diff --git a/Include/pymath.h b/Include/pymath.h
index dc2c427..e3cf22b 100644
--- a/Include/pymath.h
+++ b/Include/pymath.h
@@ -8,9 +8,9 @@
 functions and constants
 **************************************************************************/
 
-/* Python provides implementations for copysign, acosh, asinh, atanh, 
- * log1p and hypot in Python/pymath.c just in case your math library doesn't
- * provide the functions.
+/* Python provides implementations for copysign, round and hypot in
+ * Python/pymath.c just in case your math library doesn't provide the
+ * functions.
  *
  *Note: PC/pyconfig.h defines copysign as _copysign
  */
@@ -22,22 +22,6 @@
 extern double round(double);
 #endif
 
-#ifndef HAVE_ACOSH
-extern double acosh(double);
-#endif
-
-#ifndef HAVE_ASINH
-extern double asinh(double);
-#endif
-
-#ifndef HAVE_ATANH
-extern double atanh(double);
-#endif
-
-#ifndef HAVE_LOG1P
-extern double log1p(double);
-#endif
-
 #ifndef HAVE_HYPOT
 extern double hypot(double, double);
 #endif
diff --git a/Modules/Setup.dist b/Modules/Setup.dist
index e1cb235..45bf531 100644
--- a/Modules/Setup.dist
+++ b/Modules/Setup.dist
@@ -157,7 +157,7 @@
 # Modules that should always be present (non UNIX dependent):
 
 #array arraymodule.c	# array objects
-#cmath cmathmodule.c # -lm # complex math library functions
+#cmath cmathmodule.c _math.c # -lm # complex math library functions
 #math mathmodule.c _math.c # -lm # math library functions, e.g. sin()
 #_struct _struct.c	# binary structure packing/unpacking
 #time timemodule.c # -lm # time operations and variables
diff --git a/Modules/_math.c b/Modules/_math.c
index 9d330aa..e27c100 100644
--- a/Modules/_math.c
+++ b/Modules/_math.c
@@ -1,8 +1,161 @@
 /* Definitions of some C99 math library functions, for those platforms
    that don't implement these functions already. */
 
+#include "Python.h"
 #include <float.h>
-#include <math.h>
+
+/* The following copyright notice applies to the original
+   implementations of acosh, asinh and atanh. */
+
+/*
+ * ====================================================
+ * Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
+ *
+ * Developed at SunPro, a Sun Microsystems, Inc. business.
+ * Permission to use, copy, modify, and distribute this
+ * software is freely granted, provided that this notice 
+ * is preserved.
+ * ====================================================
+ */
+
+static const double ln2 = 6.93147180559945286227E-01;
+static const double two_pow_m28 = 3.7252902984619141E-09; /* 2**-28 */
+static const double two_pow_p28 = 268435456.0; /* 2**28 */
+static const double zero = 0.0;
+
+/* acosh(x)
+ * Method :
+ *      Based on
+ *	      acosh(x) = log [ x + sqrt(x*x-1) ]
+ *      we have
+ *	      acosh(x) := log(x)+ln2, if x is large; else
+ *	      acosh(x) := log(2x-1/(sqrt(x*x-1)+x)) if x>2; else
+ *	      acosh(x) := log1p(t+sqrt(2.0*t+t*t)); where t=x-1.
+ *
+ * Special cases:
+ *      acosh(x) is NaN with signal if x<1.
+ *      acosh(NaN) is NaN without signal.
+ */
+
+double
+_Py_acosh(double x)
+{
+	if (Py_IS_NAN(x)) {
+		return x+x;
+	}
+	if (x < 1.) {			/* x < 1;  return a signaling NaN */
+		errno = EDOM;
+#ifdef Py_NAN
+		return Py_NAN;
+#else
+		return (x-x)/(x-x);
+#endif
+	}
+	else if (x >= two_pow_p28) {	/* x > 2**28 */
+		if (Py_IS_INFINITY(x)) {
+			return x+x;
+		} else {
+			return log(x)+ln2;	/* acosh(huge)=log(2x) */
+		}
+	}
+	else if (x == 1.) {
+		return 0.0;			/* acosh(1) = 0 */
+	}
+	else if (x > 2.) {			/* 2 < x < 2**28 */
+		double t = x*x;
+		return log(2.0*x - 1.0 / (x + sqrt(t - 1.0)));
+	}
+	else {				/* 1 < x <= 2 */
+		double t = x - 1.0;
+		return log1p(t + sqrt(2.0*t + t*t));
+	}
+}
+
+
+/* asinh(x)
+ * Method :
+ *	Based on 
+ *		asinh(x) = sign(x) * log [ |x| + sqrt(x*x+1) ]
+ *	we have
+ *	asinh(x) := x  if  1+x*x=1,
+ *		 := sign(x)*(log(x)+ln2)) for large |x|, else
+ *		 := sign(x)*log(2|x|+1/(|x|+sqrt(x*x+1))) if|x|>2, else
+ *		 := sign(x)*log1p(|x| + x^2/(1 + sqrt(1+x^2)))  
+ */
+
+double
+_Py_asinh(double x)
+{	
+	double w;
+	double absx = fabs(x);
+
+	if (Py_IS_NAN(x) || Py_IS_INFINITY(x)) {
+		return x+x;
+	}
+	if (absx < two_pow_m28) {	/* |x| < 2**-28 */
+		return x;	/* return x inexact except 0 */
+	} 
+	if (absx > two_pow_p28) {	/* |x| > 2**28 */
+		w = log(absx)+ln2;
+	}
+	else if (absx > 2.0) {		/* 2 < |x| < 2**28 */
+		w = log(2.0*absx + 1.0 / (sqrt(x*x + 1.0) + absx));
+	}
+	else {				/* 2**-28 <= |x| < 2= */
+		double t = x*x;
+		w = log1p(absx + t / (1.0 + sqrt(1.0 + t)));
+	}
+	return copysign(w, x);
+	
+}
+
+/* atanh(x)
+ * Method :
+ *    1.Reduced x to positive by atanh(-x) = -atanh(x)
+ *    2.For x>=0.5
+ *		  1	      2x			  x
+ *      atanh(x) = --- * log(1 + -------) = 0.5 * log1p(2 * --------)
+ *		  2	     1 - x		      1 - x
+ *
+ *      For x<0.5
+ *      atanh(x) = 0.5*log1p(2x+2x*x/(1-x))
+ *
+ * Special cases:
+ *      atanh(x) is NaN if |x| >= 1 with signal;
+ *      atanh(NaN) is that NaN with no signal;
+ *
+ */
+
+double
+_Py_atanh(double x)
+{
+	double absx;
+	double t;
+
+	if (Py_IS_NAN(x)) {
+		return x+x;
+	}
+	absx = fabs(x);
+	if (absx >= 1.) {		/* |x| >= 1 */
+		errno = EDOM;
+#ifdef Py_NAN
+		return Py_NAN;
+#else
+		return x/zero;
+#endif
+	}
+	if (absx < two_pow_m28) {	/* |x| < 2**-28 */
+		return x;
+	}
+	if (absx < 0.5) {		/* |x| < 0.5 */
+		t = absx+absx;
+		t = 0.5 * log1p(t + t*absx / (1.0 - absx));
+	} 
+	else {				/* 0.5 <= |x| <= 1.0 */
+		t = 0.5 * log1p((absx + absx) / (1.0 - absx));
+	}
+	return copysign(t, x);
+}
 
 /* Mathematically, expm1(x) = exp(x) - 1.  The expm1 function is designed
    to avoid the significant loss of precision that arises from direct
@@ -29,3 +182,47 @@
     else
         return exp(x) - 1.0;
 }
+
+/* log1p(x) = log(1+x).  The log1p function is designed to avoid the
+   significant loss of precision that arises from direct evaluation when x is
+   small. */
+
+double
+_Py_log1p(double x)
+{
+    /* For x small, we use the following approach.  Let y be the nearest float
+       to 1+x, then
+
+          1+x = y * (1 - (y-1-x)/y)
+
+       so log(1+x) = log(y) + log(1-(y-1-x)/y).  Since (y-1-x)/y is tiny, the
+       second term is well approximated by (y-1-x)/y.  If abs(x) >=
+       DBL_EPSILON/2 or the rounding-mode is some form of round-to-nearest
+       then y-1-x will be exactly representable, and is computed exactly by
+       (y-1)-x.
+
+       If abs(x) < DBL_EPSILON/2 and the rounding mode is not known to be
+       round-to-nearest then this method is slightly dangerous: 1+x could be
+       rounded up to 1+DBL_EPSILON instead of down to 1, and in that case
+       y-1-x will not be exactly representable any more and the result can be
+       off by many ulps.  But this is easily fixed: for a floating-point
+       number |x| < DBL_EPSILON/2., the closest floating-point number to
+       log(1+x) is exactly x.
+    */
+
+    double y;
+    if (fabs(x) < DBL_EPSILON/2.) {
+        return x;
+    } else if (-0.5 <= x && x <= 1.) {
+        /* WARNING: it's possible than an overeager compiler
+           will incorrectly optimize the following two lines
+           to the equivalent of "return log(1.+x)". If this
+           happens, then results from log1p will be inaccurate
+           for small x. */
+        y = 1.+x;
+        return log(y)-((y-1.)-x)/y;
+    } else {
+        /* NaNs and infinities should end up here */
+        return log(1.+x);
+    }
+}
diff --git a/Modules/_math.h b/Modules/_math.h
index 69c96b5..c0ceece 100644
--- a/Modules/_math.h
+++ b/Modules/_math.h
@@ -1,4 +1,32 @@
+double _Py_acosh(double x);
+double _Py_asinh(double x);
+double _Py_atanh(double x);
 double _Py_expm1(double x);
+double _Py_log1p(double x);
+
+#ifdef HAVE_ACOSH
+#define m_acosh acosh
+#else
+/* if the system doesn't have acosh, use the substitute
+   function defined in Modules/_math.c. */
+#define m_acosh _Py_acosh
+#endif
+
+#ifdef HAVE_ASINH
+#define m_asinh asinh
+#else
+/* if the system doesn't have asinh, use the substitute
+   function defined in Modules/_math.c. */
+#define m_asinh _Py_asinh
+#endif
+
+#ifdef HAVE_ATANH
+#define m_atanh atanh
+#else
+/* if the system doesn't have atanh, use the substitute
+   function defined in Modules/_math.c. */
+#define m_atanh _Py_atanh
+#endif
 
 #ifdef HAVE_EXPM1
 #define m_expm1 expm1
@@ -7,3 +35,11 @@
    function defined in Modules/_math.c. */
 #define m_expm1 _Py_expm1
 #endif
+
+#ifdef HAVE_LOG1P
+#define m_log1p log1p
+#else
+/* if the system doesn't have log1p, use the substitute
+   function defined in Modules/_math.c. */
+#define m_log1p _Py_log1p
+#endif
diff --git a/Modules/cmathmodule.c b/Modules/cmathmodule.c
index fbf6ece..4d13e58 100644
--- a/Modules/cmathmodule.c
+++ b/Modules/cmathmodule.c
@@ -3,6 +3,7 @@
 /* much code borrowed from mathmodule.c */
 
 #include "Python.h"
+#include "_math.h"
 /* we need DBL_MAX, DBL_MIN, DBL_EPSILON, DBL_MANT_DIG and FLT_RADIX from
    float.h.  We assume that FLT_RADIX is either 2 or 16. */
 #include <float.h>
@@ -149,7 +150,7 @@
 		s2.imag = z.imag;
 		s2 = c_sqrt(s2);
 		r.real = 2.*atan2(s1.real, s2.real);
-		r.imag = asinh(s2.real*s1.imag - s2.imag*s1.real);
+		r.imag = m_asinh(s2.real*s1.imag - s2.imag*s1.real);
 	}
 	errno = 0;
 	return r;
@@ -181,7 +182,7 @@
 		s2.real = z.real + 1.;
 		s2.imag = z.imag;
 		s2 = c_sqrt(s2);
-		r.real = asinh(s1.real*s2.real + s1.imag*s2.imag);
+		r.real = m_asinh(s1.real*s2.real + s1.imag*s2.imag);
 		r.imag = 2.*atan2(s1.imag, s2.real);
 	}
 	errno = 0;
@@ -238,7 +239,7 @@
 		s2.real = 1.-z.imag;
 		s2.imag = z.real;
 		s2 = c_sqrt(s2);
-		r.real = asinh(s1.real*s2.imag-s2.real*s1.imag);
+		r.real = m_asinh(s1.real*s2.imag-s2.real*s1.imag);
 		r.imag = atan2(z.imag, s1.real*s2.real-s1.imag*s2.imag);
 	}
 	errno = 0;
@@ -342,7 +343,7 @@
 			errno = 0;
 		}
 	} else {
-		r.real = log1p(4.*z.real/((1-z.real)*(1-z.real) + ay*ay))/4.;
+		r.real = m_log1p(4.*z.real/((1-z.real)*(1-z.real) + ay*ay))/4.;
 		r.imag = -atan2(-2.*z.imag, (1-z.real)*(1+z.real) - ay*ay)/2.;
 		errno = 0;
 	}
@@ -552,7 +553,7 @@
 		if (0.71 <= h && h <= 1.73) {
 			am = ax > ay ? ax : ay;  /* max(ax, ay) */
 			an = ax > ay ? ay : ax;  /* min(ax, ay) */
-			r.real = log1p((am-1)*(am+1)+an*an)/2.;
+			r.real = m_log1p((am-1)*(am+1)+an*an)/2.;
 		} else {
 			r.real = log(h);
 		}
diff --git a/Modules/mathmodule.c b/Modules/mathmodule.c
index 92f5f42..a057cac 100644
--- a/Modules/mathmodule.c
+++ b/Modules/mathmodule.c
@@ -816,18 +816,18 @@
 
 FUNC1(acos, acos, 0,
       "acos(x)\n\nReturn the arc cosine (measured in radians) of x.")
-FUNC1(acosh, acosh, 0,
+FUNC1(acosh, m_acosh, 0,
       "acosh(x)\n\nReturn the hyperbolic arc cosine (measured in radians) of x.")
 FUNC1(asin, asin, 0,
       "asin(x)\n\nReturn the arc sine (measured in radians) of x.")
-FUNC1(asinh, asinh, 0,
+FUNC1(asinh, m_asinh, 0,
       "asinh(x)\n\nReturn the hyperbolic arc sine (measured in radians) of x.")
 FUNC1(atan, atan, 0,
       "atan(x)\n\nReturn the arc tangent (measured in radians) of x.")
 FUNC2(atan2, m_atan2,
       "atan2(y, x)\n\nReturn the arc tangent (measured in radians) of y/x.\n"
       "Unlike atan(y/x), the signs of both x and y are considered.")
-FUNC1(atanh, atanh, 0,
+FUNC1(atanh, m_atanh, 0,
       "atanh(x)\n\nReturn the hyperbolic arc tangent (measured in radians) of x.")
 
 static PyObject * math_ceil(PyObject *self, PyObject *number) {
@@ -895,7 +895,7 @@
       "gamma(x)\n\nGamma function at x.")
 FUNC1A(lgamma, m_lgamma,
       "lgamma(x)\n\nNatural logarithm of absolute value of Gamma function at x.")
-FUNC1(log1p, log1p, 1,
+FUNC1(log1p, m_log1p, 1,
       "log1p(x)\n\nReturn the natural logarithm of 1+x (base e).\n"
       "The result is computed in a way which is accurate for x near zero.")
 FUNC1(sin, sin, 0,
diff --git a/Python/pymath.c b/Python/pymath.c
index db2920c..83105f2 100644
--- a/Python/pymath.c
+++ b/Python/pymath.c
@@ -77,202 +77,3 @@
     return copysign(y, x);
 }
 #endif /* HAVE_ROUND */
-
-#ifndef HAVE_LOG1P
-#include <float.h>
-
-double
-log1p(double x)
-{
-	/* For x small, we use the following approach.  Let y be the nearest
-	   float to 1+x, then
-
-	     1+x = y * (1 - (y-1-x)/y)
-
-	   so log(1+x) = log(y) + log(1-(y-1-x)/y).  Since (y-1-x)/y is tiny,
-	   the second term is well approximated by (y-1-x)/y.  If abs(x) >=
-	   DBL_EPSILON/2 or the rounding-mode is some form of round-to-nearest
-	   then y-1-x will be exactly representable, and is computed exactly
-	   by (y-1)-x.
-
-	   If abs(x) < DBL_EPSILON/2 and the rounding mode is not known to be
-	   round-to-nearest then this method is slightly dangerous: 1+x could
-	   be rounded up to 1+DBL_EPSILON instead of down to 1, and in that
-	   case y-1-x will not be exactly representable any more and the
-	   result can be off by many ulps.  But this is easily fixed: for a
-	   floating-point number |x| < DBL_EPSILON/2., the closest
-	   floating-point number to log(1+x) is exactly x.
-	*/
-
-	double y;
-	if (fabs(x) < DBL_EPSILON/2.) {
-		return x;
-	} else if (-0.5 <= x && x <= 1.) {
-		/* WARNING: it's possible than an overeager compiler
-		   will incorrectly optimize the following two lines
-		   to the equivalent of "return log(1.+x)". If this
-		   happens, then results from log1p will be inaccurate
-		   for small x. */
-		y = 1.+x;
-		return log(y)-((y-1.)-x)/y;
-	} else {
-		/* NaNs and infinities should end up here */
-		return log(1.+x);
-	}
-}
-#endif /* HAVE_LOG1P */
-
-/*
- * ====================================================
- * Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
- *
- * Developed at SunPro, a Sun Microsystems, Inc. business.
- * Permission to use, copy, modify, and distribute this
- * software is freely granted, provided that this notice 
- * is preserved.
- * ====================================================
- */
-
-static const double ln2 = 6.93147180559945286227E-01;
-static const double two_pow_m28 = 3.7252902984619141E-09; /* 2**-28 */
-static const double two_pow_p28 = 268435456.0; /* 2**28 */
-static const double zero = 0.0;
-
-/* asinh(x)
- * Method :
- *	Based on 
- *		asinh(x) = sign(x) * log [ |x| + sqrt(x*x+1) ]
- *	we have
- *	asinh(x) := x  if  1+x*x=1,
- *		 := sign(x)*(log(x)+ln2)) for large |x|, else
- *		 := sign(x)*log(2|x|+1/(|x|+sqrt(x*x+1))) if|x|>2, else
- *		 := sign(x)*log1p(|x| + x^2/(1 + sqrt(1+x^2)))  
- */
-
-#ifndef HAVE_ASINH
-double
-asinh(double x)
-{	
-	double w;
-	double absx = fabs(x);
-
-	if (Py_IS_NAN(x) || Py_IS_INFINITY(x)) {
-		return x+x;
-	}
-	if (absx < two_pow_m28) {	/* |x| < 2**-28 */
-		return x;	/* return x inexact except 0 */
-	} 
-	if (absx > two_pow_p28) {	/* |x| > 2**28 */
-		w = log(absx)+ln2;
-	}
-	else if (absx > 2.0) {		/* 2 < |x| < 2**28 */
-		w = log(2.0*absx + 1.0 / (sqrt(x*x + 1.0) + absx));
-	}
-	else {				/* 2**-28 <= |x| < 2= */
-		double t = x*x;
-		w = log1p(absx + t / (1.0 + sqrt(1.0 + t)));
-	}
-	return copysign(w, x);
-	
-}
-#endif /* HAVE_ASINH */
-
-/* acosh(x)
- * Method :
- *      Based on
- *	      acosh(x) = log [ x + sqrt(x*x-1) ]
- *      we have
- *	      acosh(x) := log(x)+ln2, if x is large; else
- *	      acosh(x) := log(2x-1/(sqrt(x*x-1)+x)) if x>2; else
- *	      acosh(x) := log1p(t+sqrt(2.0*t+t*t)); where t=x-1.
- *
- * Special cases:
- *      acosh(x) is NaN with signal if x<1.
- *      acosh(NaN) is NaN without signal.
- */
-
-#ifndef HAVE_ACOSH
-double
-acosh(double x)
-{
-	if (Py_IS_NAN(x)) {
-		return x+x;
-	}
-	if (x < 1.) {			/* x < 1;  return a signaling NaN */
-		errno = EDOM;
-#ifdef Py_NAN
-		return Py_NAN;
-#else
-		return (x-x)/(x-x);
-#endif
-	}
-	else if (x >= two_pow_p28) {	/* x > 2**28 */
-		if (Py_IS_INFINITY(x)) {
-			return x+x;
-		} else {
-			return log(x)+ln2;	/* acosh(huge)=log(2x) */
-		}
-	}
-	else if (x == 1.) {
-		return 0.0;			/* acosh(1) = 0 */
-	}
-	else if (x > 2.) {			/* 2 < x < 2**28 */
-		double t = x*x;
-		return log(2.0*x - 1.0 / (x + sqrt(t - 1.0)));
-	}
-	else {				/* 1 < x <= 2 */
-		double t = x - 1.0;
-		return log1p(t + sqrt(2.0*t + t*t));
-	}
-}
-#endif /* HAVE_ACOSH */
-
-/* atanh(x)
- * Method :
- *    1.Reduced x to positive by atanh(-x) = -atanh(x)
- *    2.For x>=0.5
- *		  1	      2x			  x
- *      atanh(x) = --- * log(1 + -------) = 0.5 * log1p(2 * --------)
- *		  2	     1 - x		      1 - x
- *
- *      For x<0.5
- *      atanh(x) = 0.5*log1p(2x+2x*x/(1-x))
- *
- * Special cases:
- *      atanh(x) is NaN if |x| >= 1 with signal;
- *      atanh(NaN) is that NaN with no signal;
- *
- */
-
-#ifndef HAVE_ATANH
-double
-atanh(double x)
-{
-	double absx;
-	double t;
-
-	if (Py_IS_NAN(x)) {
-		return x+x;
-	}
-	absx = fabs(x);
-	if (absx >= 1.) {		/* |x| >= 1 */
-		errno = EDOM;
-#ifdef Py_NAN
-		return Py_NAN;
-#else
-		return x/zero;
-#endif
-	}
-	if (absx < two_pow_m28) {	/* |x| < 2**-28 */
-		return x;
-	}
-	if (absx < 0.5) {		/* |x| < 0.5 */
-		t = absx+absx;
-		t = 0.5 * log1p(t + t*absx / (1.0 - absx));
-	} 
-	else {				/* 0.5 <= |x| <= 1.0 */
-		t = 0.5 * log1p((absx + absx) / (1.0 - absx));
-	}
-	return copysign(t, x);
-}
-#endif /* HAVE_ATANH */
diff --git a/setup.py b/setup.py
index c2c0af1..9ea4e67 100644
--- a/setup.py
+++ b/setup.py
@@ -394,9 +394,9 @@
         # array objects
         exts.append( Extension('array', ['arraymodule.c']) )
         # complex math library functions
-        exts.append( Extension('cmath', ['cmathmodule.c'],
+        exts.append( Extension('cmath', ['cmathmodule.c', '_math.c'],
+                               depends=['_math.h'],
                                libraries=math_libs) )
-
         # math library functions, e.g. sin()
         exts.append( Extension('math',  ['mathmodule.c', '_math.c'],
                                depends=['_math.h'],