Progress.txt

# Gaia
Here is my progress through the project in Spring 2017 Semester. I created
separate files for each step, but they are all shown in the final code
"velocity_distribution_2D.py", which is the only one you need to read for code
review.

This is a project with recently released Gaia data, from which I visualize the
density and velocity of stars detected by Gaia.

Through the project I learned a lot about how to program in Python, as well as
how to use GitHub to record and communicate my work.

#First Part - High Signal to Noise Selection (02/01/2017 - 02/28/2017)
 - Code: high_signal_to_noise.py
First part of my study in this class is focused on studying Python. After I got
familiar with it, I worked on selecting data from 'tgas-source.fits', which is
a data file of Gaia. The selecting standard is based on the ratio of data's signal
to noise, and it is set to be higher than 16 so that I can have data with comparatively
low noise.

#Second Part - Velocity Distribution (03/01/2017 - 03/14/2017)
 - Code: velocity_distribution_value.py
 - Plot: velocity_distribution_value.png
For the stars with high signal-to-noise ratio, I calculated their individual
transverse velocities using distance, proper motion right ascension and declination.

#Third Part - Pytest (03/15/2017 - 04/12/2017) (To be finished)
 - Code: test_transverse_v.py, .travis.yml, __init__py
 From course lecture, I learned how to do pytest to check my results. There is another
 repository 'Phys767-Spring17/pytest_Zhiyan' to practice pytest. The pytest in this
 project is to check whether the calculated velocity has only positive values, in case
 mistakes accidentally happen.

#Fourth Part - 3D Plot and Class (03/15/2017 - 04/12/2017)
 - Code: density_distribution_3D.py
 - Plot: density_distribution_3D.npg
 From course lecture, I learned how to use class to access data. It's implemented in
 my code.
 In the meantime, I plotted the position of the selected stars and all stars in 3D.
 However, as you can see the plot, since it's a bulb filled with points, it's not helpful
 to visualize the characteristics of these stars. So I decided to only plot them in a 2D
 plane, which has declination=0.

 #Fifth Part - 2D Plot of Density Distribution (04/12/2017 - 04/26/2017)
 - Code: density_distribution_2D.py, density_distribution_2D_all_data.py
 - Plot: density_distribution_2D.npg, density_distribution_2D_all_data.png
 In the plots, you can see the density distribution of stars detected by Gaia. Two plots
 show separately the one with high signal to noise ratio and the one with all data. They
 are both denser in the center, where we and detectors are.

 #Sixth Part - 2D Plot of Velocity Distribution (04/26 - 05/19/2017) (To be finished)
 - Code: velocity_distribution_2D.py
 - Plot: velocity_distribution_2D.png
 The plot shows the magnitude of transverse velocity for all selected stars with high
 signal to noise ratio.