Further changes to allow support for both OpenBabel 2.4.1 and 3.0

Carbon_assignment.py

@@ -4,7 +4,12 @@
 from scipy.optimize import linear_sum_assignment as optimise
 from scipy.stats import linregress
 import copy
-from openbabel import *
+
+try:
+    from openbabel.openbabel import OBConversion, OBMol, OBAtomAtomIter, OBMolAtomIter
+except ImportError:
+    from openbabel import *
+
 from scipy.stats import gaussian_kde
 
 

FiveConf.py

@@ -11,8 +11,10 @@
 from math import sqrt, pi, cos, sin, acos
 import scipy.optimize as sciopt
 
-from openbabel import *
-
+try:
+    from openbabel.openbabel import OBConversion, OBMol, OBAtomAtomIter, OBMolAtomIter
+except ImportError:
+    from openbabel import *
 
 def main(f, settings):
 

Karplus.py

@@ -13,7 +13,10 @@
 from math import sqrt, pi, cos, sin, acos, atan2
 import sys
 
-from openbabel import *
+try:
+    from openbabel.openbabel import OBConversion, OBMol, OBAtomAtomIter, OBMolAtomIter
+except ImportError:
+    from openbabel import *
 
 #Parameter sets B-E for generalised Karplus equation from
 #C. A. G. Haasnoot, F. A. A. M. de Leeuw and C. Altona

Proton_assignment.py

@@ -6,7 +6,11 @@
 import copy
 import os
 import pickle
-from openbabel import *
+
+try:
+    from openbabel.openbabel import OBConversion, OBMol, OBAtomAtomIter, OBMolAtomIter
+except ImportError:
+    from openbabel import *
 
 def AssignProton(NMRData,Isomers,settings):
 

Proton_processing.py

@@ -5,7 +5,12 @@
 import nmrglue as ng
 from scipy.stats import norm
 import pickle
-from openbabel import *
+
+try:
+    from openbabel.openbabel import OBConversion, OBMol, OBAtomAtomIter, OBMolAtomIter
+except ImportError:
+    from openbabel import *
+
 from scipy.optimize import linear_sum_assignment as optimise
 import copy
 from scipy.interpolate import InterpolatedUnivariateSpline
@@ -1624,9 +1629,7 @@ def integral_score(integrals, structure_protons, proton_guess, l_protons, impuri
 
     diff = abs(proton_guess - structure_protons)
 
-    #incease the value of the scale parameter here where large devations from integer values are expected for the integrals.
-
-    probs = 4 * (1 - norm.cdf(differences, loc=0, scale = 1 / 16))
+    probs = 4 * (1 - norm.cdf(differences, loc=0, scale=1 / 16))
 
     mean = gmean(probs) * (1 - norm.cdf(diff, loc=0, scale=std)) * (1 / 2 ** impurities)