Custom map simulations

In this tutorial we will build a simulation from scratch.

We start by defining a Band that will determine our array’s sensitivity to different spectra. We then generate an array by specifying a field of view, which will be populated by evenly-spaced beams of the given band.

import maria
from maria.instrument import Band

f090 = Band(
    center=90,  # in GHz
    width=20,
    sensitivity=3e-5,  # in K sqrt(s)
    knee=1e0,
    gain_error=5e-2,
)

f150 = Band(center=150, width=30, sensitivity=5e-5, knee=1e0, gain_error=5e-2)

array = {"field_of_view": 0.5, "primary_size": 20, "bands": [f090, f150]}

instrument = maria.get_instrument(array=array)

instrument.plot()

As something to observe, we can download a map and construct a map. We also define a plan to do a daisy scan centered on the center of the map.

from maria.io import fetch

map_filename = fetch("maps/big_cluster.fits")

input_map = maria.map.read_fits(
    filename=map_filename, nu=150, index=1, width=1, center=(150, 10), units="Jy/pixel"
)

input_map.data *= 1e1
input_map.to(units="K_RJ").plot()

2024-12-14 03:51:48.501 INFO: Caching data from https://github.com/thomaswmorris/maria-data/raw/master/maps/big_cluster.fits
100%|██████████| 4.20M/4.20M [00:00<00:00, 94.1MB/s]

plan = maria.Plan(
    scan_pattern="daisy",
    scan_options={"radius": 0.4, "speed": 0.1},  # in degrees
    duration=600,  # in seconds
    sample_rate=50,  # in Hz
    scan_center=(150, 10),
    frame="ra_dec",
)

plan.plot()

sim = maria.Simulation(
    instrument,
    plan=plan,
    site="llano_de_chajnantor",
    map=input_map,
    atmosphere="2d",
)

2024-12-14 03:51:57.274 INFO: Initialized base in 7513 ms.
Building atmosphere: 100%|██████████| 6/6 [00:33<00:00,  5.61s/it]
2024-12-14 03:52:33.887 INFO: Initialized atmosphere in 36581 ms.

tod = sim.run()

Generating turbulence: 100%|██████████| 6/6 [00:00<00:00, 81.41it/s]
Sampling turbulence: 100%|██████████| 6/6 [00:07<00:00,  1.32s/it]
Computing atmospheric emission: 100%|██████████| 2/2 [00:02<00:00,  1.14s/it, band=f150]
Computing atmospheric opacity: 100%|██████████| 2/2 [00:02<00:00,  1.17s/it, band=f150]
Sampling map: 100%|██████████| 2/2 [00:28<00:00, 14.08s/it, band=f150]
Generating noise: 100%|██████████| 2/2 [00:03<00:00,  1.77s/it, band=f150]

from maria.mappers import BinMapper

mapper = BinMapper(
    center=(150, 10),
    frame="ra_dec",
    width=1e0,
    height=1e0,
    resolution=5e-3,
    tod_preprocessing={
        "window": {"name": "tukey", "kwargs": {"alpha": 0.1}},
        "despline": {"knot_spacing": 5},
        "remove_modes": {"modes_to_remove": [0]},
    },
    map_postprocessing={
        "gaussian_filter": {"sigma": 1},
        "median_filter": {"size": 1},
    },
)

mapper.add_tods(tod)

output_map = mapper.run()

Running mapper (f090): 100%|██████████| 1/1 [00:23<00:00, 23.27s/it]
Running mapper (f150): 100%|██████████| 1/1 [00:22<00:00, 22.76s/it]

output_map.plot()