|
28 | 28 | "\n",
|
29 | 29 | "This tutorial will walk you though a simple visual analysis of the Small Magellanic Cloud (SMC) using HI 21cm emission and a Herschel 250 micron map. We will learn how to read in data from vizier, query and download matching data from Herschel using astroquery, and plot the resulting images in a multitude of ways. \n",
|
30 | 30 | "\n",
|
31 |
| - "The primary libraries we will be using are: [astroquery](http://www.astropy.org/astroquery/), [spectral_cube](https://spectral-cube.readthedocs.io/en/latest/), [reproject](https://reproject.readthedocs.io/en/stable/#), [matplotlib](https://matplotlib.org/), and [aplpy](https://aplpy.github.io/)) They can be installed using conda and pip:\n", |
| 31 | + "The primary libraries we will be using are: [astroquery](http://www.astropy.org/astroquery/), [spectral_cube](https://spectral-cube.readthedocs.io/en/latest/), [reproject](https://reproject.readthedocs.io/en/stable/#), [matplotlib](https://matplotlib.org/), and [aplpy](https://aplpy.github.io/)) \n", |
| 32 | + "\n", |
| 33 | + "They can be installed using conda:\n", |
32 | 34 | "- `conda install -c astropy astroquery`\n",
|
33 |
| - "- `conda install spectral-cube`\n", |
34 |
| - "- `conda install reproject`\n", |
35 |
| - "- `conda install aplpy`" |
| 35 | + "- `conda install -c astropy spectral-cube`\n", |
| 36 | + "- `conda install -c astropy reproject`\n", |
| 37 | + "- `conda install -c astropy aplpy`\n", |
| 38 | + "\n", |
| 39 | + "Alternatively, if you don't use conda, you can use pip." |
36 | 40 | ]
|
37 | 41 | },
|
38 | 42 | {
|
|
888 | 892 | "ax.set_ylim(y_lim)"
|
889 | 893 | ]
|
890 | 894 | },
|
891 |
| - { |
892 |
| - "cell_type": "markdown", |
893 |
| - "metadata": {}, |
894 |
| - "source": [ |
895 |
| - "## Add some TRY and CHALLENGE items here to wrap things up" |
896 |
| - ] |
897 |
| - }, |
898 | 895 | {
|
899 | 896 | "cell_type": "markdown",
|
900 | 897 | "metadata": {
|
|
904 | 901 | "The real power of reproject is in actually changing the map projection used to display the data. This is done by creating a WCS object that contains a different projection type such as `CTYPE : 'RA---CAR' 'DEC--CAR'` as opposed to `CTYPE : 'RA---TAN' 'DEC--TAN'`. \n",
|
905 | 902 | "\n",
|
906 | 903 | "## Challenge:\n",
|
907 |
| - "### Use [reproject](https://reproject.readthedocs.io/en/stable/#) and WCS to create a new WCS object in a different map projection and see distortions in the image can change. " |
| 904 | + "\n", |
| 905 | + "Use [reproject](https://reproject.readthedocs.io/en/stable/#) and WCS to create a new WCS object in a different map projection and see distortions in the image can change. " |
908 | 906 | ]
|
909 | 907 | },
|
910 | 908 | {
|
|
937 | 935 | ],
|
938 | 936 | "metadata": {
|
939 | 937 | "kernelspec": {
|
940 |
| - "display_name": "Python [default]", |
| 938 | + "display_name": "Python 2", |
941 | 939 | "language": "python",
|
942 |
| - "name": "python3" |
| 940 | + "name": "python2" |
943 | 941 | },
|
944 | 942 | "language_info": {
|
945 | 943 | "codemirror_mode": {
|
946 | 944 | "name": "ipython",
|
947 |
| - "version": 3 |
| 945 | + "version": 2 |
948 | 946 | },
|
949 | 947 | "file_extension": ".py",
|
950 | 948 | "mimetype": "text/x-python",
|
951 | 949 | "name": "python",
|
952 | 950 | "nbconvert_exporter": "python",
|
953 |
| - "pygments_lexer": "ipython3", |
954 |
| - "version": "3.6.2" |
| 951 | + "pygments_lexer": "ipython2", |
| 952 | + "version": "2.7.13" |
955 | 953 | }
|
956 | 954 | },
|
957 | 955 | "nbformat": 4,
|
|
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