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bugfix: support backbone_vector as a list #120

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Merged
pm-blanco merged 2 commits into from
Mar 28, 2025
Merged

bugfix: support backbone_vector as a list #120

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356d0f8
bugfix: support backbone_vector as a list
pm-blanco Mar 19, 2025
86204f6
remove unnecesary code lines, move missplaced if condition
pm-blanco Mar 28, 2025
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3 changes: 2 additions & 1 deletion CHANGELOG.md
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
- Unit testing for reaction methods, bonds, object serialization. (#86, #113)

### Fixed
- docs in `lib.handy_functions`. (#118)
- Occassional crashes when the user provided `backbone_vector` as list instead than a `ndarray` in `pmb.create_molecule()` (#120)
- Docs in `lib.handy_functions`. (#118)
- Writing and reading `pmb.df` from file does no longer change the variable type from `int` to `float` when there are empty cells in the column. (#116)
- Espresso bond objects stored in `pmb.df` now retain the same value for the `._bond_id` attribute as the original Espresso objects. (#116)
- Warning handling and coverage in `setup_lj_interaction` (#112)
Expand Down
21 changes: 11 additions & 10 deletions pyMBE.py
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Expand Up @@ -881,6 +881,14 @@ def create_molecule(self, name, number_of_molecules, espresso_system, list_of_fi
raise ValueError(f"Number of positions provided in {list_of_first_residue_positions} does not match number of molecules desired, {number_of_molecules}")
if number_of_molecules <= 0:
return 0
# Generate an arbitrary random unit vector
if backbone_vector is None:
backbone_vector = self.generate_random_points_in_a_sphere(center=[0,0,0],
radius=1,
n_samples=1,
on_surface=True)[0]
else:
backbone_vector = np.array(backbone_vector)
self.check_if_name_is_defined_in_df(name=name,
pmb_type_to_be_defined='molecule')

Expand All @@ -904,12 +912,7 @@ def create_molecule(self, name, number_of_molecules, espresso_system, list_of_fi
else:
for item in list_of_first_residue_positions:
residue_position = [np.array(list_of_first_residue_positions[pos_index])]
# Generate an arbitrary random unit vector
if backbone_vector is None:
backbone_vector = self.generate_random_points_in_a_sphere(center=[0,0,0],
radius=1,
n_samples=1,
on_surface=True)[0]

residues_info = self.create_residue(name=residue,
espresso_system=espresso_system,
central_bead_position=residue_position,
Expand Down Expand Up @@ -1135,7 +1138,6 @@ def create_residue(self, name, espresso_system, central_bead_position=None,use_d
number_of_copies=1)
residues_index = np.where(self.df['name']==name)
residue_index_list =list(residues_index[0])[-1:]

# search for defined particle and residue names
particle_and_residue_df = self.df.loc[(self.df['pmb_type']== "particle") | (self.df['pmb_type']== "residue")]
particle_and_residue_names = particle_and_residue_df["name"].tolist()
Expand Down Expand Up @@ -1171,8 +1173,7 @@ def create_residue(self, name, espresso_system, central_bead_position=None,use_d
# create the lateral beads
side_chain_list = self.df.loc[self.df.index[residue_index]].side_chains.values[0]
side_chain_beads_ids = []
for side_chain_element in side_chain_list:

for side_chain_element in side_chain_list:
pmb_type = self.df[self.df['name']==side_chain_element].pmb_type.values[0]
if pmb_type == 'particle':
bond = self.search_bond(particle_name1=central_bead_name,
Expand All @@ -1190,7 +1191,7 @@ def create_residue(self, name, espresso_system, central_bead_position=None,use_d
n_samples=1,
on_surface=True)[0]
else:
bead_position=central_bead_position+self.generate_trial_perpendicular_vector(vector=backbone_vector,
bead_position=central_bead_position+self.generate_trial_perpendicular_vector(vector=np.array(backbone_vector),
magnitude=l0)

side_bead_id = self.create_particle(name=side_chain_element,
Expand Down