text: /****************************************************************************
   *
   *   Copyright (c) 2015 PX4 Development Team. All rights reserved.
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   *    notice, this list of conditions and the following disclaimer.
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   *
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  /**
   * @file data_validator.c
   *
   * A data validation class to identify anomalies in data streams
   *
   * @author Lorenz Meier <lorenz@px4.io>
   */
  
  #include "data_validator.h"
  #include <ecl/ecl.h>
  
  DataValidator::DataValidator(DataValidator *prev_sibling) :
  	_error_mask(ERROR_FLAG_NO_ERROR),
  	_timeout_interval(20000),
  	_time_last(0),
  	_event_count(0),
  	_error_count(0),
  	_error_density(0),
  	_priority(0),
  	_mean{0.0f},
  	_lp{0.0f},
  	_M2{0.0f},
  	_rms{0.0f},
  	_value{0.0f},
  	_vibe{0.0f},
  	_value_equal_count(0),
  	_sibling(prev_sibling)
  {
  
  }
  
  DataValidator::~DataValidator()
  {
  
  }
  
  void
  DataValidator::put(uint64_t timestamp, float val, uint64_t error_count_in, int priority_in)
  {
  	float data[dimensions] = { val }; //sets the first value and all others to 0
  
  	put(timestamp, data, error_count_in, priority_in);
  }
  
  void
  DataValidator::put(uint64_t timestamp, float val[dimensions], uint64_t error_count_in, int priority_in)
  {
  	_event_count++;
  
  	if (error_count_in > _error_count) {
  		_error_density += (error_count_in - _error_count);
  	} else if (_error_density > 0) {
  		_error_density--;
  	}
  
  	_error_count = error_count_in;
  	_priority = priority_in;
  
  	for (unsigned i = 0; i < dimensions; i++) {
  		if (_time_last == 0) {
  			_mean[i] = 0;
  			_lp[i] = val[i];
  			_M2[i] = 0;
  		} else {
  			float lp_val = val[i] - _lp[i];
  
  			float delta_val = lp_val - _mean[i];
  			_mean[i] += delta_val / _event_count;
  			_M2[i] += delta_val * (lp_val - _mean[i]);
  			_rms[i] = sqrtf(_M2[i] / (_event_count - 1));
  
  			if (fabsf(_value[i] - val[i]) < 0.000001f) {
  				_value_equal_count++;
  			} else {
  				_value_equal_count = 0;
  			}
  		}
  
  		_vibe[i] = _vibe[i] * 0.99f + 0.01f * fabsf(val[i] - _lp[i]);
  
  		// XXX replace with better filter, make it auto-tune to update rate
  		_lp[i] = _lp[i] * 0.99f + 0.01f * val[i];
  
  		_value[i] = val[i];
  	}
  
  	_time_last = timestamp;
  }
  
  float
  DataValidator::confidence(uint64_t timestamp)
  {
  	float ret = 1.0f;
  	
  	/* check if we have any data */
  	if (_time_last == 0) {
  		_error_mask |= ERROR_FLAG_NO_DATA;
  		ret = 0.0f;
  
  	/* timed out - that's it */
  	} else if (timestamp - _time_last > _timeout_interval) {
  		_error_mask |= ERROR_FLAG_TIMEOUT;
  		ret = 0.0f;
  
  	/* we got the exact same sensor value N times in a row */
  	} else if (_value_equal_count > VALUE_EQUAL_COUNT_MAX) {
  		_error_mask |= ERROR_FLAG_STALE_DATA;
  		ret = 0.0f;
  
  	/* check error count limit */
  	} else if (_error_count > NORETURN_ERRCOUNT) {
  		_error_mask |= ERROR_FLAG_HIGH_ERRCOUNT;
  		ret = 0.0f;
  
  	/* cap error density counter at window size */
  	} else if (_error_density > ERROR_DENSITY_WINDOW) {
  		_error_mask |= ERROR_FLAG_HIGH_ERRDENSITY;
  		_error_density = ERROR_DENSITY_WINDOW;
  
  	/* no error */
  	} else {
  		_error_mask = ERROR_FLAG_NO_ERROR;
  	}
  	
  	/* no critical errors */
  	if (ret > 0.0f) {
  		/* return local error density for last N measurements */
  		ret = 1.0f - (_error_density / ERROR_DENSITY_WINDOW);
  	}
  	
  	return ret;
  }
  
  void
  DataValidator::print()
  {
  	if (_time_last == 0) {
  		ECL_INFO("\tno data");
  		return;
  	}
  
  	for (unsigned i = 0; i < dimensions; i++) {
  		ECL_INFO("\tval: %8.4f, lp: %8.4f mean dev: %8.4f RMS: %8.4f conf: %8.4f",
  			(double) _value[i], (double)_lp[i], (double)_mean[i],
  			(double)_rms[i], (double)confidence(hrt_absolute_time()));
  	}
  }
  