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.

dataIntersection

dataIntersection( QDataSet tE, QDataSet tB ) → QDataSet

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

Parameters

tE - a bunch of values.
tB - a bunch of values.

Returns:

the set of values found in both.

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/jenkins/job/autoplot-test029/ This supports:

int, float, double, etc to Rank 0 datasets
List<Number> to Rank 1 datasets.
Java arrays of Number to Rank 1-4 qubes datasets
Strings to rank 0 datasets with units ("5 s" or "2014-01-01T00:00")
Datums to rank 0 datasets
DatumRanges to rank 1 bins
DatumVector to rank 1 datasets.

Parameters

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

Returns:

QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dataset

dataset( Object arg0, Units u ) → 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 https://cottagesystems.com/jenkins/job/autoplot-test029/ This supports:

int, float, double, etc to Rank 0 datasets
List<Number> to Rank 1 datasets.
Java arrays of Number to Rank 1-4 qubes datasets
Strings to rank 0 datasets with units ("5 s" or "2014-01-01T00:00")
Datums to rank 0 datasets
DatumRanges to rank 1 bins

Parameters

arg0 - null,QDataSet,Number,Datum,DatumRange,String,List,or array.
u - units providing context

Returns:

QDataSet

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 https://cottagesystems.com/jenkins/job/autoplot-test029/ This supports:

int, float, double, etc to Rank 0 datasets
Strings to rank 0 datasets with units ("5 s" or "2014-01-01T00:00")
rank 0 datasets

Parameters

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

Returns:

Datum

[search for examples] [view on GitHub] [view on old javadoc] [view source]

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 https://cottagesystems.com/jenkins/job/autoplot-test029/ This supports:

2-element rank 1 QDataSet
Strings like ("5 to 15 s" or "2014-01-01")
2-element arrays and lists

Parameters

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

Returns:

DatumRange

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.

dblarr

dblarr( int len0, int len1 ) → QDataSet

create a rank 2 dataset filled with zeros, stored in 8-byte doubles.

Parameters

len0 - the length of the zeroth dimension.
len1 - the length of the first dimension.

Returns:

rank 2 dataset filled with zeros.

dblarr

dblarr( int len0, int len1, int len2 ) → QDataSet

create a rank 3 dataset filled with zeros, stored in 8-byte doubles.

Parameters

len0 - the length of the zeroth dimension.
len1 - the length of the first dimension.
len2 - the length of the second dimension.

Returns:

rank 3 dataset filled with zeros.

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.

decimate

decimate( QDataSet ds, int m ) → QDataSet

reduce the size of the data by keeping every nth measurement (subsample), starting at the 0th measurement.

Parameters

ds - rank 1 or more dataset.
m - the decimation factor, e.g. 2 is every other measurement.

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

decimate

decimate( QDataSet ds, int m, int n ) → QDataSet

reduce the size of the data by keeping every nth measurement (subsample).

Parameters

ds - rank 2 or more dataset.
m - the decimation factor for the zeroth index, e.g. 2 is every other measurement.
n - the decimation factor for the first index, e.g. 2 is every other measurement.

Returns:

new dataset which is ds.length()/m by ds.length(0)/n.

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dependsOn

dependsOn( QDataSet ds, int dim, QDataSet dep ) → org.das2.qds.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.

[search for examples] [view on GitHub] [view on old javadoc] [view source]

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

[search for examples] [view on GitHub] [view on old javadoc] [view source]

detrend( Object yy, int size ) → QDataSet [view source]

detrend1

detrend1( 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, along each record. Points on the end are zero.

Parameters

yy - rank 2 dataset
size - size of the boxcar

Returns:

dataset

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.

dimensionCount

dimensionCount( QDataSet dss ) → int

returns the number of physical dimensions of a dataset.

JOIN, BINS do not increase dataset dimensionality.
DEPEND increases dimensionality by dimensionality of DEPEND ds.
BUNDLE increases dimensionality by N, where N is the number of bundled datasets.

Note this includes implicit dimensions taken by the primary dataset:

Z(time,freq)→3
rand(20,20)→3
B_gsm(20,[X,Y,Z])→4

Parameters

dss - the dataset

Returns:

the number of dimensions occupied by the data.

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dimensionCount

dimensionCount( Object dss ) → int

returns the number of physical dimensions of the object when interpreted as a dataset.

Parameters

dss - the object that can be coerced into a dataset.

Returns:

the number of dimensions occupied by the data.

dindgen

dindgen( int len0 ) → QDataSet

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

Parameters

len0 - an int

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dindgen

dindgen( int len0, int len1 ) → QDataSet

returns rank 2 dataset with values increasing [ [0.,1.,2.], [ 3.,4.,5.] ]

Parameters

len0 - an int
len1 - an int

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dindgen

dindgen( int len0, int len1, int len2 ) → QDataSet

returns rank 3 dataset with values increasing

Parameters

len0 - an int
len1 - an int
len2 - an int

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

dindgen

dindgen( int len0, int len1, int len2, int len3 ) → QDataSet

returns rank 4 dataset with values increasing

Parameters

len0 - an int
len1 - an int
len2 - an int
len3 - an int

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

distance

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

return a table of distances d[len0] to the indices 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

[search for examples] [view on GitHub] [view on old javadoc] [view source]

distance

distance( int len0, int len1, double c0, double c1, double r0, double r1 ) → QDataSet

return a table of distances d[len0,len1] to the indices c0,c1; in units of r0, r1. This is motivated by a need for more interesting datasets for testing.

Parameters

len0 - the length of the dataset
len1 - the length of each row of the dataset
c0 - the center point 0
c1 - the center point 1
r0 - the units to normalize in the 0 direction
r1 - the units to normalize in the 1 direction

Returns:

rank 2 table

[search for examples] [view on GitHub] [view on old javadoc] [view source]

div

div( QDataSet ds1, QDataSet ds2 ) → QDataSet

element-wise div of two datasets with compatible geometry.

Parameters

ds1 - a QDataSet
ds2 - a QDataSet

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

div( Object ds1, Object ds2 ) → QDataSet [view source]

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

[search for examples] [view on GitHub] [view on old javadoc] [view source]

divide( Object ds1, Object ds2 ) → QDataSet [view source]

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 - a QDataSet
ds2 - a QDataSet

Returns:

a QDataSet

[search for examples] [view on GitHub] [view on old javadoc] [view source]

divp( Object ds1, Object ds2 ) → QDataSet [view source]

dataIntersection

Parameters

Returns:

See Also:

dataIntersection

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Returns:

See Also:

dataset

Parameters

Returns:

dataset

Parameters

Returns:

See Also:

datum

Parameters

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datumRange

Parameters

Returns:

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dblarr

Parameters

Returns:

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dblarr

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See Also:

dblarr

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Returns:

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decimate

Parameters

Returns:

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decimate

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decimate

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dependsOn

Parameters

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detrend

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detrend1

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Returns:

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diff

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Returns:

See Also:

dimensionCount

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Returns:

dimensionCount

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Returns:

See Also:

dindgen

Parameters

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dindgen

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dindgen

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dindgen

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distance

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