class TSeries

Time series API.

Public Fields

typedef unsigned long size_t

Length type;

typedef unsigned long stat_t

Status type;

Public Methods

TSeries()

Default constructor.

TSeries(const TSeries& TS)

Copy Constructor.

TSeries(const Time& t0, const Interval& dt)

Dataless constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const float dData[]=0)

Float data constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const short dData[])

Short integer data constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const int dData[])

Integer data constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const double dData[])

Double float data constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const fComplex dData[])

Complex data constructor.

TSeries(const Time& t0, const Interval& dt, size_t NData, const Chirp& func)

Signal template function constructor.

explicit TSeries(const FSeries& fs)

FSeries constructor.

~TSeries()

TSeries Destructor.

std::ostream& Dump(std::ostream& out) const

Formatted dump of the TSeries data.

TSeries decimate(size_t dec) const

Decimate a Time Series.

TSeries decimate(size_t dec, Filter& xalias) const

Decimate a Time Series.

TSeries extract(const Time& t0, const Interval& dT=Interval(0.0)) const

Extract a subset of the data from a TSeries.

void extend(const Time& t0)

Extend a TSeries.

size_t getBin(Time t) const

Get bin index.

Time getBinT(size_t inx) const

Get bin time.

size_t getData(size_t len, short* data) const

Copy data to a short int output array.

size_t getData(size_t len, int* data) const

Copy data to an integer array

size_t getData(size_t len, float* data) const

Copy data to a float array

size_t getData(size_t len, double* data) const

Copy data to a double array

size_t getData(size_t len, fComplex* data) const

Copy data to a complex array.

double getDouble(size_t index) const

Get ith element as a double precision number.

Time getEndTime(void) const

Get the end Time of the series.

float getF0(void) const

Get heterodyne frequency.

Interval getInterval(void) const

Get series duration.

const char* getName(void) const

Get the series name.

size_t getNSample(void) const

Get the number of samples

Time getStartTime(void) const

Get the start time.

Interval getTStep(void) const

Get the sample time.

double getAverage(void) const

Average value of data.

double getMaximum(void) const

Maximum data value.

double getMinimum(void) const

Minumim data value.

size_t getNBetween(double low, double high) const

Number of entries betwee two limits.

size_t getNGreater(double Limit) const

Entries greater than limit.

size_t getNLess(double Limit) const

Entries less than Limit.

stat_t getStatus(void) const

Data status.

bool isEmpty(void) const

Test for data.

bool isGood(void) const

Test data status.

const DVector* refDVect(void) const

Get a reference to the data vector.

const void* refData(void) const

Get a constant reference to the data.

void* refData(void)

Get a reference to the data.

void appName(const char* name)

Append a string to the series name.

void combineStatus(stat_t stat)

Set the data status.

int setData(const Time& t, const Interval& Step, const short* data, size_t N)

Set the series data.

int setData(const Time& t, const Interval& Step, const int* data, size_t N)

Set the series data.

int setData(const Time& t, const Interval& Step, const float* data, size_t N)

Set the series data.

int setData(const Time& t, const Interval& Step, const double* data, size_t N)

Set the series data.

int setData(const Time& t, const Interval& Step, const fComplex* data, size_t N)

Set the series data.

void setF0(float f0)

Set the heterodyne frequency.

void setName(const char* name)

Name a series.

void setStatus(stat_t stat)

Set the data status.

int Append(const Time& t, const Interval& Step, const short* data, size_t N)

Append data to the time series.

int Append(const Time& TS, const Interval& Step, const int* data, size_t N)

Append data to the time series.

int Append(const Time& TS, const Interval& Step, const float* data, size_t N)

Append data to the time series.

int Append(const Time& TS, const Interval& Step, const double* data, size_t N)

Append data to the time series.

int Append(const Time& TS, const Interval& Step, const fComplex* data, size_t N)

Append data to the time series.

int Append(const TSeries& t, size_t decim8=1)

Concatenate two TSeries.

void Convert(int type)

Convert the data vector type.

void ReSize(size_t len)

Expand the data vector.

void Clear(const Time& t0=Time(0), const Interval& dt=Interval(0.0))

Delete the series data.

TSeries fShift(double f0, double phi0=0) const

Up-convert (heterodyne) a time series.

TSeries& operator=(const TSeries& ts)

Assignment operator.

double operator*(const TSeries& y) const

Correlate two series.

TSeries operator/(const TSeries& y) const

Divide series by another.

TSeries& operator+=(double bias)

Bias a TSeries.

TSeries& operator-=(double bias)

Bias a TSeries.

TSeries& operator*=(double scale)

Scale a TSeries.

TSeries& operator/=(double scale)

Scale a TSeries.

TSeries& operator+=(const TSeries& rhs)

Add a TSeries.

TSeries& operator-=(const TSeries& rhs)

Subtract a TSeries.

typedef unsigned long size_t

Vector length data type.

typedef unsigned long stat_t

Data Status Type.

TSeries()

A time series object is initialized without a data vector.

TSeries(const TSeries& TS)

The argument series is duplicated into the new TSeries.

Parameters:

TS - Time series to be duplicated.

TSeries(const Time& t0, const Interval& dt)

A time series is created with a specified start time and sample interval, but no data.

Parameters:

t0 - Series start time.
dt - Step interval.

TSeries(const Time& t0, const Interval& dt, size_t NData, const float dData[]=0)

A float time series object is constructed and initialized from a float data array.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
dData - float array containing series data.

TSeries(const Time& t0, const Interval& dt, size_t NData, const short dData[])

A short time series object is constructed and initialized from a short data array.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
dData - short integer array containing series data.

TSeries(const Time& t0, const Interval& dt, size_t NData, const int dData[])

An integer time series object is constructed and initialized from a integer data array.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
dData - float array containing series data.

TSeries(const Time& t0, const Interval& dt, size_t NData, const double dData[])

A double float time series object is constructed and initialized from a double float data array.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
dData - double array containing series data.

TSeries(const Time& t0, const Interval& dt, size_t NData, const fComplex dData[])

A short time series object is constructed and initialized from a Complex data array.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
dData - Complex array containing series data.

TSeries(const Time& t0, const Interval& dt, size_t NData, const Chirp& func)

Construct a time series and initialize it from a specified signal template function.

Parameters:

t0 - Series start time.
dt - Time interval between two successive samples.
NData - Number of data words.
func - Template object based on a Chirp.

explicit TSeries(const FSeries& fs)

Construct a time series from an FSeries by inverse fft.

Parameters:

fs - Frequency Series.

~TSeries()

Blow away the DVector.

std::ostream& Dump(std::ostream& out) const

Write a formatted dump of the series contents to the specified output stream.

Returns:

reference to the specified output stream.

Parameters:

out - Output stream to receive the formatted TSeries dump.

TSeries decimate(size_t dec) const

A TSeries is decimated by the specified integer factor. The resulting series is returned. The first sample in the TSeries is included in the decimated TSeries.

Returns:

A decimated time series.

Parameters:

dec - Decimation factor.

TSeries decimate(size_t dec, Filter& xalias) const

A TSeries is filtered with an anti-aliasing filter and then decimated by the specified integer factor. The resulting series is returned.

Returns:

A decimated time series.

Parameters:

dec - Decimation factor.
xalias - Anti aliasing filter.

TSeries extract(const Time& t0, const Interval& dT=Interval(0.0)) const

A TSeries is returned containing the data from the time interval t0 - t0+dT. If dT == 0, all data after t0 will be returned.

Returns:

a TSeries containing the requested subset of the data.

Parameters:

t0 - Start time of the desired subset.
dT - Time duration of the desired subset.

void extend(const Time& t0)

The series is extended to the specified time by padding on the right with zeroes.

Parameters:

t0 - Desired series end-time.

size_t getBin(Time t) const

Get the bin index corresponding to the specified time.

Returns:

Index of the bin with time t.

Time getBinT(size_t inx) const

Get the time corresponding to the specified bin number.

Returns:

Time corresponding to the specified bin.

size_t getData(size_t len, short* data) const

The TSeries data are copied to a short int data buffer pointed to by 'data'. The data will be converted to 'short int's if the data vector is of a different data type. A maximum of 'len' data words will be copied to the data buffer.

Returns:

The number of words copied.

Parameters:

len - Maximum number of words to copy.
data - Short integer array into which the data will be copied.

size_t getData(size_t len, int* data) const

The TSeries data are copied to an integer data buffer pointed to by 'data'. The data will be converted to floats if the data vector is of a different data type. A maximum of 'len' data words will be copied to the data buffer. getData() returns the number of words copied.

Returns:

Number of words copied.

Parameters:

len - Dimension of output array.
data - Array to receive series data.

size_t getData(size_t len, float* data) const

The TSeries data are copied to a float data buffer pointed to by 'data'. The data will be converted to floats if the data vector is of a different data type. A maximum of 'len' data words will be copied to the data buffer. getData() returns the number of words copied.

Returns:

Number of words copied.

Parameters:

len - Dimension of output array.
data - Array to receive series data.

size_t getData(size_t len, double* data) const

The TSeries data are copied to a double data buffer pointed to by 'data'. The data will be converted to floats if the data vector is of a different data type. A maximum of 'len' data words will be copied to the data buffer. getData() returns the number of words copied.

Returns:

Number of words copied.

Parameters:

len - Dimension of output array.
data - Array to receive series data.

size_t getData(size_t len, fComplex* data) const

The TSeries data are copied to a Complex buffer pointed to by 'data'. The data will be converted to fComplex if the data vector is of a different data type. A maximum of 'len' data words will be copied to the data buffer. getData() returns the number of words copied.

Returns:

Number of words copied.

Parameters:

len - Dimension of output array
data - Array to receive series data.

double getDouble(size_t index) const

The specified entry is converted to double precision if necessary and returned.

Returns:

ith element value.

Parameters:

index - Index of the element to be returned.

Time getEndTime(void) const

The GPS time of the last plus one is returned as a Time object.

Returns:

End time of the series.

float getF0(void) const

getF0 returns the heterodyne frequency used if the time series was frequency shifted.

Returns:

Frequency used to down-convert frequencies.

Interval getInterval(void) const

Returns the total time duration of the time series.

Returns:

Time duration of the series.

const char* getName(void) const

Get a valid pointer to a zero-terminated string containing the series name. If the name is undefined a pointer to a null string is returned.

Returns:

a constant pointer to the series name string.

size_t getNSample(void) const

Returns the number of samples stored in the data vector.

Returns:

the number of samples.

Time getStartTime(void) const

Get the GPS time of the first sample represented as a Time object.

Returns:

Time of first sample.

Interval getTStep(void) const

The time bin width (the inverse of the sampling frequency) is returned as an Interval object.

Returns:

the sample time interval.

double getAverage(void) const

The average value of the data sequence is calculated. Zero is returned if the series is empty.

Returns:

Average data value.

double getMaximum(void) const

The maximum value of the data sequence is found. Zero is returned if the series is empty.

Returns:

Maximum data value.

double getMinimum(void) const

The minimum value in the sequence is found. Zero is returned if the series is empty.

Returns:

Minimum data value.

size_t getNBetween(double low, double high) const

Count the number of entries in the range low <= x < high.

Returns:

Number of entries greater than limit.

Parameters:

low - Lower limit.
high - Upper limit.

size_t getNGreater(double Limit) const

Count the number of entries greater than the specified value.

Returns:

Number of entries greater than limit.

Parameters:

low - Lower limit.

size_t getNLess(double Limit) const

Count the number of entries less than the specified value.

Returns:

Number of entries less than limit.

stat_t getStatus(void) const

Get the status information word.

Returns:

Data status word.

Parameters:

high - Upper limit.

bool isEmpty(void) const

Test if TSeries is empty.

Returns:

true if no data are available.

bool isGood(void) const

Test the data status. The data are considered good if the status word is zero.

Returns:

True if status indicates data are good.

const DVector* refDVect(void) const

Get a constant pointer to the data vector.

Returns:

a constant pointer to the data vector.

const void* refData(void) const

Get a constant reference to the data.

Returns:

a pointer to the data.

void* refData(void)

Get a reference to the data.

Returns:

a pointer to the data.

void appName(const char* name)

The specified character string is appended to the time series name string.

Parameters:

name - Constant pointer to a character array to be appended to the series name.

void combineStatus(stat_t stat)

Combine the data status word with the specified value.

Parameters:

stat - Status value.

int setData(const Time& t, const Interval& Step, const short* data, size_t N)

The supplied data are converted if necessary to the vector data type and copied to the series vector. If the vector is not defined, a vector of short integers will be created.

Returns:

0 if successful.

Parameters:

t - New series start time.
Step - New series sample interval.
data - Short integer array containing new sample
N - Number of data words in 'data'

int setData(const Time& t, const Interval& Step, const int* data, size_t N)

The supplied data are converted if necessary to the vector data type and copied to the series vector. If the vector is not defined, a vector of floats will be created.

Returns:

0 if successful.

Parameters:

t - New series start time.
Step - New series sample interval.
data - Float array containing new sample
N - Number of data words in 'data'

int setData(const Time& t, const Interval& Step, const float* data, size_t N)

The supplied data are converted if necessary to the vector data type and copied to the series vector. If the vector is not defined, a vector of floats will be created.

Returns:

0 if successful.

Parameters:

t - New series start time.
Step - New series sample interval.
data - Float array containing new sample
N - Number of data words in 'data'

int setData(const Time& t, const Interval& Step, const double* data, size_t N)

The supplied data are converted if necessary to the vector data type and copied to the series vector. If the vector is not defined, a vector of floats will be created.

Returns:

0 if successful.

Parameters:

t - New series start time.
Step - New series sample interval.
data - Float array containing new sample
N - Number of data words in 'data'

int setData(const Time& t, const Interval& Step, const fComplex* data, size_t N)

The supplied data are converted if necessary to the vector data type and copied to the series vector. If the vector is not defined, a vector of fComplex will be created.

Returns:

0 if successful.

Parameters:

t - New series start time.
Step - New series sample interval.
data - fComplex array containing new sample
N - Number of data words in 'data'

void setF0(float f0)

Store the specified frequency in the TSeries central frequency field. The data sre left unmodified. The central frequency is defined as the true frequency of the bin that is apparently DC.

Parameters:

f0 - Frequency to which the TSeries heterodyne frequency will be set.

void setName(const char* name)

The specified name is copied to the series name string.

Parameters:

constant - pointer to series name character array.

void setStatus(stat_t stat)

Set the data status word to the specified value.

Parameters:

stat - Status value.

int Append(const Time& t, const Interval& Step, const short* data, size_t N)

The specified data are converted if necessary to the series data type, and appended to the series. If data already exist in the vector, the end time of the existing data must match the start time of the new data. The step-size of the data to be appended must also match that of the existing data.

Returns:

0	successful
-1	start time isn't equal to the series end time
-2	sample intervals aren't equal

.

Parameters:

t - Start time of data to be appended to the series.
Step - sample interval of data to be appended to the series.
data - Short integer array containing the data to be appended.
N - Number of data words to be appended to the series.

int Append(const Time& TS, const Interval& Step, const int* data, size_t N)

The specified data are converted if necessary to the series data type, and appended to the series. If data already exist in the vector, the end time of the existing data must match the start time of the new data. The step-size of the data to be appended must also match that of the existing data.

Returns:

0	successful
-1	start time isn't equal to the current end time
-2	sample intervals aren't equal.

Parameters:

t - Start time of data to be appended to the series.
Step - sample interval of data to be appended to the series.
data - Float array containing the data to be appended.
N - Number of data words to be appended to the series.

int Append(const Time& TS, const Interval& Step, const float* data, size_t N)

The specified data are converted if necessary to the series data type, and appended to the series. If data already exist in the vector, the end time of the existing data must match the start time of the new data. The step-size of the data to be appended must also match that of the existing data.

Returns:

0	successful
-1	start time isn't equal to the current end time
-2	sample intervals aren't equal.

Parameters:

t - Start time of data to be appended to the series.
Step - sample interval of data to be appended to the series.
data - Float array containing the data to be appended.
N - Number of data words to be appended to the series.

int Append(const Time& TS, const Interval& Step, const double* data, size_t N)

The specified data are converted if necessary to the series data type, and appended to the series. If data already exist in the vector, the end time of the existing data must match the start time of the new data. The step-size of the data to be appended must also match that of the existing data.

Returns:

0	successful
-1	start time isn't equal to the current end time
-2	sample intervals aren't equal.

Parameters:

t - Start time of data to be appended to the series.
Step - sample interval of data to be appended to the series.
data - Float array containing the data to be appended.
N - Number of data words to be appended to the series.

int Append(const Time& TS, const Interval& Step, const fComplex* data, size_t N)

The specified data are converted if necessary to the series data type, and appended to the series. If data already exist in the vector, the end time of the existing data must match the start time of the new data. The step-size of the data to be appended must also match that of the existing data.

Returns:

0	successful
-1	start time isn't equal to the current end time
-2	sample intervals aren't equal.

Parameters:

t - Start time of data to be appended to the series.
Step - sample interval of data to be appended to the series.
data - Complex array containing the data to be appended.
N - Number of data words to be appended to the series.

int Append(const TSeries& t, size_t decim8=1)

The argument TSeries is optionally decimated and appended to the series. The starting time of the argument series must be equal to the end time of the existing data and the sample rate must be the same as the object sample rate. Decimation is not yet implemented.

Returns:

0	successful
-1	start time of TS not equal to the end time
-2	decimated sample rate isn't equal to the current rate.

Parameters:

TS - time series to be appended.
decim8 - decimation factor.

void Convert(int type)

The data vector is converted to the specified type. Valid types are those enumerated in DVector::DVType.

Parameters:

type - The type to which the series data are to be converted.

void ReSize(size_t len)

The data vector is extended to hold the specified number of data words. No action is taken if the vector can already hold the specified number of data words. The current data are copied if vector is reallocated.

Parameters:

len - Desired vector capacity in words.

void Clear(const Time& t0=Time(0), const Interval& dt=Interval(0.0))

The current data vector length is set to zero. The data vector remains allocated with the original storage capacity. The start time and sample interval may be reset or are placed in a "don't care" state. The series name is left unchanged.

Parameters:

t0 - New start time. By default the time is zeroed.
dt - New sample interval. By default the interval is zeroed.

TSeries fShift(double f0, double phi0=0) const

fShift up-converts (heterodynes) the time series by the specified frequency shift. The resulting data vector will be of fComplex type. The sign of the frequency shift is such that the DC bin is converted to the shift frequency. The TSeries f0 value is decreasedby an equal amount.

Returns:

A complex TSeries with the heterodyned data.

Parameters:

f0 - heterodyne frequency.
phi0 - Phase shift of the first sample (defaults to 0).

TSeries& operator=(const TSeries& ts)

The TSeries data are copied to the current TSeries. The current TSeries type and name remain unchanged.

Returns:

reference to the updated TSeries.

Parameters:

TS - Constant TSeries to be copied.

double operator*(const TSeries& y) const

Take a dot product of the two data vectors.

Returns:

Correlation coefficient ().

TSeries operator/(const TSeries& y) const

Divide two series on an element-by-element basis.

Returns:

Float seies containing the ratio of the arguments.

Parameters:

Divisor - series.

TSeries& operator+=(double bias)

The argument value is converted to the TSeries data type and added to each element of the time series.

Returns:

reference to the modified TSeries.

Parameters:

bias - Value added to each element.

TSeries& operator-=(double bias)

The argument value is converted to the TSeries data type and subtracted from each element of the time series.

Returns:

reference to the modified TSeries.

Parameters:

bias - Value subtracted from each element.

TSeries& operator*=(double scale)

Each element of the time series is multiplied by the rhs value. The result is converted to the series data type and replaces the original series.

Returns:

reference to the modified TSeries.

Parameters:

scale - Value used to multiply each element.

TSeries& operator/=(double scale)

Each element of the time series is divided by the rhs value. The result is converted to the series data type and replaces the original series.

Returns:

reference to the modified TSeries.

Parameters:

scale - Value used to divide each element.

TSeries& operator+=(const TSeries& rhs)

Each element of the time series is incremented by the corresponding element of the argument.

Returns:

reference to the modified TSeries.

Parameters:

rhs - TSeries to be added to the current TSeries.

TSeries& operator-=(const TSeries& rhs)

Each element of the time series is decremented by the corresponding element of the argument.

Returns:

reference to the difference TSeries.

Parameters:

rhs - TSeries to be subtracted from the current TSeries.

This class has no child classes.

Author:

John G. Zweizig

Version:

1.2; Last modified Sep 29, 1999

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