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LSST Applications g011c388f00+f3f791b2c2,g0265f82a02+c031775a00,g0cd189fba6+f3c0b8778c,g16a3bce237+c031775a00,g2079a07aa2+6a65a43b64,g2bbee38e9b+c031775a00,g337abbeb29+c031775a00,g3ddfee87b4+ab81698e44,g410a08b1bc+d8499c193f,g50ff169b8f+f00c948d2c,g52b1c1532d+81bc2a20b4,g858d7b2824+f3c0b8778c,g88964a4962+6ae33ca3ca,g8a8a8dda67+81bc2a20b4,g99855d9996+b1cb9e63f7,g9d147d8712+99ee6e9747,g9ddcbc5298+fe33e4d80d,ga1e77700b3+ec8c1568a5,ga8c6da7877+e887ed438f,gae46bcf261+c031775a00,gb700894bec+36645553e7,gb8350603e9+fcecb4f1f4,gba4ed39666+d9abe90c32,gbeb006f7da+bc1c30aee7,gc19132b132+8fdf22815b,gc86a011abf+f3c0b8778c,gcf0d15dbbd+ab81698e44,gd162630629+544f301603,gd44f2fa1a7+03c625699a,gdaeeff99f8+6ceac51f81,ge79ae78c31+c031775a00,gee10cc3b42+81bc2a20b4,gf041782ebf+0cc2057818,gf1cff7945b+f3c0b8778c,gf9db590de0+ab81698e44,w.2024.05
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 |
1.9.8