def is_equal(self, other, threshold, chiral=True):
"""Decide if the values of two Torsion objects are equal or not
(based on Torsional RMSD). If the objects have the "initial_values"
attributes, they will be taken into account too.
Args(optional):
chiral (bool): default-True, if set to False, mirror image of the
structure will be considered too
"""
values = []
values.append(tor_rmsd(2, get_vec(self.values, other.values)))
if hasattr(other, "initial_values"):
values.append(
tor_rmsd(2, get_vec(self.values, other.initial_values)))
if not chiral:
values.append(
tor_rmsd(2, get_vec(self.values,
[-1 * i for i in other.values])))
if hasattr(other, "initial_values"):
values.append(
tor_rmsd(
2,
get_vec(self.values,
[-1 * i for i in other.initial_values])))
if min(values) > threshold:
return False
else:
return True
def is_equal(self, other, threshold, chiral=True):
"""Decide if the values of two Torsion objects are equal or not
(based on Torsional RMSD). If the objects have the "initial_values"
attributes, they will be taken into account too.
Args(optional):
chiral (bool): default-True, if set to False, mirror image of the
structure will be considered too
"""
values = []
values.append(tor_rmsd(2, get_vec(self.values, other.values)))
if hasattr(other, "initial_values"):
values.append(tor_rmsd(2, get_vec(self.values,
other.initial_values)))
if not chiral:
values.append(tor_rmsd(2, get_vec(self.values,
[-1*i for i in other.values])))
if hasattr(other, "initial_values"):
values.append(tor_rmsd(2, get_vec(self.values, [-1*i for i in
other.initial_values])))
if min(values) > threshold:
return False
else:
return True
def is_equal(self, other, threshold, chiral=True):
values = []
values.append(tor_rmsd(2, get_vec(self.values, other.values)))
if hasattr(other, "initial_values"):
values.append(tor_rmsd(2, get_vec(self.values, other.initial_values)))
if not chiral:
values.append(tor_rmsd(2, get_vec(self.values, [-1 * i for i in other.values])))
if hasattr(other, "initial_values"):
values.append(tor_rmsd(2, get_vec(self.values, [-1 * i for i in other.initial_values])))
if min(values) > threshold:
return False
else:
return True
def pyranosering_measure(sdf_string, position, dict_of_options):
"""Assign the ring to a conformation from the dictionary of options.
Args:
sdf_string (string)
position (list): 7 atoms defining the ring
dict_of_options (dict) : options for the ring
Returns:
An integer that corresponds to the best matching dict key
Raises:
ValueError: If the lenght of the position is not equal 7.
"""
if len(position) != 7:
raise ValueError("The position needs to be defined by 7 integers")
ang1 = dihedral_measure(sdf_string, position[0:4])
ang2 = dihedral_measure(sdf_string, position[1:5])
ang3 = dihedral_measure(sdf_string, position[2:6])
ang4 = dihedral_measure(sdf_string, (ig(3)(position), ig(4)(position),
ig(5)(position), ig(0)(position)))
ang5 = dihedral_measure(sdf_string, (ig(4)(position), ig(5)(position),
ig(0)(position), ig(1)(position)))
ang6 = dihedral_measure(sdf_string, (ig(5)(position), ig(0)(position),
ig(1)(position), ig(2)(position)))
all_ang = [ang1, ang2, ang3, ang4, ang5, ang6]
rmsd_dict = {}
for key in dict_of_options:
rmsd_dict[key] = (tor_rmsd(2, get_vec(all_ang, dict_of_options[key])))
return int(min(rmsd_dict.iteritems(), key=ig(1))[0])
def pyranosering_measure(sdf_string, position, dict_of_options):
"""Assign the ring to a conformation from the dictionary of options.
Args:
sdf_string (string)
position (list): 7 atoms defining the ring
dict_of_options (dict) : options for the ring
Returns:
An integer that corresponds to the best matching dict key
Raises:
ValueError: If the lenght of the position is not equal 7.
"""
if len(position) != 7:
raise ValueError("The position needs to be defined by 7 integers")
ang1 = dihedral_measure(sdf_string, position[0:4])
ang2 = dihedral_measure(sdf_string, position[1:5])
ang3 = dihedral_measure(sdf_string, position[2:6])
ang4 = dihedral_measure(
sdf_string,
(ig(3)(position), ig(4)(position), ig(5)(position), ig(0)(position)))
ang5 = dihedral_measure(
sdf_string,
(ig(4)(position), ig(5)(position), ig(0)(position), ig(1)(position)))
ang6 = dihedral_measure(
sdf_string,
(ig(5)(position), ig(0)(position), ig(1)(position), ig(2)(position)))
all_ang = [ang1, ang2, ang3, ang4, ang5, ang6]
rmsd_dict = {}
for key in dict_of_options:
rmsd_dict[key] = (tor_rmsd(2, get_vec(all_ang, dict_of_options[key])))
return int(min(rmsd_dict.iteritems(), key=ig(1))[0])
def is_equal(self, other, threshold, chiral=True):
values = []
tmp = []
for i in get_vec(self.values, other.values):
if i == 0:
tmp.append(0)
else:
tmp.append(1)
values.append(sum(tmp) / len(tmp))
if hasattr(other, "initial_values"):
tmp = []
for i in get_vec(self.values, other.initial_values):
if i == 0:
tmp.append(0)
else:
tmp.append(1)
values.append(sum(tmp) / len(tmp))
if min(values) > threshold:
return False
else:
return True
def is_equal(self, other, threshold, chiral=True):
values = []
tmp = []
for i in get_vec(self.values, other.values):
if i == 0:
tmp.append(0)
else:
tmp.append(1)
values.append(sum(tmp) / len(tmp))
if hasattr(other, "initial_values"):
tmp = []
for i in get_vec(self.values, other.initial_values):
if i == 0:
tmp.append(0)
else:
tmp.append(1)
values.append(sum(tmp) / len(tmp))
if min(values) > threshold:
return False
else:
return True
def is_equal(self, other, threshold, chiral=True):
values = []
values.append(tor_rmsd(2, get_vec(self.values, other.values)))
if hasattr(other, "initial_values"):
values.append(
tor_rmsd(2, get_vec(self.values, other.initial_values)))
if not chiral:
values.append(
tor_rmsd(2, get_vec(self.values,
[-1 * i for i in other.values])))
if hasattr(other, "initial_values"):
values.append(
tor_rmsd(
2,
get_vec(self.values,
[-1 * i for i in other.initial_values])))
if min(values) > threshold:
return False
else:
return True