private PixelColumn[] SignalToPixelConverter(Plottables.Signal signal, Settings settings)
{
PixelColumn[] pxCols = new PixelColumn[settings.dataPlotWidth];
// theoretical minimum pixel if X1 were drawn
int dataMinPx = (int)(settings.axisX.pxPerUnit * (-settings.axisX.x1));
// step column by column left to right
for (int i = 0; i < settings.dataPlotWidth; i++)
{
// determine what index values of the signal correspond to this pixel column
int iLeft = (int)(settings.axisX.unitsPerPx * signal.sampleRateHz * (i - dataMinPx));
int iRight = (int)(iLeft + settings.axisX.unitsPerPx * signal.sampleRateHz);
// ensure indexes are valid and skip columns without data
iLeft = Math.Max(iLeft, 0);
iRight = Math.Min(signal.ys.Length - 1, iRight);
iRight = Math.Max(iRight, 0);
if (iRight == 0)
{
continue;
}
if (iRight < 0 || iLeft > iRight)
{
continue;
}
// pull iLeft of this column to the same iRight as the last
if (i > 0 && pxCols[i - 1] != null)
{
iLeft = pxCols[i - 1].iRight - 1;
}
// determine vertical span of this range
double valMin = ArraySubMin(signal.ys, iLeft, iRight);
double valMax = ArraySubMax(signal.ys, iLeft, iRight);
// TODO: make indexes perfect - they don't always match-up exactly
//Console.WriteLine($"Index [{iLeft}:{iRight}] min/max = {valMin}/{valMax}");
// convert this value to a pixel location on screen
int pxMin = (int)((settings.axisY.x2 - valMin) * settings.axisY.pxPerUnit) + 1;
int pxMax = (int)((settings.axisY.x2 - valMax) * settings.axisY.pxPerUnit) + 1;
// populate the object
pxCols[i] = new PixelColumn(pxMin, pxMax, iLeft, iRight);
}
return(pxCols);
}
public void EstimateBiasedMillimeterDistances()
{
if (MillimeterColumnOMM == null)
{
throw new InvalidOperationException("MillimeterColumnOMM can not be null when calling CalculateWeight");
}
if (PixelColumn == null)
{
throw new InvalidOperationException("PixelColumn can not be null when calling CalculateWeight");
}
var millimeterDistancesUnbiased = PixelColumn.Times(Weight);
OMMvsEstimateDiff = new DataColumn("Diff", MillimeterColumnOMM.Subtract(millimeterDistancesUnbiased));
Bias = OMMvsEstimateDiff.Average();
MillimeterColumnEstimate = new DataColumn("MillimeterColumnEstimate",
millimeterDistancesUnbiased.Select(dist => dist + Bias));
}
public void ListTesting()
{
try
{
List <int> dimensions = ReturnDimensions();
Stopwatch sw = new Stopwatch();
BitmapWrapper bm1 = new BitmapWrapper(@"F:\temp\analysis\640x480\test_0.jpg");
using (System.IO.StreamWriter file = new System.IO.StreamWriter(@"f:\temp\runtime\listanalysis.txt", true))
{
for (int i = 0; i < dimensions.Count; i++)
{
for (int n = 0; n < 200; n++)
{
//Array
sw.Restart();
PixelColumnArray[] array = new PixelColumnArray[bm1.bitmap.Width];
for (int w = 0; w < bm1.bitmap.Width; w++)
{
array[w] = new PixelColumnArray();
array[w].Cells = new PixelCellArray[bm1.bitmap.Height];
for (int h = 0; h < bm1.bitmap.Height; h++)
{
array[w].Cells[h] = new PixelCellArray();
array[w].Cells[h].colour = 11111;
}
}
sw.Stop();
file.WriteLine(i + " - " + n + " - " + " array - " + sw.Elapsed.TotalMilliseconds);
//List
sw.Restart();
List <PixelColumn> list = new List <PixelColumn>();
for (int w = 0; w < bm1.bitmap.Width; w++)
{
PixelColumn column = new PixelColumn();
for (int h = 0; h < bm1.bitmap.Height; h++)
{
PixelCell cell = new PixelCell();
cell.colour = 11111;
column.Cells.Add(cell);
}
list.Add(column);
}
sw.Stop();
file.WriteLine(i + " - " + n + " - " + " list - " + sw.Elapsed.TotalMilliseconds);
} //test iterations
} //dimensions
} //write to file
Assert.IsTrue(true);
}
catch
{
Assert.IsTrue(false);
}
}
