Table of Contents

Strongly suggest installing current snapshot instead!

Binary Installation Instructions v2.99.47 (2023/03/10)

Yes, the version number is a bit odd, but this IS a release version

Choices

There are three ways to install EMAN2:

1. Traditional Binary Installation (includes Anaconda/Miniconda install)

2. NEW: Install into an existing Anaconda install 3. Install from GitHub (source build)

If you are already an active Anaconda user, you may prefer approach 2 or 3, above, since it will install within your existing Anaconda system (in its own environment). Having 2 separate Anaconda installs in the same account can be a problem. We like to encourage people to use approach 3 when possible, because A) It can also use an existing Anaconda install, B)it will optimize the binary for the specific CPU you have and C) updating to our current development version becomes a very simple/quick process (if you run into a problem it becomes trivial to check if we have already fixed it). It does require that you have a C compiler installed on your machine, but otherwise requires little other knowledge. If you have built other scientific software from source in the past, we strongly encourage you to try method 3. Method 1 is the same method we have used to distribute EMAN2 binaries for the last several years. It includes a copy of Miniconda (a small version of Anaconda), with EMAN2 installed into an environment. Again, method 1 is NOT recommended if you already have Anaconda on your machine.


«Anchor(Anaconda)»

Option 2: Install into an existing Anaconda setup (all platforms, experimental)

4. Update (optional): You may wish to consider updating Anaconda before installing:

conda update --all

but consider possible impact on other Anaconda environments you may have configured. 5. Install mamba (optional): We had been recommending that everyone install 'mamba', a MUCH faster alternative to the 'conda' command. However, mamba no longer seems to be installing properly itself with the current (as of Mar 2023) release of Anaconda. So, if you are using a somewhat older Anaconda installation, you may want to consider installing mamba, then using 'mamba' instead of 'conda' when installing packages. If you try to install mamba and it gets stuck for a long time or fails, then just use 'conda' for the EMAN2 install. Conda may take a long time to solve the install. If you want to try installing mamba:

conda install mamba -c conda-forge

6. Install: We strongly recommend installing EMAN2 within its own Anaconda/Miniconda environement:

conda create -n eman2 eman-dev==2.99.47 -c cryoem -c conda-forge

7. M1/M2 Macs (Optional): initial support for Tensorflow on the GPU is available via PyPi, but not conda.

# with the eman2 environment activated
pip install tensorflow-metal

8. Linux: see the GPU section below. 9. Activate to Use: Any time you want to use EMAN2 you will need to first activate the correct environment. You can deactivate when done.

conda activate eman2

10. Run these programs to see if the install worked:

#!highlight bash
# This will display the exact version you have installed. If you ask for help, provide the full output of this command.
e2version.py
# Relative speed factor of a single core on your computer, 2-3 typ.
e2speedtest.py
# Opens a browser window you can use to view any EMAN2 compatible file in various ways
e2display.py
# Creates a small image with a circle in the middle of it
e2proc2d.py :64:64:1 test.hdf --process mask.sharp:outer_radius=24
# Displays the file you just created
e2display.py test.hdf

«Anchor(Linux)»

Option 1 (Linux): Standard Binary Install

#!wiki note
The neural network code in EMAN2 works best on machines with Nvidia GPUs. For this to work, compatible Nvidia drivers, CUDA libraries and Tensorflow GPU support must be installed.

11. Cleanup: Only if you have an old pre-Anaconda install of EMAN2 on your machine:

12. Download: Download EMAN2.99.47 13. Install:

#!highlight bash
bash <path-to-EMAN2-installer>

14. Close Shell After installation, close your current terminal window/tab, and open a new one. The new terminal should have access to the 'conda' command. Depending on your Anaconda settings, you may need to run conda activate before using EMAN2 commands and conda deactivate to return to your normal shell settings. 15. Test: Run these programs to see if the install worked:

#!highlight bash
# This will display the exact version you have installed. If you ask for help, provide the full output of this command.
e2version.py
# Relative speed factor of a single core on your computer, 2-3 typ.
e2speedtest.py
# Opens a browser window you can use to view any EMAN2 compatible file in various ways
e2display.py
# Creates a small image with a circle in the middle of it
e2proc2d.py :64:64:1 test.hdf --process mask.sharp:outer_radius=24
# Displays the file you just created
e2display.py test.hdf

Troubleshooting and Tips

In this case try running the dependency installation manually.

conda install eman-deps=33.1 -c cryoem -c conda-forge -c defaults

«Anchor(Mac)»

Option 1: Standard Binary Install (Mac)

IMPORTANT: M1/M2 Macs - The Mac binaries we currently provide here are Intel binaries using Intel Anaconda. While these will run on M1/2 Macs, they will run much more slowly than they should. Both methods 2 & 3 above will provide Native ARM64 binaries (strongly recommended).

16. Cleanup: Only if you have a pre-Anaconda install of EMAN2 on your machine:

17. Download: Download EMAN2.99.47 18. Install:

#!highlight bash
bash <path-to-EMAN2-installer>

19. Close your current terminal window (you may actually want to log out completely), then open a new terminal. The new terminal should have access to the 'conda' command. If you see (base) at the beginning of your command line, then Anaconda is active, and the following tests can be run. If you want to stop using EMAN2, you can run conda deactivate. 20. Test: Run these programs to see if the install worked:

#!highlight bash
# This will display the exact version you have installed. If you ask for help, provide the full output of this command.
e2version.py
# Relative speed factor of a single core on your computer, 2-3 typ.
e2speedtest.py
# Opens a browser window you can use to view any EMAN2 compatible file in various ways
e2display.py
# Creates a small image with a circle in the middle of it
e2proc2d.py :64:64:1 test.hdf --process mask.sharp:outer_radius=24
# Displays the file you just created
e2display.py test.hdf

Tips and Troubleshooting

Run the dependency installation manually.

conda install eman-deps=25 -c cryoem -c defaults -c conda-forge

«Anchor(WSL)»

Windows 10/11 WSL

Windows 10/11 includes an embedded Ubuntu Linux environment. With up to date versions of WSL, it shouldn't be necessary to install additional dependencies. You will need to have WSL configured with your favorite Linux distribution first: WSL You will also need to know something about using WSL/Linux.

Once you have WSL installed and running to your satisfaction, simply follow the Linux Installation Instructions

Windows Native

We are no longer consistently providing native windows binaries for EMAN2. We strongly encourage use of the WSL approach to use EMAN2 (and other open source software) on Windows machines. The Native binaries never supported complete EMAN2/SPARX/SPHIRE functionality, and it really isn't the best approach moving forward.

Windows 10 Legacy WSL

If you are running an out of date WSL environment, you really should update then follow the WSL instructions above. However, these older instructions may be useful if you try to proceed:

It is possible to run the EMAN2 Linux binaries within this Win10 environment, but you will need to install some additional dependencies to do so. Also, you will effectively be running at a Linux command prompt, so you will have to become a bit familiar with Linux to do this, but it does avoid installing an additional operating system on your machine.

#!wiki note
https://docs.microsoft.com/en-us/windows/wsl/install-win10.

21. Click “Start” and type “Turn Windows Features on or off”.

|width=600

22. Install Ubuntu from “Microsoft Store”.

|width=600

23. Run “Ubuntu” from Start Menu.

24. Install OpenGL.

#!highlight bash
sudo apt update
sudo apt install libsm-dev libxrender-dev build-essential libgl1-mesa-dev mesa-utils mesa-common-dev libglu1-mesa libglu1-mesa-dev mesa-utils
sudo apt autoremove

25. Install Xming X Server for Windows.

26. Download and install LINUX binary, not windows binary! Download EMAN2.99.47, Linux.

#!wiki note
Make sure to follow the instructions for shell initialization using `conda-init`.

27. Start X Server and set environment variables.

#!highlight bash
export DISPLAY=:0
glxinfo | grep OpenGL

|width=700

28. Run these programs to see if the install worked:

#!highlight bash
e2version.py
e2speedtest.py
e2display.py
e2proc2d.py :64:64:1 test.hdf --process mask.sharp:outer_radius=24

|width=700


«Anchor(GPU)»

Using NVidia GPUs

Currently, GPUs are only used for a few specific programs involving deep learning, such as tomogram annotation, particle picking and GMM variability analysis.

This support is limited to Linux, and (potentially with some extra effort) Win 11 with an LSW2 installation.

Many machines will have CUDA installed already, and if CUDA is an appropriate version, this should work fine with the !TensorFlow version shipped with EMAN2. However, if you are running newer versions of CUDA there may be problems. You can test compatibility quickly with:

# Make sure you have your environment set to run EMAN2 programs
e2version.py
# The above command should work and return your current version. If it does, then run:
python -c "import tensorflow"

If this command does not return an error, then you should be able to run deep learning software within EMAN2. If it does raise an error, then you will need to debug the problem:

 <code>

apt-get install nvidia-cuda-toolkit </code>

conda remove tensorflow-gpu tensorflow-gpu-base
pip install tensorflow
# read any messages carefully, if there are errors you may need other installations

If you have problems you cannot figure out, feel free to post questions to the EMAN2 Google Group.