diff options
| author | Marcus Müller <marcus@hostalia.de> | 2018-08-24 23:00:55 +0200 |
|---|---|---|
| committer | Marcus Müller <marcus@hostalia.de> | 2018-11-02 22:15:53 +0100 |
| commit | 797994a11ac5ec6bee9ea01c092947d0c34115f1 (patch) | |
| tree | 7381f53008ba56e6b93398fa92be482d12da4f43 /gr-filter/examples/reconstruction.py | |
| parent | e07751acc8424f4dd987f79c32dd247ed347902c (diff) | |
Replace scipy/pylab where numpy/pyplot is sufficient
This should reduce the number of times users are prompted to install
pylab || scipy when they'd actually get away with functionality fully
contained in numpy and matplotlib.
This only solves the obvious cases. There's some usage of `pylab.mlab`
that would need more than 20s of consideration.
Diffstat (limited to 'gr-filter/examples/reconstruction.py')
| -rw-r--r-- | gr-filter/examples/reconstruction.py | 32 |
1 files changed, 13 insertions, 19 deletions
diff --git a/gr-filter/examples/reconstruction.py b/gr-filter/examples/reconstruction.py index c9c1cd3922..565ccef00d 100644 --- a/gr-filter/examples/reconstruction.py +++ b/gr-filter/examples/reconstruction.py @@ -27,6 +27,7 @@ from gnuradio import gr, digital from gnuradio import filter from gnuradio import blocks import sys +import numpy try: from gnuradio import channels @@ -35,14 +36,7 @@ except ImportError: sys.exit(1) try: - import scipy - from scipy import fftpack -except ImportError: - print("Error: Program requires scipy (see: www.scipy.org).") - sys.exit(1) - -try: - import pylab + from matplotlib import pyplot except ImportError: print("Error: Program requires matplotlib (see: matplotlib.sourceforge.net).") sys.exit(1) @@ -53,7 +47,7 @@ def main(): N = 10000 fs = 2000.0 Ts = 1.0 / fs - t = scipy.arange(0, N*Ts, Ts) + t = numpy.arange(0, N*Ts, Ts) # When playing with the number of channels, be careful about the filter # specs and the channel map of the synthesizer set below. @@ -70,10 +64,10 @@ def main(): # Create a modulated signal npwr = 0.01 - data = scipy.random.randint(0, 256, N) + data = numpy.random.randint(0, 256, N) rrc_taps = filter.firdes.root_raised_cosine(1, 2, 1, 0.35, 41) - src = blocks.vector_source_b(data.astype(scipy.uint8).tolist(), False) + src = blocks.vector_source_b(data.astype(numpy.uint8).tolist(), False) mod = digital.bpsk_mod(samples_per_symbol=2) chan = channels.channel_model(npwr) rrc = filter.fft_filter_ccc(1, rrc_taps) @@ -107,13 +101,13 @@ def main(): tb.connect(synthesizer, snk) tb.run() - sin = scipy.array(src_snk.data()[1000:]) - sout = scipy.array(snk.data()[1000:]) + sin = numpy.array(src_snk.data()[1000:]) + sout = numpy.array(snk.data()[1000:]) # Plot original signal fs_in = nchans*fs - f1 = pylab.figure(1, figsize=(16,12), facecolor='w') + f1 = pyplot.figure(1, figsize=(16,12), facecolor='w') s11 = f1.add_subplot(2,2,1) s11.psd(sin, NFFT=fftlen, Fs=fs_in) s11.set_title("PSD of Original Signal") @@ -133,10 +127,10 @@ def main(): s13.set_ylim([-2, 2]) # Plot channels - nrows = int(scipy.sqrt(nchans)) - ncols = int(scipy.ceil(float(nchans) / float(nrows))) + nrows = int(numpy.sqrt(nchans)) + ncols = int(numpy.ceil(float(nchans) / float(nrows))) - f2 = pylab.figure(2, figsize=(16,12), facecolor='w') + f2 = pyplot.figure(2, figsize=(16,12), facecolor='w') for n in range(nchans): s = f2.add_subplot(nrows, ncols, n+1) s.psd(vsnk[n].data(), NFFT=fftlen, Fs=fs_in) @@ -145,7 +139,7 @@ def main(): # Plot reconstructed signal fs_out = 2*nchans*fs - f3 = pylab.figure(3, figsize=(16,12), facecolor='w') + f3 = pyplot.figure(3, figsize=(16,12), facecolor='w') s31 = f3.add_subplot(2,2,1) s31.psd(sout, NFFT=fftlen, Fs=fs_out) s31.set_title("PSD of Reconstructed Signal") @@ -164,7 +158,7 @@ def main(): s33.set_xlim([-2, 2]) s33.set_ylim([-2, 2]) - pylab.show() + pyplot.show() if __name__ == "__main__": |