mirror of https://github.com/ArduPilot/ardupilot
Filter: automatically cope with duplicate timestamps
this makes it easier for callers to avoid excessive slope calculations Thanks to Jon Challinger for the idea
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@ -18,17 +18,35 @@
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template <class T, uint8_t FILTER_SIZE>
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template <class T, uint8_t FILTER_SIZE>
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void DerivativeFilter<T,FILTER_SIZE>::update(T sample, uint32_t timestamp)
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void DerivativeFilter<T,FILTER_SIZE>::update(T sample, uint32_t timestamp)
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{
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{
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uint8_t i = FilterWithBuffer<T,FILTER_SIZE>::sample_index;
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uint8_t i1;
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if (i == 0) {
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i1 = FILTER_SIZE-1;
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} else {
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i1 = i-1;
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}
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if (_timestamps[i1] == timestamp) {
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// this is not a new timestamp - ignore
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return;
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}
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// add timestamp before we apply to FilterWithBuffer
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// add timestamp before we apply to FilterWithBuffer
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_timestamps[FilterWithBuffer<T,FILTER_SIZE>::sample_index] = timestamp;
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_timestamps[i] = timestamp;
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// call parent's apply function to get the sample into the array
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// call parent's apply function to get the sample into the array
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FilterWithBuffer<T,FILTER_SIZE>::apply(sample);
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FilterWithBuffer<T,FILTER_SIZE>::apply(sample);
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_new_data = true;
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}
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}
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template <class T, uint8_t FILTER_SIZE>
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template <class T, uint8_t FILTER_SIZE>
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float DerivativeFilter<T,FILTER_SIZE>::slope(void)
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float DerivativeFilter<T,FILTER_SIZE>::slope(void)
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{
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{
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if (!_new_data) {
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return _last_slope;
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}
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float result = 0;
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float result = 0;
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// use f() to make the code match the maths a bit better. Note
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// use f() to make the code match the maths a bit better. Note
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@ -74,6 +92,9 @@ float DerivativeFilter<T,FILTER_SIZE>::slope(void)
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break;
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break;
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}
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}
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_new_data = false;
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_last_slope = result;
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return result;
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return result;
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}
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}
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@ -36,7 +36,8 @@ class DerivativeFilter : public FilterWithBuffer<T,FILTER_SIZE>
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virtual void reset();
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virtual void reset();
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private:
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private:
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uint32_t _last_time;
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bool _new_data;
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float _last_slope;
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// microsecond timestamps for samples. This is needed
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// microsecond timestamps for samples. This is needed
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// to cope with non-uniform time spacing of the data
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// to cope with non-uniform time spacing of the data
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