No project description provided
Project description
SDSS-V Solar Neighborhood Census Selection Function and Subpopulation Probabilities
This repository provides the code to calculate the selection function for the SDSS-V Solar Neighborhood Census (SNC) relative to the Gaia Catalog of Nearby Stars (GCNS). With this selection function, the code allows for the forward modeling of subpopulation probabilities across the HR diagram. A use case would be selecting all stars in the SNC with [Fe/H] < -1 and the forward model would evaluate the likely probability of selecting [Fe/H] < -1 stars from the GCNS in discrete bins across the HR diagram.
Installation
The code can be installed with pip:
git clone https://github.com/imedan/snc_sf
cd snc_sf
pip install .
or in a fresh virtual environment with poetry to fully replicate the development environment
git clone https://github.com/imedan/snc_sf
cd snc_sf
conda create -n "snc_sf" python=3.11
conda activate snc_sf
pip install poetry
poetry install
To fully utilize the code, SDSS-V and GCNS data is need. The SDSS-V DR19 astra summary data can be accessed here. The required GCNS data will automatically be downloaded when first initializing a snc_sf.selection_function.SNCSelectionFunction() object.
Examples
A number of examples using the code are located in notebooks/. These examples are fully explained in the paper accompanying this work. In summary, the examples included related to the following:
dr19_obs.ipynb: Constructs the base SNC 100 pc dataset and creates the plots in Figure 1 of the paper.SF_example_plots.ipynb: Example of the selecrtion function for different regions on the sky, as shown in Figure 2 of the paper.forward_model_GCNS_mock_proof.py: Script that replicates the example with mock data in Section 4.1 and Figure 3 in the paper.forward_model_halpha_ex.py: Script that replicates the example examing the distribution of H-alpha emitters across the HR diagram in Section 4.2 and Figure 4 in the paper.forward_model_mass_dens.py: Script that replicates the example that calculates the stellar number desnity in bins of metallicity and mass in Section 4.3 in the paper.appendix_example.ipynb: Example to demonstrate basic code usage as illustrated in the Appendix of the paper.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file snc_sf-1.1.1.tar.gz.
File metadata
- Download URL: snc_sf-1.1.1.tar.gz
- Upload date:
- Size: 14.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.4 CPython/3.11.13 Darwin/23.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
00cbf6f282df2d1722c8e800a7b0e7f4cbcc4a35ba4996434da3a4fdbd75e1b2
|
|
| MD5 |
4abdabbd14e2f98184d9fc5b4d69a743
|
|
| BLAKE2b-256 |
b2cc7f2a47dad36b6fae7a2c6ff2f8bf490183c1451354488846da78b121b0cb
|
File details
Details for the file snc_sf-1.1.1-py3-none-any.whl.
File metadata
- Download URL: snc_sf-1.1.1-py3-none-any.whl
- Upload date:
- Size: 16.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/2.1.4 CPython/3.11.13 Darwin/23.6.0
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f91bc152f4fb99a1c22ed6be077a718a27a75d3e985bb619cdcf8b0db4dad5c7
|
|
| MD5 |
fdd5c663cd511d0fb6b7f618b3affa10
|
|
| BLAKE2b-256 |
9b8c39f626711daf02c332d72c7bc63a1f30b0d5a5debaa3f4ad809d60cb8355
|