diff options
Diffstat (limited to 'gnuradio-core/src/python')
| -rwxr-xr-x | gnuradio-core/src/python/gnuradio/gr/qa_classify.py | 181 |
1 files changed, 0 insertions, 181 deletions
diff --git a/gnuradio-core/src/python/gnuradio/gr/qa_classify.py b/gnuradio-core/src/python/gnuradio/gr/qa_classify.py deleted file mode 100755 index ac5b53b57..000000000 --- a/gnuradio-core/src/python/gnuradio/gr/qa_classify.py +++ /dev/null @@ -1,181 +0,0 @@ -#!/usr/bin/env python -# -# Copyright 2008,2010 Free Software Foundation, Inc. -# -# This file is part of GNU Radio -# -# GNU Radio is free software; you can redistribute it and/or modify -# it under the terms of the GNU General Public License as published by -# the Free Software Foundation; either version 3, or (at your option) -# any later version. -# -# GNU Radio is distributed in the hope that it will be useful, -# but WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with GNU Radio; see the file COPYING. If not, write to -# the Free Software Foundation, Inc., 51 Franklin Street, -# Boston, MA 02110-1301, USA. -# - -import numpy -from gnuradio import gr, gr_unittest -import copy -#import pygsl.wavelet as wavelet # FIXME: pygsl not checked for in config -import math - - -def sqr(x): - return x*x - -def np2(k): - m = 0 - n = k - 1 - while n > 0: - m += 1 - return m - - -class test_classify(gr_unittest.TestCase): - - def setUp(self): - self.tb = gr.top_block() - - def tearDown(self): - self.tb = None - -# def test_000_(self): -# src_data = numpy.zeros(10) -# trg_data = numpy.zeros(10) -# src = gr.vector_source_f(src_data) -# dst = gr.vector_sink_f() -# self.tb.connect(src, dst) -# self.tb.run() -# rsl_data = dst.data() -# sum = 0 -# for (u,v) in zip(trg_data, rsl_data): -# w = u - v -# sum += w * w -# sum /= float(len(trg_data)) -# assert sum < 1e-6 - - def test_001_(self): - src_data = numpy.array([-1.0, 1.0, -1.0, 1.0]) - trg_data = src_data * 0.5 - src = gr.vector_source_f(src_data) - dst = gr.vector_sink_f() - rail = gr.rail_ff(-0.5, 0.5) - self.tb.connect(src, rail) - self.tb.connect(rail, dst) - self.tb.run() - rsl_data = dst.data() - sum = 0 - for (u, v) in zip(trg_data, rsl_data): - w = u - v - sum += w * w - sum /= float(len(trg_data)) - assert sum < 1e-6 - - def test_002_(self): - src_data = numpy.array([-1.0, - -1.0/2.0, - -1.0/3.0, - -1.0/4.0, - -1.0/5.0]) - trg_data = copy.deepcopy(src_data) - - src = gr.vector_source_f(src_data, False, len(src_data)) - st = gr.stretch_ff(-1.0/5.0, len(src_data)) - dst = gr.vector_sink_f(len(src_data)) - self.tb.connect(src, st) - self.tb.connect(st, dst) - self.tb.run() - rsl_data = dst.data() - sum = 0 - for (u, v) in zip(trg_data, rsl_data): - w = u - v - sum += w * w - sum /= float(len(trg_data)) - assert sum < 1e-6 - - def test_003_(self): - src_grid = (0.0, 1.0, 2.0, 3.0, 4.0) - trg_grid = copy.deepcopy(src_grid) - src_data = (0.0, 1.0, 0.0, 1.0, 0.0) - - src = gr.vector_source_f(src_data, False, len(src_grid)) - sq = gr.squash_ff(src_grid, trg_grid) - dst = gr.vector_sink_f(len(trg_grid)) - self.tb.connect(src, sq) - self.tb.connect(sq, dst) - self.tb.run() - rsl_data = dst.data() - sum = 0 - for (u, v) in zip(src_data, rsl_data): - w = u - v - sum += w * w - sum /= float(len(src_data)) - assert sum < 1e-6 - -# def test_004_(self): # FIXME: requires pygsl -# -# n = 256 -# o = 4 -# ws = wavelet.workspace(n) -# w = wavelet.daubechies(o) -# -# a = numpy.arange(n) -# b = numpy.sin(a*numpy.pi/16.0) -# c = w.transform_forward(b, ws) -# d = w.transform_inverse(c, ws) -# -# src = gr.vector_source_f(b, False, n) -# wv = gr.wavelet_ff(n, o, True) -# -# dst = gr.vector_sink_f(n) -# self.tb.connect(src, wv) -# self.tb.connect(wv, dst) -# self.tb.run() -# e = dst.data() -# -# sum = 0 -# for (u, v) in zip(c, e): -# w = u - v -# sum += w * w -# sum /= float(len(c)) -# assert sum < 1e-6 - - def test_005_(self): - - src_data = (1.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0) - - dwav = numpy.array(src_data) - wvps = numpy.zeros(3) - # wavelet power spectrum - scl = 1.0/sqr(dwav[0]) - k = 1 - for e in range(len(wvps)): - wvps[e] = scl*sqr(dwav[k:k+(01<<e)]).sum() - k += 01<<e - - src = gr.vector_source_f(src_data, False, len(src_data)) - kon = gr.wvps_ff(len(src_data)) - dst = gr.vector_sink_f(int(math.ceil(math.log(len(src_data), 2)))) - - self.tb.connect(src, kon) - self.tb.connect(kon, dst) - - self.tb.run() - snk_data = dst.data() - - sum = 0 - for (u,v) in zip(snk_data, wvps): - w = u - v - sum += w * w - sum /= float(len(snk_data)) - assert sum < 1e-6 - -if __name__ == '__main__': - gr_unittest.run(test_classify, "test_classify.xml") |