{ "cells": [ { "cell_type": "markdown", "id": "260a5d61-ff91-48fc-af4e-1f5a22ea4483", "metadata": {}, "source": [ "# 1. Exploring the Brown Dwarf Synthetic Dataset" ] }, { "cell_type": "markdown", "id": "723c394d-987d-4f2d-8bd6-378a23b1218e", "metadata": { "tags": [] }, "source": [ "\n", "\n", "In the following steps, you will: \n", "\n", "- Load the brown dwarf synthetic spectra used to train the ML models\n", "- Check the variables and parameters in the dataset\n", "- Visualize them for few cases" ] }, { "cell_type": "markdown", "id": "32491e1e-619b-4553-a77c-2b370d90fd05", "metadata": {}, "source": [ "---" ] }, { "cell_type": "markdown", "id": "aeb60d40-df78-4734-9a88-ab41b2e18ad9", "metadata": {}, "source": [ "Before going through this tutorial, make sure you have installed `TelescopeML` (Install through Git) successfully as discussed in this [installation link](https://ehsangharibnezhad.github.io/TelescopeML/installation.html).\n", "\n", "Note: The latest version is located on GitHub, so please follow the instructions provided in the \"Method 1: Install through Git (Recommended)\" section of the link to install the package.\n", "\n", "---\n", "\n", "In a nutshell:\n", "\n", "[1] You have already:\n", "\n", "- Created the *TelescopeML_project* directory.\n", "- Downloaded the *reference_data* from [this link](https://zenodo.org/records/11043721).\n", "- Cloned *TelescopeML* using `git clone https://github.com/EhsanGharibNezhad/TelescopeML.git`.\n", "\n", "[2] The trained ML models, datasets, figures, and tutorials (or notebooks) are now all in your **TelescopeML_project/reference_data** directory.\n", "\n", "[3] The path is defined to your **reference_data**. Confirm it by `os.getenv(\"TelescopeML_reference_data\")`, but if you encounter an error, simply hard code it by defining the path as `__reference_data_path__`.\n", "\n", "[4] Lastly, you should be able to execute `import TelescopeML` without any issues!\n", "\n", "Happy *TelescopeML*ing! ;)\n" ] }, { "cell_type": "markdown", "id": "8a80b0be-236f-4635-bef8-96ffe1e6462e", "metadata": {}, "source": [ "---" ] }, { "cell_type": "code", "execution_count": 1, "id": "6a0e9b08-df67-4377-9ad7-61865ed8f859", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "No Bottleneck unit testing available.\n" ] } ], "source": [ "# Let's first import libraries we need in this tutorial!\n", "from TelescopeML.StatVisAnalyzer import *" ] }, { "cell_type": "markdown", "id": "98309fb6-0ed0-4f20-a65e-45b54910a8c8", "metadata": { "tags": [] }, "source": [ "## 1.1 Load the Synthetic spectra\n", "\n", "We computed a low-resolution spectrum ($R$=200) utilizing atmopshric brown dwarfs grid model, [*Sonora-Bobcat*](https://arxiv.org/pdf/2107.07434.pdf) for spectral range $\\sim$0.9-2.4 $\\mu m$. An open-source atmospheric radiative transfer Python package, [*PICASO*](https://natashabatalha.github.io/picaso/) was employed for generating these datasets. This dataset encompass 30,888 synthetic spectra (or instances or rows). \n", "\n", "Each spectrum has 104 wavelengths (i.e., 0.897, 0.906, ..., 2.512 μm) and 4 output atmospheric parameters:\n", "\n", "- gravity (log *g*)\n", "- temperature (*T*eff)\n", "- carbon-to-oxygen ratio (C/O)\n", "- metallicity ([M/H])\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "cc47b0e4-8644-49fc-89e0-fd5d39b0df5f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "'/Users/egharibn/RESEARCH/ml/projects/TelescopeML_project/reference_data/'" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os \n", "\n", "__reference_data_path__ = os.getenv(\"TelescopeML_reference_data\")\n", "__reference_data_path__ \n", "\n", "\n", "# Note: insert the directory of the reference_data if you get an error reading the reference data!!!\n", "# __reference_data_path__ = 'INSERT_DIRECTORY_OF_reference_data'\n" ] }, { "cell_type": "markdown", "id": "b438caa7-be1e-48d4-a0de-2edfee40bcbc", "metadata": {}, "source": [ "### Load the dataset and check few instances " ] }, { "cell_type": "code", "execution_count": 3, "id": "68bfc730-ea01-488a-ae40-ad33704a34b4", "metadata": { "tags": [] }, "outputs": [ { "data": { "text/html": [ "
\n", " | gravity | \n", "temperature | \n", "c_o_ratio | \n", "metallicity | \n", "2.512 | \n", "2.487 | \n", "2.462 | \n", "2.438 | \n", "2.413 | \n", "2.389 | \n", "... | \n", "0.981 | \n", "0.971 | \n", "0.962 | \n", "0.952 | \n", "0.943 | \n", "0.933 | \n", "0.924 | \n", "0.915 | \n", "0.906 | \n", "0.897 | \n", "
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | \n", "5.00 | \n", "1100 | \n", "0.25 | \n", "-1.0 | \n", "9.103045e-08 | \n", "1.181658e-07 | \n", "1.307868e-07 | \n", "1.269229e-07 | \n", "1.159179e-07 | \n", "8.925110e-08 | \n", "... | \n", "1.257751e-07 | \n", "9.640859e-08 | \n", "7.612550e-08 | \n", "6.901364e-08 | \n", "6.247359e-08 | \n", "4.112384e-08 | \n", "5.127995e-08 | \n", "4.897355e-08 | \n", "4.087795e-08 | \n", "2.791689e-08 | \n", "
1 | \n", "5.00 | \n", "1100 | \n", "0.25 | \n", "-0.7 | \n", "9.103045e-08 | \n", "1.181658e-07 | \n", "1.307868e-07 | \n", "1.269229e-07 | \n", "1.159179e-07 | \n", "8.925110e-08 | \n", "... | \n", "1.257751e-07 | \n", "9.640859e-08 | \n", "7.612550e-08 | \n", "6.901364e-08 | \n", "6.247359e-08 | \n", "4.112384e-08 | \n", "5.127995e-08 | \n", "4.897355e-08 | \n", "4.087795e-08 | \n", "2.791689e-08 | \n", "
2 | \n", "5.00 | \n", "1100 | \n", "0.25 | \n", "-0.5 | \n", "9.103045e-08 | \n", "1.181658e-07 | \n", "1.307868e-07 | \n", "1.269229e-07 | \n", "1.159179e-07 | \n", "8.925110e-08 | \n", "... | \n", "1.257751e-07 | \n", "9.640859e-08 | \n", "7.612550e-08 | \n", "6.901364e-08 | \n", "6.247359e-08 | \n", "4.112384e-08 | \n", "5.127995e-08 | \n", "4.897355e-08 | \n", "4.087795e-08 | \n", "2.791689e-08 | \n", "
3 | \n", "5.00 | \n", "1100 | \n", "0.25 | \n", "-0.3 | \n", "9.103045e-08 | \n", "1.181658e-07 | \n", "1.307868e-07 | \n", "1.269229e-07 | \n", "1.159179e-07 | \n", "8.925110e-08 | \n", "... | \n", "1.257751e-07 | \n", "9.640859e-08 | \n", "7.612550e-08 | \n", "6.901364e-08 | \n", "6.247359e-08 | \n", "4.112384e-08 | \n", "5.127995e-08 | \n", "4.897355e-08 | \n", "4.087795e-08 | \n", "2.791689e-08 | \n", "
4 | \n", "5.00 | \n", "1100 | \n", "0.25 | \n", "0.0 | \n", "9.103045e-08 | \n", "1.181658e-07 | \n", "1.307868e-07 | \n", "1.269229e-07 | \n", "1.159179e-07 | \n", "8.925110e-08 | \n", "... | \n", "1.257751e-07 | \n", "9.640859e-08 | \n", "7.612550e-08 | \n", "6.901364e-08 | \n", "6.247359e-08 | \n", "4.112384e-08 | \n", "5.127995e-08 | \n", "4.897355e-08 | \n", "4.087795e-08 | \n", "2.791689e-08 | \n", "
... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "... | \n", "
30883 | \n", "3.25 | \n", "1000 | \n", "2.50 | \n", "0.7 | \n", "1.533414e-08 | \n", "1.244438e-08 | \n", "7.703017e-09 | \n", "5.262130e-09 | \n", "4.671165e-09 | \n", "3.026652e-09 | \n", "... | \n", "2.064408e-08 | \n", "1.919290e-08 | \n", "1.685050e-08 | \n", "1.772466e-08 | \n", "1.726968e-08 | \n", "1.341722e-08 | \n", "1.365819e-08 | \n", "8.811601e-09 | \n", "4.752807e-09 | \n", "2.206752e-09 | \n", "
30884 | \n", "3.25 | \n", "1000 | \n", "2.50 | \n", "1.0 | \n", "6.942763e-09 | \n", "5.536744e-09 | \n", "3.501408e-09 | \n", "2.445445e-09 | \n", "2.168689e-09 | \n", "1.477159e-09 | \n", "... | \n", "4.353813e-09 | \n", "4.401064e-09 | \n", "4.029425e-09 | \n", "4.482797e-09 | \n", "4.647158e-09 | \n", "3.722947e-09 | \n", "3.825720e-09 | \n", "1.921753e-09 | \n", "8.112957e-10 | \n", "3.211086e-10 | \n", "
30885 | \n", "3.25 | \n", "1000 | \n", "2.50 | \n", "1.3 | \n", "3.758895e-09 | \n", "2.988295e-09 | \n", "1.968653e-09 | \n", "1.417744e-09 | \n", "1.260679e-09 | \n", "9.059680e-10 | \n", "... | \n", "1.546743e-09 | \n", "1.698977e-09 | \n", "1.577032e-09 | \n", "1.813035e-09 | \n", "1.915084e-09 | \n", "1.497190e-09 | \n", "1.512469e-09 | \n", "5.734859e-10 | \n", "1.823897e-10 | \n", "6.218672e-11 | \n", "
30886 | \n", "3.25 | \n", "1000 | \n", "2.50 | \n", "1.7 | \n", "3.150169e-09 | \n", "2.503614e-09 | \n", "1.672564e-09 | \n", "1.218379e-09 | \n", "1.085002e-09 | \n", "7.942492e-10 | \n", "... | \n", "1.332727e-09 | \n", "1.481450e-09 | \n", "1.346700e-09 | \n", "1.538485e-09 | \n", "1.608156e-09 | \n", "1.223594e-09 | \n", "1.254078e-09 | \n", "4.561500e-10 | \n", "1.370389e-10 | \n", "4.616465e-11 | \n", "
30887 | \n", "3.25 | \n", "1000 | \n", "2.50 | \n", "2.0 | \n", "2.665630e-09 | \n", "2.117952e-09 | \n", "1.434730e-09 | \n", "1.055994e-09 | \n", "9.418247e-10 | \n", "7.020869e-10 | \n", "... | \n", "1.533098e-09 | \n", "1.647372e-09 | \n", "1.385020e-09 | \n", "1.517044e-09 | \n", "1.524311e-09 | \n", "1.096679e-09 | \n", "1.209663e-09 | \n", "4.837326e-10 | \n", "1.534210e-10 | \n", "5.612844e-11 | \n", "
30888 rows × 108 columns
\n", "\n", " | gravity | \n", "temperature | \n", "c_o_ratio | \n", "metallicity | \n", "
---|---|---|---|---|
0 | \n", "5.0 | \n", "1100 | \n", "0.25 | \n", "-1.0 | \n", "
1 | \n", "5.0 | \n", "1100 | \n", "0.25 | \n", "-0.7 | \n", "
2 | \n", "5.0 | \n", "1100 | \n", "0.25 | \n", "-0.5 | \n", "
3 | \n", "5.0 | \n", "1100 | \n", "0.25 | \n", "-0.3 | \n", "
4 | \n", "5.0 | \n", "1100 | \n", "0.25 | \n", "0.0 | \n", "