triana.types

Class TimeFrequency

java.lang.Object

triana.types.TrianaType

triana.types.GraphType

triana.types.MatrixType

triana.types.TimeFrequency

All Implemented Interfaces:

java.io.Serializable, Arithmetic, AsciiComm, SequenceInterface, Signal, Spectral

public class TimeFrequency
extends MatrixType
implements AsciiComm, Spectral, Signal

TimeFrequency is the class derived from MatrixType to represent a two-dimensional array whose elements contain frequency information associated with different times. The time-axis is the horizontal dimension of the matrix (dimension 0) and the frequency axis is the vertical dimension of the matrix (dimension 1). TimeFrequency implements the Spectral Interface and the Triana spectral data model, as described in the documentation for ComplexSpectrum. TimeFrequency allows data to be real or complex. It also implements the Signal Interface to provide information along the time-dimension.

TimeFrequency assumes the variables are uniformly sampled in both directions. It introduces new parameters resolution, twoSided, highestFrequency, narrow, and nFull, as in ComplexSpectrum. It further introduces parameters samplingRate and acquisitionTime, as in SampleSet. Finally it introduces interval, the time-interval between successive time-sets along the time axis.

See Also:

MatrixType, TrianaType, GraphType, SampleSet, ComplexSpectrum, Spectral, Signal, Serialized Form

Field Summary

Fields inherited from class triana.types.TrianaType

NOT_CONNECTED, NOT_READY, OUT_OF_RANGE

Constructor Summary

Constructors

Constructor and Description
TimeFrequency() Creates a new empty TimeFrequency, with no parameters set
TimeFrequency(boolean complex, boolean ts, boolean nrw, int lenf, int nOrig, double df, double hf, double iv, int lent, double acTime) Creates a new TimeFrequency with arguments giving whether the data are to be complex, the sidedness, whether it is narrow-band or broad-band, the data length, the number of points in the original broad-band spectrum, the frequency resolution, the highest frequency in the current spectrum, the interval between data sets along the time-axis, the number of data sets, and the acquisition time of the first data point.
TimeFrequency(boolean complex, boolean ts, int nOrig, double df, double iv, int lent, double acTime) Creates a new TimeFrequency with a given complexity, sidedness, number of points that there would be in a single two-sided spectrum, frequency resolution, interval between time-sets, number of time-sets, and acquisition tim eof the first sample.
TimeFrequency(double[][] zr, double[][] zi, boolean ts, boolean nrw, int nOrig, double df, double hf, double iv, double acTime) Creates a new TimeFrequency with arguments giving the 2D data matrix, or two matrices if the data is complex, the sidedness, whether it is narrow-band or broad-band, the number of points in the original broad-band spectrum, the frequency resolution, the highest frequency in the current spectrum, the interval between data sets along the time-axis, and the acquisition time of the first data point.

Method Summary

Methods

Modifier and Type	Method and Description
TrianaType	copyMe() This is one of the most important methods of Triana data.
protected void	copyParameters(TrianaType source) Copies modifiable parameters from the argument object to the current object.
boolean	equals(TrianaType obj) Determines whether the argument TrianaType is equal to the current TimeFrequency.
double	getAcquisitionTime() Returns the acquisition time as a double giving the number of seconds since the reference time, which should be the same reference time as for the method setAcquisitionTime.
double[]	getFrequencyArray(int dim) Returns the frequency values of the independent data points for the given dimension, in the order of lowest frequency to highest, regardless of how the data are stored internally.
double	getFrequencyResolution() Returns the frequency resolution of the data along the frequency axis.
double	getFrequencyResolution(int dim) Returns the frequency resolution of the data for the given dimension (independent variable).
java.lang.Object	getGraphArrayImag(int dv) Returns the imaginary part of the dependent variable ordered so that the frequency values all run monotonically upwards.
java.lang.Object	getGraphArrayReal(int dv) Returns the real part of the dependent variable ordered so that the frequency values all run monotonically upwards.
double[]	getIndependentScaleImag(int dim) Returns null because the independent data on both axes are real.
double[]	getIndependentScaleReal(int dim) Returns the independent data scaled the way they should be graphed.
double	getInterval() Gets the interval between data sets, in seconds.
double	getLowerFrequencyBound() Returns the (non-negative) value of the lowest frequency in the frequency band held in the object.
double	getLowerFrequencyBound(int dim) Returns the (non-negative) value of the lowest frequency in the frequency band held in the object, for the given dimension dim.
double	getNyquist() Returns the Nyquist frequency, defined to be the highest frequency that this data set could contain if it were not narrow-banded.
java.lang.Object	getOrderedSpectrumImag() Returns the imaginary parts of the values of the spectrum (data points) in a multidimensional array, ordered so that in the frequency dimension (index 1, the vertical dimension of the matrix) the values correspond to frequencies running from the lowest to the highest.
java.lang.Object	getOrderedSpectrumReal() Returns the real parts of the values of the spectrum (data points) in a two-dimensional array, ordered so that in the frequency dimension (which is the vertical dimension, index 1) the values correspond to frequencies running from the lowest to the highest.
int	getOriginalN() Returns the number of points in the data set associated with each time (each column of the matrix) whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.
int	getOriginalN(int dim) Returns the number of points in the data set in the frequency dimension whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.
double	getSamplingRate() Returns the sampling frequency of the data.
double	getUpperFrequencyBound() Returns the (non-negative) value of the highest frequency in the frequency band held in the object.
double	getUpperFrequencyBound(int dim) Returns the (non-negative) value of the highest frequency in the frequency band held in the object, for the given dimension dim.
void	inputFromStream(java.io.BufferedReader dis) Used when Triana types want to be able to receive ASCII data from the output of other programs.
boolean	isCompatible(TrianaType obj) Tests the argument object to determine if it makes sense to perform arithmetic operations between it and the current object.
boolean	isNarrow() Returns true if the data represent a narrow bandwidth derived from a full-band spectrum.
boolean	isNarrow(int dim) Returns true if the data for the given dimension represent a narrow bandwidth derived from a full-band spectrum.
boolean	isTwoSided() Returns true if the frequency data are stored as a two-sided transform, i.e.
void	outputToStream(java.io.PrintWriter dos) Used when Triana types want to be able to send ASCII data to other programs using strings.
static TimeFrequency	reduceNyquist(TimeFrequency inputNarrow, boolean allocMem) Class method that takes an input narrow-band TimeFrequency and reduces nFull to be compatible with the upper frequency bound, so that the set is no longer narrow-band at the top.
void	setAcquisitionTime(double t) Sets the acquisition time.
void	setFrequencyResolution(double df) Sets the frequency resolution of the data along the frequency axis to the given value.
void	setFrequencyResolution(double f, int dim) Sets the frequency resolution of the data for the given dimension to the given value.
void	setInterval(double iv) Sets the interval between data sets, in seconds.
void	setNarrow(boolean n) Sets the narrow-bandedness flag to the value of the argument.
void	setNarrow(boolean n, int dim) Sets the narrow-bandedness flag associated with the given dimension to the value of the argument.
void	setOriginalN(int nOrig) Sets to the given argument the number of points in the data set associated with each time (each column of the matrix) whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.
void	setOriginalN(int nOrig, int dim) Sets to the given first argument nOrig the number of points in the data set associated with each time (each column of the matrix) in the dimension given by the second argument dim whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.
void	setSamplingRate(double r) Sets the sampling rate of the signal and adjusts the data for the independent variable accordingly.
void	setTwoSided(boolean s) Sets the two-sidedness flag to the value of the argument.
void	setUpperFrequencyBound(double hf) Sets the (non-negative) value of the highest frequency in the frequency band held in the object to the given value.
void	setUpperFrequencyBound(double hf, int dim) Sets or resets the (non-negative) value of the highest frequency in the frequency band held in the object for the given direction dim to the value of the given argument hf.

Methods inherited from class triana.types.MatrixType

getData, getDataImag, getDataReal, getXorYArray, getXorYImag, getXorYReal, getXorYTriplet, initialiseData, initialiseDataComplex, initialiseDataReal, length, setData, setData, setXorY, setXorY, size, testDataModel

Methods inherited from class triana.types.GraphType

add, addToTitle, convertDependentDataArraysToBytes, convertDependentDataArraysToDoubles, convertDependentDataArraysToFloats, convertDependentDataArraysToInts, convertDependentDataArraysToLongs, convertDependentDataArraysToShorts, copyData, copyLabels, divide, equals, getDataArrayClass, getDataArrayImag, getDataArrayImag, getDataArrayImagAsBytes, getDataArrayImagAsDoubles, getDataArrayImagAsFloats, getDataArrayImagAsInts, getDataArrayImagAsLongs, getDataArrayImagAsShorts, getDataArrayReal, getDataArrayReal, getDataArrayRealAsBytes, getDataArrayRealAsDoubles, getDataArrayRealAsFloats, getDataArrayRealAsInts, getDataArrayRealAsLongs, getDataArrayRealAsShorts, getDataArrayTypeNames, getDependentLabels, getDependentVariableDimensions, getDependentVariables, getDimensionLengths, getDimensionLengths, getGraphArrayImagLog10, getGraphArrayRealLog10, getIndependentArrayImag, getIndependentArrayReal, getIndependentLabels, getIndependentScaleImagLog10, getIndependentScaleRealLog10, getIndependentTriplet, getIndependentVariables, getLabels, getLabelsColumn, getTitle, isArithmeticArray, isArithmeticData, isCompatible, isDependentComplex, isIndependentComplex, isPrimitiveArray, isPrimitiveData, isTriplet, isUniform, maxDependentGraphingValuesImag, maxDependentGraphingValuesReal, maxDependentVariablesImag, maxDependentVariablesReal, maxIndependentScalesImag, maxIndependentScalesReal, maxIndependentVariablesImag, maxIndependentVariablesReal, minDependentGraphingValuesImag, minDependentGraphingValuesReal, minDependentVariablesImag, minDependentVariablesReal, minIndependentScalesImag, minIndependentScalesReal, minIndependentVariablesImag, minIndependentVariablesReal, multiply, resetDependent, resetIndependent, restrictToSubdomain, restrictToSubdomain, setDataArrayImag, setDataArrayReal, setDefaultAxisLabelling, setDependentLabels, setDependentVariableDimensions, setDimensionLengths, setDimensionLengths, setDimensions, setIndependentArrayImag, setIndependentArrayReal, setIndependentLabels, setIndependentTriplet, setIndependentTriplet, setLabels, setTitle, subtract

Methods inherited from class triana.types.TrianaType

containerSize, dataExists, deleteFromContainer, getDataContainer, getFromContainer, getSequenceNumber, insertIntoContainer, inspectDataContainer, setDataContainer, setSequenceNumber, updateObsoletePointers

Methods inherited from class java.lang.Object

clone, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

TimeFrequency

public TimeFrequency()

Creates a new empty TimeFrequency, with no parameters set

TimeFrequency

public TimeFrequency(boolean complex,
             boolean ts,
             boolean nrw,
             int lenf,
             int nOrig,
             double df,
             double hf,
             double iv,
             int lent,
             double acTime)

Creates a new TimeFrequency with arguments giving whether the data are to be complex, the sidedness, whether it is narrow-band or broad-band, the data length, the number of points in the original broad-band spectrum, the frequency resolution, the highest frequency in the current spectrum, the interval between data sets along the time-axis, the number of data sets, and the acquisition time of the first data point. No memory is allocated for the data.

Parameters:

complex - True if the data is to be complex

ts - True if the new TimeFrequency is to be two-sided

nrw - True if the new TimeFrequency is to be narrow-band

lenf - Number of frequency points in the current data set

nOrig - Number of points in the original two-sided full spectrum

df - Frequency resolution

hf - Highest frequency in the current data set

iv - The time-interval between sets along the time-axis

lent - The number of time-sets

acTime - The time of acquisition of the first sample of the first set

TimeFrequency

public TimeFrequency(double[][] zr,
             double[][] zi,
             boolean ts,
             boolean nrw,
             int nOrig,
             double df,
             double hf,
             double iv,
             double acTime)

Creates a new TimeFrequency with arguments giving the 2D data matrix, or two matrices if the data is complex, the sidedness, whether it is narrow-band or broad-band, the number of points in the original broad-band spectrum, the frequency resolution, the highest frequency in the current spectrum, the interval between data sets along the time-axis, and the acquisition time of the first data point. Matrices are arranged so that the first index is the time-step and the second the frequency.

Parameters:

zr - the real part of the data

zi - the imaginary part of the data

ts - True if the new TimeFrequency is to be two-sided

nrw - True if the new TimeFrequency is to be narrow-band

nOrig - Number of points in the original two-sided full spectrum

df - Frequency resolution

hf - Highest frequency in the current data set

iv - The time-interval between sets along the time-axis

acTime - The time of acquisition of the first sample of the first set

TimeFrequency

public TimeFrequency(boolean complex,
             boolean ts,
             int nOrig,
             double df,
             double iv,
             int lent,
             double acTime)

Creates a new TimeFrequency with a given complexity, sidedness, number of points that there would be in a single two-sided spectrum, frequency resolution, interval between time-sets, number of time-sets, and acquisition tim eof the first sample. It does not allocate memory for the data. It assumes that the frequency data are full-bandwidth.

Parameters:

complex - True if the data is to be complex

ts - True if the new TimeFrequency is to be two-sided

nOrig - Number of points in the original two-sided full spectrum

df - Frequency resolution

iv - The time-interval between sets along the time-axis

lent - The number of time-sets

acTime - The time of acquisition of the first sample of the first set

Method Detail

getFrequencyResolution

public double getFrequencyResolution(int dim)

Returns the frequency resolution of the data for the given dimension (independent variable). Since the frequency dimension is 1, this argument must equal 1 for a sensible return. This form of the method is required by the Spectral interface.

Specified by:

getFrequencyResolution in interface Spectral

Parameters:

dim - The index of the independent variable being queried

Returns:

The frequency resolution

getFrequencyResolution

public double getFrequencyResolution()

Returns the frequency resolution of the data along the frequency axis.

Returns:

double The frequency resolution

setFrequencyResolution

public void setFrequencyResolution(double f,
                          int dim)

Sets the frequency resolution of the data for the given dimension to the given value. Since the frequency dimension is 1, this argument must be set to 1 or the method will have no effect. This form of the method is required by the Spectral interface.

Specified by:

setFrequencyResolution in interface Spectral

Parameters:

dim - The index of the independent variable being queried

f - The frequency resolution

setFrequencyResolution

public void setFrequencyResolution(double df)

Sets the frequency resolution of the data along the frequency axis to the given value.

Parameters:

df - The frequency resolution

isTwoSided

public boolean isTwoSided()

Returns true if the frequency data are stored as a two-sided transform, i.e. containing both the positive and negative frequency data. If false, the data are one-sided, containing only positive frequencies.

Specified by:

isTwoSided in interface Spectral

Returns:

boolean True if data are two-sided in frequency space

setTwoSided

public void setTwoSided(boolean s)

Sets the two-sidedness flag to the value of the argument.

Specified by:

setTwoSided in interface Spectral

Parameters:

s - True if the data will be two-sided

getOriginalN

public int getOriginalN(int dim)

Returns the number of points in the data set in the frequency dimension whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived. Since the frequency dimension has index 1, the argument must equal 1 for a sensible return.

Specified by:

getOriginalN in interface Spectral

Parameters:

dim - The index of the independent variable being queried

Returns:

The number of points in the original data set

getOriginalN

public int getOriginalN()

Returns the number of points in the data set associated with each time (each column of the matrix) whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.

Returns:

int The number of points in the original data set

setOriginalN

public void setOriginalN(int nOrig,
                int dim)

Sets to the given first argument nOrig the number of points in the data set associated with each time (each column of the matrix) in the dimension given by the second argument dim whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived. Since the frequency dimension is index 1, the second argument must equal 1 for a sensible return.

Specified by:

setOriginalN in interface Spectral

Parameters:

dim - The index of the independent variable being queried

nOrig - The new number of points in the original data set

setOriginalN

public void setOriginalN(int nOrig)

Sets to the given argument the number of points in the data set associated with each time (each column of the matrix) whose transform could have led to the present data, or equivalently the number of points in the two-sided full-bandwidth spectrum from which the present spectrum could have been derived.

Parameters:

nOrig - The new number of points in the original data set

isNarrow

public boolean isNarrow(int dim)

Returns true if the data for the given dimension represent a narrow bandwidth derived from a full-band spectrum. Since the frequency dimension has index 1, the argument must equal 1 for a ssensible return.

Specified by:

isNarrow in interface Spectral

Parameters:

dim - The index of the independent variable being queried

Returns:

True if data are narrow-band

isNarrow

public boolean isNarrow()

Returns true if the data represent a narrow bandwidth derived from a full-band spectrum.

Returns:

True if data are narrow-band

setNarrow

public void setNarrow(boolean n,
             int dim)

Sets the narrow-bandedness flag associated with the given dimension to the value of the argument. Since the frequency dimension has index 1, the second argument must equal 1.

Specified by:

setNarrow in interface Spectral

Parameters:

n - True if the data held are narrow-band

dim - The index of the independent variable being set

setNarrow

public void setNarrow(boolean n)

Sets the narrow-bandedness flag to the value of the argument.

Parameters:

n - True if the data held are narrow-band

getLowerFrequencyBound

public double getLowerFrequencyBound(int dim)

Returns the (non-negative) value of the lowest frequency in the frequency band held in the object, for the given dimension dim. Since the frequency dimension is 1, the argument must equal 1 to give a sensible return.

Specified by:

getLowerFrequencyBound in interface Spectral

Parameters:

dim - The index of the independent variable being queried

Returns:

The lowest frequency represented in the given direction

getLowerFrequencyBound

public double getLowerFrequencyBound()

Returns the (non-negative) value of the lowest frequency in the frequency band held in the object.

Returns:

double The lowest frequency represented in the given direction

getUpperFrequencyBound

public double getUpperFrequencyBound(int dim)

Returns the (non-negative) value of the highest frequency in the frequency band held in the object, for the given dimension dim. Since the frequency dimension is 1, the argument should equal 1 to give a sensible return.

Specified by:

getUpperFrequencyBound in interface Spectral

Parameters:

dim - The index of the independent variable being queried

Returns:

The highest frequency represented in the given direction

getUpperFrequencyBound

public double getUpperFrequencyBound()

Returns the (non-negative) value of the highest frequency in the frequency band held in the object.

Returns:

double The highest frequency represented in the given direction

setUpperFrequencyBound

public void setUpperFrequencyBound(double hf,
                          int dim)

Sets or resets the (non-negative) value of the highest frequency in the frequency band held in the object for the given direction dim to the value of the given argument hf. Since the frequency dimension is 1, the second argument should equal1 for a sensible action. This method should be used after altering parameters or data in the object if they have changed the upper frequency bound. This should also set the isNarrow flag if the given value is not the highest value of the original-length spectrum.

Specified by:

setUpperFrequencyBound in interface Spectral

Parameters:

dim - The index of the independent variable being queried

hf - The new highest frequency represented in the given direction

setUpperFrequencyBound

public void setUpperFrequencyBound(double hf)

Sets the (non-negative) value of the highest frequency in the frequency band held in the object to the given value. Should be used after altering parameters or data in the object if they have changed the upper frequency bound. This should also set the isNarrow flag if the given value is not the highest value of the original-length spectrum.

Parameters:

hf - The new highest frequency

getFrequencyArray

public double[] getFrequencyArray(int dim)

Returns the frequency values of the independent data points for the given dimension, in the order of lowest frequency to highest, regardless of how the data are stored internally. Since the frequency dimension is index 1, the argument should equal 1 for a sensible return.

Specified by:

getFrequencyArray in interface Spectral

Parameters:

dim - The dimension of the independent variable

Returns:

double[] Array of ordered frequency values

getOrderedSpectrumReal

public java.lang.Object getOrderedSpectrumReal()

Returns the real parts of the values of the spectrum (data points) in a two-dimensional array, ordered so that in the frequency dimension (which is the vertical dimension, index 1) the values correspond to frequencies running from the lowest to the highest. These points then correspond to the values returned by getFrequencyArray for the frequency dimension.

Specified by:

getOrderedSpectrumReal in interface Spectral

Returns:

Object Multidimensional arrray of ordered spectral values

getOrderedSpectrumImag

public java.lang.Object getOrderedSpectrumImag()

Returns the imaginary parts of the values of the spectrum (data points) in a multidimensional array, ordered so that in the frequency dimension (index 1, the vertical dimension of the matrix) the values correspond to frequencies running from the lowest to the highest. These points then correspond to the values returned by getFrequencyArray for each dimension.

Specified by:

getOrderedSpectrumImag in interface Spectral

Returns:

Object Multidimensional arrray of ordered spectral values

getNyquist

public double getNyquist()

Returns the Nyquist frequency, defined to be the highest frequency that this data set could contain if it were not narrow-banded. For full-bandwidth sets, this is the same value as is returned by getUpperFrequencyBound(), but for narrow-band data sets it may be higher.

The general formula is that if the original number of data points (given by nFull = getOriginalN()) is even, then the Nyquist frequency is nFull * resolution / 2. If the original number of data points is odd, then the Nyquist frequency is (nFull -1 ) * resolution / 2.

Returns:

double The Nyquist frequency

getSamplingRate

public double getSamplingRate()

Returns the sampling frequency of the data. If the data are irregularly sampled it returns 0.

Specified by:

getSamplingRate in interface Signal

Returns:

double The sampling frequency

setSamplingRate

public void setSamplingRate(double r)

Sets the sampling rate of the signal and adjusts the data for the independent variable accordingly. If the sampling frequency argument r is negative, nothing is done. If it is zero, irregular sampling is assumed. If positive, the sampling frequency is set to r and the values of the independent variable are re-adjusted accordingly if necessary, assuming the same starting time as before the change in the rate. This method also writes the new sampling frequency into the description StringVector. If there is an audio format, it is updated with the new sampling rate.

Specified by:

setSamplingRate in interface Signal

Parameters:

r - The sampling rate

getAcquisitionTime

public double getAcquisitionTime()

Returns the acquisition time as a double giving the number of seconds since the reference time, which should be the same reference time as for the method setAcquisitionTime. The time set is interpreted as the moment of acquisition of the first sample in the data set.

Specified by:

getAcquisitionTime in interface Signal

Returns:

double The time of acquisition in seconds since the reference time

setAcquisitionTime

public void setAcquisitionTime(double t)

Sets the acquisition time. This method also writes the acquisition time into the description StringVector. If the given acquisition time is not equal to the starting time of the independent variable, all values of the independent variable are shifted by the difference between the given time and the previous starting time.

Specified by:

setAcquisitionTime in interface Signal

Parameters:

t - The acquisition time in seconds

getInterval

public double getInterval()

Gets the interval between data sets, in seconds.

Returns:

double The interval between data sets

setInterval

public void setInterval(double iv)

Sets the interval between data sets, in seconds.

Parameters:

iv - The new interval between data sets, in seconds

getIndependentScaleReal

public double[] getIndependentScaleReal(int dim)

Returns the independent data scaled the way they should be graphed. The time-axis values are returned if the argument index is 0, the frequency-axis values in the correct order are returned if the argument is 1.

Overrides:

getIndependentScaleReal in class GraphType

Parameters:

dim - The independent dimension under consideration

Returns:

The scaled independent data values

getIndependentScaleImag

public double[] getIndependentScaleImag(int dim)

Returns null because the independent data on both axes are real.

Overrides:

getIndependentScaleImag in class GraphType

Parameters:

dim - The independent dimension under consideration

Returns:

The scaled independent data values

getGraphArrayReal

public java.lang.Object getGraphArrayReal(int dv)

Returns the real part of the dependent variable ordered so that the frequency values all run monotonically upwards. Since there is only one dependent variable the index must be 0.

Overrides:

getGraphArrayReal in class GraphType

Parameters:

dv - The dependent variable dimension

Returns:

Object An array containing the rearranged data values

getGraphArrayImag

public java.lang.Object getGraphArrayImag(int dv)

Returns the imaginary part of the dependent variable ordered so that the frequency values all run monotonically upwards. Since there is only one dependent variable the index must be 0.

Overrides:

getGraphArrayImag in class GraphType

Parameters:

dv - The dependent variable dimension

Returns:

Object An array containing the rearranged data values

copyMe

public TrianaType copyMe()

This is one of the most important methods of Triana data. types. It returns a copy of the type invoking it. This must be overridden for every derived data type derived. If not, the data cannot be copied to be given to other units. Copying must be done by value, not by reference.

To override, the programmer should not invoke the super.copyMe method. Instead, create an object of the current type and call methods copyData and copyParameters. If these have been written correctly, then they will do the copying. The code should createTool, for type YourType:

 YourType y = null; try { y =
 (YourType)getClass().newInstance(); y.copyData( this ); y.copyParameters( this ); y.setLegend( this.getLegend()
 ); } catch (IllegalAccessException ee) { System.out.println("Illegal Access: " + ee.getMessage()); } catch
 (InstantiationException ee) { System.out.println("Couldn't be instantiated: " + ee.getMessage()); } return y;
 

The copied object's data should be identical to the original. The method here modifies only one item: a String indicating that the object was created as a copy is added to the description StringVector.

Overrides:

copyMe in class MatrixType

Returns:

TrianaType Copy by value of the current Object except for an updated description

copyParameters

protected void copyParameters(TrianaType source)

Copies modifiable parameters from the argument object to the current object. The copying is by value, not by reference. Parameters are defined as data not held in dataContainer. They are modifiable if they have set... methods. Parameters that cannot be modified, but which are set by constructors, should be placed correctly into the copied object when it is constructed.

This must be overridden by any subclass that defines new parameters. The overriding method should invoke its super method. It should use the set... and get... methods for the parameters in question. This method is protected so that it cannot be called except by objects that inherit from this one. It is called by copyMe.

Overrides:

copyParameters in class GraphType

Parameters:

source - Data object that contains the data to be copied.

outputToStream

public void outputToStream(java.io.PrintWriter dos)
                    throws java.io.IOException

Used when Triana types want to be able to send ASCII data to other programs using strings. This is used to implement socket and to run other executables, written in C or other languages. With ASCII you don't have to worry about ENDIAN'ness as the conversions are all done via text. This is obviously slower than binary communication since you have to format the input and output within the other program.

This method must be overridden in every subclass that defines new data or parameters. The overriding method should first call<

 super.outputToStream(dos) 

to get output from superior classes, and then new parameters defined for the current subclass must be output. Moreover, subclasses that first dimension their data arrays must explicitly transfer these data arrays.

Specified by:

outputToStream in interface AsciiComm

Overrides:

outputToStream in class GraphType

Parameters:

dos - The data output stream

Throws:

java.io.IOException

inputFromStream

public void inputFromStream(java.io.BufferedReader dis)
                     throws java.io.IOException

Used when Triana types want to be able to receive ASCII data from the output of other programs. This is used to implement socket and to run other executables, written in C or other languages. With ASCII you don't have to worry about ENDIAN'ness as the conversions are all done via text. This is obviously slower than binary communication since you have to format the input and output within the other program.

This method must be overridden in every subclass that defines new data or parameters. The overriding method should first call

 super.inputFromStream(dis) 

to get input from superior classes, and then new parameters defined for the current subclass must be input. Moreover, subclasses that first dimension their data arrays must explicitly transfer these data arrays.

Specified by:

inputFromStream in interface AsciiComm

Overrides:

inputFromStream in class GraphType

Parameters:

dis - The data input stream

Throws:

java.io.IOException

isCompatible

public boolean isCompatible(TrianaType obj)

Tests the argument object to determine if it makes sense to perform arithmetic operations between it and the current object.

In TimeFrequency, this method tests for compatibility with superior classes, to see that the input object is a TimeFrequency, and to see if the relevant parameters are equal. It does not enforce equality of acquisitionTime because it may be desirable to compare two data sets acquired at different times.

Classes derived from this should over-ride this method with further tests as appropriate. The over-riding method should normally have the first lines

 boolean test = super.isCompatible( obj );
 

followed by other tests. If other types not subclassed from GraphType or Const should be allowed to be compatible then other tests must be implemented.

Overrides:

isCompatible in class MatrixType

Parameters:

obj - The data object to be compared with the current one

Returns:

True if the object can be combined with the current one

equals

public boolean equals(TrianaType obj)

Determines whether the argument TrianaType is equal to the current TimeFrequency. They are equal if the argument is a TimeFrequency with the same size, parameters, and data.

This method must be over-ridden in derived types. In a derived type called xxx the method should begin

 if ( !( obj instanceof xxx ) ) return false; if
 ( !isCompatible( obj ) ) return false; 

followed by tests that are specific to type xxx (testing its own parameters) and then as a last line

 return super.equals( obj ); 

This line invokes the other equals methods up the chain to GraphType. Each superior object tests its own parameters.

Parameters:

obj - The object being tested

Returns:

true if they are equal or false otherwise

reduceNyquist

public static TimeFrequency reduceNyquist(TimeFrequency inputNarrow,
                          boolean allocMem)

Class method that takes an input narrow-band TimeFrequency and reduces nFull to be compatible with the upper frequency bound, so that the set is no longer narrow-band at the top. This is useful in doing resampling of time-series data. The Nyquist frequency is the highest frequency allowed by the sampling rate. If the input is not narrow-band, then the method returns null.

Parameters:

inputNarrow - The input narrow-band spectrum

allocMem - True if the output is a modified copy of input

Returns:

The reduced-sampling-rate spectrum