waveform is stored in packets. DEPEND_0 is the time for each packet, and DEPEND_1 is the difference in time for each measurement to the packet time. Note the additional requirement that the offsets be uniform, e.g.:
    from org.das2.qds.examples import Schemes ds= Schemes.rank2Waveform() deltaT= ds.property( QDataSet.DEPEND_1 ) ddeltaT= diffs(dep1) print ddeltaT[0], ddeltT[-1] # should be the same
    Returns:
    
    rank 2 waveform.
  - isRank2Waveform
```
public static boolean isRank2Waveform(QDataSet ds)
```
    return true if the data is a rank 2 waveform.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a rank 2 waveform.
  - rank3Waveform
```
public static QDataSet rank3Waveform()
```
    return a join of rank 2 waveforms, also called a rank 3 waveform.
    
    Returns:
    
    rank 3 waveform
  - isRank3Waveform
```
public static boolean isRank3Waveform(QDataSet ds)
```
    return true if the data is a rank 3 join of rank 2 waveforms.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a rank 3 waveform.
  - rank2WaveformRank2Offsets
```
public static QDataSet rank2WaveformRank2Offsets()
```
    return a rank 2 waveform, but DEPEND_1 which contains the offsets is also rank 2. This was introduced to support study where short waveform-like structures were identified.
    
    Returns:
    
    a rank 2 waveform, but with rank 2 time-varying DEPEND_1 offsets.
  - isRank2WaveformRank2Offsets
```
public static boolean isRank2WaveformRank2Offsets(QDataSet ds)
```
    return true if the data is a rank 2 waveform with rank 2 offsets.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a rank 2 waveform.
  - vectorTimeSeries
```
public static QDataSet vectorTimeSeries()
```
    return a rank 2 vectorTimeSeries, which is a bundle of m rank 1 measurements. This tacitly asserts orthogonality, but the bundled data should at least all be rank 1 and in the same units.
    from org.das2.qds.examples import Schemes ds= Schemes.vectorTimeSeries() plot( magnitude( ds ) ) plot( unbundle( ds, 0 ) )
    dataset→rank2bundle→vectorTimeSeries.
    Returns:
    
    rank 2 vector time series.
  - isVectorTimeSeries
```
public static boolean isVectorTimeSeries(QDataSet ds)
```
    return true if the data is a vector time series.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a vector time series.
  - simpleSpectrogram
```
public static QDataSet simpleSpectrogram()
```
    return a rank 2 simple spectrogram, which has two indeces.
    
    Returns:
    
    rank 2 simple spectrogram
  - isSimpleSpectrogram
```
public static boolean isSimpleSpectrogram(QDataSet ds)
```
    return true if the data is a simple spectrogram, which is rank 2, and not a small bundle.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a simple spectrogram.
  - scalarTimeSeries
```
public static QDataSet scalarTimeSeries()
```
    return a rank 1 scalar time series.
    
    Returns:
    
    a rank 1 scalar time series.
  - isScalarTimeSeries
```
public static boolean isScalarTimeSeries(QDataSet ds)
```
    return true if the data is a simple time series of scalars.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a simple spectrogram.
  - scalarSeriesWithErrors
```
public static QDataSet scalarSeriesWithErrors()
```
    return a rank 1 scalar series with errors.
    
    Returns:
    
    a rank 1 scalar series with errors.
  - isScalarSeriesWithErrors
```
public static boolean isScalarSeriesWithErrors(QDataSet ds)
```
    return true is the data is a simple series of scalars with errors.
    
    Parameters:
    
    ds - dataset
    
    Returns:
    
    true is the data is a simple series of scalars with errors.
  - simpleSpectrogramTimeSeries
```
public static QDataSet simpleSpectrogramTimeSeries()
```
    return a rank 2 simple spectrogram, which has two indeces and is a TimeSeries.
    
    Returns:
    
    simple spectrogram time series
  - isSimpleSpectrogramTimeSeries
```
public static boolean isSimpleSpectrogramTimeSeries(QDataSet ds)
```
    return true if the data is a simple spectrogram.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a simple spectrogram.
  - isTimeSeries
```
public static boolean isTimeSeries(QDataSet ds)
```
    returns true if the dataset is a time series. This is either something that has DEPEND_0 as a dataset with time location units, or a join of other datasets that are time series.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the dataset is a time series.
    
    See Also:
    
    SemanticOps.isTimeSeries(org.das2.qds.QDataSet)
  - uniformCadence
```
public static QDataSet uniformCadence()
```
    uniform cadence is when each tag is the same distance apart, within a reasonable threshold.
    
    Returns:
    
    dataset with uniform cadence
  - isUniformCadence
```
public static boolean isUniformCadence(QDataSet ds)
```
    return true of the data has a uniform cadence. Note that the CADENCE property is ignored.
    
    Parameters:
    
    ds - a rank 1 dataset
    
    Returns:
    
    true if the data has uniform cadence.
  - uniformRatiometricCadence
```
public static QDataSet uniformRatiometricCadence()
```
    uniform ratiometric cadence is when the tags are uniform in log space.
    
    Returns:
    
    dataset with uniform ratiometric cadence.
  - isUniformRatiometricCadence
```
public static boolean isUniformRatiometricCadence(QDataSet ds)
```
    return true of the data has a uniform cadence in log space. Note that the CADENCE property is ignored.
    
    Parameters:
    
    ds - a rank 1 dataset
    
    Returns:
    
    true if the data has uniform cadence.
  - compositeImage
```
public static QDataSet compositeImage()
```
    return an example of a compositeImage.
    
    Returns:
    
    image[320,240,3]
  - isCompositeImage
```
public static boolean isCompositeImage(QDataSet ds)
```
    return true if the dataset is a composite image, and is plottable with the RGBImageRenderer
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the dataset is a composite image.
  - eventsList
```
public static QDataSet eventsList()
```
    return example events list. This is a four-column rank 2 dataset with start time, end time, RGB color, and ordinal data for the message.
    
    Returns:
    
    example events list.
  - isEventsList
```
public static boolean isEventsList(QDataSet ds)
```
    return true if the data is an events list.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is an events list.
  - angleDistribution
```
public static QDataSet angleDistribution()
```
    return example angle distribution.
    
    Returns:
    
    example angle distribution.
  - angleDistribution
```
public static QDataSet angleDistribution(int i)
```
    return example angle distribution.
    
    Parameters:
    
    i - the example number. 0..n-1.
    
    Returns:
    
    example angle distribution.
  - isAngleDistribution
```
public static boolean isAngleDistribution(QDataSet ds)
```
    return true if the data is an angle distribution.
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is an angle distribution.
  - complexBundleDataSet2
```
public static QDataSet complexBundleDataSet2()
```
    A complexBundleDataSet is a set of datasets which have different rank. The rank 2 datasets take multiple columns of the dataset, and rank 3 and 4 datasets are unrolled to make them rank 2 and the property ELEMENT_DIMENSIONS is used to re-form them. This returns an example bundle dataset that bundles timetags, density, velocity, and flux. Yes, this was coded this twice, not realizing it was already done. This code is probably easier to read, so it is left in.
    
    Returns:
    
    an example bundle dataset
    
    See Also:
    
    complexBundleDataSet()
  - bundleDataSet
```
public static QDataSet bundleDataSet()
```
    return an example bundle dataset that bundles timetags, a rank 1 dataset and a rank 1 dataset.
    
    Returns:
    
    an example bundle dataset
    
    See Also:
    
    which has differing rank.
  - isBundleDataSet
```
public static boolean isBundleDataSet(QDataSet ds)
```
    return true if the data is a bundle dataset
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a bundle dataset
  - isBundleDescriptor
```
public static boolean isBundleDescriptor(QDataSet bds)
```
    return true if the data describes the columns of another dataset.
    
    Parameters:
    
    bds -
    
    Returns:
  - bundleDescriptor
```
public static QDataSet bundleDescriptor()
```
    return data that describes the columns of another dataset. Note these are typically not found in APIs. The bundle descriptor will be
    - rank 2,
    - length() gives the number of columns.
    - length(i) gives the number of indices of the ith column, or the ith column's rank.
    - property(i,NAME) gives the name of the column
    - property(i,START_INDEX) gives the column which is the first column of the rank 2 or higher bundled data set.
    - property(i,xxx) gives property xxx of the column
    - property(i,DEPEND0_NAME) gives the name of the column containing the depend 0 values.
    Returns:
    
    data that describes the columns of another dataset.
  - rank2ComplexNumbers
```
public static QDataSet rank2ComplexNumbers()
```
    return a complex rank 2 dataset, N by 2, which can be thought of as a 1-D array of N complex numbers
    
    Returns:
    
    a complex rank 2 dataset ds[N,2]
    
    See Also:
    
    isComplexNumbers(org.das2.qds.QDataSet)
  - complexCoordinateSystemDepend
```
public static QDataSet complexCoordinateSystemDepend()
```
    returns the QDataSet used to identify the columns of a complex coordinate frame.
    
    Returns:
    
    the QDataSet used to identify the columns of a complex coordinate frame.
  - isComplexCoordinateSystemDepend
```
public static boolean isComplexCoordinateSystemDepend(QDataSet dep)
```
    return true if the data is length 2, rank 1, and has "ComplexNumber" as the COORDINATE_FRAME.
    
    Parameters:
    
    dep -
    
    Returns:
  - isComplexNumbers
```
public static boolean isComplexNumbers(QDataSet ds1)
```
    return true if the data represents an array of complex numbers, containing the property COORDINATE_FRAME on the last DEPEND, which is equal to "ComplexNumber"
    
    Parameters:
    
    ds1 - a dataset
    
    Returns:
    
    true if the data represents an array of complex numbers.
    
    See Also:
    
    Ops.checkComplexArgument(org.das2.qds.QDataSet)
  - complexBundleDataSet
```
public static QDataSet complexBundleDataSet()
```
    return bundle with Time, Density, Speed, and Flux, to demonstrate a bundle of datasets with differing rank.
    
    Returns:
    
    bundle with Time, Density, Speed, and Flux
    
    See Also:
    
    complexBundleDataSet2()
  - trajectory
```
public static QDataSet trajectory()
```
    return a trajectory through a space
    
    Returns:
    
    rank 2 dataset
  - isTrajectory
```
public static boolean isTrajectory(QDataSet ds)
```
    return true is the data is a trajectory
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is a trajectory
  - rank1AlongTrajectory
```
public static QDataSet rank1AlongTrajectory()
```
    return a rank 1 dataset that depends on a trajectory through a space, which is not supported currently.
    
    Returns:
    
    rank 1 dataset with DEPEND_0 a trajectory.
  - isRank1AlongTrajectory
```
public static boolean isRank1AlongTrajectory(QDataSet ds)
```
    return true if the data is rank 1 along a trajectory
    
    Parameters:
    
    ds - a dataset
    
    Returns:
    
    true if the data is rank 1 along a trajectory
  - xyScatter
```
public static QDataSet xyScatter()
```
    "scatter" is meant to indicate there is no connection between successive points, and that there is no dependence indicates no clean relation between the bundled datasets.
    
    Returns:
  - isXYScatter
```
public static boolean isXYScatter(QDataSet ds)
```
    is a xyScatter data set.
    
    Parameters:
    
    ds -
    
    Returns:
    
    true if is a xyScatter data set.
  - rank1AtXYScatter
```
public static QDataSet rank1AtXYScatter()
```
    Here there is a Z that is a function of X and Y of a xyScatter.
    
    Returns:
    
    rank 1 dataset that has bundle for DEPEND_0.
    
    See Also:
    
    xyzScatter()
  - isRank1AtXYScatter
```
public static boolean isRank1AtXYScatter(QDataSet ds)
```
    is a Z that is a function of X and Y of a xyScatter.
    
    Parameters:
    
    ds -
    
    Returns:
    
    true if is a Z that is a function of X and Y of a xyScatter.
  - isRank2Bins
```
public static boolean isRank2Bins(QDataSet dep)
```
    return true if the data is a rank 2 list of M bins. The data will have rank=2 and the property BINS_1='min,max'
    
    Parameters:
    
    dep -
    
    Returns:
    
    true if the data is a rank 2 list of M bins
  - rank2Bins
```
public static QDataSet rank2Bins()
```
    return a rank 2 dataset that is a list of bins.
    
    Returns:
  - isLegacyXYZScatter
```
public static boolean isLegacyXYZScatter(QDataSet zds)
```
    Many of Autoplot's codes use the "legacyXYZScatter" QDataSet scheme, where the X tags are in DEPEND_0, the Y tags are the QDataSet, and PLANE_0 contains the Z values.
    
    Parameters:
    
    zds -
    
    Returns:
  - legacyXYZScatter
```
public static QDataSet legacyXYZScatter()
```
    Many code use this form of data to represent Z(X,Y). This is not preferred, and ds[n;x,y,z] should be used instead. This is available for testing.
    
    Returns:
    
    rank 1 dataset with DEPEND_0 and PLANE_0 properties.
    
    See Also:
    
    rank1AtXYScatter()
  - isXYZScatter
```
public static boolean isXYZScatter(QDataSet zds)
```
    Parameters:
    
    zds -
    
    Returns:
    
    true is it is an xyzScatter scheme.
    
    See Also:
    
    xyzScatter()
  - xyzScatter
```
public static QDataSet xyzScatter()
```
    This will be the preferred way to represent X,Y → Z. This shows a problem, however, where there is no way to indicate the dependencies for the columns. The Z column can have DEPENDNAME_0, but how does one declare the dependence on Y as well? In https://sourceforge.net/p/autoplot/bugs/1710/, I propose CONTEXT_0=field0,field2, which seems like it would work nicely.
    
    Returns:
    
    See Also:
    
    rank1AlongTrajectory(), rank1AtXYScatter()
  - isIrregularJoin
```
public static boolean isIrregularJoin(QDataSet ds)
```
    return true if the data is a join of datasets of different cadences or lengths.
    
    Parameters:
    
    ds -
    
    Returns:
    
    return true if the data is a join of datasets of different cadences or lengths.
  - irregularJoin
```
public static QDataSet irregularJoin()
```
    return a rank 3 irregular join of three datasets, the first is 13 records of 27 energies, the second is 13 records of 20 energies, and the third is 14 records of 24 energies.
    
    Returns:
    
    a rank 3 irregular join.
  - polyMesh
```
public static QDataSet polyMesh()
```
    set of 2-d or 3-d points and the triangles connecting them. Note that Ops.triangulate does not return this schema. This is introduced to experiment with an oddly-structured dataset. For example, this can be a DEPEND_0 of a rank 1 rgb color dataset.
    
    Returns:
    
    a triangular mesh.
  - isPolyMesh
```
public static boolean isPolyMesh(QDataSet ds)
```
    return true if the data can be used as a triangulation or tessalation of 4-point rectangles.
    
    Parameters:
    
    ds -
    
    Returns:
    
    See Also:
    
    Ops.polyCenters(org.das2.qds.QDataSet), https://sourceforge.net/p/autoplot/feature-requests/819/

Class Schemes

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

Schemes

Method Detail

boundingBox

isBoundingBox

arrayOfBoundingBox

isArrayOfBoundingBox

rank2Waveform

isRank2Waveform

rank3Waveform

isRank3Waveform

rank2WaveformRank2Offsets

isRank2WaveformRank2Offsets

vectorTimeSeries

isVectorTimeSeries

simpleSpectrogram

isSimpleSpectrogram

scalarTimeSeries

isScalarTimeSeries

scalarSeriesWithErrors

isScalarSeriesWithErrors

simpleSpectrogramTimeSeries

isSimpleSpectrogramTimeSeries

isTimeSeries

uniformCadence

isUniformCadence

uniformRatiometricCadence

isUniformRatiometricCadence

compositeImage

isCompositeImage

eventsList

isEventsList

angleDistribution

angleDistribution

isAngleDistribution

complexBundleDataSet2

bundleDataSet

isBundleDataSet

isBundleDescriptor

bundleDescriptor

rank2ComplexNumbers

complexCoordinateSystemDepend

isComplexCoordinateSystemDepend

isComplexNumbers

complexBundleDataSet

trajectory

isTrajectory

rank1AlongTrajectory

isRank1AlongTrajectory

xyScatter

isXYScatter

rank1AtXYScatter

isRank1AtXYScatter

isRank2Bins

rank2Bins

isLegacyXYZScatter

legacyXYZScatter

isXYZScatter

xyzScatter

isIrregularJoin

irregularJoin

polyMesh

isPolyMesh