Revert "Added Power Spectral Density curves at the spectrum chart (Completion of #820 PR)" (#830)

Revert "Added Power Spectral Density curves at the spectrum chart (Completion…"

This reverts commit cd62b52.

Author: demvlad

index.html

@@ -459,7 +459,6 @@ <h4>Workspace</h4>
                                 <option value="1">Freq. vs Throttle</option>
                                 <option value="3">Freq. vs RPM</option>
                                 <option value="2">Error vs Setpoint</option>
-                                <option value="4">Power spectral density</option>
                             </select>
                         </div>
 

src/graph_spectrum.js

@@ -116,10 +116,6 @@ export function FlightLogAnalyser(flightLog, canvas, analyserCanvas) {
           fftData = GraphSpectrumCalc.dataLoadPidErrorVsSetpoint();
           break;
 
-        case SPECTRUM_TYPE.POWER_SPECTRAL_DENSITY:
-          fftData = GraphSpectrumCalc.dataLoadPSD(analyserZoomY);
-          break;
-
         case SPECTRUM_TYPE.FREQUENCY:
         default:
           fftData = GraphSpectrumCalc.dataLoadFrequency();
@@ -191,11 +187,6 @@ export function FlightLogAnalyser(flightLog, canvas, analyserCanvas) {
         debounce(100, function () {
           analyserZoomY = 1 / (analyserZoomYElem.val() / 100);
           GraphSpectrumPlot.setZoom(analyserZoomX, analyserZoomY);
-          // Recalculate PSD with updated samples per segment count
-          if (userSettings.spectrumType == SPECTRUM_TYPE.POWER_SPECTRAL_DENSITY) {
-            dataLoad();
-            GraphSpectrumPlot.setData(fftData, userSettings.spectrumType);
-          }
           that.refresh();
         })
       )

src/graph_spectrum_calc.js

@@ -106,33 +106,6 @@ GraphSpectrumCalc.dataLoadFrequency = function() {
   return fftData;
 };
 
-GraphSpectrumCalc.dataLoadPSD = function(analyserZoomY) {
-  const flightSamples = this._getFlightSamplesFreq(false);
-
-  let pointsPerSegment = 512;
-  const multipiler = Math.floor(1 / analyserZoomY); // 0. ... 10
-  if (multipiler == 0) {
-    pointsPerSegment = 256;
-  } else if (multipiler > 1) {
-    pointsPerSegment *= 2 ** Math.floor(multipiler / 2);
-  }
-  pointsPerSegment = Math.min(pointsPerSegment, flightSamples.samples.length);
-  const overlapCount = Math.floor(pointsPerSegment / 2);
-
-  const psd =  this._psd(flightSamples.samples, pointsPerSegment, overlapCount);
-
-  const psdData = {
-    fieldIndex   : this._dataBuffer.fieldIndex,
-    fieldName  : this._dataBuffer.fieldName,
-    psdLength  : psd.psdOutput.length,
-    psdOutput  : psd.psdOutput,
-    blackBoxRate : this._blackBoxRate,
-    minimum: psd.min,
-    maximum: psd.max,
-    maxNoiseIdx: psd.maxNoiseIdx,
-  };
-  return psdData;
-};
 
 GraphSpectrumCalc._dataLoadFrequencyVsX = function(vsFieldNames, minValue = Infinity, maxValue = -Infinity) {
 
@@ -310,7 +283,7 @@ GraphSpectrumCalc._getFlightChunks = function() {
   return allChunks;
 };
 
-GraphSpectrumCalc._getFlightSamplesFreq = function(scaled = true) {
+GraphSpectrumCalc._getFlightSamplesFreq = function() {
 
   const allChunks = this._getFlightChunks();
 
@@ -320,11 +293,7 @@ GraphSpectrumCalc._getFlightSamplesFreq = function(scaled = true) {
   let samplesCount = 0;
   for (const chunk of allChunks) {
     for (const frame of chunk.frames) {
-      if (scaled) {
-        samples[samplesCount] = this._dataBuffer.curve.lookupRaw(frame[this._dataBuffer.fieldIndex]);
-      } else {
-        samples[samplesCount] = frame[this._dataBuffer.fieldIndex];
-      }
+      samples[samplesCount] = (this._dataBuffer.curve.lookupRaw(frame[this._dataBuffer.fieldIndex]));
       samplesCount++;
     }
   }
@@ -515,116 +484,3 @@ GraphSpectrumCalc._normalizeFft = function(fftOutput, fftLength) {
 
   return fftData;
 };
-
-/**
- * Compute PSD for data samples by Welch method follow Python code
- */
-GraphSpectrumCalc._psd  = function(samples, pointsPerSegment, overlapCount, scaling = 'density') {
-// Compute FFT for samples segments
-  const fftOutput = this._fft_segmented(samples, pointsPerSegment, overlapCount);
-
-  const dataCount = fftOutput[0].length;
-  const segmentsCount = fftOutput.length;
-  const psdOutput = new Float64Array(dataCount);
-
-// Compute power scale coef
-  let scale = 1;
-  if (userSettings.analyserHanning) {
-    const window = Array(pointsPerSegment).fill(1);
-    this._hanningWindow(window, pointsPerSegment);
-    if (scaling == 'density') {
-      let skSum = 0;
-      for (const value of window) {
-        skSum += value ** 2;
-      }
-      scale = 1 / (this._blackBoxRate * skSum);
-    } else if (scaling == 'spectrum') {
-      let sum = 0;
-      for (const value of window) {
-        sum += value;
-      }
-      scale = 1 / sum ** 2;
-    }
-  } else if (scaling == 'density') {
-    scale = 1 / pointsPerSegment;
-  } else if (scaling == 'spectrum') {
-    scale = 1 / pointsPerSegment ** 2;
-  }
-
-// Compute average for scaled power
-  let min = 1e6,
-      max = -1e6;
-      // Early exit if no segments were processed
-  if (segmentsCount === 0) {
-    return {
-      psdOutput: new Float64Array(0),
-      min: 0,
-      max: 0,
-      maxNoiseIdx: 0,
-    };
-  }
-  const maxFrequency = (this._blackBoxRate / 2.0);
-  const noise50HzIdx = 50 / maxFrequency * dataCount;
-  const noise3HzIdx = 3 / maxFrequency * dataCount;
-  let maxNoiseIdx = 0;
-  let maxNoise = -100;
-  for (let i = 0; i < dataCount; i++) {
-    psdOutput[i] = 0.0;
-    for (let j = 0; j < segmentsCount; j++) {
-      let p = scale * fftOutput[j][i] ** 2;
-      if (i != dataCount - 1) {
-        p *= 2;
-      }
-      psdOutput[i] += p;
-    }
-
-    const min_avg = 1e-7; // limit min value for -70db
-    let avg = psdOutput[i] / segmentsCount;
-    avg = Math.max(avg, min_avg);
-    psdOutput[i] = 10 * Math.log10(avg);
-    if (i > noise3HzIdx) {    // Miss big zero freq magnitude
-      min = Math.min(psdOutput[i], min);
-      max = Math.max(psdOutput[i], max);
-    }
-    if (i > noise50HzIdx && psdOutput[i] > maxNoise) {
-      maxNoise = psdOutput[i];
-      maxNoiseIdx = i;
-    }
-  }
-
-  const maxNoiseFrequency = maxNoiseIdx / dataCount * maxFrequency;
-
-  return {
-      psdOutput: psdOutput,
-      min: min,
-      max: max,
-      maxNoiseIdx: maxNoiseFrequency,
-    };
-};
-
-
-/**
- * Compute FFT for samples segments by lenghts as pointsPerSegment with overlapCount overlap points count
- */
-GraphSpectrumCalc._fft_segmented  = function(samples, pointsPerSegment, overlapCount) {
-  const samplesCount = samples.length;
-  let output = [];
-  for (let i = 0; i <= samplesCount - pointsPerSegment; i += pointsPerSegment - overlapCount) {
-    const fftInput = samples.slice(i, i + pointsPerSegment);
-
-    if (userSettings.analyserHanning) {
-      this._hanningWindow(fftInput, pointsPerSegment);
-    }
-
-    const fftComplex = this._fft(fftInput);
-    const magnitudes = new Float64Array(pointsPerSegment / 2);
-    for (let i = 0; i < pointsPerSegment / 2; i++) {
-      const re = fftComplex[2 * i];
-      const im = fftComplex[2 * i + 1];
-      magnitudes[i] = Math.hypot(re, im);
-    }
-    output.push(magnitudes);
-  }
-
-  return output;
-};