OPTICAM

Suite of software to prepare and analyse data from OPTICAM

Prerequisites

- numpy
- pandas
- matplotlib
- astropy
- astroalign
- aplpy
- synphot
- lmfit
- yaml

You also need a working version of SExtractor in your machine to perform the aperture photometry.

Section 1: Exposure Time Calculator

This package is used to calculate an exposure time based on a desired signal to noise ratio for OPTICAM <https://www.southampton.ac.uk/opticam/>. This code has been modified and adapted specifically for OPTICAM: The original code can be downloaded here: here <https://apoexposuretimecalculator.github.io/APOExptime/>.

Import the four distinct objects inside OPTICAM:

from opticam import Sky, Target, Instrument, Observation

Sky

First, let's create the Sky conditions, where lunar phase can go from 0 (New moon) to 1 (Full moon). Seeing is in arcseconds:

sky = Sky(lunar_phase=0.5, seeing=1.5)

Target

Then, let's create our Target Object. First entry is the target's magnitude, second entry is a string that specifies the magnitude system of the input magnitude [vegamag/stmag/abmag], third entry is the band pass for entered magnitude (only Johnson filters are supported at the moment). Default object is a blackbody spectrum with a solar temperature T=5778 K. You can choose between a blackbody, a powerlaw F_λ∝λ^-index

#BlackBody T=5000 K
star1 = Target(16.5, 'VEGAMAG', 'V', temp=5000)			
# PowerLaw F<sub>&lambda;</sub>, index = -4
star2 = Target(20.1, 'stmag', 'B', index=4)				

You can also upload a custom SED

import numpy as np

# custom_sed.txt has two columns: 1) Wavelenght [AA]; 2) Flux [erg/s/cm^2/AA]
custom_sed = np.loadtxt('custom_sed.txt')				
star3 = Target(13.8, 'abmag', 'B', sed=custom_sed)	

Instrument

Now, let's load the instrument. Only Opticam is supported at the moment.

inst = Instrument('Opticam')

Observation

We can now combine all three objects to generate and observation.

obs = Observation(star, sky, inst)

Now, we can use this object to generate either the SNR for a given exposure time or viceversa:

snr_1 = obs.SNfromTime(200) #value in seconds
time_1 = obs.TimefromSN(50) #value in S/N ratio

print(snr_1)
print(time_1)

This will generate for every filter in OPTICam the desired SNR (assuming a unique exposure time for all filters), or the exposure time required in each filter to achieve the desired SNR.

[[35.7873250731623, 'uprime_filter'], [141.40232164373245, 'gprime_filter'], [182.41241192694474, 'rprime_filter'], [183.60018496695776, 'iprime_filter'], [114.7288335187604, 'zprime_filter']]

[[387.1788766085068, 'uprime_filter'], [25.201236621119214, 'gprime_filter'], [15.179251054637014, 'rprime_filter'], [14.98133450353503, 'iprime_filter'], [38.189538299358965, 'zprime_filter']]

Plotting

A more convenient way of using this calculator is to export the information as a plot.

from opticam import makeplots

ob3 = Observation(star, sky, inst)
# 10 second integrations
ob3.SNfromTime(10)   					

# 'SN', will create a SNR plot for the 10 sec exposures
dd = makeplots(ob3, 'SN')				

ob4 = Observation(star, sky, inst)
# SNR = 50
ob4.TimefromSN(50)

# 'Time', will create a Exposure time plot for SNR=50
dd = makeplots(ob4, 'Time')					
											

Limitations

---

This package is only for the 2.1m telescope at the Observatorio Astronomico Nacional. The current supported instruments are: OPTICam

Section 2 - Quick Aperture Photometry

You need to set the all the raw/reduced files in a folder (e.g., 'bl_cam') inside your working directory (e.g., './'). Since we will extract a single camera at a time,

import opticam

datadir = 'bl_cam/'
catdir = 'bl_cam_cat/'
name = 'BL_Cam_r'                   

Then import the Reduction object and set all the keywords. You need to do the reduction one camera at a time! Here you can select the images for the camera 2 --> 'C2'.

op = opticam.Reduction(rawdata=datadir,savedir=catdir,
                        name=name,rule='C2*.fits')
op.sextractor()         # Perform aperture photometry
op.creat_ref_list()     # Make master star list & FoV image
op.photometry()         # Cross-match between all images

After using SExtractor to create all the catalogues, the program will create a master list (e.g., 'BL_Cam_r_ref_stars.csv') with unique identifiers for all the stars in the field (based on the first image, it can be defined as well). You can check the id of the target of interest in a image (as seen below) of the field with all the id numbers of the stars. In this case BL Cam has the identifier 21. In the end, the 'op.photometry' will create a singel 'csv' and 'pkl' file, containing all the photometry from all the stars.

After checking the number for our target, we can recover the differential photomety for this particular target.

target = 21

photo = opticam.Analysis(catalogue=catdir,name=name)
photo.differential_photo(target=target,ignore=None)
photo.rms_mag(target=target)
photo.lightcurve(std=True)
photo.ccd_noise()

These commands will produce a final file with the photometry for this target; 'BL_Cam_r_lc_21.csv'. It will also output plots of the light curve:

as well as diagnostic plots: