Comments (3)
Hey, when you are installing it via pip it'll try to compile it locally, you could call conda install compilers
beforehand.
conda installation is usually easier. Perhaps give it some more time to sort out the dependencies. If that doesnt work, what is your operating system and the exact commands you invoked and the full error message of the pip install?
Cheers!
from deeptime.
Many thanks for your fast reply. Problem solved! I had just created the environment, activated it and tried conda install -c conda-forge deeptime and when that didn't work, pip install deeptime. Then I tried both again in the base environment, and when that failed, conda install in the newly created environment worked.
I'm pretty sure I wouldn't be able to reproduce this. Thanks again!
from deeptime.
Glad it works for you now :) you are welcome
from deeptime.
Related Issues (20)
- Better error handling for custom_sde
- Cannot install deeptime. I have Python 3.10 (Windows 10) and trying to install using Visual Studio 2022 HOT 12
- Error when installing from local repo via pip HOT 4
- TICA fit-once transform-many HOT 6
- Automate generating bdist wheels HOT 1
- Allowing weights for VAMP dimensionality reduction HOT 6
- Error importing deeptime with scikit-learn 1.2.0 HOT 4
- About applying Deeptime to molecular dynamics simulation trajectories on protien HOT 3
- Handling parallel simulations HOT 1
- Implied timescales from deeptime.decomposition.TICA HOT 2
- [Bug] At least one of the given states is not contained in this model HOT 2
- VAMPnet gives highly fluctuating score results HOT 1
- Bayesian Markov models give different MFPT
- How to compute any actual quantity of the coarse-grained kinetics with employing the fuzzy memberships? HOT 7
- Installation without conda and pip HOT 3
- Which version of VAMPNets is there? HOT 1
- deeptime cannot be installed on Mac computers with Apple Silicon and Python 3.12.0. HOT 4
- Does one need identical features to compare between related systems? HOT 4
- Example/tutorial for dealing with MD trajectories HOT 1
- Applying TICA to ragged feature vectors HOT 2
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