Getting into SunPy 

Attempting Pull Request: Spectrogram log y axis #291 

 

I'm love spectra. So, when the GSoC process required that I dive into issues in the open source Python library SunPy, I looked for something regarding spectra. I'm still getting used to GitHub, though, so attempting to change the code of such a large and utilized library is kind of intimidating. Then, I found the pull request linked above using a spectrogram... Great! I have low resolution data that I can use to test this!

As it turns out, this class is still being developed. I also realized that a spectrogram is slightly different than the spectra I've been working with so far.

A spectrogram show a spectrum of frequencies as they vary with time. It is used to visualize sounds plotted with time on the x axis and frequency on the y axis. This is different, but closely related to a spectra or spectrum of light that I am accustomed to, where frequencies (or wavelengths) are plotted on the x axis and the amount of of light (or flux) is plotted on the y axis. This means that I probably shouldn't try to test it with  my visual range spectra. Instead, this is most likely working with radio frequencies.

This makes sense for solar data. Radio bursts from the corona are observed, and need to be analysed.

Getting Started:

I found the code needing to be tested. On first glance, I noticed that the spectrogram class has a plot definition, and thought that a simple 'logy' keyword and an if statement added in the plot definition would suffice, like this:
  if logy:
      ax.yscale('log')

I need to test this though, and started with loading in the module and inserting a basic 2D array of random data:

>>> import spectrogram
>>> import numpy as np
>>> data = np.ndarray((10,10), buffer = np.array(np.random.random(100)))
>>> freq_axis = np.linespace(30, 300, 10)
>>> time_axis = np.array(range(0, 10, 1))





Then, I set up some arbitrary start and end times (10 seconds) to suffice the keywords:
>>> import datetime
>>> start = datetime.datetime(2016, 2, 2, 12, 30, 30)
>>> end = datetime.datetime(2016, 2, 2, 12, 30, 40)

Put it all together:
>>> gram = spectrogram.Spectrogram(data, time_axis, freq_axis, start, end)

And, just like that I have a spectrogram object. Next, to test the plot function:
>>> gram.plot()

Colorful! Now, let's try this with my addition if statement:
>>> gram.plot(logy=True)

This flopped with many, many errors. and it is not showing a a frequency range. So, I think my data may not be in the right format.

I tried it again, this time with making a sine wave with 10 being the sampling rate.
>>> sine = np.sin(2 * np.pi * (3*10**4) * (np.arange(100)) / 10)
>>> data2 = np.ndarray((10,10), buffer=sine)
>>> gram2 = spectrogram.Spectrogram(data2, time_axis, freq_axis, start, end)

It produces:

Looking less like noise. But, still not making a frequency axis. I'm going to look for data to use so that I can reproduce the use of this module, and then add my changes to test the log y axis change.


***

Implementing AIA response functions in SunPy 

 

Project Abstract:

Solar physics uses the CHIANTI atomic physics database to obtain properties about various elements and ionisation states. By using observed elemental abundances and ionization states, one can use CHIANTI to obtain synthetic spectra of solar plasma of various features which informs a response function used by the observational instruments themselves. This response function is vital to understanding observations.

The Atmospheric Imaging Assembly (AIA) is a multi-wavelength imager on the Solar Dynamics Observatory, specifically looking at the solar corona to understand magnetic processes.

This project aims to use SunPy to infer plasma properties like temperature and density by

developing the routines necessary to calculate two response functions for the AIA using python and ChiantiPy:

• Wavelength response functions: calculate the amount of flux per wavelength measured by AIA
• Temperature response functions: calculate the sensitivity of light from the plasma per temperature measured by AIA
  

Why am I interested?

My goal is to explore the connection between what we observe on the sun (heliophysics) and how it relates to what we see in other stars (astrophysics). My current research has been looking at visual wavelength range spectra for stellar objects such as M Dwarfs, K Giants, and eclipsing binaries. I would like to use this summer to expand my knowledge on solar observations, and the modules and vernacular that come with solar research.

 

I'm excited to learn about ChiantiPy,  the python interface for astrophysical spectroscopy using the atomic database  CHIANTI. I've observed spectra before, but this project is all about understanding observations by the AIA through python code. This project also wants to get away from using SolarSoftWare (SSW), an idl libray, to calculate these response data structures.  

 

 In reading Boerner et al 2012, I'm learning that the response functions need to use instrument calibration to better the results. The main idea for this project is to analyse the AIA  instrument responses to output a wavelength response, and then use a spectral model to obtain a temperature response.  Now back to work on my proposal! 

 

 

Source of SunPy project idea

Hello World. 

This blog is the beginning of my professional insights. As a current Physics and Astronomy undergraduate at the University of Washington, I hope to join an open source project offered by:

Google Summer of Code 2016

During the summer, Google offers experience to those willing to do the work! Students work with mentors from around the world to better software from various sub-organizations.

Projects of Interest: OpenAstronomy Organization

Astropy

1.  Implement Scheduling capabilities for Astroplan
2.  Implement PSF photometry for fitting several overlapping objects at once

Sunpy

1.  Lightcurve Refactor
2.  Implementing AIA response functions in Sunpy

These projects are exciting and have great potential. As part of the next step in the proposal process, I have joined each development google groups associated with the suborganizations above, and introduced myself with a post. Next, I need to pick a project in each that matches my skills and interests to start a proposal. This is this hard part .

Time to do some project research!