IOData can be used to read and write different quantum chemistry file formats.
The simplest way to use IOData, without writing any code is to use the
iodata-convert in.fchk out.molden
--help option for more details on usage.
More complex use cases can be implemented in Python, using IOData as a library. IOData stores an object containing the data read from the file.
To read a file, use something like this:
from iodata import load_one mol = load_one('water.xyz') # XYZ files contain atomic coordinates in Angstrom print(mol.atcoords) # print coordinates in Bohr.
Note that IOData will automatically convert units from the file format’s official specification to atomic units (which is the format used throughout HORTON3).
The file format is inferred from the extension, but one can override the detection mechanism by manually specifying the format:
from iodata import load_one mol = load_one('water.foo', 'xyz') # XYZ file with unusual extension print(mol.atcoords)
IOData also has basic support for loading databases of molecules. For example, the following will iterate over all frames in an XYZ file:
from iodata import load_many # print the title line from each frame in the trajectory. for mol in load_many('trajectory.xyz'): print(mol.title)
IOData can also be used to write different file formats:
from iodata import load_one, dump_one mol = load_one('water.fchk') # Here you may put some code to manipulate mol before writing it the data # to a different file. dump_one(mol, 'water.molden')
One could als convert (and manipulate) an entire trajectory. The following example converts a geometry optimization trajectory from a Gaussian FCHK file to an XYZ file:
from iodata import load_many, dump_many # Conversion without manipulation. dump_many((mol for mol in load_many('water_opt.fchk')), 'water_opt.xyz')
If you wish to perform some manipulations before writing the trajectory, the simplest way is to load the entire trajectory in a list of IOData objects and dump it later:
from iodata import load_many, dump_many # Read the trajectory trj = list(load_many('water_opt.fchk')) # Manipulate if desired # ... # Write the trajectory dump_many(trj, 'water_opt.xyz')
For very large trajectories, you may want to avoid loading it as a whole in
memory. For this, one should avoid making the
list object in the above
example. The following approach would be more memory efficient.
from iodata import load_many, dump_many def itermols(): for mol in load_many("traj1.xyz"): # Do some manipulations yield modified_mol dump_many(itermols(), "traj2.xyz")
IOData can be used to store data in a consistent format for writing at a future point.
import numpy as np from iodata import IOData mol = IOData(title="water") mol.atnums = np.array([8, 1, 1]) mol.coordinates = np.array([[0, 0, 0,], [0, 1, 0,], [0, -1, 0,]]) # in Bohr
IOData always represents all quantities in atomic units and unit conversion
constants are defined in
iodata.utils. Conversion _to_ atomic units is done
by _multiplication_ with a unit constant. This convention can be easily
remembered with the following examples:
When you say “this bond length is 1.5 Å”, the IOData equivalent is
bond_length = 1.5 * angstrom.
The conversion from atomic units is similar to axes labels in old papers. For example. a bond length in angstrom is printed as “Bond length / Å”. Expressing this with IOData’s conventions gives
print("Bond length in Angstrom:", bond_length / angstrom)
(This is rather different from the ASE conventions.)