STCI 0.1.3

SpaceTelescopeColorImage tools for astronomy cutouts.

STCI

STCI stands for SpaceTelescopeColorImage.

STCI is a small astronomy image-composition tool for making display-ready color JPEGs or 16-bit TIFFs from space telescope cutouts and other aligned mono images.

Installation

pip install STCI

The installed Python import module is STCI.

Example usage

mk_colorimg creates one color image from either a 3-channel RGB array or three mono images in (R, G, B) order. For Euclid-style color images, the default mapping is NIR_J, NIR_Y, VIS.

from STCI import mk_colorimg

mk_colorimg(
    [
        "cutout_H.fits",    # R channel
        "cutout_VIS.fits",  # G channel
        "cutout_Y.fits",    # B channel
    ],
    output_jpg="target_mtf_vis_y_h.jpg",
    input_mode="raw",
    ReplaceL=False,
    reference_ROI=200,
)

For a NumPy RGB cube:

from STCI import mk_colorimg

mk_colorimg(rgb_array, output_jpg="target_color.jpg", input_mode="normalized")

Use a .tif or .tiff output filename to write a 16-bit TIFF instead of an 8-bit JPEG:

mk_colorimg(rgb_array, output_jpg="target_color.tiff", input_mode="normalized")

Set ReplaceL=False to skip replacing the CIELab L* channel with the stretched blue luminosity channel. By default, mk_colorimg keeps the original replacement behavior.

Set reference_ROI=200 to estimate the raw normalization, color calibration, and STF/HT stretch from the centered 200 x 200 pixel region, then apply those settings to the full image. By default, reference_ROI=None estimates from the full image.

Single-Band MTF Image

mk_monoimg creates one grayscale image from a single mono image. It uses the same MTF-style stretch as mk_colorimg, but omits RGB-only steps such as color calibration, Lab luminance replacement, SCNR, and saturation.

from STCI import mk_monoimg

mk_monoimg(
    "cutout_VIS.fits",
    output_jpg="target_vis_mtf.jpg",
    input_mode="raw",
)

For a NumPy mono image:

from STCI import mk_monoimg

mk_monoimg(mono_array, output_jpg="target_mono.jpg", input_mode="normalized")

Download a Euclid Color Image

Euclidimg downloads Euclid DR1 VIS, NIR_Y, NIR_J, and NIR_H FITS cutouts, then renders one color image using the NIR_J / NIR_Y / VIS channel order.

from STCI import Euclidimg

result = Euclidimg(
    ra=50.7163333,
    dec=-39.7693889,
    size=5.0,
    path="euclid_color",
    cred="Euclid/cred.txt",
    output_jpg="EUCLJ032251.92-394609.8.jpg",
    ReplaceL=True,
    RGB="auto",
    reference_ROI=None,
)

print(result["jpg"])
print(result["fits"])
print(result["rgb_bands"])

Arguments:

• ra, dec: target coordinates in degrees.
• size: cutout radius in arcsec. For example, size=5.0 makes a 10" x 10" image.
• path: output directory for the FITS files and rendered image.
• cred: Euclid credentials file passed to astroquery.esa.euclid.
• output_jpg: optional output filename written inside path; use .tif or .tiff for 16-bit TIFF.
• ReplaceL: if False, skip replacing the CIELab L* channel with the stretched blue luminosity channel.
• RGB: Euclid bands in (R, G, B) order. Use "auto" for the default available-band choice, or pass bands such as ("NIR_H", "NIR_Y", "VIS") or ("H", "Y", "VIS").
• reference_ROI: optional centered square ROI size, in pixels, used to estimate the display scaling before applying it to the full image.

The returned dictionary contains the selected FITS paths and the final rendered image path. If the first overlapping mosaic tile for a band is empty or all zero, the downloader tries the next matching tile.

Download Euclid FITS Only

from Download_Euclid import EUC_download

fits_paths = EUC_download(
    ra=50.7163333,
    dec=-39.7693889,
    size=5.0,
    path="euclid_fits",
    cred="Euclid/cred.txt",
)