from pyscript import when, document, display import numpy as np import matplotlib.pyplot as plt #import scipy.io.wavfile as wavfile import soundfile as sf from ps_tools import fileUpload, printToDebug, pcm2float from ps_tools import constrainInputValue as constrainValue from myPyFunc import myPyFunc # Some basic settings DEBUG = True # If printing to debug console DEBUG_PREFIX = "PY" # Prefix for identifying messages in debug console STATUS_PREFIX = "Status: " # Prefix for on screen status update N_TRIM = int(1e6) # Max number of input samples to keep (just so we have a limit on the length to analyse) THRESHOLD = 0.5 # Threshold used for 'analysis' # Get some HTML elements by their id (don't need to do it this way, but it can be tidier) statusUpdateElement = document.getElementById("statusUpdateId") uploadButtonElement = document.getElementById("uploadButtonId") analyseButtonElement = document.getElementById("analyseButtonId") analysisThresholdElement = document.getElementById("analysisThresholdId") filenameTableDataElement = document.getElementById("filenameTableDataId") nChannelTableDataElement = document.getElementById("nChannelTableDataId") sampleRateTableDataElement = document.getElementById("sampleRateTableDataId") nSampleTableDataElement = document.getElementById("nSampleTableDataId") timeLengthTableDataElement = document.getElementById("timeLengthTableDataId") rmsTableDataElement = document.getElementById("rmsTableDataId") maxAbsTableDataElement = document.getElementById("maxAbsTableDataId") signalStatsTableElement = document.getElementById("signalStatsTableId") # Print status update to screen def printStatusUpdate(txt): statusUpdateElement.innerText = STATUS_PREFIX + txt # Initial status printStatusUpdate("Loading...") # Initialise filtering object myPyFuncObj = myPyFunc() # Disable buttons that shouldn't be used until we're ready uploadButtonElement.disabled = False analyseButtonElement.disabled = True # Trigger on upload input change @when("change", "#uploadWavId") async def uploadAudio(event): ''' Await file upload, then load and set page ready to analyse ''' # Print to debug and screen printToDebug("File upload", DEBUG, DEBUG_PREFIX) printStatusUpdate("File upload...") # Await getting file - i.e. loading to virtual file system filename = await fileUpload(event) # If we have a file... if len(filename) > 0: # Print to debug printToDebug("File read", DEBUG, DEBUG_PREFIX) # File is first file (regardless of if more than one file was selected) filename = filename[0] # Read data #(fs, yIn) = wavfile.read(filename) (yIn, fs) = sf.read(filename) # use soundfile for reading .wav # In case received PCM integer data make float yIn = pcm2float(yIn) # Set the input in the analysis object myPyFuncObj.setInput(yIn, fs, N_TRIM) # Initialise table(s) - clear any previous results on page and print filename initTable(filename) # Make the plot makePlot() # Enable analyse button analyseButtonElement.disabled = False # Print to debug (and let user know max size of processed audio if trimmed) updateStr = "File upload finished" if myPyFuncObj.trimmed: updateStr += " (note: input trimmed to max N = %i samples)"%N_TRIM printStatusUpdate(updateStr) # Trigger on any analysis threshold change @when("change", "#analysisThresholdId") def analysisThresholdChange(event): ''' Tidy up after get threshold change ''' # Print to debug and screen printToDebug("Analysis threshold change", DEBUG, DEBUG_PREFIX) printStatusUpdate("Ready") # Make sure any entered value is within min/max limits constrainValue(event, doStep = True) # Trigger on analyse button click @when("click", "#analyseButtonId") def analyseAudio(event): ''' Analyse audio and update page results and plot ''' # Print to debug and screen printToDebug("Analysing audio", DEBUG, DEBUG_PREFIX) printStatusUpdate("Analysing...") # Get analysis threshold from page threshold = float(analysisThresholdElement.value) # Do signal analysis doMultiChan = True doMono = True myPyFuncObj.analyseInput(threshold=threshold, doMultiChan=doMultiChan, doMono=doMono) # Add results to page printMultiChan = True printMono = myPyFuncObj.NChan > 1 # Only print mono if have more than one channel printResultsToPage(printMultiChan=printMultiChan, printMono=printMono) # Remake plot makePlot() # Update status printStatusUpdate("Analysis finished") def initTable(filename=""): ''' Clear/reset table(s) and add filename if passed ''' # Update file properties table filenameTableDataElement.innerText = filename nChannelTableDataElement.innerText = "" sampleRateTableDataElement.innerText = "" nSampleTableDataElement.innerText = "" timeLengthTableDataElement.innerText = "" # Update signal stats table for row in signalStatsTableElement.rows: # For each row - clear data in second column and remove any following columns cols = row.cells NCols = len(cols) cols[1].innerText = "" for i in range(NCols-2): row.deleteCell(-1) def printResultsToPage(printMultiChan, printMono): ''' # Get results and add to page ''' # Print to debug printToDebug("Print results to page", DEBUG, DEBUG_PREFIX) # Add file properties nChannelTableDataElement.innerText = "%i"%myPyFuncObj.NChan sampleRateTableDataElement.innerText = "%i"%myPyFuncObj.fs nSampleTableDataElement.innerText = "%i"%myPyFuncObj.N timeLengthTableDataElement.innerText = "%0.4f"%myPyFuncObj.T # Add signal stats # For each row - add any columns if needed... numColsNeeded = 1 + int(printMono) + int(printMultiChan)*myPyFuncObj.NChan for row in signalStatsTableElement.rows: cols = row.cells NCols = len(cols) addNCols = numColsNeeded-NCols for i in range(addNCols): row.insertCell(-1) # Rows we want to edit rows = signalStatsTableElement.rows # If doing multichannel, set NChan columns if printMultiChan: for i in range(myPyFuncObj.NChan): rows[0].cells[i+1].innerText = i+1 rows[1].cells[i+1].innerText = "%i"%myPyFuncObj.samplesOverThreshold[i] rows[2].cells[i+1].innerText = "%0.2f"%myPyFuncObj.percentOverThreshold[i] # If doing mono, set end column if printMono: rows[0].cells[-1].innerText = "'Mono'" rows[1].cells[-1].innerText = "%i"%myPyFuncObj.samplesOverThresholdMono rows[2].cells[-1].innerText = "%0.2f"%myPyFuncObj.percentOverThresholdMono # Make plot(s) and add to page def makePlot(): ''' Make the plot ''' # Print to debug and screen printToDebug("Making plot", DEBUG, DEBUG_PREFIX) printStatusUpdate("Plotting...") # Create plot fig, ax = plt.subplots() # Plot data (if we have data)... if not myPyFuncObj.yIn is None: # Input time and frequency data N = myPyFuncObj.N fs = myPyFuncObj.fs T = (N-1)/fs t = np.linspace(0, T, N) # Plot input data (use mono signal) ax.plot(t, myPyFuncObj.yInMono, 'b-', linewidth=1, label='Input') # Plot labels, limits etc... ax.set_xlim(0, t[-1]) ax.set_xlabel('Time (s)') ax.set_ylabel('Level') ax.set_title('Mono signal') ax.grid() # Add analysis data (if there is any)... if not myPyFuncObj.overThresholdMono is None: # Use masked version of signal (positive and negative) yOverThresholdUpper = np.ma.masked_where( np.logical_or(myPyFuncObj.overThresholdMono == False, myPyFuncObj.yInMono <= 0), myPyFuncObj.yInMono) yOverThresholdLower = np.ma.masked_where( np.logical_or(myPyFuncObj.overThresholdMono == False, myPyFuncObj.yInMono >= 0), myPyFuncObj.yInMono) # Add to plot ax.plot(t, yOverThresholdUpper, 'r.--', linewidth=1, label='Above threshold') ax.plot(t, yOverThresholdLower, 'r.--', linewidth=1) # Put legend in upper right (note: use of default "best" can cause errors due to being too slow) ax.legend(loc="upper right") # Display plot(s) (append False to overwrite any previous content) display(fig, target="plotDivId", append=False) # Delete plot handles(s) when finished plt.close(fig) # Print to screen (let know we're at the end of the code) printToDebug("End of PyScript code", DEBUG, DEBUG_PREFIX) # Update status printStatusUpdate("Ready")