restructure and organize
This commit is contained in:
Silas Oettinghaus
@@ -1,133 +1,370 @@
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function [symbols_for_lvl,avg_for_lvl] = showLevelScatter(eq_signal,ref_symbols,options)
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function [symbols_for_lvl, avg_for_lvl, info] = showLevelScatter(rxInput, refSymbols, options)
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%SHOWLEVELSCATTER Plot received samples separated by reference PAM level.
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% Supports plain numeric vectors, Signal objects, synchronized scope cell
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% arrays, and raw unsynchronized Signal input. Raw Signal input is
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% synchronized to refSymbols and stitched before plotting.
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arguments
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eq_signal
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ref_symbols
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options.fignum (1,1) double = NaN % Default to NaN if not provided
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options.displayname (1,:) char = '' % Default to an empty string if not provided
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options.f_sym =1e6;
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rxInput
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refSymbols
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options.fignum (1,1) double = NaN
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options.displayname (1,:) char = ''
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options.f_sym double = []
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options.fsym double = []
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options.syncFs (1,1) double = 0
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options.shiftFs (1,1) double = 0
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options.shifts double = []
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options.maxOccurences (1,1) double = Inf
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options.normalize (1,1) logical = false
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options.debug_plots (1,1) logical = false
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options.showPlot (1,1) logical = true
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options.clear (1,1) logical = true
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options.windowLength (1,1) double {mustBePositive, mustBeInteger} = 500
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options.xLimits double = []
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options.yLimits (1,2) double = [-3 3]
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options.showStdAnnotations (1,1) logical = true
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end
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plot_shit = 1;
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fsym = resolveSymbolRate(rxInput, refSymbols, options);
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[symbols_for_lvl, avg_for_lvl, xAxisUs, info] = prepareLevelScatterData(rxInput, refSymbols, fsym, options);
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if isa(eq_signal,'Signal')
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options.f_sym = eq_signal.fs;
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eq_signal = eq_signal.signal;
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assert(~isempty(options.f_sym),'No fsym given');
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if options.showPlot
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plotLevelScatter(symbols_for_lvl, avg_for_lvl, refSymbols, xAxisUs, options);
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end
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if isa(ref_symbols,'Signal')
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ref_symbols = ref_symbols.signal;
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end
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function fsym = resolveSymbolRate(rxInput, refSymbols, options)
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if ~isempty(options.fsym)
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fsym = options.fsym;
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elseif ~isempty(options.f_sym)
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fsym = options.f_sym;
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elseif isa(refSymbols, "Signal") && ~isempty(refSymbols.fs)
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fsym = refSymbols.fs;
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elseif isa(rxInput, "Signal") && ~isempty(rxInput.fs)
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fsym = rxInput.fs;
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elseif iscell(rxInput) && ~isempty(rxInput) && isa(rxInput{1}, "Signal") && ~isempty(rxInput{1}.fs)
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fsym = rxInput{1}.fs;
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else
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fsym = 1e6;
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end
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end
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if plot_shit
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% Determine the figure number to use or create a new figure
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if isnan(options.fignum)
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fig = figure; % Create a new figure and get its handle
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function [symbols_for_lvl, avg_for_lvl, xAxisUs, info] = prepareLevelScatterData(rxInput, refSymbols, fsym, options)
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refSignal = numericSignal(refSymbols);
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info = defaultInfo(fsym);
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if iscell(rxInput)
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[symbols_for_lvl, avg_for_lvl, info] = prepareCellInput(rxInput, refSymbols, fsym, options, info);
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elseif isa(rxInput, "Signal")
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[symbols_for_lvl, avg_for_lvl, info] = prepareSignalInput(rxInput, refSymbols, fsym, options, info);
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else
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rxSymbols = numericSignal(rxInput);
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[symbols_for_lvl, avg_for_lvl] = levelScatterForOneSequence(rxSymbols, refSignal, options.windowLength);
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end
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xAxisUs = ((1:size(avg_for_lvl, 2)) / fsym) * 1e6;
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end
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function info = defaultInfo(fsym)
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info = struct();
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info.found_sync = true;
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info.startSamples = 1;
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info.shifts = [];
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info.fsym = fsym;
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info.shiftFs = fsym;
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info.varianceByLevel = [];
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end
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function [symbols_for_lvl, avg_for_lvl, info] = prepareSignalInput(rxSignal, refSymbols, fsym, options, info)
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rxAtSymbolRate = rxSignal.resample("fs_in", rxSignal.fs, "fs_out", fsym);
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refSignal = numericSignal(refSymbols);
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if numel(rxAtSymbolRate.signal) == numel(refSignal)
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rxSymbols = rxAtSymbolRate.signal;
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if options.normalize
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rxSymbols = normalizeNumericRms(rxSymbols);
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end
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[symbols_for_lvl, avg_for_lvl] = levelScatterForOneSequence(rxSymbols, refSignal, options.windowLength);
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info.varianceByLevel = var(symbols_for_lvl, 0, 2, "omitnan");
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return
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end
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[scopeCell, shifts, shiftFs, foundSync] = synchronizeRawSignal(rxSignal, refSymbols, fsym, options);
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info.found_sync = foundSync;
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info.shifts = shifts;
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info.shiftFs = shiftFs;
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if isempty(scopeCell)
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symbols_for_lvl = [];
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avg_for_lvl = [];
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warning("showLevelScatter:NoScopeCells", ...
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"No synchronized scope signal occurrences available.");
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return
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end
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[symbols_for_lvl, avg_for_lvl, startSamples] = stitchScopeCells(scopeCell, refSymbols, fsym, shifts, shiftFs, options);
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info.startSamples = startSamples;
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info.varianceByLevel = var(symbols_for_lvl, 0, 2, "omitnan");
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end
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function [symbols_for_lvl, avg_for_lvl, info] = prepareCellInput(scopeCell, refSymbols, fsym, options, info)
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scopeCell = scopeCell(:);
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if isempty(scopeCell)
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symbols_for_lvl = [];
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avg_for_lvl = [];
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info.found_sync = false;
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warning("showLevelScatter:NoScopeCells", ...
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"No synchronized scope signal occurrences available.");
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return
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end
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shiftFs = options.shiftFs;
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if shiftFs <= 0
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shiftFs = fsym;
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end
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[symbols_for_lvl, avg_for_lvl, startSamples] = stitchScopeCells(scopeCell, refSymbols, fsym, options.shifts, shiftFs, options);
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info.found_sync = true;
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info.shifts = options.shifts;
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info.shiftFs = shiftFs;
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info.startSamples = startSamples;
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info.varianceByLevel = var(symbols_for_lvl, 0, 2, "omitnan");
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end
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function [scopeCell, shifts, shiftFs, foundSync] = synchronizeRawSignal(rxSignal, refSymbols, fsym, options)
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syncFs = options.syncFs;
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if syncFs <= 0
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syncFs = 2*fsym;
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end
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syncSignal = rxSignal.resample("fs_in", rxSignal.fs, "fs_out", syncFs);
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if options.normalize
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syncSignal = syncSignal.normalize("mode", "rms");
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end
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[~, scopeCell, ~, foundSync, shifts] = syncSignal.tsynch( ...
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"reference", refSymbols, ...
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"fs_ref", fsym, ...
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"debug_plots", options.debug_plots);
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if options.shiftFs > 0
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shiftFs = options.shiftFs;
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else
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shiftFs = syncFs;
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end
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end
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function [symbols_for_lvl, avg_for_lvl, startSamples] = stitchScopeCells(scopeCell, refSymbols, fsym, shifts, shiftFs, options)
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recordOccurrences = min(numel(scopeCell), options.maxOccurences);
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scopeCell = scopeCell(1:recordOccurrences);
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refSignal = numericSignal(refSymbols);
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startSamples = getStartSamples(shifts, recordOccurrences, shiftFs, fsym, numel(refSignal));
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levelScatter = cell(1, recordOccurrences);
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levelAverage = cell(1, recordOccurrences);
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for occurrenceIdx = 1:recordOccurrences
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occurrence = scopeCell{occurrenceIdx};
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if isa(occurrence, "Signal")
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occurrence = occurrence.resample("fs_out", fsym);
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occurrence = occurrence.signal;
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end
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[levelScatter{occurrenceIdx}, levelAverage{occurrenceIdx}] = ...
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levelScatterForOneSequence(occurrence, refSignal, options.windowLength);
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end
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numLevels = size(levelScatter{1}, 1);
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traceLength = max(startSamples(:).' + cellfun(@(x) size(x, 2), levelScatter) - 1);
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symbols_for_lvl = NaN(numLevels, traceLength);
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avg_for_lvl = NaN(numLevels, traceLength);
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for occurrenceIdx = 1:recordOccurrences
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writeIdx = startSamples(occurrenceIdx):(startSamples(occurrenceIdx) + size(levelScatter{occurrenceIdx}, 2) - 1);
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symbols_for_lvl(:, writeIdx) = levelScatter{occurrenceIdx};
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avg_for_lvl(:, writeIdx) = levelAverage{occurrenceIdx};
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end
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end
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function startSamples = getStartSamples(shifts, recordOccurrences, shiftFs, fsym, symbolLength)
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if isempty(shifts)
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startSamples = ((0:recordOccurrences-1) .* symbolLength) + 1;
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return
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end
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shifts = shifts(:);
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if numel(shifts) ~= recordOccurrences
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positiveShifts = shifts(shifts >= 0);
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if numel(positiveShifts) >= recordOccurrences
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shifts = positiveShifts(1:recordOccurrences);
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else
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fig = figure(options.fignum); % Use the specified figure number
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warning("showLevelScatter:ShiftCountMismatch", ...
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"Shift count does not match scope cell count. Using sequential stitching.");
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startSamples = ((0:recordOccurrences-1) .* symbolLength) + 1;
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return
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end
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end
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startSamples = round((shifts(1:recordOccurrences) - shifts(1)) ./ shiftFs .* fsym) + 1;
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end
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function [symbols_for_lvl, avg_for_lvl] = levelScatterForOneSequence(rxSymbols, refSymbols, windowLength)
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rxSymbols = numericSignal(rxSymbols);
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refSymbols = numericSignal(refSymbols);
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assert(numel(rxSymbols) == numel(refSymbols), ...
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'showLevelScatter:LengthMismatch', ...
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'rxInput and refSymbols must have the same number of samples after resampling/synchronization.');
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levels = unique(refSymbols);
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[symbols_for_lvl, levels] = splitByReferenceLevels(rxSymbols, refSymbols, levels);
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avg_for_lvl = NaN(numel(levels), numel(refSymbols));
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for levelIdx = 1:numel(levels)
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levelMask = ~isnan(symbols_for_lvl(levelIdx, :));
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levelSamples = symbols_for_lvl(levelIdx, levelMask);
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if isempty(levelSamples)
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continue
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end
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smoothWindowLength = min(windowLength, numel(levelSamples));
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avg_for_lvl(levelIdx, levelMask) = movmean(levelSamples, smoothWindowLength, 'Endpoints', 'shrink');
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avg_for_lvl(levelIdx, :) = interpolateMissingLevelAverage(avg_for_lvl(levelIdx, :));
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end
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end
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function [symbols_for_lvl, levels] = splitByReferenceLevels(rxSymbols, refSymbols, levels)
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supportedPamLevels = [2 4 6 8 16];
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if ismember(numel(levels), supportedPamLevels)
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[symbols_for_lvl, levels] = PAMmapper(numel(levels), 0).splitByReferenceLevels( ...
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rxSymbols, refSymbols, ...
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"levels", levels);
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else
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symbols_for_lvl = NaN(numel(levels), numel(refSymbols));
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for levelIdx = 1:numel(levels)
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levelMask = refSymbols == levels(levelIdx);
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symbols_for_lvl(levelIdx, levelMask) = rxSymbols(levelMask);
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end
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end
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end
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function plotLevelScatter(symbols_for_lvl, avg_for_lvl, refSymbols, xAxisUs, options)
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if isempty(symbols_for_lvl)
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return
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end
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if isnan(options.fignum)
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figure;
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else
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figure(options.fignum);
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if options.clear
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clf;
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end
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end
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hold on
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numLevels = size(symbols_for_lvl, 1);
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cols = cbrewer2("Paired", 2*numLevels);
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rx_symbols = eq_signal; %./ rms(eq_signal);
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correct_symbols = ref_symbols;
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f_sym = options.f_sym;
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col = cbrewer2('Paired',numel(unique(correct_symbols))*2);
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ccnt = -1;
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levels = unique(correct_symbols);
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symbols_for_lvl = NaN(numel(levels),length(correct_symbols));
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start = 1;
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ende = length(correct_symbols);
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for l = 1:numel(levels)
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ccnt = ccnt+2;
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level_amplitude = levels(l);
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symbols_for_lvl(l,correct_symbols==level_amplitude) = rx_symbols(correct_symbols==level_amplitude);
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std_lvl(l) = std(symbols_for_lvl(l,:),'omitnan');
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xax_in_sec = ((1:length(correct_symbols)) / f_sym) * 1e6;
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if plot_shit
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scatter(xax_in_sec(start:ende),symbols_for_lvl(l,start:ende),10,'.','MarkerFaceAlpha',0.5,'MarkerEdgeAlpha',0.5,'MarkerEdgeColor',col(ccnt,:));
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hold on;
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end
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for levelIdx = 1:numLevels
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scatter(xAxisUs, symbols_for_lvl(levelIdx, :), 10, ".", ...
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"MarkerEdgeColor", cols((2*levelIdx)-1, :), ...
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"MarkerEdgeAlpha", 0.5);
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end
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std_lvl = round(std_lvl,2);
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ccnt = 0;
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avg_for_lvl = NaN(numel(levels),length(correct_symbols));
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% Add the windowed/ smoothed curves
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for l = 1:numel(levels)
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ccnt = ccnt+2;
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level_amplitude = levels(l);
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L = 500;
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movmean = 1/L .* movsum(rx_symbols(correct_symbols==level_amplitude),[L/2,L/2], 'Endpoints', 'fill');
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avg_for_lvl(l,correct_symbols==level_amplitude) = movmean;
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nanx = isnan(avg_for_lvl(l,:));
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t = 1:numel(avg_for_lvl(l,:));
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avg_for_lvl(l,nanx) = interp1(t(~nanx), avg_for_lvl(l,~nanx), t(nanx));
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xax_in_sec = ((1:length(correct_symbols)) / f_sym) * 1e6;
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% xax_in_sec = 1:length(correct_symbols);
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if plot_shit
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plot(xax_in_sec(start:ende),avg_for_lvl(l,start:ende),'Color',col(ccnt,:));
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end
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hold on
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for levelIdx = 1:numLevels
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plot(xAxisUs, avg_for_lvl(levelIdx, :), ...
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"LineWidth", 1, ...
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"Color", cols(2*levelIdx, :));
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end
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if 0
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annotation(fig,'textbox',...
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[0.660523809523809 0.844444444444448 0.133523809523809 0.0603174603174607],...
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'String',['\sigma = ',num2str(std_lvl(4))],...
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'LineWidth',1.8,...
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'LineStyle','none',...
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'FontSize',12,...
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'FitBoxToText','off');
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% Create textbox
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annotation(fig,'textbox',...
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[0.667666666666665 0.642857142857147 0.133523809523809 0.0603174603174607],...
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'String',['\sigma = ',num2str(std_lvl(3))],...
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'LineWidth',1.8,...
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'LineStyle','none',...
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'FontSize',12,...
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'FitBoxToText','off');
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% Create textbox
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annotation(fig,'textbox',...
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[0.671238095238093 0.442857142857148 0.133523809523809 0.0603174603174608],...
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'String',['\sigma = ',num2str(std_lvl(2))],...
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'LineWidth',1.8,...
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'LineStyle','none',...
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'FontSize',12,...
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'FitBoxToText','off');
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% Create textbox
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annotation(fig,'textbox',...
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[0.670047619047616 0.265079365079371 0.133523809523809 0.0603174603174608],...
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'String',['\sigma = ',num2str(std_lvl(1))],...
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'LineWidth',1.8,...
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'LineStyle','none',...
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'FontSize',12,...
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'FitBoxToText','off');
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refValues = numericSignal(refSymbols);
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yline(unique(refValues), "HandleVisibility", "off");
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if options.showStdAnnotations
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annotateLevelStd(symbols_for_lvl, avg_for_lvl, xAxisUs, options.xLimits);
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end
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if plot_shit
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% yline(levels);
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xlabel('Time in $\mu$s');
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ylabel('Normalized Amplitude');
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ylim([-3 3]);
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xlim(getXLimits(options.xLimits, xAxisUs, symbols_for_lvl));
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ylim(options.yLimits);
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grid on
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drawnow;
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end
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function xLimits = getXLimits(configuredLimits, xAxisUs, symbols_for_lvl)
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if ~isempty(configuredLimits)
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xLimits = configuredLimits;
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return
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end
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filledColumns = any(~isnan(symbols_for_lvl), 1);
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if ~any(filledColumns)
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xLimits = [xAxisUs(1), xAxisUs(end)];
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return
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end
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lastFilledColumn = find(filledColumns, 1, "last");
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xMax = xAxisUs(lastFilledColumn);
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xLimits = [0, 1.05*xMax];
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end
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function annotateLevelStd(symbols_for_lvl, avg_for_lvl, xAxisUs, configuredXLimits)
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xLimits = getXLimits(configuredXLimits, xAxisUs, symbols_for_lvl);
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xText = xLimits(1) + 0.96*diff(xLimits);
|
||||
|
||||
for levelIdx = 1:size(symbols_for_lvl, 1)
|
||||
levelSamples = symbols_for_lvl(levelIdx, :);
|
||||
levelStd = std(levelSamples, 0, 2, 'omitnan');
|
||||
if isnan(levelStd)
|
||||
continue
|
||||
end
|
||||
|
||||
levelAverage = avg_for_lvl(levelIdx, :);
|
||||
yText = median(levelAverage(~isnan(levelAverage)), 'omitnan');
|
||||
if isnan(yText)
|
||||
yText = median(levelSamples(~isnan(levelSamples)), 'omitnan');
|
||||
end
|
||||
|
||||
label = ['std = ', sprintf('%.3f', levelStd)];
|
||||
text(xText, yText, label, ...
|
||||
'Interpreter', 'none', ...
|
||||
'HorizontalAlignment', 'right', ...
|
||||
'VerticalAlignment', 'middle', ...
|
||||
'FontSize', 10, ...
|
||||
'BackgroundColor', 'w', ...
|
||||
'Margin', 2, ...
|
||||
'EdgeColor', [0.8 0.8 0.8]);
|
||||
end
|
||||
end
|
||||
|
||||
function levelAverage = interpolateMissingLevelAverage(levelAverage)
|
||||
validSamples = ~isnan(levelAverage);
|
||||
|
||||
if nnz(validSamples) == 0
|
||||
return
|
||||
elseif nnz(validSamples) == 1
|
||||
levelAverage(:) = levelAverage(validSamples);
|
||||
return
|
||||
end
|
||||
|
||||
t = 1:numel(levelAverage);
|
||||
levelAverage(~validSamples) = interp1(t(validSamples), levelAverage(validSamples), ...
|
||||
t(~validSamples), 'linear', 'extrap');
|
||||
end
|
||||
|
||||
function values = numericSignal(signalLike)
|
||||
if isa(signalLike, "Signal")
|
||||
values = signalLike.signal;
|
||||
else
|
||||
values = signalLike;
|
||||
end
|
||||
|
||||
values = values(:).';
|
||||
end
|
||||
|
||||
function values = normalizeNumericRms(values)
|
||||
values = values ./ sqrt(mean(values.^2, "omitnan"));
|
||||
end
|
||||
|
||||
Reference in New Issue
Block a user