You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The SKA Science Data Challenge 1 (SDC1, https://astronomers.skatelescope.org/ska-science-data-challenge-1/) tasked participants with identifying and classifying sources in synthetic radio images.
7
6
8
-
Here we present a tutorial for producing a solution to this challenge that can easily be developed further.
7
+
Here we present a tutorial to this challenge that can easily be developed further. The aim of the tutorial is as follows:
8
+
- Source finding (RA, Dec) to locate the centroids and/or core positions,
9
+
- Source property characterization (integrated flux density, possible core fraction, major and minor axis size, major axis position angle)
10
+
- Source classification (one of SFG, AGN-steep, AGN-flat)
A small subsample of each image can be downloaded using the script `binder/download_sample_data.sh`, to excute the script run the following:
15
22
16
23
```bash
@@ -24,4 +31,27 @@ Then make sure you have the right Python libraries for the tutorials. They can a
24
31
```
25
32
26
33
27
-
After downloading the sample data you can start with the tutorials.
34
+
-----
35
+
36
+
### New to Github?
37
+
38
+
The easiest way to get all of the lecture and tutorial material is to clone this repository. To do this you need git installed on your laptop. If you're working on Linux you can install git using apt-get (you might need to use sudo):
0 commit comments