Made beadModelTwist omit beadModel-style crossover bonds and angles

beadModelTwist.py

@@ -257,7 +257,7 @@ class beadModelTwist():
         # self._dihedralParamFiles = set()
 
         self.twistPersistenceLength = twistPersistenceLength
-
+        self.apply_extra_crossover_potentials = False
 
         self._buildModel(part, maxBpsPerDNode, maxNtsPerSNode)
         
@@ -1255,12 +1255,13 @@ component "data" value 3
                 self.addAngle( *args )
 
             self.addAngle( n1,n2,n3,Angle(k,180) )
-            
-        a,d = self._getCrossoverAnglesAndDihedrals()
-        for nodes,sep in a:
-            n1,n2,n3 = nodes
-            k = (1.0/2) * 1.5 * kT * (1.0 / (1-exp(-float(sep)/147))) * 0.00030461742; # kcal_mol/degree^2                
-            self.addAngle( n1,n2,n3,Angle(k,90) )
+
+        if self.apply_extra_crossover_potentials:
+            a,d = self._getCrossoverAnglesAndDihedrals()
+            for nodes,sep in a:
+                n1,n2,n3 = nodes
+                k = (1.0/2) * 1.5 * kT * (1.0 / (1-exp(-float(sep)/147))) * 0.00030461742; # kcal_mol/degree^2                
+                self.addAngle( n1,n2,n3,Angle(k,90) )
 
         ## Intrahelical 90 deg orientation angles
         for nodes,seps in self._getOrientationAngles():
@@ -1289,40 +1290,42 @@ component "data" value 3
 
     def _buildDihedrals(self, prefix, directory="potentials"):
         kT = 0.58622522         # kcal/mol
-        a,d = self._getCrossoverAnglesAndDihedrals()
-        for nodes,sep,isFwd1,isFwd2 in d:
-            n1,n2,n3,n4 = nodes
-            ## <cos(q)> = exp(-s/Lp) = integrate( cos[x] exp(-A x^2), {x, 0, pi} ) / integrate( exp(-A x^2), {x, 0, pi} )
-            ##   Assume A is small
-            ## int[B_] :=  Normal[Integrate[ Series[Cos[x] Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]/
-            ##             Integrate[Series[Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]]
-            ## Actually, without assumptions I get fitFun below
-
-            ## From http://www.annualreviews.org/doi/pdf/10.1146/annurev.bb.17.060188.001405
-            ##   units "3e-19 erg cm/ 295 k K" "nm" =~ 73
-            Lp = self.twistPersistenceLength/0.34  # set semi-arbitrarily as there is a large spread in literature
-
-            fitFun = lambda x: np.real(erf( (4*np.pi*x + 1j)/(2*np.sqrt(x)) )) * np.exp(-1/(4*x)) / erf(2*np.sqrt(x)*np.pi) - exp(-sep/Lp)
-            k = opt.leastsq( fitFun, x0=exp(-sep/Lp) )
-            k = k[0][0] * 2*kT*0.00030461742
-
-            # intrinsicDegrees=30
-            # fitFun = lambda x: (1.0/(2*x) - 2*np.sqrt(np.pi)*np.exp(-4*np.pi**2*x) / (np.sqrt(x)*erf(2*np.pi*np.sqrt(x))) ) - \
-            #          ( (intrinsicDegrees*np.pi/180)**2 + 2*(1-exp(-sep/Lp)) )
-            # k = opt.leastsq( fitFun, x0=1/(1-exp(-sep/Lp)) )
-            # k = k[0][0] * 2*kT*0.00030461742
-
-            t0 = sep*(360.0/10.5)
-
-            # pdb.set_trace()
-            if isFwd1[0]: t0 -= 120
-            if isFwd2[0]: t0 += 120
-
-            t0 = t0 % 360
 
-            # if n2.idx == 0:
-            #     print( n1.idx,n2.idx,n3.idx,n4.idx,k,t0,sep )
-            self.addDihedral( n1,n2,n3,n4,Dihedral(k,t0) )
+        if self.apply_extra_crossover_potentials:
+            a,d = self._getCrossoverAnglesAndDihedrals()
+            for nodes,sep,isFwd1,isFwd2 in d:
+                n1,n2,n3,n4 = nodes
+                ## <cos(q)> = exp(-s/Lp) = integrate( cos[x] exp(-A x^2), {x, 0, pi} ) / integrate( exp(-A x^2), {x, 0, pi} )
+                ##   Assume A is small
+                ## int[B_] :=  Normal[Integrate[ Series[Cos[x] Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]/
+                ##             Integrate[Series[Exp[-B x^2], {B, 0, 1}], {x, 0, \[Pi]}]]
+                ## Actually, without assumptions I get fitFun below
+
+                ## From http://www.annualreviews.org/doi/pdf/10.1146/annurev.bb.17.060188.001405
+                ##   units "3e-19 erg cm/ 295 k K" "nm" =~ 73
+                Lp = self.twistPersistenceLength/0.34  # set semi-arbitrarily as there is a large spread in literature
+
+                fitFun = lambda x: np.real(erf( (4*np.pi*x + 1j)/(2*np.sqrt(x)) )) * np.exp(-1/(4*x)) / erf(2*np.sqrt(x)*np.pi) - exp(-sep/Lp)
+                k = opt.leastsq( fitFun, x0=exp(-sep/Lp) )
+                k = k[0][0] * 2*kT*0.00030461742
+
+                # intrinsicDegrees=30
+                # fitFun = lambda x: (1.0/(2*x) - 2*np.sqrt(np.pi)*np.exp(-4*np.pi**2*x) / (np.sqrt(x)*erf(2*np.pi*np.sqrt(x))) ) - \
+                #          ( (intrinsicDegrees*np.pi/180)**2 + 2*(1-exp(-sep/Lp)) )
+                # k = opt.leastsq( fitFun, x0=1/(1-exp(-sep/Lp)) )
+                # k = k[0][0] * 2*kT*0.00030461742
+
+                t0 = sep*(360.0/10.5)
+
+                # pdb.set_trace()
+                if isFwd1[0]: t0 -= 120
+                if isFwd2[0]: t0 += 120
+
+                t0 = t0 % 360
+
+                # if n2.idx == 0:
+                #     print( n1.idx,n2.idx,n3.idx,n4.idx,k,t0,sep )
+                self.addDihedral( n1,n2,n3,n4,Dihedral(k,t0) )
 
         for nodes,seps in self._getOrientationDihedrals():
             n1,n2,n3,n4 = nodes