Thanks! You can check out the interactive vega spec for that example viz here:
Enjoy!
2 Likes
Thank you! 
3 Likes
Thank you for a new release! Great work
2 Likes
Just wanted to thank the team for their hard work. Qiime2-2019.4 and the tool as a whole is a huge deal and I am privileged to use it. Definitely looking forward to the cutadapt bug fixes, new filter parameters, trim left on Deblur.
Really exciting stuff! Thank you!
4 Likes
Hello, I am excited for the new release! I am only able to use QIIME2 through the Virtual Box, so I was wondering when the disk image file will be available so that I am able to upgrade?
The disk images for virtual box are usually released a few days after the main release, so that should be available some time this week. Thanks for your patience @Liyah_Smith!
We just deployed new slightly tweaked QIIME 2 2019.4 environment files — these pin the version of numpy to 1.15.4. Maybe @mortonjt can say a few words here about why we made this change, and why it might matter to you. Thanks!
Thanks @thermokarst for deploying an older version.
We’ve seen that the SVD operation in the newest release of numpy and scipy are broken: https://github.com/numpy/numpy/issues/13401
What this means is that all beta diversity calculations involving svd (i.e. pcoa), in addition to the balances will output wrong results using qiime2-2019.4
The newest qiime2-2019.4 environment files should avoid this issue by pinning numpy to an older version. So make sure your qiime2 environments are up-to-date if you are using qiime2-2019.4
Hello,
How could I know if the results (diversity calculations, gneiss) are correct or not? I already installed the new release 2-2019.4 successfully and am using it since yesterday.
Thank you
As @mortonjt mentioned, the issue to do with a bug in a specific version of numpy — the best way to ensure that everything is okay is to re-install 2019.4, being sure to download the newest environment file.
Okay, so after installing the newest environment file, all what I need is to re-do diversity analysis and gneiss. I mean other plugins are still good and no need to re-run them.
Thank you
Great timing! I installed 2019.4 only yesterday. I checked the yml file and the numpy version listed was 1.16.3, so I removed the environment and reinstalled. FYI, I got a conda error when trying to remove the environment:
pre-unlink script failed for package conda-forge::widgetsnbextension-3.4.2-py36_1000
I solved this based on suggestions here and here
Sorry to post conda issues here, but in case anyone else gets this error.
Thanks for continued development!
4 Likes
@mortonjt: can we just install the older version of numpy instead reinstall the new updated QIIME2-2019.4 environment? And how?
Thanks.
Correct! Only analysis downstream of your feature table could have been impacted by this. Since those steps are (usually) very fast, its best to just re-run them so you don’t have to worry about it.
Yes, the only difference between the two environment files is the numpy version.
You can correct that by running:
conda install -c conda-forge numpy=1.15.4
in your QIIME 2 environment. If you are at all nervous about that or conda, the safest thing to do is still to reinstall.
As a general note to anyone: if you or someone you know may have been impacted by this bug, you can always check provenance at the bottom. Just click on python-packages and expand the list until you see numpy. You want to see numpy 1.15.4 with QIIME 2 2019.4. If you see 1.16.3, that could be an issue, so you should verify that the steps recorded do not use some of the problematic OpenBLAS bindings (this is hard to do, so best just re-run).
1 Like
After searching numpy files on my desktop pc (installed 2019.4 envs on 6 May '19), i got this..
There is both of the versions (1.16.3 and 1.15.4).
Is it ok with this condition on my desktop pc? or should I uninstall the 1.16.3 version?
And on my laptop (installed 2019.4 envs on 5 May '19), there is only numpy-1.16.3 version. I will install numpy-1.15.4 on my laptop. thanks @ebolyen.
Thanks all.
Your search is showing your miniconda3/pkgs which is an internal cache for conda, it keeps all versions, but doesn’t reflect which version is actually used. Use conda list to identify that. Otherwise numpy 1.16.3 isn’t itself causing any harm by existing on the hard drive so just verify the environment is correct and you will be fine.
Update: the situation appears to be a bit worse than originally thought. See this announcement for details. We will be releasing a new environment shortly.
1 Like
New environment files are now available. We’ll be releasing VMs soon.
4 Likes
Check out