This is a fork from rdkit/rdkit. This fork adds the possibility to produce detailed labelling information for 2D images of chemical compounds produced by RDkit. This can be useful for machine learning tools like ChemGrapher. To make use of this fork you can find below some installation instructions and example code. However the official repository README you can find here.
First create your conda environment and install the required packages:
conda install -y cmake cairo pillow eigen pkg-config
conda install -y boost-cpp boost py-boost
conda install -c conda-forge xorg-libxrender
conda install -c conda-forge xorg-libxext
conda install -c conda-forge xorg-libxau
conda install -y gxx_linux-64
Clone this repo, create build folder and start to build from sources:
git clone https://github.com/biolearning-stadius/rdkit.git
cd rdkit
mkdir build && cd build
cmake -DPy_ENABLE_SHARED=1 \
-DRDK_INSTALL_INTREE=ON \
-DRDK_INSTALL_STATIC_LIBS=OFF \
-DRDK_BUILD_CPP_TESTS=ON \
-DPYTHON_NUMPY_INCLUDE_PATH="$(python -c 'import numpy ; print(numpy.get_include())')" \
-DBOOST_ROOT="$CONDA_PREFIX" \
-D RDK_BUILD_CAIRO_SUPPORT=ON \
..
make
make install
ctest
Some necessary configuration steps:
export RDBASE=<install-dir>/rdkit/
export LD_LIBRARY_PATH=$RDBASE/lib
export PYTHONPATH=$RDBASE
conda env config vars set RDBASE=<install-dir>/rdkit/
conda env config vars set LD_LIBRARY_PATH=<install-dir>/rdkit/lib
conda env config vars set PYTHONPATH=<install-dir>/rdkit/
from rdkit import Chem
from rdkit.Chem.Draw import rdMolDraw2D
import os
os.environ["RDKIT_LABELPATH"] = "labels_rdkit"
mol = Chem.MolFromSmiles('Cl[C@H](F)NC\C=C\C')
d = rdMolDraw2D.MolDraw2DCairo(1000,1000)
d.DrawMolecule(mol)
d.FinishDrawing()
with open('0.png', 'wb') as f:
f.write(d.GetDrawingText())Now the labels should be in the labels_rdkit file.