/*
* @file	pid_from_msl.cpp
*
* @date Oct 5, 2019
* @author andreika, (c) 2019
*/

#include "global.h"
#include <fstream>
#include <vector>

#include "pid_auto.h"


class MslData {
public:
	bool readMsl(const char *fname, double startTime, double endTime, int inputIdx, int outputIdx) {
		std::ifstream fp(fname);

		if (!fp)
			return false;
		
		curIdx = -1;
		settings.minValue = settings.maxValue = settings.maxPoint = 0;
		settings.timeScale = 1,
		settings.stepPoint = -1.0;
		totalTime = 0;

		std::string str;
		for (int i = 0; std::getline(fp, str); i++) {
			// data starts at 4th line
			if (i < 4)
				continue;
			parseLine(str, startTime, endTime, inputIdx, outputIdx);
		}
		
		settings.maxPoint = getSaturationStartPoint();
		assert(data.size() == curIdx);

		settings.timeScale = settings.maxPoint / totalTime;

		fp.close();
		return true;
	}

	bool parseLine(const std::string & str, double startTime, double endTime, int inputIdx, int outputIdx) {
		std::stringstream sstr(str);
		std::string item;
		for (int j = 0; getline(sstr, item, '\t'); j++) {
			double v = atof(item.c_str());
			// the first column is timestamp
			if (j == 0) {
				if (v < startTime || v > endTime)
					return false;
				if (curIdx < 0)
					prevTime = v;
				totalTime += v - prevTime;
				prevTime = v;
			} else if (j == inputIdx) {
				// this is an input step, we should find it
				if (curIdx < 0) {
					settings.minValue = v;
					curIdx = 0;
				} else if (v != settings.minValue && settings.stepPoint < 0) {
					settings.maxValue = v;
					settings.stepPoint = curIdx;
				}
				curIdx++;
			} else if (j == outputIdx) {
				/*const float alpha = 0.5f;
				float fv = alpha * prevV + (1.0f - alpha) * (float)v;
				prevV = v;
				data.push_back(fv);*/
				data.push_back((float)v);
				if (curIdx >= 0 && settings.stepPoint < 0) {
					// calculate averaged level to determine the acceptable noise level
					averagedMin = (averagedMin * (curIdx - 1) + v) / curIdx;
					// this is not accurate because 'averagedMin' is continuously changing
					acceptableNoiseLevel = std::max(acceptableNoiseLevel, abs(v - averagedMin));
				}
			}
		}
		return true;
	}

	double getSaturationStartPoint() {
		int i;
		double j;
		// max noise level is used to get the saturation limit of the signal
		double curNoiseLevel = 0, averagedMax = 0;
		// we step back some points from the last one and find the saturation start
		for (i = curIdx - 1, j = 1.0; i > settings.stepPoint; i--, j += 1.0) {
			double v = data[i];
			averagedMax = (averagedMax * (j - 1) + v) / j;
			// this is not accurate because 'averagedMax' is continuously changing
			curNoiseLevel = std::max(curNoiseLevel, abs(v - averagedMax));
			
			// we assume that the "upper" level noise is like the same as the "lower" noise, so we compare them,
			// and if the noise level starts growing, then we're in the step transient zone, and we stop
			if (curNoiseLevel > acceptableNoiseLevel) {
				break;
			}
		}
		// return the point in the middle, just to be safe (we don't want to be close to the transient zone)
		return (curIdx - 1 + i) / 2;
	}

public:
	std::vector<float> data;
	double totalTime = 0, prevTime = 0;
	PidAutoTuneSettings settings;
	int curIdx = -1;
	float prevV = 0;
	
	// we assume that the signal is quasi-stable (asymptotic) from the start point until the 'stepPoint';
	// it's noise level is used to find the saturation limit of the rest of the data (see getSaturationStartPoint())
	double acceptableNoiseLevel = 0;
	double averagedMin = 0;
};

#if 1
int main(int argc, char **argv) {
	if (argc < 6) {
		printf("Usage: PID_FROM_MSL file.msl start_time end_time input_column output_column...\r\n");
		return -1;
	}
	
	printf("PID_FROM_MSL - find PID controller coefficients based on a measured step response in a rusEFI log file.\r\n");
	printf("Version 0.1 (c) andreika, 2019\r\n\r\n");
	printf("Reading file %s...\r\n", argv[1]);
	
	MslData data;
	if (!data.readMsl(argv[1], atof(argv[2]), atof(argv[3]), atoi(argv[4]), atoi(argv[5]))) {
		return -2;
	}

	printf("Measuring Settings: minValue=%g maxValue=%g stepPoint=%g maxPoint=%g numPoints=%d timeScale=%g\r\n",
		data.settings.minValue, data.settings.maxValue, data.settings.stepPoint, data.settings.maxPoint, data.data.size(), data.settings.timeScale);

	PidAutoTune chr1, chr2;

	for (size_t i = 0; i < data.data.size(); i++) {
		chr1.addData(data.data[i]);
		chr2.addData(data.data[i]);
	}

	// todo: more flexible method chooser
	PidTuneMethod method = PID_TUNE_AUTO1;
	printf("\r\nTrying method Auto1:\r\n");
	chr1.findPid(method, data.settings, nullptr);
	
	method = PID_TUNE_AUTO2;
	printf("\r\nTrying method Auto2:\r\n");
	chr2.findPid(method, data.settings, nullptr);

	printf("Done!\r\n");

	// todo: is it correct?
	double dTime = 1.0 / data.settings.timeScale;
	const int numSimPoints = 1024;

	PidAutoTune *chr[2] = { &chr1, &chr2 };
	for (int k = 0; k < 2; k++) {
		const double *p = chr[k]->getParams();
		printf("Model-%d Params: K=%g T1=%g T2=%g L=%g\r\n", (k + 1), p[PARAM_K], p[PARAM_T], p[PARAM_T2], p[PARAM_L]);
		const pid_s pid0 = chr[k]->getPid0();
		const pid_s pid = chr[k]->getPid();
		printf("  PID0: P=%.8f I=%.8f D=%.8f offset=%.8f\r\n", pid0.pFactor, pid0.iFactor, pid0.dFactor, pid0.offset);

		PidSimulator<numSimPoints> sim(chr[k]->getMethodOrder(method), chr[k]->getAvgMeasuredMin(), chr[k]->getAvgMeasuredMax(), dTime, true);
		PidAccuracyMetric metric0 = sim.simulate(numSimPoints, pid0, p);
		printf("  Metric0 result: ITAE=%g ISE=%g Overshoot=%g%%\r\n", metric0.getItae(), metric0.getIse(), metric0.getMaxOvershoot() * 100.0);

		printf("  PID:  P=%.8f I=%.8f D=%.8f offset=%.8f\r\n", pid.pFactor, pid.iFactor, pid.dFactor, pid.offset);
		PidAccuracyMetric metric = sim.simulate(numSimPoints, pid, p);
		printf("  Metric result:  ITAE=%g ISE=%g Overshoot=%g%%\r\n", metric.getItae(), metric.getIse(), metric.getMaxOvershoot() * 100.0);
	}

	return 0;
}
#endif