Notebooks auxiliar

Auxiliar/GenerarMascaras.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b6649867",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from astropy.io import fits\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import glob\n",
+    "import cv2\n",
+    "from PIL import Image\n",
+    "import copy\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ed76de12",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ruta_fits = \"RUTA_INPUT_FITS/\"\n",
+    "ruta_guardar_mascaras_2_clases=\"RUTA_OUTPUT_MASCARAS/\"\n",
+    "tam_fotos_x=512\n",
+    "tam_fotos_y=512"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4ee87765",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if not os.path.exists(ruta_guardar_mascaras_2_clases):\n",
+    "    os.makedirs(ruta_guardar_mascaras_2_clases)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "187a3d92",
+   "metadata": {},
+   "source": [
+    "## Creamos máscaras de segmentación con 2 clases y de 3 clases"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "62e367b8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def get_numero_galaxia(nombre_galaxia:str):\n",
+    "    numero_galaxia = nombre_galaxia.split('.')[0].split('_')[-1]\n",
+    "    return numero_galaxia"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "25dc0528",
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [],
+   "source": [
+    "#Leemos las galaxy convolved y las stream convolved\n",
+    "rutas_stream_convolved = glob.glob(ruta_fits+\"stream_pix_above_surf_bright_limit_*.fits\")\n",
+    "\n",
+    "for ruta_stream in rutas_stream_convolved:\n",
+    "    print(ruta_stream)\n",
+    "    numero_galaxia = get_numero_galaxia(ruta_stream)\n",
+    "    print(numero_galaxia)\n",
+    "    \n",
+    "    #Hacemos el mismo proceso para la imagen de la cola de marea\n",
+    "    stream_fits = fits.open(ruta_stream)\n",
+    "    array_imagen_stream_fits = stream_fits[1].data\n",
+    "    mascara_cola = np.zeros((tam_fotos_x,tam_fotos_y))\n",
+    "    mascara_cola[array_imagen_stream_fits!=0] = 1\n",
+    "    #Combinamos las mascaras \n",
+    "    \n",
+    "    #Guardamos la mascara de la cola\n",
+    "    cv2.imwrite(ruta_guardar_mascaras_2_clases+\"mascara_\"+str(numero_galaxia)+\".png\",mascara_cola)\n",
+    "    #Mostramos la mascara\n",
+    "    plt.imshow(mascara_cola,interpolation='none', origin=\"lower\")\n",
+    "    plt.show()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

Auxiliar/inserting_tidal_tails.py

+import glob
+from astropy.io import fits
+import numpy as np
+import pandas as pd
+import montage_wrapper as montage
+import os.path
+import pdb
+
+
+input_folder = "./INPUT_FOLDER/"
+output_folder = "./OUTPUT_FOLDER/"
+vis_path = "./"
+vis_image = "EUC_VIS_SWL-STK-000-000000-0000000__20210613T225647.742318Z.fits"
+
+
+#I open the VIS image
+hdu = fits.open(vis_path+vis_image)
+img = hdu[1].data
+hdr = hdu[1].header
+dim1 = hdr["NAXIS1"]
+dim2 = hdr["NAXIS2"]
+
+if not os.path.exists(output_folder):
+    os.mkdir(output_folder)
+
+#these are the only files I will accept as inputs
+filename_sims =  glob.glob(input_folder+"galaxy_and_stream_convolved_[!w]*.fits") #in the termina use ^ instead of !
+
+for filename_sim in filename_sims:
+    print(filename_sim)
+    #I open each of the simulated galaxies
+    hdu_sim = fits.open(filename_sim)
+    img_sim = hdu_sim[1].data
+    hdr_sim = hdu_sim[1].header
+    dim1_sim = hdr_sim["NAXIS1"]
+    dim2_sim = hdr_sim["NAXIS2"]
+    
+    flag_cutted = False
+    while flag_cutted == False:
+        #I obtain the new random centroid within the VIS image
+        x_center = np.random.randint(0, dim1)
+        y_center = np.random.randint(0, dim2)
+        
+        #I will take a cutout in the new centroid position with the dimensions of the simulated galaxy
+        pix_in_x_halfsize = int(dim1_sim/2)
+        pix_in_y_halfsize = int(dim2_sim/2)
+        cutout = img[y_center-pix_in_y_halfsize:y_center+pix_in_y_halfsize, x_center-pix_in_x_halfsize:x_center+pix_in_x_halfsize]
+        
+        #I will accept this new image if less than 10% of the pixels are zeros and the dimensions are all right
+        if np.count_nonzero(cutout == 0) >= (dim1_sim*dim2_sim)/10 or cutout.shape[0] != dim1_sim or cutout.shape[1] != dim2_sim:
+            flag_cutted = False
+        else:
+            flag_cutted = True
+            
+    #I create the cutout itself
+    new_filename = output_folder+filename_sim[len(input_folder):-5]+"_in_"+vis_image[:-5]+".fits"
+    montage.mSubimage_pix(vis_path+vis_image,new_filename, x_center-pix_in_x_halfsize, y_center-pix_in_y_halfsize, hdu = 1, xpixsize = (pix_in_x_halfsize*2)-1, ypixsize = (pix_in_y_halfsize*2)-1 )
+    hdu_cutout = fits.open(new_filename)
+    img_cutout = hdu_cutout[0].data
+    hdr_cutout = hdu_cutout[0].header
+    fits.writeto(new_filename,img_cutout+img_sim,hdr_cutout,overwrite=True)
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