Installation

Requirements

Wind-AE requires the following packages and will pip install them automatically by following the Installation guide below.

  • python >= 3.13.0

  • numpy

  • scipy

  • astropy

  • pandas >= 2.2.3

  • matplotlib

  • datetime

  • pyarrow

  • fastparquet

  • requests

  • ChiantiPy

Installation Instructions

Until Wind-AE is dockerized, it is recommended to use a Python environment to avoid dependency issues. However, if your system meets the above requirements, there is no need to create an environment and you can skip to the compilation step.

To create an environment use either

python3 -m venv venv_name.venv
source venv_name.venv/bin/activate

or using conda

conda create -n venv_name
conda activate venv_name
conda install pip

Pip install

Recommended to upgrade pip first:

pip install --upgrade pip

Then

pip install wind_ae

OR Compile from source (BETA)

Clone the repository using

git clone https://github.com/mibroome/wind-ae/

or navigate to github.com/mibroome/wind-ae/ and download and unzip the zip file.

To compile from the source

pip install -r requirements.txt
pip install -e .

Confirming the import was successful

Run tests (optional). Estimated time: 4 minutes

cd wind-ae && pytest

Otherwise, you can test the install by running

python -c "import wind_ae"

Now you can run Wind-AE from anywhere! As seen in the tutorial, the following imports are helpful for most purposes:

from wind_ae.wrapper.relax_wrapper import wind_simulation as wind_sim
from wind_ae.wrapper.wrapper_utils.plots import energy_plot, six_panel_plot, quick_plot
from wind_ae.wrapper.wrapper_utils import constants as const
from wind_ae.wrapper.wrapper_utils.system import system
from wind_ae.wrapper.wrapper_utils.spectrum import spectrum

Note

If you ever need to interface directly with the C code, it lives in wind_ae/src/ and can be executed from within the wind_ae/ folder via ./bin/relaxed_ae. The solution generated will be for a planet with the parameters detailed in the input files in the Inputs/ folder. There is generally no need to interface with the C code and most standard tasks can be accomplished by using the Python wrapper.

Future features and known problems

  • Computation of the complementary error function that governs the drop off of bolometric heating/cooling is not truly self-consistent (converge_mol_atomic_transition(polish=True,width=)) and may require visual confirmation via energy_plot() (checking whether bolometric heating/cooling impede too far into photoionization heating or fall too short) and manual adjustment of the width parameter

sim.load_planet('path/to/planet/file')
bcs = np.copy(sim.windsoln.bcs_tuple)
# erf_loc - normalized velocity value at radius where you want the erf to drop
# erf_rate - how quickly the erf drops off in units of Hsc at erf_loc
# To get initial estimate, run sim.erf_velocity(polish=True)
bcs[-1] = np.array([erf_loc,erf_rate])
sim.inputs.write_bcs(*bcs)
sim.run_wind()

  • Knudsen number calculations currently only contain H-H collisions.

  • Converting spectrum kind from 'full' to 'mono' occasionally has issues.

Check out the open issues.