# Messier explorer -- all 110 Messier objects on a live Aladin Lite viewer. # showcase | ~245 lines (most of it is the embedded catalog) | # run: uv run --with pandas shiny run showcase_messier_explorer.py # Data: the Messier catalog (public domain; embedded below as a small CSV). # # Pan and zoom the sky and the table tracks whatever is in view (target()/ # fov()). Select a table row and the viewer flies there in place. Click a # marker and Python sees the object (clicked_object()). Box-select a region # (after arming it) and the sources inside land in a second table # (selected()). Survey and color map re-skin the viewer in place. from __future__ import annotations import io import numpy as np import pandas as pd from astropy.table import Table from ipyaladin import Aladin from shiny import App, reactive, render, ui from shinywidgets import output_widget, reactive_read, render_ipyaladin MESSIER_CSV = """name,ra,dec,type,mag M1,83.633,22.014,Supernova remnant,8.4 M2,323.363,-0.823,Globular cluster,6.5 M3,205.548,28.377,Globular cluster,6.2 M4,245.897,-26.526,Globular cluster,5.9 M5,229.638,2.081,Globular cluster,5.9 M6,265.03,-32.22,Open cluster,4.2 M7,268.47,-34.79,Open cluster,3.3 M8,270.92,-24.38,Nebula,6.0 M9,259.799,-18.516,Globular cluster,7.7 M10,254.288,-4.100,Globular cluster,6.6 M11,282.77,-6.27,Open cluster,6.3 M12,251.809,-1.949,Globular cluster,6.7 M13,250.423,36.460,Globular cluster,5.8 M14,264.401,-3.246,Globular cluster,7.6 M15,322.493,12.167,Globular cluster,6.2 M16,274.70,-13.81,Nebula,6.4 M17,275.11,-16.17,Nebula,6.0 M18,274.99,-17.80,Open cluster,7.5 M19,255.657,-26.268,Globular cluster,6.8 M20,270.60,-23.03,Nebula,6.3 M21,271.13,-22.49,Open cluster,6.5 M22,279.100,-23.906,Globular cluster,5.1 M23,269.05,-18.99,Open cluster,6.9 M24,274.20,-18.50,Star cloud,4.6 M25,277.90,-19.12,Open cluster,6.5 M26,281.33,-9.38,Open cluster,8.0 M27,299.902,22.721,Planetary nebula,7.5 M28,276.137,-24.870,Globular cluster,6.8 M29,305.98,38.52,Open cluster,7.1 M30,325.092,-23.180,Globular cluster,7.2 M31,10.685,41.269,Galaxy,3.4 M32,10.674,40.865,Galaxy,8.1 M33,23.462,30.660,Galaxy,5.7 M34,40.52,42.75,Open cluster,5.5 M35,92.23,24.33,Open cluster,5.3 M36,84.06,34.14,Open cluster,6.3 M37,88.08,32.55,Open cluster,6.2 M38,82.17,35.85,Open cluster,6.4 M39,322.96,48.43,Open cluster,4.6 M40,185.55,58.08,Double star,8.4 M41,101.50,-20.76,Open cluster,4.5 M42,83.822,-5.391,Nebula,4.0 M43,83.87,-5.27,Nebula,9.0 M44,130.10,19.67,Open cluster,3.7 M45,56.75,24.12,Open cluster,1.6 M46,115.43,-14.81,Open cluster,6.1 M47,114.15,-14.50,Open cluster,4.4 M48,123.43,-5.75,Open cluster,5.8 M49,187.445,8.00,Galaxy,8.4 M50,105.69,-8.38,Open cluster,5.9 M51,202.470,47.195,Galaxy,8.4 M52,351.20,61.59,Open cluster,7.3 M53,198.23,18.17,Globular cluster,7.6 M54,283.764,-30.480,Globular cluster,7.6 M55,294.999,-30.965,Globular cluster,6.3 M56,289.148,30.063,Globular cluster,8.3 M57,283.396,33.029,Planetary nebula,8.8 M58,189.43,11.82,Galaxy,9.7 M59,190.51,11.65,Galaxy,9.6 M60,190.917,11.553,Galaxy,8.8 M61,185.479,4.474,Galaxy,9.7 M62,255.303,-30.112,Globular cluster,6.5 M63,198.955,42.029,Galaxy,8.6 M64,194.182,21.683,Galaxy,8.5 M65,169.733,13.092,Galaxy,9.3 M66,170.063,12.991,Galaxy,8.9 M67,132.83,11.81,Open cluster,6.1 M68,189.867,-26.744,Globular cluster,7.8 M69,277.846,-32.348,Globular cluster,7.6 M70,280.803,-32.292,Globular cluster,7.9 M71,298.444,18.779,Globular cluster,8.2 M72,313.365,-12.537,Globular cluster,9.3 M73,314.73,-12.63,Asterism,9.0 M74,24.174,15.783,Galaxy,9.4 M75,301.042,-21.922,Globular cluster,8.5 M76,25.58,51.57,Planetary nebula,10.1 M77,40.670,-0.013,Galaxy,8.9 M78,86.69,0.08,Nebula,8.3 M79,81.04,-24.55,Globular cluster,7.7 M80,244.260,-22.976,Globular cluster,7.3 M81,148.888,69.065,Galaxy,6.9 M82,148.968,69.680,Galaxy,8.4 M83,204.254,-29.866,Galaxy,7.5 M84,186.265,12.887,Galaxy,9.1 M85,186.35,18.19,Galaxy,9.1 M86,186.549,12.946,Galaxy,8.9 M87,187.706,12.391,Galaxy,8.6 M88,187.997,14.420,Galaxy,9.6 M89,188.916,12.556,Galaxy,9.8 M90,189.208,13.163,Galaxy,9.5 M91,188.860,14.496,Galaxy,10.2 M92,259.281,43.136,Globular cluster,6.4 M93,116.11,-23.86,Open cluster,6.0 M94,192.721,41.120,Galaxy,8.2 M95,160.99,11.70,Galaxy,9.7 M96,161.69,11.82,Galaxy,9.2 M97,168.699,55.019,Planetary nebula,9.9 M98,183.451,14.900,Galaxy,10.1 M99,184.707,14.416,Galaxy,9.9 M100,185.729,15.822,Galaxy,9.3 M101,210.802,54.349,Galaxy,7.9 M102,226.62,55.76,Galaxy,9.9 M103,23.34,60.70,Open cluster,7.4 M104,189.998,-11.623,Galaxy,8.0 M105,161.96,12.58,Galaxy,9.3 M106,184.740,47.304,Galaxy,8.4 M107,248.133,-13.054,Globular cluster,7.9 M108,167.879,55.674,Galaxy,10.0 M109,179.400,53.375,Galaxy,9.8 M110,10.092,41.685,Galaxy,8.1 """ messier = pd.read_csv(io.StringIO(MESSIER_CSV)) SURVEYS = { "https://alaskybis.unistra.fr/DSS/DSSColor": "DSS color (optical)", "https://alaskybis.unistra.fr/2MASS/Color": "2MASS color (infrared)", "https://alaskybis.unistra.fr/AllWISE/Color": "allWISE color (mid-IR)", } CMAPS = ["native", "viridis", "cubehelix", "grayscale"] app_ui = ui.page_sidebar( ui.sidebar( ui.input_select("survey", "Survey", SURVEYS), ui.input_select("cmap", "Color map", CMAPS), ui.input_action_button("arm_selection", "Arm rectangle selection"), ui.p( "Drag to pan, scroll to zoom. Click a marker for details, box-select " "a region, or pick a table row to fly there.", class_="text-muted small", ), width=280, ), ui.card(ui.card_header("Messier explorer"), output_widget("sky"), full_screen=True), ui.layout_columns( ui.card(ui.card_header("In the current view"), ui.output_data_frame("in_view")), ui.card( ui.card_header("Clicked object"), ui.output_code("detail"), ui.card_header("Box selection"), ui.output_data_frame("selected"), ), col_widths=[7, 5], ), title="Messier explorer", fillable=True, ) def server(input, output, session): @render_ipyaladin def sky(): aladin = Aladin(survey=list(SURVEYS)[0], target=(56.75, 24.12), fov=5) aladin.add_table( Table.from_pandas(messier), name="messier", color="#ffb14e", source_size=14, shape="square", ) return aladin @reactive.effect def _survey(): w = sky.widget if w: w.survey = input.survey() @reactive.effect def _cmap(): w = sky.widget if w and reactive_read(w, "_is_loaded") and input.cmap() != "native": w.set_color_map(input.cmap()) @reactive.effect def _arm(): w = sky.widget if input.arm_selection() > 0 and w and reactive_read(w, "_is_loaded"): w.selection("rectangle") @reactive.calc def visible(): center, radius = sky.target(), max(sky.fov().deg, 1.0) / 2 dist = np.hypot( (messier["ra"] - center.ra.deg) * np.cos(np.radians(center.dec.deg)), messier["dec"] - center.dec.deg, ) return messier[dist <= radius].sort_values("mag").reset_index(drop=True) @render.data_frame def in_view(): return render.DataGrid(visible(), selection_mode="row", width="100%") # Selecting a row flies the rendered viewer to the object, in place @reactive.effect def _fly_to_selected_row(): rows = input.in_view_selected_rows() w = sky.widget if not (w and rows and reactive_read(w, "_is_loaded")): return with reactive.isolate(): df = visible() if not df.empty and rows[0] < len(df): row = df.iloc[rows[0]] w.target = f"{row.ra} {row.dec}" w.fov = 4 @render.code def detail(): clicked = sky.clicked_object() if clicked is None or not clicked.get("data"): return "Click a marker in the sky to inspect it." return "\n".join(f"{k}: {v}" for k, v in clicked["data"].items()) @render.data_frame def selected(): tables = sky.selected() if not tables: return pd.DataFrame({"name": [], "type": [], "mag": []}) return tables[0].to_pandas()[["name", "type", "mag"]] app = App(app_ui, server)