WPILibC++ 2024.3.2

This class implements a linear, digital filter. More...
#include <frc/filter/LinearFilter.h>
Public Member Functions  
LinearFilter (std::span< const double > ffGains, std::span< const double > fbGains)  
Create a linear FIR or IIR filter. More...  
LinearFilter (std::initializer_list< double > ffGains, std::initializer_list< double > fbGains)  
Create a linear FIR or IIR filter. More...  
void  Reset () 
Reset the filter state. More...  
void  Reset (std::span< const double > inputBuffer, std::span< const double > outputBuffer) 
Resets the filter state, initializing internal buffers to the provided values. More...  
T  Calculate (T input) 
Calculates the next value of the filter. More...  
T  LastValue () const 
Returns the last value calculated by the LinearFilter. More...  
Static Public Member Functions  
static LinearFilter< T >  SinglePoleIIR (double timeConstant, units::second_t period) 
Creates a onepole IIR lowpass filter of the form: y[n] = (1  gain) x[n] + gain y[n1] where gain = e^{dt / T}, T is the time constant in seconds. More...  
static LinearFilter< T >  HighPass (double timeConstant, units::second_t period) 
Creates a firstorder highpass filter of the form: y[n] = gain x[n] + (gain) x[n1] + gain y[n1] where gain = e^{dt / T}, T is the time constant in seconds. More...  
static LinearFilter< T >  MovingAverage (int taps) 
Creates a Ktap FIR moving average filter of the form: y[n] = 1/k (x[k] + x[k1] + … + x[0]) More...  
template<int Derivative, int Samples>  
static LinearFilter< T >  FiniteDifference (const wpi::array< int, Samples > stencil, units::second_t period) 
Creates a finite difference filter that computes the nth derivative of the input given the specified stencil points. More...  
template<int Derivative, int Samples>  
static LinearFilter< T >  BackwardFiniteDifference (units::second_t period) 
Creates a backward finite difference filter that computes the nth derivative of the input given the specified number of samples. More...  
This class implements a linear, digital filter.
All types of FIR and IIR filters are supported. Static factory methods are provided to create commonly used types of filters.
Filters are of the form:
y[n] = (b0 x[n] + b1 x[n1] + … + bP x[nP])  (a0 y[n1] + a2 y[n2] + … + aQ y[nQ])
Where:
y[n] is the output at time "n"
x[n] is the input at time "n"
y[n1] is the output from the LAST time step ("n1")
x[n1] is the input from the LAST time step ("n1")
b0 … bP are the "feedforward" (FIR) gains
a0 … aQ are the "feedback" (IIR) gains
IMPORTANT! Note the "" sign in front of the feedback term! This is a common convention in signal processing.
What can linear filters do? Basically, they can filter, or diminish, the effects of undesirable input frequencies. High frequencies, or rapid changes, can be indicative of sensor noise or be otherwise undesirable. A "low pass" filter smooths out the signal, reducing the impact of these high frequency components. Likewise, a "high pass" filter gets rid of slowmoving signal components, letting you detect large changes more easily.
Example FRC applications of filters:
For more on filters, we highly recommend the following articles:
https://en.wikipedia.org/wiki/Linear_filter
https://en.wikipedia.org/wiki/Iir_filter
https://en.wikipedia.org/wiki/Fir_filter
Note 1: Calculate() should be called by the user on a known, regular period. You can use a Notifier for this or do it "inline" with code in a periodic function.
Note 2: For ALL filters, gains are necessarily a function of frequency. If you make a filter that works well for you at, say, 100Hz, you will most definitely need to adjust the gains if you then want to run it at 200Hz! Combining this with Note 1  the impetus is on YOU as a developer to make sure Calculate() gets called at the desired, constant frequency!

inline 
Create a linear FIR or IIR filter.
ffGains  The "feedforward" or FIR gains. 
fbGains  The "feedback" or IIR gains. 

inline 
Create a linear FIR or IIR filter.
ffGains  The "feedforward" or FIR gains. 
fbGains  The "feedback" or IIR gains. 

inlinestatic 
Creates a backward finite difference filter that computes the nth derivative of the input given the specified number of samples.
For example, a first derivative filter that uses two samples and a sample period of 20 ms would be
LinearFilter<double>::BackwardFiniteDifference<1, 2>(20_ms);
Derivative  The order of the derivative to compute. 
Samples  The number of samples to use to compute the given derivative. This must be one more than the order of derivative or higher. 
period  The period in seconds between samples taken by the user. 

inline 
Calculates the next value of the filter.
input  Current input value. 

inlinestatic 
Creates a finite difference filter that computes the nth derivative of the input given the specified stencil points.
Stencil points are the indices of the samples to use in the finite difference. 0 is the current sample, 1 is the previous sample, 2 is the sample before that, etc. Don't use positive stencil points (samples from the future) if the LinearFilter will be used for streambased online filtering (e.g., taking derivative of encoder samples in realtime).
Derivative  The order of the derivative to compute. 
Samples  The number of samples to use to compute the given derivative. This must be one more than the order of the derivative or higher. 
stencil  List of stencil points. 
period  The period in seconds between samples taken by the user. 

inlinestatic 
Creates a firstorder highpass filter of the form:
y[n] = gain x[n] + (gain) x[n1] + gain y[n1]
where gain = e^{dt / T}, T is the time constant in seconds.
Note: T = 1 / (2 pi f) where f is the cutoff frequency in Hz, the frequency below which the input starts to attenuate.
This filter is stable for time constants greater than zero.
timeConstant  The discretetime time constant in seconds. 
period  The period in seconds between samples taken by the user. 

inline 
Returns the last value calculated by the LinearFilter.

inlinestatic 
Creates a Ktap FIR moving average filter of the form:
y[n] = 1/k (x[k] + x[k1] + … + x[0])
This filter is always stable.
taps  The number of samples to average over. Higher = smoother but slower 
std::runtime_error  if number of taps is less than 1. 

inline 
Reset the filter state.

inline 
Resets the filter state, initializing internal buffers to the provided values.
These are the expected lengths of the buffers, depending on what type of linear filter used:
Type  Input Buffer Size  Output Buffer Size 

Unspecified  size of ffGains  size of fbGains 
Single Pole IIR  1  1 
HighPass  2  1 
Moving Average  taps  0 
Finite Difference  size of stencil  0 
Backward Finite Difference  Samples  0 
inputBuffer  Values to initialize input buffer. 
outputBuffer  Values to initialize output buffer. 
std::runtime_error  if size of inputBuffer or outputBuffer does not match the size of ffGains and fbGains provided in the constructor. 

inlinestatic 
Creates a onepole IIR lowpass filter of the form:
y[n] = (1  gain) x[n] + gain y[n1]
where gain = e^{dt / T}, T is the time constant in seconds.
Note: T = 1 / (2 pi f) where f is the cutoff frequency in Hz, the frequency above which the input starts to attenuate.
This filter is stable for time constants greater than zero.
timeConstant  The discretetime time constant in seconds. 
period  The period in seconds between samples taken by the user. 