ceil

ceil( QDataSet ds1 ) → QDataSet

element-wise ceil function.

Parameters

ds1 -

Returns:

org.das2.qds.QDataSet

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chirp

chirp( QDataSet t, Datum df0, Datum dt1, Datum df1 ) → QDataSet

scipy chirp function, used for testing.

Parameters

t - Times at which to evaluate the waveform.
df0 - Frequency (e.g. Hz) at time t=0.
dt1 - Time at which `f1` is specified.
df1 - Frequency (e.g. Hz) of the waveform at time `t1`.

Returns:

org.das2.qds.QDataSet

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circle

circle( QDataSet radius, QDataSet x, QDataSet y ) → QDataSet

return a dataset with X and Y forming a circle, introduced as a convenient way to indicate planet location.

Parameters

x - the x coordinate of the circle
y - the y coordinate of the circle
radius - rank 0 dataset

Returns:

QDataSet that when plotted is a circle.

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cleanData

cleanData( QDataSet ds ) → QDataSet

remove the data which is 3 sigmas from the mean of the data.

Parameters

ds - rank 1 dataset.

Returns:

cleaned dataset of the same geometry.

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clearWritable

clearWritable( org.das2.qds.WritableDataSet ds ) → void

assign zeros to all the values of the dataset. The dataset must be mutable. This was used to verify Jython behavior.

Parameters

ds -

Returns:

void (returns nothing)

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collapse0

collapse0( QDataSet fillDs, int st, int en ) → QDataSet

this is introduced to mimic the in-line function which reduces the dimensionality by averaging over the zeroth dimension. collapse0( ds[30,20] ) → ds[20]

Parameters

fillDs -
st - the start index
en - the non-inclusive end index

Returns:

the averaged dataset

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collapse0R4

collapse0R4( QDataSet ds, ProgressMonitor mon ) → QDataSet

Collapse the rank 4 dataset on the zeroth index.

Parameters

ds - rank 4 dataset
mon -

Returns:

rank 3 dataset

See Also:

Ops_r.mdorg.das2.qds.OperationsProcessor#sprocess(java.lang.String, QDataSet, org.das2.util.monitor.ProgressMonitor)


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collapse1

collapse1( QDataSet ds ) → QDataSet

this is introduced to mimic the in-line function which reduces the dimensionality by averaging over the first dimension collapse1( ds[30,20] ) → ds[30]

Parameters

ds -

Returns:

the averaged dataset

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collapse1R4

collapse1R4( QDataSet ds, ProgressMonitor mon ) → QDataSet

Collapse the rank 4 dataset on the first index.

Parameters

ds - rank 4 dataset
mon -

Returns:

rank 3 dataset

See Also:

Ops_r.mdorg.das2.qds.OperationsProcessor#sprocess(java.lang.String, QDataSet, org.das2.util.monitor.ProgressMonitor)


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collapse2

collapse2( QDataSet fillDs ) → QDataSet

this is introduced to mimic the in-line function which reduces the dimensionality by averaging over the first dimension collapse2( ds[30,20,10,5] ) → ds[30,20,5]

Parameters

fillDs -

Returns:

the averaged dataset

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collapse2R4

collapse2R4( QDataSet ds, ProgressMonitor mon ) → QDataSet

Collapse the rank 4 dataset on the second index.

Parameters

ds - rank 4 dataset
mon -

Returns:

rank 3 dataset

See Also:

Ops_r.mdorg.das2.qds.OperationsProcessor#sprocess(java.lang.String, QDataSet, org.das2.util.monitor.ProgressMonitor)


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collapse3

collapse3( QDataSet fillDs ) → QDataSet

this is introduced to mimic the in-line function which reduces the dimensionality by averaging over the first dimension collapse3( ds[30,20,10,5] ) → ds[30,20,10]

Parameters

fillDs -

Returns:

the averaged dataset

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collapse3R4

collapse3R4( QDataSet ds, ProgressMonitor mon ) → QDataSet

Collapse the rank 4 dataset on the third index.

Parameters

ds - rank 4 dataset
mon -

Returns:

rank 3 dataset

See Also:

Ops_r.mdorg.das2.qds.OperationsProcessor#sprocess(java.lang.String, QDataSet, org.das2.util.monitor.ProgressMonitor)


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colorFromString

colorFromString( String sval ) → Color

return the color encoded as one of:

Parameters

sval - the string representation

Returns:

the color

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complexConj

complexConj( QDataSet ds ) → QDataSet

return the complex conjugate of the rank 1 or rank 2 QDataSet.

Parameters

ds - ds[2] or ds[n,2]

Returns:

ds[2] or ds[n,2]

See Also:

complexMultiply(QDataSet, QDataSet)


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complexDataset

complexDataset( QDataSet realPart, QDataSet imaginaryPart ) → QDataSet

create a complex dataset.

Parameters

realPart - the real component.
imaginaryPart - the complex component.

Returns:

complex dataset

See Also:

Ops_r.mdorg.das2.qds.examples.Schemes#rank2ComplexNumbers()


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complexMultiply

complexMultiply( QDataSet ds1, QDataSet ds2 ) → QDataSet

perform complex multiplication, where the two datasets must have the same rank and must both end with a complex dimension.

Parameters

ds1 - ds[2] or ds[n,2] or ds[n,m,2]
ds2 - ds[2] or ds[n,2] or ds[n,m,2]

Returns:

ds[2] or ds[n,2] or ds[n,m,2]

See Also:

complexConj(QDataSet)


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concatenate

Deprecated: use append instead.

convertPropertyValue

convertPropertyValue( QDataSet context, String name, Object value ) → Object

convert the object into the type needed for the property.

Parameters

context - the dataset to which we are assigning the value.
name - the property name
value - the value

Returns:

the correct value.

See Also:

Ops_r.mdorg.autoplot.jythonsupport.PyQDataSet#convertPropertyValue


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convertUnitsTo

convertUnitsTo( QDataSet ds, Units u ) → QDataSet

convert the dataset to the target units

Parameters

ds - the original dataset.
u - units of the new dataset

Returns:

a new dataset with all the same properties but with the new units.

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copyIndexedProperties

copyIndexedProperties( QDataSet srcds, org.das2.qds.MutablePropertyDataSet mds ) → void

copy over all the indexed properties into the mutable property dataset. This was introduced to support DataSetOps.unbundle, but should probably always be used. See https://sourceforge.net/p/autoplot/bugs/1704/

Parameters

srcds - the source dataset
mds - the destination dataset

Returns:

void (returns nothing)

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copyProperties

copyProperties( QDataSet ds ) → Map

copies the properties, copying depend datasets as well. TODO: This is not thorough, and this needs to be reviewed.

Parameters

ds - the data from which the properties are extracted.

Returns:

a map of the properties.

See Also:

Ops_a.mdDataSetUtil#getProperties(QDataSet)


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copysign

copysign( QDataSet magnitude, QDataSet sign ) → QDataSet

Returns the first floating-point argument with the sign of the second floating-point argument.

Parameters

magnitude -
sign -

Returns:

org.das2.qds.QDataSet

See Also:

Ops_s.md#signum
Ops_n.md#negate


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cos

cos( QDataSet ds ) → QDataSet

element-wise cos.

Parameters

ds -

Returns:

org.das2.qds.QDataSet

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cosh

cosh( QDataSet ds ) → QDataSet

element-wise cosh.

Parameters

ds -

Returns:

org.das2.qds.QDataSet

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createEvent

createEvent( String timeRange, int rgbcolor, String annotation ) → QDataSet

tool for creating ad-hoc events datasets.

Parameters

timeRange - a timerange like "2010-01-01" or "2010-01-01/2010-01-10" or "2010-01-01 through 2010-01-09"
rgbcolor - and RGB color like 0xFF0000 (red), 0x00FF00 (green), or 0x0000FF (blue),
annotation - label for event, possibly including granny codes.

Returns:

a rank 2 QDataSet with [[ startTime, stopTime, rgbColor, annotation ]]

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createEvents

createEvents( QDataSet vds ) → QDataSet

make canonical rank 2 bundle dataset of min,max,color,text This was originally part of EventsRenderer, but it became clear that this was generally useful.

Parameters

vds - dataset in a number of forms that can be converted to an events dataset.

Returns:

rank 2 QDataSet [ index; 4( time, stopTime, rgbColor, label ) ]

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cubicRoot

cubicRoot( QDataSet coefficients ) → QDataSet

Solves each of a set of cubic equations of the form: a*x^3 + b*x^2 + c*x + d = 0. Takes a rank 2 dataset with each equation across the first dimension and coefficients of each equation across the second.

Parameters

coefficients - Set of all coefficients.

Returns:

Roots of each equation. Double.NaN is returned for complex roots.

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cumulativeMax

cumulativeMax( QDataSet ds ) → QDataSet

for each element i of ds, set the result[i] to the maximum of ds[0:(i+1)]

Parameters

ds - rank 1 dataset

Returns:

the cumulative maximum

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cumulativeMin

cumulativeMin( QDataSet ds ) → QDataSet

for each element i of ds, set the result[i] to the minimum of ds[0:(i+1)]

Parameters

ds - rank 1 dataset

Returns:

the cumulative minimum

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