Hi Peter,
good idea. As far as I can tell for know it seems to work fine but again no
extensive testing done.
There is however 1 issue I encountered with pillow. I think the conda-forge
one or a dependency of it is broken. Eg. pillow must be installed from defaults
manually and not via
Hi Christos,
The differences are as far as I can see all in the /b layer of the InChI
(/b = stereo parity of double bonds), so my guess is that differing 2D
coordinates is the cause. Do you also see the difference if you run the
output SDF back through KNIME (that is: Are the coordinates
Another option would be to try the conda-forge rdkit. It doesn't appear to
use MKL -- I think the MKL dependency for the rdkit::rdkit package is
coming from the defaults::numpy dependency.
some tools for example scipy and pandas are only available as openblas
> builds via pypi (pip).
I believe
On Tue, Nov 12, 2019 at 2:00 PM Thomas Strunz wrote:
>
> So for me this is temporary workaround but not really a permanent long
> term solution (and as far as I can tell mostly an issue of conda and
> windows and not rdkit)
>
Yeah, it's clearly not the idea solution to the problem. And, yes,
Hi Greg,
great. Thanks for these commands. This leads to below yml (edited to include
pip) which I came up with through looking at the conda package meta.yml file.
name: rdkit_openblas
channels:
- defaults
dependencies:
- python=3.7
- libboost
- py-boost
- pillow
- cairo
-
Dear RDKiters,
I'm having the following problem.
I have a workflow that standardises compounds and as part of the process it
generates standard InChI and InChIkey for the compound. The output is
stored in an SDF.
If I parse the SDF to a dataframe in jupyter notebook, then use the mol
object to
Sorry I missed that you were on windows.
It looks like you can probably carefully construct an environment manually
using the '--no-deps' argument to "conda install"
I created and activated a python 3.7 environment on windows, installed
pandas and numpy from pip, and then did:
conda install
Hi Greg,
thanks for your quick reply.
The main problem is windows. This doesn't work on windows (one needs to add -c
anaconda to your command so that nomkl is found) but then this is the result:
[cid:d11d4da5-0d46-462c-860b-bb266f8e84b8]
eg. it still wants to install mkl together with nomkl.
Hi Thomas,
I'm not sure how to configure conda so that a pip-installed version of
numpy and/or pandas is used, but you can use conda versions without MKL by
installing the nomkl package.
This conda command creates a functioning environment that does not have the
MKL installed:
conda create -n
Dear all,
would it be possible to make RDKit package not depend on mkl (probably via
numpy, pandas) and that it accepts pre-installed numpy and pandas for example
from pip as sufficient?
The background to this is simple. Intel MKL cripples performance on any AMD
bases processor (4-5 times
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