icl::cv::Extrapolator< valueType, timeType > Class Template Reference

class for linear and quadatic extrapolation More...

#include <Extrapolator.h>

Static Public Member Functions
static valueType	predict (valueType x2, valueType x1)
	extrapolates the next value (time t) using linear interpolation More...
static valueType	predict (valueType x3, valueType x2, valueType x1)
	extrapolates the next value using quadratic interpolation More...
static valueType	predict (valueType x2, timeType t2, valueType x1, timeType t1, timeType t)
	linear interpolation, but with timestamped value More...
static valueType	predict (valueType x3, timeType t3, valueType x2, timeType t2, valueType x1, timeType t1, timeType t)
	quadratic interpolation, but with timestamped value More...
static valueType	predict (int n, valueType *xs, timeType *ts=0, timeType t=timeType(0))
	generic interpolation function abstracting from number of mesh points availability of timestamps More...

Detailed Description

template<class valueType, class timeType>
class icl::cv::Extrapolator< valueType, timeType >

class for linear and quadatic extrapolation

The Extrapolator class is designed as template and abstracts from the type of the values as well as from the type that is used to indicate time stamps for values.

The template is explicitly intantiated for value type icl32f and the time types long int, int and icl32f

Member Function Documentation

predict() [1/5]

template<class valueType , class timeType >

static valueType icl::cv::Extrapolator< valueType, timeType >::predict ( valueType  x2, valueType  x1  )

static

extrapolates the next value (time t) using linear interpolation

The time series is x_2(t-2),x_1(t-1),result(t) \; with \; dt=1

Parameters

x2	first value at time t-2
x1	second value at time t-1

Returns

extrapolated value at time t

predict() [2/5]

template<class valueType , class timeType >

static valueType icl::cv::Extrapolator< valueType, timeType >::predict ( valueType  x3, valueType  x2, valueType  x1  )

static

extrapolates the next value using quadratic interpolation

The time series is x3@t-3 x2@t-2 x1@t-1 result@t with dt=1

Parameters

x3	second value at time t-3
x2	first value at time t-2
x1	second value at time t-1

Returns

extrapolated value at time t

predict() [3/5]

template<class valueType , class timeType >

static valueType icl::cv::Extrapolator< valueType, timeType >::predict ( valueType  x2, timeType  t2, valueType  x1, timeType  t1, timeType  t  )

static

linear interpolation, but with timestamped value

The time series is ... x2(t2) x1(t1) result(t)

Parameters

x2	third value at time t2
t2	time stamp for value x2
x1	third value at time t1
t1	time stamp for value x1
t	time stamp for the returned value

Returns

extrapolated value at time t

predict() [4/5]

template<class valueType , class timeType >

static valueType icl::cv::Extrapolator< valueType, timeType >::predict ( valueType  x3, timeType  t3, valueType  x2, timeType  t2, valueType  x1, timeType  t1, timeType  t  )

static

quadratic interpolation, but with timestamped value

The time series is ... x3(t3) x2(t2) x1(t1) result(t)

Parameters

x3	third value at time t3
t3	time stamp for value x3
x2	third value at time t2
t2	time stamp for value x2
x1	third value at time t1
t1	time stamp for value x1
t	time stamp for the returned value

Returns

extrapolated value at time t

predict() [5/5]

template<class valueType , class timeType >

static valueType icl::cv::Extrapolator< valueType, timeType >::predict ( int  n, valueType *  xs, timeType *  ts = 0, timeType  t = timeType(0)  )

static

generic interpolation function abstracting from number of mesh points availability of timestamps

In valueTypetime environments, not every time 3 mesh points for the extrapolation are available. To avoid the necessity of switching between the cases of a different mesh point counts, this function provides a generic interface.

Please considere, that n must be one of {1,2,3} and t must not be 0 if ts is given

If n is 1, the prediction returns the current value *xs.

If n is 2, the prediction returns the first order extrapolated next value:

dt1 = t1 - t2              for ts=NULL: return x1 + x1 - p2
dt0 = t - t1
v1 = (x1-x2)/dt1
return x1 + dt0*v1

If n is 3, the prediction returns the second order extraploated next value:

dt2 = t2 - t3              for ts=NULL: v1 = p1-p2
dt1 = t1 - t2                           a = v1-( p2-p3 )
dt0 = t - t1                            return p1 + v1 +  a/2.0
v2 = (x2-x3)/dt2
v1 = (x1-x2)/dt1
a = (v1-v2)/((dt1+dt2)/2)
return x1 + dt0*v1 + (dt0*dt0)/2.0 * a

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The documentation for this class was generated from the following file:

• /Users/alneuman/vm/icl/ICLCV/src/ICLCV/Extrapolator.h