org.das2.qds.FDataSet

rank 0,1,2,3 or 4 dataset backed by float array (4 byte real numbers). Note access to the array is still done via doubles.

version

addValue

addValue( int i0, double value ) → void

add this value to the current value.

Parameters

i0 - the index
value - the value

Returns:

void (returns nothing)

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addValue

addValue( int i0, int i1, double value ) → void

add this value to the current value.

Parameters

i0 - the index
i1 - the index
value - the value

Returns:

void (returns nothing)

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capability

capability( java.lang.Class clazz ) → Object

TODO: this is untested, but is left in to demonstrate how the capability method should be implemented. Clients should use this instead of casting the class to the capability class.

Parameters

clazz - the class, such as WritableDataSet.class

Returns:

null or the capability if exists, such as WritableDataSet

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create

create( int[] qube ) → org.das2.qds.FDataSet

Makes an array from array of dimension sizes. The result will have rank qube.length().

Parameters

qube - array specifying the rank and size of each dimension

Returns:

the array as a QDataSet

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createRank1

createRank1( int len0 ) → org.das2.qds.FDataSet

create a rank 1 dataset backed by array of floats.

Parameters

len0 - length of the dimension

Returns:

rank 1 qube dataset of backed by array of floats.

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createRank2

createRank2( int len0, int len1 ) → org.das2.qds.FDataSet

create a rank 2 qube dataset backed by array of floats.

Parameters

len0 - length of the dimension
len1 - length of the dimension

Returns:

rank 2 qube dataset of backed by array of floats.

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createRank3

createRank3( int len0, int len1, int len2 ) → org.das2.qds.FDataSet

create a rank 3 qube dataset backed by array of floats.

Parameters

len0 - length of the dimension
len1 - length of the dimension
len2 - length of the dimension

Returns:

rank 3 qube dataset of backed by array of floats.

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

createRank4

createRank4( int len0, int len1, int len2, int len3 ) → org.das2.qds.FDataSet

create a rank 4 qube dataset backed by array of floats.

Parameters

len0 - length of the dimension
len1 - length of the dimension
len2 - length of the dimension
len3 - length of the dimension

Returns:

rank 4 qube dataset of backed by array of floats.

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

putProperty

putProperty( String name, Object value ) → void

check for fill as well, since often numerical noise will corrupt the fill values.

Parameters

name - the property name
value - the property value

Returns:

void (returns nothing)

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putValue

putValue( double value ) → void

Parameters

value - a double

Returns:

void (returns nothing)

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putValue

putValue( int i0, double value ) → void

Parameters

i0 - an int
value - a double

Returns:

void (returns nothing)

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putValue

putValue( int i0, int i1, double value ) → void

Parameters

i0 - an int
i1 - an int
value - a double

Returns:

void (returns nothing)

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putValue

putValue( int i0, int i1, int i2, double value ) → void

Parameters

i0 - an int
i1 - an int
i2 - an int
value - a double

Returns:

void (returns nothing)

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putValue

putValue( int i0, int i1, int i2, int i3, double value ) → void

Parameters

i0 - an int
i1 - an int
i2 - an int
i3 - an int
value - a double

Returns:

void (returns nothing)

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

slice

slice( int i ) → QDataSet

the slice operator is better implemented here. Presently, we use System.arraycopy to copy out the data, but this could be re-implemented along with an offset parameter so the original data can be used to back the data.

Parameters

i - the index

Returns:

a rank N-1 slice of the data.

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trim

trim( int start, int end ) → QDataSet

trim operator copies the data into a new dataset.

Parameters

start - the first index
end - the last index, exclusive

Returns:

a shorter dataset of the same rank.

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value

value( ) → double

Returns:

double

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value

value( int i0 ) → double

Parameters

i0 - an int

Returns:

double

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value

value( int i0, int i1 ) → double

Parameters

i0 - an int
i1 - an int

Returns:

double

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value

value( int i0, int i1, int i2 ) → double

Parameters

i0 - an int
i1 - an int
i2 - an int

Returns:

double

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value

value( int i0, int i1, int i2, int i3 ) → double

Parameters

i0 - an int
i1 - an int
i2 - an int
i3 - an int

Returns:

double

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wrap

wrap( float[] data, int[] qube ) → org.das2.qds.FDataSet

Wraps an array from array of dimension sizes. The result will have rank qube.length(). For rank 0, data is 1-element array.

Parameters

data - array containing the data, with the last dimension contiguous in memory.
qube - array specifying the rank and size of each dimension

Returns:

the array as a QDataSet

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

wrap

wrap( float[] back, int rank, int len0, int len1, int len2 ) → org.das2.qds.FDataSet

wrap the array to make it into a dataset. This is the same as wrap( back, qube ). The data is not copied, so be sure that no outside codes modify the data unintentionally.

Parameters

back - the array
rank - the rank of the dataset
len0 - the length, or 1 if the index is not needed.
len1 - the length, or 1 if the index is not needed.
len2 - the length, or 1 if the index is not needed.

Returns:

the dataset wrapping the array.

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wrap

wrap( float[] back ) → org.das2.qds.FDataSet

creates a rank1 FDataSet by wrapping an existing array.

Parameters

back - the new backing array

Returns:

the dataset

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wrap

wrap( float[] back, int nx, int ny ) → org.das2.qds.FDataSet

creates a FDataSet by wrapping an existing array, aliasing it to rank 2.

Parameters

back - the new backing array
nx - number of elements in the zeroth index
ny - number of elements in the first index

Returns:

the dataset

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wrap

wrap( float[] back, int nx, int ny, int nz ) → org.das2.qds.FDataSet

creates a rank1 DDataSet by wrapping an existing array.

Parameters

back - the new backing array
nx - number of elements in the zeroth index
ny - number of elements in the first index
nz - number of elements in the second index

Returns:

the dataset

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