{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Viewing and manipulating FITS images\n",
"\n",
"## Authors\n",
"Lia Corrales, Kris Stern, Stephanie T. Douglas, Kelle Cruz\n",
"\n",
"## Learning Goals\n",
"* Open FITS files and load image data\n",
"2. Make a 2D histogram with image data\n",
"3. Stack several images into a single image\n",
"4. Write image data to a FITS file\n",
"\n",
"## Keywords\n",
"FITS, file input/output, image manipulation, numpy, matplotlib, histogram, colorbar\n",
"\n",
"## Summary\n",
"\n",
"This tutorial demonstrates the use of `astropy.utils.data` to download a data file, then uses `astropy.io.fits` to open the file, and lastly uses `matplotlib` to view the image with different color scales and stretches and to make histograms. In this tutorial we've also included a demonstration of simple image stacking."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"# Set up matplotlib\n",
"import matplotlib.pyplot as plt\n",
"%matplotlib inline\n",
"\n",
"from astropy.io import fits"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Download the example FITS files for this tutorial."
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"from astropy.utils.data import download_file\n",
"# image_file = download_file('http://data.astropy.org/tutorials/FITS-images/HorseHead.fits', cache=True )\n",
"image_file = download_file('https://macroconsortium.org/images/knox/knh/2024/019/knh0191dc.fts', cache=True )"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Opening FITS files and loading the image data"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Let's open the FITS file to find out what it contains."
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Filename: /Users/research/.astropy/cache/download/url/01d9ff931a2c757b32d4be3b6335564c/contents\n",
"No. Name Ver Type Cards Dimensions Format\n",
" 0 PRIMARY 1 PrimaryHDU 158 (4096, 4096) int16 (rescales to uint16) \n"
]
}
],
"source": [
"hdu_list = fits.open(image_file)\n",
"hdu_list.info()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Generally, the image information is located in the PRIMARY
block. The blocks are numbered and can be accessed by indexing hdu_list
."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"image_data = hdu_list[0].data\n",
"image_header = hdu_list[0].header"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Our data is now stored as a 2D numpy array. But how do we know the dimensions of the image? We can look at the `shape` of the array."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"(4096, 4096)\n"
]
}
],
"source": [
"print(type(image_data))\n",
"print(image_data.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Great! At this point, we can close the FITS file because we've stored everything we wanted to a variable."
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {},
"outputs": [],
"source": [
"hdu_list.close()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### SHORTCUT"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"If you don't need to examine the FITS header, you can call `fits.getdata` to bypass the previous steps."
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"(4096, 4096)\n"
]
}
],
"source": [
"image_data = fits.getdata(image_file)\n",
"print(type(image_data))\n",
"print(image_data.shape)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Viewing the image data and getting basic statistics"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
""
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
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",
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