25:["$","title",null,{"children":"activities sequence in stair, nurse role | Lucas Melchiori Pereira's Workspace | Observable"}] 49:T510,intro = md`A tree with multiple inheritance (sometimes called *tangled tree*) cannot be represented by using a classic tree visualization. It is technically a directed acyclic graph (DAG) with one (or more) nodes identified as root. Using a graph visualization technique solves the issue, but poorly represents some peculiarities of a quasi-tree structure. This visualization tries to address the representation of a tangled tree (a genealogy in this specific example). The layout and basic technique is the same underlying [Geneaquilts](https://aviz.fr/Research/Geneaquilts) [[1](#footnote1)], but with curved links instead of matrices. Metro-style bundling is used when a parent node appears in multiple "families", and the layout is made more compact on the y axis. The intention is for the graphic to be more readily understood, while losing some of the advantages of Geneaquilts (e.g., representing a union without children). See also [this older, simpler example](https://beta.observablehq.com/@nitaku/tangled-tree-visualization). The technique can also be applied to other types of tangled trees. Such structures are commonly found in computational linguistics (thesauri, some ontologies, wordnets). (Thanks to [@trebor](https://observablehq.com/@trebor) for making it more reusable!)`4a:T668,renderChart = (data, options={}) => { options.color ||= (d, i) => color(i) const tangleLayout = constructTangleLayout(_.cloneDeep(data), options); return svg``; }4b:T7d9,data = [ [ { id: 'arrival' }, { id: 'spontaneous arrival' }, { id: 'ambulance arrival' } ], [{ id: 'clean uniform removal', parents: ['arrival'] }], [{ id: 'uniform dressing', parents: ['clean uniform removal'] }], [{ id: 'entry point', parents: ['uniform dressing', 'arrival'] }], [ { id: 'nursing supervision', parents: ['entry point'] }, { id: 'activity distribution', parents: ['entry point'] }, { id: 'ambulance reception', parents: ['entry point', 'ambulance arrival'] }, { id: 'spontaneous search triage', parents: ['entry point', 'spontaneous arrival'] } ], [{ id: 'staff meeting', parents: ['activity distribution'] }, { id: 'patient clinical assessment', parents: ['ambulance reception', 'spontaneous search triage'] } ], [ { id: 'schedule management', parents: ['staff meeting'] }, { id: 'point control', parents: ['staff meeting'] }, { id: 'demand referral', parents: ['staff meeting'] }, { id: 'classification and referral', parents: ['patient clinical assessment'] } ], [ { id: 'stable nursing care', parents: ['nursing supervision', 'classification and referral'] }, { id: 'unstable nursing care', parents: ['nursing supervision', 'classification and referral'] }, { id: 'contagious nursing care', parents: ['nursing supervision', 'classification and referral'] }, { id: 'trauma nursing care', parents: ['nursing supervision', 'classification and referral'] }, { id: 'report filling', parents: ['point control'] }, { id: 'initial clinical care monitoring', parents: ['classification and referral'] } ], [ { id: 'report referral', parents: ['report filling'] }, { id: 'examination referral', parents: ['initial clinical care monitoring'] } ], [ { id: 'examination execution', parents: ['examination referral'] } ], [{ id: 'medical diagnosis and prescription', parents: ['examination execution'] }], [{ id: 'observation', parents: ['medical diagnosis and prescription'] }] ]4c:T1089,constructTangleLayout = (levels, options={}) => { // precompute level depth levels.forEach((l, i) => l.forEach(n => (n.level = i))); var nodes = levels.reduce((a, x) => a.concat(x), []); var nodes_index = {}; nodes.forEach(d => (nodes_index[d.id] = d)); // objectification nodes.forEach(d => { d.parents = (d.parents === undefined ? [] : d.parents).map( p => nodes_index[p] ); }); // precompute bundles levels.forEach((l, i) => { var index = {}; l.forEach(n => { if (n.parents.length == 0) { return; } var id = n.parents .map(d => d.id) .sort() .join('-X-'); if (id in index) { index[id].parents = index[id].parents.concat(n.parents); } else { index[id] = { id: id, parents: n.parents.slice(), level: i, span: i - d3.min(n.parents, p => p.level) }; } n.bundle = index[id]; }); l.bundles = Object.keys(index).map(k => index[k]); l.bundles.forEach((b, i) => (b.i = i)); }); var links = []; nodes.forEach(d => { d.parents.forEach(p => links.push({ source: d, bundle: d.bundle, target: p }) ); }); var bundles = levels.reduce((a, x) => a.concat(x.bundles), []); // reverse pointer from parent to bundles bundles.forEach(b => b.parents.forEach(p => { if (p.bundles_index === undefined) { p.bundles_index = {}; } if (!(b.id in p.bundles_index)) { p.bundles_index[b.id] = []; } p.bundles_index[b.id].push(b); }) ); nodes.forEach(n => { if (n.bundles_index !== undefined) { n.bundles = Object.keys(n.bundles_index).map(k => n.bundles_index[k]); } else { n.bundles_index = {}; n.bundles = []; } n.bundles.sort((a,b) => d3.descending(d3.max(a, d => d.span), d3.max(b, d => d.span))) n.bundles.forEach((b, i) => (b.i = i)); }); links.forEach(l => { if (l.bundle.links === undefined) { l.bundle.links = []; } l.bundle.links.push(l); }); // layout const padding = 8; const node_height = 22; const node_width = 70; const bundle_width = 14; const level_y_padding = 16; const metro_d = 4; const min_family_height = 22; options.c ||= 16; const c = options.c; options.bigc ||= node_width+c; nodes.forEach( n => (n.height = (Math.max(1, n.bundles.length) - 1) * metro_d) ); var x_offset = padding; var y_offset = padding; levels.forEach(l => { x_offset += l.bundles.length * bundle_width; y_offset += level_y_padding; l.forEach((n, i) => { n.x = n.level * node_width + x_offset; n.y = node_height + y_offset + n.height / 2; y_offset += node_height + n.height; }); }); var i = 0; levels.forEach(l => { l.bundles.forEach(b => { b.x = d3.max(b.parents, d => d.x) + node_width + (l.bundles.length - 1 - b.i) * bundle_width; b.y = i * node_height; }); i += l.length; }); links.forEach(l => { l.xt = l.target.x; l.yt = l.target.y + l.target.bundles_index[l.bundle.id].i * metro_d - (l.target.bundles.length * metro_d) / 2 + metro_d / 2; l.xb = l.bundle.x; l.yb = l.bundle.y; l.xs = l.source.x; l.ys = l.source.y; }); // compress vertical space var y_negative_offset = 0; levels.forEach(l => { y_negative_offset += -min_family_height + d3.min(l.bundles, b => d3.min(b.links, link => link.ys - 2*c - (link.yt + c)) ) || 0; l.forEach(n => (n.y -= y_negative_offset)); }); // very ugly, I know links.forEach(l => { l.yt = l.target.y + l.target.bundles_index[l.bundle.id].i * metro_d - (l.target.bundles.length * metro_d) / 2 + metro_d / 2; l.ys = l.source.y; l.c1 = l.source.level - l.target.level > 1 ? Math.min(options.bigc, l.xb-l.xt, l.yb-l.yt)-c : c; l.c2 = c; }); var layout = { width: d3.max(nodes, n => n.x) + node_width + 2 * padding, height: d3.max(nodes, n => n.y) + node_height / 2 + 2 * padding, node_height, node_width, bundle_width, level_y_padding, metro_d }; return { levels, nodes, nodes_index, links, bundles, layout }; }4d:[] 29:{"id":"2ae42ba575eee9b2","slug":null,"title":"activities sequence in stair, nurse role","thumbnail":"7e424809d16a2831d6a4ba37f51cd2d07989dc87cd638ef30e6967e2a1e045d7","access_level":"public","create_time":"$D2023-10-24T13:39:43.429Z","update_time":"$D2023-10-24T13:54:34.550Z","view_time":null,"first_public_time":"$D2023-10-24T13:39:43.429Z","has_unpublished_edits":null,"fork":true,"stars":0,"starred":false,"owner":{"type":"team","id":"665e817c1f7d0f7d","login":"lucas-melchiori-pereira2-ws","name":"Lucas Melchiori Pereira's 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References`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":539,"value":"footnote1 = footnote(\"intro\", 1, `A. Bezerianos, P. Dragicevic, J. Fekete, J. Bae and B. Watson, \"GeneaQuilts: A System for Exploring Large Genealogies,\" in IEEE Transactions on Visualization and Computer Graphics, vol. 16, no. 6, pp. 1073-1081, Nov.-Dec. 2010, doi: 10.1109/TVCG.2010.159.`)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","tool":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W4d","stdlib":"1"}} 24:null