Stripped down recorder, copied bits from ozel

README.md

@@ -2,6 +2,7 @@
 witgit is free software gamma ray spectroscopy software
 under development intended to be used
 with low cost and DIY hardware running on a free operating system.
+For educational use only, and probably not even that.
 
 
 # Hardware

requirements.txt

@@ -3,4 +3,5 @@ msgpack
 numpy
 pandas
 pyaudio
+pyqtgraph
 scipy

witgit-rec

@@ -10,3 +10,123 @@ https://github.com/ozel/DIY_particle_detector
 @date: January 2022
 """
 
+import sys
+import time
+from pyqtgraph.Qt import QtCore, QtGui, QtWidgets
+import numpy as np
+import pyqtgraph as pg
+import pyaudio
+import pandas as pd
+import datetime
+from functools import partial
+from scipy.signal import argrelextrema
+
+class Scope(QtGui.QMainWindow):
+    def __init__(self, parent=None):
+        global app
+        QtGui.QMainWindow.__init__(self, parent)
+
+        self.app = app
+        self.app.aboutToQuit.connect(self.close)
+        self.pcounter=0
+        self.creation_time=datetime.datetime.now()
+
+        self.df = pd.DataFrame(columns = ['ts','ptype'])
+        self.ptypes = pd.Series(["alpha", "beta", "betagamma", "x-ray", "muon" ,"unknown"], dtype="category")
+
+        self.thl =  -300
+        self.hl = -1243 # green cursor, highlight line for measuring only
+        self.peaks=[]
+
+        def audio_callback(in_data, frame_count, time_info, status):
+            now = time.time()
+            samples = np.frombuffer(in_data, dtype=np.int16)
+            peak = samples.min()
+            if  peak < self.thl:
+                t =  pd.datetime.fromtimestamp(now)
+                print("* ", t, end="")
+                pulse = pd.DataFrame()
+                pulse = pulse.assign(ts=[t])
+                if peak < -1243:
+                    pulse = pulse.assign(ptype=[self.ptypes[0]]) #alpha
+                    print("   alpha  ", end="")
+                else:
+                    pulse = pulse.assign(ptype=[self.ptypes[1]]) #beta/electron
+                    print("   elect   ", end="")
+                print(self.pcounter, "  ", end="")
+                print(peak)
+                minima=argrelextrema(samples, np.less)
+                self.peaks.append(sum(minima[0])/len(minima[0]/2))
+                self.peaks = self.peaks[-100:] #only keep the last 100 for averaging
+                pulse = pulse.assign(pulse=[samples])
+                self.df = self.df.append(pulse, ignore_index=True,sort=False)
+                self.pcounter+=1
+                # calculate pulse rate in counts per second
+                dt = (now-self.lastupdate)
+                if dt <= 0:
+                    dt = 0.000000000001
+                cps2 = 1.0 / dt
+                self.lastupdate = now
+                self.cps = self.cps * 0.9 + cps2 * 0.1 # simple weighted average
+                tx = 'Mean pulse rate:  {cps:.1f} CPS'.format(cps=self.cps )
+                self.label.setText(tx + ", THL (red): " + str(self.thl) + ", cursor(green): " + str(self.hl) + ", (avg peak: "+str(round(sum(self.peaks)/100,1)) + ")")
+                self.ydata=np.frombuffer(in_data, dtype=np.int16)
+                self.frame_counter+=frame_count
+                self.h2.setData(self.ydata)
+            self.thlp.setData(4096*[self.thl])
+            self.hlp.setData(4096*[self.hl]) #draw green highlight line
+
+            return (in_data, pyaudio.paContinue)
+
+        #### Create Gui Elements ###########
+        self.mainbox = QtGui.QWidget()
+        self.setCentralWidget(self.mainbox)
+        self.mainbox.setLayout(QtGui.QVBoxLayout())
+
+        self.canvas = pg.GraphicsLayoutWidget()
+        self.mainbox.layout().addWidget(self.canvas)
+
+        self.label = QtGui.QLabel()
+        self.mainbox.layout().addWidget(self.label)
+
+        self.otherplot = self.canvas.addPlot()
+        self.h2 = self.otherplot.plot(pen='y')
+        self.thlp = self.otherplot.plot(pen='r')
+        self.hlp = self.otherplot.plot(pen='g')
+
+        self.p = pyaudio.PyAudio()
+        self.stream = self.p.open(format=pyaudio.paInt16, channels=1, rate=48000, input=True, frames_per_buffer=4096,stream_callback=audio_callback)
+
+        #### Set Data  #####################
+        self.x = np.linspace(0,50., num=100)
+        self.X,self.Y = np.meshgrid(self.x,self.x)
+
+        self.frame_counter = 0
+        self.cps = 0.
+        self.lastupdate = time.time()
+
+        #### Start  #####################
+        self.stream.start_stream()
+
+    def close_stream(self):
+        self.stream.close()
+        self.stream.stop_stream()
+
+    def close(self):
+        timediff = datetime.datetime.now() - self.creation_time
+        self.close_stream()
+        if self.pcounter > 0:
+            td_str = '-'.join(str(timediff).split(':')[:2])
+            _ = self.df.to_pickle("./data" + self.creation_time.strftime("/pulses_%Y-%m-%d_%H-%M-%S") + "___" + str(self.pcounter) + "___" + td_str + ".pkl")
+            print('Number of recorded waveforms:', self.pcounter, "of",self.frame_counter, "total audio frames")
+            print(len(self.df[self.df['ptype'] == 'alpha']) ,"alphas detected")
+            print(len(self.df[self.df['ptype'] == 'beta']) ,"electrons/betas detected")
+        self.p.terminate()
+        app.exit()
+
+if __name__ == '__main__':
+    app = QtWidgets.QApplication(sys.argv)
+    mainWin = Scope()
+    mainWin.show()
+    app.exec_()
+