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Exercises for the IRIS-4 Workshop
Release 1.0
Tiago M. D. Pereira
May 19, 2015
CONTENTS
1
Introduction
1
2
Exercise questions
2.1 IRIS and data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Line properties and tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
2
2
3
3
Tutorials
3.1 Preparation . . . . . . . . . . . . .
3.2 IRIS xfiles . . . . . . . . . . . . .
3.3 Mg II Dopplergrams . . . . . . . .
3.4 Mg II spectral feature identification
3.5 CRISPEX . . . . . . . . . . . . . .
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i
CHAPTER
ONE
INTRODUCTION
These exercises and tutorials were prepared for the IRIS-4 Workshop taking place in Boulder, CO in May 2015.
They cover the author’s tutorial on IRIS data analysis.
The answers to most of these questions will be found in the IRIS documentation or the provided slides. Some of
the questions will also require the user to search in the IRIS webpage, examine some of the data files, and run
some IDL commands. For these it is assumed that the user has access to a machine with IDL and the solarsoft
package installed (with the IRIS branch).
The tutorials are meant to be a guided starting point to data exploration and analysis with IRIS. They provide lists
and descriptions of a few basic tasks, and the users and encouraged to explore further and advance from them.
1
CHAPTER
TWO
EXERCISE QUESTIONS
The following list of questions is a test of your knowledge of IRIS.
2.1 IRIS and data
2.1.1 What is the recommended IRIS data level for new users?
1. Level 0 data
2. Level 1 data
3. Level 2 data
4. Level 3 data
2.1.2 Which of the following statements is TRUE?
1. Level 2 data is level 1.5 data with cosmic rays removed
2. For SJIs there is no level 3 data
3. For spectral rasters, level 3 data cubes have a maximum of three dimensions
4. Level 1 data are flat-fielded and dark-subtracted
2.1.3 Were there limb observations on the 1st of March 2014?
2.1.4 With an OBS-ID=3800111235, what is the exposure time? How many steps
has the raster?
2.1.5 Which of the following statements is TRUE?
1. It is possible to observe simultaneously in the FUV and NUV slit-jaws
2. The planning for IRIS observations takes place once per week
3. IRIS level 1 data is only available from the University of Oslo
4. The eclipse season of IRIS is from November to February
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Exercises for the IRIS-4 Workshop, Release 1.0
2.1.6 When observing a very large sit and stare with a 10s cadence and exposing
the full detectors, how long can you observe until the spacecraft memory
fills up?
2.1.7 Which of the following statements is FALSE?
1. Observing with a roll angle other than 0 can decrease the telemetry rate
2. The strongest line in the FUV 1 window is the Si IV 139 nm line
3. The step size of a dense raster is about 0.35 arcsec
4. The 282.3 nm slit-jaw image is formed in the chromosphere
2.2 Line properties and tools
2.2.1 Which of the following statements is FALSE?
1. The IRIS 279.6 nm SJI is the best channel to align with the AIA coronal channels (17.1, 9.3, 21.1 nm, etc.)
2. The IRIS 140.0 nm SJI is the best channel to align with the AIA 170.0 nm channel
3. The IRIS 283.2 nm SJI is the best channel to align with the HMI continuum image
4. The WCS keywords in the IRIS file headers are obtained by cross correlation of the slit-jaw images with
AIA
2.2.2 Which of these lines is formed in higher temperatures?
Figure 2.1: You will need to click on the correct line when answering.
2.2.3 Which of the following statements is TRUE?
1. The spectral lines in the NUV window provide velocity diagnostics for several heights from the photosphere
to the mid chromosphere
2. The spectral lines in the FUV 1 window provide temperature diagnostics for several heights from the convective zone to the photosphere
3. The C II lines at 133.5 nm have a higher signal to noise ratio than the Mg II h and k lines
4. The Fe XII line is observed only in the quiet sun
2.2. Line properties and tools
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Exercises for the IRIS-4 Workshop, Release 1.0
2.2.4 Which of the following statements is FALSE?
1. In the umbra of sunspots and very strong active region plage, the Mg II k & h lines have a nearly Gaussian
shape
2. The Mg II h & k lines have an accompanying triplet of lines at 279.16, 279.87, and 279.88 nm
3. In the average quiet sun the Mg II k2r peak is stronger than the k2v peak
4. The Mg II k line is stronger than the h line and therefore it is formed in higher layers
2.2.5 Which of the following statements is FALSE?
1. CRISPEX uses the WCS keywords in the IRIS files to calculate the solar (x, y) coordinates
2. With IRIS files CRISPEX loads the first timestep into memory to calculate scaling factors
3. The y scale of the detailed spectrum window can be adjusted in the Displays tab
4. The maximum animation speed is 10 frames per second
2.2. Line properties and tools
4
CHAPTER
THREE
TUTORIALS
These tutorials comprise step-by-step instructions and exercises to perform some tasks with IRIS data and
CRISPEX. As time allows, these will be done by participants in the tutorial session. Most of these tutorials
are also included in section 8 of the User’s Guide to IRIS Data Analysis (ITN 26).
3.1 Preparation
The data files for these tutorials can be found in the USB stick given to participants at registration. A tar file
called IRISdata.tar.bz2 can be found under /Volumes/IRIS4/tutorials/data_analysis/ (or
a similar name for the mounted stick in your system). This file contains several datasets from IRIS. Throughout
the tutorials it is assumed that this file is unpacked into a directory called ~/data_temp/. If you want to use a
different directory, just replace the name when necessary.
Note: Please don’t download the data for the tutorials yourself, use the supplied data to avoid any network
bottleneck.
Warning: The data file upacks to about 6 Gb in size. Please make sure you have at least 10 Gb of free disk
space (ideally 12 Gb) to keep all the data and temporary files. Unpacking will take about 5-15 minutes.
To start, unpack the files into a directory in your computer:
% mkdir ~/data_temp
% tar jxvf /Volumes/IRIS4/tutorials/data_analysis/IRISdata.tar.bz2 -C ~/data_temp
(...)
Here we assume that this USB stick is mounted under /Volumes/IRIS4, replace with your system’s path if
different. This will create a directory ~/data_temp/iris with three subdirectories, one per dataset.
You will need to make sure that you have a up-to-date version of SolarSoft IDL with the IRIS branch. You’ll need
to have included iris in the SSW_INSTR environment variable, e.g.:
setenv SSW_INSTR "sot iris ontology"
If you have a working version of SolarSoft with the IRIS package you don’t need to do anything else.
It is outside the scope of these tutorials to help you install and configure SolarSoft. If you don’t have it already
in your system we provide a tar file with a minimal version that can be used to run the tutorials. This minimal
version of SolarSoft has not been tested in many platforms, and is not guaranteed to work. It should be used as a
last resort only for those who didn’t have time to do a proper installation. To install it start by unpacking the tar
file:
tar jxvf /Volumes/IRIS4/tutorials/data_analysis/ssw_iris_minimal.tar.bz2 -C ~/
(Again we assume the USB stick is mounted at /Volumes/IRIS4, replace as needed.) This will create a directory ~/ssw with an installation of SolarSoft. Now configure the startup file for your shell, typically ~/.cshrc
or ~/.tcshrc (you MUST use csh or tcsh – bash et al. will not work). Add the following lines to your configuration file:
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Exercises for the IRIS-4 Workshop, Release 1.0
setenv SSW $HOME/ssw
setenv SSW_INSTR "sot iris ontology"
After that, start a new shell and type sswidl. If all went well you have SolarSoft working and are ready to run
the tutorials!
3.2 IRIS xfiles
This tutorial will guide you step-by-step into some features of iris_xfiles, a quicklook tool. Go to the
directory with the IRIS data, open solarsoft IDL and launch iris_xfiles:
% cd ~/data_temp/iris
% sswidl
(...)
IDL> iris_xfiles
In the middle panel, next to Search Directory: press Change.
Then navigate to the directory
~/data_temp/iris/20131226_171752_3840007146, press OK when this directory is selected. Notice that Search Pattern changed to free search. Make sure the time of these observations (2013 December 26,
17:17 UT) is contained in between the Start Time and Stop Time range, adjust if necessary.
Now press Start Search, and you should see the list of files appear. Feel free to check the slit-jaw movies and
then double click on the raster file. What can you say about the line list?
Figure 3.1: How the wavelength selection iris_xfiles moment tool should look like.
Select the Si IV 1403 line and under Line fit select Profile Moments. On the Moments Prep Tool window adjust
the reference wavelength so that it matches the core of the line, and set the line start and stop so that it covers
the line. Set the continuum to be about 5-10 pixels wide on a region with no lines. Press Finished (and wait a
while...). What do you see?
The result for intensity should look like this (set log(HistoOpt Value) to -1.65):
3.2. IRIS xfiles
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Exercises for the IRIS-4 Workshop, Release 1.0
3.2. IRIS xfiles
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Exercises for the IRIS-4 Workshop, Release 1.0
Now select the Mg II k 2796 line instead, and choose again Profile moments. Set the line start and stop so that
it is about 5 pixels wide around k3. Set the continuum to be about 5 pixels wide on the right side of the plot, in a
region with no absorption lines. The result for intensity should look like this:
Note: The single or double Gauss fit options in Line fit are not currently working.
Go back to the IRIS_Xcontrol window of the raster file. Select the Si IV 1403 and Mg II k 2796 lines and press
Generate level3 files. In the next dialog select only add “20131226_171752_3840007146/” to save directory, so
that the level 3 file is saved in the existing directory. We will use this level 3 file later with CRISPEX. Note that
no sp file was created, as these observations comprise only a single 400-step raster.
3.3 Mg II Dopplergrams
In this tutorial we are going to produce a Dopplergram for the Mg II k line from an IRIS 400-step raster. The
Dopplergram is obtained by subtracting the intensities at symmetrical velocity shifts from the line core (e.g. ±50
km/s). For this kind of analysis we need a consistent wavelength calibration for each step of the raster.
The data set directory should be:
IDL> data_dir = '~/data_temp/iris/20140708_114109_3824262996'
3.3. Mg II Dopplergrams
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Exercises for the IRIS-4 Workshop, Release 1.0
Feel free to examine these data in iris_xfiles. This very large dense raster took more than three hours to
complete the 400 scans (30 s exposures), which means that the orbital velocity and thermal drifts were changed
during the observations. This means that any precise wavelength calibration will need to correct for those shifts.
In most cases level 2 data have already been corrected for these shifts, but this example shows a dataset for which
the automatic calibration still left a significant component which must be corrected for.
First lets load the data using the IDL object interface:
IDL> filename = 'iris_l2_20140708_114109_3824262996_raster_t000_r00000.fits'
IDL> filename = data_dir + '/' + filename
IDL> d = iris_obj(filename)
Let us see the lines that are saved in this raster:
IDL> d->show_lines
Spectral regions(windows)
0
1335.71
C II 1336
1
1349.43
Fe XII 1349
2
1355.60
O I 1356
3
1393.78
Si IV 1394
4
1402.77
Si IV 1403
5
2832.70
2832
6
2814.43
2814
7
2796.20
Mg II k 2796
Let us load the Mg II k line into memory:
IDL> wave = d->getlam(7)
IDL> data = d->getvar(7, /load)
We can see how the the spatially averaged spectrum looks like:
IDL> mspec = total(total(data, 2), 2)
IDL> plot, wave, mspec
IDL> plot, wave, mspec, xrange=[2794, 2799], /xst
To better understand the orbital velocity problem let us look at how the line intensity varies for a strong Mn I line
at around 280.2 nm, in between the Mg II k and h lines. For this dataset, the line core of this line falls around index
350. To plot it in the correct orientation we will make use of IDL’s rotate, and the procedure pih (available in
the IRIS tree of solarsoft) to make the plot:
IDL> pih, rotate(reform(data[350, *, *]), 1), min=0, max=200, scale=[0.35, 0.1667]
The result should look like this:
You can see that the left side of the figure is brighter, and indication that its intensities are not taken at the same
position in the line because of wavelength shifts.
To calculate the wavelength shifts from the orbital velocity and thermal drifts we do the following:
IDL> iris_orbitvar_corr_l2, filename, corr_fuv, corr_nuv
IDL> loadct, 0
This saves the shifts (in Ångström) into the variables corr_fuv and corr_nuv (respectively, for FUV and
NUV spectra). The loadct call is to change to the default colormap. To look at intensities at any given scan we
only need to subtract this shift from the wavelength scale, but to look at the whole image at a given wavelength we
must interpolate the original data to take this shift into account. Here is a way to do it (note that array dimensions
apply to this specific set only!):
IDL> new_data = fltarr(535, 1094, 400, /n)
IDL> .r
for i=0, 399 do begin
for j=0, 1091 do begin
new_data[*, j, i] = interpol(data[*, j, i], wave - corr_nuv[i], wave)
endfor
3.3. Mg II Dopplergrams
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Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.2: Intensity at Mn I 280.2 nm line when orbital velocity and thermal drifts are not accounted for.
3.3. Mg II Dopplergrams
10
Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.3: Fit to the orbital velocity/thermal shifts from iris_orbitvar_corr_l2.
endfor
end
(This double loop may take a while to complete.)
Once you have the calibrated data, we can compare again how it looks at the Mn I line wavelength:
IDL> pih, rotate(reform(new_data[350, *, *]), 1), min=0, max=30, scale=[0.35, 0.1667]
And now we can see that the intensity map is uniform along the solar disk:
We can use this calibrated data for example to calculate dopplergrams. A dopplergram is the difference between
the intensities at two wavelength positions at the same (and opposite) distance from the line core. For example,
at +/- 50 km/s from the Mg II h3 core. To do this, let us first calculate a velocity scale for the h line and find the
indices of the -50 and +50 km/s velocity positions:
IDL>
IDL>
IDL>
IDL>
IDL>
h_centre = 2796.41
vel = (h_centre - wave) * 3e5 / h_centre
; find index of -50 and 50 km/s
tmp = min(abs(vel - 50), i50p)
tmp = min(abs(vel + 50), i50m)
Now get the dopplergram and plot it:
IDL> doppgr = rotate(reform(new_data[i50m, *, *] - new_data[i50p, *, *]), 1)
IDL> pih, doppgr, min=-30, max=30, scale=[0.35, 0.1667]
3.4 Mg II spectral feature identification
In this tutorial we will measure the intensities and velocity shifts of the Mg II k3 and k2 features. We will make
use of the iris_get_mg_features_lev2 procedure, which is included in the IRIS SSW package.
Here we will use the same dataset as for the tutorial IRIS xfiles above. The files can be loaded like this:
IDL> data_dir = '~/data_tmp/iris/20131226_171752_3840007146'
IDL> filename = 'iris_l2_20131226_171752_3840007146_raster_t000_r00000.fits'
IDL> filename = data_dir + '/' + filename
We can calculate the properties of the Mg II k line in the following manner:
3.4. Mg II spectral feature identification
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Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.4: Intensity at Mn I 280.2 nm line when orbital velocity and thermal drifts are accounted for.
3.4. Mg II spectral feature identification
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Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.5: Dopplegram for Mg II h at +/- 50 km/s.
3.4. Mg II spectral feature identification
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Exercises for the IRIS-4 Workshop, Release 1.0
IDL> iris_get_mg_features_lev2, filename, 3, [-40, 40], lc, rp, bp, /onlyk
The output was saved in the arrays lc (line centre), rp (red peak), and bp (blue peak). To save time we calculated
only for the k line. We can then visualise both the derived velocities and intensities. For the intensities:
IDL> pih, rotate(reform(lc[0, 1, *, *]), 1), min=0, max=500,
IDL> pih, rotate(reform(bp[0, 1, *, *]), 1), min=0, max=750,
IDL> pih, rotate(reform(rp[0, 1, *, *]), 1), min=0, max=750,
scale=[0.35, 0.1667]
scale=[0.35, 0.1667]
scale=[0.35, 0.1667]
and for the velocities:
IDL> pih, rotate(reform(lc[0, 0, *, *]), 1), min=-15, max=15, scale=[0.35, 0.1667]
IDL> pih, rotate(reform(rp[0, 0, *, *]), 1), min=0, max=30, scale=[0.35, 0.1667]
IDL> pih, rotate(reform(bp[0, 0, *, *]), 1), min=-30, max=0, scale=[0.35, 0.1667]
3.5 CRISPEX
3.5.1 Active region 400-step raster
Let us go back to the directory of the first dataset we worked with, and run CRISPEX on the level 3 file:
IDL> cd, '~/data_temp/iris/20131226_171752_3840007146'
IDL> crispex, 'iris_l3_20131226_171752_3840007146_t000_SiIV1403_MgIIk2796_im.fits'
Note: If you haven’t created the level 3 file with iris_xfiles, you can create it quickly from the IDL
command line (assuming you are at the directory with the level 2 files):
IDL> f = iris_files('*raster*')
IDL> iris_make_fits_level3, f, [1, 3]
Explore the dataset with CRISPEX, and go through the following tasks/questions:
• Adjust the scaling of the spectral plot so that the lines are visible (Displays tab, lower/upper y-values, and
also multipliers in Scaling tab under Detailed spectrum)
• Look at the main image in the cores of the Mg II k and Si IV lines. Adjust scaling for Si IV 1403 so that it
becomes visible (change Histogram optimisation to 0.001 and/or set gamma lower than 1)
• Blink the image between the spectral positions of the cores of the Si IV and Mg II k lines (use animation
speed of about 2 frames/s)
• Can you find a large dot where Si IV is greatly enhanced but Mg II is not too unusual? What are its solar (x,
y) coordinates?
• Is there a sunspot or a pore in these observations? How do you find out?
3.5.2 Penumbral 16-step raster
Now let us look at a different type of IRIS observation, a 16-step dense raster with 100 repeats. We have not yet
produced the level 3 files for this dataset, so let us change directory and do that from IDL:
IDL>
IDL>
IDL>
IDL>
cd, '~/data_temp/iris/20140630_205235_3820255482'
f = iris_files('*raster*')
; make level 3 files with C II, Si IV, and Mg II (indices 0, 3, 7)
iris_make_fits_level3, f, [0, 3, 7], /sp
Let us now run CRISPEX using both im and sp files, and also use a slit-jaw image:
3.5. CRISPEX
14
Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.6: Intensity for the k3 peak from iris_get_mg_features.
3.5. CRISPEX
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Exercises for the IRIS-4 Workshop, Release 1.0
Figure 3.7: Velocity shifts for the k3 peak from iris_get_mg_features.
3.5. CRISPEX
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Exercises for the IRIS-4 Workshop, Release 1.0
IDL> l3files = iris_files('iris_l3*')
IDL> sji = iris_files('*SJI*')
IDL> crispex, l3files[0], l3files[1], sjicube=sji[0]
When CRISPEX opens, you can see multiple windows, including the slit-jaw image with the 16 raster positions
superimposed.
In CRISPEX the visualisation of this dataset has both a time domain and a main image with 16 columns. Feel
free to explore this dataset, first by creating the level 3 files and loading them in CRISPEX. When used with a
sjicube option, one can see the 16 positions superimposed in the slit-jaw image.
Explore the dataset with CRISPEX, and go through the following tasks/questions:
• Start running the time sequence. At what time does this observation finish?
• Adjust the scaling in of the detailed spectra so you can see the C II and S IV lines
• Where can you find the strongest brightenings in TR lines?
• Show only the Mg II k line (Diagnostics tab, unselect other lines and then Spectral tab, narrow down
Doppler minimum/maximum values)
• Lock the mouse at a given position, see how the temporal evolution goes through the Spectral T-slice window
• Can you find a location with shock signatures in Mg II?
3.5. CRISPEX
17
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