RACS_luminosities_preds_July_2021.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "RACS_luminosities_preds_July_2021.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dA41H9WzbcEn"
      },
      "source": [
        "# Calculating Luminosities and Luminosity Functions (at 1.4 GHz)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cGxXx8kheFxG"
      },
      "source": [
        "First, let's install some packages."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "e6-YJ1YREnpu",
        "outputId": "c83f8a79-f1dd-4a2c-f66c-976e94995bc0"
      },
      "source": [
        "!pip install scikit-learn==0.23.2\n",
        "\n",
        "!pip install \"tune-sklearn>=0.2.1\"\n",
        "!pip install \"scikit-optimize>=0.8.1\"\n",
        "\n",
        "!pip install ppscore\n",
        "\n",
        "!pip install sklearn-som\n",
        "!pip install umap\n",
        "!pip install trimap\n",
        "!pip install \"pacmap==0.4\"\n",
        "\n",
        "!pip install cmasher\n",
        "!pip install colorcet\n",
        "!pip install mpl-scatter-density\n",
        "\n",
        "# Only for GPU usage\n",
        "# !pip uninstall lightgbm -y\n",
        "# !pip install --upgrade lightgbm\n",
        "# install lightgbm GPU\n",
        "# !pip install lightgbm --install-option=--gpu --install-option=\"--opencl-include-dir=/usr/local/cuda/include/\" --install-option=\"--opencl-library=/usr/local/cuda/lib64/libOpenCL.so\"\n",
        "\n",
        "# !pip install --upgrade \"xgboost>=1.1.0\"\n",
        "# !pip install --upgrade \"catboost>=0.23.2\"\n",
        "!pip install --upgrade shap\n",
        "!pip install pycaret"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
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            "Collecting alembic<=1.4.1\n",
            "  Downloading alembic-1.4.1.tar.gz (1.1 MB)\n",
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            "\u001b[?25hCollecting Mako\n",
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            "\u001b[?25hCollecting smmap<5,>=3.0.1\n",
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            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
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            "  Downloading pyLDAvis-3.2.2.tar.gz (1.7 MB)\n",
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            "  Downloading funcy-1.16-py2.py3-none-any.whl (32 kB)\n",
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            "  Downloading pynndescent-0.5.4.tar.gz (1.1 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.1 MB 33.6 MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: htmlmin, imagehash, alembic, databricks-cli, prometheus-flask-exporter, pyLDAvis, pyod, umap-learn, pynndescent\n",
            "  Building wheel for htmlmin (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for htmlmin: filename=htmlmin-0.1.12-py3-none-any.whl size=27098 sha256=3f18eed1f772604b5e9fa668ff455e764a8e67da0fe6e31f38d76d434c089a4b\n",
            "  Stored in directory: /root/.cache/pip/wheels/70/e1/52/5b14d250ba868768823940c3229e9950d201a26d0bd3ee8655\n",
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            "  Created wheel for imagehash: filename=ImageHash-4.2.1-py2.py3-none-any.whl size=295206 sha256=b62fbe07b93b1e3932f64431bfcec2b8c71beff9349e812b81a8eb71cba8aba1\n",
            "  Stored in directory: /root/.cache/pip/wheels/4c/d5/59/5e3e297533ddb09407769762985d134135064c6831e29a914e\n",
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            "  Created wheel for alembic: filename=alembic-1.4.1-py2.py3-none-any.whl size=158170 sha256=3bd4dc09a3a78a2660a63704eae4698fe3025a6f808ba51a2f7845c524710a62\n",
            "  Stored in directory: /root/.cache/pip/wheels/be/5d/0a/9e13f53f4f5dfb67cd8d245bb7cdffe12f135846f491a283e3\n",
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            "  Stored in directory: /root/.cache/pip/wheels/3b/60/14/6930445b08959fbdf4e3029bac7e1f2cccb2e94df8afa00b29\n",
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            "  Created wheel for prometheus-flask-exporter: filename=prometheus_flask_exporter-0.18.2-py3-none-any.whl size=17416 sha256=16144c6b510ac80ae2f9876d594514faff6a76403a9ca504f40b9ccd61c51fb2\n",
            "  Stored in directory: /root/.cache/pip/wheels/6a/1e/1c/c765920cb92b2f0343d2dd8b481a407cee2823f9b4bbd2e52a\n",
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            "  Created wheel for pyLDAvis: filename=pyLDAvis-3.2.2-py2.py3-none-any.whl size=135618 sha256=7c9bb8c473ad35c7212d8826493dd63761958a32965b5706005773a2f3912ade\n",
            "  Stored in directory: /root/.cache/pip/wheels/f8/b1/9b/560ac1931796b7303f7b517b949d2d31a4fbc512aad3b9f284\n",
            "  Building wheel for pyod (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyod: filename=pyod-0.9.0-py3-none-any.whl size=122560 sha256=a8991a22ea624284debf9b8daeb98c38b925f2a41974596abb2d46e3a7271ac8\n",
            "  Stored in directory: /root/.cache/pip/wheels/42/5f/59/5984a6116a4d19aee28d8ebeffd431364ce1cf21eb73a6ad34\n",
            "  Building wheel for umap-learn (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for umap-learn: filename=umap_learn-0.5.1-py3-none-any.whl size=76566 sha256=fdf66d1cb8138fd99649f3506ea0f83e58073e2380bb7b8b26d0b4e4c0aceca6\n",
            "  Stored in directory: /root/.cache/pip/wheels/01/e7/bb/347dc0e510803d7116a13d592b10cc68262da56a8eec4dd72f\n",
            "  Building wheel for pynndescent (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pynndescent: filename=pynndescent-0.5.4-py3-none-any.whl size=52372 sha256=0b7e4ea4565ce1e7a0bdcfe0f394bfb11e6f94445ff2877fd921f335df3b62a5\n",
            "  Stored in directory: /root/.cache/pip/wheels/d0/5b/62/3401692ddad12324249c774c4b15ccb046946021e2b581c043\n",
            "Successfully built htmlmin imagehash alembic databricks-cli prometheus-flask-exporter pyLDAvis pyod umap-learn pynndescent\n",
            "Installing collected packages: tangled-up-in-unicode, smmap, scipy, multimethod, websocket-client, visions, tqdm, requests, python-editor, Mako, imagehash, gitdb, querystring-parser, PyYAML, pynndescent, prometheus-flask-exporter, phik, htmlmin, gunicorn, gitpython, funcy, docker, databricks-cli, alembic, yellowbrick, umap-learn, scikit-plot, pyod, pyLDAvis, pandas-profiling, mlxtend, mlflow, lightgbm, kmodes, imbalanced-learn, Boruta, pycaret\n",
            "  Attempting uninstall: scipy\n",
            "    Found existing installation: scipy 1.4.1\n",
            "    Uninstalling scipy-1.4.1:\n",
            "      Successfully uninstalled scipy-1.4.1\n",
            "  Attempting uninstall: tqdm\n",
            "    Found existing installation: tqdm 4.41.1\n",
            "    Uninstalling tqdm-4.41.1:\n",
            "      Successfully uninstalled tqdm-4.41.1\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: PyYAML\n",
            "    Found existing installation: PyYAML 3.13\n",
            "    Uninstalling PyYAML-3.13:\n",
            "      Successfully uninstalled PyYAML-3.13\n",
            "  Attempting uninstall: yellowbrick\n",
            "    Found existing installation: yellowbrick 0.9.1\n",
            "    Uninstalling yellowbrick-0.9.1:\n",
            "      Successfully uninstalled yellowbrick-0.9.1\n",
            "  Attempting uninstall: pandas-profiling\n",
            "    Found existing installation: pandas-profiling 1.4.1\n",
            "    Uninstalling pandas-profiling-1.4.1:\n",
            "      Successfully uninstalled pandas-profiling-1.4.1\n",
            "  Attempting uninstall: mlxtend\n",
            "    Found existing installation: mlxtend 0.14.0\n",
            "    Uninstalling mlxtend-0.14.0:\n",
            "      Successfully uninstalled mlxtend-0.14.0\n",
            "  Attempting uninstall: lightgbm\n",
            "    Found existing installation: lightgbm 2.2.3\n",
            "    Uninstalling lightgbm-2.2.3:\n",
            "      Successfully uninstalled lightgbm-2.2.3\n",
            "  Attempting uninstall: imbalanced-learn\n",
            "    Found existing installation: imbalanced-learn 0.4.3\n",
            "    Uninstalling imbalanced-learn-0.4.3:\n",
            "      Successfully uninstalled imbalanced-learn-0.4.3\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.26.0 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed Boruta-0.3 Mako-1.1.4 PyYAML-5.4.1 alembic-1.4.1 databricks-cli-0.14.3 docker-5.0.0 funcy-1.16 gitdb-4.0.7 gitpython-3.1.18 gunicorn-20.1.0 htmlmin-0.1.12 imagehash-4.2.1 imbalanced-learn-0.7.0 kmodes-0.11.0 lightgbm-3.2.1 mlflow-1.19.0 mlxtend-0.18.0 multimethod-1.4 pandas-profiling-3.0.0 phik-0.12.0 prometheus-flask-exporter-0.18.2 pyLDAvis-3.2.2 pycaret-2.3.3 pynndescent-0.5.4 pyod-0.9.0 python-editor-1.0.4 querystring-parser-1.2.4 requests-2.26.0 scikit-plot-0.3.7 scipy-1.5.4 smmap-4.0.0 tangled-up-in-unicode-0.1.0 tqdm-4.61.2 umap-learn-0.5.1 visions-0.7.1 websocket-client-1.1.0 yellowbrick-1.3.post1\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z2ixmp_5eK7q"
      },
      "source": [
        "We need to restart Google's runtime for updating all internal links."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mYXC5XmeFmf8"
      },
      "source": [
        "import os\n",
        "os._exit(00)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W-qIpUSXeSFM"
      },
      "source": [
        "Importing the packages we will use."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K7u20fCrFm96"
      },
      "source": [
        "%matplotlib inline\n",
        "# Static plots\n",
        "#%matplotlib ipympl\n",
        "# Interactive plots\n",
        "import copy\n",
        "import numpy as np\n",
        "import matplotlib.cm as cm\n",
        "import matplotlib.pyplot as plt\n",
        "import matplotlib.colors as mcolors\n",
        "import matplotlib.patheffects as mpe\n",
        "from matplotlib.ticker import FuncFormatter\n",
        "# from mpl_toolkits.axes_grid1.inset_locator import inset_axes\n",
        "import mpl_scatter_density\n",
        "from scipy import optimize\n",
        "from astropy.table import Table, join\n",
        "from astropy import units as u\n",
        "from astropy.cosmology import FlatLambdaCDM\n",
        "from astropy.coordinates import SkyCoord\n",
        "from astropy.visualization import LogStretch\n",
        "from astropy.visualization.mpl_normalize import ImageNormalize\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "from sklearn.model_selection import train_test_split, StratifiedKFold\n",
        "from sklearn.metrics import plot_confusion_matrix, classification_report\n",
        "import ppscore as pps\n",
        "import seaborn as sns\n",
        "import cmasher as cmr\n",
        "import colorcet as cc\n",
        "import getpass\n",
        "# import pacmap\n",
        "# import umap\n",
        "# import trimap\n",
        "from sklearn.manifold import TSNE\n",
        "from sklearn.decomposition import PCA\n",
        "from sklearn_som import som\n",
        "import pandas as pd\n",
        "import re\n",
        "import shap\n",
        "# import pycaret.regression as pyr\n",
        "# import pycaret.classification as pyc\n",
        "# import missingno as msno\n",
        "import os\n",
        "import subprocess"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mICRzJPuhmTR"
      },
      "source": [
        "Small function for normalization of colorbars."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sZAwCZlAF2-h"
      },
      "source": [
        "class MidpointNormalize(mcolors.Normalize):\n",
        "    \"\"\"\n",
        "    Normalise the colorbar so that diverging bars work there way either side from a prescribed midpoint value)\n",
        "\n",
        "    e.g. im=ax1.imshow(array, norm=MidpointNormalize(midpoint=0.,vmin=-100, vmax=100))\n",
        "    \"\"\"\n",
        "    def __init__(self, vmin=None, vmax=None, midpoint=None, clip=False):\n",
        "        self.midpoint = midpoint\n",
        "        mcolors.Normalize.__init__(self, vmin, vmax, clip)\n",
        "\n",
        "    def __call__(self, value, clip=None):\n",
        "        # I'm ignoring masked values and all kinds of edge cases to make a\n",
        "        # simple example...\n",
        "        x, y = [self.vmin, self.midpoint, self.vmax], [0, 0.5, 1]\n",
        "        return np.ma.masked_array(np.interp(value, x, y), np.isnan(value))"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9rwK0_J2hqs_"
      },
      "source": [
        "Configuration snippets for texts in plots with too-crowded backgrounds."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a85Ov1WcMwrg"
      },
      "source": [
        "pe1            = [mpe.Stroke(linewidth=5.0, foreground='black'),\n",
        "                  mpe.Stroke(foreground='white', alpha=1),\n",
        "                  mpe.Normal()]\n",
        "pe2            = [mpe.Stroke(linewidth=3.0, foreground='white'),\n",
        "                  mpe.Stroke(foreground='white', alpha=1),\n",
        "                  mpe.Normal()]"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "10CHE9w3hhx3"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "osnHhVmIhjGM"
      },
      "source": [
        "## Load data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "584vuvMnekD5"
      },
      "source": [
        "We will use predicted redshifts and spectral classes from both DES (Dark Energy Survey) and SM (Sky Mapper)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KyMkBBbMF8NC"
      },
      "source": [
        "file_name_DES = 'RACS_DES_classPred_zPred_df.csv'\n",
        "file_name_SM  = 'RACS_SM_predicts_z_spec_class.csv'"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gd5cl12afZMB"
      },
      "source": [
        "Downloading datasets."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5l3REaF_GRAF"
      },
      "source": [
        "if not os.path.exists(file_name_DES):\n",
        "    subprocess.run(['wget', '--no-check-certificate',\\\n",
        "                    'https://docs.google.com/uc?export=download&id=1jxEMlQxb8kk3PlF6e8LUgA4NuTujciE3',\\\n",
        "                    '-O', file_name_DES], check=True, text=True)"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sQJ4ToS6GR4s"
      },
      "source": [
        "if not os.path.exists(file_name_SM):\n",
        "    subprocess.run(['wget', '--no-check-certificate',\\\n",
        "                    'https://docs.google.com/uc?export=download&id=152dAw9px9A6DiZP4jiviKiT_RSnbKNTp',\\\n",
        "                    '-O', file_name_SM], check=True, text=True)"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D_4stUqIHMkR"
      },
      "source": [
        "catalog_full_DES_df = pd.read_csv(file_name_DES)\n",
        "catalog_full_SM_df  = pd.read_csv(file_name_SM)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b1Mp_W2Hff8g"
      },
      "source": [
        "Get stats from datasets."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AtVYBc9cHYi2",
        "outputId": "40641dd2-2f5d-4d74-dd14-ba0556459e80"
      },
      "source": [
        "catalog_full_DES_df.info(verbose=True)"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 175754 entries, 0 to 175753\n",
            "Data columns (total 31 columns):\n",
            " #   Column               Non-Null Count   Dtype  \n",
            "---  ------               --------------   -----  \n",
            " 0   Unnamed: 0           175754 non-null  int64  \n",
            " 1   Unnamed: 0.1         175754 non-null  int64  \n",
            " 2   MAG_G                175754 non-null  float64\n",
            " 3   MAG_R                175754 non-null  float64\n",
            " 4   MAG_I                175754 non-null  float64\n",
            " 5   MAG_Z                175754 non-null  float64\n",
            " 6   J_VISTA              175754 non-null  float64\n",
            " 7   KS_VISTA             175754 non-null  float64\n",
            " 8   W1MAG                175754 non-null  float64\n",
            " 9   W2MAG                175754 non-null  float64\n",
            " 10  flux_int             175754 non-null  float64\n",
            " 11  color_GmR            175754 non-null  float64\n",
            " 12  color_RmZ            175754 non-null  float64\n",
            " 13  color_ZmJ            175754 non-null  float64\n",
            " 14  color_JmKs           175754 non-null  float64\n",
            " 15  color_KsmW1          175754 non-null  float64\n",
            " 16  color_W1mW2          175754 non-null  float64\n",
            " 17  color_GmRadio_RACS   175754 non-null  float64\n",
            " 18  color_RmRadio_RACS   175754 non-null  float64\n",
            " 19  color_ZmRadio_RACS   175754 non-null  float64\n",
            " 20  color_JmRadio_RACS   175754 non-null  float64\n",
            " 21  color_KsmRadio_RACS  175754 non-null  float64\n",
            " 22  color_W1mRadio_RACS  175754 non-null  float64\n",
            " 23  color_W2mRadio_RACS  175754 non-null  float64\n",
            " 24  n_components         175754 non-null  int64  \n",
            " 25  PSTAR_VISTA          175754 non-null  float64\n",
            " 26  spec_class           12528 non-null   float64\n",
            " 27  z_spec               12528 non-null   float64\n",
            " 28  classLabel           175754 non-null  int64  \n",
            " 29  classScore           175754 non-null  float64\n",
            " 30  zPred                175754 non-null  float64\n",
            "dtypes: float64(27), int64(4)\n",
            "memory usage: 41.6 MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nM6OnE5sHabE",
        "outputId": "5de332fa-663f-4486-8f15-0a6ef660870a"
      },
      "source": [
        "catalog_full_SM_df.info(verbose=True)"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 92013 entries, 0 to 92012\n",
            "Data columns (total 34 columns):\n",
            " #   Column            Non-Null Count  Dtype  \n",
            "---  ------            --------------  -----  \n",
            " 0   Unnamed: 0        92013 non-null  int64  \n",
            " 1   Unnamed: 0.1      92013 non-null  int64  \n",
            " 2   catalogue_id      92013 non-null  int64  \n",
            " 3   n_components      92013 non-null  int64  \n",
            " 4   flux_int          92013 non-null  float64\n",
            " 5   flux_peak         92013 non-null  float64\n",
            " 6   quality_level     92013 non-null  object \n",
            " 7   SOURCEID_VISTA    92013 non-null  int64  \n",
            " 8   W1MAG             92013 non-null  float64\n",
            " 9   W2MAG             92013 non-null  float64\n",
            " 10  J_VISTA           92013 non-null  float64\n",
            " 11  KS_VISTA          92013 non-null  float64\n",
            " 12  PSTAR_VISTA       92013 non-null  float64\n",
            " 13  MAG_U             92013 non-null  float64\n",
            " 14  MAG_G             92013 non-null  float64\n",
            " 15  MAG_R             92013 non-null  float64\n",
            " 16  MAG_I             92013 non-null  float64\n",
            " 17  MAG_Z             92013 non-null  float64\n",
            " 18  z_spec            14699 non-null  float64\n",
            " 19  spec_class        14699 non-null  float64\n",
            " 20  u_g               92013 non-null  float64\n",
            " 21  g_r               92013 non-null  float64\n",
            " 22  r_i               92013 non-null  float64\n",
            " 23  i_z               92013 non-null  float64\n",
            " 24  u_r               92013 non-null  float64\n",
            " 25  g_i               92013 non-null  float64\n",
            " 26  w1_w2             92013 non-null  float64\n",
            " 27  J_K               92013 non-null  float64\n",
            " 28  u_radio           92013 non-null  float64\n",
            " 29  w1_radio          92013 non-null  float64\n",
            " 30  K_radio           92013 non-null  float64\n",
            " 31  z_pred            92013 non-null  float64\n",
            " 32  spec_class_pred   92013 non-null  int64  \n",
            " 33  spec_class_score  92013 non-null  float64\n",
            "dtypes: float64(27), int64(6), object(1)\n",
            "memory usage: 23.9+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YQxoLMomhZAr"
      },
      "source": [
        "## Obtain fluxes and luminosities as 1.4 GHz"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "bbz0xSu9hVY7"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JSR8MFIKfj3w"
      },
      "source": [
        "We assume that, in the radio regime, fluxes are proportional to frequency as:  \n",
        "\n",
        "$$\n",
        "S_{\\nu} \\propto \\nu^{-\\alpha}\n",
        "$$  \n",
        "\n",
        "We will assume a spectral index of $\\alpha = -0.8$."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q8rmOUABIbHk"
      },
      "source": [
        "alpha = -0.8"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4iZGWySZh257"
      },
      "source": [
        "RACS has a sensitivity limit of $0.25$ mJy. We will use sources that have a flux three times that or higher."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wT_bj9a_ldDX"
      },
      "source": [
        "limit_flux = 0.75  # mJy, 3 x 0.25 mJy"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "L6pcD6biiceK"
      },
      "source": [
        "We will assume a $\\Lambda$-CDM cosmology."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sOOxL30OI23p"
      },
      "source": [
        "cosmo = FlatLambdaCDM(H0=70, Om0=0.3)"
      ],
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "m6HIOlmFjm2M"
      },
      "source": [
        "Our original radio measurements are in magnitude units. We need to convert them into fluxes (mJy)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HtTzWti3mAVN"
      },
      "source": [
        "radio_flx_DES     = (catalog_full_DES_df.loc[:, 'flux_int'].to_numpy() * u.mag(u.AB)).to(u.mJy)\n",
        "radio_flx_SM      = (catalog_full_SM_df.loc[:, 'flux_int'].to_numpy() * u.mag(u.AB)).to(u.mJy)"
      ],
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jkFNeFEAmG-W"
      },
      "source": [
        "catalog_full_DES_df['flux_int_mJy'] = radio_flx_DES\n",
        "catalog_full_SM_df['flux_int_mJy']  = radio_flx_SM"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3ErFzpAilvMn"
      },
      "source": [
        "For the sake of using only extragalactic sources, we discard sources classified as stars. Also at this point, we discard sources with fluxes below our limit."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yg4yuFEa5J3V"
      },
      "source": [
        "filter_DES = np.array(catalog_full_DES_df.loc[:, 'flux_int_mJy'] >= limit_flux) &\\\n",
        "                 np.array(catalog_full_DES_df.loc[:, 'classLabel'] != 0)\n",
        "filter_SM  = np.array(catalog_full_SM_df.loc[:, 'flux_int_mJy'] >= limit_flux) &\\\n",
        "                 np.array(catalog_full_SM_df.loc[:, 'spec_class_pred'] != 0)"
      ],
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "W32dDfW9lmLZ"
      },
      "source": [
        "catalog_full_DES_df = catalog_full_DES_df.loc[filter_DES]\n",
        "catalog_full_SM_df  = catalog_full_SM_df.loc[filter_SM]"
      ],
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tKzrlSM4mVGy"
      },
      "source": [
        "From Astropy's cosmology package, we compute luminosity distances, in meters."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZL1B9H5BI4Ud"
      },
      "source": [
        "lum_distances_DES = cosmo.luminosity_distance(catalog_full_DES_df.loc[:, 'zPred']).to(u.m).value\n",
        "lum_distances_SM  = cosmo.luminosity_distance(catalog_full_SM_df.loc[:, 'z_pred']).to(u.m).value"
      ],
      "execution_count": 17,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KQHOXoSJxJaL"
      },
      "source": [
        "For future comparisons, we need to calculate fluxes and luminosities at $1.4$ GHz. From RACS, we have data at $887.5$ MHz.  \n",
        "\n",
        "We will use the following relation for that  \n",
        "\n",
        "$$\n",
        "S_{a} = S_{b} \\times \\left(\\frac{\\nu_{a}}{\\nu_{b}}\\right)^{2}\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y1BuSQSSJk4e"
      },
      "source": [
        "radio_flx_DES_14  = (catalog_full_DES_df.loc[:, 'flux_int'].to_numpy() * u.mag(u.AB)).to(u.mJy) * (1.4e9/887.5e6)**alpha\n",
        "radio_flx_SM_14   = (catalog_full_SM_df.loc[:, 'flux_int'].to_numpy() * u.mag(u.AB)).to(u.mJy) * (1.4e9/887.5e6)**alpha"
      ],
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "g9ExoO8CnChq"
      },
      "source": [
        "Now, we can compute $1.4$ GHz luminosities.  \n",
        "\n",
        "$$\n",
        "\\mathrm{L}_{1.4\\mathrm{GHz}} = \\frac{4 \\pi D_{l}^{2} [\\mathrm{m}^{2}] S_{1.4\\mathrm{GHz}} [\\mathrm{mJy}] \\times 10^{-3} \\times 10^{-26}}{(1 + z)^{1 + \\alpha}} [\\mathrm{W/Hz}]\n",
        "$$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vjwuDgKiJSei"
      },
      "source": [
        "luminosity_DES   = 4 * np.pi * lum_distances_DES**2 * radio_flx_DES_14 * 1e-3  * 1e-26 /\\\n",
        "                     (1 + catalog_full_DES_df.loc[:, 'zPred'])**(1 + alpha)  # in W/Hz\n",
        "luminosity_SM    = 4 * np.pi * lum_distances_SM**2  * radio_flx_SM_14  * 1e-3  * 1e-26 /\\\n",
        "                     (1 + catalog_full_SM_df.loc[:, 'z_pred'])**(1 + alpha)  # in W/Hz"
      ],
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hzv_gPqUMV2i"
      },
      "source": [
        "catalog_full_DES_df['flux_int_mJy_14'] = radio_flx_DES_14\n",
        "catalog_full_SM_df['flux_int_mJy_14']  = radio_flx_SM_14"
      ],
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SXOTdQ66L30r"
      },
      "source": [
        "catalog_full_DES_df['lum_racs'] = luminosity_DES\n",
        "catalog_full_SM_df['lum_racs']  = luminosity_SM"
      ],
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4LKe5iNGn2ms"
      },
      "source": [
        "As a way to clean the samples and their predictions, we will assume that all sources with a $1.4$ GHz luminosity higher than $10^{25}$ W/Hz is an AGN, and we will change its predicted spectroscopic class."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mQFFwzl9J6A2"
      },
      "source": [
        "filt_class_lum_DES = np.array(catalog_full_DES_df['lum_racs'] > 1e25)\n",
        "filt_class_lum_SM  = np.array(catalog_full_SM_df['lum_racs'] > 1e25)"
      ],
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Rk2QjdbOKCpO"
      },
      "source": [
        "catalog_full_DES_df.loc[:, 'classLabel'].mask(filt_class_lum_DES, other=1, inplace=True)\n",
        "catalog_full_SM_df.loc[:, 'spec_class_pred'].mask(filt_class_lum_SM, other=1, inplace=True)"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wYMlko_woJ3_"
      },
      "source": [
        "We can, now, plot the distributions of luminosities as a function of redshift and class."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "4KlTlYYsLn6p",
        "outputId": "8b7b87bf-e5ea-48c4-b8fb-97673c16ac0d"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='log')\n",
        "\n",
        "norm_f = mcolors.LogNorm(vmin=1e-2, vmax=1e6)\n",
        "\n",
        "sc_p = ax1.scatter(catalog_full_DES_df.loc[:, 'zPred'].sample(frac=1, random_state=42),\\\n",
        "            catalog_full_DES_df.loc[:, 'lum_racs'].sample(frac=1, random_state=42),\\\n",
        "            c=catalog_full_DES_df.loc[:, 'classLabel'].sample(frac=1, random_state=42),\\\n",
        "            s=90, plotnonfinite=True, linewidths=0.7, cmap=cm.get_cmap('cet_bgy', 2),\\\n",
        "            edgecolors='k', alpha=0.8, label=f'N = {np.sum(np.isfinite(catalog_full_DES_df.loc[:, \"lum_racs\"]))}')\n",
        "\n",
        "ax1.axhline(y=1e25, ls='--', color='Gray', lw=4)\n",
        "\n",
        "clb             = plt.colorbar(sc_p, ticks=[1.25, 1.75])\n",
        "# clb             = plt.colorbar(sc_p, ticks=[0.33, 1.0, 1.66])\n",
        "# clb.set_ticks([0.33, 1.0, 1.66])\n",
        "clb.ax.set_yticklabels(['AGN', 'Galaxy'])\n",
        "# clb.ax.set_yticklabels(['Star', 'AGN', 'Galaxy'])\n",
        "clb.ax.tick_params(labelsize=14)\n",
        "clb.outline.set_linewidth(2.5)\n",
        "# clb.ax.set_ylabel('$\\mathrm{F}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{mJy}]$', size=14, path_effects=pe2)\n",
        "clb.set_label('Spectral Class', size=14, path_effects=pe2)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('z', size=20)\n",
        "ax1.set_ylabel('$\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.set_xlim(left=-0.05, right=catalog_full_DES_df.loc[:, 'zPred'].max())\n",
        "# ax1.set_ylim(bottom=1e23, top=2e29)\n",
        "ax1.legend(loc=4, fontsize=15, title='DES', title_fontsize=14)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        },
        "id": "37V1IFKqMkKk",
        "outputId": "43347eb5-a012-4cb4-b14a-7de28780a81c"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='log')\n",
        "\n",
        "norm_f = mcolors.LogNorm(vmin=1e-2, vmax=1e6)\n",
        "\n",
        "sc_p = ax1.scatter(catalog_full_SM_df.loc[:, 'z_pred'].sample(frac=1, random_state=42),\\\n",
        "            catalog_full_SM_df.loc[:, 'lum_racs'].sample(frac=1, random_state=42),\\\n",
        "            c=catalog_full_SM_df.loc[:, 'spec_class_pred'].sample(frac=1, random_state=42),\\\n",
        "            s=90, plotnonfinite=True, linewidths=0.7, cmap=cm.get_cmap('cet_bgy', 2),\\\n",
        "            edgecolors='k', alpha=0.8, label=f'N = {np.sum(np.isfinite(catalog_full_SM_df.loc[:, \"lum_racs\"]))}')\n",
        "\n",
        "ax1.axhline(y=1e25, ls='--', color='Gray', lw=4)\n",
        "\n",
        "# clb             = plt.colorbar(sc_p, ticks=[0.33, 1.0, 1.66])\n",
        "clb             = plt.colorbar(sc_p, ticks=[1.25, 1.75])\n",
        "# clb.set_ticks([0.33, 1.0, 1.66])\n",
        "clb.ax.set_yticklabels(['AGN', 'Galaxy'])\n",
        "# clb.ax.set_yticklabels(['Star', 'AGN', 'Galaxy'])\n",
        "clb.ax.tick_params(labelsize=14)\n",
        "clb.outline.set_linewidth(2.5)\n",
        "# clb.ax.set_ylabel('Spectral Class', size=14, path_effects=pe2)\n",
        "clb.set_label('Spectral Class', size=14, path_effects=pe2)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('z', size=20)\n",
        "ax1.set_ylabel('$\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.set_xlim(left=-0.05, right=catalog_full_SM_df.loc[:, 'z_pred'].max())\n",
        "# ax1.set_ylim(bottom=1e23, top=2e29)\n",
        "ax1.legend(loc=4, fontsize=15, title='SM', title_fontsize=14)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "id": "HKBmgyh3NlWW",
        "outputId": "3c4aa28a-e05c-4d1b-d832-0e2620c0a97f"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='log', projection='scatter_density')\n",
        "\n",
        "\n",
        "norm = ImageNormalize(stretch=LogStretch())\n",
        "\n",
        "dens_1 = ax1.scatter_density(catalog_full_DES_df.loc[:, 'zPred'],\\\n",
        "            catalog_full_DES_df.loc[:, 'lum_racs'],\\\n",
        "            cmap=plt.get_cmap('cet_CET_L17'), zorder=0, dpi=12, norm=norm, alpha=0.93)\n",
        "\n",
        "# dens_1 = ax1.scatter_density(catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==2, 'zPred'],\\\n",
        "#             catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==2, 'lum_racs'],\\\n",
        "#             color='b', zorder=0, dpi=12, norm=norm, alpha=0.53)\n",
        "# dens_2 = ax1.scatter_density(catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==1, 'zPred'],\\\n",
        "#             catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==1, 'lum_racs'],\\\n",
        "#             color='r', zorder=0, dpi=12, norm=norm, alpha=0.53)\n",
        "# dens_3 = ax1.scatter_density(catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==0, 'zPred'],\\\n",
        "#             catalog_full_DES_df.loc[catalog_full_DES_df.loc[:, 'classLabel']==0, 'lum_racs'],\\\n",
        "#             color='g', zorder=0, dpi=12, norm=norm, alpha=0.53)\n",
        "\n",
        "# False point for legend\n",
        "ax1.scatter([0], [0], marker='s', s=70, c='k',\\\n",
        "            label=f'N = {np.sum(np.isfinite(catalog_full_DES_df.loc[:, \"lum_racs\"]))}')\n",
        "\n",
        "ax1.axhline(y=1e25, ls='--', color='Gray', lw=4)\n",
        "\n",
        "clb             = plt.colorbar(dens_1)\n",
        "clb.ax.tick_params(labelsize=14)\n",
        "clb.outline.set_linewidth(2.5)\n",
        "# clb.ax.set_ylabel('Points per pixel', size=14, path_effects=pe2)\n",
        "clb.set_label('Points per pixel', size=14, path_effects=pe2)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('z', size=20)\n",
        "ax1.set_ylabel('$\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.set_xlim(left=-0.05, right=catalog_full_DES_df.loc[:, 'zPred'].max())\n",
        "# ax1.set_ylim(bottom=1e23, top=2e29)\n",
        "ax1.legend(loc=4, fontsize=15, title='DES', title_fontsize=14)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "All-NaN slice encountered\n",
            "All-NaN slice encountered\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 88
        },
        "id": "bVXkzQG8Xfag",
        "outputId": "bb088673-3321-4a95-9165-d2794f7ef9cc"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='log', projection='scatter_density')\n",
        "\n",
        "\n",
        "norm = ImageNormalize(stretch=LogStretch())\n",
        "\n",
        "dens_1 = ax1.scatter_density(catalog_full_SM_df.loc[:, 'z_pred'],\\\n",
        "            catalog_full_SM_df.loc[:, 'lum_racs'],\\\n",
        "            cmap=plt.get_cmap('cet_CET_L17'), zorder=0, dpi=12, norm=norm, alpha=0.93)\n",
        "\n",
        "# False point for legend\n",
        "ax1.scatter([0], [0], marker='s', s=70, c='k',\\\n",
        "            label=f'N = {np.sum(np.isfinite(catalog_full_SM_df.loc[:, \"lum_racs\"]))}')\n",
        "\n",
        "ax1.axhline(y=1e25, ls='--', color='Gray', lw=4)\n",
        "\n",
        "clb             = plt.colorbar(dens_1)\n",
        "clb.ax.tick_params(labelsize=14)\n",
        "clb.outline.set_linewidth(2.5)\n",
        "clb.set_label('Points per pixel', size=14, path_effects=pe2)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('z', size=20)\n",
        "ax1.set_ylabel('$\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.set_xlim(left=-0.05, right=catalog_full_SM_df.loc[:, 'z_pred'].max())\n",
        "# ax1.set_ylim(bottom=1e23, top=2e29)\n",
        "ax1.legend(loc=4, fontsize=15, title='SM', title_fontsize=14)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "All-NaN slice encountered\n",
            "All-NaN slice encountered\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RqEAtNEqoUiS"
      },
      "source": [
        "---"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oFlp6bsDoVyQ"
      },
      "source": [
        "## Luminosity functions"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9i8VtLRPplmw"
      },
      "source": [
        "For obtaining luminosity functions, we will use the $\\mathrm{V}_{\\mathrm{max}}$ method. A nice practical example can be seen in [this link](http:https://www.star.bris.ac.uk/sxp/galaxyproblem2ans.pdf)."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a62bnKo7MuY2"
      },
      "source": [
        "With this method, the luminosity function is defined as:  \n",
        "\n",
        "$$\n",
        "\\phi = \\frac{1}{\\Delta \\log{\\mathrm{L}}} \\times \\sum_{i} \\frac{1}{\\mathrm{V}_{\\mathrm{max}, i}}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QySTFKuSNG52"
      },
      "source": [
        "And its uncertainty is obtained as follows:\n",
        "\n",
        "$$\n",
        "\\sigma_{\\phi} = \\frac{1}{\\Delta \\log{\\mathrm{L}}} \\times \\sqrt{\\sum_{i} \\frac{1}{\\mathrm{V}_{\\mathrm{max}, i}^{2}}}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0gQ7IrbZqFfG"
      },
      "source": [
        "What we need to obtain, initially, is the maximum redshift value at which each source would still be seen by RACS.  \n",
        "\n",
        "In order to get that value, we need to use the luminosities we already have and the predicted redshifts.  \n",
        "\n",
        "Theoretically, at that $z_{\\mathrm{max}}$ value, our sources (with a fixed luminosity) will have a flux equal to $\\mathrm{S}_{lim} = 0.75$ mJy."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3g8FHjILq7wV"
      },
      "source": [
        "That can be seen in the following expression:  \n",
        "\n",
        "$$\n",
        "\\mathrm{L}_{1.4\\mathrm{GHz}} = \\frac{4 \\pi D_{l}^{2}(z_{\\mathrm{max}}) \\mathrm{S}_{\\mathrm{lim}}^{\\mathrm{RACS}}}{(1 + z_{\\mathrm{max}})^{1 + \\alpha}} \\times \\left(\\frac{1.4\\mathrm{GHz}}{887.5\\mathrm{MHz}}\\right)^{\\alpha}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UH6AjIFEr5JL"
      },
      "source": [
        "We can manipulate this expression a bit given that we know an expression for $\\mathrm{L}_{1.4\\mathrm{GHz}}$  \n",
        "\n",
        "$$\n",
        "\\frac{4 \\pi D_{l}^{2} \\mathrm{S}_{887.5\\mathrm{MHz}}}{(1 + z)^{1 + \\alpha}} \\times \\left(\\frac{1.4\\mathrm{GHz}}{887.5\\mathrm{MHz}}\\right)^{\\alpha} = \\frac{4 \\pi D_{l}^{2}(z_{\\mathrm{max}}) \\mathrm{S}_{\\mathrm{lim}}^{\\mathrm{RACS}}}{(1 + z_{\\mathrm{max}})^{1 + \\alpha}} \\times \\left(\\frac{1.4\\mathrm{GHz}}{887.5\\mathrm{MHz}}\\right)^{\\alpha}\n",
        "$$\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_bWyV5OXtRE_"
      },
      "source": [
        "$$\n",
        "\\frac{D_{l}^{2} \\mathrm{S}_{887.5\\mathrm{MHz}}}{(1 + z)^{1 + \\alpha}} = \\frac{D_{l}^{2}(z_{\\mathrm{max}}) \\mathrm{S}_{\\mathrm{lim}}^{\\mathrm{RACS}}}{(1 + z_{\\mathrm{max}})^{1 + \\alpha}}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "oJyGr5fqtf4w"
      },
      "source": [
        "$$\n",
        "\\frac{(1 + z_{\\mathrm{max}})^{1 + \\alpha}}{D_{l}^{2}(z_{\\mathrm{max}})} = \\frac{(1 + z)^{1 + \\alpha}}{D_{l}^{2}} \\times \\frac{\\mathrm{S}_{\\mathrm{lim}}^{\\mathrm{RACS}}}{\\mathrm{S}_{887.5\\mathrm{MHz}}}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CaIE0gw4rkUi"
      },
      "source": [
        "So, we need to solve this expression for $z_{\\mathrm{max}}$. But it is not so simple since the luminosity function is not easily invertible.  \n",
        "\n",
        "What we can do is use `Scipy` to find the roots of the following function:  \n",
        "\n",
        "$$\n",
        "f(z_{\\mathrm{max}}) = \\frac{(1 + z_{\\mathrm{max}})^{1 + \\alpha}}{D_{l}^{2}(z_{\\mathrm{max}})} - \\frac{(1 + z)^{1 + \\alpha}}{D_{l}^{2}} \\times \\frac{\\mathrm{S}_{\\mathrm{lim}}^{\\mathrm{RACS}}}{\\mathrm{S}_{887.5\\mathrm{MHz}}}\n",
        "$$"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "K--ORsIXumXZ"
      },
      "source": [
        "The last term is constant for each source, so the algorithm can focus on the first term only."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uF5h79EOvANG"
      },
      "source": [
        "Let's save that last term for each element in our datasets."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hHzwlRzv20QK"
      },
      "source": [
        "catalog_full_DES_df['inter_val'] = ((1 + (1 + catalog_full_DES_df.loc[:, 'zPred'])**(1 + alpha)) / lum_distances_DES**2) *\\\n",
        "         (limit_flux / catalog_full_DES_df['flux_int_mJy'])\n",
        "\n",
        "catalog_full_SM_df['inter_val'] = ((1 + (1 + catalog_full_SM_df.loc[:, 'z_pred'])**(1 + alpha)) / lum_distances_SM**2) *\\\n",
        "         (limit_flux / catalog_full_SM_df['flux_int_mJy'])"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "wjHKJdSdvLsD"
      },
      "source": [
        "Now, we can define the function to use for the root-finding algorithm."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "v4FjnESC4XSF"
      },
      "source": [
        "def func(z, factor):\n",
        "    return (1 + z)**(1 + alpha) / cosmo.luminosity_distance(z).to(u.m).value**2 - factor"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W0bdjiFwvWHY"
      },
      "source": [
        "Finally, we can tell `scipy` to find the roots of the function.  \n",
        "We are doing this inside of `pandas` to save some running time.  \n",
        "`optimize.root` takes, here, three parameters. The first, the function we want to study. The second, a first guess for the redshift (we will use the predicted redshift, it could be any other better guess). And, finally, the other argument in the function, the second constant term."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JH1SXnLp4j5l"
      },
      "source": [
        "catalog_full_DES_df['max_z'] = catalog_full_DES_df.apply(lambda row: optimize.root(func, row['zPred'], args=(row['inter_val'], )).x[0], axis=1)"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kb3caIPaKhGJ"
      },
      "source": [
        "catalog_full_SM_df['max_z'] = catalog_full_SM_df.apply(lambda row: optimize.root(func, row['z_pred'], args=(row['inter_val'], )).x[0], axis=1)"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AiBIdx6cv99Z"
      },
      "source": [
        "Now, we have our maximum redshifts for all the sources in the datasets. We can see some basic statistics."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8UPHjk5N7vP7",
        "outputId": "117de7c0-40d7-4885-8814-08e93e137309"
      },
      "source": [
        "catalog_full_DES_df.loc[:, 'max_z'].describe()"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    106159.000000\n",
              "mean          1.510662\n",
              "std           2.926079\n",
              "min           0.002897\n",
              "25%           0.363137\n",
              "50%           0.764108\n",
              "75%           1.426554\n",
              "max         115.777554\n",
              "Name: max_z, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GB5c2F87qzTh",
        "outputId": "2e85bb43-27f0-4f83-ebb8-6e0952ad1c02"
      },
      "source": [
        "catalog_full_SM_df.loc[:, 'max_z'].describe()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    62590.000000\n",
              "mean         0.653398\n",
              "std          2.381491\n",
              "min         -0.000398\n",
              "25%          0.094776\n",
              "50%          0.193309\n",
              "75%          0.433550\n",
              "max         88.511261\n",
              "Name: max_z, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eC_9D1yJwH99"
      },
      "source": [
        "The next step in the process for our Luminosity Functions is obtaining the maximum volume each source can be detected.  \n",
        "\n",
        "First, from these max redshifts, we compute the max luminosity distances."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hztE0TKsrCm7"
      },
      "source": [
        "catalog_full_DES_df['d_max_mpc'] = cosmo.luminosity_distance(catalog_full_DES_df.loc[:, 'max_z']).to(u.Mpc).value\n",
        "catalog_full_SM_df['d_max_mpc'] = cosmo.luminosity_distance(catalog_full_SM_df.loc[:, 'max_z']).to(u.Mpc).value"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qYrEi9u7wer4"
      },
      "source": [
        "Each source has been detected in a particular survey, and these surveys have a certain sky coverage which is measured in square degrees. You can see these values in Table 1 of [this article](https://arxiv.org/pdf/2103.09257.pdf)."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fOD_9BNDrewX"
      },
      "source": [
        "DES_area = 4900  # sq deg\n",
        "SM_area  = 9300  # sq deg  # old value: 17000"
      ],
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "U6vsXHqJxz3m"
      },
      "source": [
        "With these areas, we can compute the maximum volume each of our sources might have been detected (in $\\mathrm{Mpc}^{3}$). We are using the fact that $1 \\mathrm{deg}^{2} = \\frac{1}{3282} \\mathrm{sr}$."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m9XHgW2Xrlvk"
      },
      "source": [
        "catalog_full_DES_df['max_vol_mpc3'] = DES_area * catalog_full_DES_df['d_max_mpc']**3 / 3 / 3282  # 1 square degree is 1/3282 steradians\n",
        "catalog_full_SM_df['max_vol_mpc3']  = SM_area * catalog_full_SM_df['d_max_mpc']**3 / 3 / 3282  # 1 square degree is 1/3282 steradians"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "44YipGWxyel-"
      },
      "source": [
        "Next, we invert these values to have $1/\\mathrm{V}_{\\mathrm{max}}$"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "deXwO__Nv7nh"
      },
      "source": [
        "catalog_full_DES_df['1_vmax'] = 1 / catalog_full_DES_df['max_vol_mpc3']\n",
        "catalog_full_SM_df['1_vmax']  = 1 / catalog_full_SM_df['max_vol_mpc3']"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "IYqDP_kJCdXW"
      },
      "source": [
        "We also compute $1 / \\mathrm{V}_{\\mathrm{max}}^{2}$ for the error bars in future plots."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "A37C8qr-CcyF"
      },
      "source": [
        "catalog_full_DES_df['1_vmax2'] = 1 / catalog_full_DES_df['max_vol_mpc3']**2\n",
        "catalog_full_SM_df['1_vmax2']  = 1 / catalog_full_SM_df['max_vol_mpc3']**2"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c_EqHiXubCsX",
        "outputId": "219c7c64-1443-4e41-9880-48a7f524cbbb"
      },
      "source": [
        "catalog_full_DES_df['1_vmax'].describe()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    1.061590e+05\n",
              "mean     3.177311e-08\n",
              "std      3.315341e-06\n",
              "min      6.148770e-19\n",
              "25%      1.863808e-12\n",
              "50%      1.883678e-11\n",
              "75%      2.757472e-10\n",
              "max      1.045482e-03\n",
              "Name: 1_vmax, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5fqV8JFAzkxU"
      },
      "source": [
        "Following with the process, now we want to separate our $\\mathrm{V}_{\\mathrm{max}}$ values in bins of luminosity and redshift."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eHV9P8IrzyJ1"
      },
      "source": [
        "First, we create luminosity bins. They could be any array of values that suit your dataset. Check the ranges your luminosities have before creating them."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uS9xBwkOwzUu"
      },
      "source": [
        "bins_size_dex = 0.1  # Log(luminosity) bin size\n",
        "\n",
        "cut_bins_DES = np.logspace(19, 29, int((29 - 19)/bins_size_dex + 1))\n",
        "# cut_bins_DES = [1e19, 1e20, 1e21, 1e22, 1e23, 1e24, 1e25, 1e26,\\\n",
        "#                 1e27, 1e28, 1e29]\n",
        "cut_bins_SM  = np.logspace(9, 29, int((29 - 9)/bins_size_dex + 1))\n",
        "# cut_bins_SM  = [1e9, 1e10, 1e11, 1e12, 1e13, 1e14, 1e15, 1e16,\\\n",
        "#                 1e17, 1e18, 1e19, 1e20, 1e21, 1e22, 1e23, 1e24, 1e25,\\\n",
        "#                 1e26, 1e27, 1e28, 1e29]"
      ],
      "execution_count": 99,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kTeg7C-_0Hc_"
      },
      "source": [
        "With the help of `pandas` we add a column to our datasets flagging each source to which luminosity bin they belong to."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WxbPP2rIxCcx"
      },
      "source": [
        "catalog_full_DES_df['cut_lums'] = pd.cut(catalog_full_DES_df.loc[:, 'lum_racs'],\\\n",
        "                                             bins=cut_bins_DES)\n",
        "catalog_full_SM_df['cut_lums']  = pd.cut(catalog_full_SM_df.loc[:, 'lum_racs'],\\\n",
        "                                             bins=cut_bins_SM)"
      ],
      "execution_count": 100,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BGsGFJim0S0G"
      },
      "source": [
        "These are the luminosity distributions after the binning."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yOtyI8XXxbZL",
        "outputId": "7150b263-a05e-4209-de6f-70dcce48f4dd"
      },
      "source": [
        "catalog_full_DES_df.loc[:, 'cut_lums'].value_counts(sort=False)"
      ],
      "execution_count": 101,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1e+19, 1.2589254117941713e+19]                     0\n",
              "(1.2589254117941713e+19, 1.5848931924611109e+19]    0\n",
              "(1.5848931924611109e+19, 1.9952623149688828e+19]    1\n",
              "(1.9952623149688828e+19, 2.511886431509572e+19]     0\n",
              "(2.511886431509572e+19, 3.162277660168379e+19]      0\n",
              "                                                   ..\n",
              "(3.1622776601683795e+28, 3.981071705534986e+28]     1\n",
              "(3.981071705534986e+28, 5.011872336272756e+28]      2\n",
              "(5.011872336272756e+28, 6.309573444801943e+28]      1\n",
              "(6.309573444801943e+28, 7.943282347242789e+28]      1\n",
              "(7.943282347242789e+28, 1e+29]                      1\n",
              "Name: cut_lums, Length: 100, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 101
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hE_J8hws1XJN",
        "outputId": "2272f0f3-948c-4fa8-955a-8a2ac1f80d6a"
      },
      "source": [
        "catalog_full_SM_df.loc[:, 'cut_lums'].value_counts(sort=False)"
      ],
      "execution_count": 102,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1000000000.0, 1258925411.794]                     1\n",
              "(1258925411.794, 1584893192.461]                   0\n",
              "(1584893192.461, 1995262314.969]                   0\n",
              "(1995262314.969, 2511886431.51]                    0\n",
              "(2511886431.51, 3162277660.168]                    0\n",
              "                                                  ..\n",
              "(3.1622776601683795e+28, 3.981071705534986e+28]    2\n",
              "(3.981071705534986e+28, 5.011872336272756e+28]     0\n",
              "(5.011872336272756e+28, 6.309573444801943e+28]     2\n",
              "(6.309573444801943e+28, 7.943282347242854e+28]     0\n",
              "(7.943282347242854e+28, 1e+29]                     0\n",
              "Name: cut_lums, Length: 200, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 102
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "x7LwG06U0g8S"
      },
      "source": [
        "Finally, we can create new `pandas` DataFrames with the sums of all features by luminosity bin.  \n",
        "\n",
        "We can create separate objects for galaxies and AGN and different redshift bins.  \n",
        "\n",
        "We will use, in principle, two redshift bins $[0.1, 0.4]$ and $[1.0, 1.3]$ to match the examples from Israel's slides (and [this article](https://iopscience.iop.org/article/10.1088/1742-6596/1231/1/012005/pdf))."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uX2vkl-p29Po"
      },
      "source": [
        "filter_z0_DES = np.array(catalog_full_DES_df.loc[:, 'zPred'] >= 0.1) & np.array(catalog_full_DES_df.loc[:, 'zPred'] <= 0.4)\n",
        "filter_z1_DES = np.array(catalog_full_DES_df.loc[:, 'zPred'] >= 1.0) & np.array(catalog_full_DES_df.loc[:, 'zPred'] <= 1.3)\n",
        "filter_z0_SM  = np.array(catalog_full_SM_df.loc[:, 'z_pred'] >= 0.1) & np.array(catalog_full_SM_df.loc[:, 'z_pred'] <= 0.4)\n",
        "filter_z1_SM  = np.array(catalog_full_SM_df.loc[:, 'z_pred'] >= 1.0) & np.array(catalog_full_SM_df.loc[:, 'z_pred'] <= 1.3)\n",
        "\n",
        "filter_AGN_DES = np.array(catalog_full_DES_df.loc[:, 'classLabel'] == 1)\n",
        "filter_gal_DES = np.array(catalog_full_DES_df.loc[:, 'classLabel'] == 2)\n",
        "filter_AGN_SM  = np.array(catalog_full_SM_df.loc[:, 'spec_class_pred'] == 1)\n",
        "filter_gal_SM  = np.array(catalog_full_SM_df.loc[:, 'spec_class_pred'] == 2)"
      ],
      "execution_count": 103,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CQlbIBsc4Evg"
      },
      "source": [
        "Here we add up all the columns (and in particular, the $1/\\mathrm{V}_\\mathrm{max}$) for each z-L bin."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8I2JTnIrxxrv"
      },
      "source": [
        "DES_AGN_sumed_bins_z0 = catalog_full_DES_df.loc[filter_AGN_DES & filter_z0_DES].groupby('cut_lums').sum()\n",
        "DES_gal_sumed_bins_z0 = catalog_full_DES_df.loc[filter_gal_DES & filter_z0_DES].groupby('cut_lums').sum()\n",
        "SM_AGN_sumed_bins_z0  = catalog_full_SM_df.loc[filter_AGN_SM & filter_z0_SM].groupby('cut_lums').sum()\n",
        "SM_gal_sumed_bins_z0  = catalog_full_SM_df.loc[filter_gal_SM & filter_z0_SM].groupby('cut_lums').sum()\n",
        "\n",
        "DES_AGN_sumed_bins_z1 = catalog_full_DES_df.loc[filter_AGN_DES & filter_z1_DES].groupby('cut_lums').sum()\n",
        "DES_gal_sumed_bins_z1 = catalog_full_DES_df.loc[filter_gal_DES & filter_z1_DES].groupby('cut_lums').sum()\n",
        "SM_AGN_sumed_bins_z1  = catalog_full_SM_df.loc[filter_AGN_SM & filter_z1_SM].groupby('cut_lums').sum()\n",
        "SM_gal_sumed_bins_z1  = catalog_full_SM_df.loc[filter_gal_SM & filter_z1_SM].groupby('cut_lums').sum()"
      ],
      "execution_count": 104,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lDm4xgQn3-Cy"
      },
      "source": [
        "We add an extra column with the number of elements per bin for drawing error bars in our plots."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yRr_VAls1dKJ"
      },
      "source": [
        "DES_AGN_sumed_bins_z0['size'] = catalog_full_DES_df.loc[filter_AGN_DES & filter_z0_DES, 'cut_lums'].value_counts(sort=False)\n",
        "DES_gal_sumed_bins_z0['size'] = catalog_full_DES_df.loc[filter_gal_DES & filter_z0_DES, 'cut_lums'].value_counts(sort=False)\n",
        "SM_AGN_sumed_bins_z0['size']  = catalog_full_SM_df.loc[filter_AGN_SM & filter_z0_SM, 'cut_lums'].value_counts(sort=False)\n",
        "SM_gal_sumed_bins_z0['size']  = catalog_full_SM_df.loc[filter_gal_SM & filter_z0_SM, 'cut_lums'].value_counts(sort=False)\n",
        "\n",
        "DES_AGN_sumed_bins_z1['size'] = catalog_full_DES_df.loc[filter_AGN_DES & filter_z1_DES, 'cut_lums'].value_counts(sort=False)\n",
        "DES_gal_sumed_bins_z1['size'] = catalog_full_DES_df.loc[filter_gal_DES & filter_z1_DES, 'cut_lums'].value_counts(sort=False)\n",
        "SM_AGN_sumed_bins_z1['size']  = catalog_full_SM_df.loc[filter_AGN_SM & filter_z1_SM, 'cut_lums'].value_counts(sort=False)\n",
        "SM_gal_sumed_bins_z1['size']  = catalog_full_SM_df.loc[filter_gal_SM & filter_z1_SM, 'cut_lums'].value_counts(sort=False)"
      ],
      "execution_count": 105,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ayuI6LzaTbJz"
      },
      "source": [
        "DES_AGN_sumed_bins_z0['delta_L'] = (DES_AGN_sumed_bins_z0.index.categories.right - DES_AGN_sumed_bins_z0.index.categories.left).values\n",
        "DES_gal_sumed_bins_z0['delta_L'] = (DES_gal_sumed_bins_z0.index.categories.right - DES_gal_sumed_bins_z0.index.categories.left).values\n",
        "SM_AGN_sumed_bins_z0['delta_L']  = (SM_AGN_sumed_bins_z0.index.categories.right - SM_AGN_sumed_bins_z0.index.categories.left).values\n",
        "SM_gal_sumed_bins_z0['delta_L']  = (SM_gal_sumed_bins_z0.index.categories.right - SM_gal_sumed_bins_z0.index.categories.left).values\n",
        "\n",
        "DES_AGN_sumed_bins_z1['delta_L'] = (DES_AGN_sumed_bins_z1.index.categories.right - DES_AGN_sumed_bins_z1.index.categories.left).values\n",
        "DES_gal_sumed_bins_z1['delta_L'] = (DES_gal_sumed_bins_z1.index.categories.right - DES_gal_sumed_bins_z1.index.categories.left).values\n",
        "SM_AGN_sumed_bins_z1['delta_L']  = (SM_AGN_sumed_bins_z1.index.categories.right - SM_AGN_sumed_bins_z1.index.categories.left).values\n",
        "SM_gal_sumed_bins_z1['delta_L']  = (SM_gal_sumed_bins_z1.index.categories.right - SM_gal_sumed_bins_z1.index.categories.left).values"
      ],
      "execution_count": 106,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Zn7uwbaOzKnx",
        "outputId": "45030e54-40c2-4876-e0a8-ad28ac42d4ef"
      },
      "source": [
        "DES_AGN_sumed_bins_z0.loc[:, '1_vmax']"
      ],
      "execution_count": 107,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut_lums\n",
              "(1e+19, 1.2589254117941713e+19]                     0.0\n",
              "(1.2589254117941713e+19, 1.5848931924611109e+19]    0.0\n",
              "(1.5848931924611109e+19, 1.9952623149688828e+19]    0.0\n",
              "(1.9952623149688828e+19, 2.511886431509572e+19]     0.0\n",
              "(2.511886431509572e+19, 3.162277660168379e+19]      0.0\n",
              "                                                   ... \n",
              "(3.1622776601683795e+28, 3.981071705534986e+28]     0.0\n",
              "(3.981071705534986e+28, 5.011872336272756e+28]      0.0\n",
              "(5.011872336272756e+28, 6.309573444801943e+28]      0.0\n",
              "(6.309573444801943e+28, 7.943282347242789e+28]      0.0\n",
              "(7.943282347242789e+28, 1e+29]                      0.0\n",
              "Name: 1_vmax, Length: 100, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 107
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3dOoFNeHToj4",
        "outputId": "6ed53d31-b230-4f15-8d41-34f7093947db"
      },
      "source": [
        "np.log10(DES_AGN_sumed_bins_z0.loc[:, 'delta_L'])"
      ],
      "execution_count": 108,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "cut_lums\n",
              "(1e+19, 1.2589254117941713e+19]                     18.413175\n",
              "(1.2589254117941713e+19, 1.5848931924611109e+19]    18.513175\n",
              "(1.5848931924611109e+19, 1.9952623149688828e+19]    18.613175\n",
              "(1.9952623149688828e+19, 2.511886431509572e+19]     18.713175\n",
              "(2.511886431509572e+19, 3.162277660168379e+19]      18.813175\n",
              "                                                      ...    \n",
              "(3.1622776601683795e+28, 3.981071705534986e+28]     27.913175\n",
              "(3.981071705534986e+28, 5.011872336272756e+28]      28.013175\n",
              "(5.011872336272756e+28, 6.309573444801943e+28]      28.113175\n",
              "(6.309573444801943e+28, 7.943282347242789e+28]      28.213175\n",
              "(7.943282347242789e+28, 1e+29]                      28.313175\n",
              "Name: delta_L, Length: 100, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 108
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w7k_l-aU8ICJ"
      },
      "source": [
        "We can, finally, plot our results."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 598
        },
        "id": "P4Mvc9GryxCb",
        "outputId": "de600129-ee76-47d9-894d-453ce3248f7c"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='linear')\n",
        "\n",
        "y_errs = np.array([np.log10(DES_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "         np.log10(DES_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex -\\\n",
        "                  np.sqrt(DES_AGN_sumed_bins_z0.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "          np.log10(np.sqrt(DES_AGN_sumed_bins_z0.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex +\\\n",
        "                   DES_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "          np.log10(DES_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex)])\n",
        "\n",
        "ax1.errorbar(np.log10(cut_bins_DES[:-1]) + bins_size_dex / 2, np.log10(DES_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='o', ls='',\\\n",
        "             label='DES AGN', ms=10, color='royalblue', alpha=0.8)\n",
        "ax1.errorbar(np.log10(cut_bins_DES[:-1]) + bins_size_dex / 2, np.log10(DES_gal_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='s', ls='',\\\n",
        "             label='DES Galaxies', ms=10, color='tomato', alpha=0.8)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('$\\log{}\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "ax1.set_ylabel('$\\log{}\\mathrm{\\phi}\\, [\\mathrm{Mpc}^{-3}\\mathrm{dex}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.legend(loc=1, fontsize=20, title='0.1 < z < 0.4', title_fontsize=16)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "divide by zero encountered in log10\n",
            "invalid value encountered in log10\n",
            "invalid value encountered in subtract\n",
            "divide by zero encountered in log10\n",
            "divide by zero encountered in log10\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 581
        },
        "id": "YcEwj42GzsyN",
        "outputId": "58ae5149-35b1-4aed-9b81-34e987bba8ce"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='linear')\n",
        "\n",
        "y_errs = np.array([np.log10(SM_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "         np.log10(SM_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex -\\\n",
        "                  np.sqrt(SM_AGN_sumed_bins_z0.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "          np.log10(np.sqrt(SM_AGN_sumed_bins_z0.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex +\\\n",
        "                   SM_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "          np.log10(SM_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex)])\n",
        "\n",
        "ax1.errorbar(np.log10(cut_bins_SM[:-1]) + bins_size_dex / 2, np.log10(SM_AGN_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                      bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='o', ls='',\\\n",
        "             label='SM AGN', ms=10, color='royalblue', alpha=0.8)\n",
        "ax1.errorbar(np.log10(cut_bins_SM[:-1]) + bins_size_dex / 2, np.log10(SM_gal_sumed_bins_z0.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                      bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='s', ls='',\\\n",
        "             label='SM Galaxies', ms=10, color='tomato', alpha=0.8)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('$\\log{}\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "ax1.set_ylabel('$\\log{}\\mathrm{\\phi}\\, [\\mathrm{Mpc}^{-3}\\mathrm{dex}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.legend(loc=1, fontsize=20, title='0.1 < z < 0.4', title_fontsize=16)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "divide by zero encountered in log10\n",
            "invalid value encountered in subtract\n",
            "divide by zero encountered in log10\n",
            "divide by zero encountered in log10\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "23_Vq3lcsOkd",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 581
        },
        "outputId": "18917cd0-0ccb-4889-d2ca-9a7aa828cffe"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='linear')\n",
        "\n",
        "y_errs = np.array([np.log10(DES_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "         np.log10(DES_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex -\\\n",
        "                  np.sqrt(DES_AGN_sumed_bins_z1.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "          np.log10(np.sqrt(DES_AGN_sumed_bins_z1.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex +\\\n",
        "                   DES_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "          np.log10(DES_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex)])\n",
        "\n",
        "ax1.errorbar(np.log10(cut_bins_DES[:-1]) + bins_size_dex / 2, np.log10(DES_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='o', ls='',\\\n",
        "             label='DES AGN', ms=10, color='royalblue', alpha=0.8)\n",
        "ax1.errorbar(np.log10(cut_bins_DES[:-1]) + bins_size_dex / 2, np.log10(DES_gal_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='s', ls='',\\\n",
        "             label='DES Galaxies', ms=10, color='tomato', alpha=0.8)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('$\\log{}\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "ax1.set_ylabel('$\\log{}\\mathrm{\\phi}\\, [\\mathrm{Mpc}^{-3}\\mathrm{dex}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.legend(loc=1, fontsize=20, title='1.0 < z < 1.3', title_fontsize=16)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "divide by zero encountered in log10\n",
            "invalid value encountered in subtract\n",
            "divide by zero encountered in log10\n",
            "divide by zero encountered in log10\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "F8aDanZH8Wye",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 581
        },
        "outputId": "96f65bfe-c620-4aa5-82b4-568ef8ca0931"
      },
      "source": [
        "fig             = plt.figure(figsize=(13,7))\n",
        "ax1             = fig.add_subplot(111, xscale='linear', yscale='linear')\n",
        "\n",
        "y_errs = np.array([np.log10(SM_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "         np.log10(SM_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex -\\\n",
        "                  np.sqrt(SM_AGN_sumed_bins_z1.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex),\\\n",
        "          np.log10(np.sqrt(SM_AGN_sumed_bins_z1.loc[:, '1_vmax2'].to_numpy()) /\\\n",
        "                                                                       bins_size_dex +\\\n",
        "                   SM_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex) -\\\n",
        "          np.log10(SM_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                       bins_size_dex)])\n",
        "\n",
        "ax1.errorbar(np.log10(cut_bins_SM[:-1]) + bins_size_dex / 2, np.log10(SM_AGN_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                      bins_size_dex),\\\n",
        "              xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='o', ls='',\\\n",
        "             label='SM AGN', ms=10, color='royalblue', alpha=0.8)\n",
        "ax1.errorbar(np.log10(cut_bins_SM[:-1]) + bins_size_dex / 2, np.log10(SM_gal_sumed_bins_z1.loc[:, '1_vmax'].to_numpy() /\\\n",
        "                                                                      bins_size_dex), xerr=bins_size_dex / 2, yerr=y_errs * 1e0, marker='s', ls='',\\\n",
        "             label='SM Galaxies', ms=10, color='tomato', alpha=0.8)\n",
        "\n",
        "ax1.tick_params(which='both', top=True, right=True, direction='in')\n",
        "ax1.tick_params(axis='both', which='major', labelsize=14)\n",
        "ax1.tick_params(which='major', length=8, width=1.5)\n",
        "ax1.tick_params(which='minor', length=4, width=1.5)\n",
        "ax1.set_xlabel('$\\log{}\\mathrm{L}_{1.4 \\mathrm{GHz}}\\, [\\mathrm{W}/\\mathrm{Hz}^{-1}]$', size=20)\n",
        "ax1.set_ylabel('$\\log{}\\mathrm{\\phi}\\, [\\mathrm{Mpc}^{-3}\\mathrm{dex}^{-1}]$', size=20)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "plt.setp(ax1.spines.values(), linewidth=3.5)\n",
        "ax1.legend(loc=1, fontsize=20, title='1.0 < z < 1.3', title_fontsize=16)\n",
        "#ax1.set_aspect('equal', 'box')\n",
        "fig.tight_layout()"
      ],
      "execution_count": 120,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "divide by zero encountered in log10\n",
            "invalid value encountered in subtract\n",
            "divide by zero encountered in log10\n",
            "divide by zero encountered in log10\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 936x504 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
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    {
      "cell_type": "code",
      "metadata": {
        "id": "rSLtK7F5Hk93"
      },
      "source": [
        ""
      ],
      "execution_count": 112,
      "outputs": []
    }
  ]
}