Installation guide for Windows

Follow these instructions to install the CEA on a Windows system (tested with Windows 10)

Prerequisites

Installation

  1. Open Github Desktop from the start menu.
  2. Press Ctrl+Shift+O (clone repository) and select the URL tab.
  3. Paste the CEA Github address: https://github.com/architecture-building-systems/CityEnergyAnalyst
  4. Click Clone.
  5. Open Anaconda prompt (terminal console) from the start menu.
  6. Type cd Documents\Github\CityEnergyAnalyst and press ENTER.
  7. Type conda env create and press ENTER.
  8. Type activate cea and press ENTER.
  9. Type pip install -e .[dev] and press ENTER (mind the dot ‘.’ included in this comand!).
  10. Grab a cup of tea and some toast, this will take about 45 minutes.
  11. Type cea install-toolbox and press ENTER.

Configuration of Pycharm

  1. Open PyCharm from the start menu and open project CityEnergyAnalyst (stored where you downloaded CEA (/Documents).
  2. Open File>Settings>Project:CityEnergyAnalyst>Project Interpreter>Project Interpreter.
  3. Click on the settings button (it looks like a wheel) next to the current interpreter path, and click Add.
  4. Click Conda Environment from the left hand list and select existing environment.
  5. Point to the location of your conda environment. It should look something like C:\Users\your_name\Anaconda2\envs\cea\python.exe or C:\Users\your_name\AppData\Local\conda\conda\envs\cea\python.exe. Where ‘your_name’ represents your user name in windows.
  6. Click apply changes.

Note

We advise to follow the above guide precisely. Especially the conda env create command can trip up users with previous experience in Anaconda / Miniconda as it looks very similar to the conda create command often used to create new conda environments. In addition to creating an environment, conda env create reads in the environment.yml file which contains a list of packages (and versions) to install as well as a definition of the channels to check. If you need to create a conda environment for the CEA that has a specific name (the default is cea) then use the name parameter: conda env create --name your-env-name-here