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-qtgui/apps/plot_base.py | 20 ++++++++------------
1 file changed, 8 insertions(+), 12 deletions(-)
(limited to 'gr-qtgui/apps/plot_base.py')
diff --git a/gr-qtgui/apps/plot_base.py b/gr-qtgui/apps/plot_base.py
index ce409000bd..46f85ab8f5 100644
--- a/gr-qtgui/apps/plot_base.py
+++ b/gr-qtgui/apps/plot_base.py
@@ -37,11 +37,7 @@ except ImportError:
print("Error: Program requires PyQt4 and gr-qtgui.")
sys.exit(1)
-try:
- import scipy
-except ImportError:
- print("Error: Scipy required (www.scipy.org).")
- sys.exit(1)
+import numpy
try:
from gnuradio.qtgui.plot_constellation_form import *
@@ -60,7 +56,7 @@ def read_samples(filename, start, in_size, min_size, dtype, dtype_size):
# Read in_size number of samples from file
fhandle = open(filename, 'r')
fhandle.seek(start*dtype_size, 0)
- data = scipy.fromfile(fhandle, dtype=dtype, count=in_size)
+ data = numpy.fromfile(fhandle, dtype=dtype, count=in_size)
data_min = 1.1*data.min()
data_max = 1.1*data.max()
data = data.tolist()
@@ -80,31 +76,31 @@ def read_samples(filename, start, in_size, min_size, dtype, dtype_size):
def read_samples_f(filename, start, in_size, min_size=0):
return read_samples(filename, start, in_size, min_size,
- scipy.float32, gr.sizeof_float)
+ numpy.float32, gr.sizeof_float)
def read_samples_i(filename, start, in_size, min_size=0):
return read_samples(filename, start, in_size, min_size,
- scipy.int32, gr.sizeof_int)
+ numpy.int32, gr.sizeof_int)
def read_samples_s(filename, start, in_size, min_size=0):
return read_samples(filename, start, in_size, min_size,
- scipy.int16, gr.sizeof_short)
+ numpy.int16, gr.sizeof_short)
def read_samples_b(filename, start, in_size, min_size=0):
d,mn,mx = read_samples(filename, start, in_size, min_size,
- scipy.int8, gr.sizeof_char)
+ numpy.int8, gr.sizeof_char)
# Bit of a hack since we want to read the data as signed ints, but
# the blocks.vector_source_b will only accept unsigned. We read in as
# signed, do our min/max and things on that, then convert here.
- d = scipy.array(d, dtype=scipy.uint8).tolist()
+ d = numpy.array(d, dtype=numpy.uint8).tolist()
return d,mn,mx
def read_samples_c(filename, start, in_size, min_size=0):
# Complex samples are handled differently
fhandle = open(filename, 'r')
fhandle.seek(start*gr.sizeof_gr_complex, 0)
- data = scipy.fromfile(fhandle, dtype=scipy.complex64, count=in_size)
+ data = numpy.fromfile(fhandle, dtype=numpy.complex64, count=in_size)
data_min = 1.1*float(min(data.real.min(), data.imag.min()))
data_max = 1.1*float(max(data.real.max(), data.imag.max()))
data = data.tolist()
--
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