mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-12-23 02:38:02 +00:00
589 lines
821 KiB
Text
589 lines
821 KiB
Text
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"The autoreload extension is already loaded. To reload it, use:\n",
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" %reload_ext autoreload\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import scienceplots\n",
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"import seaborn as sns\n",
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"from h5py import File\n",
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"\n",
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"\n",
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"from reconstruction_comparison import *\n",
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"SPEED_OF_LIGHT = 299_792.458\n",
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"from csiborgtools import radec_to_galactic\n",
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"\n",
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"%load_ext autoreload\n",
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"%autoreload 2\n",
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Paper plots"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 27,
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"metadata": {},
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"outputs": [],
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"source": [
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"with File(\"/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5\", 'r') as f:\n",
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" SFI = {}\n",
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" for key in f[\"SFI_gals\"].keys():\n",
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" SFI[key] = f[\"SFI_gals\"][key][...]\n",
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" \n",
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" TWOMTF = {}\n",
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" for key in f[\"2MTF\"].keys():\n",
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" TWOMTF[key] = f[\"2MTF\"][key][...]\n",
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" \n",
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" FOUNDATION = {}\n",
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" for key in f[\"Foundation\"].keys():\n",
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" FOUNDATION[key] = f[\"Foundation\"][key][...]\n",
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" \n",
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" LOSS = {}\n",
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" for key in f[\"LOSS\"].keys():\n",
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" LOSS[key] = f[\"LOSS\"][key][...]\n",
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"\n",
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"\n",
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"\n",
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"with File(\"/mnt/extraspace/rstiskalek/catalogs/PV/CF4/CF4_TF-distances.hdf5\", 'r') as f:\n",
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" CF4_TFR = {}\n",
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" for key in f.keys():\n",
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" CF4_TFR[key] = f[key][...]\n",
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" \n",
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" RA = f[\"RA\"][...] * 360 / 24\n",
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" CF4_TFR[\"RA\"] = RA\n",
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" \n",
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" CF4_TFR[\"DEC\"] = f[\"DE\"][...]\n",
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"\n",
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" l, b = radec_to_galactic(CF4_TFR[\"RA\"], CF4_TFR[\"DE\"])\n",
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" m = np.abs(b) > 7.5\n",
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" for key in CF4_TFR.keys():\n",
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" CF4_TFR[key] = CF4_TFR[key][m]"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 1. Redshift distribution"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 28,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 350x262.5 with 1 Axes>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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}
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],
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"source": [
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"with plt.style.context('science'):\n",
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" plt.rcParams.update({'font.size': 9})\n",
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" plt.figure()\n",
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"\n",
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" sns.kdeplot(LOSS[\"z_CMB\"], label=\"LOSS\", fill=True, bw_adjust=0.75)\n",
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" sns.kdeplot(FOUNDATION[\"z_CMB\"], label=\"Foundation\", fill=True, bw_adjust=0.75)\n",
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" sns.kdeplot(SFI[\"z_CMB\"], label=\"SFI\", fill=True, bw_adjust=0.75)\n",
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" sns.kdeplot(TWOMTF[\"z_CMB\"], label=\"2MTF\", fill=True, bw_adjust=0.75)\n",
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"\n",
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" m = CF4_TFR[\"i\"] > 5\n",
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" sns.kdeplot(CF4_TFR[\"Vcmb\"][m] / SPEED_OF_LIGHT, label=catalogue_to_pretty(\"CF4_TFR_i\"), fill=True)\n",
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"\n",
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" m = CF4_TFR[\"w1\"] > 5\n",
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" sns.kdeplot(CF4_TFR[\"Vcmb\"][m] / SPEED_OF_LIGHT, label=catalogue_to_pretty(\"CF4_TFR_w1\"), fill=True)\n",
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"\n",
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" plt.xlabel(r\"$z_{\\rm CMB}$\")\n",
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" plt.ylabel(\"Normalised PDF\")\n",
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"\n",
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" plt.legend()\n",
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" plt.xlim(0, 0.07)\n",
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"\n",
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" plt.tight_layout()\n",
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" plt.savefig(f\"../../plots/zcmb_dist.pdf\", dpi=450)\n",
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" plt.show()"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"### 2. Sky distribution"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/png": "iVBORw0KGgoAAAANSUhEUgAAAzcAAAFFCAYAAADRpBM5AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjguMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/H5lhTAAAACXBIWXMAAA9hAAAPYQGoP6dpAAEAAElEQVR4nOydeVhUR9b/v92gccENRCBoDAKCSxIFFRWN4BoTJc6MGs1IzJsxmXeS+c1ETVySWTIZFTUqycybTNRMEgOKUZxxyyK74hoEQdlXlV2CoqAodHf9/mjrevv27e7bewP1eZ48ke6+t+rWcu45dU6dkhFCCBgMBoPBYDAYDAajgyO3dwUYDAaDwWAwGAwGwxIw44bBYDAYDAaDwWB0Cphxw2AwGAwGg8FgMDoFzLhhMBgMBoPBYDAYnQJm3DAYDAaDwWAwGIxOATNuGAwGg8FgMBgMRqeAGTcMBoPBYDAYDAajU8CMGwaDwWAwGAwGg9EpYMYNg8FgMBgMBoPB6BQ427sC1sbNzQ3dunWDt7c3vL29JV1TXV0t+bfmXNNZy3L0+nXWshy9fsZeV11djerqarS3t6OxsdHosvgwOWD7shy9fp21LEevn7HXMTnAyrLmNZ21LEevn7HXGS0HSCfHw8PD6Gvmz59vk2s6a1mOXr/OWpaj18/U60yZw5a4h6O3i6OX5ej166xlOXr9TL2OyQFWljWu6axlOXr9TL1O6hxmYWkiLF261CbX2LosU2BtYX5ZtnquztoWpqwIWQI29s0ri7WF+dextngEkwOWLcsUHP25WFuYd42pOKQcMNps6mBYYrWns2Cqdd0ZYW3xCEdvC0vUj8mBRzh6f9uS+fPnk3aFkqTl1ZF2hdLe1bErjj4umBzQxpyxK2zPrjwPHH3s2xJHbwup9ev0nht7rfY4Ira05B0d1haP6AptweTAI7pCf0tl6dKlOFPUgHmbk3GmqMHe1bErXWFcdDY5YM7YFfZ3V54HXWHsS8WWbaFQqnAyvx4Kpcri95YRQojF7+pARERE4OjRo/auBoPBMBFLzGEmBxi6UChVOFPUgNAAdzg7dfr1vg4LkwPaSB27Un7H5gHD1pzMr8e8zck4vm4Gpo30kHSN1DnMRjCDwWAwuizOTnJMG+nBFDpGh0Pq2NXnlaGr5wC4e1lzRZ3BoIQGuOP4uhkIDXC3+L07vTSvrq5GREQE4uLi7F0VBoNhBHFxcYiIiEB1dbXZ92JygMHomDA5YBp8A0WfEilm+HTlEDWG7TBmYclYOcDC0hgMhkPDwlEYDAaTA4bhh5ZRA8VQyI9YOBoLUWM4KiwsjcFgMBgMBqOLwPe4SA35EVs9NzVUk4WzMRwFZtwwGAwGg8FgdHD4Bo019pIZMl5MDWdjRhHD0jDjhsFgMBgmwZQSBsO6GDPHzDFopJRjyHgReouk1p3t8ela2OK9wYwbBoPBYJgEU0oYDOtyurAeb3/9E04X1mt8bmkFkc7l04X1Ou9rKNRNaFxJlQ/WzJrVmTDU58aMCXsuTNnivcGMGwaDwWCYhDWVEuYVYjAAQoDSumYIUz9ZWkGkc5kQ6LyvsZ4hc/b9MLQx1OfGjAl7LkzZwpjt9NnSgoOD4e3tjaVLl7JTaBmMDkRcXBzi4uJQXV2NzMxMs+7F5EDHw5QD3hidj64uB3RlLrNWRjNLHgzKsCz8NgdgVpa7jtZ/xsqBTm/cdPbUjwxGZ4elgO2adLSXL8O6MDlgfaSkhaZ/q1QqRGxNZYsPOrC2/Oqqiz8sFTSDwWAwOiwsVIXBsB5iYZ9ioUrCPT/0NzIZ2D4ZPVg77IvtU9IPe2swGAwGo8PD9ugwuhqmjnmFUoWv08q0lO8QPzdELx+PED837t5KJdHY80OV6imBHmzxQQ/WNj7Y4o9+WKswGAwGo8PTWTK3MSONIRVTx/yZogas35eF6OXjNZTvC6WNWLknAxdKG7l7OznJcHzdDEwdoQ59Ykq1NFg72RfW6gwGg8Ho8HSWMI3OYqQxrI+UMS9mLIcGuCN+dRheDfPVUL759+N7aEID3HGmqIEZ3FaELWpYFmbcMBgMBqPD01lWSjuLkcawPobGvK7wM13X8T/n//tMUQMWbk/D12llosq3PRXzzmIUSF3UEHveztIGlqRjvwUkUF1djYiICMTFxdm7KgyJsInKANSpHyMiIlBdXW32vZgcYHQUOouRZimYHDAdYfiZse9W+vsQPzdEvRyElXsyRJVve3obO7qnk9/GUhY1xJ63o7eBFIyWA6STM3/+fHtXgWEkaXl1xCVyL0nLq7N3VRgOgCXmMJMDDEbHhskB42lXKElaXh1pVygJIdLerfxr+L+nf7c+aNe4p1g5huph7nNI+c7cMm2FsfqO2HNZ4lk7SntJncNsaYjhcLCwDAaDwWAwzIN6AQFI9g7wvQD8dzG914XSRslhbmL3NCUyQ+iZ4N9DV9n29mZIfU5j9R3+89IyAJjt7bV3e1kahzZusrKyUF5ejqamJiQlJaGpqQkAkJSUhF27diE+Ph5bt261byUZFoeFZTAYDAaDYRmo4nqhtNHguzU0wB3H1oZDqVQgvaBe6xBKUxYf+deYokQLy5RyD3svkkp9TnP0HVMNEl1JJjrTorJDa49RUVHw9fWFj48PsrKy0L9/fwDAli1b8MYbb2DhwoUAgPj4eDvWksFgMBgMBsMxMUZxdXaSQyaTY3VMFiK2pmopzsYo42KeBVOUaHod9fxIuYe9F0ltYSyYWoaYUWTv9rI0Dv0Us2bNAiEEt27dwpo1awCovTbUyAGAoKAgfPvtt3aqIYPBYDA6IixxCaOrYKziGhrgjujl43B0TbgkxVnXXLKkEs2/l6n3sOacF97bXsaClGfsbF4aMRzauAGA8vJyZGVlcX9nZWXB1dWV+9vV1VXjewaDwWAwDGHpGHNmLDE6C85OcoSN8kL4aC9JyrmuuWRJJdoS97LmvhJb7lmhsia9oN6kzGmdzUsjhsM/WVNTE4YNG4ZFixahqakJjY2N9q5Sp4G9jBkMRlfF0quXnW1DLqPzoe+db875KWJzSaFUcUkJLKFEG6uQ329T4IvkEtxvU+itp6WwpTeEyhqZDFplmnqwq6ND60wIkfR7hzZu3njjDQQFBaF///6YNWsW1q5dCzc3N6PuQfPa0/+6Sn57KbCXMcMRofns6X+WPN+CyYGOiTVexpZevewKoR62xF5yQEwp7izoe+ebc36K2FwSu1bqPLbE72LTK7ByTwZi0yv01tPUsoXY0htCZc2UQA+tMqXUoyPpflQOTJs5FzPmPI+ismvSLrRqQmozSExMJDNnzuT+3rlzJ1m4cCFJTEwkCxcu1Pgd/28hXS2vvTF0lLzmjK5NRzzfgs0ty+LIZ19J6Ws2HszHVnJgd1IxcYncS3YnFZtdHiGO1ffGnhdjTt3FrtU3j3Wdr6MPfb9rfdBOdicVk9YH7UbV25FljaVwpDEpFVrnefPmSfq9w3puhg0bht/+9rfc35mZmXjppZcwc+ZMlJeXc59nZWXhpZdeskcVOzxdIe6SwbAHHWllzFJYM9TBkb0iUvq6K46HjsqyqT6IXj4ey6b6cJ+ZM7Ydqe/1vfPFvjNHRxC7Vt88pu10urAehKgkJTPQd78e3Z3xapgvLpQ2GtVv5sgaS8lAS3u4hHRE3Y/WWSaTSfq9wz7ZsGHDAAC7du3Crl274Ovry6V+3rJlC7Zu3cqlgKafMxgMhj2hLxsph+V1NqypxDnyy1iKMmRp46wjxsx3FHp0d8aKGf7o0d2Z+8ycse3Ihrmt0TePaTsRAszfkgq5XG5wvhtzeKgl6igGfy5aSgZKvY8jGc4Oh5U9SXaHhaUx7E1HdAE7Eh0hLI32ccqVmk4f0qALNs7V2KIdukLojBBLygFDfdSuUJLU3BqScqWGtCuUksK5Wh+0d6rxb6/5bMlybT0XLVWe1PuYEkrY0eW0VDngeMtgDIeHrRoahzkbK62JI9Shs6Ave01XQd+KZ1caa7ZYTWXeAPMw1Ednihqwcs9FLI4+ha/TygBA59im94pNr+DuaU7mMVuir072em9Z0kt
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 830x332 with 6 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"with plt.style.context('science'):\n",
|
||
|
|
" plt.rcParams.update({'font.size': 9})\n",
|
||
|
|
" figwidth = 8.3\n",
|
||
|
|
" fig, axs = plt.subplots(2, 3, figsize=(figwidth, 0.4 * figwidth),\n",
|
||
|
|
" sharex=True, sharey=True)\n",
|
||
|
|
"\n",
|
||
|
|
"\n",
|
||
|
|
" names = [\"LOSS\", \"Foundation\", \"SFI\", \"2MTF\", \"CF4_TFR_i\", \"CF4_TFR_w1\"]\n",
|
||
|
|
" vals = [LOSS, FOUNDATION, SFI, TWOMTF, CF4_TFR, CF4_TFR]\n",
|
||
|
|
" for i, ax in enumerate(axs.flat):\n",
|
||
|
|
" RA = vals[i][\"RA\"]\n",
|
||
|
|
" DEC = vals[i][\"DEC\"]\n",
|
||
|
|
"\n",
|
||
|
|
" if names[i] == \"CF4_TFR_i\":\n",
|
||
|
|
" m = vals[i][\"i\"] > 5\n",
|
||
|
|
" RA = RA[m]\n",
|
||
|
|
" DEC = DEC[m]\n",
|
||
|
|
"\n",
|
||
|
|
" if names[i] == \"CF4_TFR_w1\":\n",
|
||
|
|
" m = vals[i][\"w1\"] > 5\n",
|
||
|
|
" RA = RA[m]\n",
|
||
|
|
" DEC = DEC[m]\n",
|
||
|
|
"\n",
|
||
|
|
" sns.scatterplot(x=RA, y=DEC, ax=ax, s=1.5, rasterized=True)\n",
|
||
|
|
"\n",
|
||
|
|
" # Add panel name in top-left corner of each subplot\n",
|
||
|
|
" ax.text(0.04, 0.16, catalogue_to_pretty(names[i]), transform=ax.transAxes, \n",
|
||
|
|
" fontsize=9, verticalalignment='top', \n",
|
||
|
|
" bbox=dict(boxstyle=\"round\", facecolor='lightgray', alpha=1),\n",
|
||
|
|
" zorder=10) # Ensure text is on top of other plot elements\n",
|
||
|
|
"\n",
|
||
|
|
" axs[0, 0].set_xlim(0, 360)\n",
|
||
|
|
" axs[0, 0].set_ylim(-90, 90)\n",
|
||
|
|
"\n",
|
||
|
|
" for i in range(3):\n",
|
||
|
|
" axs[-1, i].set_xlabel(r\"$\\mathrm{RA} ~ [\\mathrm{deg}]$\")\n",
|
||
|
|
"\n",
|
||
|
|
" for i in range(2):\n",
|
||
|
|
" axs[i, 0].set_ylabel(r\"$\\delta ~ [\\mathrm{deg]}$\")\n",
|
||
|
|
"\n",
|
||
|
|
" fig.tight_layout()\n",
|
||
|
|
" plt.savefig(f\"../../plots/sky_dist.pdf\", dpi=350)\n",
|
||
|
|
" fig.show()\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "markdown",
|
||
|
|
"metadata": {},
|
||
|
|
"source": [
|
||
|
|
"## Experimenting"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 21,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"l, b = radec_to_galactic(CF4_TFR[\"RA\"], CF4_TFR[\"DE\"])\n",
|
||
|
|
"# l, b = radec_to_galactic(SFI[\"RA\"], SFI[\"DEC\"])"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"0.06692355049302931"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 22,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"np.abs(b).min()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"text/plain": [
|
||
|
|
"232"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"execution_count": 26,
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "execute_result"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"(np.abs(b) < 10).sum()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 23,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure()\n",
|
||
|
|
"plt.hist(np.abs(b), bins=\"auto\")\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 17,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"name": "stdout",
|
||
|
|
"output_type": "stream",
|
||
|
|
"text": [
|
||
|
|
"<KeysViewHDF5 ['DEC', 'RA', 'e_eta', 'e_mag', 'eta', 'mag', 'z_CMB']>\n"
|
||
|
|
]
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"with File(\"/mnt/extraspace/rstiskalek/catalogs/PV_compilation.hdf5\", 'r') as f:\n",
|
||
|
|
" print(f[\"SFI_gals\"].keys())\n",
|
||
|
|
"\n",
|
||
|
|
" zCMB_sfi = f[\"SFI_gals\"][\"z_CMB\"][...]\n",
|
||
|
|
" mag_sfi = f[\"SFI_gals\"][\"mag\"][...]\n",
|
||
|
|
" eta_sfi = f[\"SFI_gals\"][\"eta\"][...]\n",
|
||
|
|
" e_mag_sfi = f[\"SFI_gals\"][\"e_mag\"][...]\n",
|
||
|
|
" e_eta_sfi = f[\"SFI_gals\"][\"e_eta\"][...]\n",
|
||
|
|
"\n",
|
||
|
|
" zCMB_2MTF = f[\"2MTF\"][\"z_CMB\"][...]\n",
|
||
|
|
" mag_2MTF = f[\"2MTF\"][\"mag\"][...]\n",
|
||
|
|
" eta_2MTF = f[\"2MTF\"][\"eta\"][...]\n",
|
||
|
|
" e_mag_2MTF = f[\"2MTF\"][\"e_mag\"][...]\n",
|
||
|
|
" e_eta_2MTF = f[\"2MTF\"][\"e_eta\"][...]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 28,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"with File(\"/mnt/extraspace/rstiskalek/catalogs/PV/CF4/CF4_TF-distances.hdf5\", 'r') as f:\n",
|
||
|
|
" zCMB = f[\"Vcmb\"][...] / 3e5\n",
|
||
|
|
" rband = f[\"r\"][...]\n",
|
||
|
|
" iband = f[\"i\"][...]\n",
|
||
|
|
" w1band = f[\"w1\"][...]\n",
|
||
|
|
" RA = f[\"RA\"][...] * 360 / 24\n",
|
||
|
|
" dec = f[\"DE\"][...]\n",
|
||
|
|
"\n",
|
||
|
|
"# m = (iband > 5) #& (w1band > 5)\n",
|
||
|
|
"m = (w1band> 5) #& (w1band > 5)\n",
|
||
|
|
"w1band = w1band[m]\n",
|
||
|
|
"iband = iband[m]\n",
|
||
|
|
"RA = RA[m]\n",
|
||
|
|
"dec = dec[m]"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 29,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": [
|
||
|
|
"dmag = iband - w1band"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 30,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 2 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure()\n",
|
||
|
|
"plt.scatter(RA, dec, c=dmag, s=1)\n",
|
||
|
|
"plt.colorbar()\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 11,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure()\n",
|
||
|
|
"plt.hist(iband - w1band, bins=\"auto\")\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 69,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"m = rband > 0\n",
|
||
|
|
"\n",
|
||
|
|
"plt.figure()\n",
|
||
|
|
"plt.hist(rband[m], bins=\"auto\")\n",
|
||
|
|
"plt.axvline(17.6, c=\"red\")\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 64,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 640x480 with 1 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"plt.figure()\n",
|
||
|
|
"plt.hist(zCMB, bins=\"auto\")\n",
|
||
|
|
"plt.xlabel(r\"$z_{\\rm CMB}$\")\n",
|
||
|
|
"plt.ylabel(\"Counts\")\n",
|
||
|
|
"plt.xlim(0)\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.savefig(\"../../plots/zCMB_CF4.png\")\n",
|
||
|
|
"plt.show()"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": 53,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [
|
||
|
|
{
|
||
|
|
"data": {
|
||
|
|
"image/png": "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
|
||
|
|
"text/plain": [
|
||
|
|
"<Figure size 1337.25x1250 with 20 Axes>"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
"metadata": {},
|
||
|
|
"output_type": "display_data"
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"source": [
|
||
|
|
"import seaborn as sns\n",
|
||
|
|
"import pandas as pd\n",
|
||
|
|
"import matplotlib.pyplot as plt\n",
|
||
|
|
"\n",
|
||
|
|
"df_sfi = pd.DataFrame({\n",
|
||
|
|
" r\"$z_{\\rm CMB}$\": zCMB_sfi,\n",
|
||
|
|
" r\"$m$\": mag_sfi,\n",
|
||
|
|
" r\"$\\eta$\": eta_sfi,\n",
|
||
|
|
" r\"$\\sigma_{m}$\": e_mag_sfi,\n",
|
||
|
|
" r\"$\\sigma_\\eta$\": e_eta_sfi,\n",
|
||
|
|
" \"Dataset\": \"SFI\"\n",
|
||
|
|
"})\n",
|
||
|
|
"\n",
|
||
|
|
"df_2mtf = pd.DataFrame({\n",
|
||
|
|
" r\"$z_{\\rm CMB}$\": zCMB_2MTF,\n",
|
||
|
|
" r\"$m$\": mag_2MTF,\n",
|
||
|
|
" r\"$\\eta$\": eta_2MTF,\n",
|
||
|
|
" r\"$\\sigma_{m}$\": e_mag_2MTF,\n",
|
||
|
|
" r\"$\\sigma_\\eta$\": e_eta_2MTF,\n",
|
||
|
|
" \"Dataset\": \"2MTF\"\n",
|
||
|
|
"})\n",
|
||
|
|
"\n",
|
||
|
|
"df_combined = pd.concat([df_sfi, df_2mtf])\n",
|
||
|
|
"g = sns.pairplot(df_combined, hue=\"Dataset\", kind=\"kde\", diag_kind=\"kde\",\n",
|
||
|
|
" palette=\"Set1\", corner=True, plot_kws={\"alpha\": 0.75},\n",
|
||
|
|
" diag_kws={\"fill\": True})\n",
|
||
|
|
"sns.move_legend(g, \"upper right\", bbox_to_anchor=(0.7, 0.7))\n",
|
||
|
|
"\n",
|
||
|
|
"# Show the plot\n",
|
||
|
|
"plt.tight_layout()\n",
|
||
|
|
"plt.savefig(\"../../plots/TFR_data.pdf\", dpi=450)\n",
|
||
|
|
"plt.show()\n"
|
||
|
|
]
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"cell_type": "code",
|
||
|
|
"execution_count": null,
|
||
|
|
"metadata": {},
|
||
|
|
"outputs": [],
|
||
|
|
"source": []
|
||
|
|
}
|
||
|
|
],
|
||
|
|
"metadata": {
|
||
|
|
"kernelspec": {
|
||
|
|
"display_name": "venv_csiborg",
|
||
|
|
"language": "python",
|
||
|
|
"name": "python3"
|
||
|
|
},
|
||
|
|
"language_info": {
|
||
|
|
"codemirror_mode": {
|
||
|
|
"name": "ipython",
|
||
|
|
"version": 3
|
||
|
|
},
|
||
|
|
"file_extension": ".py",
|
||
|
|
"mimetype": "text/x-python",
|
||
|
|
"name": "python",
|
||
|
|
"nbconvert_exporter": "python",
|
||
|
|
"pygments_lexer": "ipython3",
|
||
|
|
"version": "3.11.4"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|