selcal/scripts/selcal-detect.py

124 lines
3.9 KiB
Python
Executable File

#! /usr/bin/env python3
import csv
import sys
import numpy as np
from scipy import signal
from scipy.io import wavfile
from scipy.signal import butter, lfilter
tones = {}
with open('tones.csv', newline='') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
tones[row['designator']] = float(row['frequency'])
'''
def freq_of_key(midi_key):
return 440.0 * (2 ** ((midi_key - 69)/12))
tones = {}
for c in range(65, 90):
tones[c] = freq_of_key(c)
'''
# Shamelessly lifted from
# https://scipy.github.io/old-wiki/pages/Cookbook/ButterworthBandpass
def butter_bandpass(lowcut, highcut, fs, order=5):
nyq = 0.5 * fs
low = lowcut / nyq
high = highcut / nyq
b, a = butter(order, [low, high], btype='band')
return b, a
def butter_bandpass_filter(data, lowcut, highcut, fs, order=5):
b, a = butter_bandpass(lowcut, highcut, fs, order=order)
y = lfilter(b, a, data)
return y
# tone synthesis
def note(freq, cycles, amp=32767.0, rate=44100):
len = cycles * (1.0/rate)
t = np.linspace(0, len, int(len * rate))
if freq == 0:
data = np.zeros(int(len * rate))
else:
data = np.sin(2 * np.pi * freq * t) * amp
return data.astype(int)
def decimate_from_sample_rate(sample_rate):
if sample_rate == 44100:
return 4 # rate = 11025, Fmax = 5512.5 Hz
elif sample_rate == 48000:
return 5 # rate = 9600, Fmax = 4800 Hz
elif sample_rate == 22050:
return 2 # rate = 11025, Fmax = 5512.5 Hz
elif sample_rate == 11025:
return 1 # rate = 11025, Fmax = 5512.5 Hz
else:
raise ValueError("Sample rate not supported")
if __name__ == '__main__':
# TODO JMT: What is this?
FLT_LEN = 2000
file_name = sys.argv[1]
sample_rate, data = wavfile.read(file_name)
print(f"{file_name}: {len(data)} samples @ {sample_rate} Hz")
decimate = decimate_from_sample_rate(sample_rate)
if decimate > 1:
data = signal.decimate(data, decimate)
sample_rate = sample_rate / decimate
print(f'Length after decimation: {len(data)} samples')
data = butter_bandpass_filter(data, 270, 1700, sample_rate, order=8)
pure_signals = {tone:note(freq, FLT_LEN, rate=sample_rate) for tone,freq in tones.items()}
correlations = {tone:np.abs(signal.correlate(data, pure, mode='same')) for tone,pure in pure_signals.items()}
N = FLT_LEN # Rolling average length
cumsum_convolution = np.ones(N)/N
massaged = {tone:np.convolve(correlation, cumsum_convolution, mode='valid') for tone,correlation in correlations.items()}
# Only import if we're actually plotting, these imports are pretty heavy.
import pyqtgraph as pg
from PyQt5 import QtWidgets
app = QtWidgets.QApplication([])
layout = pg.GraphicsLayoutWidget(show=True, title="SELCAL Tone Correlation")
layout.setGeometry(0, 0, 1600, 960)
plot = layout.addPlot(title=file_name)
legend_view = layout.addViewBox()
legend = pg.LegendItem(offset=(0, 0))
legend.setParentItem(legend_view)
color_map = pg.colormap.get('CET-C6s')
colors = color_map.getLookupTable(nPts=len(tones))
for (tone, correlation), color in zip(massaged.items(), colors):
line = plot.plot(correlation, pen=pg.mkPen(color=color), fillLevel=0.1, name=tone)
legend.addItem(line, tone)
y_max = max(line.getData()[1]) # Maximum y-value
x_max = line.getData()[0][np.argmax(line.getData()[1])] # Corresponding x-coordinate
label = pg.TextItem(html=f'<div style="text-align: center"><span style="color: #FFFFFF; font-size: 12pt;">{line.opts["name"]}</span></div>', anchor=(0.5, 0.5))
plot.addItem(label)
label.setPos(x_max, y_max)
label.setZValue(100) # Ensure label is above other items
plot.setLabel('left', 'Signal Correlation')
plot.setLabel('bottom', 'Time (samples)')
plot.showGrid(x=True, y=True)
legend_view.setFixedWidth(80)
layout.ci.layout.setColumnFixedWidth(1, 80)
app.exec_()