{ "cells": [ { "cell_type": "markdown", "id": "eb864fad", "metadata": {}, "source": [ "# Sccala Photometry" ] }, { "cell_type": "markdown", "id": "448456fe", "metadata": {}, "source": [ "This is an example how to use the `sccala-photometry` module, which essentially is a tool to generate synthetic photometry from absolutely calibrated spectra." ] }, { "cell_type": "markdown", "id": "d7495485", "metadata": {}, "source": [ "The easiest way to use this tool is via its CLI. Simply run\n", "```console\n", "sccala-photometry \n", "```" ] }, { "cell_type": "markdown", "id": "d01e621a", "metadata": {}, "source": [ "This should generate synthetic photometry for every spectrum specified in the `` together with some diagnostic plots." ] }, { "cell_type": "markdown", "id": "aadfb77d", "metadata": {}, "source": [ "But you can also achieve the same result using the functions provided by the package itself:" ] }, { "cell_type": "markdown", "id": "1dcc4950", "metadata": {}, "source": [ "``" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.5" } }, "nbformat": 4, "nbformat_minor": 5 }