Comments (2)
In case we took too long to train things, and in case we wanted to allocate something else to that 6th channel, should we have it like this:
encoder_list = dataset.attrs["atom_encoder"]
for i, (pdb_code, chain_id, residue_id, _) in enumerate(data_point_batch):
# Extract frame:
residue_frame = np.asarray(dataset[pdb_code][chain_id][residue_id][()])
# Check if the frame has the correct shape (final dimension is 6) for swapping:
if residue_frame.ndim == 4 and ("Q" or "P" in encoder_list):
# Swap only the 4th and 5th channels (index 3 and 4)
residue_frame[..., 3], residue_frame[..., 4] = residue_frame[..., 4].copy(), residue_frame[..., 3].copy()
X[i] = residue_frame
# Extract residue label:
y[i] = dataset[pdb_code][chain_id][residue_id].attrs["encoded_residue"]
from timed-design.
from timed-design.
Related Issues (20)
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from timed-design.