dataIntersection

dataIntersection( int[] itE, int[] itB ) → int

return the values which occur in both rank 1 datasets. Each dataset is sorted.

Parameters

itE - a bunch of values.
itB - a bunch of values.

Returns:

the set of values found in both.

See Also:

Ops_e.md#eventsConjunction(QDataSet, QDataSet)


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dataset

dataset( Object arg0 ) → QDataSet

coerce Java objects like arrays Lists and scalars into a QDataSet. This is introduced to mirror the useful Jython dataset command. This is a nasty business that is surely going to cause all sorts of problems, so we should do it all in one place. See http://jfaden.net:8080/hudson/job/autoplot-test029/ This supports:

Parameters

arg0 - null,QDataSet,Number,Datum,DatumRange,String,List,or array.

Returns:

QDataSet

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datum

datum( Object arg0 ) → Datum

coerce Java objects like numbers and strings into a Datum. This is introduced to mirror the useful Jython dataset command. This is a nasty business that is surely going to cause all sorts of problems, so we should do it all in one place. See http://jfaden.net:8080/hudson/job/autoplot-test029/ This supports:

Parameters

arg0 - null,QDataSet,Number,Datum, or String.

Returns:

Datum

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datumRange

datumRange( Object arg0 ) → DatumRange

coerce Java objects like arrays and strings into a DatumRange. This is introduced to mirror the useful Jython dataset command. This is a nasty business that is surely going to cause all sorts of problems, so we should do it all in one place. See http://jfaden.net:8080/hudson/job/autoplot-test029/ This supports:

Parameters

arg0 - null, QDataSet, String, array or List.

Returns:

DatumRange

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dblarr

dblarr( int len0 ) → QDataSet

create a rank 1 dataset filled with zeros, stored in 8-byte doubles.

Parameters

len0 - the length of the zeroth dimension.

Returns:

rank 1 dataset filled with zeros.

See Also:

Ops_z.md#zeros(int)
Ops_f.md#fltarr(int)
Ops_b.md#bytarr(int)
Ops_s.md#shortarr(int)
Ops_i.md#intarr(int)


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decimate

decimate( QDataSet ds ) → QDataSet

reduce the size of the data by keeping every 10th measurement.

Parameters

ds - a qube dataset.

Returns:

a decimated qube dataset.

See Also:

decimate(QDataSet, int)


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dependsOn

dependsOn( QDataSet ds, int dim, QDataSet dep ) → MutablePropertyDataSet

declare that the dataset is a dependent parameter of an independent parameter. This isolates the QDataSet semantics, and verifies correctness. See also link(x,y).

Parameters

ds - the dataset
dim - dimension to declare dependence: 0,1,2.
dep - the independent dataset.

Returns:

the dataset, which may be a copy if the data was not mutable.

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detrend

detrend( QDataSet yy, int size ) → QDataSet

remove D/C and low-frequency components from the data by subtracting out the smoothed data with a boxcar of the given size. Points on the end are zero.

Parameters

yy - rank 1 dataset
size - size of the boxcar

Returns:

dataset

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diff

diff( QDataSet ds ) → QDataSet

return array that is the differences between each successive pair in the dataset. Result[i]= ds[i+1]-ds[i], so that for an array with N elements, an array with N-1 elements is returned. When the data has a DEPEND_0, the result will have a DEPEND_0 which contains the average of the corresponding points.

Parameters

ds - a rank 1 dataset with N elements.

Returns:

a rank 1 dataset with N-1 elements.

See Also:

Ops_a.md#accum(QDataSet)


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dimensionCount

dimensionCount( QDataSet dss ) → int

returns the number of physical dimensions of a dataset.

Note this includes implicit dimensions taken by the primary dataset:

Parameters

dss - the dataset

Returns:

the number of dimensions occupied by the data.

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dindgen

dindgen( int len0 ) → QDataSet

returns rank 1 dataset with values [0.,1.,2.,...]

Parameters

len0 -

Returns:

org.das2.qds.QDataSet

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distance

distance( int len0, double c0, double r0 ) → QDataSet

return a table of distances d[len0] to the indeces c0; in units of r0. This is motivated by a need for more interesting datasets for testing.

Parameters

len0 - the length of the dataset
c0 - the center point 0
r0 - the units to normalize in the 0 direction

Returns:

rank 2 table

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div

div( QDataSet ds1, QDataSet ds2 ) → QDataSet

element-wise div of two datasets with compatible geometry.

Parameters

ds1 -
ds2 -

Returns:

org.das2.qds.QDataSet

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divide

divide( QDataSet ds1, QDataSet ds2 ) → QDataSet

element-wise divide of two datasets with compatible geometry. Either ds1 or ds2 should be dimensionless, or the units be convertible. TODO: units improvements.

Parameters

ds1 - the numerator
ds2 - the divisor

Returns:

the ds1/ds2

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divp

divp( QDataSet ds1, QDataSet ds2 ) → QDataSet

This div goes with modp, where -18 divp 10 = -2 and -18 modp 10 = 8. the div operator always goes towards zero, but divp always goes to the more negative number so the remainder is positive.

Parameters

ds1 -
ds2 -

Returns:

org.das2.qds.QDataSet

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