Index: doc/genapi.py
===================================================================
--- doc/genapi.py	(revision 2e66ef55022b7fe939fdb5874c2c919d97e01b2c)
+++ doc/genapi.py	(revision 706f46620c115bdbc319d902ba7678c9d247d6d0)
@@ -59,6 +59,7 @@
     #('alignment', 'GPU data alignment [unused]'),
     ('bumps_model', 'Bumps interface'),
+    ('compare', 'Compare models on different compute engines'),
     ('compare_many', 'Batch compare models on different compute engines'),
-    ('compare', 'Compare models on different compute engines'),
+    ('conversion_table', 'Model conversion table'),
     ('convert', 'Sasview to sasmodel converter'),
     ('core', 'Model access'),
@@ -82,4 +83,5 @@
     ('sasview_model', 'Sasview interface'),
     ('sesans', 'SESANS calculation routines'),
+    ('special', 'Special functions library'),
     ('weights', 'Distribution functions'),
 ]
Index: sasmodels/special.py
===================================================================
--- sasmodels/special.py	(revision 4f611f17b9c0d3789af36365fc5205fbbfb56447)
+++ sasmodels/special.py	(revision 706f46620c115bdbc319d902ba7678c9d247d6d0)
@@ -1,3 +1,3 @@
-"""
+r"""
 Special Functions
 .................
@@ -10,12 +10,16 @@
     M_PI, M_PI_2, M_PI_4, M_SQRT1_2, M_E:
         $\pi$, $\pi/2$, $\pi/4$, $1/\sqrt{2}$ and Euler's constant $e$
+
     exp, log, pow(x,y), expm1, sqrt:
         Power functions $e^x$, $\ln x$, $x^y$, $e^x - 1$, $\sqrt{x}$.
         The function expm1(x) is accurate across all $x$, including $x$
         very close to zero.
+
     sin, cos, tan, asin, acos, atan:
         Trigonometry functions and inverses, operating on radians.
+
     sinh, cosh, tanh, asinh, acosh, atanh:
         Hyperbolic trigonometry functions.
+
     atan2(y,x):
         Angle from the $x$\ -axis to the point $(x,y)$, which is equal to
@@ -24,13 +28,17 @@
         atan(y/x) would return a value in quadrant I. Similarly for
         quadrants II and IV when $x$ and $y$ have opposite sign.
+
     fmin(x,y), fmax(x,y), trunc, rint:
         Floating point functions.  rint(x) returns the nearest integer.
+
     NAN:
         NaN, Not a Number, $0/0$.  Use isnan(x) to test for NaN.  Note that
         you cannot use :code:`x == NAN` to test for NaN values since that
         will always return false.  NAN does not equal NAN!
+
     INFINITY:
         $\infty, 1/0$.  Use isinf(x) to test for infinity, or isfinite(x)
         to test for finite and not NaN.
+
     erf, erfc, tgamma, lgamma:  **do not use**
         Special functions that should be part of the standard, but are missing
@@ -42,17 +50,24 @@
     M_PI_180, M_4PI_3:
         $\frac{\pi}{180}$, $\frac{4\pi}{3}$
+
     SINCOS(x, s, c):
         Macro which sets s=sin(x) and c=cos(x). The variables *c* and *s*
         must be declared first.
+
     square(x):
         $x^2$
+
     cube(x):
         $x^3$
+
     sas_sinx_x(x):
         $\sin(x)/x$, with limit $\sin(0)/0 = 1$.
+
     powr(x, y):
         $x^y$ for $x \ge 0$; this is faster than general $x^y$ on some GPUs.
+
     pown(x, n):
         $x^n$ for $n$ integer; this is faster than general $x^n$ on some GPUs.
+
     FLOAT_SIZE:
         The number of bytes in a floating point value.  Even though all
@@ -67,4 +82,5 @@
             ... code for single precision ...
             #endif
+
     SAS_DOUBLE:
         A replacement for :code:`double` so that the declared variable will
@@ -88,6 +104,4 @@
         sorted from highest to lowest.
 
-        :code:`source = ["lib/polevl.c", ...]` (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/polevl.c>`_)
-
     p1evl(x, c, n):
         Evaluation of normalized polynomial $p(x) = x^n + \sum_{i=0}^{n-1} c_i x^i$
@@ -97,7 +111,4 @@
         sorted from highest to lowest.
 
-        :code:`source = ["lib/polevl.c", ...]`
-        (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/polevl.c>`_)
-
     sas_gamma(x):
         Gamma function $\text{sas_gamma}(x) = \Gamma(x)$.
@@ -105,7 +116,4 @@
         The standard math function, tgamma(x) is unstable for $x < 1$
         on some platforms.
-
-        :code:`source = ["lib/sasgamma.c", ...]`
-        (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_gamma.c>`_)
 
     sas_erf(x), sas_erfc(x):
@@ -118,7 +126,4 @@
         on some platforms.
 
-        :code:`source = ["lib/polevl.c", "lib/sas_erf.c", ...]`
-        (`link to error functions' code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_erf.c>`_)
-
     sas_J0(x):
         Bessel function of the first kind $\text{sas_J0}(x)=J_0(x)$ where
@@ -127,7 +132,4 @@
         The standard math function j0(x) is not available on all platforms.
 
-        :code:`source = ["lib/polevl.c", "lib/sas_J0.c", ...]`
-        (`link to Bessel function's code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_J0.c>`_)
-
     sas_J1(x):
         Bessel function of the first kind  $\text{sas_J1}(x)=J_1(x)$ where
@@ -135,7 +137,4 @@
 
         The standard math function j1(x) is not available on all platforms.
-
-        :code:`source = ["lib/polevl.c", "lib/sas_J1.c", ...]`
-        (`link to Bessel function's code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_J1.c>`_)
 
     sas_JN(n, x):
@@ -147,7 +146,4 @@
         The standard math function jn(n, x) is not available on all platforms.
 
-        :code:`source = ["lib/polevl.c", "lib/sas_J0.c", "lib/sas_J1.c", "lib/sas_JN.c", ...]`
-        (`link to Bessel function's code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_JN.c>`_)
-
     sas_Si(x):
         Sine integral $\text{Si}(x) = \int_0^x \tfrac{\sin t}{t}\,dt$.
@@ -170,7 +166,4 @@
            - \frac{x^3}{3\times 3!} + \frac{x^5}{5 \times 5!} - \frac{x^7}{7 \times 7!}
            + \frac{x^9}{9\times 9!} - \frac{x^{11}}{11\times 11!}
-
-        :code:`source = ["lib/Si.c", ...]`
-        (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/Si.c>`_)
 
     sas_3j1x_x(x):
@@ -182,7 +175,4 @@
         This function uses a Taylor series for small $x$ for numerical accuracy.
 
-        :code:`source = ["lib/sas_3j1x_x.c", ...]`
-        (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_3j1x_x.c>`_)
-
 
     sas_2J1x_x(x):
@@ -191,7 +181,4 @@
         and first order.
 
-        :code:`source = ["lib/polevl.c", "lib/sas_J1.c", ...]`
-        (`link to Bessel form's code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/sas_J1.c>`_)
-
 
     Gauss76Z[i], Gauss76Wt[i]:
@@ -201,8 +188,4 @@
         Similar arrays are available in :code:`gauss20.c` for 20-point
         quadrature and in :code:`gauss150.c` for 150-point quadrature.
-
-        :code:`source = ["lib/gauss76.c", ...]`
-        (`link to code <https://github.com/SasView/sasmodels/tree/master/sasmodels/models/lib/gauss76.c>`_)
-
 
 """
@@ -290,5 +273,5 @@
             retvalue = (sin(x) - x*cos(x))/x**2
         retvalue[x == 0.] = 0.
-        
+
 def sas_3j1x_x(x):
     if np.isscalar(x):
@@ -313,510 +296,510 @@
 
 Gauss20Wt = np.array([
-	.0176140071391521,
-	.0406014298003869,
-	.0626720483341091,
-	.0832767415767047,
-	.10193011981724,
-	.118194531961518,
-	.131688638449177,
-	.142096109318382,
-	.149172986472604,
-	.152753387130726,
-	.152753387130726,
-	.149172986472604,
-	.142096109318382,
-	.131688638449177,
-	.118194531961518,
-	.10193011981724,
-	.0832767415767047,
-	.0626720483341091,
-	.0406014298003869,
-	.0176140071391521
+    .0176140071391521,
+    .0406014298003869,
+    .0626720483341091,
+    .0832767415767047,
+    .10193011981724,
+    .118194531961518,
+    .131688638449177,
+    .142096109318382,
+    .149172986472604,
+    .152753387130726,
+    .152753387130726,
+    .149172986472604,
+    .142096109318382,
+    .131688638449177,
+    .118194531961518,
+    .10193011981724,
+    .0832767415767047,
+    .0626720483341091,
+    .0406014298003869,
+    .0176140071391521
 ])
 
 Gauss20Z = np.array([
-	-.993128599185095,
-	-.963971927277914,
-	-.912234428251326,
-	-.839116971822219,
-	-.746331906460151,
-	-.636053680726515,
-	-.510867001950827,
-	-.37370608871542,
-	-.227785851141645,
-	-.076526521133497,
-	.0765265211334973,
-	.227785851141645,
-	.37370608871542,
-	.510867001950827,
-	.636053680726515,
-	.746331906460151,
-	.839116971822219,
-	.912234428251326,
-	.963971927277914,
-	.993128599185095
+    -.993128599185095,
+    -.963971927277914,
+    -.912234428251326,
+    -.839116971822219,
+    -.746331906460151,
+    -.636053680726515,
+    -.510867001950827,
+    -.37370608871542,
+    -.227785851141645,
+    -.076526521133497,
+    .0765265211334973,
+    .227785851141645,
+    .37370608871542,
+    .510867001950827,
+    .636053680726515,
+    .746331906460151,
+    .839116971822219,
+    .912234428251326,
+    .963971927277914,
+    .993128599185095
 ])
 
 Gauss76Wt = np.array([
-	.00126779163408536,		#0
-	.00294910295364247,
-	.00462793522803742,
-	.00629918049732845,
-	.00795984747723973,
-	.00960710541471375,
-	.0112381685696677,
-	.0128502838475101,
-	.0144407317482767,
-	.0160068299122486,
-	.0175459372914742,		#10
-	.0190554584671906,
-	.020532847967908,
-	.0219756145344162,
-	.0233813253070112,
-	.0247476099206597,
-	.026072164497986,
-	.0273527555318275,
-	.028587223650054,
-	.029773487255905,
-	.0309095460374916,		#20
-	.0319934843404216,
-	.0330234743977917,
-	.0339977794120564,
-	.0349147564835508,
-	.0357728593807139,
-	.0365706411473296,
-	.0373067565423816,
-	.0379799643084053,
-	.0385891292645067,
-	.0391332242205184,		#30
-	.0396113317090621,
-	.0400226455325968,
-	.040366472122844,
-	.0406422317102947,
-	.0408494593018285,
-	.040987805464794,
-	.0410570369162294,
-	.0410570369162294,
-	.040987805464794,
-	.0408494593018285,		#40
-	.0406422317102947,
-	.040366472122844,
-	.0400226455325968,
-	.0396113317090621,
-	.0391332242205184,
-	.0385891292645067,
-	.0379799643084053,
-	.0373067565423816,
-	.0365706411473296,
-	.0357728593807139,		#50
-	.0349147564835508,
-	.0339977794120564,
-	.0330234743977917,
-	.0319934843404216,
-	.0309095460374916,
-	.029773487255905,
-	.028587223650054,
-	.0273527555318275,
-	.026072164497986,
-	.0247476099206597,		#60
-	.0233813253070112,
-	.0219756145344162,
-	.020532847967908,
-	.0190554584671906,
-	.0175459372914742,
-	.0160068299122486,
-	.0144407317482767,
-	.0128502838475101,
-	.0112381685696677,
-	.00960710541471375,		#70
-	.00795984747723973,
-	.00629918049732845,
-	.00462793522803742,
-	.00294910295364247,
-	.00126779163408536		#75 (indexed from 0)
+    .00126779163408536,		#0
+    .00294910295364247,
+    .00462793522803742,
+    .00629918049732845,
+    .00795984747723973,
+    .00960710541471375,
+    .0112381685696677,
+    .0128502838475101,
+    .0144407317482767,
+    .0160068299122486,
+    .0175459372914742,		#10
+    .0190554584671906,
+    .020532847967908,
+    .0219756145344162,
+    .0233813253070112,
+    .0247476099206597,
+    .026072164497986,
+    .0273527555318275,
+    .028587223650054,
+    .029773487255905,
+    .0309095460374916,		#20
+    .0319934843404216,
+    .0330234743977917,
+    .0339977794120564,
+    .0349147564835508,
+    .0357728593807139,
+    .0365706411473296,
+    .0373067565423816,
+    .0379799643084053,
+    .0385891292645067,
+    .0391332242205184,		#30
+    .0396113317090621,
+    .0400226455325968,
+    .040366472122844,
+    .0406422317102947,
+    .0408494593018285,
+    .040987805464794,
+    .0410570369162294,
+    .0410570369162294,
+    .040987805464794,
+    .0408494593018285,		#40
+    .0406422317102947,
+    .040366472122844,
+    .0400226455325968,
+    .0396113317090621,
+    .0391332242205184,
+    .0385891292645067,
+    .0379799643084053,
+    .0373067565423816,
+    .0365706411473296,
+    .0357728593807139,		#50
+    .0349147564835508,
+    .0339977794120564,
+    .0330234743977917,
+    .0319934843404216,
+    .0309095460374916,
+    .029773487255905,
+    .028587223650054,
+    .0273527555318275,
+    .026072164497986,
+    .0247476099206597,		#60
+    .0233813253070112,
+    .0219756145344162,
+    .020532847967908,
+    .0190554584671906,
+    .0175459372914742,
+    .0160068299122486,
+    .0144407317482767,
+    .0128502838475101,
+    .0112381685696677,
+    .00960710541471375,		#70
+    .00795984747723973,
+    .00629918049732845,
+    .00462793522803742,
+    .00294910295364247,
+    .00126779163408536		#75 (indexed from 0)
 ])
 
 Gauss76Z = np.array([
-	-.999505948362153,		#0
-	-.997397786355355,
-	-.993608772723527,
-	-.988144453359837,
-	-.981013938975656,
-	-.972229228520377,
-	-.961805126758768,
-	-.949759207710896,
-	-.936111781934811,
-	-.92088586125215,
-	-.904107119545567,		#10
-	-.885803849292083,
-	-.866006913771982,
-	-.844749694983342,
-	-.822068037328975,
-	-.7980001871612,
-	-.77258672828181,
-	-.74587051350361,
-	-.717896592387704,
-	-.688712135277641,
-	-.658366353758143,		#20
-	-.626910417672267,
-	-.594397368836793,
-	-.560882031601237,
-	-.526420920401243,
-	-.491072144462194,
-	-.454895309813726,
-	-.417951418780327,
-	-.380302767117504,
-	-.342012838966962,
-	-.303146199807908,		#30
-	-.263768387584994,
-	-.223945802196474,
-	-.183745593528914,
-	-.143235548227268,
-	-.102483975391227,
-	-.0615595913906112,
-	-.0205314039939986,
-	.0205314039939986,
-	.0615595913906112,
-	.102483975391227,			#40
-	.143235548227268,
-	.183745593528914,
-	.223945802196474,
-	.263768387584994,
-	.303146199807908,
-	.342012838966962,
-	.380302767117504,
-	.417951418780327,
-	.454895309813726,
-	.491072144462194,		#50
-	.526420920401243,
-	.560882031601237,
-	.594397368836793,
-	.626910417672267,
-	.658366353758143,
-	.688712135277641,
-	.717896592387704,
-	.74587051350361,
-	.77258672828181,
-	.7980001871612,	#60
-	.822068037328975,
-	.844749694983342,
-	.866006913771982,
-	.885803849292083,
-	.904107119545567,
-	.92088586125215,
-	.936111781934811,
-	.949759207710896,
-	.961805126758768,
-	.972229228520377,		#70
-	.981013938975656,
-	.988144453359837,
-	.993608772723527,
-	.997397786355355,
-	.999505948362153		#75
+    -.999505948362153,		#0
+    -.997397786355355,
+    -.993608772723527,
+    -.988144453359837,
+    -.981013938975656,
+    -.972229228520377,
+    -.961805126758768,
+    -.949759207710896,
+    -.936111781934811,
+    -.92088586125215,
+    -.904107119545567,		#10
+    -.885803849292083,
+    -.866006913771982,
+    -.844749694983342,
+    -.822068037328975,
+    -.7980001871612,
+    -.77258672828181,
+    -.74587051350361,
+    -.717896592387704,
+    -.688712135277641,
+    -.658366353758143,		#20
+    -.626910417672267,
+    -.594397368836793,
+    -.560882031601237,
+    -.526420920401243,
+    -.491072144462194,
+    -.454895309813726,
+    -.417951418780327,
+    -.380302767117504,
+    -.342012838966962,
+    -.303146199807908,		#30
+    -.263768387584994,
+    -.223945802196474,
+    -.183745593528914,
+    -.143235548227268,
+    -.102483975391227,
+    -.0615595913906112,
+    -.0205314039939986,
+    .0205314039939986,
+    .0615595913906112,
+    .102483975391227,			#40
+    .143235548227268,
+    .183745593528914,
+    .223945802196474,
+    .263768387584994,
+    .303146199807908,
+    .342012838966962,
+    .380302767117504,
+    .417951418780327,
+    .454895309813726,
+    .491072144462194,		#50
+    .526420920401243,
+    .560882031601237,
+    .594397368836793,
+    .626910417672267,
+    .658366353758143,
+    .688712135277641,
+    .717896592387704,
+    .74587051350361,
+    .77258672828181,
+    .7980001871612,	#60
+    .822068037328975,
+    .844749694983342,
+    .866006913771982,
+    .885803849292083,
+    .904107119545567,
+    .92088586125215,
+    .936111781934811,
+    .949759207710896,
+    .961805126758768,
+    .972229228520377,		#70
+    .981013938975656,
+    .988144453359837,
+    .993608772723527,
+    .997397786355355,
+    .999505948362153		#75
 ])
 
 Gauss150Z = np.array([
-  	-0.9998723404457334,
-  	-0.9993274305065947,
-  	-0.9983473449340834,
-  	-0.9969322929775997,
-  	-0.9950828645255290,
-  	-0.9927998590434373,
-  	-0.9900842691660192,
-  	-0.9869372772712794,
-  	-0.9833602541697529,
-  	-0.9793547582425894,
-  	-0.9749225346595943,
-  	-0.9700655145738374,
-  	-0.9647858142586956,
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