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MSI_NOT

README.md

Data Reduction

Here, we provide the code that we used to derive polarimetric results in Ishiguro et al. 2021. The contents are

Notebook, Script, Directory Explanation
Masking_image.py The code for making the "Masking image" of FITS file. The "Masking image" masks the 1) nearby stars, 2)cosmic ray, and if data is MSI's data then, 3) the polarization mask area.
NO_Polarimetric_Analysis.py The code to do aperture photometry and derive the stokes parameter from Data taken by MSI at Pirka telescope.
NOT_Polarimetric_Analysis.py The code to do aperture photometry and derive the stokes parameter from Data taken by ALFOSC+FAPOL at NOT.
NOT_Subtract.py The code to do the subtraction technique which removes the nearby stars and the background's gradient in data taken by NOT. This technique is used only for ALFOSC's data taken at 2018 Sep 12 and 19.
result_quplane/ The directory contains the results of NO and NOT as a qu-plane image.
result_csv/ Result files from polarimetry.

The polarimetric data is available in Zenodo (https://zenodo.org/record/5461099#.YZ2_91MzY3w). You can download the followings files at the link.

  1. MSI_2005UD.tar.gz: Zip file containing the images of 2005UD taken with MSI (a total of 1,673 images)
  2. msi181009_640355.fits: the sample image (one of the images contained in MSI_2005UD.tar.gz)

Requirements

Before running the script, the following packages must be installed.

  1. astropy
  2. Astro-SCRAPPY
  3. Source Extraction and Photometry

How to use

Let me take the MSI's data taken at 20180925 as an example.

  1. First, let's check the directory. Your directory must contain the following:

    • Polarimetric pre-processed data (FITS format). All sets should be consisted of 4 images (taken at HWP=0, 22.5, 45, 67.5 deg). If even one set does not have 4 images (e.g., set having images taken at HWP = 0, 45, 67.5 deg), an error will occur. In other words, the number of data in the directory must be a multiple of 4.

    • *.mag.1 file (file made with IRAF's DAOPHOT task) containing the center information of the target.

    • (If you are processing MSI data) A directory named 'Flat/' where the dome flat image is stored.

    • Data, *.mag.1 file and the dome flat image are provied in the Zenodo Repository.

  2. Making the masking image by with Masking_image.py.

    • Fill in the INTPUR VALUE

    • For example,

      #*******************************#
#*        INPUT VALUE          *#
#*******************************#
INSTRUMENT = 'MSI'  # Choose which data you use. one of 'MSI' or 'NOT'
Observatory = 'q33' # Nayoro observatory: 'q33', NOT: 'Z23'
OBJECT = 155140  # 2005 UD
Limiting_mag = 18  # Masking the star brighter than the given magnitude
Pill_masking_with = 30  # [pix] #The Width of pill box masking the nearby stars
path = os.path.join('/home/judy/20180927')  # Path of directory where images to be masked are saved
IMAGE_list = glob.glob(os.path.join(path,'msi.fits'))  # Bring all FITS preprocessed image to be masked in the directory

    • Run the script.

  3. Deriving the stokes parameter by using NOT_Polarimetric_Analysis.py or NO_Polarimetric_Analysis.py for ALFOSC data or MSI data respectively.

    • Fill in the INPUT VALUE.
    • For example, 
      #*******************************#
#*        INPUT VALUE          *#
#*******************************#
Observatory = 'q33' # Observatory code of Pirks
OBJECT = 155140  # 2005 UD
path = os.path.join('/home/judy/20180927')           # Path of directory where images to be masked are saved
IMAGE_list = glob.glob(os.path.join(path,'*.fits'))  # Bring all FITS preprocessed image in the directory
#####################################
# Photometry Parameter
#####################################
Aperture_scale = 1.7  # Aperture radius = Aperture_scale * FWHM
ANN_sacle = 4         # Annulus radius = ANN_sacle * FWHM
Dan = 20              # [pix] #Dannulus size 
####################################
# Calibration Parameter (Please see Ishiguro et al. 2021)
####################################
eff = 0.9913         # Polarimetric efficiency of instrument
eff_err = 0.0001     # Error of polarimetric efficiency of instrument
q_inst = 0.00791     # Instrumental polarization, q{inst}
u_inst = 0.00339     # Instrumental polarization, u{inst}
eq_inst = 0.00025    # Error of instrumental polarization, error of q{inst}
eu_inst = 0.00020    # Error of instrumental polarization, error of u{inst}
theta_offset = 3.66  # Offset of polarization angle 
err_theta = 0.17     # Error of offset
    • Run the script.

  4. If you want to apply the subtraction technique, run NOT_Subtraction.py from the beginning and then do step 3. (Do not make the masking image in this case.)

Output Files

When you run the script you will get two files (result_Photo_XXXX.csv and result_Pol_XXXX.csv where XXXX is the observation date).

Each csv file contains the photometric result of each image and the polarimetric result of each set. The header information is below.

result_Photo_<ObservationDate>.csv

Column Unit Explanation
Object Filename ... Name of FITS file
set ... Set number
TIME ... Mid-point of exposure in UT
JD ... Mid-point of exposure in JD
HWPANG deg Retarder Plate Angle
FWHM_o pixel FWHM of the ordinary component
FWHM_e pixel FWHM of the extra-ordinary component
EXP [s] second Exposure time
Aper [pix] pixel Aperture radius
Ann pixel Inner circle radius of the annulus
Ann_out pixel Outher circle radius of the annulus
Flux_o e- Sum of flux within the aperture of the ordinary component
eFLux_o e- Error of Flux_o
Flux_e e- Sum of flux within the aperture of the extra-ordinary component
eFLux_e e- Error of Flux_e
Sky_o e- Background value around the ordinary component
eSky_o e- Error of Sky_o
Sky_e e- Background value around the extra-ordinary component
eSky_e e- Error of Sky_e
SNR_o ... SNR of the ordinary component
SNR_e ... SNR of the extra-ordinary component

​

result_Pol_<ObservationDate>.csv

Header Keyword Unit Explanation
filename ... Name of FITS file
JD ... Mid-point of set in JD
alpha [deg] deg Average phase angle of set
PsANG [deg] deg Average position angle of the scattering plane of set
q ... q of the Stokes parameters
u ... u of the Stokes parameters
ran_q ... Random error of q
ran_u ... Random error of u
sys_q ... Systemic error of q
sys_u ... Systemic error of u
P ... Linear polarization degree
eP ... Error of P
Pr ... Polarisation degree referring to the scattering plane
theta deg Positino angle
theta_r deg Position angle referring to the scattering plane
eTheta deg Error of theta
Aper_radius [pix] pixel Aperture radius

​

Contact

Created by Jooyeon Geem. - If you have any questions, please feel free to contact me ([email protected]) !

The data reduction pipeline of MSI will continue to be developed in @Geemjy in the future.

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