I don't think you even need to cast them to numpy arrays if you use
scipy. It should be able to take bit arrays. Also, jaccard distance is
another name for tanimoto distance. This simplifies the code above:
*from __future__ import print_function
from rdkit import Chem*
*from rdkit.Chem import AllChem*
*
*
*from scipy.spatial import distance
*
*
*
*mol1 = Chem.MolFromSmiles('CCO')*
*mol2 = Chem.MolFromSmiles('CCC')*
*
*
*fp1 = AllChem.GetMorganFingerprintAsBitVect(mol1, 8)
*
*fp2 = AllChem.GetMorganFingerprintAsBitVect(mol2, 8)*
*
# jaccard distance is the same as tanimoto distance
# 1 - distance = similarity
print(1 - distance.jaccard(fp1, fp2))
*
# 0.4285714285714286
Matt
PhD Student
Chemoinformatics Research Group
University of Sheffield
On 16/03/2017 17:38, Curt Fischer wrote:
If you are looking for something quick and dirty, you could stay in
numpy to calculate Tanimoto.
*from rdkit import Chem*
*from rdkit.Chem import AllChem*
*
*
*import numpy as np*
*from __future__ import division*
*
*
*mol1 = Chem.MolFromSmiles('CCO')*
*mol2 = Chem.MolFromSmiles('CCC')*
*
*
*fp1 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol1, 8),
dtype='bool')*
*fp2 = np.array(AllChem.GetMorganFingerprintAsBitVect(mol2, 8),
dtype='bool')*
*
*
*def tanimoto(v1, v2):*
* """*
* Calculates tanimoto similarity for two bit vectors*
* """*
*return(np.bitwise_and(v1, v2).sum() / np.bitwise_or(v1, v2).sum())*
*
*
*tanimoto(fp1, fp2)*
*
*
*Out[4]:0.42857142857142855*
On Thu, Mar 16, 2017 at 7:28 AM, Thomas Evangelidis <teva...@gmail.com
<mailto:teva...@gmail.com>> wrote:
Hello,
I created a numpyarray from a molecule using the following function:
AllChem.GetMorganFingerprintAsBitVect()
Now I would like to convert back to bit vector the numpy array, in
order to calculate the Tanimoto similarity of two compounds. Is
this possible?
thanks
Thomas
--
======================================================================
Thomas Evangelidis
Research Specialist
CEITEC - Central European Institute of Technology
Masaryk University
Kamenice 5/A35/1S081,
62500 Brno, Czech Republic
email: tev...@pharm.uoa.gr <mailto:tev...@pharm.uoa.gr>
teva...@gmail.com <mailto:teva...@gmail.com>
website: https://sites.google.com/site/thomasevangelidishomepage/
<https://sites.google.com/site/thomasevangelidishomepage/>
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