"""!
Create a log10(abs(fft)) stream chain, with real or complex input.
"""
-
+
def __init__(self, sample_rate, fft_size, ref_scale, frame_rate, avg_alpha, average):
- """!
- Create an log10(abs(fft)) stream chain.
- Provide access to the setting the filter and sample rate.
- @param sample_rate Incoming stream sample rate
- @param fft_size Number of FFT bins
- @param ref_scale Sets 0 dB value input amplitude
- @param frame_rate Output frame rate
- @param avg_alpha FFT averaging (over time) constant [0.0-1.0]
- @param average Whether to average [True, False]
- """
- gr.hier_block2.__init__(self, self._name,
- gr.io_signature(1, 1, self._item_size), # Input signature
- gr.io_signature(1, 1, gr.sizeof_float*fft_size)) # Output signature
+ """!
+ Create an log10(abs(fft)) stream chain.
+ Provide access to the setting the filter and sample rate.
+ @param sample_rate Incoming stream sample rate
+ @param fft_size Number of FFT bins
+ @param ref_scale Sets 0 dB value input amplitude
+ @param frame_rate Output frame rate
+ @param avg_alpha FFT averaging (over time) constant [0.0-1.0]
+ @param average Whether to average [True, False]
+ """
+ gr.hier_block2.__init__(self, self._name,
+ gr.io_signature(1, 1, self._item_size), # Input signature
+ gr.io_signature(1, 1, gr.sizeof_float*fft_size)) # Output signature
- self._sd = stream_to_vector_decimator(item_size=self._item_size,
- sample_rate=sample_rate,
- vec_rate=frame_rate,
- vec_len=fft_size)
-
- fft_window = window.blackmanharris(fft_size)
- fft = self._fft_block[0](fft_size, True, fft_window)
- window_power = sum(map(lambda x: x*x, fft_window))
+ self._sd = stream_to_vector_decimator(item_size=self._item_size,
+ sample_rate=sample_rate,
+ vec_rate=frame_rate,
+ vec_len=fft_size)
- c2mag = gr.complex_to_mag(fft_size)
- self._avg = gr.single_pole_iir_filter_ff(1.0, fft_size)
- self._log = gr.nlog10_ff(20, fft_size,
- -10*math.log10(fft_size) # Adjust for number of bins
- -10*math.log10(window_power/fft_size) # Adjust for windowing loss
- -20*math.log10(ref_scale/2)) # Adjust for reference scale
- self.connect(self, self._sd, fft, c2mag, self._avg, self._log, self)
- self.set_average(average)
- self.set_avg_alpha(avg_alpha)
+ fft_window = window.blackmanharris(fft_size)
+ fft = self._fft_block[0](fft_size, True, fft_window)
+ window_power = sum(map(lambda x: x*x, fft_window))
+
+ c2mag = gr.complex_to_mag(fft_size)
+ self._avg = gr.single_pole_iir_filter_ff(1.0, fft_size)
+ self._log = gr.nlog10_ff(20, fft_size,
+ -10*math.log10(fft_size) # Adjust for number of bins
+ -10*math.log10(window_power/fft_size) # Adjust for windowing loss
+ -20*math.log10(ref_scale/2)) # Adjust for reference scale
+ self.connect(self, self._sd, fft, c2mag, self._avg, self._log, self)
+ self.set_average(False)
+ self.set_avg_alpha(avg_alpha)
+ self.set_average(average)
def set_sample_rate(self, sample_rate):
- """!
- Set the new sampling rate
- @param sample_rate the new rate
- """
- self._sd.set_sample_rate(sample_rate)
+ """!
+ Set the new sampling rate
+ @param sample_rate the new rate
+ """
+ self._sd.set_sample_rate(sample_rate)
def set_average(self, average):
"""!
@param average true to set averaging on
"""
self._average = average
- if self._average:
- self._avg.set_taps(self._avg_alpha)
- else:
- self._avg.set_taps(1.0)
+ if self._average:
+ self._avg.set_taps(self._avg_alpha)
+ else:
+ self._avg.set_taps(1.0)
def set_avg_alpha(self, avg_alpha):
- """!
- Set the average alpha and set the taps if average was on.
- @param avg_alpha the new iir filter tap
- """
- self._avg_alpha = avg_alpha
- self.set_average(self._average)
+ """!
+ Set the average alpha and set the taps if average was on.
+ @param avg_alpha the new iir filter tap
+ """
+ self._avg_alpha = avg_alpha
+ self.set_average(self._average)
+
+ def sample_rate(self):
+ """!
+ Return the current sample rate.
+ """
+ return self._sd.sample_rate()
def average(self):
- """!
- Return whether or not averaging is being performed.
- """
- return self._average
-
- def avg_alpha(self):
- """!
- Return averaging filter constant.
- """
- return self._avg_alpha
+ """!
+ Return whether or not averaging is being performed.
+ """
+ return self._average
+ def avg_alpha(self):
+ """!
+ Return averaging filter constant.
+ """
+ return self._avg_alpha
class logpwrfft_f(_logpwrfft_base):
- """!
- Create an fft block chain, with real input.
- """
- _name = "logpwrfft_f"
- _item_size = gr.sizeof_float
- _fft_block = (gr.fft_vfc, )
+ """!
+ Create an fft block chain, with real input.
+ """
+ _name = "logpwrfft_f"
+ _item_size = gr.sizeof_float
+ _fft_block = (gr.fft_vfc, )
class logpwrfft_c(_logpwrfft_base):
- """!
- Create an fft block chain, with complex input.
- """
- _name = "logpwrfft_c"
- _item_size = gr.sizeof_gr_complex
- _fft_block = (gr.fft_vcc, )
+ """!
+ Create an fft block chain, with complex input.
+ """
+ _name = "logpwrfft_c"
+ _item_size = gr.sizeof_gr_complex
+ _fft_block = (gr.fft_vcc, )
projects / debian / gnuradio / blobdiff