MAXI/SSC All-Sky Map Visualization

beginnerPythonastropymatplotlibnumpyMAXISSCall-sky mapX-rayvisualizationFITSHEALPixAitoff-Hammer

MAXI All-Sky Map Visualization

This playbook describes how to visualize the pre-generated all-sky maps provided by the MAXI team.
For generating maps from event-by-event photon data, see the separate playbook maxi-allskymap-from-events.

MAXI provides all-sky X-ray maps from two instruments: the Solid-state Slit Camera (SSC) and the Gas Slit Camera (GSC).
File URLs for each energy band are listed on the dataset pages at DARTS:

Available Energy Bands

MAXI/SSC (0.7–4.0 keV, 2009–2011)

Units: counts deg⁻² cm⁻² s⁻¹

Energy (keV) PI Channel
0.7–1.0 192–273
1.0–2.0 274–547
2.0–4.0 548–1095

MAXI/GSC (2–16 keV, 2009–2020)

Units: counts cm⁻² s⁻¹

Energy (keV) PI Channel
2–4 40–80
4–8 80–160
8–16 160–320

Both instruments share the same FITS structure:

  • Primary HDU: 2D image in Aitoff-Hammer projection (Galactic coordinates)
  • Secondary HDU: HEALPix table (Equatorial coordinates, NESTED, NSIDE=128); intensity column is RATE (SSC) or CNTS (GSC)

Visualization with Python

Requirements

pip install astropy matplotlib numpy

Example 1: Display a single-band image

import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits

# Obtain the URL from the dataset page
url = "https://..."

with fits.open(url) as hdul:
    image = hdul[0].data

image = np.where(image > 0, image, np.nan)

fig, ax = plt.subplots(figsize=(12, 6))
im = ax.imshow(np.log10(image), origin="lower", cmap="afmhot", aspect="auto")
fig.colorbar(im, ax=ax, label=r"log$_{10}$ Intensity")
ax.set_title("MAXI/SSC All-Sky Map (Galactic, Aitoff-Hammer)")
ax.set_xlabel("Galactic Longitude")
ax.set_ylabel("Galactic Latitude")
plt.tight_layout()
plt.close()

Example 2: Three-color (RGB) composite image

import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits

# Obtain the URLs from the dataset page; assign soft→R, mid→G, hard→B
url_r = "https://..."
url_g = "https://..."
url_b = "https://..."

channels = {}
for key, url in [("r", url_r), ("g", url_g), ("b", url_b)]:
    with fits.open(url) as hdul:
        data = hdul[0].data
    channels[key] = np.where(data > 0, data, 0.0)

def normalize(arr):
    vmax = np.nanpercentile(arr[arr > 0], 99)
    return np.clip(arr / vmax, 0, 1)

rgb = np.stack([normalize(channels["r"]),
                normalize(channels["g"]),
                normalize(channels["b"])], axis=-1)

fig, ax = plt.subplots(figsize=(12, 6))
ax.imshow(rgb, origin="lower", aspect="auto")
ax.set_title("MAXI All-Sky RGB Map")
ax.set_xlabel("Galactic Longitude")
ax.set_ylabel("Galactic Latitude")
plt.tight_layout()
plt.close()

Example 3: Read the HEALPix data from the secondary HDU

from astropy.io import fits
from astropy.table import Table

# SSC: intensity column is "RATE"; GSC: "CNTS"
url = "https://..."

with fits.open(url) as hdul:
    table = Table(hdul[1].data)

print(table.colnames)
print(table[:5])

Acknowledgement

When using this data in publications, please include:

“This research has made use of MAXI data provided by RIKEN, JAXA and the MAXI team.”

and cite:

References

Related Datasets