[Commit-gnuradio] [gnuradio] 01/13: include random.h in swig; add qa_random testcase

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commit 1206251231696359270a260508551e044f3af33a
Author: Stefan <address@hidden>
Date:   Tue Sep 1 12:46:09 2015 +0200

    include random.h in swig; add qa_random testcase
---
 gnuradio-runtime/python/gnuradio/gr/qa_random.py | 99 ++++++++++++++++++++++++
 gnuradio-runtime/swig/runtime_swig.i             |  2 +
 2 files changed, 101 insertions(+)

diff --git a/gnuradio-runtime/python/gnuradio/gr/qa_random.py 
b/gnuradio-runtime/python/gnuradio/gr/qa_random.py
new file mode 100644
index 0000000..39d75f3
--- /dev/null
+++ b/gnuradio-runtime/python/gnuradio/gr/qa_random.py
@@ -0,0 +1,99 @@
+#!/usr/bin/env python
+#
+# Copyright 2006,2007,2010 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.
+#
+
+from gnuradio import gr, gr_unittest
+import numpy as np
+from scipy.stats import norm, laplace
+
+class test_random(gr_unittest.TestCase):
+
+    # Disclaimer
+    def test_0(self):
+        print 'NOTE: Following tests are not statistically significant! Check 
out fulltest_random.py for full testing.'
+        self.assertEqual(1,1)
+
+    # Check for range [0,1) of uniform distributed random numbers and print 
minimal and maximal value
+    def test_1(self):
+        print '# TEST 1'
+        print 'Uniform distributed numbers: Range'
+        num_tests = 10000
+        values = np.zeros(num_tests)
+        rndm = gr.random()
+        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):', num_tests, min(values), 
max(values)
+
+    # Check uniformly distributed random numbers on uniformity (without 
assert, only printing)
+    def test_2(self):
+        print '# TEST 2'
+        print 'Uniform random numbers: Distribution'
+        num_tests = 10000
+        num_bins = 11
+        values = np.zeros(num_tests)
+        rndm = gr.random()
+        for k in range(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(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_tests = 10000
+        num_bins = 11
+        hist_range = [-5,5]
+        values = np.zeros(num_tests)
+        rndm = gr.random()
+        for k in range(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]))*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_tests = 100000
+        num_bins = 11
+        hist_range = [-5,5]
+        values = np.zeros(num_tests)
+        rndm = gr.random()
+        for k in range(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]))*num_tests
+
+if __name__ == '__main__':
+    gr_unittest.run(test_random, "test_random.xml")
diff --git a/gnuradio-runtime/swig/runtime_swig.i 
b/gnuradio-runtime/swig/runtime_swig.i
index d4b55f1..15cfebd 100644
--- a/gnuradio-runtime/swig/runtime_swig.i
+++ b/gnuradio-runtime/swig/runtime_swig.i
@@ -60,6 +60,7 @@
 #include <gnuradio/top_block.h>
 #include <gnuradio/logger.h>
 #include <gnuradio/math.h>
+#include <gnuradio/random.h>
 %}
 
 %constant int sizeof_char      = sizeof(char);
@@ -95,3 +96,4 @@
 %include "gr_ctrlport.i"
 
 %include "gnuradio/math.h"
+%include "gnuradio/random.h"