NIRISS AMI Extraction¶

In this tutorial, we will read in simulated NIRISS AMI data using AMICAL, for a target-calibrator pair, and then visualize the data and extract calibrated observables.

In [1]:

from pathlib import Path

from astropy.io import fits

import amical

from pathlib import Path from astropy.io import fits import amical

Simulated NIRISS data¶

This example comes with two NIRISS simulated dataset representing a relatively faint binary star (dm = 6) @ 4.3 μm :

• λ/D: sep = 147.7, theta = 46.6
• λ/D: sep = 302.0, theta = 260.9

We will use the first example for this tutorial. Feel free to change the values to explore the other dataset.

In [2]:

sep = 147.7  # binary separation [mas]
theta = 46.6  # position angle (pa) [deg]
dm = 6.0  # contrast ratio [mag]

sep = 147.7 # binary separation [mas] theta = 46.6 # position angle (pa) [deg] dm = 6.0 # contrast ratio [mag]

In our simulated data, _t is for target (astronomical scene) and _c for calibrator (point source)/

We point the path to target and calibrator files, then open these fits files as cubes.

In [3]:

datadir = Path("../NRM_DATA/")
file_pattern = f"binary_s={sep:2.1f}mas_mag=6.0_dm={dm:2.1f}_posang={theta:2.1f}__F430M_81_flat_x11__00.fits"
file_t = datadir / f"t_{file_pattern}"
file_c = datadir / f"c_{file_pattern}"

datadir = Path("../NRM_DATA/") file_pattern = f"binary_s={sep:2.1f}mas_mag=6.0_dm={dm:2.1f}_posang={theta:2.1f}__F430M_81_flat_x11__00.fits" file_t = datadir / f"t_{file_pattern}" file_c = datadir / f"c_{file_pattern}"

In [4]:

hdul = fits.open(file_t)
cube_t = hdul[0].data
hdul.info()
hdul.close()

hdul = fits.open(file_t) cube_t = hdul[0].data hdul.info() hdul.close()

Filename: ../NRM_DATA/t_binary_s=147.7mas_mag=6.0_dm=6.0_posang=46.6__F430M_81_flat_x11__00.fits
No.    Name      Ver    Type      Cards   Dimensions   Format
  0  PRIMARY       1 PrimaryHDU      92   (81, 81, 316)   float64   

In [5]:

hdul = fits.open(file_c)
cube_c = hdul[0].data
hdul.info()
hdul.close()

hdul = fits.open(file_c) cube_c = hdul[0].data hdul.info() hdul.close()

Filename: ../NRM_DATA/c_binary_s=147.7mas_mag=6.0_dm=6.0_posang=46.6__F430M_81_flat_x11__00.fits
No.    Name      Ver    Type      Cards   Dimensions   Format
  0  PRIMARY       1 PrimaryHDU      92   (81, 81, 316)   float64   

Additional cleaning steps would be required for real NIRISS data or MIRAGE simulations (bad pixel, centering, and background). See the getting started and SPHERE tutorials for more on this. However, with the current simulations we can jump straight to the observable extraction!

Extracting Observables¶

We extract raw complex observables for both the target and the calibrator.

In [6]:

params_ami = {
    "peakmethod": "fft",
    "bs_multi_tri": False,
    "maskname": "g7",
    "fw_splodge": 0.7,
}

bs_t = amical.extract_bs(
    cube_t, file_t, targetname="fakebinary", **params_ami, display=True
)
bs_c = amical.extract_bs(
    cube_c, file_c, targetname="fakepsf", **params_ami, display=False
)

params_ami = { "peakmethod": "fft", "bs_multi_tri": False, "maskname": "g7", "fw_splodge": 0.7, } bs_t = amical.extract_bs( cube_t, file_t, targetname="fakebinary", **params_ami, display=True ) bs_c = amical.extract_bs( cube_c, file_c, targetname="fakepsf", **params_ami, display=False )

/home/vandal/repos/astro/AMICAL/src/amical/tools.py:448: RuntimeWarning: No SCI header for NIRISS. No PA correction will be applied.
  l_pa = fct_pa(**kwargs_pa)

Calibration¶

Now we calibrate the raw data to get calibrated visibility amplitudes (V2) and closure phases (CP).

In [7]:

cal = amical.calibrate(bs_t, bs_c)

cal = amical.calibrate(bs_t, bs_c)

Finally, we can display the calibrated observables. We will also save them to an OIFITS file so they can be re-used in the companion search tutorial.

In [8]:

amical.show(cal)
_ = amical.save(cal, oifits_file="example_fakebinary_NIRISS.oifits", fake_obj=True)

amical.show(cal) _ = amical.save(cal, oifits_file="example_fakebinary_NIRISS.oifits", fake_obj=True)

 -- SHOW -- Inputs are classes from amical.calibrate:
-> (Check true_flag_v2, true_flag_t3 and snr parameters)

### Create Saveoifits directory to save all requested Oifits ###