diff options
| author | Stefan <stefan.wunsch@student.kit.edu> | 2015-09-04 11:22:13 +0200 |
|---|---|---|
| committer | Stefan <stefan.wunsch@student.kit.edu> | 2015-09-04 11:22:13 +0200 |
| commit | 44fb1cb0482fa778c8e652164551711818db5476 (patch) | |
| tree | 7de348490303418f1212caebca3d68ef602f1a89 /gnuradio-runtime/python | |
| parent | 190ebe6caa1b92172fba691285b1bdb684e6ae83 (diff) | |
redo qa_random without print statements and scipy; add stand-alone evaluation script in gnuradio-runtime/apps
Diffstat (limited to 'gnuradio-runtime/python')
| -rw-r--r-- | gnuradio-runtime/python/gnuradio/gr/qa_random.py | 109 |
1 files changed, 9 insertions, 100 deletions
diff --git a/gnuradio-runtime/python/gnuradio/gr/qa_random.py b/gnuradio-runtime/python/gnuradio/gr/qa_random.py index c0d9a7f34c..83fee56181 100644 --- a/gnuradio-runtime/python/gnuradio/gr/qa_random.py +++ b/gnuradio-runtime/python/gnuradio/gr/qa_random.py @@ -1,6 +1,6 @@ #!/usr/bin/env python # -# Copyright 2006,2007,2010 Free Software Foundation, Inc. +# Copyright 2006,2007,2010,2015 Free Software Foundation, Inc. # # This file is part of GNU Radio # @@ -22,133 +22,42 @@ from gnuradio import gr, gr_unittest import numpy as np -from scipy.stats import norm, laplace, rayleigh -#from time import sleep class test_random(gr_unittest.TestCase): - num_tests = 10000 + # NOTE: For tests on the output distribution of the random numbers, see gnuradio-runtime/apps/evaluation_random_numbers.py. - # Disclaimer - def test_0(self): - print 'NOTE: Following tests are not statistically significant!' - print 'Realisations per test:',self.num_tests - self.assertEqual(1,1) - - # Check for range [0,1) of uniform distributed random numbers and print minimal and maximal value + # Check for range [0,1) of uniform distributed random numbers def test_1(self): - print '# TEST 1' - print 'Uniform distributed numbers: Range' - values = np.zeros(self.num_tests) + num_tests = 10000 + values = np.zeros(num_tests) rndm = gr.random() - for k in range(self.num_tests): + for k in range(num_tests): values[k] = rndm.ran1() for value in values: self.assertLess(value, 1) self.assertGreaterEqual(value, 0) - print 'Uniform random numbers (num/min/max):', self.num_tests, min(values), max(values) - # Check uniformly distributed random numbers on uniformity (without assert, only printing) + # Check reseed method (init with time and seed as fix number) def test_2(self): - print '# TEST 2' - print 'Uniform random numbers: Distribution' - num_bins = 11 - values = np.zeros(self.num_tests) - rndm = gr.random() - for k in range(self.num_tests): - values[k] = rndm.ran1() - bins = np.linspace(0,1,num_bins) # These are the bin edges! - hist = np.histogram(values,bins) - print 'Lower edge bin / upper edge bin / count / expected' - for k in range(len(hist[0])): - print hist[1][k], hist[1][k+1], hist[0][k], float(self.num_tests)/(num_bins-1) - - # Check distribution of normally (gaussian, mean=0, variance=1) distributed random numbers (no assert) - def test_3(self): - print '# TEST 3' - print 'Normal random numbers: Distribution' - num_bins = 11 - hist_range = [-5,5] - values = np.zeros(self.num_tests) - rndm = gr.random() - for k in range(self.num_tests): - values[k] = rndm.gasdev() - bins = np.linspace(hist_range[0],hist_range[1],num_bins) - hist = np.histogram(values,bins) - print 'Lower edge bin / upper edge bin / count / expected' - for k in range(len(hist[0])): - print hist[1][k], hist[1][k+1], hist[0][k], float(norm.cdf(hist[1][k+1])-norm.cdf(hist[1][k]))*self.num_tests - - # Check distribution of laplacian (mean=0, variance=1) distributed random numbers (no assert) - def test_4(self): - print '# TEST 4' - print 'Laplacian random numbers: Distribution' - num_bins = 11 - hist_range = [-5,5] - values = np.zeros(self.num_tests) - rndm = gr.random() - for k in range(self.num_tests): - values[k] = rndm.laplacian() - bins = np.linspace(hist_range[0],hist_range[1],num_bins) - hist = np.histogram(values,bins) - print 'Lower edge bin / upper edge bin / count / expected' - for k in range(len(hist[0])): - print hist[1][k], hist[1][k+1], hist[0][k], float(laplace.cdf(hist[1][k+1])-laplace.cdf(hist[1][k]))*self.num_tests - - # Check distribution of laplacian (mean=0, variance=1) distributed random numbers (no assert) - def test_5(self): - print '# TEST 5' - print 'Rayleigh random numbers: Distribution' - num_bins = 11 - hist_range = [0,10] - values = np.zeros(self.num_tests) - rndm = gr.random() - for k in range(self.num_tests): - values[k] = rndm.rayleigh() - bins = np.linspace(hist_range[0],hist_range[1],num_bins) - hist = np.histogram(values,bins) - print 'Lower edge bin / upper edge bin / count / expected' - for k in range(len(hist[0])): - print hist[1][k], hist[1][k+1], hist[0][k], float(rayleigh.cdf(hist[1][k+1])-rayleigh.cdf(hist[1][k]))*self.num_tests - - # Check seeds (init with time and seed as fix number) - def test_6(self): - print '# TEST 6' num = 5 - print 'Some random numbers in [0,1), should change every run:' - rndm0 = gr.random(0); # init with time - # NOTE: the sleep increases the executiont time massively, remove assert for convenience - #sleep(1) - #rndm1 = gr.random(0); # init with fix seed - for k in range(num): - x = rndm0.ran1(); - print x, - # y = rndm1.ran1(); - # print x, '!=', y - # self.assertNotEqual(x,y) - print ' ' - - print 'Some random numbers in [0,1) (seed two instances), should be the same every run:' rndm0 = gr.random(42); # init with time rndm1 = gr.random(42); # init with fix seed for k in range(num): x = rndm0.ran1(); y = rndm1.ran1(); - print x, '=', y self.assertEqual(x,y) - print 'Some random numbers in [0,1) (reseed one instance), should be the same every run:' x = np.zeros(num) y = np.zeros(num) - rndm0 = gr.random(42); # init with time + rndm0 = gr.random(42); # init with fix seed 1 for k in range(num): x[k] = rndm0.ran1(); - rndm1.reseed(43); # init with fix seed + rndm1.reseed(43); # init with fix seed 2 for k in range(num): y[k] = rndm0.ran1(); for k in range(num): - print x[k], '!=', y[k] self.assertNotEqual(x[k],y[k]) if __name__ == '__main__': |