waterfall and fft use a common autoscale function

[debian/gnuradio] / gr-wxgui / src / python / common.py

diff --git a/gr-wxgui/src/python/common.py b/gr-wxgui/src/python/common.py
index d555a1f055a9c3b824e2b71cb0c793c0ec562fcb..9c97ce1ecad898a32e1871f9445c42713db7fd9e 100644 (file)
--- a/gr-wxgui/src/python/common.py
+++ b/gr-wxgui/src/python/common.py
@@ -137,6 +137,25 @@ def get_min_max(samples):
        scale_factor = 3
        mean = numpy.average(samples)
        rms = numpy.max([scale_factor*((numpy.sum((samples-mean)**2)/len(samples))**.5), .1])
-       min = mean - rms
-       max = mean + rms
-       return min, max
+       min_val = mean - rms
+       max_val = mean + rms
+       return min_val, max_val
+
+def get_min_max_fft(fft_samps):
+       """
+       Get the minimum and maximum bounds for an array of fft samples.
+       @param samples the array of real values
+       @return a tuple of min, max
+       """
+       #get the peak level (max of the samples)
+       peak_level = numpy.max(fft_samps)
+       #separate noise samples
+       noise_samps = numpy.sort(fft_samps)[:len(fft_samps)/2]
+       #get the noise floor
+       noise_floor = numpy.average(noise_samps)
+       #get the noise deviation
+       noise_dev = numpy.std(noise_samps)
+       #determine the maximum and minimum levels
+       max_level = peak_level
+       min_level = noise_floor - abs(2*noise_dev)
+       return min_level, max_level