Initial import

validation/data_validator.cpp

@@ -0,0 +1,162 @@
+/****************************************************************************
+ *
+ *   Copyright (c) 2015 PX4 Development Team. All rights reserved.
+ *
+ * Redistribution and use in source and binary forms, with or without
+ * modification, are permitted provided that the following conditions
+ * are met:
+ *
+ * 1. Redistributions of source code must retain the above copyright
+ *    notice, this list of conditions and the following disclaimer.
+ * 2. Redistributions in binary form must reproduce the above copyright
+ *    notice, this list of conditions and the following disclaimer in
+ *    the documentation and/or other materials provided with the
+ *    distribution.
+ * 3. Neither the name PX4 nor the names of its contributors may be
+ *    used to endorse or promote products derived from this software
+ *    without specific prior written permission.
+ *
+ * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+ * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+ * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
+ * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+ * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
+ * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
+ * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS
+ * OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED
+ * AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT
+ * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
+ * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
+ * POSSIBILITY OF SUCH DAMAGE.
+ *
+ ****************************************************************************/
+
+/**
+ * @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) :
+	_time_last(0),
+	_timeout_interval(20000),
+	_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},
+	_value_equal_count(0),
+	_sibling(prev_sibling)
+{
+
+}
+
+DataValidator::~DataValidator()
+{
+
+}
+
+void
+DataValidator::put(uint64_t timestamp, float val[3], 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;
+			}
+		}
+
+		// XXX replace with better filter, make it auto-tune to update rate
+		_lp[i] = _lp[i] * 0.5f + val[i] * 0.5f;
+
+		_value[i] = val[i];
+	}
+
+	_time_last = timestamp;
+}
+
+float
+DataValidator::confidence(uint64_t timestamp)
+{
+	/* check if we have any data */
+	if (_time_last == 0) {
+		return 0.0f;
+	}
+
+	/* check error count limit */
+	if (_error_count > NORETURN_ERRCOUNT) {
+		return 0.0f;
+	}
+
+	/* we got the exact same sensor value N times in a row */
+	if (_value_equal_count > VALUE_EQUAL_COUNT_MAX) {
+		return 0.0f;
+	}
+
+	/* timed out - that's it */
+	if (timestamp - _time_last > _timeout_interval) {
+		return 0.0f;
+	}
+
+	/* cap error density counter at window size */
+	if (_error_density > ERROR_DENSITY_WINDOW) {
+		_error_density = ERROR_DENSITY_WINDOW;
+	}
+
+	/* return local error density for last N measurements */
+	return 1.0f - (_error_density / ERROR_DENSITY_WINDOW);
+}
+
+int
+DataValidator::priority()
+{
+	return _priority;
+}
+
+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()));
+	}
+}