Xtb contribution #711
Xtb contribution #711
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| def from_hdf(self, hdf=None, group_name=None): | ||
| super(FitsnapJob, self).from_hdf(hdf=hdf, group_name=group_name) | ||
| super(FitsnapJob, self).from_hdf(hdf=hdf, group_name=group_name) |
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I didn't see this in the original PR, but this shouldn't be necessary if you're just calling super() anyway. Is there something weird going on, that made it necessary? If so we should look closer to the source.
| from xtb.ase.calculator import XTB | ||
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| @contextlib.contextmanager | ||
| def make_temp_directory(prefix=None): |
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Can we not use TemporyDirectory?
| outstring = '{}\n\n'.format(len(ase_atoms)) | ||
| for atom in ase_atoms: | ||
| outstring += '{} {} {} {}\n'.format(atom.symbol, | ||
| atom.position[0], | ||
| atom.position[1], | ||
| atom.position[2]) | ||
| outstring = outstring.strip('\n') | ||
| return outstring |
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Using StringIO and ase_atoms.write() should work as well, or are you specifically trying to surpress the cell dimensions in the output?
| if (self['output'] is not None) and ('xtb' in self['output'].list_groups()) and \ | ||
| (self.resultsdf.shape[0] == 0): | ||
| self.resultsdf = pd.read_hdf(self.project_hdf5.file_name, | ||
| key=self.job_name+'/output/xtb') |
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I think writing/reading dataframes directly to hdf should work, but disregard if you've tried that.
| ase_atoms.get_total_energy() | ||
| except: | ||
| pass | ||
| if len(ase_atoms.calc.results) > 0: |
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Should set the job.status.aborted in the else clause.
Added xTB calculator.