Installation

There are two ways of using MatFlow:

• The MatFlow command-line interface (CLI)

• The MatFlow Python package

Both of these options allow workflows to be designed and executed. The MatFlow CLI is recommended for beginners and strongly recommended if you want to run MatFlow on a cluster. The Python package allows workflows to be designed and explored via the Python API and is recommended for users comfortable working with Python. If you are interested in contributing to the development of MatFlow, the Python package is the place to start.

The CLI and the Python package can be used simultaneously.

Using pip

The recommended way to install MatFlow is to use pip to install the Python package from PyPI:

pip install matflow-new

This installs the python package, which also gives the CLI version of MatFlow.

Release notes

Release notes for this version (0.3.0a155) are available on GitHub. Use the version switcher in the top-right corner of the page to download/install other versions.

Alternative installation methods

Although not currently recommended, advanced users may wish to use one of the alternative installation methods.

Configuration

MatFlow uses a config file to control details of how it executes workflows. A default config file will be created the first time you submit a workflow. This will work without modification on a personal machine, however if you are using MatFlow on HPC you will likely need to make some modifications to describe the job scheduler, and settings for multiple cores, and to point to your MatFlow environments file.

Some examples are given for the University of Manchester’s CSF.

The path to your config file can be found using matflow manage get-config-path, or to open the config file directly, use matflow open config.

Environments

Matflow has the concept of environments, similar to python virtual environments. These are required so that tasks can run using the specific software they require. Your MatFlow environments must be defined in your environments (YAML) file before MatFlow can run workflows, and this environment file must be pointed to in the config file via the environment_sources key. Once this has been done, your environment file can be be opened using matflow open env-source.

You may wish to modify this template environments file for your own computer, in particular the setup sections for each environment.

- name: damask_parse_env
  setup: |
    source /full/path/to/.venv/bin/activate
  executables:
    - label: python_script
      instances:
        - command: python <<script_name>> <<args>>
          num_cores:
            start: 1
            stop: 32
          parallel_mode: null

- name: formable_env
  setup: |
    source /full/path/to/.venv/bin/activate
  executables:
    - label: python_script
      instances:
        - command: python <<script_name>> <<args>>
          num_cores:
            start: 1
            stop: 32
          parallel_mode: null

- name: defdap_env
  setup: |
    source /full/path/to/.venv/bin/activate
  executables:
    - label: python_script
      instances:
        - command: python <<script_name>> <<args>>
          num_cores:
            start: 1
            stop: 32
          parallel_mode: null

- name: damask_env
  setup: |
    module load mpi/intel-18.0/openmpi/4.1.0
    IMG_PATH=/full/path/to/DAMASK-docker-images/damask-grid_3.0.0-alpha7.sif
    export HDF5_USE_FILE_LOCKING=FALSE
  executables:
    - label: damask_grid
      instances:
        - command: singularity run $IMG_PATH
          num_cores: 1
          parallel_mode: null
        - command: mpirun -n $NSLOTS singularity run $IMG_PATH
          num_cores:
            start: 2
            stop: 32
          parallel_mode: null

- name: matlab_env
  setup: |
    module load apps/binapps/matlab/R2019a
    module load apps/binapps/matlab/third-party-toolboxes/mtex/5.3
  executables:

    - label: compile_mtex
      instances:
        - command: compile-mtex <<script_name>> <<args>>
          num_cores: 1
          parallel_mode: null

    - label: run_compiled_mtex
      instances:
        - command: ./run_<<script_name>>.sh $MATLAB_HOME <<args>>
          num_cores: 1
          parallel_mode: null

    - label: run_mtex
      instances:
      - command: matlab -singleCompThread -batch "<<script_name_no_ext>> <<args>>"
        num_cores: 1
        parallel_mode: null
      - command: matlab -batch "<<script_name_no_ext>> <<args>>"
        num_cores:
          start: 2
          stop: 16
        parallel_mode: null

- name: python_env
  executables:
    - label: python_script
      instances:
        - command: python <<script_name>> <<args>>
          num_cores:
            start: 1
            stop: 32
          parallel_mode: null

- name: dream_3D_env
  executables:
  - label: dream_3D_runner
    instances:
    - command: /full/path/to/dream3d/DREAM3D-6.5.171-Linux-x86_64/bin/PipelineRunner
      num_cores: 1
      parallel_mode: null
  - label: python_script
    instances:
      - command: python <<script_name>> <<args>>
        num_cores: 1
        parallel_mode: null