add quick and dirty code to stabilize laser

stabilize.py

@@ -0,0 +1,92 @@
+import SoapySDR
+import numpy as np
+from scipy.signal import blackmanharris
+import serial
+
+fs = 5e6
+base_freq = 1086e6
+threshold = 0.4
+target_freq = 1088.3e6
+k = 200e-6
+
+induction_min = 430e3
+induction_max = 445e3
+
+generator = serial.Serial("/dev/ttyUSB0", 57600, writeTimeout=0)
+
+def set_induction_freq(freq):
+    command = ":s1f{:010d}\n".format(int(freq*1e2))
+    generator.write(command.encode())
+    generator.readline()
+
+def set_induction(amount):
+    amount = max(min(amount, 0.5), -0.5)
+    freq = (induction_min + induction_max)/2 + amount*(induction_max - induction_min)
+    set_induction_freq(freq)
+
+
+def parabolic(f, x):
+    """Quadratic interpolation for estimating the true position of an
+    inter-sample maximum when nearby samples are known.
+    f is a vector and x is an index for that vector.
+    Returns (vx, vy), the coordinates of the vertex of a parabola that goes
+    through point x and its two neighbors.
+    Example:
+    Defining a vector f with a local maximum at index 3 (= 6), find local
+    maximum if points 2, 3, and 4 actually defined a parabola.
+    In [3]: f = [2, 3, 1, 6, 4, 2, 3, 1]
+    In [4]: parabolic(f, argmax(f))
+    Out[4]: (3.2142857142857144, 6.1607142857142856)
+    """
+    xv = 1/2. * (f[x-1] - f[x+1]) / (f[x-1] - 2 * f[x] + f[x+1]) + x
+    yv = f[x] - 1/4. * (f[x-1] - f[x+1]) * (xv - x)
+    return (xv, yv)
+
+def fmt_range(x, m):
+    pos = int(round(x*80/m))
+    return " "*pos + "*"
+
+sdr = SoapySDR.Device()
+samples = np.array([0]*4096, np.complex64)
+
+sdr.setSampleRate(SoapySDR.SOAPY_SDR_RX, 0, fs)
+sdr.setFrequency(SoapySDR.SOAPY_SDR_RX, 0, base_freq)
+
+rxStream = sdr.setupStream(SoapySDR.SOAPY_SDR_RX, SoapySDR.SOAPY_SDR_CF32)
+sdr.activateStream(rxStream)
+
+decimation = 0
+
+try:
+    while True:
+        sr = sdr.readStream(rxStream, [samples], len(samples))
+        if sr.ret != len(samples):
+            print("!")
+            continue
+
+        freqs = np.abs(np.fft.fft(samples*blackmanharris(len(samples)))[0:len(samples)//2])
+        for i in range(len(freqs)//100):
+            freqs[i] = 0
+            freqs[-i] = 0
+
+        # https://gist.github.com/endolith/255291
+        i = np.argmax(freqs)
+        true_i = parabolic(freqs, i)[0]
+        freq = 0.5 * fs * true_i / len(freqs)
+        amplitude = freqs[i]
+
+        if amplitude > threshold:
+            actual_freq = base_freq + freq
+            print("{:8.3f} {:6.2f} {}".format(actual_freq/1e6, amplitude, fmt_range(freq, fs/2)))
+            induction = (actual_freq - target_freq)*k
+        else:
+            print("<no signal>", amplitude)
+            induction = 0.0
+
+        decimation += 1
+        if decimation == 15:
+            set_induction(induction)
+            decimation = 0
+finally:
+    sdr.deactivateStream(rxStream)
+    sdr.closeStream(rxStream)