--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/spandsp-0.0.3/spandsp-0.0.3/tests/awgn_tests.c	Fri Jun 25 16:00:21 2010 +0200
@@ -0,0 +1,150 @@
+/*
+ * SpanDSP - a series of DSP components for telephony
+ *
+ * awgn_tests.c
+ *
+ * Written by Steve Underwood <steveu@coppice.org>
+ *
+ * Copyright (C) 2001 Steve Underwood
+ *
+ * All rights reserved.
+ *
+ * This program is free software; you can redistribute it and/or modify
+ * it under the terms of the GNU General Public License version 2, as
+ * published by the Free Software Foundation.
+ *
+ * This program 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 this program; if not, write to the Free Software
+ * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
+ *
+ * $Id: awgn_tests.c,v 1.12 2006/11/19 14:07:26 steveu Exp $
+ */
+
+/*! \page awgn_tests_page AWGN tests
+\section awgn_tests_page_sec_1 What does it do?
+*/
+
+#ifdef HAVE_CONFIG_H
+#include "config.h"
+#endif
+
+#include <stdio.h>
+#include <inttypes.h>
+#include <stdlib.h>
+#include <string.h>
+#if defined(HAVE_TGMATH_H)
+#include <tgmath.h>
+#endif
+#if defined(HAVE_MATH_H)
+#include <math.h>
+#endif
+#include <tiffio.h>
+
+#include "spandsp.h"
+
+#if !defined(M_PI)
+# define M_PI           3.14159265358979323846  /* pi */
+#endif
+
+#define OUT_FILE_NAME   "awgn.wav"
+
+/* Some simple sanity tests for the Gaussian noise generation routines */
+
+int main (int argc, char *argv[])
+{
+    int i;
+    int j;
+    int clip_high;
+    int clip_low;
+    int total_samples;
+    int idum = 1234567;
+    int16_t value;
+    double total;
+    double x;
+    double p;
+    double o;
+    double error;
+    int bins[65536];
+    awgn_state_t noise_source;
+
+    /* Generate noise at several RMS levels between -50dBm and 0dBm. Noise is
+       generated for a large number of samples (1,000,000), and the RMS value
+       of the noise is calculated along the way. If the resulting level is
+       close to the requested RMS level, at least the scaling of the noise
+       should be Ok. At high level some clipping may distort the result a
+       little. */
+    for (j = -50;  j <= 0;  j += 5)
+    {
+        clip_high = 0;
+        clip_low = 0;
+        total = 0.0;
+        awgn_init_dbm0(&noise_source, idum, (float) j);
+        total_samples = 1000000;
+        for (i = 0;  i < total_samples;  i++)
+        {
+            value = awgn(&noise_source);
+            if (value == 32767)
+                clip_high++;
+            else if (value == -32768)
+                clip_low++;
+            total += ((double) value)*((double) value);
+        }
+        error = 100.0*(1.0 - sqrt(total/total_samples)/noise_source.rms);
+        printf("RMS = %.3f (expected %d) %.2f%% error [clipped samples %d+%d]\n",
+               log10(sqrt(total/total_samples)/32768.0)*20.0 + DBM0_MAX_POWER,
+               j,
+               error,
+               clip_low,
+               clip_high);
+        /* We don't check the result at 0dBm0, as there will definitely be a lot of error due to clipping */
+        if (j < 0  &&  fabs(error) > 0.2)
+        {
+            printf("Test failed.\n");
+            exit(2);
+        }
+    }
+    /* Now look at the statistical spread of the results, by collecting data in
+       bins from a large number of samples. Use a fairly high noise level, but
+       low enough to avoid significant clipping. Use the Gaussian model to
+       predict the real probability, and present the results for graphing. */
+    memset(bins, 0, sizeof(bins));
+    clip_high = 0;
+    clip_low = 0;
+    awgn_init_dbm0(&noise_source, idum, -15);
+    total_samples = 10000000;
+    for (i = 0;  i < total_samples;  i++)
+    {
+        value = awgn(&noise_source);
+        if (value == 32767)
+            clip_high++;
+        else if (value == -32768)
+            clip_low++;
+        bins[value + 32768]++;
+    }
+    o = noise_source.rms;
+    for (i = 0;  i < 65536 - 10;  i++)
+    {
+        x = i - 32768;
+        /* Find the real probability for this bin */
+        p = (1.0/(o*sqrt(2.0*M_PI)))*exp(-(x*x)/(2.0*o*o));
+        /* Now do a little smoothing on the real data to get a reasonably
+           steady answer */
+        x = 0;
+        for (j = 0;  j < 10;  j++)
+            x += bins[i + j];
+        x /= 10.0;
+        x /= total_samples;
+        /* Now send it out for graphing. */
+        printf("%6d %.7f %.7f\n", i - 32768, x, p);
+    }
+    
+    printf("Tests passed.\n");
+    return  0;
+}
+/*- End of function --------------------------------------------------------*/
+/*- End of file ------------------------------------------------------------*/