tweak two Yukawa docs

sasmodels/models/TY_YukawaSq.c

@@ -29,7 +29,6 @@ void translate(
  }
 
  TY_SolveEquations(*z1, *z2, *k1, *k2, *volumefraction, a, b, c1, c2, d1, d2, debug );
-
  int checkFlag = TY_CheckSolution( *z1, *z2, *k1, *k2, *volumefraction, *a, *b, *c1, *c2, *d1, *d2 );
  if (!checkFlag) {
  *a = NAN;
@@ -67,7 +66,7 @@ double Iq(
  )
 {
  if (isnan(a)) {
- return a;
+ return NAN;
  } else {
  return SqTwoYukawa( qexp * 2 * radius, z1, z2, k1, k2, volumefraction, a, b, c1, c2, d1, d2 );
  }

sasmodels/models/TY_YukawaSq.py

@@ -1,12 +1,11 @@
 r"""
-
-This model calculates the interparticle structure factor for a colloidal system with
-an interaction potential consisting of two Yukawa terms. If one Yukawa term 
-is chosen to be an attractive potential and another one to be a repulsive potential,
-the two Yukawa potential can simulate a potential with both a short-range
-attraction and long-range repulsion (SALR). [1,2]. When combined with an
-appropriate form factor $P(q)$, this allows for inclusion of the
-interparticle interference effects due to a relative complex potential.
+This model calculates the interparticle structure factor for a colloidal system
+with an interaction potential consisting of two Yukawa terms. If one Yukawa term
+is chosen to be an attractive potential and the other a repulsive potential, the
+two Yukawa potential can simulate a potential with both a short-range attraction
+and long-range repulsion (SALR).[1,2] When combined with an appropriate form
+factor $P(q)$, this allows for inclusion of the interparticle interference
+effects due to a relatively complex potential.
 
 The interaction potential $V(r)$ is
 
@@ -17,45 +16,48 @@
  K_1 \frac{e^{-Z_1(r-2R)}}{r} + K_2 \frac{e^{-Z_2(r-2R)}}{r} & r \geq 2R
  \end{cases}
 
-And $R$ is the radius_effective.
+where $R$ is radius_effective.
 $K_1$ ( or $K_2$ ) is positive when there is a repulsion.
 $K_1$ ( or $K_2$ ) is negative when there is an attraction.
 
 .. note::
 
- This routine only works for a potential with two Yukawa terms. 
- If the amplitude, $K_1$ or $K_2$ of either Yukawa potential
- becomes zero, the routine may self-destruct! But one can make either
- amplitude very small if there is a need to make one amplitude to be zero.
- Also, $Z_1$ and $Z_2$ should be different. If these two numbers are identical,
- it essentially becomes a potential with one Yukawa term. 
- But these two values can be very close to each other.
- Therefore, the initial parameters of $Z_1$ and $Z_2$ should be different. 
+ This routine only works for a potential with two Yukawa terms. If the
+ amplitude, $K_1$ or $K_2$, of either Yukawa potential becomes zero, the
+ routine may self-destruct! But one can make either amplitude very small if
+ there is a need to make one amplitude to be zero. Also, $Z_1$ and $Z_2$
+ should be different. If these two numbers are identical, it essentially
+ becomes a potential with one Yukawa term. But these two values can be very
+ close to each other. Therefore, the initial parameters of $Z_1$ and $Z_2$
+ should be different.
 
 .. note::
 
- Earlier versions of SasView did not incorporate the so-called
- $\beta(q)$ ("beta") correction [3] for polydispersity and non-sphericity.
- This is only available in SasView versions 5.0 and higher.
+ Earlier versions of SasView did not incorporate the so-called $\beta(q)$
+ ("beta") correction [3] for polydispersity and non-sphericity. This is only
+ available in SasView versions 5.0 and higher.
 
-This code calculates the structure factor, $S(q)$, of one component liquid systems interacting 
-with a two-term Yukawa potential with the mean spherical approximation (MSA). 
-The structure factor is generated by following Blum's method,[4] 
-in which the structure factor is solved using the Ornstein-Zernike equation by Baxter's Q-method with the MSA closure.
+This code calculates the structure factor, $S(q)$, of one component liquid
+systems interacting with a two-term Yukawa potential with the mean spherical
+approximation (MSA). The structure factor is generated by following Blum's
+method,[4] in which the structure factor is solved using the Ornstein-Zernike
+equation by Baxter's Q-method with the MSA closure.
 
-The algorithm used in this model was originally proposed and developled by Liu et al. in 2005 and implemented using MatLab.[1]
-The algorithm was later reimplemented using C and Igor.
-SasView used the C codes developed by M. Hennig in 2010. 
+The algorithm used in this model was originally proposed and developled by Liu
+et al. in 2005 and implemented using MatLab.[1] The algorithm was later
+reimplemented using C and Igor. SasView uses the C codes developed by M. Hennig
+in 2010.
 
-When the overall attraction is not very strong, this algorithm produces reasonably accurate results.[2]
-However, whent the net attraction is very strong. It has been shown that the fitting algorithm 
-tend to underestimate the attraction strength. 
-Accuracy of this algorithm was evaluated by Broccio et al..[2]
+When the overall attraction is not very strong, this algorithm produces
+reasonably accurate results.[2] However, when the net attraction is very strong,
+it has been shown that the fitting algorithm tends to underestimate the
+attraction strength. Accuracy of this algorithm was evaluated by Broccio, et
+al.[2]
 
-When using the OZ euqation to obtain the structure factor, it assumes that a system is in a liquid state.
-However, when the attraction potential is too strong, a physical system may not be in a liquid system any more.
-But the OZ equation may still have a solution. But the result may not be physically meaningful.
-When this happends, the solution of the OZ equation may return unphysical results or fail to return any result, 
+When using the O-Z equation to obtain the structure factor, it assumes that a
+system is in a liquid state. However, when the attraction potential is too
+strong the system may not be in a liquid state, and the O-Z equation may not
+have a solution, or the solution may be unphysical.
 
 References
 ----------
@@ -86,6 +88,8 @@
 single = False # make sure that it has double digit precision
 opencl = False # related with parallel computing
 
+valid = "k1 != 0 && k2 != 0 && z1 != z2"
+
 parameters = [ 
 # ["name", "units", default, [lower, upper], "type", "description"],
  ["radius_effective", "Ang", 50.0, [-inf, inf], '', ''],