Getting Started

To get started with the DENOPTIM tutorials follow this procedure:

  • get just a little bit of knowledge of the command line (Step 1)),

  • install conda on your system (Step 2),

  • create an environment for running DENOPTIM (Step 3 - this is where you install DENOPTIM),

  • download data sets needed for the exercises (Step 4).

Step 1: Get a Command line

Some very simple commands are used in these tutorials. Here is a good introduction to learn the basics (Chapters 1-3 are well more than enough). For the tutorial, you can use any command line interface of your choice:

Step 2: Install Conda

Since conda is extremely popular in data sciences, chances are you already have it installed and know how to use it. In this case, you can jump directly to the section Create DENOPTIM Environment, below.

The instructions are inspired by and derived from work by Software Carpentry and CodeRefinery which is licensed under the terms of the Creative Commons Attribution license 4.0.

Miniconda (and Anaconda, too) comes with a complete Python distribution that lets you create isolated environments that don’t affect anything else. conda is the tool that manages these environments.

Do I Have Conda?

On macOS/Linux, open a Terminal and run the following command. On Windows, open the Anaconda prompt from the Windows search bar (if Anaconda Prompt is not found, then install Miniconda as shown below):

conda list

If you have conda installed, a list of packages will be printed and you can skip the installation and go to the upgrade section.

Installation: If you don’t have Miniconda or Anaconda at all

  • From the Miniconda installer page, download Miniconda3 installer with the latest Python version.

  • Follow regular installation instructions of your operating system.

  • Make sure selecting:

    • installing just for you

    • “Add miniconda3 to my PATH environment variable”

    • “Register Miniconda3 as my default Python 3.9”

Upgrade: If you have Miniconda or Anaconda but you have not used it for a long time

  • If you have only old Anaconda, but not Miniconda, then install Miniconda3 following the instruction above.

  • If you have old Miniconda (no matter if you have Anaconda or not), follow the instruction below and upgrade Conda. Please replace anaconda with conda in the instruction for Windows and macOS:

Setting path to Conda from your terminal shell

This step is usually not needed, but if after the installation you still get an error message like conda command not found whey you type conda --version in your shell terminal.

Windows

  1. Go to the Miniconda3 (or if you have a relatively new Anaconda, then Anaconda3) folder. You can find it by serching from File Explorer search bar.

  2. Navigate to etc folder, and then to profile.d folder. You will find the conda.sh file.

  3. In the folder, right click and choose “Git Bash Here”. You should be able to see the path to this folder in the Git Bash (something like ~/Miniconda3/etc/profile.d).

  4. Run the following command (type the following and enter):

    echo ". '${PWD}'/conda.sh" >> ~/.bashrc

  5. Close Git Bash and reopen it.

  6. Verify that now Git Bash can “see” conda by running conda --version After step 5 you may see this warning but this is nothing to worry about and will not show up the next time you open Git Bash:

WARNING: Found ~/.bashrc but no ~/.bash_profile, ~/.bash_login or ~/.profile.
This looks like an incorrect setup.
A ~/.bash_profile that loads ~/.bashrc will be created for you.

Reference: “Setting Up Conda in Git Bash”, Sep 2020, at Codecademy Forums

macOS

  1. Open a terminal window.

  2. Find the .zshrc file (or .bash_profile if your shell is Bash) which should be located in your home directory (/User/your-user-name)

  3. Navigate to the directory where .zshrc is located (or .bash_profile if your shell is Bash).

  4. Add the following in .zshrc file (or .bash_profile):

export PATH="$HOME/miniconda3/bin:$PATH"

Linux

  1. Open a terminal window.

  2. Run this command which will append to your .bashrc file (adapt the path if Miniconda has been installed to a different place):

echo 'source $HOME/miniconda3/bin/activate' >> ~/.bashrc

If you prefer not to edit your .bashrc, you can also run this command after opening your terminal (each time you open one) and it will bring all conda commands “into view”:

source $HOME/miniconda3/bin/activate

How to uninstall/remove Conda

If you wish to remove Conda again after the workshop, here is how:

Step 3: Create DENOPTIM Environment

We now ask conda to create a dedicated environment for the workshop. The environment required DENOPTIM do conda will install is and make it available within such environment.

  1. Open a new terminal (macOS/Linux) or a new GitBash (Windows) after having completed the installation of conda.

  2. If you have not done so during the installation of Miniconda (see above), activate conda in Miniconda first using conda activate or source ~/miniconda3/bin/activate. If neither works, please go back to the installation section. You probably need to restart your shell terminal. Then try conda activate or source ~/miniconda3/bin/activate again.

  3. Run the following command:

conda env create -f  https://raw.githubusercontent.com/denoptim-project/tutorials/main/environment.yml

  1. Make sure that you see “dnp_work” in the output when you ask for a list of all available environments:

conda env list

Activating the dnp_work environment

In the workshop, we will ask you to activate this environment. This operation must be done every time you have a new session on the terminal. For example, when you open a new terminal.

Then run the following:

conda activate dnp_work

If this does not work, the dnp_work part should be replaced with the whole path, for example:

source activate ~/Miniconda3/envs/dnp_work

How to verify the environment

Once activated, try the following command:

denoptim -v

You should see an output like this and not see errors (exact version numbers are not too important, but should be at least 4.0.0):

V4.0.0

Deactivating the dnp_work environment

Deactivating will remove the denoptim command, so it is an operation meant for when you are done working with the software. After deactivating, you can always re-activate the environment again.

conda deactivate
Warning! we assume that any command line interface used in this tutorial has the dnp_work environment active.

Step 4: Download Datasets

Download all the data from this link. Remember to unzip/extract the zip archive before moving ahead.