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-analog/examples/fmtest.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-analog/examples/fmtest.py')
| -rw-r--r-- | gr-analog/examples/fmtest.py | 34 |
1 files changed, 14 insertions, 20 deletions
diff --git a/gr-analog/examples/fmtest.py b/gr-analog/examples/fmtest.py index 04218a4472..f58c202592 100644 --- a/gr-analog/examples/fmtest.py +++ b/gr-analog/examples/fmtest.py @@ -29,13 +29,7 @@ from gnuradio import filter from gnuradio import analog from gnuradio import channels import sys, math, time - -try: - import scipy - from scipy import fftpack -except ImportError: - print("Error: Program requires scipy (see: www.scipy.org).") - sys.exit(1) +import numpy try: import pylab @@ -147,7 +141,7 @@ def main(): Ne = 100000 fftlen = 8192 - winfunc = scipy.blackman + winfunc = numpy.blackman # Plot transmitted signal fs = fm._if_rate @@ -158,8 +152,8 @@ def main(): X,freq = sp1_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs, window = lambda d: d*winfunc(fftlen), visible=False) - X_in = 10.0*scipy.log10(abs(fftpack.fftshift(X))) - f_in = scipy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size)) + X_in = 10.0*numpy.log10(abs(numpy.fft.fftshift(X))) + f_in = numpy.arange(-fs / 2.0, fs / 2.0, fs / float(X_in.size)) p1_f = sp1_f.plot(f_in, X_in, "b") sp1_f.set_xlim([min(f_in), max(f_in)+1]) sp1_f.set_ylim([-120.0, 20.0]) @@ -171,16 +165,16 @@ def main(): Ts = 1.0 / fs Tmax = len(d)*Ts - t_in = scipy.arange(0, Tmax, Ts) - x_in = scipy.array(d) + t_in = numpy.arange(0, Tmax, Ts) + x_in = numpy.array(d) sp1_t = fig1.add_subplot(2, 1, 2) p1_t = sp1_t.plot(t_in, x_in.real, "b-o") #p1_t = sp1_t.plot(t_in, x_in.imag, "r-o") sp1_t.set_ylim([-5, 5]) # Set up the number of rows and columns for plotting the subfigures - Ncols = int(scipy.floor(scipy.sqrt(fm.num_rx_channels()))) - Nrows = int(scipy.floor(fm.num_rx_channels() / Ncols)) + Ncols = int(numpy.floor(numpy.sqrt(fm.num_rx_channels()))) + Nrows = int(numpy.floor(fm.num_rx_channels() / Ncols)) if(fm.num_rx_channels() % Ncols != 0): Nrows += 1 @@ -197,10 +191,10 @@ def main(): X,freq = sp2_f.psd(d, NFFT=fftlen, noverlap=fftlen / 4, Fs=fs_o, window = lambda d: d*winfunc(fftlen), visible=False) - #X_o = 10.0*scipy.log10(abs(fftpack.fftshift(X))) - X_o = 10.0*scipy.log10(abs(X)) - #f_o = scipy.arange(-fs_o/2.0, fs_o/2.0, fs_o/float(X_o.size)) - f_o = scipy.arange(0, fs_o / 2.0, fs_o/2.0/float(X_o.size)) + #X_o = 10.0*numpy.log10(abs(numpy.fft.fftshift(X))) + 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)) + f_o = numpy.arange(0, fs_o / 2.0, fs_o/2.0/float(X_o.size)) p2_f = sp2_f.plot(f_o, X_o, "b") sp2_f.set_xlim([min(f_o), max(f_o)+0.1]) sp2_f.set_ylim([-120.0, 20.0]) @@ -213,9 +207,9 @@ def main(): Ts = 1.0 / fs_o Tmax = len(d)*Ts - t_o = scipy.arange(0, Tmax, Ts) + t_o = numpy.arange(0, Tmax, Ts) - x_t = scipy.array(d) + x_t = numpy.array(d) sp2_t = fig3.add_subplot(Nrows, Ncols, 1+i) p2_t = sp2_t.plot(t_o, x_t.real, "b") p2_t = sp2_t.plot(t_o, x_t.imag, "r") |