From 797994a11ac5ec6bee9ea01c092947d0c34115f1 Mon Sep 17 00:00:00 2001
From: Marcus Müller <marcus@hostalia.de>
Date: Fri, 24 Aug 2018 23:00:55 +0200
Subject: 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.
---
gr-analog/examples/fmtest.py | 34 ++++++++++++++--------------------
1 file changed, 14 insertions(+), 20 deletions(-)
(limited to 'gr-analog/examples/fmtest.py')
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")
--
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