[Commit-gnuradio] [gnuradio] 07/13: redo qa_random without print statements and scipy; add stand-alone evaluation script in gnuradio-runtime/apps

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commit 44fb1cb0482fa778c8e652164551711818db5476
Author: Stefan <address@hidden>
Date:   Fri Sep 4 11:22:13 2015 +0200

    redo qa_random without print statements and scipy; add stand-alone 
evaluation script in gnuradio-runtime/apps
---
 gnuradio-runtime/apps/evaluation_random_numbers.py | 139 +++++++++++++++++++++
 gnuradio-runtime/python/gnuradio/gr/qa_random.py   | 109 ++--------------
 2 files changed, 148 insertions(+), 100 deletions(-)

diff --git a/gnuradio-runtime/apps/evaluation_random_numbers.py 
b/gnuradio-runtime/apps/evaluation_random_numbers.py
new file mode 100644
index 0000000..069493c
--- /dev/null
+++ b/gnuradio-runtime/apps/evaluation_random_numbers.py
@@ -0,0 +1,139 @@
+#!/usr/bin/env python
+#
+# Copyright 2015 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.
+#
+
+from gnuradio import gr
+import numpy as np
+from scipy.stats import norm, laplace, rayleigh
+from matplotlib import pyplot as plt
+
+# NOTE: scipy and matplotlib are optional packages and not included in the 
default gnuradio dependencies
+
+#*** SETUP ***#
+
+# Number of realisations per histogram
+num_tests = 1000000
+
+# Set number of bins in histograms
+uniform_num_bins = 31
+gauss_num_bins = 31
+rayleigh_num_bins = 31
+laplace_num_bins = 31
+
+rndm = gr.random() # instance of gnuradio random class (gr::random)
+
+print 'All histograms contain',num_tests,'realisations.'
+
+#*** GENERATE DATA ***#
+
+uniform_values = np.zeros(num_tests)
+gauss_values = np.zeros(num_tests)
+rayleigh_values = np.zeros(num_tests)
+laplace_values = np.zeros(num_tests)
+
+for k in range(num_tests):
+    uniform_values[k] = rndm.ran1()
+    gauss_values[k] = rndm.gasdev()
+    rayleigh_values[k] = rndm.rayleigh()
+    laplace_values[k] = rndm.laplacian()
+
+#*** HISTOGRAM DATA AND CALCULATE EXPECTED COUNTS ***#
+
+uniform_bins = np.linspace(0,1,uniform_num_bins)
+gauss_bins = np.linspace(-8,8,gauss_num_bins)
+laplace_bins = np.linspace(-8,8,laplace_num_bins)
+rayleigh_bins = np.linspace(0,10,rayleigh_num_bins)
+
+uniform_hist = np.histogram(uniform_values,uniform_bins)
+gauss_hist = np.histogram(gauss_values,gauss_bins)
+rayleigh_hist = np.histogram(rayleigh_values,rayleigh_bins)
+laplace_hist = np.histogram(laplace_values,laplace_bins)
+
+uniform_expected = np.zeros(uniform_num_bins-1)
+gauss_expected = np.zeros(gauss_num_bins-1)
+rayleigh_expected = np.zeros(rayleigh_num_bins-1)
+laplace_expected = np.zeros(laplace_num_bins-1)
+
+for k in range(len(uniform_hist[0])):
+    uniform_expected[k] = num_tests/float(uniform_num_bins-1)
+
+for k in range(len(gauss_hist[0])):
+    gauss_expected[k] = 
float(norm.cdf(gauss_hist[1][k+1])-norm.cdf(gauss_hist[1][k]))*num_tests
+
+for k in range(len(rayleigh_hist[0])):
+    rayleigh_expected[k] = 
float(rayleigh.cdf(rayleigh_hist[1][k+1])-rayleigh.cdf(rayleigh_hist[1][k]))*num_tests
+
+for k in range(len(laplace_hist[0])):
+    laplace_expected[k] = 
float(laplace.cdf(laplace_hist[1][k+1])-laplace.cdf(laplace_hist[1][k]))*num_tests
+
+#*** PLOT HISTOGRAMS AND EXPECTATIONS TAKEN FROM SCIPY ***#
+
+uniform_bins_center = uniform_bins[0:-1]+(uniform_bins[1]-uniform_bins[0])/2.0
+gauss_bins_center = gauss_bins[0:-1]+(gauss_bins[1]-gauss_bins[0])/2.0
+rayleigh_bins_center = 
rayleigh_bins[0:-1]+(rayleigh_bins[1]-rayleigh_bins[0])/2.0
+laplace_bins_center = laplace_bins[0:-1]+(laplace_bins[1]-laplace_bins[0])/2.0
+
+plt.figure(1)
+
+plt.subplot(2,1,1)
+plt.plot(uniform_bins_center,uniform_hist[0],'s--',uniform_bins_center,uniform_expected,'o:')
+plt.xlabel('Bins'), plt.ylabel('Count'), plt.title('Uniform: Distribution')
+plt.legend(['histogram gr::random','calculation scipy'],loc=1)
+
+plt.subplot(2,1,2)
+plt.plot(uniform_bins_center,uniform_hist[0]/uniform_expected,'rs--')
+plt.xlabel('Bins'), plt.ylabel('Relative deviation'), plt.title('Uniform: 
Relative deviation to scipy')
+
+plt.figure(2)
+
+plt.subplot(2,1,1)
+plt.plot(gauss_bins_center,gauss_hist[0],'s--',gauss_bins_center,gauss_expected,'o:')
+plt.xlabel('Bins'), plt.ylabel('Count'), plt.title('Gauss: Distribution')
+plt.legend(['histogram gr::random','calculation scipy'],loc=1)
+
+plt.subplot(2,1,2)
+plt.plot(gauss_bins_center,gauss_hist[0]/gauss_expected,'rs--')
+plt.xlabel('Bins'), plt.ylabel('Relative deviation'), plt.title('Gauss: 
Relative deviation to scipy')
+
+plt.figure(3)
+
+plt.subplot(2,1,1)
+plt.plot(rayleigh_bins_center,rayleigh_hist[0],'s--',rayleigh_bins_center,rayleigh_expected,'o:')
+plt.xlabel('Bins'), plt.ylabel('Count'), plt.title('Rayleigh: Distribution')
+plt.legend(['histogram gr::random','calculation scipy'],loc=1)
+
+
+plt.subplot(2,1,2)
+plt.plot(rayleigh_bins_center,rayleigh_hist[0]/rayleigh_expected,'rs--')
+plt.xlabel('Bins'), plt.ylabel('Relative deviation'), plt.title('Rayleigh: 
Relative deviation to scipy')
+
+plt.figure(4)
+
+plt.subplot(2,1,1)
+plt.plot(laplace_bins_center,laplace_hist[0],'s--',laplace_bins_center,laplace_expected,'o:')
+plt.xlabel('Bins'), plt.ylabel('Count'), plt.title('Laplace: Distribution')
+plt.legend(['histogram gr::random','calculation scipy'],loc=1)
+
+plt.subplot(2,1,2)
+plt.plot(laplace_bins_center,laplace_hist[0]/laplace_expected,'rs--')
+plt.xlabel('Bins'), plt.ylabel('Relative deviation'), plt.title('Laplace: 
Relative deviation to scipy')
+
+plt.show()
diff --git a/gnuradio-runtime/python/gnuradio/gr/qa_random.py 
b/gnuradio-runtime/python/gnuradio/gr/qa_random.py
index c0d9a7f..83fee56 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__':