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LSST Applications g0603fd7c41+d727c1d375,g124d44cf3d+604aa34adb,g180d380827+5ffeb7c294,g1afd7665f7+eb25d4c773,g2079a07aa2+86d27d4dc4,g2305ad1205+89e8e9cf63,g2bbee38e9b+44a02a0554,g337abbeb29+44a02a0554,g33d1c0ed96+44a02a0554,g3a166c0a6a+44a02a0554,g3d1719c13e+9a7b30876f,g487adcacf7+719c5abdea,g50ff169b8f+96c6868917,g52b1c1532d+585e252eca,g591dd9f2cf+85bc5ede60,g858d7b2824+9a7b30876f,g991b906543+9a7b30876f,g99cad8db69+8994cf29ec,g9b9dfce982+0fdee8fa3c,g9ddcbc5298+9a081db1e4,ga1e77700b3+03d07e1c1f,gb0e22166c9+60f28cb32d,gb23b769143+9a7b30876f,gb3a676b8dc+e2510deafe,gb4b16eec92+8df1cf93fe,gba4ed39666+c2a2e4ac27,gbb8dafda3b+7edb7fc777,gbd998247f1+585e252eca,gc120e1dc64+79b8551dca,gc28159a63d+44a02a0554,gc3e9b769f7+20d5ea8805,gcf0d15dbbd+0fdee8fa3c,gdaeeff99f8+f9a426f77a,ge79ae78c31+44a02a0554,gee10cc3b42+585e252eca,w.2024.19
LSST Data Management Base Package
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Go to the source code of this file.
Classes | |
| class | lsst.scarlet.lite.display.LinearPercentileNorm |
| class | lsst.scarlet.lite.display.AsinhPercentileNorm |
Namespaces | |
| namespace | lsst |
| namespace | lsst.scarlet |
| namespace | lsst.scarlet.lite |
| namespace | lsst.scarlet.lite.display |
Functions | |
| np.ndarray | lsst.scarlet.lite.display.channels_to_rgb (int channels) |
| np.ndarray | lsst.scarlet.lite.display.img_to_3channel (np.ndarray img, np.ndarray|None channel_map=None, float fill_value=0) |
| np.ndarray | lsst.scarlet.lite.display.img_to_rgb (np.ndarray|Image img, np.ndarray|None channel_map=None, float fill_value=0, Mapping|None norm=None, np.ndarray|None mask=None) |
| matplotlib.pyplot.Figure | lsst.scarlet.lite.display.show_likelihood (Blend blend, tuple[float, float]|None figsize=None, **kwargs) |
| lsst.scarlet.lite.display._add_markers (Source src, tuple[float, float, float, float] extent, matplotlib.pyplot.Axes ax, bool add_markers, bool add_boxes, dict marker_kwargs, dict box_kwargs) | |
| lsst.scarlet.lite.display.show_observation (Observation observation, Mapping|None norm=None, np.ndarray|None channel_map=None, Sequence|None centers=None, str|None psf_scaling=None, tuple[float, float]|None figsize=None) | |
| matplotlib.pyplot.Figure | lsst.scarlet.lite.display.show_scene (Blend blend, Mapping|None norm=None, np.ndarray|None channel_map=None, bool show_model=True, bool show_observed=False, bool show_rendered=False, bool show_residual=False, bool add_labels=True, bool add_boxes=False, tuple[float, float]|None figsize=None, bool linear=True, bool use_flux=False, dict|None box_kwargs=None) |
| tuple[int, int, int, int] | lsst.scarlet.lite.display.get_extent (Box bbox) |
| matplotlib.pyplot.Figure | lsst.scarlet.lite.display.show_sources (Blend blend, list[Source]|None sources=None, Mapping|None norm=None, np.ndarray|None channel_map=None, bool show_model=True, bool show_observed=False, bool show_rendered=False, bool show_spectrum=True, tuple[float, float]|None figsize=None, bool model_mask=True, bool add_markers=True, bool add_boxes=False, bool use_flux=False) |
| matplotlib.pyplot.Figure | lsst.scarlet.lite.display.compare_spectra (bool use_flux=True, bool use_template=True, **list[Source] all_sources) |
Variables | |
| float | lsst.scarlet.lite.display.panel_size = 4.0 |
1.10.0