public abstract class AbstractDataset extends LazyDatasetBase implements Dataset
Each subclass has an array of primitive types, elements of this array are grouped or compounded to make items
Data items can be boolean, integer, float, complex float, vector float, etc
| Modifier and Type | Field and Description |
|---|---|
protected AbstractDataset |
base |
protected static char |
BLOCK_CLOSE |
protected static char |
BLOCK_OPEN |
protected Serializable |
odata
The data itself, held in a 1D array, but the object will wrap it to appear as possessing as many dimensions as
wanted
|
protected int |
offset |
protected int |
size |
protected int[] |
stride |
protected Format |
stringFormat |
catchExceptions, logger, metadata, name, shapeARRAYFLOAT32, ARRAYFLOAT64, ARRAYINT16, ARRAYINT32, ARRAYINT64, ARRAYINT8, ARRAYMUL, BOOL, COMPLEX, COMPLEX128, COMPLEX64, DATE, FLOAT, FLOAT32, FLOAT64, INT, INT16, INT32, INT64, INT8, OBJECT, RGB, STRING| Constructor and Description |
|---|
AbstractDataset()
Constructor required for serialisation.
|
| Modifier and Type | Method and Description |
|---|---|
boolean |
all()
Test if all items are true
|
BooleanDataset |
all(int axis) |
boolean |
any()
Test if any items are true
|
BooleanDataset |
any(int axis) |
int |
argMax(boolean... ignoreInvalids)
Find absolute index of maximum value (in a flattened view)
|
IntegerDataset |
argMax(int axis,
boolean... ignoreInvalids)
Find indices of maximum values along given axis
|
int |
argMin(boolean... ignoreInvalids)
Find absolute index of minimum value (in a flattened view)
|
IntegerDataset |
argMin(int axis,
boolean... ignoreInvalids)
Find indices of minimum values along given axis
|
protected static int |
calcSteps(double start,
double stop,
double step) |
Dataset |
cast(boolean repeat,
int dtype,
int isize)
Cast a dataset
|
<T extends Dataset> |
cast(Class<T> clazz)
Cast a dataset
|
Dataset |
cast(int dtype)
Cast a dataset
|
<T extends Dataset> |
cast(int isize,
Class<T> clazz,
boolean repeat)
Cast a dataset
|
int |
checkAxis(int axis)
Check that axis is in range [-rank,rank)
|
protected static int |
checkAxis(int rank,
int axis)
Deprecated.
|
void |
checkCompatibility(ILazyDataset g)
This method takes a dataset and checks its shape against the current dataset.
|
abstract AbstractDataset |
clone()
Clone dataset
|
<T extends Dataset> |
copy(Class<T> clazz)
Copy and cast a dataset
|
Dataset |
copy(int dtype)
Copy and cast a dataset
|
protected static void |
copyToView(Dataset orig,
AbstractDataset view,
boolean clone,
boolean cloneMetadata)
Copy fields from original to view
|
long |
count(boolean... ignoreInvalids) |
Dataset |
count(int[] axes,
boolean... ignoreInvalids) |
Dataset |
count(int axis,
boolean... ignoreInvalids) |
static int[] |
createStrides(Dataset a,
int[] offset)
Create a stride array from dataset
|
static int[] |
createStrides(int isize,
int[] shape,
int[] oStride,
int oOffset,
int[] offset)
Create a stride array from dataset
|
static int[] |
createStrides(SliceND slice,
Dataset a,
int[] stride,
int[] offset)
Create a stride array from slice information and a dataset
|
static int[] |
createStrides(SliceND slice,
int isize,
int[] shape,
int[] oStride,
int oOffset,
int[] stride,
int[] offset)
Create a stride array from slice and dataset information
|
protected void |
fillData(Object obj,
int depth,
int[] pos)
Fill dataset from object at depth dimension
|
Dataset |
flatten()
Flatten shape
|
int |
get1DIndex(int... n)
This method calculates the index in the data array that corresponds to
the given n-dimensional position
|
protected int |
get1DIndex(int i) |
protected int |
get1DIndex(int i,
int j) |
protected int |
get1DIndexFromShape(int[] n) |
protected static int |
get1DIndexFromShape(int[] shape,
int[] n) |
BooleanIterator |
getBooleanIterator(Dataset choice)
Get an iterator that visits every item in this dataset where the corresponding item in
choice dataset is true
|
BooleanIterator |
getBooleanIterator(Dataset choice,
boolean value)
Get an iterator that visits every item in this dataset where the corresponding item in
choice dataset is given by value
|
Dataset |
getBroadcastView(int... broadcastShape) |
Serializable |
getBuffer() |
protected abstract int |
getBufferLength() |
Dataset |
getBy1DIndex(IntegerDataset index)
This is modelled after the NumPy get item with an index dataset
|
Dataset |
getByBoolean(Dataset selection)
This is modelled after the NumPy get item with a condition specified by a boolean dataset
|
Dataset |
getByIndexes(Object... indexes)
This is modelled after the NumPy get item with an array of indexing objects
|
int |
getElementsPerItem() |
double |
getError()
Get the error for the first item.
|
double |
getError(int... pos)
Get the error for a given position.
|
double |
getError(int i)
Get the error for given position.
|
double |
getError(int i,
int j)
Get the error for given position.
|
double[] |
getErrorArray(int... pos)
Get the error values for a single point in the dataset
|
double[] |
getErrorArray(int i)
Get the error values for given position
|
double[] |
getErrorArray(int i,
int j)
Get the error values for given position
|
Dataset |
getErrorBuffer()
Get the (un-broadcasted) dataset that backs the (squared) error data
|
Dataset |
getErrors()
Get the errors, if any.
|
protected int |
getFirst1DIndex() |
IntegerDataset |
getIndices()
Generate an index dataset for current dataset
|
protected Dataset |
getInternalSquaredError() |
int |
getItemBytes() |
IndexIterator |
getIterator() |
IndexIterator |
getIterator(boolean withPosition) |
static int |
getMaxLineLength() |
int |
getNbytes() |
int[] |
getNDPosition(int n)
This method calculates the n-dimensional position in the dataset of
the given index in the data array
|
int |
getOffset() |
PositionIterator |
getPositionIterator(int... axes) |
int |
getRank()
The rank (or number of dimensions/indices) of the dataset can be zero for a zero-rank
(single-valued) dataset
|
Dataset |
getRealPart() |
Dataset |
getRealView() |
int[] |
getShape()
The shape (or array of lengths for each dimension) of the dataset can be empty for zero-rank
datasets
|
int[] |
getShapeRef()
The shape (or array of lengths for each dimension) of the dataset can be empty for zero-rank
datasets and null for null datasets
|
int |
getSize()
The size of the dataset is the number of items in the array
|
Dataset |
getSlice(IMonitor monitor,
int[] start,
int[] stop,
int[] step)
Get a slice of the dataset.
|
Dataset |
getSlice(IMonitor monitor,
Slice... slice)
Get a slice of the dataset.
|
Dataset |
getSlice(IMonitor monitor,
SliceND slice)
Get a slice of the dataset.
|
Dataset |
getSlice(int[] start,
int[] stop,
int[] step)
Get a slice of the dataset.
|
Dataset |
getSlice(Slice... slice)
Get a slice of the dataset.
|
abstract AbstractDataset |
getSlice(SliceIterator iterator)
Get a slice of the dataset.
|
Dataset |
getSlice(SliceND slice)
Get a slice of the dataset.
|
IndexIterator |
getSliceIterator(int[] start,
int[] stop,
int[] step) |
IndexIterator |
getSliceIterator(SliceND slice) |
SliceIterator |
getSliceIteratorFromAxes(int[] pos,
boolean[] axes)
Get a slice iterator that is defined by a starting position and a set of axes to include
|
Dataset |
getSliceView(int[] start,
int[] stop,
int[] step)
Get a slice of the dataset.
|
Dataset |
getSliceView(Slice... slice)
Get a slice of the dataset.
|
Dataset |
getSliceView(SliceND slice)
Get a slice of the dataset.
|
protected StatisticsMetadata<Number> |
getStats() |
int[] |
getStrides() |
protected StatisticsMetadata<String> |
getStringStats() |
Dataset |
getTransposedView(int... axes)
Permute copy of dataset's axes so that given order is old order:
|
abstract AbstractDataset |
getView(boolean deepCopyMetadata) |
boolean |
hasFloatingPointElements() |
int |
hashCode() |
Dataset |
ifloorDivide(Object o)
In-place floor division with object o
|
boolean |
isCompatibleWith(ILazyDataset g)
This method takes a dataset and checks its shape against the current dataset.
|
boolean |
isComplex() |
Number |
max(boolean... ignoreInvalids) |
Dataset |
max(int[] axes,
boolean... ignoreInvalids) |
Dataset |
max(int axis,
boolean... ignoreInvalids) |
Object |
mean(boolean... ignoreInvalids) |
Dataset |
mean(int[] axes,
boolean... ignoreInvalids) |
Dataset |
mean(int axis,
boolean... ignoreInvalids) |
Number |
min(boolean... ignoreInvalids) |
Dataset |
min(int[] axes,
boolean... ignoreInvalids) |
Dataset |
min(int axis,
boolean... ignoreInvalids) |
void |
overrideInternal(Serializable buffer,
int... shape)
Set the buffer that backs the dataset and its shape
|
Number |
peakToPeak(boolean... ignoreInvalids) |
Dataset |
peakToPeak(int[] axes,
boolean... ignoreInvalids) |
Dataset |
peakToPeak(int axis,
boolean... ignoreInvalids) |
Object |
product(boolean... ignoreInvalids) |
Dataset |
product(int[] axes,
boolean... ignoreInvalids) |
Dataset |
product(int axis,
boolean... ignoreInvalids) |
Dataset |
reshape(int... shape)
Returns new dataset with new shape but old data if possible, otherwise a copy is made
|
double |
residual(Object o)
Calculate residual of dataset with object o
See
Dataset.residual(Object o, boolean ignoreNaNs) with ignoreNaNs = false |
double |
residual(Object o,
boolean ignoreNaNs)
Calculate residual of dataset with object o
|
double |
rootMeanSquare(boolean... ignoreInvalids) |
Dataset |
rootMeanSquare(int[] axes,
boolean... ignoreInvalids) |
Dataset |
rootMeanSquare(int axis,
boolean... ignoreInvalids) |
protected abstract void |
setData()
Set aliased data as base data
|
void |
setErrorBuffer(Serializable buffer)
Set a copy of the buffer that backs the (squared) error data
|
protected abstract void |
setItemDirect(int dindex,
int sindex,
Object src)
Set item from compatible dataset in a direct and speedy way.
|
static void |
setMaxLineLength(int maxLineLength)
Set maximum line length for toString() method
|
void |
setShape(int... shape)
Set a compatible shape for dataset.
|
Dataset |
setSlice(Object obj,
int[] start,
int[] stop,
int[] step)
This is modelled after the NumPy array slice
|
Dataset |
setSlice(Object obj,
Slice... slice)
This is modelled after the NumPy array slice
|
Dataset |
setSlice(Object obj,
SliceND slice)
This is modelled after the NumPy array slice
|
void |
setStringFormat(Format format)
Set string output format
|
Dataset |
squeeze()
Remove dimensions of 1 in shape of the dataset
|
Dataset |
squeeze(boolean onlyFromEnds)
Remove dimensions of 1 in shape of the dataset from ends only if true
|
Dataset |
squeezeEnds()
Remove dimensions of 1 from ends of shape of the dataset
|
double |
stdDeviation()
Standard deviation is square root of the variance
|
double |
stdDeviation(boolean isWholePopulation,
boolean... ignoreInvalids)
Standard deviation is square root of the variance
|
Dataset |
stdDeviation(int axis)
Standard deviation is square root of the variance
|
Dataset |
stdDeviation(int[] axes)
Standard deviation is square root of the variance
|
Dataset |
stdDeviation(int[] axes,
boolean isWholePopulation,
boolean... ignoreInvalids)
Standard deviation is square root of the variance
|
Dataset |
stdDeviation(int axis,
boolean isWholePopulation,
boolean... ignoreInvalids)
Standard deviation is square root of the variance
|
Object |
sum(boolean... ignoreInvalids) |
Dataset |
sum(int[] axes,
boolean... ignoreInvalids) |
Dataset |
sum(int axis,
boolean... ignoreInvalids) |
Dataset |
swapAxes(int axis1,
int axis2)
Swap two axes in dataset
|
Dataset |
synchronizedCopy()
This is a synchronized version of the clone method
|
String |
toString() |
String |
toString(boolean showData) |
Dataset |
transpose(int... axes)
|
double |
variance() |
double |
variance(boolean isWholePopulation,
boolean... ignoreInvalids)
The sample variance can be calculated in two ways: if the dataset is considered as the
entire population then the sample variance is simply the second central moment:
|
Dataset |
variance(int axis) |
Dataset |
variance(int[] axes) |
Dataset |
variance(int[] axes,
boolean isWholePopulation,
boolean... ignoreInvalids) |
Dataset |
variance(int axis,
boolean isWholePopulation,
boolean... ignoreInvalids) |
addMetadata, checkPermutatedAxes, clearMetadata, copyMetadata, copyMetadata, createFromSerializable, dirtyMetadata, equals, findMetadataTypeSubInterfaces, getDType, getElementClass, getErrorMetadata, getFirstMetadata, getMetadata, getMetadata, getMetadataMap, getName, hasErrors, reshapeMetadata, restoreMetadata, setDirty, setErrors, setMetadata, setName, sliceMetadata, transposeMetadatafinalize, getClass, notify, notifyAll, wait, wait, waitcontainsInfs, containsInvalidNumbers, containsNans, copyItemsFromAxes, fill, fillDataset, getBoolean, getBoolean, getBoolean, getByte, getByte, getByte, getDouble, getDouble, getDouble, getDType, getElementBooleanAbs, getElementDoubleAbs, getElementLongAbs, getFloat, getFloat, getFloat, getInt, getInt, getInt, getLong, getLong, getLong, getObject, getObject, getObject, getObjectAbs, getShort, getShort, getShort, getString, getString, getString, getStringAbs, getUniqueItems, iadd, idivide, ifloor, imultiply, ipower, iremainder, isubtract, residual, set, set, set, setBy1DIndex, setByBoolean, setByIndexes, setDirty, setItemsOnAxes, setObjectAbs, setSlice, sortgetBoolean, getByte, getDouble, getFloat, getInt, getLong, getMetadata, getObject, getShort, getString, maxPos, minPos, resize, setaddMetadata, clearMetadata, getElementClass, hasErrors, setErrors, setMetadatagetFirstMetadata, getMetadataprotected int size
protected transient AbstractDataset base
protected int[] stride
protected int offset
protected Serializable odata
protected Format stringFormat
protected static final char BLOCK_OPEN
protected static final char BLOCK_CLOSE
public AbstractDataset()
protected abstract void setData()
public Dataset synchronizedCopy()
DatasetsynchronizedCopy in interface Datasetpublic int hashCode()
hashCode in class LazyDatasetBasepublic abstract AbstractDataset clone()
ILazyDatasetclone in interface Datasetclone in interface IDatasetclone in interface ILazyDatasetclone in class LazyDatasetBasepublic void setStringFormat(Format format)
IDatasetsetStringFormat in interface IDatasetpublic Dataset copy(int dtype)
Datasetpublic <T extends Dataset> T copy(Class<T> clazz)
Datasetpublic <T extends Dataset> T cast(Class<T> clazz)
Datasetpublic Dataset cast(boolean repeat, int dtype, int isize)
Datasetpublic abstract AbstractDataset getView(boolean deepCopyMetadata)
protected static void copyToView(Dataset orig, AbstractDataset view, boolean clone, boolean cloneMetadata)
orig - view - clone - if true, then clone everything but bulk datacloneMetadata - if true, clone metadatapublic IntegerDataset getIndices()
DatasetgetIndices in interface Datasetpublic Dataset getTransposedView(int... axes)
IDatasetaxisPerm = (p(0), p(1),...) => newdata(n(0), n(1),...) = olddata(o(0), o(1), ...) such that n(i) = o(p(i)) for all iI.e. for a 3D dataset (1,0,2) implies the new dataset has its 1st dimension running along the old dataset's 2nd dimension and the new 2nd is the old 1st. The 3rd dimension is left unchanged.
getTransposedView in interface DatasetgetTransposedView in interface IDatasetgetTransposedView in interface ILazyDatasetaxes - if zero length then axes order reversedpublic Dataset swapAxes(int axis1, int axis2)
Datasetprotected void fillData(Object obj, int depth, int[] pos)
obj - depth - pos - positionpublic IndexIterator getIterator(boolean withPosition)
getIterator in interface DatasetwithPosition - set true if position is neededpublic IndexIterator getIterator()
getIterator in interface Datasetpublic PositionIterator getPositionIterator(int... axes)
getPositionIterator in interface Datasetaxes - axes to omit from iteratorpublic IndexIterator getSliceIterator(int[] start, int[] stop, int[] step)
getSliceIterator in interface Datasetstart - specifies the starting indexesstop - specifies the stopping indexes (nb, these are not included in the slice)step - specifies the steps in the slicepublic IndexIterator getSliceIterator(SliceND slice)
getSliceIterator in interface Datasetslice - public SliceIterator getSliceIteratorFromAxes(int[] pos, boolean[] axes)
DatasetgetSliceIteratorFromAxes in interface Datasetaxes - to includepublic BooleanIterator getBooleanIterator(Dataset choice)
DatasetgetBooleanIterator in interface Datasetpublic BooleanIterator getBooleanIterator(Dataset choice, boolean value)
DatasetgetBooleanIterator in interface Datasetpublic Dataset getByBoolean(Dataset selection)
DatasetgetByBoolean in interface Datasetselection - a boolean dataset of same shape to use for selecting itemspublic Dataset getBy1DIndex(IntegerDataset index)
DatasetgetBy1DIndex in interface Datasetindex - an integer datasetpublic Dataset getByIndexes(Object... indexes)
DatasetgetByIndexes in interface Datasetindexes - an array of integer dataset, boolean dataset, slices or null entries (same as
full slices)public boolean hasFloatingPointElements()
hasFloatingPointElements in interface Datasetpublic int getElementsPerItem()
getElementsPerItem in interface ILazyDatasetpublic int getItemBytes()
getItemBytes in interface IDatasetpublic int getSize()
ILazyDatasetgetSize in interface ILazyDatasetpublic int[] getShape()
ILazyDatasetgetShape in interface ILazyDatasetgetShape in class LazyDatasetBasepublic int getRank()
ILazyDatasetgetRank in interface ILazyDatasetgetRank in class LazyDatasetBasepublic int getNbytes()
public void setShape(int... shape)
ILazyDatasetsetShape in interface ILazyDatasetpublic int[] getShapeRef()
DatasetgetShapeRef in interface Datasetpublic int getOffset()
public int[] getStrides()
getStrides in interface Datasetpublic Serializable getBuffer()
public void overrideInternal(Serializable buffer, int... shape)
DatasetThis is very, very dangerous. Please use carefully
overrideInternal in interface Datasetbuffer - (can be null to leave unchanged)shape - (can be null to leave unchanged)public static int[] createStrides(Dataset a, int[] offset)
a - datasetoffset - output offsetpublic static int[] createStrides(int isize, int[] shape, int[] oStride, int oOffset, int[] offset)
isize - shape - oStride - original strideoOffset - original offset (only used if there is an original stride)offset - output offsetpublic static int[] createStrides(SliceND slice, Dataset a, int[] stride, int[] offset)
slice - a - datasetstride - output strideoffset - output offsetpublic static int[] createStrides(SliceND slice, int isize, int[] shape, int[] oStride, int oOffset, int[] stride, int[] offset)
slice - isize - shape - oStride - original strideoOffset - original offset (only used if there is an original stride)stride - output strideoffset - output offsetpublic Dataset getBroadcastView(int... broadcastShape)
getBroadcastView in interface Datasetpublic Dataset getSliceView(int[] start, int[] stop, int[] step)
IDatasetgetSliceView in interface DatasetgetSliceView in interface IDatasetgetSliceView in interface ILazyDatasetstart - specifies the starting indexes (can be null for origin)stop - specifies the stopping indexes (can be null for end)step - specifies the steps in the slice (can be null for unit steps)public Dataset getSliceView(Slice... slice)
IDatasetgetSliceView in interface DatasetgetSliceView in interface IDatasetgetSliceView in interface ILazyDatasetslice - an array of slice objects (the array can be null or contain nulls)public Dataset getSliceView(SliceND slice)
getSliceView in interface DatasetgetSliceView in interface IDatasetgetSliceView in interface ILazyDatasetslice - protected int getFirst1DIndex()
public int get1DIndex(int... n)
Datasetget1DIndex in interface Datasetn - the integer array specifying the n-D positionprotected int get1DIndex(int i)
i - protected int get1DIndex(int i, int j)
i - j - protected int get1DIndexFromShape(int[] n)
protected static int get1DIndexFromShape(int[] shape, int[] n)
public int[] getNDPosition(int n)
DatasetgetNDPosition in interface Datasetn - The index in the arrayprotected abstract int getBufferLength()
public int checkAxis(int axis)
Dataset@Deprecated protected static int checkAxis(int rank, int axis)
public static void setMaxLineLength(int maxLineLength)
maxLineLength - public static int getMaxLineLength()
public Dataset squeezeEnds()
ILazyDatasetsqueezeEnds in interface DatasetsqueezeEnds in interface IDatasetsqueezeEnds in interface ILazyDatasetpublic Dataset squeeze()
IDatasetpublic Dataset squeeze(boolean onlyFromEnds)
IDatasetpublic boolean isCompatibleWith(ILazyDataset g)
DatasetisCompatibleWith in interface Datasetg - The dataset to be comparedpublic void checkCompatibility(ILazyDataset g) throws IllegalArgumentException
DatasetcheckCompatibility in interface Datasetg - The dataset to be comparedIllegalArgumentException - This will be thrown if there is a problem with the compatibilitypublic Dataset reshape(int... shape)
Datasetprotected static int calcSteps(double start, double stop, double step)
start - stop - step - public boolean isComplex()
public Dataset getRealPart()
getRealPart in interface Datasetpublic Dataset getRealView()
getRealView in interface Datasetpublic Dataset getSlice(int[] start, int[] stop, int[] step)
ILazyDatasetgetSlice in interface DatasetgetSlice in interface IDatasetgetSlice in interface ILazyDatasetstart - specifies the starting indexes (can be null for origin)stop - specifies the stopping indexes (can be null for end)step - specifies the steps in the slice (can be null for unit steps)public Dataset getSlice(Slice... slice)
ILazyDatasetpublic Dataset getSlice(IMonitor monitor, Slice... slice)
ILazyDatasetgetSlice in interface DatasetgetSlice in interface ILazyDatasetslice - an array of slice objects (the array can be null or contain nulls)public Dataset getSlice(IMonitor monitor, SliceND slice)
ILazyDatasetgetSlice in interface DatasetgetSlice in interface ILazyDatasetslice - an n-D slicepublic Dataset getSlice(IMonitor monitor, int[] start, int[] stop, int[] step)
ILazyDatasetgetSlice in interface DatasetgetSlice in interface ILazyDatasetstart - specifies the starting indexes (can be null for origin)stop - specifies the stopping indexes (can be null for end)step - specifies the steps in the slice (can be null for unit steps)public Dataset getSlice(SliceND slice)
public abstract AbstractDataset getSlice(SliceIterator iterator)
iterator - Slice iteratorpublic Dataset setSlice(Object obj, SliceND slice)
Datasetpublic Dataset setSlice(Object obj, int[] start, int[] stop, int[] step)
DatasetsetSlice in interface Datasetobj - specifies the object used to set the specified slicestart - specifies the starting indexesstop - specifies the stopping indexes (nb, these are not included in the slice)step - specifies the steps in the slicepublic Dataset setSlice(Object obj, Slice... slice)
Datasetpublic BooleanDataset all(int axis)
public BooleanDataset any(int axis)
public Dataset ifloorDivide(Object o)
DatasetifloorDivide in interface Datasetpublic double residual(Object o)
DatasetDataset.residual(Object o, boolean ignoreNaNs) with ignoreNaNs = falsepublic double residual(Object o, boolean ignoreNaNs)
Datasetprotected StatisticsMetadata<Number> getStats()
protected StatisticsMetadata<String> getStringStats()
public Number max(boolean... ignoreInvalids)
max in interface IDatasetignoreInvalids - - Can be null, empty, or one or more booleans. By default, all booleans
are false. If the first boolean is true, will ignore NaNs and ignore infinities. Use the second
boolean to ignore infinities separately.public Dataset max(int axis, boolean... ignoreInvalids)
max in interface DatasetignoreInvalids - - Can be null, empty, or one or more booleans. By default, all booleans
are false. If the first boolean is true, will ignore NaNs and ignore infinities. Use the second
boolean to ignore infinities separately.public Dataset max(int[] axes, boolean... ignoreInvalids)
max in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Number min(boolean... ignoreInvalids)
min in interface IDatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset min(int axis, boolean... ignoreInvalids)
min in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset min(int[] axes, boolean... ignoreInvalids)
min in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public int argMax(boolean... ignoreInvalids)
DatasetargMax in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public IntegerDataset argMax(int axis, boolean... ignoreInvalids)
DatasetargMax in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public int argMin(boolean... ignoreInvalids)
DatasetargMin in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public IntegerDataset argMin(int axis, boolean... ignoreInvalids)
DatasetargMin in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Number peakToPeak(boolean... ignoreInvalids)
peakToPeak in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset peakToPeak(int axis, boolean... ignoreInvalids)
peakToPeak in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset peakToPeak(int[] axes, boolean... ignoreInvalids)
peakToPeak in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public long count(boolean... ignoreInvalids)
count in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset count(int axis, boolean... ignoreInvalids)
count in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset count(int[] axes, boolean... ignoreInvalids)
count in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Object sum(boolean... ignoreInvalids)
sum in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset sum(int axis, boolean... ignoreInvalids)
sum in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset sum(int[] axes, boolean... ignoreInvalids)
sum in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Object product(boolean... ignoreInvalids)
product in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset product(int axis, boolean... ignoreInvalids)
product in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset product(int[] axes, boolean... ignoreInvalids)
product in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Object mean(boolean... ignoreInvalids)
mean in interface IDatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset mean(int axis, boolean... ignoreInvalids)
mean in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset mean(int[] axes, boolean... ignoreInvalids)
mean in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public double variance()
variance in interface Datasetwith isWholePopulation = falsepublic double variance(boolean isWholePopulation, boolean... ignoreInvalids)
Dataset
sum((x_i - m)^2)/N
where {x_i} are set of N population values and m is the mean
m = sum(x_i)/N
Otherwise, if the dataset is a set of samples (with replacement) from the population then
sum((x_i - m)^2)/(N-1)
where {x_i} are set of N sample values and m is the unbiased estimate of the mean
m = sum(x_i)/N
Note that the second definition is also the unbiased estimator of population variance.variance in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset variance(int axis)
variance in interface Datasetwith isWholePopulation = falsepublic Dataset variance(int[] axes)
variance in interface Datasetwith isWholePopulation = falsepublic Dataset variance(int axis, boolean isWholePopulation, boolean... ignoreInvalids)
variance in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset variance(int[] axes, boolean isWholePopulation, boolean... ignoreInvalids)
variance in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public double stdDeviation()
DatasetstdDeviation in interface Datasetwith isWholePopulation = falsepublic double stdDeviation(boolean isWholePopulation, boolean... ignoreInvalids)
DatasetstdDeviation in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)Dataset.variance(boolean, boolean...)public Dataset stdDeviation(int axis)
DatasetstdDeviation in interface Datasetwith isWholePopulation = falsepublic Dataset stdDeviation(int[] axes)
DatasetstdDeviation in interface Datasetwith isWholePopulation = falsepublic Dataset stdDeviation(int axis, boolean isWholePopulation, boolean... ignoreInvalids)
DatasetstdDeviation in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset stdDeviation(int[] axes, boolean isWholePopulation, boolean... ignoreInvalids)
DatasetstdDeviation in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public double rootMeanSquare(boolean... ignoreInvalids)
rootMeanSquare in interface DatasetignoreInvalids - - see IDataset.max(boolean...)public Dataset rootMeanSquare(int axis, boolean... ignoreInvalids)
rootMeanSquare in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)public Dataset rootMeanSquare(int[] axes, boolean... ignoreInvalids)
rootMeanSquare in interface DatasetignoreInvalids - - see Dataset.max(int, boolean...)protected abstract void setItemDirect(int dindex, int sindex, Object src)
dindex - sindex - src - is the source data bufferpublic Dataset getErrors()
ILazyDatasetgetErrors in interface DatasetgetErrors in interface IDatasetgetErrors in interface ILazyDatasetgetErrors in class LazyDatasetBasepublic double getError()
Datasetpublic double getError(int i)
Datasetpublic double getError(int i, int j)
Datasetpublic double getError(int... pos)
IDatasetpublic double[] getErrorArray(int i)
DatasetgetErrorArray in interface Datasetpublic double[] getErrorArray(int i, int j)
DatasetgetErrorArray in interface Datasetpublic double[] getErrorArray(int... pos)
IDatasetgetErrorArray in interface IDatasetpos - of the point to be referencedprotected Dataset getInternalSquaredError()
public Dataset getErrorBuffer()
DatasetgetErrorBuffer in interface Datasetpublic void setErrorBuffer(Serializable buffer)
setErrorBuffer in interface Datasetbuffer - can be null, anything that can be used to create a DoubleDataset or CompoundDoubleDatasetCopyright © 2014–2019 Eclipse Foundation. All rights reserved.