This is a tutorial for the web app found here.
When you first load the app, there is an empty plot with several components enumerated below.
Load Button: You can load a new DLPS by clicking the green
Load DLPS button. Press this button again after you change any of the settings described below.
Chart Type: There are 4 DLPS types:
Linear 90 and
Log 90. Log and Linear refer to logarithmic or linear time scales on the x-axis. 68 and 90 refer to the percentile regions shown for each transient class.
Log 68 will show a DLPS where the x-axis is log (Duration), and each region contains roughly 68% of the class models generated in Villar et al. (in prep). If no option is selected, the DLPS will automatically be the logarithmic 68th percentiles regions.
Note: The Novae, GRB and Ia classes do not toggle between 68th and 90th percentiles. Each highlighted region for these classes reflects the full parameter range.
Class Toggles: The colored sliders let you turn classes on/off. Click the slider to turn a transient class off, and the slider will change to grey. Every transient class is visible by default.
Note: By unchecking the boxes on the right, you can remove transients from both the plot and the legend. However, you can also keep transient classes on the legend but remove them from the plot by clicking their names on the legend, as shown below.
Data Input: Add your own transients to the plot by typing the coordinates in the textbox. Enter each object on a new line as a set of coordinates: (duration, magnitude, color). The color of the plotted datapoint is optional and must be one of these 140 named colors. If no color is specified, the object will be plotted in black.
For example, a sample input list can be:
30,-19.2,red 100 -15 blue 200 -18
Other Options: You can move around the image and zoom in/out using the icons on the right-hand side. You can also save your final DLPS using the floppy disk icon.
Q: Can I save a pdf version of my plot?
A: No, currently only .png versions are supported.
Q: I want to add my own theoretical model to the plot. How can I do this?
The code for this app will be open source when the paper is accepted for publication. You will need bokeh and Flask to run it in its current form.
Q: I have a feature recommendation/question for you.
You can email me at vvillar-at-cfa.harvard.edu with comments and questions.