Installation

Environment Setup

We provides two methods to install MPicker, using Conda or using a offline package without Conda.

Using Conda

• Download MPicker_code.tar.gz.
• Uncompress it into an empty folder. Let's call it /absolute/path_to/save_code. Replace it with the actual path where you want to install MPicker.

  mkdir /absolute/path_to/save_code
  tar -zxvf MPicker_code.tar.gz -C /absolute/path_to/save_code
  

• You can edit the env.yml file in the folder path_to/save_code/mpicker_gui:
  • Change "mpicker_full" to your preferred environment name.
  • Modify "cudatoolkit=11.0" to another version if your GPU driver doesn't support it (e.g., =10.1 or =9.2).
  • The library versions don't have to match exactly as in the yml file. We just provide the versions we use. However, scipy>=1.7, yacs>=0.1.8, and pyqt=5 must be satisfied. We choose open3d=0.9.0 for compatibility with older systems, but newer versions are allowed if your machine supports it.
• Create the Conda environment from this file (may take 10 minutes or more):

  conda env create -f path_to/save_code/mpicker_gui/env.yml
  

• Finally, activate the environment with:

  conda activate mpicker_full
  

Without Conda

We still recommend using Conda because our offline environment package is quite large, and Conda is commonly used in Python. You can install Conda from https://docs.conda.io/projects/miniconda/en/latest/.

We generate the environment packages using conda-pack on CentOS7, but it should work for other Linux systems. You have to use Conda if your system is not Linux.

• Download MPicker_environment.tar.gz and MPicker_code.tar.gz.
• Uncompress them into two different empty folders. Let's call them /absolute/path_to/save_code and /absolute/path_to/save_env. Replace them with the real paths where you want to install MPicker.

  mkdir /absolute/path_to/save_code
  tar -zxvf MPicker_code.tar.gz -C /absolute/path_to/save_code
  mkdir /absolute/path_to/save_env
  tar -zxvf MPicker_environment.tar.gz -C /absolute/path_to/save_env
  

• Unpack the Conda environment (only need to do this once):

  source path_to/save_env/bin/activate
  conda-unpack
  source path_to/save_env/bin/deactivate
  

After installation, you can activate the environment using:

source path_to/save_env/bin/activate

and deactivate it using:

source path_to/save_env/bin/deactivate

Environment Setup without Membrane Segmentation

This version doesn't include AI-based automatic membrane segmentation but requires less libraries and has a smaller installation size.

• Replace MPicker_code.tar.gz with MPicker_code_noseg.tar.gz, which lacks the folder memseg_v3.
• Replace MPicker_environment.tar.gz with MPicker_environment_noseg.tar.gz if you set up environment without Conda.
• Replace the env.yml file with env_simple.yml if you set up environment by Conda.
• In fact, you can use most of MPicker's functions in the environment of IsoNet, but scipy must be >=1.7.

Get Started

Quick Start Guide

First, activate the environment. Verify the Python environment using:

which python

Expect a path like:

path_to/save_env/bin/python # if without conda
path_to/miniconda/envs/mpicker_full/bin/python # if using conda

Run the following command to open Mpicker:

python path_to/save_code/mpicker_gui/Mpicker_gui.py

Alternatively, add path_to/save_code/mpicker_gui to your $PATH and open Mpicker with:

Mpicker_gui.py

Then you will get the following GUI:

Troubleshooting

• For Linux users: If your shell is not bash (e.g., csh), switching to bash may resolve environment setup issues. Check your shell using:

  echo $0
  

• If executing .py files directly fails, try running bin/mpicker.sh, a bash wrapper. Add path_to/save_code/bin to your PATH, activate the environment, and run MPicker using:

  mpicker.sh
  

• Modify PYTHON="$(which python)" in bin/mpicker.sh to PYTHON=/absolute/path_of/python if your system fails to locate the installed Python. This allows running Mpicker with mpicker.sh without activating the environment first.

Command Start

Mpicker support these parameters input from command line:

--raw Path of raw tomogram map

--mask Path fo mask tomogram map

--out Existed path to save all the result files

--config Path of config file (config file for reloading all the process history)

Example: (Open a new GUI)

Mpicker_gui.py --raw tomogram.mrc --mask segmentation.mrc --out ./

Example: (Reload a existing job)

Mpicker_gui.py --config ./tomogram.config