From 09cd2d7cccf0a472ee2623c4a388a4ce950c0c5c Mon Sep 17 00:00:00 2001
From: Josh Morman <jmorman@gnuradio.org>
Date: Wed, 24 Nov 2021 12:34:58 -0500
Subject: filter: pep8 formatting
Signed-off-by: Josh Morman <jmorman@gnuradio.org>
---
gr-filter/examples/channelize.py | 56 +++++++++++++++++++++-------------------
1 file changed, 29 insertions(+), 27 deletions(-)
(limited to 'gr-filter/examples/channelize.py')
diff --git a/gr-filter/examples/channelize.py b/gr-filter/examples/channelize.py
index 4d92bdce3f..83e85bc9c1 100644
--- a/gr-filter/examples/channelize.py
+++ b/gr-filter/examples/channelize.py
@@ -12,7 +12,8 @@ from gnuradio import gr
from gnuradio import blocks
from gnuradio import filter
from gnuradio.fft import window
-import sys, time
+import sys
+import time
import numpy
try:
@@ -25,9 +26,11 @@ try:
import pylab
from pylab import mlab
except ImportError:
- sys.stderr.write("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).\n")
+ sys.stderr.write(
+ "Error: Program requires matplotlib (see: matplotlib.sourceforge.net).\n")
sys.exit(1)
+
class pfb_top_block(gr.top_block):
def __init__(self):
gr.top_block.__init__(self)
@@ -35,7 +38,7 @@ class pfb_top_block(gr.top_block):
self._N = 2000000 # number of samples to use
self._fs = 1000 # initial sampling rate
self._M = M = 9 # Number of channels to channelize
- self._ifs = M*self._fs # initial sampling rate
+ self._ifs = M * self._fs # initial sampling rate
# Create a set of taps for the PFB channelizer
self._taps = filter.firdes.low_pass_2(1, self._ifs, 475.50, 50,
@@ -55,9 +58,10 @@ class pfb_top_block(gr.top_block):
self.add = blocks.add_cc()
freqs = [-70, -50, -30, -10, 10, 20, 40, 60, 80]
for i in range(len(freqs)):
- f = freqs[i] + (M / 2-M+i+1)*self._fs
- self.signals.append(analog.sig_source_c(self._ifs, analog.GR_SIN_WAVE, f, 1))
- self.connect(self.signals[i], (self.add,i))
+ f = freqs[i] + (M / 2 - M + i + 1) * self._fs
+ self.signals.append(analog.sig_source_c(
+ self._ifs, analog.GR_SIN_WAVE, f, 1))
+ self.connect(self.signals[i], (self.add, i))
self.head = blocks.head(gr.sizeof_gr_complex, self._N)
@@ -72,7 +76,7 @@ class pfb_top_block(gr.top_block):
self.connect(self.add, self.snk_i)
# Use this to play with the channel mapping
- #self.pfb.set_channel_map([5,6,7,8,0,1,2,3,4])
+ # self.pfb.set_channel_map([5,6,7,8,0,1,2,3,4])
# Create a vector sink for each of M output channels of the filter and connect it
self.snks = list()
@@ -91,9 +95,9 @@ def main():
print("Run time: %f" % (tend - tstart))
if 1:
- fig_in = pylab.figure(1, figsize=(16,9), facecolor="w")
- fig1 = pylab.figure(2, figsize=(16,9), facecolor="w")
- fig2 = pylab.figure(3, figsize=(16,9), facecolor="w")
+ fig_in = pylab.figure(1, figsize=(16, 9), facecolor="w")
+ fig1 = pylab.figure(2, figsize=(16, 9), facecolor="w")
+ fig2 = pylab.figure(3, figsize=(16, 9), facecolor="w")
Ns = 1000
Ne = 10000
@@ -106,22 +110,21 @@ def main():
d = tb.snk_i.data()[Ns:Ne]
spin_f = fig_in.add_subplot(2, 1, 1)
- X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs,
- window = lambda d: d*winfunc(fftlen),
- scale_by_freq=True)
- X_in = 10.0*numpy.log10(abs(X))
+ X, freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs,
+ window=lambda d: d * winfunc(fftlen),
+ scale_by_freq=True)
+ X_in = 10.0 * numpy.log10(abs(X))
f_in = numpy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size))
pin_f = spin_f.plot(f_in, X_in, "b")
- spin_f.set_xlim([min(f_in), max(f_in)+1])
+ spin_f.set_xlim([min(f_in), max(f_in) + 1])
spin_f.set_ylim([-200.0, 50.0])
spin_f.set_title("Input Signal", weight="bold")
spin_f.set_xlabel("Frequency (Hz)")
spin_f.set_ylabel("Power (dBW)")
-
Ts = 1.0 / fs
- Tmax = len(d)*Ts
+ Tmax = len(d) * Ts
t_in = numpy.arange(0, Tmax, Ts)
x_in = numpy.array(d)
@@ -141,21 +144,21 @@ def main():
# time signals on Figure 3
fs_o = tb._fs
Ts_o = 1.0 / fs_o
- Tmax_o = len(d)*Ts_o
+ Tmax_o = len(d) * Ts_o
for i in range(len(tb.snks)):
# remove issues with the transients at the beginning
# also remove some corruption at the end of the stream
# this is a bug, probably due to the corner cases
d = tb.snks[i].data()[Ns:Ne]
- sp1_f = fig1.add_subplot(Nrows, Ncols, 1+i)
- X,freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs_o,
- window = lambda d: d*winfunc(fftlen),
- scale_by_freq=True)
- X_o = 10.0*numpy.log10(abs(X))
+ sp1_f = fig1.add_subplot(Nrows, Ncols, 1 + i)
+ X, freq = mlab.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs_o,
+ window=lambda d: d * winfunc(fftlen),
+ scale_by_freq=True)
+ X_o = 10.0 * numpy.log10(abs(X))
f_o = numpy.arange(-fs_o / 2.0, fs_o / 2.0, fs_o / float(X_o.size))
p2_f = sp1_f.plot(f_o, X_o, "b")
- sp1_f.set_xlim([min(f_o), max(f_o)+1])
+ sp1_f.set_xlim([min(f_o), max(f_o) + 1])
sp1_f.set_ylim([-200.0, 50.0])
sp1_f.set_title(("Channel %d" % i), weight="bold")
@@ -164,10 +167,10 @@ def main():
x_o = numpy.array(d)
t_o = numpy.arange(0, Tmax_o, Ts_o)
- sp2_o = fig2.add_subplot(Nrows, Ncols, 1+i)
+ sp2_o = fig2.add_subplot(Nrows, Ncols, 1 + i)
p2_o = sp2_o.plot(t_o, x_o.real, "b")
p2_o = sp2_o.plot(t_o, x_o.imag, "r")
- sp2_o.set_xlim([min(t_o), max(t_o)+1])
+ sp2_o.set_xlim([min(t_o), max(t_o) + 1])
sp2_o.set_ylim([-2, 2])
sp2_o.set_title(("Channel %d" % i), weight="bold")
@@ -182,4 +185,3 @@ if __name__ == "__main__":
main()
except KeyboardInterrupt:
pass
-
--
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