Dne po 2. 12. 2019 4:45 PM uživatel Greg Landrum
napsal:
> [Adding the mailing list back on]
>
Oops, sorry about that.
> But if you add partial charges (a floating point number) then essentially
> every atom is going to end up with its own invariant. That's unlikely to
> end well.
>
>
I
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On Mon, Dec 2, 2019 at 3:23 PM Thomas Evangelidis wrote:
>
> Thank you for the corrections and the explanation! As stated in my
> original email, I want to add extra atomic properties, like the partial
> charges, as atom invariants and assess whether they are
Hi Thomas,
I think you are making your life more complicated than it needs to be while
testing things. You're certainly making it harder for us to follow what
you're doing. Please try and keep questions as simple as possible. In the
case below, the calls to getNumpyArray() aren't relevant to your
Hi Paolo,
Many thanks for the detailed explanation! Standing by your statement "If
the invariants are provided by the user, they will be used instead", I
attempted to reproduce the default ECFP fingerprint for a small and a large
molecule. Here is the code:
import numpy as np
from rdkit import
Dear Thomas,
You can get the SMILES of substructures that are extracted via
`GetMorganFingerprint` function as follows. Then, you can append any labels
to the SMILES string but not real numbers.
```python
from rdkit import Chem
mol = Chem.MolFromSmiles('Cc1n1')
info = {}
This is my 3rd attempt to get an explanation about how these invariants
work in the ECFP fingerprint cause I can't find it anywhere in the
documentation.
I tried the generateAtomInvariant() [see below] and the resulting ECFP
bit-vectors had for the same molecules drastically reduced variance, 2360
Greetings,
Could someone please clarify how can I pass atomic partial charges to the
ECFP fingerprint generator along with the default atomic properties that it
considers? Can I pass the real charge values or do I have to group them
into bins and pass the bin identifier? I found a function in
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