LSST Applications 27.0.0,g0265f82a02+469cd937ee,g02d81e74bb+21ad69e7e1,g1470d8bcf6+cbe83ee85a,g2079a07aa2+e67c6346a6,g212a7c68fe+04a9158687,g2305ad1205+94392ce272,g295015adf3+81dd352a9d,g2bbee38e9b+469cd937ee,g337abbeb29+469cd937ee,g3939d97d7f+72a9f7b576,g487adcacf7+71499e7cba,g50ff169b8f+5929b3527e,g52b1c1532d+a6fc98d2e7,g591dd9f2cf+df404f777f,g5a732f18d5+be83d3ecdb,g64a986408d+21ad69e7e1,g858d7b2824+21ad69e7e1,g8a8a8dda67+a6fc98d2e7,g99cad8db69+f62e5b0af5,g9ddcbc5298+d4bad12328,ga1e77700b3+9c366c4306,ga8c6da7877+71e4819109,gb0e22166c9+25ba2f69a1,gb6a65358fc+469cd937ee,gbb8dafda3b+69d3c0e320,gc07e1c2157+a98bf949bb,gc120e1dc64+615ec43309,gc28159a63d+469cd937ee,gcf0d15dbbd+72a9f7b576,gdaeeff99f8+a38ce5ea23,ge6526c86ff+3a7c1ac5f1,ge79ae78c31+469cd937ee,gee10cc3b42+a6fc98d2e7,gf1cff7945b+21ad69e7e1,gfbcc870c63+9a11dc8c8f
LSST Data Management Base Package
|
Classes | |
class | Observation |
Functions | |
np.ndarray | get_filter_coords (np.ndarray filter_values, tuple[int, int]|None center=None) |
tuple[int, int, int, int] | get_filter_bounds (np.ndarray coords) |
convolve (np.ndarray image, np.ndarray psf, tuple[int, int, int, int] bounds) | |
Image | _set_image_like (np.ndarray|Image images, tuple|None bands=None, Box|None bbox=None) |
|
protected |
Ensure that an image-like array is cast appropriately as an image Parameters ---------- images: The multiband image-like array to cast as an Image. If it already has `bands` and `bbox` properties then it is returned with no modifications. bands: The bands for the multiband-image. If `images` is a numpy array, this parameter is mandatory. If `images` is an `Image` and `bands` is not `None`, then `bands` is ignored. bbox: Bounding box containing the image. If `images` is a numpy array, this parameter is mandatory. If `images` is an `Image` and `bbox` is not `None`, then `bbox` is ignored. Returns ------- images: Image The input images converted into an image.
Definition at line 131 of file observation.py.
lsst.scarlet.lite.observation.convolve | ( | np.ndarray | image, |
np.ndarray | psf, | ||
tuple[int, int, int, int] | bounds ) |
Convolve an image with a PSF in real space Parameters ---------- image: The multi-band image to convolve. psf: The psf to convolve the image with. bounds: The filter bounds required by the ``apply_filter`` C++ method, usually obtained by calling `get_filter_bounds`.
Definition at line 100 of file observation.py.
tuple[int, int, int, int] lsst.scarlet.lite.observation.get_filter_bounds | ( | np.ndarray | coords | ) |
Get the slices in x and y to apply a filter Parameters ---------- coords: The coordinates of the filter, defined by `get_filter_coords`. Returns ------- y_start, y_end, x_start, x_end: The start and end of each slice that is passed to `apply_filter`.
Definition at line 76 of file observation.py.
np.ndarray lsst.scarlet.lite.observation.get_filter_coords | ( | np.ndarray | filter_values, |
tuple[int, int] | None | center = None ) |
Create filter coordinate grid needed for the apply filter function Parameters ---------- filter_values: The 2D array of the filter to apply. center: The center (y,x) of the filter. If `center` is `None` then `filter_values` must have an odd number of rows and columns and the center will be set to the center of `filter_values`. Returns ------- coords: The coordinates of the pixels in `filter_values`, where the coordinates of the `center` pixel are `(0,0)`.
Definition at line 38 of file observation.py.