From 37b06677d1c19d6a9e346dfbab23a4d8f403cd15 Mon Sep 17 00:00:00 2001 From: athirupathiraja Date: Wed, 14 Oct 2026 16:29:23 -0400 Subject: [PATCH] added investments, drillholes, and medical imaging demo apps --- .gitignore | 4 +- drillholes-demo/app.py | 116 + drillholes-demo/assets/explorer.js | 588 ++ drillholes-demo/assets/plotly-logo-old.png | Bin 0 -> 13629 bytes drillholes-demo/assets/plotly-logo.png | Bin 0 -> 24095 bytes drillholes-demo/assets/styles.css | 390 + drillholes-demo/callbacks/__init__.py | 0 drillholes-demo/callbacks/block_model.py | 30 + drillholes-demo/callbacks/comparison.py | 31 + drillholes-demo/callbacks/cross_section.py | 102 + drillholes-demo/callbacks/downhole.py | 177 + drillholes-demo/components/__init__.py | 0 .../components/overview_widgets.py | 132 + drillholes-demo/data/assay.csv | 7665 +++++++++++++++++ drillholes-demo/data/collar.csv | 51 + drillholes-demo/data/lith.csv | 275 + drillholes-demo/data/survey.csv | 585 ++ drillholes-demo/data_generator.py | 130 + drillholes-demo/pages/__init__.py | 0 drillholes-demo/pages/block_model.py | 108 + drillholes-demo/pages/comparison.py | 202 + drillholes-demo/pages/cross_section.py | 543 ++ drillholes-demo/pages/downhole_logs.py | 430 + drillholes-demo/pages/explorer.py | 146 + drillholes-demo/requirements.txt | 9 + drillholes-demo/utils.py | 210 + investments-dashboard/Procfile | 1 + investments-dashboard/app.py | 230 + investments-dashboard/assets/DE-logo.png | Bin 0 -> 24095 bytes investments-dashboard/assets/styles.css | 137 + investments-dashboard/callbacks/__init__.py | 5 + investments-dashboard/callbacks/dashboard.py | 224 + investments-dashboard/callbacks/export_all.py | 56 + investments-dashboard/callbacks/fees.py | 129 + .../callbacks/performance.py | 341 + investments-dashboard/callbacks/portfolio.py | 192 + investments-dashboard/components/__init__.py | 1 + investments-dashboard/components/charts.py | 232 + investments-dashboard/components/kpi_cards.py | 87 + investments-dashboard/components/tables.py | 103 + investments-dashboard/data/df_after_tax.csv | 10 + investments-dashboard/data/df_avg_returns.csv | 4 + .../data/df_current_prices.csv | 7 + investments-dashboard/data/df_dividend.csv | 8 + investments-dashboard/data/df_equity_char.csv | 13 + .../data/df_equity_diver.csv | 14 + investments-dashboard/data/df_expenses.csv | 4 + investments-dashboard/data/df_fund_facts.csv | 7 + investments-dashboard/data/df_graph.csv | 2564 ++++++ investments-dashboard/data/df_hist_prices.csv | 6 + investments-dashboard/data/df_minimums.csv | 6 + investments-dashboard/data/df_price_perf.csv | 4 + investments-dashboard/data/df_realized.csv | 4 + .../data/df_recent_returns.csv | 4 + investments-dashboard/data/df_unrealized.csv | 3 + .../demos/callbacks/01_simple_callback.py | 93 + .../demos/callbacks/02_gapminder_slider.py | 75 + .../demos/callbacks/03_multiple_inputs.py | 121 + .../demos/callbacks/04_state_button.py | 118 + .../01_debug_interactions.py | 115 + .../02_hover_timeseries.py | 183 + .../interactive-graphing/03_crossfilter.py | 111 + .../demos/layout/01_hello_dash.py | 54 + .../demos/layout/02_styled_layout.py | 47 + .../demos/layout/03_core_components.py | 109 + investments-dashboard/pages/__init__.py | 1 + investments-dashboard/pages/dashboard.py | 293 + investments-dashboard/pages/fees.py | 333 + investments-dashboard/pages/performance.py | 364 + investments-dashboard/pages/portfolio.py | 414 + investments-dashboard/requirements.txt | 10 + .../scripts/dash-callbacks-intro.md | 102 + .../dash-interactive-graphing-intro.md | 90 + .../scripts/dash-layout-intro.md | 108 + investments-dashboard/utils/__init__.py | 1 + investments-dashboard/utils/data_loader.py | 135 + investments-dashboard/utils/pdf_export.py | 85 + medical-imaging-demo/.gitignore | 7 + medical-imaging-demo/Procfile | 1 + medical-imaging-demo/README.md | 69 + medical-imaging-demo/app.py | 209 + medical-imaging-demo/assets/DE-logo.png | Bin 0 -> 24095 bytes medical-imaging-demo/assets/logo.svg | 9 + medical-imaging-demo/assets/styles.css | 86 + medical-imaging-demo/assets/xrays/xray_01.png | Bin 0 -> 97988 bytes medical-imaging-demo/assets/xrays/xray_02.png | Bin 0 -> 98479 bytes medical-imaging-demo/assets/xrays/xray_03.png | Bin 0 -> 98548 bytes medical-imaging-demo/assets/xrays/xray_04.png | Bin 0 -> 98405 bytes medical-imaging-demo/assets/xrays/xray_05.png | Bin 0 -> 97777 bytes medical-imaging-demo/assets/xrays/xray_06.png | Bin 0 -> 98439 bytes medical-imaging-demo/assets/xrays/xray_07.png | Bin 0 -> 98113 bytes medical-imaging-demo/assets/xrays/xray_08.png | Bin 0 -> 98191 bytes medical-imaging-demo/callbacks/__init__.py | 3 + medical-imaging-demo/callbacks/cohort.py | 95 + medical-imaging-demo/callbacks/dashboard.py | 106 + medical-imaging-demo/callbacks/export_all.py | 33 + medical-imaging-demo/callbacks/imaging.py | 192 + medical-imaging-demo/callbacks/vitals.py | 74 + medical-imaging-demo/components/__init__.py | 0 medical-imaging-demo/components/charts.py | 287 + medical-imaging-demo/components/imaging.py | 172 + medical-imaging-demo/components/kpi_cards.py | 61 + medical-imaging-demo/components/tables.py | 110 + medical-imaging-demo/data/admissions.csv | 211 + medical-imaging-demo/data/cohort.csv | 201 + medical-imaging-demo/data/labs.csv | 201 + medical-imaging-demo/data/patients.csv | 61 + medical-imaging-demo/data/studies.csv | 9 + medical-imaging-demo/data/vitals.csv | 2305 +++++ medical-imaging-demo/pages/__init__.py | 0 medical-imaging-demo/pages/cohort.py | 214 + medical-imaging-demo/pages/dashboard.py | 286 + medical-imaging-demo/pages/imaging.py | 557 ++ medical-imaging-demo/pages/vitals.py | 176 + medical-imaging-demo/requirements.txt | 13 + medical-imaging-demo/scripts/generate_data.py | 216 + .../scripts/generate_xrays.py | 164 + medical-imaging-demo/utils/__init__.py | 0 medical-imaging-demo/utils/data_loader.py | 104 + medical-imaging-demo/utils/pdf_export.py | 214 + 120 files changed, 25727 insertions(+), 1 deletion(-) create mode 100644 drillholes-demo/app.py create mode 100644 drillholes-demo/assets/explorer.js create mode 100644 drillholes-demo/assets/plotly-logo-old.png create mode 100644 drillholes-demo/assets/plotly-logo.png create mode 100644 drillholes-demo/assets/styles.css create mode 100644 drillholes-demo/callbacks/__init__.py create mode 100644 drillholes-demo/callbacks/block_model.py create mode 100644 drillholes-demo/callbacks/comparison.py create mode 100644 drillholes-demo/callbacks/cross_section.py create mode 100644 drillholes-demo/callbacks/downhole.py create mode 100644 drillholes-demo/components/__init__.py create mode 100644 drillholes-demo/components/overview_widgets.py create mode 100644 drillholes-demo/data/assay.csv create mode 100644 drillholes-demo/data/collar.csv create mode 100644 drillholes-demo/data/lith.csv create mode 100644 drillholes-demo/data/survey.csv create mode 100644 drillholes-demo/data_generator.py create mode 100644 drillholes-demo/pages/__init__.py create mode 100644 drillholes-demo/pages/block_model.py create mode 100644 drillholes-demo/pages/comparison.py create mode 100644 drillholes-demo/pages/cross_section.py create mode 100644 drillholes-demo/pages/downhole_logs.py create mode 100644 drillholes-demo/pages/explorer.py create mode 100644 drillholes-demo/requirements.txt create mode 100644 drillholes-demo/utils.py create mode 100644 investments-dashboard/Procfile create mode 100644 investments-dashboard/app.py create mode 100644 investments-dashboard/assets/DE-logo.png create mode 100644 investments-dashboard/assets/styles.css create mode 100644 investments-dashboard/callbacks/__init__.py create mode 100644 investments-dashboard/callbacks/dashboard.py create mode 100644 investments-dashboard/callbacks/export_all.py create mode 100644 investments-dashboard/callbacks/fees.py create mode 100644 investments-dashboard/callbacks/performance.py create mode 100644 investments-dashboard/callbacks/portfolio.py create mode 100644 investments-dashboard/components/__init__.py create mode 100644 investments-dashboard/components/charts.py create mode 100644 investments-dashboard/components/kpi_cards.py create mode 100644 investments-dashboard/components/tables.py create mode 100644 investments-dashboard/data/df_after_tax.csv create mode 100644 investments-dashboard/data/df_avg_returns.csv create mode 100644 investments-dashboard/data/df_current_prices.csv create mode 100644 investments-dashboard/data/df_dividend.csv create mode 100644 investments-dashboard/data/df_equity_char.csv create mode 100644 investments-dashboard/data/df_equity_diver.csv create mode 100644 investments-dashboard/data/df_expenses.csv create mode 100644 investments-dashboard/data/df_fund_facts.csv create mode 100644 investments-dashboard/data/df_graph.csv create mode 100644 investments-dashboard/data/df_hist_prices.csv create mode 100644 investments-dashboard/data/df_minimums.csv create mode 100644 investments-dashboard/data/df_price_perf.csv create mode 100644 investments-dashboard/data/df_realized.csv create mode 100644 investments-dashboard/data/df_recent_returns.csv create mode 100644 investments-dashboard/data/df_unrealized.csv create mode 100644 investments-dashboard/demos/callbacks/01_simple_callback.py create mode 100644 investments-dashboard/demos/callbacks/02_gapminder_slider.py create mode 100644 investments-dashboard/demos/callbacks/03_multiple_inputs.py create mode 100644 investments-dashboard/demos/callbacks/04_state_button.py create mode 100644 investments-dashboard/demos/interactive-graphing/01_debug_interactions.py create mode 100644 investments-dashboard/demos/interactive-graphing/02_hover_timeseries.py create mode 100644 investments-dashboard/demos/interactive-graphing/03_crossfilter.py create mode 100644 investments-dashboard/demos/layout/01_hello_dash.py create mode 100644 investments-dashboard/demos/layout/02_styled_layout.py create mode 100644 investments-dashboard/demos/layout/03_core_components.py create mode 100644 investments-dashboard/pages/__init__.py create mode 100644 investments-dashboard/pages/dashboard.py create mode 100644 investments-dashboard/pages/fees.py create mode 100644 investments-dashboard/pages/performance.py create mode 100644 investments-dashboard/pages/portfolio.py create mode 100644 investments-dashboard/requirements.txt create mode 100644 investments-dashboard/scripts/dash-callbacks-intro.md create mode 100644 investments-dashboard/scripts/dash-interactive-graphing-intro.md create mode 100644 investments-dashboard/scripts/dash-layout-intro.md create mode 100644 investments-dashboard/utils/__init__.py create mode 100644 investments-dashboard/utils/data_loader.py create mode 100644 investments-dashboard/utils/pdf_export.py create mode 100644 medical-imaging-demo/.gitignore create mode 100644 medical-imaging-demo/Procfile create mode 100644 medical-imaging-demo/README.md create mode 100644 medical-imaging-demo/app.py create mode 100644 medical-imaging-demo/assets/DE-logo.png create mode 100644 medical-imaging-demo/assets/logo.svg create mode 100644 medical-imaging-demo/assets/styles.css create mode 100644 medical-imaging-demo/assets/xrays/xray_01.png create mode 100644 medical-imaging-demo/assets/xrays/xray_02.png create mode 100644 medical-imaging-demo/assets/xrays/xray_03.png create mode 100644 medical-imaging-demo/assets/xrays/xray_04.png create mode 100644 medical-imaging-demo/assets/xrays/xray_05.png create mode 100644 medical-imaging-demo/assets/xrays/xray_06.png create mode 100644 medical-imaging-demo/assets/xrays/xray_07.png create mode 100644 medical-imaging-demo/assets/xrays/xray_08.png create mode 100644 medical-imaging-demo/callbacks/__init__.py create mode 100644 medical-imaging-demo/callbacks/cohort.py create mode 100644 medical-imaging-demo/callbacks/dashboard.py create mode 100644 medical-imaging-demo/callbacks/export_all.py create mode 100644 medical-imaging-demo/callbacks/imaging.py create mode 100644 medical-imaging-demo/callbacks/vitals.py create mode 100644 medical-imaging-demo/components/__init__.py create mode 100644 medical-imaging-demo/components/charts.py create mode 100644 medical-imaging-demo/components/imaging.py create mode 100644 medical-imaging-demo/components/kpi_cards.py create mode 100644 medical-imaging-demo/components/tables.py create mode 100644 medical-imaging-demo/data/admissions.csv create mode 100644 medical-imaging-demo/data/cohort.csv create mode 100644 medical-imaging-demo/data/labs.csv create mode 100644 medical-imaging-demo/data/patients.csv create mode 100644 medical-imaging-demo/data/studies.csv create mode 100644 medical-imaging-demo/data/vitals.csv create mode 100644 medical-imaging-demo/pages/__init__.py create mode 100644 medical-imaging-demo/pages/cohort.py create mode 100644 medical-imaging-demo/pages/dashboard.py create mode 100644 medical-imaging-demo/pages/imaging.py create mode 100644 medical-imaging-demo/pages/vitals.py create mode 100644 medical-imaging-demo/requirements.txt create mode 100644 medical-imaging-demo/scripts/generate_data.py create mode 100644 medical-imaging-demo/scripts/generate_xrays.py create mode 100644 medical-imaging-demo/utils/__init__.py create mode 100644 medical-imaging-demo/utils/data_loader.py create mode 100644 medical-imaging-demo/utils/pdf_export.py diff --git a/.gitignore b/.gitignore index ee5f51a..2f295e9 100644 --- a/.gitignore +++ b/.gitignore @@ -146,4 +146,6 @@ cython_debug/ /output # Pycache -*.pyc \ No newline at end of file +*.pyc +# AgentOps session artifacts +.agents/ diff --git a/drillholes-demo/app.py b/drillholes-demo/app.py new file mode 100644 index 0000000..4b5ec83 --- /dev/null +++ b/drillholes-demo/app.py @@ -0,0 +1,116 @@ +import dash +from dash import dcc, html, Input, Output, callback, clientside_callback +import dash_mantine_components as dmc + +from pages import cross_section, downhole_logs, comparison, explorer, block_model +from utils import create_header, create_nav_sidebar, NAV_ITEMS +import callbacks.cross_section # noqa: F401 — registers callbacks +import callbacks.downhole # noqa: F401 +import callbacks.comparison # noqa: F401 +import callbacks.block_model # noqa: F401 +# Explorer page is fully driven by assets/explorer.js — no Python callbacks. + +app = dash.Dash( + __name__, + meta_tags=[{"name": "viewport", "content": "width=device-width, initial-scale=1"}], + external_stylesheets=dmc.styles.ALL, + suppress_callback_exceptions=True, +) +app.title = "Drillhole Visualizer — WA Au-Cu Porphyry" +server = app.server + +app.layout = dmc.MantineProvider( + id="mantine-provider", + forceColorScheme="light", + children=[ + dcc.Location(id="url", refresh=False), + dcc.Store(id="measure-store"), + dmc.AppShell( + [ + dmc.AppShellHeader(create_header(), withBorder=True), + dmc.AppShellMain( + html.Div( + [ + create_nav_sidebar(), + dmc.Container(id="page-content", fluid=True, p="md", className="main-content"), + ], + className="main-layout", + ), + ), + ], + header={"height": 60}, + padding=0, + ), + ], +) + +clientside_callback( + """ + function(n_clicks) { + if (n_clicks === undefined || n_clicks === null) { + var nu = window.dash_clientside.no_update; + return [nu, nu, nu, nu, nu, nu, nu, nu]; + } + var collapsed = (n_clicks % 2) !== 0; + if (collapsed) { + return [ + "filter-sidebar collapsed", + "pad-0 justify-center", + "basil:caret-right-solid", + {"display": "none"}, + null, + {"display": "none"}, + {"display": "none"}, + {"display": "none"} + ]; + } + return [ + "filter-sidebar", + "title-pad space-between", + "charm:cross", + null, + {"display": "none"}, + null, + null, + null + ]; + } + """, + Output("filter-sidebar", "className"), + Output("sidebar-title-div", "className"), + Output("sidebar-btn-icon", "icon"), + Output("sidebar-title", "style"), + Output("sidebar-collapsed-title-div", "style"), + Output("sidebar-outer-div", "style"), + Output("sidebar-inner-div", "style"), + Output("sidebar-btn-div", "style"), + Input("sidebar-btn", "n_clicks"), +) + + +@callback(Output("page-content", "children"), Input("url", "pathname")) +def display_page(pathname): + if pathname == "/downhole-logs": + return downhole_logs.layout() + elif pathname == "/comparison": + return comparison.layout() + elif pathname == "/explorer": + return explorer.layout() + elif pathname == "/block-model": + return block_model.layout() + else: + return cross_section.layout() + + +@callback( + [Output(item["id"], "active") for item in NAV_ITEMS], + Input("url", "pathname"), +) +def update_nav_active(pathname): + path = pathname or "/" + return [item["href"] == path for item in NAV_ITEMS] + + +if __name__ == "__main__": + app.run(debug=True, port=8051) + diff --git a/drillholes-demo/assets/explorer.js b/drillholes-demo/assets/explorer.js new file mode 100644 index 0000000..4fbfa75 --- /dev/null +++ b/drillholes-demo/assets/explorer.js @@ -0,0 +1,588 @@ +/* + * Drill-Hole Cross-Section Explorer — port of the CodePen of the same name. + * + * The CodePen renders into a single #chart div with raw Plotly.js. Dash + * unmounts/remounts the page on every SPA route change, so we wrap the + * codepen body in a MutationObserver-driven init() that re-binds whenever + * the #explorer-chart div appears in the DOM. assets/*.js loads on every + * Dash page; the early-out at the top of init() makes this a no-op when + * the explorer page isn't mounted. + */ +(function () { + var initialized = false; + var retryTimer = null; + + function scheduleRetry() { + if (retryTimer) return; + retryTimer = setTimeout(function () { + retryTimer = null; + init(); + }, 100); + } + + function init() { + var gd = document.getElementById("explorer-chart"); + if (!gd) { + initialized = false; + return; + } + if (initialized) return; + // Dash 4 lazy-loads Plotly.js when a dcc.Graph mounts. Poll until it's + // available rather than bailing once. + if (!window.Plotly) { + scheduleRetry(); + return; + } + initialized = true; + + /* ===== begin verbatim CodePen JS ===== */ + var holeNames = ["DH-001", "DH-002", "DH-003", "DH-004"]; + var holeColors = ["#2563eb", "#16a34a", "#d97706", "#9333ea"]; + var yAxes = ["y", "y2", "y3", "y4"]; + var xAxes = ["x", "x2", "x3", "x4"]; + var domainXs = [ + [0.05, 0.22], + [0.3, 0.47], + [0.55, 0.72], + [0.8, 0.97], + ]; + + function makeLog(seed, nPoints) { + var depths = [], + values = []; + var v = 30 + seed * 5; + for (var i = 0; i <= nPoints; i++) { + var d = i * (100 / nPoints); + depths.push(d); + v += + Math.sin(d * 0.12 + seed) * 3 + + Math.cos(d * 0.07 - seed * 2) * 2 + + (Math.random() - 0.5) * 4; + v = Math.max(5, Math.min(95, v)); + if (d > 35 + seed * 3 && d < 70 - seed * 2) v += 15; + values.push(v); + } + return { depths: depths, values: values }; + } + + var units = [ + { + name: "Overburden", + tops: [0, 0, 0, 0], + bots: [10, 8, 13, 9], + fill: "rgba(139,90,43,0.22)", + line: "rgba(139,90,43,0.7)", + }, + { + name: "Upper Sandstone", + tops: [10, 8, 13, 9], + bots: [28, 25, 30, 26], + fill: "rgba(194,178,128,0.22)", + line: "rgba(194,178,128,0.7)", + }, + { + name: "Ore Zone", + tops: [28, 25, 30, 26], + bots: [68, 64, 72, 66], + fill: "rgba(220,50,50,0.18)", + line: "rgba(220,50,50,0.7)", + }, + { + name: "Lower Shale", + tops: [68, 64, 72, 66], + bots: [85, 82, 88, 84], + fill: "rgba(80,120,80,0.18)", + line: "rgba(80,120,80,0.7)", + }, + { + name: "Basement Gneiss", + tops: [85, 82, 88, 84], + bots: [100, 100, 100, 100], + fill: "rgba(100,100,160,0.18)", + line: "rgba(100,100,160,0.7)", + }, + ]; + + var traces = []; + for (var h = 0; h < 4; h++) { + var log = makeLog(h, 80); + var c = holeColors[h]; + var r = parseInt(c.slice(1, 3), 16), + g = parseInt(c.slice(3, 5), 16), + b = parseInt(c.slice(5, 7), 16); + traces.push({ + x: log.values, + y: log.depths, + xaxis: xAxes[h], + yaxis: yAxes[h], + type: "scatter", + mode: "lines", + name: holeNames[h], + line: { color: c, width: 1.5 }, + fill: "tozerox", + fillcolor: "rgba(" + r + "," + g + "," + b + ",0.18)", + hoverinfo: "none", + }); + } + + var baseShapes = []; + + units.forEach(function (u) { + for (var i = 0; i < 3; i++) { + baseShapes.push({ + type: "path", + xref: "paper", + yref: [yAxes[i], yAxes[i + 1], yAxes[i + 1], yAxes[i]], + path: + "M " + + domainXs[i][1] + + " " + + u.tops[i] + + " L " + + domainXs[i + 1][0] + + " " + + u.tops[i + 1] + + " L " + + domainXs[i + 1][0] + + " " + + u.bots[i + 1] + + " L " + + domainXs[i][1] + + " " + + u.bots[i] + + " Z", + fillcolor: u.fill, + line: { color: u.line, width: 1 }, + }); + } + }); + + for (var hh = 0; hh < 4; hh++) { + baseShapes.push({ + type: "rect", + xref: xAxes[hh], + yref: yAxes[hh], + x0: 0, + x1: 100, + y0: units[2].tops[hh], + y1: units[2].bots[hh], + fillcolor: "rgba(220,50,50,0.10)", + line: { width: 0 }, + layer: "below", + }); + } + + var depthRange = [105, -5]; + var valRange = [0, 100]; + + function yAxisCfg(extra) { + return Object.assign( + { + range: depthRange, + gridcolor: "#ecedf0", + zerolinecolor: "#e2e4e9", + linecolor: "#d1d5db", + tickfont: { color: "#6b7280", size: 9 }, + }, + extra || {} + ); + } + + function xAxisCfg(domain, anchor, title) { + return { + domain: domain, + anchor: anchor, + range: valRange, + gridcolor: "#ecedf0", + zerolinecolor: "#e2e4e9", + linecolor: "#d1d5db", + tickfont: { color: "#6b7280", size: 9 }, + title: { + text: title, + font: { size: 11, color: "#4b5563" }, + standoff: 6, + }, + }; + } + + var layout = { + paper_bgcolor: "#fff", + plot_bgcolor: "#fafbfc", + font: { color: "#1e2028" }, + margin: { l: 55, r: 16, t: 44, b: 44 }, + showlegend: true, + legend: { + x: 0.5, + y: 1.07, + xanchor: "center", + orientation: "h", + bgcolor: "rgba(255,255,255,0)", + font: { color: "#4b5563", size: 11 }, + }, + + hoveranywhere: true, + clickanywhere: true, + hovermode: "closest", + + shapes: baseShapes.slice(), + + yaxis: yAxisCfg({ + domain: [0, 1], + anchor: "x", + title: { + text: "Depth (m)", + font: { size: 11, color: "#4b5563" }, + standoff: 6, + }, + }), + yaxis2: yAxisCfg({ + domain: [0, 1], + anchor: "x2", + title: { + text: "Depth (m)", + font: { size: 11, color: "#4b5563" }, + standoff: 6, + }, + }), + yaxis3: yAxisCfg({ + domain: [0, 1], + anchor: "x3", + title: { + text: "Depth (m)", + font: { size: 11, color: "#4b5563" }, + standoff: 6, + }, + }), + yaxis4: yAxisCfg({ + domain: [0, 1], + anchor: "x4", + title: { + text: "Depth (m)", + font: { size: 11, color: "#4b5563" }, + standoff: 6, + }, + }), + + xaxis: xAxisCfg(domainXs[0], "y", "DH-001"), + xaxis2: xAxisCfg(domainXs[1], "y2", "DH-002"), + xaxis3: xAxisCfg(domainXs[2], "y3", "DH-003"), + xaxis4: xAxisCfg(domainXs[3], "y4", "DH-004"), + + annotations: [], + }; + + var clicks = []; + + function dot(xa, ya, xval, depth) { + var axObj = + gd._fullLayout[ya === "y" ? "yaxis" : "yaxis" + ya.slice(1)]; + var xAxObj = + gd._fullLayout[xa === "x" ? "xaxis" : "xaxis" + xa.slice(1)]; + var px = 4; + var rx = + (px * (xAxObj.range[1] - xAxObj.range[0])) / (xAxObj._length || 1); + var ry = + (px * (axObj.range[1] - axObj.range[0])) / (axObj._length || 1); + return { + type: "circle", + xref: xa, + yref: ya, + x0: xval - rx, + x1: xval + rx, + y0: depth - ry, + y1: depth + ry, + fillcolor: "rgba(220,38,38,0.5)", + line: { color: "#dc2626", width: 1.5 }, + }; + } + + function getClickInfo(data) { + var depth, xval, holeIdx; + if (data.points && data.points.length > 0) { + var pt = data.points[0]; + depth = pt.y; + xval = pt.x; + var traceXa = pt.data.xaxis || "x"; + holeIdx = + traceXa === "x" ? 0 : parseInt(traceXa.replace("x", "")) - 1; + } else if (data.yvals && data.yvals.length > 0) { + depth = data.yvals[0]; + xval = data.xvals ? data.xvals[0] : 50; + if (data.xaxes && data.xaxes.length > 0) { + var axId = data.xaxes[0]._id || ""; + holeIdx = axId === "x" ? 0 : parseInt(axId.replace("x", "")) - 1; + } + } + if (depth !== undefined && holeIdx !== undefined) { + return { depth: depth, xval: xval, holeIdx: holeIdx }; + } + return null; + } + + Plotly.newPlot(gd, traces, layout, { + responsive: true, + displayModeBar: true, + modeBarButtonsToRemove: ["lasso2d", "select2d"], + displaylogo: false, + }).then(function () { + gd.on("plotly_hover", function (d) { + var gs = gd._fullLayout._size; + var layer = gd._fullLayout._hoverlayer; + + layer.selectAll(".pseudo-spike").remove(); + + var yPos = d.event.offsetY; + + layer + .insert("line", ":first-child") + .attr({ + x1: gs.l, + x2: gs.l + gs.w, + y1: yPos, + y2: yPos, + "stroke-width": 1, + stroke: "rgba(100,100,100,0.4)", + "stroke-dasharray": "4,3", + }) + .classed("pseudo-spike", true); + + var depthVal = d.yvals + ? d.yvals[0] + : d.points && d.points.length > 0 + ? d.points[0].y + : null; + if (depthVal !== null) { + layer + .append("rect") + .attr({ + x: gs.l - 52, + y: yPos - 9, + width: 48, + height: 18, + rx: 3, + fill: "#4b5563", + }) + .classed("pseudo-spike", true); + layer + .append("text") + .attr({ + x: gs.l - 48, + y: yPos + 4, + fill: "white", + "font-size": "10px", + "font-family": "Inter, Segoe UI, system-ui, sans-serif", + }) + .text(depthVal.toFixed(1) + " m") + .classed("pseudo-spike", true); + } + + if (d.points && d.points.length > 0) { + var pt = d.points[0]; + var tc = pt.data.line.color; + var xax = pt.xaxis; + var yax = pt.yaxis; + + var mkX = + xax._offset + + ((pt.x - xax.range[0]) / (xax.range[1] - xax.range[0])) * + xax._length; + var mkY = + yax._offset + + ((pt.y - yax.range[1]) / (yax.range[0] - yax.range[1])) * + yax._length; + + layer + .append("circle") + .attr({ + cx: mkX, + cy: mkY, + r: 4.5, + fill: tc, + stroke: "white", + "stroke-width": 2, + }) + .classed("pseudo-spike", true); + + var yStr = pt.y.toFixed(1) + " m"; + var lblW = yStr.length * 6.5 + 18; + var lblH = 20; + var gap = 10; + var lx = mkX + gap; + if (lx + lblW > gs.l + gs.w) lx = mkX - lblW - gap; + var ly = mkY - lblH / 2; + + layer + .append("rect") + .attr({ x: lx, y: ly, width: lblW, height: lblH, rx: 10, fill: tc }) + .classed("pseudo-spike", true); + + layer + .append("text") + .attr({ + x: lx + lblW / 2, + y: ly + 13, + fill: "white", + "font-size": "10.5px", + "font-family": "Inter, Segoe UI, system-ui, sans-serif", + "font-weight": "600", + "text-anchor": "middle", + }) + .text(yStr) + .classed("pseudo-spike", true); + } + + var depth, holeName, xval; + if (d.points && d.points.length > 0) { + var pt2 = d.points[0]; + depth = pt2.y; + xval = pt2.x; + holeName = pt2.data.name; + } else if (d.yvals && d.yvals.length > 0) { + depth = d.yvals[0]; + xval = d.xvals ? d.xvals[0] : null; + if (d.xaxes && d.xaxes.length > 0) { + var axId = d.xaxes[0]._id || ""; + var hIdx = axId === "x" ? 0 : parseInt(axId.replace("x", "")) - 1; + holeName = holeNames[hIdx] || "--"; + } + } + if (depth !== undefined) { + var depthEl = document.getElementById("cursor-depth"); + var holeEl = document.getElementById("cursor-hole"); + var valueEl = document.getElementById("cursor-value"); + if (depthEl) depthEl.textContent = depth.toFixed(1) + " m"; + if (holeEl) holeEl.textContent = holeName || "--"; + if (valueEl) + valueEl.textContent = + xval !== null && xval !== undefined ? xval.toFixed(1) : "--"; + } + }); + + gd.on("plotly_unhover", function () { + if (gd._fullLayout && gd._fullLayout._hoverlayer) { + gd._fullLayout._hoverlayer.selectAll(".pseudo-spike").remove(); + } + var depthEl = document.getElementById("cursor-depth"); + var holeEl = document.getElementById("cursor-hole"); + var valueEl = document.getElementById("cursor-value"); + if (depthEl) depthEl.textContent = "--"; + if (holeEl) holeEl.textContent = "--"; + if (valueEl) valueEl.textContent = "--"; + }); + + gd.on("plotly_click", function (data) { + var info = getClickInfo(data); + if (!info) return; + + var distEl = document.getElementById("distance-result"); + var xa = xAxes[info.holeIdx]; + var ya = yAxes[info.holeIdx]; + + if (clicks.length >= 2) { + clicks = []; + Plotly.relayout(gd, { + shapes: baseShapes.slice(), + annotations: [], + }); + if (distEl) distEl.style.display = "none"; + return; + } + + clicks.push({ + depth: info.depth, + xval: info.xval, + holeIdx: info.holeIdx, + xa: xa, + ya: ya, + }); + + if (clicks.length === 1) { + if (distEl) { + distEl.style.display = "block"; + distEl.innerHTML = + "Point 1: " + + info.depth.toFixed(1) + + " m on " + + holeNames[info.holeIdx]; + } + Plotly.relayout(gd, { + shapes: baseShapes.concat([dot(xa, ya, info.xval, info.depth)]), + annotations: [], + }); + } else { + var a = clicks[0], + b = clicks[1]; + + if (a.holeIdx !== b.holeIdx) { + clicks.pop(); + return; + } + + var dist = Math.abs(b.depth - a.depth); + var mx = (a.xval + b.xval) / 2; + var my = (a.depth + b.depth) / 2; + + if (distEl) { + distEl.style.display = "block"; + distEl.innerHTML = + "" + + dist.toFixed(1) + + " m on " + + holeNames[a.holeIdx]; + } + + Plotly.relayout(gd, { + shapes: baseShapes.concat([ + dot(a.xa, a.ya, a.xval, a.depth), + dot(b.xa, b.ya, b.xval, b.depth), + { + type: "line", + xref: a.xa, + yref: a.ya, + x0: a.xval, + y0: a.depth, + x1: b.xval, + y1: b.depth, + line: { color: "#dc2626", width: 2 }, + }, + ]), + annotations: [ + { + x: mx, + y: my, + xref: a.xa, + yref: a.ya, + text: dist.toFixed(1) + " m", + showarrow: false, + font: { color: "#dc2626", size: 12 }, + bgcolor: "rgba(255,255,255,0.9)", + bordercolor: "#dc2626", + borderwidth: 1, + borderpad: 4, + }, + ], + }); + } + }); + }); + /* ===== end verbatim CodePen JS ===== */ + } + + var observer = new MutationObserver(function () { + if (!document.getElementById("explorer-chart")) { + initialized = false; + return; + } + init(); + }); + + if (document.body) { + observer.observe(document.body, { childList: true, subtree: true }); + } else { + document.addEventListener("DOMContentLoaded", function () { + observer.observe(document.body, { childList: true, 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zSSNDLu~0X+npTj}1c*`k5&_<*Ct{%hyJ{-H!3xrbt+WK28htc#&pN2EQsHXcPW8uc zk{Xhr++tYtmCUmxdjkJ1`NY|PVRYmTPPe02foe0yS;aK&L6=8ot(AI`_kf#Tf$e z1$rQ*8qGp63tC8%bEo31JKhWe(6|6+SF57_!My6cuaKDlayPg`qL^*AkDkUv5{Nz4 zffwa?eeN|nyg{<-{a579p+_vdWpVW-zZxGikH1xtePx|%po5*;kP${-oSXf&E=Gr0 z|94Y>!KFQ6i~OUfW$^luSL2DeTRoQ%Uw9H{Tl=HlA#Rrbr}(d<4}3)c4iM-i@Q*s4 z$H~op%hsneTD%j=;uf&u)`G41U#2~<L#Usk0_n^hV0C4)pPz@wdja!-P7Hv{W&rmx+yEK_}WMi zmnk_ATk6d%h{Jq#Ho5tt)?`P3$Z9EEqqhB^!0N)%M#_7$gln5u@$_uhTv?Ra_fr1C z10k|NBN0=wsF=Bp2w6(gAHYQ1V1u8Bd22O&bmhOay-~dk8lfeAbHkCAZno6r?Cmcd zqE{^%SK0v@Z9+KV%WWXGg+*TZ7Guu`>ox20Kyh}I_*ed#uFRL1gM03fWVAW=I?ECU zZ7ij6Ak0q9pPMR5o)N+$^5SS?z*9%Axln53ksI1Kzemzhbp82>RZOcQ0YGQ9b%4Jt z&`ml^vIFP|^rc5956_-eTbD5^UTm@CriN2>{Wjc8KA>&?Y-&heE?mgqO${v?nsd+M zEBs(m>z-U8w~IyDWC2I;}nfX2uN?T 0) { + return {"display": "none"}; + } + return currentStyle || {"display": "flex"}; + } + """, + Output("cs-yaxis-hint", "style"), + Input("cross-section-chart", "relayoutData"), + State("cs-yaxis-hint", "style"), + prevent_initial_call=True, +) + + +# Elevation cursor — tracks mouse elevation across all three panels. +clientside_callback( + """ + function(hoverData, figure) { + if (!hoverData || !hoverData.points || !hoverData.points.length) { + return window.dash_clientside.no_update; + } + var elev = hoverData.points[0].y; + if (elev == null) return window.dash_clientside.no_update; + var fig = JSON.parse(JSON.stringify(figure)); + if (!fig.layout.shapes) return window.dash_clientside.no_update; + for (var i = 0; i < fig.layout.shapes.length; i++) { + var n = fig.layout.shapes[i].name || ""; + if (n === "elev-cursor-1" || n === "elev-cursor-2" || n === "elev-cursor-3") { + fig.layout.shapes[i].y0 = elev; + fig.layout.shapes[i].y1 = elev; + fig.layout.shapes[i].visible = true; + } + } + return fig; + } + """, + Output("cross-section-chart", "figure", allow_duplicate=True), + Input("cross-section-chart", "hoverData"), + State("cross-section-chart", "figure"), + prevent_initial_call=True, +) + + +# Click to pin a marker line at the clicked elevation across all three panels. +clientside_callback( + """ + function(clickData, figure) { + if (!clickData || !clickData.points || !clickData.points.length) { + return window.dash_clientside.no_update; + } + var elev = clickData.points[0].y; + if (elev == null) return window.dash_clientside.no_update; + var fig = JSON.parse(JSON.stringify(figure)); + if (!fig.layout.shapes) return window.dash_clientside.no_update; + for (var i = 0; i < fig.layout.shapes.length; i++) { + var n = fig.layout.shapes[i].name || ""; + if (n.indexOf("measure-span-") === 0) { + fig.layout.shapes[i].y0 = elev - 0.5; + fig.layout.shapes[i].y1 = elev + 0.5; + fig.layout.shapes[i].visible = true; + } + } + return fig; + } + """, + Output("cross-section-chart", "figure", allow_duplicate=True), + Input("cross-section-chart", "clickData"), + State("cross-section-chart", "figure"), + prevent_initial_call=True, +) diff --git a/drillholes-demo/callbacks/downhole.py b/drillholes-demo/callbacks/downhole.py new file mode 100644 index 0000000..63d751f --- /dev/null +++ b/drillholes-demo/callbacks/downhole.py @@ -0,0 +1,177 @@ +""" +Downhole callbacks: +1. Hole selector → rebuild strip log figure +2. Clientside callback: hoverData → update depth cursor shape (zero Python round-trip) +3. Python callback: clickData → click-to-measure state machine +4. Clear button → reset measurement +""" + +import json +import plotly.graph_objects as go +from dash import Input, Output, State, callback, clientside_callback, no_update, ctx +import dash + +from pages.downhole_logs import _strip_log_figure +from utils import load_data + + +@callback( + Output("strip-log-chart", "figure"), + Input("hole-selector", "value"), +) +def update_strip_log(hole_id): + collar, assay, lith, survey = load_data() + return _strip_log_figure(hole_id, collar, assay, lith, survey) + + +@callback( + [Output("kpi-hole-depth", "children"), + Output("kpi-lith-count", "children")], + Input("hole-selector", "value"), +) +def update_hole_kpis(hole_id): + collar, _, lith, _ = load_data() + row = collar.loc[collar["HOLEID"] == hole_id] + depth = int(row["TOTDEPTH"].iloc[0]) if not row.empty else 0 + lith_count = int(lith[lith["HOLEID"] == hole_id].shape[0]) + return f"{depth} m", str(lith_count) + + +# ── Depth cursor — clientside for zero latency ────────────────────────────── +# Plot-wide hover events fire even over empty plot areas (not just data points). +# The transparent sentinel traces in each panel ensure hoverData is populated +# anywhere along the depth axis. +clientside_callback( + """ + function(hoverData, figure) { + if (!hoverData || !hoverData.points || hoverData.points.length === 0) { + return window.dash_clientside.no_update; + } + var depth = hoverData.points[0].y; + if (depth === undefined || depth === null) { + return window.dash_clientside.no_update; + } + // Deep-copy so Dash detects the change + var fig = JSON.parse(JSON.stringify(figure)); + if (!fig.layout.shapes) return window.dash_clientside.no_update; + for (var i = 0; i < fig.layout.shapes.length; i++) { + if (fig.layout.shapes[i].name === 'depth-cursor') { + fig.layout.shapes[i].y0 = depth; + fig.layout.shapes[i].y1 = depth; + fig.layout.shapes[i].visible = true; + } + } + return fig; + } + """, + Output("strip-log-chart", "figure", allow_duplicate=True), + Input("strip-log-chart", "hoverData"), + State("strip-log-chart", "figure"), + prevent_initial_call=True, +) + + +# ── Click-to-measure state machine ────────────────────────────────────────── +@callback( + [Output("measure-readout", "children"), + Output("measure-store", "data"), + Output("strip-log-chart", "figure", allow_duplicate=True)], + [Input("strip-log-chart", "clickData"), + Input("measure-clear-btn", "n_clicks")], + [State("measure-store", "data"), + State("strip-log-chart", "figure")], + prevent_initial_call=True, +) +def handle_click_measure(click_data, clear_clicks, store, current_fig): + triggered = ctx.triggered_id + + # Clear button + if triggered == "measure-clear-btn": + fig = go.Figure(current_fig) + for shape in fig.layout.shapes: + if shape.name == "measure-span": + shape.visible = False + fig.layout.annotations = [ + a for a in fig.layout.annotations if "click again" not in (a.text or "") + ] + return "Click a depth to start measuring", None, fig + + # Click events + if not click_data or not click_data.get("points"): + return no_update, no_update, no_update + + depth = click_data["points"][0].get("y") + if depth is None: + return no_update, no_update, no_update + + fig = go.Figure(current_fig) + + # Strip any pending "click again" prompt before updating + fig.layout.annotations = [ + a for a in fig.layout.annotations if "click again" not in (a.text or "") + ] + + if store is None or store.get("first_depth") is None: + # First click: store depth + new_store = {"first_depth": float(depth)} + readout = f"From: {depth:.1f} m — click again to set end depth" + + # Show a thin line at the first click depth + for shape in fig.layout.shapes: + if shape.name == "measure-span": + shape.y0 = float(depth) + shape.y1 = float(depth) + 0.5 + shape.visible = True + + # On-chart prompt so user knows a second click is needed + fig.add_annotation( + x=0.5, y=float(depth) + 10, + xref="paper", yref="y", + text="↓ click again to set end depth", + showarrow=True, arrowhead=2, + arrowcolor="#e8a020", ax=0, ay=22, + font=dict(size=10, color="#e8a020", family="monospace"), + bgcolor="rgba(255,255,255,0.9)", + bordercolor="#e8a020", borderwidth=1, + xanchor="center", + ) + + return readout, new_store, fig + + else: + # Second click: compute interval, draw span + d1 = store["first_depth"] + d2 = float(depth) + lo, hi = min(d1, d2), max(d1, d2) + thickness = hi - lo + + for shape in fig.layout.shapes: + if shape.name == "measure-span": + shape.y0 = lo + shape.y1 = hi + shape.visible = True + + # Add annotation showing the thickness + fig.add_annotation( + x=0.98, y=(lo + hi) / 2, + xref="paper", yref="y", + text=f" {thickness:.1f} m ", + showarrow=False, + font=dict(size=11, color="#d48806", family="monospace"), + bgcolor="rgba(255,255,255,0.9)", + bordercolor="#e8a020", + borderwidth=1, + xanchor="right", + ) + + readout = f"{lo:.1f} m — {hi:.1f} m = {thickness:.1f} m interval" + return readout, None, fig # reset store for next measurement + + +@callback( + Output("dl-tour", "isOpen"), + Input("dl-tour-btn", "n_clicks"), + prevent_initial_call=True, +) +def open_dl_tour(_): + return True diff --git a/drillholes-demo/components/__init__.py b/drillholes-demo/components/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/drillholes-demo/components/overview_widgets.py b/drillholes-demo/components/overview_widgets.py new file mode 100644 index 0000000..373a1f0 --- /dev/null +++ b/drillholes-demo/components/overview_widgets.py @@ -0,0 +1,132 @@ +"""Reusable widgets sourced from the retired Overview page.""" + +import pandas as pd +import plotly.graph_objects as go +from dash import html + +from utils import CHART_LAYOUT + + +def best_au_intercept(assay: pd.DataFrame, min_width: float = 4.0) -> str: + """Best consecutive Au composite across all holes (min cumulative width in m).""" + best_grade, best_hole, best_from, best_to = 0.0, "", 0.0, 0.0 + for hole_id, grp in assay.groupby("HOLEID"): + grp = grp.sort_values("FROM").reset_index(drop=True) + for i in range(len(grp)): + for j in range(i + 1, min(i + 20, len(grp) + 1)): + sub = grp.iloc[i:j] + width = sub["TO"].iloc[-1] - sub["FROM"].iloc[0] + if width < min_width: + continue + avg = sub["Au_ppm"].mean() + if avg > best_grade: + best_grade = avg + best_hole = hole_id + best_from = sub["FROM"].iloc[0] + best_to = sub["TO"].iloc[-1] + width = best_to - best_from + return f"{best_grade:.2f} g/t / {width:.0f}m ({best_hole})" + + +def collar_map(collar: pd.DataFrame) -> go.Figure: + fig = go.Figure() + fig.add_trace(go.Scatter( + x=collar["EAST"], + y=collar["NORTH"], + mode="markers+text", + text=collar["HOLEID"], + textposition="top center", + textfont=dict(size=8, color="#6c757d"), + marker=dict( + size=10, + color=collar["TOTDEPTH"], + colorscale="Viridis", + showscale=True, + colorbar=dict( + title=dict(text="Total Depth (m)", font=dict(color="#495057")), + tickfont=dict(color="#495057"), + bgcolor="#ffffff", + bordercolor="#dee2e6", + ), + line=dict(width=1, color="#dee2e6"), + ), + hovertemplate=( + "%{text}
" + "Easting: %{x:.1f} m MGA94
" + "Northing: %{y:.1f} m MGA94
" + "Total Depth: %{marker.color:.0f} m" + "" + ), + )) + fig.update_layout(**{ + **CHART_LAYOUT, + "margin": dict(l=60, r=20, t=20, b=50), + "height": 460, + "xaxis": dict( + title="Easting (m MGA94 Zone 50)", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + ), + "yaxis": dict( + title="Northing (m MGA94 Zone 50)", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + scaleanchor="x", scaleratio=1, + ), + "hoverlabel": dict(bgcolor="#ffffff", font_color="#212529", bordercolor="#dee2e6"), + }) + return fig + + +def summary_table(collar: pd.DataFrame, n: int = 20): + cols = ["HOLEID", "EAST", "NORTH", "ELEV", "TOTDEPTH", "AZ", "DIP"] + rows = [] + for _, r in collar[cols].head(n).iterrows(): + rows.append(html.Tr([ + html.Td(str(r["HOLEID"]), style={"color": "#d48806", "fontWeight": "600"}), + html.Td(f"{r['EAST']:.0f}"), + html.Td(f"{r['NORTH']:.0f}"), + html.Td(f"{r['ELEV']:.0f} m RL"), + html.Td(f"{r['TOTDEPTH']:.0f} m"), + html.Td(f"{r['AZ']:.0f}°"), + html.Td(f"{r['DIP']:.0f}°"), + ])) + return html.Table( + [html.Thead(html.Tr([html.Th(c) for c in ["Hole", "East", "North", "RL", "Depth", "Az", "Dip"]]))] + + [html.Tbody(rows)], + className="data-table", + ) + + +def depth_histogram(collar: pd.DataFrame) -> go.Figure: + fig = go.Figure() + fig.add_trace(go.Histogram( + x=collar["TOTDEPTH"], + nbinsx=15, + marker=dict(color="#e8a020", line=dict(color="#ffffff", width=1)), + hovertemplate="Depth: %{x:.0f} m
Number of holes: %{y}", + name="", + )) + fig.update_layout(**{ + **CHART_LAYOUT, + "height": 200, + "margin": dict(l=50, r=20, t=10, b=40), + "xaxis": dict( + title="Total Depth (m)", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + ), + "yaxis": dict( + title="Number of Holes", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + ), + "bargap": 0.05, + "showlegend": False, + "hoverlabel": dict(bgcolor="#ffffff", font_color="#212529", bordercolor="#dee2e6"), + }) + return fig diff --git a/drillholes-demo/data/assay.csv b/drillholes-demo/data/assay.csv new file mode 100644 index 0000000..8f3d860 --- /dev/null +++ b/drillholes-demo/data/assay.csv @@ -0,0 +1,7665 @@ +HOLEID,FROM,TO,Au_ppm,Cu_pct,Ag_ppm +DH001,0.0,2.0,0.093,0.0104,0.112 +DH001,2.0,4.0,0.089,0.0057,0.092 +DH001,4.0,6.0,0.257,0.0146,0.293 +DH001,6.0,8.0,0.152,0.0169,0.199 +DH001,8.0,10.0,0.021,0.0252,0.013 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+DH002,20.6,60.2,Weathered Granite +DH002,60.2,118.1,Granite +DH002,118.1,194.8,Quartz Diorite +DH002,194.8,279.6,Mineralized Porphyry +DH002,279.6,419.0,Fresh Granite +DH003,0.0,17.7,Alluvium +DH003,17.7,47.0,Weathered Granite +DH003,47.0,122.8,Granite +DH003,122.8,171.8,Quartz Diorite +DH003,171.8,192.0,Mineralized Porphyry +DH004,0.0,6.5,Alluvium +DH004,6.5,74.4,Weathered Granite +DH004,74.4,119.1,Granite +DH004,119.1,191.9,Quartz Diorite +DH004,191.9,279.3,Mineralized Porphyry +DH004,279.3,316.0,Fresh Granite +DH005,0.0,29.7,Alluvium +DH005,29.7,64.4,Weathered Granite +DH005,64.4,128.5,Granite +DH005,128.5,177.8,Quartz Diorite +DH005,177.8,183.0,Mineralized Porphyry +DH006,0.0,30.7,Alluvium +DH006,30.7,63.9,Weathered Granite +DH006,63.9,115.4,Granite +DH006,115.4,184.9,Quartz Diorite +DH006,184.9,285.2,Mineralized Porphyry +DH006,285.2,352.0,Fresh Granite +DH007,0.0,16.1,Alluvium +DH007,16.1,57.8,Weathered Granite +DH007,57.8,129.4,Granite +DH007,129.4,180.2,Quartz Diorite 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Porphyry +DH035,269.9,382.0,Fresh Granite +DH036,0.0,28.5,Alluvium +DH036,28.5,51.3,Weathered Granite +DH036,51.3,132.5,Granite +DH036,132.5,190.5,Quartz Diorite +DH036,190.5,290.5,Mineralized Porphyry +DH036,290.5,348.0,Fresh Granite +DH037,0.0,6.5,Alluvium +DH037,6.5,71.0,Weathered Granite +DH037,71.0,114.2,Granite +DH037,114.2,183.6,Quartz Diorite +DH037,183.6,262.0,Mineralized Porphyry +DH038,0.0,8.8,Alluvium +DH038,8.8,68.4,Weathered Granite +DH038,68.4,133.2,Granite +DH038,133.2,178.0,Quartz Diorite +DH039,0.0,18.2,Alluvium +DH039,18.2,71.3,Weathered Granite +DH039,71.3,120.8,Granite +DH039,120.8,187.3,Quartz Diorite +DH039,187.3,289.6,Mineralized Porphyry +DH039,289.6,374.0,Fresh Granite +DH040,0.0,13.6,Alluvium +DH040,13.6,48.5,Weathered Granite +DH040,48.5,112.2,Granite +DH040,112.2,180.1,Quartz Diorite +DH040,180.1,229.0,Mineralized Porphyry +DH041,0.0,22.5,Alluvium +DH041,22.5,56.9,Weathered Granite +DH041,56.9,128.6,Granite +DH041,128.6,192.4,Quartz Diorite 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+DH047,126.4,181.9,Quartz Diorite +DH047,181.9,279.9,Mineralized Porphyry +DH047,279.9,330.0,Fresh Granite +DH048,0.0,15.4,Alluvium +DH048,15.4,71.0,Weathered Granite +DH048,71.0,105.9,Granite +DH048,105.9,176.9,Quartz Diorite +DH048,176.9,293.4,Mineralized Porphyry +DH048,293.4,412.0,Fresh Granite +DH049,0.0,27.5,Alluvium +DH049,27.5,52.7,Weathered Granite +DH049,52.7,131.0,Granite +DH049,131.0,187.4,Quartz Diorite +DH049,187.4,209.0,Mineralized Porphyry +DH050,0.0,11.5,Alluvium +DH050,11.5,60.9,Weathered Granite +DH050,60.9,128.4,Granite +DH050,128.4,172.4,Quartz Diorite +DH050,172.4,243.0,Mineralized Porphyry diff --git a/drillholes-demo/data/survey.csv b/drillholes-demo/data/survey.csv new file mode 100644 index 0000000..a67e692 --- /dev/null +++ b/drillholes-demo/data/survey.csv @@ -0,0 +1,585 @@ +HOLEID,DEPTH,AZ,DIP +DH001,0.0,282.7,-72.6 +DH001,30.0,280.3,-70.3 +DH001,60.0,283.5,-70.6 +DH001,90.0,278.8,-69.6 +DH001,120.0,277.6,-72.6 +DH001,150.0,279.7,-70.9 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+DH050,90.0,151.8,-73.2 +DH050,120.0,150.6,-71.1 +DH050,150.0,157.8,-71.4 +DH050,180.0,156.0,-70.5 +DH050,210.0,150.1,-71.8 +DH050,240.0,154.8,-69.7 +DH050,243.0,152.6,-72.3 diff --git a/drillholes-demo/data_generator.py b/drillholes-demo/data_generator.py new file mode 100644 index 0000000..eae323d --- /dev/null +++ b/drillholes-demo/data_generator.py @@ -0,0 +1,130 @@ +""" +Generate synthetic Western Australia mineral exploration drillhole data. +Modeled on the Kaggle "mineral-exploration-drillholes-western-australia" structure. +Au-Cu porphyry prospect, ~50 holes in a 7x7 grid pattern. +Run once: python data_generator.py +""" + +import numpy as np +import pandas as pd +import pathlib + +DATA_PATH = pathlib.Path(__file__).parent / "data" +DATA_PATH.mkdir(exist_ok=True) + +rng = np.random.default_rng(42) + +EAST_ORIGIN = 350000.0 +NORTH_ORIGIN = 7200000.0 +SPACING = 100.0 +N_HOLES = 50 + +# --- COLLAR --- + +hole_ids = [f"DH{i:03d}" for i in range(1, N_HOLES + 1)] + +cols = 7 +east_base = [EAST_ORIGIN + (i % cols) * SPACING for i in range(N_HOLES)] +north_base = [NORTH_ORIGIN + (i // cols) * SPACING for i in range(N_HOLES)] + +collar = pd.DataFrame({ + "HOLEID": hole_ids, + "EAST": np.round(np.array(east_base) + rng.uniform(-15, 15, N_HOLES), 1), + "NORTH": np.round(np.array(north_base) + rng.uniform(-15, 15, N_HOLES), 1), + "ELEV": np.round(400 + rng.uniform(-10, 10, N_HOLES), 1), + "TOTDEPTH": np.round(rng.uniform(150, 450, N_HOLES), 0), + "AZ": np.round(rng.uniform(0, 360, N_HOLES), 1), + "DIP": np.round(rng.uniform(-90, -60, N_HOLES), 1), +}) + +collar.to_csv(DATA_PATH / "collar.csv", index=False) +print(f"collar.csv: {len(collar)} holes") + +# --- SURVEY --- + +survey_rows = [] +for _, hole in collar.iterrows(): + depths = np.arange(0, hole["TOTDEPTH"] + 30, 30) + for d in depths: + d = min(d, hole["TOTDEPTH"]) + survey_rows.append({ + "HOLEID": hole["HOLEID"], + "DEPTH": round(float(d), 1), + "AZ": round(float(hole["AZ"]) + float(rng.uniform(-5, 5)), 1), + "DIP": round(float(hole["DIP"]) + float(rng.uniform(-3, 3)), 1), + }) + +survey = pd.DataFrame(survey_rows).drop_duplicates(["HOLEID", "DEPTH"]) +survey.to_csv(DATA_PATH / "survey.csv", index=False) +print(f"survey.csv: {len(survey)} stations") + +# --- LITHOLOGY --- + +LITH_SEQUENCE = [ + ("Alluvium", 0, 20), + ("Weathered Granite", 20, 60), + ("Granite", 60, 120), + ("Quartz Diorite", 120, 180), + ("Mineralized Porphyry",180, 280), + ("Fresh Granite", 280, 9999), +] + +lith_rows = [] +for _, hole in collar.iterrows(): + depth = 0.0 + for lith, base_from, base_to in LITH_SEQUENCE: + jitter = float(rng.uniform(-15, 15)) + actual_from = round(depth, 1) + actual_to = round(min(float(hole["TOTDEPTH"]), base_to + jitter), 1) + if actual_from >= float(hole["TOTDEPTH"]): + break + actual_to = max(actual_to, actual_from + 2.0) + actual_to = min(actual_to, float(hole["TOTDEPTH"])) + lith_rows.append({ + "HOLEID": hole["HOLEID"], + "FROM": actual_from, + "TO": actual_to, + "LITHOLOGY": lith, + }) + depth = actual_to + if depth >= float(hole["TOTDEPTH"]): + break + +lith = pd.DataFrame(lith_rows) +lith.to_csv(DATA_PATH / "lith.csv", index=False) +print(f"lith.csv: {len(lith)} intervals") + +# --- ASSAY (2m composites) --- + +assay_rows = [] +for _, hole in collar.iterrows(): + depth = 0.0 + tot = float(hole["TOTDEPTH"]) + while depth < tot: + to = min(depth + 2.0, tot) + mid = (depth + to) / 2.0 + in_zone = 80 <= mid <= 250 + + if in_zone: + au = float(max(0, rng.lognormal(mean=0.8, sigma=1.2))) + cu = float(max(0, rng.lognormal(mean=-1.5, sigma=0.8))) + ag = au * float(rng.uniform(1.5, 3.0)) + else: + au = float(max(0, rng.lognormal(mean=-2.5, sigma=0.6))) + cu = float(max(0, rng.lognormal(mean=-4.0, sigma=0.5))) + ag = au * float(rng.uniform(0.5, 1.5)) + + assay_rows.append({ + "HOLEID": hole["HOLEID"], + "FROM": round(depth, 1), + "TO": round(to, 1), + "Au_ppm": round(au, 3), + "Cu_pct": round(cu, 4), + "Ag_ppm": round(ag, 3), + }) + depth = to + +assay = pd.DataFrame(assay_rows) +assay.to_csv(DATA_PATH / "assay.csv", index=False) +print(f"assay.csv: {len(assay)} intervals") +print("Done — all CSVs written to data/") diff --git a/drillholes-demo/pages/__init__.py b/drillholes-demo/pages/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/drillholes-demo/pages/block_model.py b/drillholes-demo/pages/block_model.py new file mode 100644 index 0000000..2b3445b --- /dev/null +++ b/drillholes-demo/pages/block_model.py @@ -0,0 +1,108 @@ +from dash import dcc, html +import dash_ag_grid as dag +import dash_mantine_components as dmc +from dash_iconify import DashIconify + +from utils import load_data + +COLUMN_DEFS = [ + { + "field": "HOLEID", + "headerName": "Hole ID", + "pinned": "left", + "lockPinned": True, + "filter": "agTextColumnFilter", + "minWidth": 110, + }, + {"field": "FROM", "headerName": "From (m)", "filter": "agNumberColumnFilter", "minWidth": 110}, + {"field": "TO", "headerName": "To (m)", "filter": "agNumberColumnFilter", "minWidth": 110}, + { + "field": "Au_ppm", + "headerName": "Au (g/t)", + "filter": "agNumberColumnFilter", + "minWidth": 110, + "cellStyle": { + "styleConditions": [ + {"condition": "params.value >= 1.0", "style": {"backgroundColor": "#c6efce", "color": "#276221", "fontWeight": "600"}}, + {"condition": "params.value >= 0.3 && params.value < 1.0", "style": {"backgroundColor": "#ffeb9c", "color": "#9c6500"}}, + ], + "defaultStyle": {"backgroundColor": "white", "color": "#495057"}, + }, + }, + { + "field": "Cu_pct", + "headerName": "Cu (%)", + "filter": "agNumberColumnFilter", + "minWidth": 110, + "cellStyle": { + "styleConditions": [ + {"condition": "params.value >= 0.5", "style": {"backgroundColor": "#c6efce", "color": "#276221", "fontWeight": "600"}}, + {"condition": "params.value >= 0.2 && params.value < 0.5", "style": {"backgroundColor": "#ffeb9c", "color": "#9c6500"}}, + ], + "defaultStyle": {"backgroundColor": "white", "color": "#495057"}, + }, + }, + { + "field": "Ag_ppm", + "headerName": "Ag (ppm)", + "filter": "agNumberColumnFilter", + "minWidth": 110, + "cellStyle": { + "styleConditions": [ + {"condition": "params.value >= 5.0", "style": {"backgroundColor": "#c6efce", "color": "#276221", "fontWeight": "600"}}, + {"condition": "params.value >= 1.0 && params.value < 5.0", "style": {"backgroundColor": "#ffeb9c", "color": "#9c6500"}}, + ], + "defaultStyle": {"backgroundColor": "white", "color": "#495057"}, + }, + }, +] + + +def layout(): + _, assay, _, _ = load_data() + + return dmc.Stack([ + dmc.Group([ + DashIconify(icon="tabler:cube", width=22, color="#868e96"), + dmc.Title("Block Model", order=3, c="dark"), + ], gap="sm"), + + dmc.Group([ + dcc.Input( + id="bm-quick-filter", + placeholder="Search all columns...", + debounce=True, + style={"width": 280, "padding": "6px 10px", "border": "1px solid #dee2e6", "borderRadius": 6, "fontSize": 13}, + ), + dmc.Text(id="bm-row-count", size="sm", c="dimmed"), + dmc.Button( + "Export CSV", + id="bm-export-btn", + leftSection=DashIconify(icon="tabler:download", width=16), + variant="light", + color="gray", + size="sm", + ), + ], gap="sm", align="center"), + + dag.AgGrid( + id="bm-grid", + columnDefs=COLUMN_DEFS, + rowData=assay.to_dict("records"), + columnSize="autoSize", + dashGridOptions={ + "theme": "themeAlpine", + "pagination": True, + "paginationPageSize": 20, + "paginationPageSizeSelector": [20, 50, 100], + }, + defaultColDef={ + "filter": True, + "floatingFilter": True, + "sortable": True, + "resizable": True, + "minWidth": 100, + }, + style={"height": "600px"}, + ), + ], gap="md", p="md") diff --git a/drillholes-demo/pages/comparison.py b/drillholes-demo/pages/comparison.py new file mode 100644 index 0000000..a4d6ed3 --- /dev/null +++ b/drillholes-demo/pages/comparison.py @@ -0,0 +1,202 @@ +""" +Comparison page — compare Au/Cu/Ag grade profiles across multiple holes +side by side, with shared depth axis. +""" + +import plotly.graph_objects as go +from plotly.subplots import make_subplots +from dash import html, dcc +import dash_mantine_components as dmc +import plotly.express as px + +from utils import load_data, CHART_LAYOUT, GRADE_COLORS, GRADE_LABELS + + +DEFAULT_HOLES = ["DH001", "DH002", "DH003", "DH004", "DH005"] +DEFAULT_GRADE = "Au_ppm" +SUBPLOT_COLORS = px.colors.qualitative.Set2 + + +def build_comparison_figure(selected_holes, grade_col): + collar, assay, lith, _ = load_data() + + if not selected_holes: + fig = go.Figure() + fig.update_layout(**{**CHART_LAYOUT, "height": 500, + "title_text": "Select at least one hole"}) + return fig + + n = len(selected_holes) + grade_label = GRADE_LABELS.get(grade_col, grade_col) + + fig = make_subplots( + rows=1, cols=n, + shared_yaxes=True, + subplot_titles=selected_holes, + horizontal_spacing=max(0.01, 0.04 - 0.003 * n), + ) + for ann in fig.layout.annotations: + ann.font = dict(size=10, color="#495057") + + for i, hole_id in enumerate(selected_holes, start=1): + hole_assay = assay[assay["HOLEID"] == hole_id].sort_values("FROM") + if hole_assay.empty: + continue + + mid_depths = (hole_assay["FROM"] + hole_assay["TO"]) / 2 + widths = hole_assay["TO"] - hole_assay["FROM"] + color = SUBPLOT_COLORS[(i - 1) % len(SUBPLOT_COLORS)] + + grade_max = float(hole_assay[grade_col].quantile(0.98)) or 1.0 + + fig.add_trace(go.Bar( + x=hole_assay[grade_col], + y=mid_depths, + orientation="h", + width=widths, + marker=dict( + color=hole_assay[grade_col], + colorscale=[ + [0, "#f0f0f0"], + [0.4, color], + [1.0, "#212529"], + ], + cmin=0, cmax=grade_max, + showscale=False, + line_width=0, + ), + name=hole_id, + showlegend=False, + hovertemplate=f"{hole_id}
Depth: %{{y:.1f}} m
{grade_label}: %{{x:.4g}}", + ), row=1, col=i) + + # Best intercept annotation + peak_idx = hole_assay[grade_col].idxmax() + peak_row = hole_assay.loc[peak_idx] + fig.add_annotation( + x=float(peak_row[grade_col]), + y=float((peak_row["FROM"] + peak_row["TO"]) / 2), + xref=f"x{i}" if i > 1 else "x", + yref="y", + text=f" {peak_row[grade_col]:.2g} ←peak", + showarrow=False, + font=dict(size=8, color="#d48806"), + xanchor="left", + ) + + fig.update_xaxes( + title_text=grade_label, + title_font=dict(color="#495057", size=10), + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d", size=8), + zeroline=True, zerolinecolor="#ced4da", + row=1, col=i, + ) + + fig.update_yaxes( + autorange="reversed", + title_text="Depth (m ↓)", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + row=1, col=1, + ) + fig.update_layout(**{ + **CHART_LAYOUT, + "height": 650, + "margin": dict(l=60, r=20, t=45, b=50), + "bargap": 0, "bargroupgap": 0, + "hoverlabel": dict(bgcolor="#ffffff", font_color="#212529", bordercolor="#dee2e6"), + "title_text": f"{grade_label} Grade Profile Comparison", + "title_font": dict(color="#212529", size=13), + }) + return fig + + +def layout(): + collar, assay, _, _ = load_data() + all_hole_ids = sorted(collar["HOLEID"].tolist()) + + default_total_m = int(collar.loc[collar["HOLEID"].isin(DEFAULT_HOLES), "TOTDEPTH"].sum()) + + badge_strip = dmc.Group(gap="sm", id="comparison-badges", children=[ + dmc.Badge(f"Holes selected: {len(DEFAULT_HOLES)}", color="orange", variant="light", + id="badge-hole-count", size="lg"), + dmc.Badge(f"Combined meters: {default_total_m:,} m", color="gray", variant="light", + id="badge-total-meters", size="lg"), + dmc.Badge(f"Grade: {GRADE_LABELS[DEFAULT_GRADE]}", color="orange", variant="filled", + id="badge-grade", size="lg"), + ]) + + return dmc.Stack([ + # Header + badge strip + dmc.Group([ + html.Div([ + html.P("Grade Profile Comparison", className="section-title"), + html.P( + "Side-by-side grade profiles across selected holes on a shared depth axis.", + className="section-description", + ), + ], style={"flex": 1}), + badge_strip, + ], justify="space-between", align="center", wrap="nowrap"), + + dmc.Grid(gutter="md", children=[ + # Controls panel + dmc.GridCol( + dmc.Paper([ + html.P("Grade Type", className="section-title"), + html.P( + "Au = gold (g/t). Cu = copper (%). Ag = silver (ppm).", + className="section-description", + ), + dmc.SegmentedControl( + id="grade-selector", + data=[ + {"value": "Au_ppm", "label": "Au (g/t)"}, + {"value": "Cu_pct", "label": "Cu (%)"}, + {"value": "Ag_ppm", "label": "Ag (ppm)"}, + ], + value=DEFAULT_GRADE, + color="orange", + size="xs", + fullWidth=True, + mb="md", + ), + html.P("Select Holes (up to 10)", className="section-title"), + dmc.CheckboxGroup( + id="hole-checklist", + value=DEFAULT_HOLES, + children=dmc.Stack([ + dmc.Checkbox( + label=h, value=h, + styles={"label": {"color": "#495057", "fontSize": "0.8rem"}}, + ) + for h in all_hole_ids[:20] + ], gap=6), + ), + ], p="md", radius="md", withBorder=True, className="chart-paper", + style={"maxHeight": "700px", "overflowY": "auto"}), + span={"base": 12, "md": 3}, + ), + + # Comparison chart + dmc.GridCol( + dmc.Paper([ + html.P("Grade Profiles", className="section-title"), + html.P( + "Each panel is one hole's grade profile vs. downhole depth on a shared Y-axis. " + "Peak-grade interval is annotated.", + className="section-description", + ), + dcc.Graph( + id="comparison-chart", + figure=build_comparison_figure(DEFAULT_HOLES, DEFAULT_GRADE), + config={"displayModeBar": True, "scrollZoom": True}, + style={"height": "650px"}, + ), + ], p="md", radius="md", withBorder=True, className="chart-paper"), + span={"base": 12, "md": 9}, + ), + ]), + ], gap="md") diff --git a/drillholes-demo/pages/cross_section.py b/drillholes-demo/pages/cross_section.py new file mode 100644 index 0000000..4b6ef5a --- /dev/null +++ b/drillholes-demo/pages/cross_section.py @@ -0,0 +1,543 @@ +""" +Cross-Section page — showcases Plotly.js multi-axis shapes. + +Each geological formation contact is a line shape whose left endpoint +anchors to one subplot x-axis and the right endpoint anchors to a DIFFERENT +subplot x-axis, via the new xref array syntax: xref=["x", "x2"]. +When the user pans or zooms col 1, only the left endpoint pixel moves; +the right endpoint stays locked to col 2's coordinate system — correct +geological cross-section behaviour. +""" + +import plotly.graph_objects as go +from plotly.subplots import make_subplots +from dash import html, dcc +import dash_mantine_components as dmc +from dash_iconify import DashIconify +import dash_tour_component as dtc +import numpy as np + +from utils import load_data, CHART_LAYOUT, LITH_COLORS, compute_trace_easting_elevation, kpi_card +from components.overview_widgets import collar_map, summary_table, depth_histogram + +# Formation contacts: approximate elevations (m RL) at deposit centre +FORMATION_CONTACTS = [ + {"name": "Alluvium / Weathered Granite", "elev": 382, "color": "#8B6914", "dip_m_per_m": 0.04}, + {"name": "Weathered Granite / Granite", "elev": 350, "color": "#7B5C2A", "dip_m_per_m": 0.06}, + {"name": "Granite / Quartz Diorite", "elev": 290, "color": "#6B4E2A", "dip_m_per_m": 0.08}, + {"name": "Porphyry Top (mineralised)", "elev": 220, "color": "#A0522D", "dip_m_per_m": 0.10}, +] + +AXIS_STYLE = dict( + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + zeroline=False, +) + +CS_TOUR_STEPS = [ + { + "selector": "#cs-chart-paper", + "content": "Welcome to Cross-Section View! Step through to discover all the interactive features on this page.", + "position": "bottom", + }, + { + "selector": "#cross-section-chart", + "content": "Hover anywhere on the chart — a gold cursor line tracks your elevation across all three panels simultaneously. Click once to pin a start elevation, then click again to measure the vertical distance between any two contacts.", + "position": "right", + }, + { + "selector": "#cross-section-chart", + "content": "Drag the Elevation (Y) axis — hover the tick labels on the left edge, then drag up or down to pan the elevation range. Scroll over the axis to zoom into any elevation band. Double-click anywhere to reset.", + "position": "right", + }, + { + "selector": "#cross-section-chart", + "content": "Each of the three panels has its own independent X-axis. Scroll or drag within Section A to zoom its grade range — Sections B and C stay exactly where they are.", + "position": "top", + }, + { + "selector": "#cs-formation-legend", + "content": "These dotted formation contact lines span all three panels simultaneously. Each endpoint is anchored to its own panel axis — zoom Section A and only its segment moves, keeping the geology correct.", + "position": "bottom", + }, +] + + +def _build_figure(collar, survey, orientation="EW"): + """ + Build the cross-section figure with multi-axis formation shapes. + orientation: "EW" groups holes by northing thirds; "NS" by easting thirds. + """ + if orientation == "EW": + sort_col, split_col = "NORTH", "EAST" + x_title = "Easting (m)" + else: + sort_col, split_col = "EAST", "NORTH" + x_title = "Northing (m)" + + sorted_collar = collar.sort_values(sort_col).reset_index(drop=True) + n = len(sorted_collar) + thirds = [ + sorted_collar.iloc[: n // 3], + sorted_collar.iloc[n // 3: 2 * n // 3], + sorted_collar.iloc[2 * n // 3:], + ] + section_labels = ["Section A (South)" if orientation == "EW" else "Section A (West)", + "Section B (Central)", + "Section C (North)" if orientation == "EW" else "Section C (East)"] + + fig = make_subplots( + rows=1, cols=3, + shared_yaxes=False, + column_widths=[0.33, 0.34, 0.33], + subplot_titles=section_labels, + horizontal_spacing=0.04, + ) + + for ann in fig.layout.annotations: + ann.font = dict(size=11, color="#495057") + + colors = ["#1971c2", "#2f9e44", "#e67700", "#c92a2a", "#862e9c", + "#0c8599", "#1864ab", "#5c940d", "#e67700", "#a61e4d"] + + for col_idx, (section_holes, _) in enumerate(zip(thirds, section_labels), start=1): + for hi, (_, hole) in enumerate(section_holes.iterrows()): + east_list, elev_list = compute_trace_easting_elevation( + hole["HOLEID"], collar, survey + ) + x_vals = east_list if orientation == "EW" else [hole["NORTH"]] * len(east_list) + + fig.add_trace(go.Scatter( + x=x_vals, + y=elev_list, + mode="lines", + line=dict(color=colors[hi % len(colors)], width=2), + name=hole["HOLEID"], + hovertemplate=( + f"{hole['HOLEID']}
" + f"{x_title[:-4]}: %{{x:.0f}} m
" + "Elevation RL: %{y:.0f} m" + ), + legendgroup=hole["HOLEID"], + showlegend=(col_idx == 1), + ), row=1, col=col_idx) + + x0 = east_list[0] if orientation == "EW" else hole["NORTH"] + fig.add_trace(go.Scatter( + x=[x0], + y=[elev_list[0]], + mode="markers+text", + marker=dict(color=colors[hi % len(colors)], size=7, symbol="triangle-down"), + text=[hole["HOLEID"]] if hi == 0 else [], + textposition="top center", + textfont=dict(size=7, color="#6c757d"), + showlegend=False, + hoverinfo="skip", + legendgroup=hole["HOLEID"], + ), row=1, col=col_idx) + + # ─── Multi-axis formation contact shapes ───────────────────────────────── + def section_x_range(section_holes): + xs = section_holes["EAST"].tolist() if orientation == "EW" else section_holes["NORTH"].tolist() + if not xs: + return 350000, 350600 + return min(xs) - 20, max(xs) + 20 + + x_ranges = [section_x_range(s) for s in thirds] + mids = [(lo + hi) / 2 for lo, hi in x_ranges] + + # ─── Sentinel traces for plot-wide hover ───────────────────────────────── + # Invisible scatter points spanning the elevation range ensure hoverData + # fires anywhere in the chart, not just near actual hole trace data. + elev_sentinel = list(np.linspace(50, 450, 150)) + for col_idx, x_range in enumerate(x_ranges, start=1): + x_mid = (x_range[0] + x_range[1]) / 2 + fig.add_trace(go.Scatter( + x=[x_mid] * len(elev_sentinel), + y=elev_sentinel, + mode="markers", + marker=dict(opacity=0, size=3), + hoverinfo="skip", + showlegend=False, + ), row=1, col=col_idx) + + # ─── Elevation cursor + measure shapes (one per panel) ──────────────────── + # Each shape anchored to its own yref so they align correctly even when + # panels are zoomed independently. + for cidx, (xref, yref, x_range) in enumerate( + zip(["x", "x2", "x3"], ["y", "y2", "y3"], x_ranges), start=1 + ): + fig.add_shape( + type="line", + x0=x_range[0], x1=x_range[1], + y0=-1000, y1=-1000, + xref=xref, yref=yref, + line=dict(color="#e8a020", width=1.5, dash="dash"), + name=f"elev-cursor-{cidx}", + visible=False, + ) + fig.add_shape( + type="rect", + x0=x_range[0], x1=x_range[1], + y0=0, y1=0, + xref=xref, yref=yref, + fillcolor="rgba(232,160,32,0.12)", + line=dict(color="#e8a020", width=1), + name=f"measure-span-{cidx}", + visible=False, + ) + + for contact in FORMATION_CONTACTS: + elev_base = contact["elev"] + dip = contact["dip_m_per_m"] + color = contact["color"] + + # Elevation at each panel's (lo, hi) x-edge, computed from the dip slope + ys = [ + (elev_base + dip * (x_ranges[i][0] - mids[i]), + elev_base + dip * (x_ranges[i][1] - mids[i])) + for i in range(3) + ] + + # Single multi-axis path traversing both panels and the gaps between them. + # Each coordinate in the path maps to the matching xref entry. + fig.add_shape( + type="path", + path=( + f"M {x_ranges[0][0]} {ys[0][0]} " + f"L {x_ranges[0][1]} {ys[0][1]} " + f"L {x_ranges[1][0]} {ys[1][0]} " + f"L {x_ranges[1][1]} {ys[1][1]} " + f"L {x_ranges[2][0]} {ys[2][0]} " + f"L {x_ranges[2][1]} {ys[2][1]}" + ), + xref=["x", "x", "x2", "x2", "x3", "x3"], + yref=["y", "y", "y2", "y2", "y3", "y3"], + line=dict(color=color, width=1.5, dash="dot"), + layer="below", + ) + + # Label at right edge of col3, anchored to panel 3's own y-axis. + x_col3_right = x_ranges[2][1] + elev_label = ys[2][1] + fig.add_annotation( + x=x_col3_right, + y=elev_label, + xref="x3", yref="y3", + text=contact["name"], + showarrow=False, + xanchor="left", + font=dict(size=9, color=color), + bgcolor="rgba(255,255,255,0.85)", + ) + + # ─── Spanning Mineralised Porphyry Zone rect ───────────────────────────── + porphyry_top = 220 + porphyry_bottom = 90 + + fig.add_shape( + type="rect", + xref=["x", "x3"], + yref=["y", "y3"], + x0=x_ranges[0][0], y0=porphyry_bottom, + x1=x_ranges[2][1], y1=porphyry_top, + fillcolor="rgba(232, 160, 32, 0.10)", + line=dict(color="#e8a020", width=1, dash="dash"), + layer="below", + label=dict( + text="Mineralised Porphyry Zone", + textposition="top left", + font=dict(size=10, color="#d48806", family="Inter, sans-serif"), + padding=6, + ), + ) + + # ─── Layout ────────────────────────────────────────────────────────────── + fig.update_layout(**{ + **CHART_LAYOUT, + "height": 600, + "margin": dict(l=60, r=140, t=50, b=50), + "hovermode": "closest", + "legend": dict( + bgcolor="#ffffff", + bordercolor="#dee2e6", + font=dict(color="#495057", size=9), + orientation="v", + x=1.01, y=1, + ), + "hoverlabel": dict(bgcolor="#ffffff", font_color="#212529", bordercolor="#dee2e6"), + }) + + for col_idx in range(1, 4): + fig.update_yaxes( + title_text="Elevation RL (m)" if col_idx == 1 else None, + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + zeroline=False, + range=[150, 450], + row=1, col=col_idx, + ) + fig.update_xaxes( + title_text=x_title, + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + zeroline=False, + row=1, col=col_idx, + ) + + return fig + + +def layout(): + collar, assay, lith, survey = load_data() + + total_holes = len(collar) + total_meters = int(collar["TOTDEPTH"].sum()) + east_range = collar["EAST"].max() - collar["EAST"].min() + north_range = collar["NORTH"].max() - collar["NORTH"].min() + area_km2 = (east_range * north_range) / 1e6 + + formation_legend = dmc.Group( + id="cs-formation-legend", + gap="md", + children=[ + dmc.Group(gap="xs", children=[ + html.Span(style={ + "display": "inline-block", + "width": "24px", "height": "3px", + "borderTop": f"2px dotted {c['color']}", + "verticalAlign": "middle", + }), + dmc.Text(c["name"], size="xs", c="dimmed"), + ]) + for c in FORMATION_CONTACTS + ], + ) + + feature_chips = dmc.Group(gap="xs", mt="xs", mb="xs", children=[ + dmc.Tooltip( + label="Hover the Elevation (Y) axis tick labels and drag up/down to pan · scroll over the axis to zoom · double-click anywhere to reset", + multiline=True, w=300, withArrow=True, position="bottom", + children=dmc.Badge("↕ Drag Y-Axis", color="blue", variant="light", size="sm", + style={"cursor": "help"}), + ), + ]) + + things_to_try = dmc.Paper([ + dmc.Group(gap="xs", mb="sm", children=[ + DashIconify(icon="tabler:bulb", width=16, color="#e8a020"), + dmc.Text("Things to Try", fw=600, size="sm", c="orange"), + ]), + dmc.Stack(gap="sm", children=[ + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:arrows-up-down", width=14), + size="sm", variant="light", color="blue", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Drag the Elevation (Y) axis", fw=600, size="xs"), + dmc.Text( + "Hover the tick labels on the left edge and drag up or down to pan. " + "Scroll over the axis to zoom into any elevation band.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:zoom", width=14), + size="sm", variant="light", color="teal", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Zoom any single panel independently", fw=600, size="xs"), + dmc.Text( + "Each section panel has its own X-axis. Scroll or drag within Section A — " + "Sections B and C are completely unaffected.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:line-dashed", width=14), + size="sm", variant="light", color="orange", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Watch the formation contacts span all panels", fw=600, size="xs"), + dmc.Text( + "Dotted lines and the Porphyry Zone rect are anchored to each panel's own axis " + "via xref/yref arrays. Zoom Section A — only its segment moves.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:rotate-2", width=14), + size="sm", variant="light", color="gray", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Double-click to reset view", fw=600, size="xs"), + dmc.Text( + "Double-click anywhere on the chart to reset all axes to their default range.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:crosshair", width=14), + size="sm", variant="light", color="grape", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Hover to track elevation · click to pin", fw=600, size="xs"), + dmc.Text( + "A gold cursor line tracks your elevation across all three panels simultaneously. " + "Click anywhere to pin the marker at that elevation.", + size="xs", c="dimmed", + ), + ]), + ]), + ]), + ], p="md", radius="md", withBorder=True, className="tip-paper") + + return [ + dtc.DashTour( + id="cs-tour", + isOpen=False, + accentColor="#e8a020", + rounded=8, + showNumber=True, + steps=CS_TOUR_STEPS, + ), + + dmc.Stack([ + things_to_try, + + dmc.SimpleGrid( + cols={"base": 2, "md": 4}, + spacing="md", + children=[ + kpi_card("Total Holes", str(total_holes), "drillholes in program", icon="tabler:drone"), + kpi_card("Meters Drilled", f"{total_meters:,} m", "cumulative penetration", icon="tabler:ruler-measure"), + kpi_card("Prospect Area", f"{area_km2:.2f} km²", "surface footprint", icon="tabler:map-pin"), + kpi_card("Section Panels", "3", "South · Central · North", icon="tabler:chart-grid-dots"), + ], + ), + + # Cross-section chart card + dmc.Paper([ + dmc.Group([ + html.Div([ + html.P("Cross-Section View", className="section-title"), + html.P( + "Three geographic panels. Drag the Elevation axis to pan · " + "scroll to zoom · hover a panel's X-axis to zoom grade independently.", + className="section-description", + ), + ], style={"flex": 1}), + html.Div( + id="cs-orientation-group", + children=dmc.Group(gap="xs", align="center", children=[ + dmc.Button( + dmc.Group([DashIconify(icon="tabler:help", width=13), "Tour"], + gap=4, align="center"), + id="cs-tour-btn", + variant="subtle", + color="gray", + size="xs", + ), + dmc.SegmentedControl( + id="section-orientation", + data=[ + {"value": "EW", "label": "E–W Sections"}, + {"value": "NS", "label": "N–S Sections"}, + ], + value="EW", + color="orange", + size="xs", + ), + ]), + ), + ], justify="space-between", align="flex-start", wrap="nowrap", mb="xs"), + + # Feature interaction chips + feature_chips, + + formation_legend, + + # Chart with Y-axis hint overlay + html.Div( + style={"position": "relative"}, + children=[ + html.Div( + id="cs-yaxis-hint", + className="y-axis-hint", + children=[ + DashIconify(icon="tabler:arrows-up-down", width=10, color="#adb5bd"), + " drag · scroll to zoom", + ], + ), + dcc.Graph( + id="cross-section-chart", + figure=_build_figure(collar, survey, "EW"), + config={"displayModeBar": True, "scrollZoom": True}, + style={"height": "600px", "marginTop": "8px"}, + ), + ], + ), + ], id="cs-chart-paper", p="md", radius="md", withBorder=True, className="chart-paper"), + + dmc.Grid(gutter="md", children=[ + dmc.GridCol( + dmc.Paper([ + html.P("Collar Plan Map", className="section-title"), + html.P( + "Plan view of drillhole collar positions. Marker colour = total depth drilled. " + "Equal-aspect projection preserves true spatial relationships.", + className="section-description", + ), + dcc.Graph( + figure=collar_map(collar), + config={"displayModeBar": False, "scrollZoom": True}, + ), + ], p="md", radius="md", withBorder=True, className="chart-paper"), + span={"base": 12, "md": 8}, + ), + dmc.GridCol( + dmc.Paper([ + html.P("Hole Summary", className="section-title"), + html.P( + "AZ = azimuth from North. DIP = downhole inclination (negative = sub-vertical).", + className="section-description", + ), + html.Div(summary_table(collar), className="table-scroll"), + dmc.Text( + f"Showing 20 of {total_holes} holes · scroll for more", + size="xs", c="dimmed", mt="xs", + ), + ], p="md", radius="md", withBorder=True, className="chart-paper"), + span={"base": 12, "md": 4}, + ), + ]), + + # Depth distribution + dmc.Paper([ + html.P("Hole Depth Distribution", className="section-title"), + html.P( + "Most holes target the 200–350 m depth range where the Au-Cu mineralized porphyry sits. " + "Shallower holes test the weathered zone; deeper holes test the fresh granite footwall.", + className="section-description", + ), + dcc.Graph(figure=depth_histogram(collar), config={"displayModeBar": False}), + ], p="md", radius="md", withBorder=True, className="chart-paper"), + ], gap="md"), + ] diff --git a/drillholes-demo/pages/downhole_logs.py b/drillholes-demo/pages/downhole_logs.py new file mode 100644 index 0000000..7148832 --- /dev/null +++ b/drillholes-demo/pages/downhole_logs.py @@ -0,0 +1,430 @@ +""" +Downhole Logs page — showcases Plotly.js plot-wide hover/click events. + +Two new-feature demonstrations: +1. Depth cursor: a horizontal gold line that tracks the mouse across ALL + four strip-log panels simultaneously, even over empty areas between + data points (plot-wide hover events via transparent sentinel traces + + clientside callback for zero-latency response). + +2. Click-to-measure: clicking anywhere on the plot (plot-wide click events) + records a start depth, then a second click computes the interval + thickness and draws a shaded span across all panels. +""" + +import plotly.graph_objects as go +from plotly.subplots import make_subplots +from dash import html, dcc +import dash_mantine_components as dmc +from dash_iconify import DashIconify +import dash_tour_component as dtc +import numpy as np +import pandas as pd + +from utils import load_data, CHART_LAYOUT, LITH_COLORS, LITH_ORDER + +DL_TOUR_STEPS = [ + { + "selector": "#strip-log-chart-paper", + "content": "Welcome to Downhole Logs! Step through to discover all the interactive features on this page.", + "position": "bottom", + }, + { + "selector": "#strip-log-chart", + "content": "Hover anywhere on the chart — even over lithology blocks and empty areas — to see a gold dashed cursor track depth across all four panels simultaneously.", + "position": "right", + }, + { + "selector": "#strip-log-chart", + "content": "Click once anywhere to mark a start depth (a gold line snaps to that position). Then click a second time to measure the interval — a shaded span appears across all panels and the exact thickness is shown.", + "position": "right", + }, + { + "selector": "#hole-selector", + "content": "Use this dropdown to switch between drillholes. All four panels update together.", + "position": "bottom", + }, +] + + +def _strip_log_figure(hole_id: str, collar, assay, lith, survey) -> go.Figure: + hole_assay = assay[assay["HOLEID"] == hole_id].sort_values("FROM") + hole_lith = lith[lith["HOLEID"] == hole_id].sort_values("FROM") + hole_survey = survey[survey["HOLEID"] == hole_id].sort_values("DEPTH") + hole_collar = collar[collar["HOLEID"] == hole_id].iloc[0] + + max_depth = float(hole_collar["TOTDEPTH"]) + depth_range = list(np.arange(0, max_depth + 5, 5)) + + fig = make_subplots( + rows=1, cols=4, + shared_yaxes=True, + column_widths=[0.14, 0.30, 0.30, 0.26], + subplot_titles=["Lithology", "Au Grade (g/t)", "Cu Grade (%)", "Hole Deviation (°)"], + horizontal_spacing=0.03, + ) + + for ann in fig.layout.annotations: + ann.font = dict(size=11, color="#495057") + + # ── Col 1: Lithology rectangles ───────────────────────────────────────── + for _, row in hole_lith.iterrows(): + color = LITH_COLORS.get(row["LITHOLOGY"], "#aaa") + fig.add_shape( + type="rect", + x0=0, x1=1, + y0=row["FROM"], y1=row["TO"], + xref="x", yref="y", + fillcolor=color, + line_width=0, + layer="below", + ) + mid = (row["FROM"] + row["TO"]) / 2 + if row["TO"] - row["FROM"] >= 8: + fig.add_annotation( + x=0.5, y=mid, + text=row["LITHOLOGY"], + xref="x", yref="y", + showarrow=False, + font=dict(size=8, color="#212529"), + bgcolor="rgba(255,255,255,0.75)", + borderpad=2, + ) + + # Invisible trace on col1 so axis is registered + fig.add_trace(go.Scatter( + x=[0.5] * len(depth_range), + y=depth_range, + mode="markers", + marker=dict(opacity=0, size=1), + hoverinfo="skip", + showlegend=False, + ), row=1, col=1) + + fig.update_xaxes( + showticklabels=False, showgrid=False, zeroline=False, + range=[0, 1], row=1, col=1, + ) + + # ── Col 2: Au grade bars ───────────────────────────────────────────────── + mid_depths = (hole_assay["FROM"] + hole_assay["TO"]) / 2 + widths = hole_assay["TO"] - hole_assay["FROM"] + + fig.add_trace(go.Bar( + x=hole_assay["Au_ppm"], + y=mid_depths, + orientation="h", + width=widths, + marker=dict( + color=hole_assay["Au_ppm"], + colorscale=[[0, "#f8f9fa"], [0.3, "#e8a020"], [1, "#ff6b35"]], + cmin=0, cmax=float(hole_assay["Au_ppm"].quantile(0.99)), + showscale=False, + line_width=0, + ), + hovertemplate="Depth: %{y:.1f} m
Au: %{x:.3f} g/t", + name="Au (g/t)", + showlegend=False, + ), row=1, col=2) + + # Sentinel trace for hover coverage on col2 + fig.add_trace(go.Scatter( + x=[0] * len(depth_range), y=depth_range, + mode="markers", marker=dict(opacity=0, size=3), + hoverinfo="skip", showlegend=False, + ), row=1, col=2) + + # ── Col 3: Cu grade bars ───────────────────────────────────────────────── + fig.add_trace(go.Bar( + x=hole_assay["Cu_pct"], + y=mid_depths, + orientation="h", + width=widths, + marker=dict( + color=hole_assay["Cu_pct"], + colorscale=[[0, "#f8f9fa"], [0.3, "#FF8C00"], [1, "#ff4444"]], + cmin=0, cmax=float(hole_assay["Cu_pct"].quantile(0.99)), + showscale=False, + line_width=0, + ), + hovertemplate="Depth: %{y:.1f} m
Cu: %{x:.4f} %", + name="Cu (%)", + showlegend=False, + ), row=1, col=3) + + fig.add_trace(go.Scatter( + x=[0] * len(depth_range), y=depth_range, + mode="markers", marker=dict(opacity=0, size=3), + hoverinfo="skip", showlegend=False, + ), row=1, col=3) + + # ── Col 4: Survey dip line ──────────────────────────────────────────────── + fig.add_trace(go.Scatter( + x=hole_survey["DIP"], + y=hole_survey["DEPTH"], + mode="lines+markers", + line=dict(color="#1971c2", width=2), + marker=dict(size=4, color="#1971c2"), + hovertemplate="Depth: %{y:.1f} m
Dip: %{x:.1f}° from vertical", + name="Dip (°)", + showlegend=False, + ), row=1, col=4) + + fig.add_trace(go.Scatter( + x=[hole_survey["DIP"].mean()] * len(depth_range), y=depth_range, + mode="markers", marker=dict(opacity=0, size=3), + hoverinfo="skip", showlegend=False, + ), row=1, col=4) + + # ── Depth cursor shape ────────────────────────────────────────────────── + # xref="paper" spans the full plot width across all 4 panels. + # Updated by a clientside callback on hoverData (plot-wide hover feature). + fig.add_shape( + type="line", + x0=0, x1=1, + y0=-10, y1=-10, + xref="paper", yref="y", + line=dict(color="#e8a020", width=1.5, dash="dash"), + name="depth-cursor", + visible=False, + ) + + # ── Measurement span shape (hidden initially) ──────────────────────────── + fig.add_shape( + type="rect", + x0=0, x1=1, + y0=0, y1=0, + xref="paper", yref="y", + fillcolor="rgba(232,160,32,0.12)", + line=dict(color="#e8a020", width=1), + name="measure-span", + visible=False, + ) + + # ── Layout ──────────────────────────────────────────────────────────────── + fig.update_yaxes( + autorange="reversed", + title_text="Depth (m ↓ downhole)", + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + title_font=dict(color="#495057"), + range=[max_depth + 5, -5], + row=1, col=1, + ) + for col_idx in range(2, 5): + fig.update_xaxes( + showgrid=True, gridcolor="#e9ecef", + tickfont=dict(color="#6c757d"), + zeroline=True, zerolinecolor="#ced4da", + row=1, col=col_idx, + ) + fig.update_xaxes( + title_text="Au (g/t) — gold grade", title_font=dict(color="#495057"), row=1, col=2, + ) + fig.update_xaxes( + title_text="Cu (%) — copper grade", title_font=dict(color="#495057"), row=1, col=3, + ) + fig.update_xaxes( + title_text="Dip (°) from vertical", title_font=dict(color="#495057"), row=1, col=4, + ) + + fig.update_layout(**{ + **CHART_LAYOUT, + "height": 750, + "margin": dict(l=60, r=20, t=40, b=50), + "hovermode": "y", + "hoverdistance": 30, + "bargap": 0, + "bargroupgap": 0, + "hoverlabel": dict(bgcolor="#ffffff", font_color="#212529", bordercolor="#dee2e6"), + }) + + return fig + + +def layout(): + collar, assay, lith, survey = load_data() + hole_ids = sorted(collar["HOLEID"].tolist()) + default_hole = hole_ids[0] + + default_depth = int(collar.loc[collar["HOLEID"] == default_hole, "TOTDEPTH"].iloc[0]) + default_lith_count = int(lith[lith["HOLEID"] == default_hole].shape[0]) + + things_to_try = dmc.Paper([ + dmc.Group(gap="xs", mb="sm", children=[ + DashIconify(icon="tabler:bulb", width=16, color="#e8a020"), + dmc.Text("Things to Try", fw=600, size="sm", c="orange"), + ]), + dmc.Stack(gap="sm", children=[ + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:arrow-move-down", width=14), + size="sm", variant="light", color="orange", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Hover to track depth", fw=600, size="xs"), + dmc.Text( + "The gold depth cursor tracks your mouse across all four panels simultaneously, " + "even over lithology rectangles and empty areas.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:vector-triangle", width=14), + size="sm", variant="light", color="grape", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Click once · click again to measure", fw=600, size="xs"), + dmc.Text( + "Click anywhere to mark a start depth (a gold line appears and the readout confirms it). " + "Click a second time — the shaded span and thickness annotation appear across all panels.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:rotate-2", width=14), + size="sm", variant="light", color="gray", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Clear and restart", fw=600, size="xs"), + dmc.Text( + "Hit the Clear button to dismiss the span and reset to a fresh measurement.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:adjustments-horizontal", width=14), + size="sm", variant="light", color="blue", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Switch drillholes", fw=600, size="xs"), + dmc.Text( + "Use the Hole Selector dropdown to jump between holes — all panels update together.", + size="xs", c="dimmed", + ), + ]), + ]), + ]), + ], p="md", radius="md", withBorder=True, className="tip-paper") + + return [ + dtc.DashTour( + id="dl-tour", + isOpen=False, + accentColor="#e8a020", + rounded=8, + showNumber=True, + steps=DL_TOUR_STEPS, + ), + dmc.Stack([ + things_to_try, + + dmc.SimpleGrid( + cols={"base": 1, "sm": 2}, + spacing="md", + children=[ + dmc.Paper([ + dmc.Group([ + dmc.Text("Current Hole Depth", size="xs", c="dimmed", tt="uppercase", fw=600), + DashIconify(icon="tabler:arrow-down-to-arc", width=16, color="#868e96"), + ], justify="space-between"), + dmc.Text(f"{default_depth} m", id="kpi-hole-depth", size="xl", fw=700, c="dark", mt=4), + dmc.Text("total drilled depth", size="xs", c="dimmed"), + ], p="md", radius="md", withBorder=True, className="kpi-card"), + dmc.Paper([ + dmc.Group([ + dmc.Text("Lithology Intervals", size="xs", c="dimmed", tt="uppercase", fw=600), + DashIconify(icon="tabler:layers-difference", width=16, color="#868e96"), + ], justify="space-between"), + dmc.Text(str(default_lith_count), id="kpi-lith-count", size="xl", fw=700, c="dark", mt=4), + dmc.Text("logged intervals for hole", size="xs", c="dimmed"), + ], p="md", radius="md", withBorder=True, className="kpi-card"), + ], + ), + + # Strip log card + dmc.Paper([ + dmc.Group([ + html.Div([ + html.P("Downhole Strip Log", className="section-title"), + html.P( + "Four-panel strip log: lithology, Au (g/t), Cu (%), hole deviation. " + "Hover anywhere to track depth across all panels. Click once to start an interval, " + "click again to measure its thickness.", + className="section-description", + ), + ], style={"flex": 1}), + html.Div(children=dmc.Group(gap="xs", align="center", children=[ + dmc.Button( + dmc.Group([DashIconify(icon="tabler:help", width=13), "Tour"], + gap=4, align="center"), + id="dl-tour-btn", + variant="subtle", + color="gray", + size="xs", + ), + dmc.Select( + id="hole-selector", + label="Select Hole", + data=[{"value": h, "label": h} for h in hole_ids], + value=default_hole, + w=160, + size="xs", + styles={"label": {"color": "#6c757d", "fontSize": "0.75rem"}}, + ), + ])), + ], justify="space-between", align="flex-end", wrap="nowrap", mb="xs"), + dmc.Group(gap="xs", mt="xs", mb="xs", children=[ + dmc.Tooltip( + label=( + "Click once anywhere on the chart to mark a start depth — " + "a gold line appears. Click a second time to measure the interval " + "and see the thickness." + ), + multiline=True, w=300, withArrow=True, position="bottom", + children=dmc.Badge( + "⊕ Click to Measure", color="orange", variant="light", size="sm", + style={"cursor": "help"}, + ), + ), + ]), + + # Measurement readout + dmc.Group(gap="xs", mb="sm", children=[ + dmc.Text("Interval:", size="sm", c="dimmed"), + html.Div(id="measure-readout", className="measure-readout", + children="Click a depth to start measuring"), + dmc.Button("Clear", id="measure-clear-btn", variant="subtle", + color="gray", size="xs"), + ]), + + dcc.Graph( + id="strip-log-chart", + figure=_strip_log_figure(default_hole, collar, assay, lith, survey), + config={"displayModeBar": True, "scrollZoom": True}, + style={"height": "750px"}, + ), + ], id="strip-log-chart-paper", p="md", radius="md", withBorder=True, className="chart-paper"), + + dmc.Paper([ + html.P("Lithology Key", className="section-title"), + dmc.Group(gap="md", wrap="wrap", children=[ + dmc.Group(gap="xs", children=[ + html.Span(className="lith-swatch", style={"backgroundColor": color}), + dmc.Text(lith_name, size="xs", c="dimmed"), + ]) + for lith_name, color in LITH_COLORS.items() + ]), + ], p="md", radius="md", withBorder=True, className="chart-paper"), + ], gap="md"), + ] diff --git a/drillholes-demo/pages/explorer.py b/drillholes-demo/pages/explorer.py new file mode 100644 index 0000000..62bb50f --- /dev/null +++ b/drillholes-demo/pages/explorer.py @@ -0,0 +1,146 @@ +""" +Explorer page — port of the "Drill-Hole Cross-Section Explorer" CodePen. + +Dash owns the page shell only. The chart (4-hole subplots, multi-axis spanning +geological bands) and all hover/click interactivity are built in +assets/explorer.js using Plotly.js 3.x's hoveranywhere/clickanywhere flags. +The sidebar exposes id-tagged spans the JS writes into directly. +""" + +from dash import html, dcc +import dash_mantine_components as dmc +from dash_iconify import DashIconify + + +def _things_to_try(): + return dmc.Paper([ + dmc.Group(gap="xs", mb="sm", children=[ + DashIconify(icon="tabler:bulb", width=16, color="#e8a020"), + dmc.Text("Things to Try", fw=600, size="sm", c="orange"), + ]), + dmc.Stack(gap="sm", children=[ + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:crosshair", width=14), + size="sm", variant="light", color="grape", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Hover anywhere to track depth", fw=600, size="xs"), + dmc.Text( + "A horizontal crosshair plus depth pill follows the cursor across all four " + "hole panels — including the empty space between them. Powered by Plotly 3.x's " + "hoveranywhere flag.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:layers-intersect", width=14), + size="sm", variant="light", color="orange", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Multi-axis spanning bands", fw=600, size="xs"), + dmc.Text( + "Geological units are quadrilateral paths anchored to consecutive y-axes " + '(yref=["y","y2","y2","y"]) — they connect adjacent subplots automatically ' + "even when each hole has its own axis pair.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:vector-triangle", width=14), + size="sm", variant="light", color="red", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Click two points to measure", fw=600, size="xs"), + dmc.Text( + "Click two depths inside the same hole panel to drop markers and read out the " + "depth interval. A third click resets. Cross-hole clicks are ignored.", + size="xs", c="dimmed", + ), + ]), + ]), + dmc.Group(gap="sm", wrap="nowrap", align="flex-start", children=[ + dmc.ThemeIcon( + DashIconify(icon="tabler:zoom", width=14), + size="sm", variant="light", color="teal", radius="xl", + style={"flexShrink": 0}, + ), + html.Div([ + dmc.Text("Each hole is independent", fw=600, size="xs"), + dmc.Text( + "Every hole has its own x/y axis pair. Pan or zoom one panel without disturbing " + "the others — the spanning geological bands stretch correctly.", + size="xs", c="dimmed", + ), + ]), + ]), + ]), + ], p="md", radius="md", withBorder=True, className="tip-paper") + + +def _sidebar(): + cursor_panel = dmc.Paper([ + dmc.Text("Cursor Position", className="explorer-panel-title"), + html.Div(className="explorer-info-row", children=[ + html.Span("Depth", className="explorer-info-label"), + html.Span("--", id="cursor-depth", className="explorer-info-value"), + ]), + html.Div(className="explorer-info-row", children=[ + html.Span("Hole", className="explorer-info-label"), + html.Span("--", id="cursor-hole", className="explorer-info-value"), + ]), + html.Div(className="explorer-info-row", children=[ + html.Span("Value", className="explorer-info-label"), + html.Span("--", id="cursor-value", className="explorer-info-value"), + ]), + ], p="md", radius="md", withBorder=True, className="chart-paper explorer-info-panel") + + measure_panel = dmc.Paper([ + dmc.Text("Click-to-Measure", className="explorer-panel-title"), + dmc.Text( + "Click two points in the same subplot to measure the depth interval. " + "Click again to reset.", + size="xs", c="dimmed", mb=6, + ), + html.Div(id="distance-result", className="explorer-distance-result"), + ], p="md", radius="md", withBorder=True, className="chart-paper explorer-info-panel") + + return dmc.Stack([cursor_panel, measure_panel], gap="md") + + +def _chart_paper(): + return dmc.Paper([ + html.P("Drill-Hole Cross-Section Explorer", className="section-title"), + html.P( + "Four drill holes side by side. Geological units span between panels via multi-axis " + "shapes. Hover anywhere for the depth crosshair; click two points within one hole to " + "measure interval thickness.", + className="section-description", + ), + html.Div( + id="explorer-chart", + style={"height": "640px", "width": "100%"}, + ), + ], p="md", radius="md", withBorder=True, className="chart-paper") + + +def layout(): + return [ + # Hidden dcc.Graph forces Dash 4 to lazy-load Plotly.js on this page. + # The visible chart is rendered by assets/explorer.js into #explorer-chart. + dcc.Graph(id="_explorer-plotly-loader", figure={}, style={"display": "none"}), + dmc.Stack([ + _things_to_try(), + dmc.Grid(gutter="md", children=[ + dmc.GridCol(_sidebar(), span={"base": 12, "md": 3}), + dmc.GridCol(_chart_paper(), span={"base": 12, "md": 9}), + ]), + ], gap="md"), + ] diff --git a/drillholes-demo/requirements.txt b/drillholes-demo/requirements.txt new file mode 100644 index 0000000..294daa7 --- /dev/null +++ b/drillholes-demo/requirements.txt @@ -0,0 +1,9 @@ +dash>=3.0.0 +dash-ag-grid>=33.0.0 +dash-mantine-components>=0.14.0 +dash-iconify>=0.1.2 +dash-tour-component>=0.0.2 +plotly>=6.0.0 +pandas>=2.0.0 +numpy>=1.26.0 +gunicorn>=21.0.0 diff --git a/drillholes-demo/utils.py b/drillholes-demo/utils.py new file mode 100644 index 0000000..cc0f823 --- /dev/null +++ b/drillholes-demo/utils.py @@ -0,0 +1,210 @@ +import pathlib +from functools import lru_cache +import numpy as np +import pandas as pd +from dash import html +import dash_mantine_components as dmc +from dash_iconify import DashIconify + +PATH = pathlib.Path(__file__).parent +DATA_PATH = PATH / "data" + +LITH_COLORS = { + "Alluvium": "#C2B280", + "Weathered Granite": "#D4A574", + "Granite": "#9E8B6B", + "Quartz Diorite": "#8B7355", + "Mineralized Porphyry": "#A0522D", + "Fresh Granite": "#6B5B45", +} + +LITH_ORDER = list(LITH_COLORS.keys()) + +CHART_LAYOUT = dict( + paper_bgcolor="#ffffff", + plot_bgcolor="#f8f9fa", + font=dict(family="Inter, sans-serif", size=12, color="#495057"), + margin=dict(l=50, r=20, t=40, b=50), +) + +# Keep alias so any external references still work +DARK_CHART_LAYOUT = CHART_LAYOUT + +GRADE_COLORS = { + "Au_ppm": "#FFD700", + "Cu_pct": "#FF8C00", + "Ag_ppm": "#C0C0C0", +} + +GRADE_LABELS = { + "Au_ppm": "Au (g/t)", + "Cu_pct": "Cu (%)", + "Ag_ppm": "Ag (ppm)", +} + + +@lru_cache(maxsize=1) +def load_data(): + collar = pd.read_csv(DATA_PATH / "collar.csv") + assay = pd.read_csv(DATA_PATH / "assay.csv") + lith = pd.read_csv(DATA_PATH / "lith.csv") + survey = pd.read_csv(DATA_PATH / "survey.csv") + return collar, assay, lith, survey + + +def compute_trace_easting_elevation(hole_id, collar_df, survey_df): + """ + Minimum-curvature method: converts downhole survey (depth, az, dip) + to (easting, elevation) pairs for cross-section plotting. + """ + hole = collar_df[collar_df["HOLEID"] == hole_id].iloc[0] + surveys = survey_df[survey_df["HOLEID"] == hole_id].sort_values("DEPTH").copy() + + e, z = float(hole["EAST"]), float(hole["ELEV"]) + east_list, elev_list = [e], [z] + + prev_depth = 0.0 + prev_az = np.radians(float(hole["AZ"])) + prev_dip = np.radians(abs(float(hole["DIP"]))) + + for _, svy in surveys.iterrows(): + dl = float(svy["DEPTH"]) - prev_depth + if dl <= 0: + continue + az2 = np.radians(float(svy["AZ"])) + dip2 = np.radians(abs(float(svy["DIP"]))) + + dl_cos = (np.cos(dip2 - prev_dip) + - np.sin(prev_dip) * np.sin(dip2) * (1 - np.cos(az2 - prev_az))) + rf = 2.0 / (1.0 + dl_cos) if abs(1.0 + dl_cos) > 0.001 else 1.0 + + de = (dl / 2.0) * (np.sin(prev_dip) * np.sin(prev_az) + + np.sin(dip2) * np.sin(az2)) * rf + dz = -(dl / 2.0) * (np.cos(prev_dip) + np.cos(dip2)) * rf + + e += de + z += dz + east_list.append(round(e, 2)) + elev_list.append(round(z, 2)) + + prev_depth = float(svy["DEPTH"]) + prev_az, prev_dip = az2, dip2 + + return east_list, elev_list + + +NAV_ITEMS = [ + {"label": "Cross-Section", "href": "/", "icon": "tabler:chart-grid-dots", "id": "nav-cross-section"}, + {"label": "Explorer", "href": "/explorer", "icon": "tabler:compass", "id": "nav-explorer"}, + {"label": "Downhole Logs", "href": "/downhole-logs", "icon": "tabler:align-left", "id": "nav-downhole"}, + {"label": "Comparison", "href": "/comparison", "icon": "tabler:columns-3", "id": "nav-comparison"}, + {"label": "Block Model", "href": "/block-model", "icon": "tabler:cube", "id": "nav-block-model"}, +] + + +def create_header(): + brand = dmc.Group([ + html.Img(src="/assets/plotly-logo.png", height=40, alt="Plotly"), + dmc.Divider(orientation="vertical", size="sm"), + html.Div([ + html.P("Drillhole Visualizer", className="brand-title"), + html.P("Western Australia", className="brand-subtitle"), + ]), + ], gap="sm", align="center", wrap="nowrap") + + status = dmc.Group([ + dmc.Group([ + DashIconify(icon="tabler:circle-filled", width=10, color="#40c057"), + dmc.Text("Active", size="xs", c="dimmed"), + ], gap=4), + dmc.Divider(orientation="vertical", size="sm"), + dmc.Text("Prospect", size="xs", c="dimmed"), + dmc.Badge("WA Au-Cu Porphyry", color="orange", variant="light", size="sm"), + dmc.Divider(orientation="vertical", size="sm"), + dmc.Text("Last Survey", size="xs", c="dimmed"), + dmc.Text("Apr 2026", size="xs", fw=500), + dmc.ActionIcon( + DashIconify(icon="tabler:bell", width=18), + variant="subtle", + color="gray", + size="lg", + ), + ], gap="sm", wrap="nowrap") + + return dmc.Paper( + dmc.Group([brand, status], justify="space-between", align="center"), + px="md", + py="sm", + radius=0, + withBorder=False, + className="app-header", + ) + + +def create_nav_sidebar(): + nav_links = [ + dmc.NavLink( + label=item["label"], + leftSection=DashIconify(icon=item["icon"], width=16), + href=item["href"], + id=item["id"], + variant="subtle", + ) + for item in NAV_ITEMS + ] + + return html.Div( + [ + dmc.Group( + [ + dmc.Text("Navigation", id="sidebar-title", size="xs", fw=600, c="dimmed", tt="uppercase"), + dmc.ActionIcon( + DashIconify(icon="charm:cross", width=14, id="sidebar-btn-icon"), + id="sidebar-btn", + size="sm", + variant="subtle", + color="gray", + ), + ], + id="sidebar-title-div", + justify="space-between", + align="center", + className="title-pad space-between", + ), + html.Div( + [ + dmc.Space(h="35vh"), + html.Div( + html.Div("▾ Navigation ▾", className="sidebar-collapsed-title"), + style={"transform": "rotate(270deg)"}, + ), + ], + id="sidebar-collapsed-title-div", + style={"display": "none"}, + ), + html.Div( + html.Div( + html.Div(nav_links, id="sidebar-inner-div", className="sidebar-inner"), + id="sidebar-outer-div", + className="sidebar-outer", + ), + id="sidebar-btn-div", + ), + ], + id="filter-sidebar", + className="filter-sidebar flex-column", + ) + + +def kpi_card(title, value, unit="", icon=None): + header_children = [ + dmc.Text(title, size="xs", c="dimmed", tt="uppercase", fw=600), + ] + if icon: + header_children.append(DashIconify(icon=icon, width=16, color="#868e96")) + + return dmc.Paper([ + dmc.Group(header_children, justify="space-between", align="center"), + dmc.Text(value, size="xl", fw=700, c="dark", mt=4), + dmc.Text(unit, size="xs", c="dimmed") if unit else None, + ], p="md", radius="md", withBorder=True, className="kpi-card") diff --git a/investments-dashboard/Procfile b/investments-dashboard/Procfile new file mode 100644 index 0000000..673048e --- /dev/null +++ b/investments-dashboard/Procfile @@ -0,0 +1 @@ +web: uvicorn app:server --host 0.0.0.0 --port 8000 diff --git a/investments-dashboard/app.py b/investments-dashboard/app.py new file mode 100644 index 0000000..3bbc775 --- /dev/null +++ b/investments-dashboard/app.py @@ -0,0 +1,230 @@ +import dash +from dash import html, dcc, Input, Output, callback +import dash_mantine_components as dmc +from dash_iconify import DashIconify + +from pages import dashboard, performance, portfolio, fees +from callbacks import dashboard as dashboard_callbacks +from callbacks import performance as performance_callbacks +from callbacks import portfolio as portfolio_callbacks +from callbacks import fees as fees_callbacks +from callbacks import export_all as export_all_callbacks + +app = dash.Dash( + __name__, + backend="fastapi", + websocket_callbacks=True, + suppress_callback_exceptions=True, + external_stylesheets=dmc.styles.ALL, + title="Investment Insights" +) +server = app.server + +def create_nav_link(icon, label, href): + return dmc.NavLink( + label=label, + leftSection=DashIconify(icon=icon, width=20), + href=href, + variant="subtle", + active=True, + ) + +def create_header(): + return dmc.Paper( + dmc.Group([ + dmc.Group([ + dmc.Title("Investment Insights", order=3), + dmc.Divider(orientation="vertical", size="sm"), + html.Img(src="/assets/DE-logo.png", height=40), + ], gap="sm", align="center", wrap="nowrap"), + dmc.Group([ + dmc.Group([ + DashIconify(icon="tabler:circle-filled", width=10, color="#40c057"), + dmc.Text("Market Open", size="xs", c="dimmed"), + ], gap=4), + dmc.Text("NYSE", size="xs", fw=500), + dmc.Divider(orientation="vertical", size="sm"), + dmc.Text("Last Updated", size="xs", c="dimmed"), + dmc.Text("Apr 8, 2026 3:45 PM", size="xs", fw=500), + dmc.Divider(orientation="vertical", size="sm"), + dmc.Button( + "Download PDF", + id="generate-pdf-all-btn", + size="xs", + variant="light", + color="blue", + leftSection=DashIconify(icon="tabler:file-type-pdf", width=14), + ), + dmc.ActionIcon( + DashIconify(icon="tabler:bell", width=20), + variant="subtle", + size="lg", + ), + ], gap="sm", align="center", wrap="nowrap"), + ], justify="space-between", align="center", wrap="nowrap"), + p="md", + withBorder=True, + radius=0, + ) + +def create_navbar(): + return dmc.Paper( + dmc.Stack([ + dmc.Stack([ + dmc.Text("Navigation", size="xs", c="dimmed", fw=600, tt="uppercase", mb="xs"), + dmc.NavLink( + label="Dashboard", + leftSection=DashIconify(icon="tabler:dashboard", width=20), + href="/", + id="nav-dashboard", + ), + dmc.NavLink( + label="Price Performance", + leftSection=DashIconify(icon="tabler:chart-line", width=20), + href="/performance", + id="nav-performance", + ), + dmc.NavLink( + label="Portfolio Analysis", + leftSection=DashIconify(icon="tabler:chart-donut", width=20), + href="/portfolio", + id="nav-portfolio", + ), + dmc.NavLink( + label="Fees & Distributions", + leftSection=DashIconify(icon="tabler:receipt", width=20), + href="/fees", + id="nav-fees", + ), + dmc.Divider(my="md"), + dmc.Text("Fund Info", size="xs", c="dimmed", fw=600, tt="uppercase", mb="xs"), + dmc.Stack([ + dmc.Group([ + dmc.Text("Fund:", size="sm", c="dimmed"), + dmc.Text("500 Index Fund", size="sm", fw=500), + ], justify="space-between"), + dmc.Group([ + dmc.Text("Category:", size="sm", c="dimmed"), + dmc.Text("Large Blend", size="sm", fw=500), + ], justify="space-between"), + dmc.Group([ + dmc.Text("Expense:", size="sm", c="dimmed"), + dmc.Badge("0.14%", color="green", size="sm"), + ], justify="space-between"), + ], gap="xs"), + dmc.Divider(my="md"), + dmc.Text("Resources", size="xs", c="dimmed", fw=600, tt="uppercase", mb="xs"), + dmc.Anchor( + dmc.NavLink( + label="Prospectus", + leftSection=DashIconify(icon="tabler:file-text", width=18), + rightSection=DashIconify(icon="tabler:external-link", width=14, color="gray"), + variant="subtle", + py=6, + ), + href="https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000036405&type=485&dateb=&owner=include&count=40", + target="_blank", + underline=False, + ), + dmc.Anchor( + dmc.NavLink( + label="Fact Sheet", + leftSection=DashIconify(icon="tabler:file-description", width=18), + rightSection=DashIconify(icon="tabler:external-link", width=14, color="gray"), + variant="subtle", + py=6, + ), + href="https://investor.vanguard.com/investment-products/mutual-funds/profile/vfiax", + target="_blank", + underline=False, + ), + dmc.Anchor( + dmc.NavLink( + label="Annual Report", + leftSection=DashIconify(icon="tabler:report", width=18), + rightSection=DashIconify(icon="tabler:external-link", width=14, color="gray"), + variant="subtle", + py=6, + ), + href="https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000036405&type=N-CSR&dateb=&owner=include&count=40", + target="_blank", + underline=False, + ), + dmc.Anchor( + dmc.NavLink( + label="Tax Documents", + leftSection=DashIconify(icon="tabler:file-invoice", width=18), + rightSection=DashIconify(icon="tabler:external-link", width=14, color="gray"), + variant="subtle", + py=6, + ), + href="https://investor.vanguard.com/client-benefits/tax-center", + target="_blank", + underline=False, + ), + ], gap=4, style={"flex": 1}), + ], gap="md", justify="space-between", h="100%"), + p="md", + h="100%", + withBorder=True, + radius=0, + style={"minWidth": "250px"} + ) + +app.layout = dmc.MantineProvider( + id="mantine-provider", + forceColorScheme="light", + children=[ + dcc.Location(id="url", refresh=False), + dcc.Download(id="download-pdf-all"), + html.Div(id="pdf-status-all", style={"display": "none"}), + dmc.AppShell( + [ + dmc.AppShellHeader(create_header()), + dmc.AppShellNavbar(create_navbar()), + dmc.AppShellMain( + dmc.Container( + id="page-content", + fluid=True, + p="md", + ) + ), + ], + header={"height": 73}, + navbar={"width": 280, "breakpoint": "sm", "collapsed": {"mobile": True}}, + padding="md", + ), + ] +) + +@callback( + Output("page-content", "children"), + Input("url", "pathname") +) +def display_page(pathname): + if pathname == "/performance": + return performance.layout + elif pathname == "/portfolio": + return portfolio.layout + elif pathname == "/fees": + return fees.layout + else: + return dashboard.layout + +@callback( + [Output("nav-dashboard", "active"), + Output("nav-performance", "active"), + Output("nav-portfolio", "active"), + Output("nav-fees", "active")], + Input("url", "pathname") +) +def update_nav_active(pathname): + return [ + pathname == "/" or pathname is None, + pathname == "/performance", + pathname == "/portfolio", + pathname == "/fees", + ] + +if __name__ == "__main__": + app.run(debug=True) diff --git 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z10k|NBN0=wsF=Bp2w6(gAHYQ1V1u8Bd22O&bmhOay-~dk8lfeAbHkCAZno6r?Cmcd zqE{^%SK0v@Z9+KV%WWXGg+*TZ7Guu`>ox20Kyh}I_*ed#uFRL1gM03fWVAW=I?ECU zZ7ij6Ak0q9pPMR5o)N+$^5SS?z*9%Axln53ksI1Kzemzhbp82>RZOcQ0YGQ9b%4Jt z&`ml^vIFP|^rc5956_-eTbD5^UTm@CriN2>{Wjc8KA>&?Y-&heE?mgqO${v?nsd+M zEBs(m>z-U8w~IyDWC2I;}nfX2uN?T 0 else "↓" + trend_value = f"{trend_icon} {abs(metrics['period_return']):.1f}% {period}" + trend_color = "teal" if metrics['period_return'] > 0 else "red" + + period_labels = {"1Y": "1 Year", "3Y": "3 Year", "5Y": "5 Year", "10Y": "10 Year", "All": "All Time"} + period_title = f"{period_labels.get(period, period)} Return" + + period_return_map = {"1Y": metrics['1y_return'], "3Y": metrics['3y_return'], + "5Y": metrics['5y_return'], "10Y": metrics['10y_return'], "All": metrics['period_return']} + period_value = f"{period_return_map.get(period, metrics['1y_return']):.2f}%" + + growth_chart = create_dynamic_growth_chart(fund, investment, show_benchmark) + + return ( + nav_value, + trend_value, + trend_color, + period_value, + period_title, + "vs S&P 500", + metrics['expense_ratio'], + metrics['category'], + metrics['asset_class'], + growth_chart, + f"{metrics['1y_return']:.2f}%", + f"{metrics['3y_return']:.2f}%", + f"{metrics['5y_return']:.2f}%", + metrics['min_investment'].replace('"', ''), + risk['volatility_pct'], + risk['volatility_level'], + risk['beta_pct'], + f"{risk['beta']:.2f}", + risk['sharpe_pct'], + f"{risk['sharpe']:.2f}", + risk['alpha_pct'], + f"{risk['alpha']:.2f}%", + ) + +@callback( + Output("live-streaming", "data"), + Input("live-toggle", "checked"), +) +def toggle_streaming(checked): + return checked + + +@callback(persistent=True) +async def stream_market_prices(): + ws = ctx.websocket + prices = {"AAPL": 189.50, "GOOGL": 176.30, "MSFT": 420.15, "AMZN": 185.60, "TSLA": 178.90} + base_prices = dict(prices) + history = {s: [p] for s, p in prices.items()} + + while not ws.is_shutdown: + streaming = await ws.get_prop("live-streaming", "data") + if streaming: + for sym in prices: + change_pct = round(random.gauss(0, 0.3), 2) + prices[sym] = round(prices[sym] * (1 + change_pct / 100), 2) + history[sym].append(prices[sym]) + if len(history[sym]) > 30: + history[sym] = history[sym][-30:] + + dollar_change = round(prices[sym] - base_prices[sym], 2) + total_pct = round((prices[sym] - base_prices[sym]) / base_prices[sym] * 100, 2) + sign = "+" if dollar_change >= 0 else "" + color = "#40c057" if dollar_change >= 0 else "#fa5252" + + set_props(f"live-price-{sym}", {"children": f"${prices[sym]:.2f}"}) + set_props(f"live-change-{sym}", { + "children": f"{sign}{dollar_change:.2f} ({sign}{total_pct:.2f}%)", + "style": {"color": color}, + }) + + selected = await ws.get_prop("sparkline-symbol", "value") + if selected and selected in history: + fig = create_sparkline(history[selected], selected) + set_props("sparkline-chart", {"figure": fig}) + + await asyncio.sleep(1) + else: + await asyncio.sleep(0.5) + + diff --git a/investments-dashboard/callbacks/export_all.py b/investments-dashboard/callbacks/export_all.py new file mode 100644 index 0000000..42067e3 --- /dev/null +++ b/investments-dashboard/callbacks/export_all.py @@ -0,0 +1,56 @@ +from datetime import datetime + +from dash import callback, Input, Output, dcc, html + +from utils.pdf_export import create_pdf_report +from utils.data_loader import get_time_series_data, get_sector_allocation +from components.charts import ( + create_hypothetical_growth_chart, + create_performance_line_chart, + create_sector_donut_chart, + create_fee_comparison_chart, +) +from pages.performance import create_drawdown_chart + + +@callback( + Output("download-pdf-all", "data"), + Output("pdf-status-all", "children"), + Input("generate-pdf-all-btn", "n_clicks"), + prevent_initial_call=True, +) +def generate_all_pdf(n_clicks): + if not n_clicks: + return None, "" + try: + ts_data = get_time_series_data() + sector_data = get_sector_allocation() + + figures = [ + create_hypothetical_growth_chart().to_dict(), + create_performance_line_chart(ts_data, "Performance Over Time").to_dict(), + create_drawdown_chart(ts_data).to_dict(), + create_sector_donut_chart(sector_data, "Sector Allocation").to_dict(), + create_fee_comparison_chart().to_dict(), + ] + titles = [ + "Hypothetical Growth", + "Price Performance", + "Drawdown Analysis", + "Sector Allocation", + "Fee Comparison", + ] + + pdf_bytes = create_pdf_report( + figures=figures, + titles=titles, + report_title="Investment Report", + ) + filename = f"investment_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf" + return dcc.send_bytes(pdf_bytes, filename), "" + except Exception as e: + import traceback + return None, html.Div( + f"PDF error: {e}\n{traceback.format_exc()}", + style={"color": "red", "white-space": "pre-wrap", "fontSize": "12px"}, + ) diff --git a/investments-dashboard/callbacks/fees.py b/investments-dashboard/callbacks/fees.py new file mode 100644 index 0000000..755e7ab --- /dev/null +++ b/investments-dashboard/callbacks/fees.py @@ -0,0 +1,129 @@ +from dash import callback, Input, Output, State, dcc, html +import plotly.graph_objects as go +import pandas as pd +from datetime import datetime + +from utils.data_loader import get_dividend_history +from components.charts import CHART_COLORS, CHART_LAYOUT + +def calculate_fees(investment, years, fund_expense=0.0014, avg_expense=0.0099, annual_return=0.07): + """Calculate fee impact over time""" + fund_values = [] + avg_values = [] + + fund_value = investment + avg_value = investment + + for _ in range(years): + fund_value *= (1 + annual_return - fund_expense) + avg_value *= (1 + annual_return - avg_expense) + fund_values.append(fund_value) + avg_values.append(avg_value) + + fund_fees = investment * (1 + annual_return) ** years - fund_values[-1] + avg_fees = investment * (1 + annual_return) ** years - avg_values[-1] + savings = avg_fees - fund_fees + + return { + 'fund_values': fund_values, + 'avg_values': avg_values, + 'fund_final': fund_values[-1], + 'avg_final': avg_values[-1], + 'fund_fees': fund_fees, + 'avg_fees': avg_fees, + 'savings': savings + } + +def create_dynamic_fee_comparison(investment, years): + """Create fee comparison chart with custom investment amount""" + results = calculate_fees(investment, years) + + fig = go.Figure() + + fig.add_trace(go.Bar( + x=['Category Average', 'This Fund'], + y=[results['avg_fees'], results['fund_fees']], + marker_color=[CHART_COLORS['gray'], CHART_COLORS['primary']], + text=[f"${results['avg_fees']:,.0f}", f"${results['fund_fees']:,.0f}"], + textposition='outside', + )) + + fig.add_annotation( + x=1, y=results['fund_fees'] + results['savings'] * 0.15, + text=f"Save ${results['savings']:,.0f}", + showarrow=True, + arrowhead=2, + arrowcolor=CHART_COLORS['secondary'], + font={'color': CHART_COLORS['secondary'], 'weight': 600}, + ) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': f'Fees on ${investment:,} Over {years} Years', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': '$', 'tickformat': ','}, + showlegend=False, + ) + + return fig + +def create_dynamic_cost_impact(investment, years): + """Create cost impact chart with custom parameters""" + all_years = list(range(1, years + 1)) + results = calculate_fees(investment, years) + + fig = go.Figure() + + fig.add_trace(go.Scatter( + x=all_years, + y=results['avg_values'], + name='Category Avg (0.99%)', + line={'color': CHART_COLORS['gray'], 'width': 2}, + )) + + fig.add_trace(go.Scatter( + x=all_years, + y=results['fund_values'], + name='This Fund (0.14%)', + line={'color': CHART_COLORS['primary'], 'width': 2}, + fill='tonexty', + fillcolor='rgba(34, 139, 230, 0.1)', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': f'Long-Term Cost Impact (7% annual return)', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + xaxis={'title': 'Years'}, + yaxis={'title': 'Portfolio Value', 'tickprefix': '$', 'tickformat': ','}, + legend={'orientation': 'h', 'y': -0.15}, + ) + + return fig + +@callback( + [Output("fee-comparison-chart", "figure"), + Output("cost-impact-chart", "figure"), + Output("savings-amount", "children"), + Output("final-value-fund", "children"), + Output("final-value-avg", "children")], + [Input("investment-amount", "value"), + Input("time-horizon", "value")] +) +def update_fee_calculations(amount, years): + if amount is None or amount <= 0: + amount = 10000 + if years is None or years <= 0: + years = 10 + + results = calculate_fees(amount, years) + + fee_chart = create_dynamic_fee_comparison(amount, years) + cost_chart = create_dynamic_cost_impact(amount, years) + + return ( + fee_chart, + cost_chart, + f"${results['savings']:,.0f}", + f"${results['fund_final']:,.0f}", + f"${results['avg_final']:,.0f}" + ) + diff --git a/investments-dashboard/callbacks/performance.py b/investments-dashboard/callbacks/performance.py new file mode 100644 index 0000000..b042c18 --- /dev/null +++ b/investments-dashboard/callbacks/performance.py @@ -0,0 +1,341 @@ +from dash import callback, Input, Output, State, dcc, html +import plotly.graph_objects as go +import pandas as pd +from datetime import datetime, timedelta + +from utils.data_loader import get_time_series_data +from components.charts import CHART_COLORS, CHART_LAYOUT + +BENCHMARK_COLUMNS = { + "calibre": ("Calibre Index Fund", CHART_COLORS['primary']), + "msci": ("MSCI EAFE Index Fund (ETF)", CHART_COLORS['secondary']), + "sp500": ('"S&P 500 Index, y"', CHART_COLORS['tertiary']), +} + +BENCHMARK_LABELS = { + "calibre": "Calibre Index Fund", + "msci": "MSCI EAFE Index", + "sp500": "S&P 500", +} + +def calculate_date_range_from_period(period, df): + """Calculate date range based on period selector""" + if period == "All" or not period: + return None + + end_date = df['Date'].max() + + period_map = { + "1M": timedelta(days=30), + "3M": timedelta(days=90), + "6M": timedelta(days=180), + "1Y": timedelta(days=365), + "3Y": timedelta(days=365 * 3), + "5Y": timedelta(days=365 * 5), + } + + delta = period_map.get(period, timedelta(days=365)) + start_date = end_date - delta + + return [start_date.strftime('%Y-%m-%d'), end_date.strftime('%Y-%m-%d')] + +def filter_data_by_date(df, date_range): + """Filter dataframe by date range""" + if date_range and len(date_range) == 2 and date_range[0] and date_range[1]: + start_date = pd.to_datetime(date_range[0]) + end_date = pd.to_datetime(date_range[1]) + return df[(df['Date'] >= start_date) & (df['Date'] <= end_date)] + return df + +def normalize_series(df, columns): + """Normalize series to start at 100""" + normalized_df = df.copy() + for col in columns: + if col in normalized_df.columns: + first_val = normalized_df[col].iloc[0] + if first_val != 0: + normalized_df[col] = (normalized_df[col] / first_val) * 100 + return normalized_df + +def calculate_moving_average(df, col_name, window): + """Calculate moving average""" + if col_name in df.columns and window > 0: + return df[col_name].rolling(window=window).mean() + return None + +def calculate_performance_metrics(df, col_name): + """Calculate volatility, max drawdown, Sharpe, best/worst day""" + if col_name not in df.columns or len(df) < 2: + return { + 'volatility': 0, 'max_drawdown': 0, 'sharpe': 0, + 'best_day': 0, 'worst_day': 0 + } + + returns = df[col_name].pct_change().dropna() + + if len(returns) == 0: + return { + 'volatility': 0, 'max_drawdown': 0, 'sharpe': 0, + 'best_day': 0, 'worst_day': 0 + } + + volatility = returns.std() * (252 ** 0.5) * 100 + + prices = df[col_name].values + peak = prices[0] + max_dd = 0 + for price in prices: + if price > peak: + peak = price + dd = (price - peak) / peak * 100 + if dd < max_dd: + max_dd = dd + + risk_free = 0.02 + excess = returns.mean() * 252 - risk_free + std_ann = returns.std() * (252 ** 0.5) + sharpe = excess / std_ann if std_ann > 0 else 0 + + best_day = returns.max() * 100 + worst_day = returns.min() * 100 + + return { + 'volatility': volatility, + 'max_drawdown': max_dd, + 'sharpe': sharpe, + 'best_day': best_day, + 'worst_day': worst_day + } + +def create_dynamic_performance_chart(df, benchmarks, normalize=False, ma_period=None, log_scale=False, title="Performance Over Time"): + """Create performance chart with selected benchmarks, normalization, MA, and log scale""" + fig = go.Figure() + + columns_to_plot = [] + for benchmark in benchmarks: + if benchmark in BENCHMARK_COLUMNS: + col_name, _ = BENCHMARK_COLUMNS[benchmark] + if col_name in df.columns: + columns_to_plot.append(col_name) + + plot_df = df.copy() + if normalize and columns_to_plot: + plot_df = normalize_series(plot_df, columns_to_plot) + + for benchmark in benchmarks: + if benchmark in BENCHMARK_COLUMNS: + col_name, color = BENCHMARK_COLUMNS[benchmark] + if col_name in plot_df.columns: + fig.add_trace(go.Scatter( + x=plot_df['Date'], + y=plot_df[col_name], + name=BENCHMARK_LABELS.get(benchmark, benchmark), + line={'color': color, 'width': 2}, + hovertemplate='%{y:.2f}' + )) + + if ma_period and ma_period != "none": + window = int(ma_period) + ma = calculate_moving_average(plot_df, col_name, window) + if ma is not None: + fig.add_trace(go.Scatter( + x=plot_df['Date'], + y=ma, + name=f"{BENCHMARK_LABELS.get(benchmark, benchmark)} {window}MA", + line={'color': color, 'width': 1, 'dash': 'dot'}, + hovertemplate='%{y:.2f}' + )) + + y_prefix = '' if normalize else '$' + y_type = 'log' if log_scale else 'linear' + + fig.update_layout( + **CHART_LAYOUT, + title={'text': title, 'x': 0, 'font': {'size': 16, 'weight': 600}}, + legend={'orientation': 'h', 'y': -0.15}, + xaxis={ + 'showgrid': True, + 'gridcolor': 'rgba(0,0,0,0.05)', + }, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': y_prefix, 'type': y_type}, + ) + + return fig + +def create_dynamic_drawdown_chart(df, benchmarks, show_all=False): + """Calculate and plot drawdown for selected benchmarks""" + fig = go.Figure() + + colors = [CHART_COLORS['danger'], CHART_COLORS['secondary'], CHART_COLORS['tertiary']] + fill_colors = ['rgba(250, 82, 82, 0.2)', 'rgba(64, 192, 87, 0.15)', 'rgba(250, 176, 5, 0.15)'] + + benchmarks_to_show = benchmarks if show_all else [benchmarks[0]] if benchmarks else ["calibre"] + + for idx, benchmark in enumerate(benchmarks_to_show): + col_name = BENCHMARK_COLUMNS.get(benchmark, BENCHMARK_COLUMNS["calibre"])[0] + + if col_name not in df.columns: + continue + + prices = df[col_name].values + peak = prices[0] + drawdowns = [] + + for price in prices: + if price > peak: + peak = price + drawdown = (price - peak) / peak * 100 + drawdowns.append(drawdown) + + color = colors[idx % len(colors)] + fill = fill_colors[idx % len(fill_colors)] if idx == 0 else 'rgba(0,0,0,0)' + + fig.add_trace(go.Scatter( + x=df['Date'], + y=drawdowns, + fill='tozeroy' if idx == 0 else 'none', + line={'color': color, 'width': 2 if idx == 0 else 1}, + fillcolor=fill, + name=BENCHMARK_LABELS.get(benchmark, benchmark), + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Drawdown Analysis', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'ticksuffix': '%'}, + showlegend=len(benchmarks_to_show) > 1, + legend={'orientation': 'h', 'y': -0.15}, + ) + return fig + +def create_rolling_returns_chart(df, benchmarks, show_all=False, window=252): + """Create rolling returns chart for selected benchmarks""" + fig = go.Figure() + + if len(df) < window + 1: + fig.update_layout( + **CHART_LAYOUT, + title={'text': f'Rolling 1-Year Returns', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + annotations=[{'text': 'Insufficient data for rolling calculation', 'showarrow': False, 'x': 0.5, 'y': 0.5, 'xref': 'paper', 'yref': 'paper'}] + ) + return fig + + benchmarks_to_show = benchmarks if show_all else [benchmarks[0]] if benchmarks else ["calibre"] + + for idx, benchmark in enumerate(benchmarks_to_show): + col_name, color = BENCHMARK_COLUMNS.get(benchmark, BENCHMARK_COLUMNS["calibre"]) + + if col_name not in df.columns: + continue + + rolling_returns = (df[col_name] / df[col_name].shift(window) - 1) * 100 + + fill = 'tozeroy' if idx == 0 else 'none' + fill_color = 'rgba(34, 139, 230, 0.15)' if idx == 0 else 'rgba(0,0,0,0)' + + fig.add_trace(go.Scatter( + x=df['Date'], + y=rolling_returns, + fill=fill, + line={'color': color, 'width': 2 if idx == 0 else 1}, + fillcolor=fill_color, + name=BENCHMARK_LABELS.get(benchmark, benchmark), + )) + + fig.add_hline(y=0, line_dash="dash", line_color="gray", line_width=1) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': f'Rolling 1-Year Returns', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'ticksuffix': '%'}, + showlegend=len(benchmarks_to_show) > 1, + legend={'orientation': 'h', 'y': -0.15}, + ) + return fig + +def calculate_stats(df, col_name="Calibre Index Fund"): + """Calculate stats for the filtered data""" + if col_name not in df.columns: + col_name = "Calibre Index Fund" + + high_val = df[col_name].max() + high_date = df.loc[df[col_name].idxmax(), 'Date'] + + low_val = df[col_name].min() + low_date = df.loc[df[col_name].idxmin(), 'Date'] + + current_val = df[col_name].iloc[-1] + + total_return = ((df[col_name].iloc[-1] - df[col_name].iloc[0]) / df[col_name].iloc[0]) * 100 + + return { + 'high': high_val, + 'high_date': high_date, + 'low': low_val, + 'low_date': low_date, + 'current': current_val, + 'total_return': total_return + } + +@callback( + [Output("performance-chart", "figure"), + Output("drawdown-chart", "figure"), + Output("rolling-returns-chart", "figure"), + Output("period-high-value", "children"), + Output("period-high-date", "children"), + Output("period-low-value", "children"), + Output("period-low-date", "children"), + Output("current-price-value", "children"), + Output("total-return-value", "children"), + Output("total-return-value", "c"), + Output("perf-volatility", "children"), + Output("perf-max-drawdown", "children"), + Output("perf-sharpe", "children"), + Output("perf-best-day", "children"), + Output("perf-worst-day", "children")], + [Input("benchmark-selector", "value"), + Input("performance-period", "value"), + Input("normalize-toggle", "checked"), + Input("ma-selector", "value"), + Input("log-scale-toggle", "checked")] +) +def update_performance(benchmarks, period, normalize, ma_period, log_scale): + df = get_time_series_data() + + date_range = calculate_date_range_from_period(period, df) + filtered_df = filter_data_by_date(df, date_range) + + if not benchmarks: + benchmarks = ["calibre"] + + primary_benchmark = benchmarks[0] if benchmarks else "calibre" + col_name = BENCHMARK_COLUMNS.get(primary_benchmark, BENCHMARK_COLUMNS["calibre"])[0] + + perf_chart = create_dynamic_performance_chart(filtered_df, benchmarks, normalize, ma_period, log_scale) + drawdown_chart = create_dynamic_drawdown_chart(filtered_df, benchmarks, show_all=normalize) + rolling_chart = create_rolling_returns_chart(filtered_df, benchmarks, show_all=normalize) + + stats = calculate_stats(filtered_df, col_name) + metrics = calculate_performance_metrics(filtered_df, col_name) + + high_date_str = stats['high_date'].strftime('%Y-%m-%d') if hasattr(stats['high_date'], 'strftime') else str(stats['high_date']) + low_date_str = stats['low_date'].strftime('%Y-%m-%d') if hasattr(stats['low_date'], 'strftime') else str(stats['low_date']) + + return ( + perf_chart, + drawdown_chart, + rolling_chart, + f"${stats['high']:.2f}", + high_date_str, + f"${stats['low']:.2f}", + low_date_str, + f"${stats['current']:.2f}", + f"{stats['total_return']:.1f}%", + "green" if stats['total_return'] > 0 else "red", + f"{metrics['volatility']:.1f}%", + f"{metrics['max_drawdown']:.1f}%", + f"{metrics['sharpe']:.2f}", + f"+{metrics['best_day']:.1f}%", + f"{metrics['worst_day']:.1f}%", + ) + diff --git a/investments-dashboard/callbacks/portfolio.py b/investments-dashboard/callbacks/portfolio.py new file mode 100644 index 0000000..418bccf --- /dev/null +++ b/investments-dashboard/callbacks/portfolio.py @@ -0,0 +1,192 @@ +from dash import callback, Input, Output, State, dcc, html +import plotly.graph_objects as go +import plotly.express as px +from datetime import datetime + +from utils.data_loader import get_sector_allocation +from components.charts import CHART_COLORS, CHART_LAYOUT + +sector_data = get_sector_allocation() + +def create_sector_bar_with_highlight(highlighted_sector=None): + """Create sector bar chart with optional highlight""" + fig = go.Figure() + + colors = [CHART_COLORS['primary'] if (highlighted_sector is None or s == highlighted_sector) + else 'rgba(34, 139, 230, 0.3)' + for s in sector_data['Sector']] + + fig.add_trace(go.Bar( + y=sector_data['Sector'], + x=sector_data['Fund'], + name='Fund', + orientation='h', + marker_color=colors, + )) + + benchmark_colors = [CHART_COLORS['gray'] if (highlighted_sector is None or s == highlighted_sector) + else 'rgba(134, 142, 150, 0.3)' + for s in sector_data['Sector']] + + fig.add_trace(go.Bar( + y=sector_data['Sector'], + x=sector_data['Benchmark'], + name='Benchmark', + orientation='h', + marker_color=benchmark_colors, + )) + + title = 'Sector Allocation vs Benchmark' + if highlighted_sector: + title = f'Sector Allocation - {highlighted_sector} Highlighted' + + fig.update_layout( + **CHART_LAYOUT, + title={'text': title, 'x': 0, 'font': {'size': 16, 'weight': 600}}, + barmode='group', + bargap=0.3, + legend={'orientation': 'h', 'y': -0.15}, + xaxis={'title': 'Allocation %', 'ticksuffix': '%'}, + yaxis={'title': ''}, + height=450, + ) + + return fig + +@callback( + [Output("allocation-view", "style"), + Output("characteristics-view", "style"), + Output("risk-view", "style")], + Input("portfolio-view", "value") +) +def switch_portfolio_view(view): + """Switch between allocation, characteristics, and risk views""" + hidden = {"display": "none"} + visible = {"display": "block"} + + if view == "allocation": + return visible, hidden, hidden + elif view == "characteristics": + return hidden, visible, hidden + else: + return hidden, hidden, visible + +@callback( + Output("sector-bar-chart", "figure"), + Input("sector-donut", "clickData"), + State("sector-donut", "figure"), + prevent_initial_call=True +) +def highlight_sector(click_data, current_figure): + """Highlight selected sector in bar chart (synced with donut toggle)""" + if click_data and 'points' in click_data: + selected_idx = click_data['points'][0].get('pointNumber', None) + sector_name = click_data['points'][0].get('label', None) + + current_pull = current_figure.get('data', [{}])[0].get('pull', []) + already_selected = ( + current_pull and + selected_idx is not None and + len(current_pull) > selected_idx and + current_pull[selected_idx] > 0 + ) + + if not already_selected: + return create_sector_bar_with_highlight(sector_name) + return create_sector_bar_with_highlight(None) + +@callback( + Output("sector-detail-text", "children"), + Input("sector-donut", "clickData"), + State("sector-donut", "figure") +) +def update_sector_detail(click_data, current_figure): + """Show sector details when clicked (synced with donut toggle)""" + if click_data and 'points' in click_data: + point = click_data['points'][0] + selected_idx = point.get('pointNumber', None) + sector = point.get('label', 'Unknown') + value = point.get('value', 0) + + current_pull = current_figure.get('data', [{}])[0].get('pull', []) if current_figure else [] + already_selected = ( + current_pull and + selected_idx is not None and + len(current_pull) > selected_idx and + current_pull[selected_idx] > 0 + ) + + if not already_selected: + return f"Selected: {sector} ({value:.1f}% allocation)" + return "Click on a sector to see details" + +@callback( + Output("sector-donut", "figure"), + Input("sector-donut", "clickData"), + State("sector-donut", "figure"), + prevent_initial_call=True +) +def highlight_donut_sector(click_data, current_figure): + """Highlight selected sector in donut chart (click again to reset)""" + import re + colors = px.colors.qualitative.Set3[:len(sector_data)] + + pull_values = [0] * len(sector_data) + opacities = [1] * len(sector_data) + + if click_data and 'points' in click_data: + selected_idx = click_data['points'][0].get('pointNumber', None) + if selected_idx is not None: + current_pull = current_figure.get('data', [{}])[0].get('pull', []) + already_selected = ( + current_pull and + len(current_pull) > selected_idx and + current_pull[selected_idx] > 0 + ) + + if not already_selected: + pull_values = [0.15 if i == selected_idx else 0 for i in range(len(sector_data))] + opacities = [1 if i == selected_idx else 0.4 for i in range(len(sector_data))] + + adjusted_colors = [] + for i, c in enumerate(colors): + if c.startswith('rgb('): + rgb_match = re.match(r'rgb\((\d+),\s*(\d+),\s*(\d+)\)', c) + if rgb_match: + r, g, b = rgb_match.groups() + adjusted_colors.append(f'rgba({r}, {g}, {b}, {opacities[i]})') + else: + adjusted_colors.append(c) + elif c.startswith('#'): + rgb = px.colors.hex_to_rgb(c) + adjusted_colors.append(f'rgba({rgb[0]}, {rgb[1]}, {rgb[2]}, {opacities[i]})') + else: + adjusted_colors.append(c) + + fig = go.Figure(go.Pie( + labels=sector_data['Sector'], + values=sector_data['Fund'], + hole=0.6, + marker={'colors': adjusted_colors, 'line': {'color': 'white', 'width': 2}}, + textinfo='percent', + textposition='outside', + pull=pull_values, + hovertemplate='%{label}
%{value:.1f}%' + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Sector Allocation (Click to highlight)', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + showlegend=True, + legend={'orientation': 'v', 'x': 1.05, 'y': 0.5}, + annotations=[{ + 'text': 'Sectors', + 'x': 0.5, 'y': 0.5, + 'font': {'size': 14, 'weight': 600}, + 'showarrow': False + }] + ) + + return fig + + diff --git a/investments-dashboard/components/__init__.py b/investments-dashboard/components/__init__.py new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/investments-dashboard/components/__init__.py @@ -0,0 +1 @@ + diff --git a/investments-dashboard/components/charts.py b/investments-dashboard/components/charts.py new file mode 100644 index 0000000..9377d30 --- /dev/null +++ b/investments-dashboard/components/charts.py @@ -0,0 +1,232 @@ +import dash_mantine_components as dmc +from dash import dcc +import plotly.graph_objects as go +import plotly.express as px + +CHART_COLORS = { + 'primary': '#228be6', + 'secondary': '#40c057', + 'tertiary': '#fab005', + 'danger': '#fa5252', + 'gray': '#868e96', +} + +CHART_LAYOUT = { + 'paper_bgcolor': 'rgba(0,0,0,0)', + 'plot_bgcolor': 'rgba(0,0,0,0)', + 'font': {'family': 'Inter, sans-serif'}, + 'margin': {'l': 40, 'r': 20, 't': 40, 'b': 40}, + 'hovermode': 'x unified', + 'hoverlabel': { + 'bgcolor': 'white', + 'bordercolor': '#dee2e6', + 'font': {'family': 'Inter, sans-serif', 'size': 13, 'color': '#333'}, + }, +} + +def create_performance_line_chart(df, title="Performance Over Time"): + """Create multi-series line chart for fund performance""" + + fig = go.Figure() + + fig.add_trace(go.Scatter( + x=df['Date'], + y=df['Calibre Index Fund'], + name='Calibre Index Fund', + line={'color': CHART_COLORS['primary'], 'width': 2}, + hovertemplate='%{y:.2f}' + )) + + fig.add_trace(go.Scatter( + x=df['Date'], + y=df['MSCI EAFE Index Fund (ETF)'], + name='MSCI EAFE Index', + line={'color': CHART_COLORS['secondary'], 'width': 2}, + hovertemplate='%{y:.2f}' + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': title, 'x': 0, 'font': {'size': 16, 'weight': 600}}, + legend={'orientation': 'h', 'y': -0.15}, + xaxis={ + 'showgrid': True, + 'gridcolor': 'rgba(0,0,0,0.05)', + 'rangeselector': { + 'buttons': [ + {'count': 1, 'label': '1M', 'step': 'month'}, + {'count': 6, 'label': '6M', 'step': 'month'}, + {'count': 1, 'label': 'YTD', 'step': 'year', 'stepmode': 'todate'}, + {'count': 1, 'label': '1Y', 'step': 'year'}, + {'count': 3, 'label': '3Y', 'step': 'year'}, + {'count': 5, 'label': '5Y', 'step': 'year'}, + {'step': 'all', 'label': 'All'} + ], + 'bgcolor': 'rgba(0,0,0,0.02)', + 'activecolor': CHART_COLORS['primary'], + }, + 'rangeslider': {'visible': False}, + }, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': '$'}, + ) + fig.update_layout(margin={'l': 40, 'r': 20, 't': 100, 'b': 40}) + + return fig + +def create_sparkline(prices, symbol=""): + """Minimal area sparkline for live price history""" + color = CHART_COLORS['secondary'] if len(prices) > 1 and prices[-1] >= prices[0] else CHART_COLORS['danger'] + hex_to_rgba = lambda c, a: f"rgba({int(c[1:3],16)},{int(c[3:5],16)},{int(c[5:7],16)},{a})" + + fig = go.Figure(go.Scatter( + y=prices, + mode='lines', + fill='tozeroy', + line={'color': color, 'width': 2.5}, + fillcolor=hex_to_rgba(color, 0.15), + hovertemplate='$%{y:.2f}', + )) + + if len(prices) > 1: + ymin, ymax = min(prices), max(prices) + padding = max((ymax - ymin) * 0.3, 0.10) + yrange = [ymin - padding, ymax + padding] + else: + yrange = None + + fig.update_layout( + paper_bgcolor='rgba(0,0,0,0)', + plot_bgcolor='rgba(0,0,0,0)', + font={'family': 'Inter, sans-serif'}, + margin={'l': 0, 'r': 0, 't': 20, 'b': 0}, + xaxis={'visible': False}, + yaxis={'visible': False, 'range': yrange}, + showlegend=False, + title={'text': symbol, 'x': 0, 'font': {'size': 13, 'weight': 600}}, + hovermode='x unified', + ) + return fig + +def create_sector_donut_chart(sector_data, title="Sector Allocation"): + """Create donut chart for sector allocation""" + + colors = px.colors.qualitative.Set3[:len(sector_data)] + + fig = go.Figure(go.Pie( + labels=sector_data['Sector'], + values=sector_data['Fund'], + hole=0.6, + marker={'colors': colors}, + textinfo='percent', + textposition='outside', + hovertemplate='%{label}
%{value:.1f}%' + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': title, 'x': 0, 'font': {'size': 16, 'weight': 600}}, + showlegend=True, + legend={'orientation': 'v', 'x': 1.05, 'y': 0.5}, + annotations=[{ + 'text': 'Sectors', + 'x': 0.5, 'y': 0.5, + 'font': {'size': 14, 'weight': 600}, + 'showarrow': False + }] + ) + + return fig + +def create_hypothetical_growth_chart(initial=10000): + """Create hypothetical growth of $10k chart""" + + years = ['2008', '2010', '2012', '2014', '2016', '2018'] + fund_values = [10000, 11500, 14000, 18500, 22000, 27500] + benchmark_values = [10000, 10800, 13200, 17000, 20500, 25000] + + fig = go.Figure() + + fig.add_trace(go.Scatter( + x=years, + y=fund_values, + name='Calibre Index Fund', + fill='tozeroy', + line={'color': CHART_COLORS['primary'], 'width': 2}, + fillcolor='rgba(34, 139, 230, 0.1)', + hovertemplate='$%{y:,.2f}', + )) + + fig.add_trace(go.Scatter( + x=years, + y=benchmark_values, + name='S&P 500 Index', + line={'color': CHART_COLORS['gray'], 'width': 2, 'dash': 'dash'}, + hovertemplate='$%{y:,.2f}', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': f'Hypothetical Growth of ${initial:,}', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + legend={'orientation': 'h', 'y': -0.15}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': '$', 'tickformat': ','}, + xaxis={'showgrid': False}, + ) + + return fig + +def create_fee_comparison_chart(fund_fee=329, avg_fee=2242): + """Create fee comparison bar chart""" + + savings = avg_fee - fund_fee + + fig = go.Figure() + + fig.add_trace(go.Bar( + x=['Category Average', 'This Fund'], + y=[avg_fee, fund_fee], + marker_color=[CHART_COLORS['gray'], CHART_COLORS['primary']], + text=[f'${avg_fee:,}', f'${fund_fee:,}'], + textposition='outside', + )) + + fig.add_annotation( + x=1, y=fund_fee + 300, + text=f'Save ${savings:,}', + showarrow=True, + arrowhead=2, + arrowcolor=CHART_COLORS['secondary'], + font={'color': CHART_COLORS['secondary'], 'weight': 600}, + ) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Fees on $10,000 Over 10 Years', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': '$'}, + showlegend=False, + ) + + return fig + +def create_dividend_timeline(dividend_data): + """Create dividend history chart""" + + df = dividend_data.copy() + df['Amount'] = df['Amount'].str.replace('$', '').astype(float) + + fig = go.Figure() + + fig.add_trace(go.Bar( + x=df['Payable_Date'], + y=df['Amount'], + marker_color=CHART_COLORS['primary'], + name='Dividend', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Dividend History', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'tickprefix': '$'}, + xaxis={'title': 'Payment Date'}, + ) + + return fig diff --git a/investments-dashboard/components/kpi_cards.py b/investments-dashboard/components/kpi_cards.py new file mode 100644 index 0000000..036d311 --- /dev/null +++ b/investments-dashboard/components/kpi_cards.py @@ -0,0 +1,87 @@ +import dash_mantine_components as dmc +from dash import html +from dash_iconify import DashIconify + +def create_kpi_card(title, value, subtitle=None, trend=None, trend_positive=True, icon=None): + """Create a KPI card with optional trend indicator""" + + trend_color = "teal" if trend_positive else "red" + trend_icon = "tabler:trending-up" if trend_positive else "tabler:trending-down" + + content = [ + dmc.Group([ + dmc.Text(title, size="sm", c="dimmed", fw=500), + DashIconify(icon=icon, width=20, color="gray") if icon else None, + ], justify="space-between"), + dmc.Group([ + dmc.Text(value, size="xl", fw=700), + dmc.Group([ + DashIconify(icon=trend_icon, width=16, color=trend_color) if trend else None, + dmc.Text(trend, size="sm", c=trend_color, fw=500) if trend else None, + ], gap=4) if trend else None, + ], justify="space-between", mt="xs"), + ] + + if subtitle: + content.append(dmc.Text(subtitle, size="xs", c="dimmed", mt=4)) + + return dmc.Paper( + dmc.Stack(content, gap="xs"), + p="md", + radius="md", + withBorder=True, + style={"minWidth": "200px"} + ) + +def create_kpi_grid(metrics): + """Create a grid of KPI cards from metrics dict""" + + cards = [ + create_kpi_card( + title="Net Asset Value", + value=f"${metrics['nav']:.2f}", + trend=f"{metrics['ytd_return']:.1f}% YTD", + trend_positive=metrics['ytd_return'] > 0, + icon="tabler:currency-dollar" + ), + create_kpi_card( + title="1 Year Return", + value=f"{metrics['1y_return']:.2f}%", + subtitle="vs S&P 500", + trend_positive=True, + icon="tabler:chart-line" + ), + create_kpi_card( + title="Expense Ratio", + value=metrics['expense_ratio'], + subtitle="vs 0.99% category avg", + trend="85% lower", + trend_positive=True, + icon="tabler:percentage" + ), + create_kpi_card( + title="Category", + value=metrics['category'], + subtitle=metrics['asset_class'], + icon="tabler:category" + ), + ] + + return dmc.SimpleGrid( + cards, + cols={"base": 1, "sm": 2, "lg": 4}, + spacing="md" + ) + +def create_stat_card(label, value, description=None): + """Simple stat card for fund facts""" + return dmc.Paper( + dmc.Stack([ + dmc.Text(label, size="xs", c="dimmed", tt="uppercase", fw=600), + dmc.Text(value, size="lg", fw=600), + dmc.Text(description, size="xs", c="dimmed") if description else None, + ], gap=4), + p="sm", + radius="sm", + withBorder=True, + ) diff --git a/investments-dashboard/components/tables.py b/investments-dashboard/components/tables.py new file mode 100644 index 0000000..e14c6c8 --- /dev/null +++ b/investments-dashboard/components/tables.py @@ -0,0 +1,103 @@ +import dash_mantine_components as dmc +from dash import html +import pandas as pd + +def create_data_table(df, title=None, striped=True): + """Create a styled Mantine table from DataFrame""" + + columns = df.columns.tolist() + + header = dmc.TableThead( + dmc.TableTr([ + dmc.TableTh(col, style={'fontWeight': 600}) for col in columns + ]) + ) + + rows = [] + for _, row in df.iterrows(): + cells = [] + for i, val in enumerate(row): + style = {} + if isinstance(val, str): + if '%' in val: + try: + num = float(val.replace('%', '')) + style['color'] = '#40c057' if num > 0 else '#fa5252' if num < 0 else None + style['fontWeight'] = 500 + except: + pass + cells.append(dmc.TableTd(val, style=style)) + rows.append(dmc.TableTr(cells)) + + body = dmc.TableTbody(rows) + + table = dmc.Table( + [header, body], + striped=striped, + highlightOnHover=True, + withTableBorder=True, + withColumnBorders=True, + ) + + if title: + return dmc.Stack([ + dmc.Text(title, fw=600, size="lg"), + dmc.ScrollArea(table, type="auto"), + ], gap="sm") + + return dmc.ScrollArea(table, type="auto") + +def create_returns_table(df): + """Create formatted returns comparison table""" + return create_data_table(df, title="Average Annual Returns") + +def create_fund_facts_table(df): + """Create fund facts key-value table""" + + rows = [] + for _, row in df.iterrows(): + rows.append( + dmc.TableTr([ + dmc.TableTd(row['label'], style={'fontWeight': 500, 'color': 'dimmed'}), + dmc.TableTd(str(row['value']).replace('"', ''), style={'fontWeight': 600}), + ]) + ) + + return dmc.Table( + dmc.TableTbody(rows), + withTableBorder=True, + highlightOnHover=True, + ) + +def create_dividend_table(df): + """Create dividend history table""" + return create_data_table(df, title="Distribution History") + +def create_comparison_table(data, columns, title=None): + """Create a generic comparison table""" + + header = dmc.TableThead( + dmc.TableTr([dmc.TableTh(col, style={'fontWeight': 600}) for col in columns]) + ) + + rows = [] + for row_data in data: + cells = [dmc.TableTd(cell) for cell in row_data] + rows.append(dmc.TableTr(cells)) + + body = dmc.TableTbody(rows) + + table = dmc.Table( + [header, body], + striped=True, + highlightOnHover=True, + withTableBorder=True, + ) + + if title: + return dmc.Stack([ + dmc.Text(title, fw=600, size="lg"), + table + ], gap="sm") + + return table diff --git a/investments-dashboard/data/df_after_tax.csv b/investments-dashboard/data/df_after_tax.csv new file mode 100644 index 0000000..9ca9949 --- /dev/null +++ b/investments-dashboard/data/df_after_tax.csv @@ -0,0 +1,10 @@ +A,B,C,D,E,F +'-,1 Year,3 Year,5 Year,10 Year,Since Inception 08/31/1976 +500 Index Fund Inv,'-,'-,'-,'-,'- +Returns before taxes,21.67%,11.26%,15.62%,8.37%,11.11% +Returns after taxes on distributions,21.15%,10.75%,15.10%,7.95%,— +Returns after taxes on distributions and sale of fund shares,12.64%,8.71%,12.51%,6.75%,— +Average Large Blend Fund,'-,'-,'-,'-,'- +Returns before taxes,20.44%,9.70%,14.24%,7.61%,— +Returns after taxes on distributions,—,—,—,—,— +Returns after taxes on distributions and sale of fund shares,—,—,—,—,— diff --git a/investments-dashboard/data/df_avg_returns.csv b/investments-dashboard/data/df_avg_returns.csv new file mode 100644 index 0000000..b659957 --- /dev/null +++ b/investments-dashboard/data/df_avg_returns.csv @@ -0,0 +1,4 @@ +A,B,C,D,E,F +'-,1 Year,3 Year,5 Year,10 Year,Since Inception 08/31/1976 +500 Index Fund Inv,16.94%,11.00%,14.57%,9.60%,11.12% +S&P 500 Index*,17.10%,11.14%,14.73%,9.73%,'- diff --git a/investments-dashboard/data/df_current_prices.csv b/investments-dashboard/data/df_current_prices.csv new file mode 100644 index 0000000..b8c13ad --- /dev/null +++ b/investments-dashboard/data/df_current_prices.csv @@ -0,0 +1,7 @@ +label,price,percent +Price as of 02/27/2018,$254.07, +Change,'-$3.23,'-1.26% +SEC yield,,1.67% +52-week high 01/26/2018,$265.42, +52-week low 04/13/2017,$215.11, +Range,$50.31,23.39% diff --git a/investments-dashboard/data/df_dividend.csv b/investments-dashboard/data/df_dividend.csv new file mode 100644 index 0000000..9a2e8ef --- /dev/null +++ b/investments-dashboard/data/df_dividend.csv @@ -0,0 +1,8 @@ +A,B,C,D,E,F,G,H +Distribution Type,Most Recent Distribution,Record Date,Reinvest Date,Payable Date,Reinvest Price,Distribution Yield,SEC Yield +Dividend,$1.12620,12/21/2017,12/22/2017,12/26/2017,$247.63,—,1.77% B +Dividend,$1.12900,09/18/2017,09/19/2017,09/20/2017,$231.32,—,— +Dividend,$0.96000,06/21/2017,06/22/2017,06/23/2017,$224.71,—,— +Dividend,$0.96100,03/20/2017,03/21/2017,03/22/2017,$216.27,—,— +Dividend,$1.25400,12/20/2016,12/21/2016,12/22/2016,$208.90,—,— +Dividend,$0.85200,09/09/2016,09/12/2016,09/13/2016,$199.17,—,— diff --git a/investments-dashboard/data/df_equity_char.csv b/investments-dashboard/data/df_equity_char.csv new file mode 100644 index 0000000..766bdf9 --- /dev/null +++ b/investments-dashboard/data/df_equity_char.csv @@ -0,0 +1,13 @@ +A,B,C +'-,500 Index Fund Inv,S&P 500 Index +Number of stocks,507,505 +Median market cap,$105.4 billion,$105.4 billion +Price/earnings ratio,23.9x,24.3x +Price/book ratio,3.3x,3.3x +Return on equity,16.1%,16.1% +Earnings growth rate,9.9%,8.9% +Foreign holdings,0.1%,— +Turnover rate (as of fiscal year end December),4.1%,— +Short-term reserves,0.0%,— +Fund total net assets,$421.1 billion,— +Share class total net assets,$29.0 billion,— diff --git a/investments-dashboard/data/df_equity_diver.csv b/investments-dashboard/data/df_equity_diver.csv new file mode 100644 index 0000000..ef345d8 --- /dev/null +++ b/investments-dashboard/data/df_equity_diver.csv @@ -0,0 +1,14 @@ +A,B,C +'-,500 Index Fund Inv as of 01/31/2018,S&P 500 Index as of 01/31/2018 +Consumer Discretionary,12.60%,12.60% +Consumer Staples,7.90%,7.90% +Energy,6.00%,6.00% +Financials,14.90%,14.90% +Health Care,13.90%,13.90% +Industrials,10.30%,10.30% +Information Technology,24.20%,24.20% +Materials,2.90%,2.90% +Other,0.00%,— +Real Estate,2.70%,2.70% +Telecommunication Services,1.90%,1.90% +Utilities,2.70%,2.70% diff --git a/investments-dashboard/data/df_expenses.csv b/investments-dashboard/data/df_expenses.csv new file mode 100644 index 0000000..5fa99cf --- /dev/null +++ b/investments-dashboard/data/df_expenses.csv @@ -0,0 +1,4 @@ +A,B +'-,Expense Ratio +500 Index Fund Inv,0.14% +Average expense ratio of similar funds*,0.99% diff --git a/investments-dashboard/data/df_fund_facts.csv b/investments-dashboard/data/df_fund_facts.csv new file mode 100644 index 0000000..9136141 --- /dev/null +++ b/investments-dashboard/data/df_fund_facts.csv @@ -0,0 +1,7 @@ +label,value +Asset Class,Domestic Stock - General +Category,Large Blend +Expense ratio as of 04/27/2017,0.14% +Minimum investment,"""$3,000""" +Fund number,0040 +Fund advisor,Equity Index Group diff --git a/investments-dashboard/data/df_graph.csv b/investments-dashboard/data/df_graph.csv new file mode 100644 index 0000000..6ca62e7 --- /dev/null +++ b/investments-dashboard/data/df_graph.csv @@ -0,0 +1,2564 @@ +Date,Calibre Index Fund,"""Nasdaq Composite, x""","""Nasdaq Composite, y""","""MSCI EAFE Index Fund (ETF), x""",MSCI EAFE Index Fund (ETF),"""Dow Jones Industrial Average, y""","""S&P 500 Index, y""" +2007-12-31,135.149994,2018-02-07,7051.97998,2008-01-02,78.22,13264.820313,1468.359985 +2008-01-02,133.220001,2018-02-08,6777.160156,2008-01-03,78.35,13043.959961,1447.160034 +2008-01-03,133.220001,2018-02-09,6874.490234000001,2008-01-04,76.57,13056.719727,1447.160034 +2008-01-04,129.949997,2018-02-12,6981.959961,2008-01-07,76.65,12800.179688,1411.630005 +2008-01-07,130.369995,2018-02-13,7013.509765999999,2008-01-08,76.22,12827.490234,1416.180054 +2008-01-08,128.020004,2018-02-14,7143.620117,2008-01-09,76.77,12589.070313,1390.189941 +2008-01-09,129.770004,2018-02-15,7256.430176000001,2008-01-10,76.69,12735.30957,1409.130005 +2008-01-10,130.800003,2018-02-16,7239.470215,2008-01-11,75.16,12853.089844,1420.329956 +2008-01-11,129.03999299999998,2018-02-20,7234.310059,2008-01-14,76.36,12606.299805,1401.02002 +2008-01-14,130.440002,2018-02-21,7218.22998,2008-01-15,73.88,12778.150391,1416.25 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b/investments-dashboard/data/df_hist_prices.csv @@ -0,0 +1,6 @@ +date,price +02/28/2018,$251.27 +02/27/2018,$254.07 +02/26/2018,$257.30 +02/23/2018,$254.29 +02/22/2018,$250.26 diff --git a/investments-dashboard/data/df_minimums.csv b/investments-dashboard/data/df_minimums.csv new file mode 100644 index 0000000..3ffe5d7 --- /dev/null +++ b/investments-dashboard/data/df_minimums.csv @@ -0,0 +1,6 @@ +A,B,C +'-,Initial Minimum,Additional Investments +General Account,"""$3,000""",$1 +UGMA/UTMA,"""$3,000""",$1 +IRA,"""$3,000""",$1 +Education savings account,"""$2,000""",$1 diff --git a/investments-dashboard/data/df_price_perf.csv b/investments-dashboard/data/df_price_perf.csv new file mode 100644 index 0000000..0c01d6d --- /dev/null +++ b/investments-dashboard/data/df_price_perf.csv @@ -0,0 +1,4 @@ +label,price,percent +Price as of 02/27/2018,$254.07,None +Change,'-$3.23,'-1.26% +SEC yield,1.67%,B diff --git a/investments-dashboard/data/df_realized.csv b/investments-dashboard/data/df_realized.csv new file mode 100644 index 0000000..87dfd15 --- /dev/null +++ b/investments-dashboard/data/df_realized.csv @@ -0,0 +1,4 @@ +A,B +Realized capital gain/loss,–$0.60 +Realized capital gain/loss as a % of NAV,–0.23% +Fiscal year end,12/31/2018 diff --git a/investments-dashboard/data/df_recent_returns.csv b/investments-dashboard/data/df_recent_returns.csv new file mode 100644 index 0000000..53ab5d3 --- /dev/null +++ b/investments-dashboard/data/df_recent_returns.csv @@ -0,0 +1,4 @@ +A,B,C,D,E +'-,YTD as of 03/05/2018,YTD as of 02/28/2018,Previous Month 02/28/2018,3M Total as of 02/28/2018 +500 Index Fund Inv,2.09%,1.81%,–3.69%,2.93% +S&P 500 Index*,—,1.83%,–3.69%,2.96% diff --git a/investments-dashboard/data/df_unrealized.csv b/investments-dashboard/data/df_unrealized.csv new file mode 100644 index 0000000..678eccf --- /dev/null +++ b/investments-dashboard/data/df_unrealized.csv @@ -0,0 +1,3 @@ +A,B +Unrealized appreciation/depreciation,$107.02 +Unrealized appreciation/depreciation as a % of NAV,41.02% diff --git a/investments-dashboard/demos/callbacks/01_simple_callback.py b/investments-dashboard/demos/callbacks/01_simple_callback.py new file mode 100644 index 0000000..4ed076a --- /dev/null +++ b/investments-dashboard/demos/callbacks/01_simple_callback.py @@ -0,0 +1,93 @@ +from dash import Dash, dcc, html, Input, Output, callback + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +ACCENT = '#7c3aed' + +app = Dash(__name__) + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '48px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', + 'maxWidth': '640px', + 'margin': '0 auto', +}, children=[ + html.H2('Callback Anatomy', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('The output reacts automatically whenever the input changes.', + style={'color': MUTED, 'marginBottom': '40px'}), + + # Input section + html.Div(style={ + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '10px', + 'padding': '20px', + 'marginBottom': '12px', + }, children=[ + html.Div('INPUT', style={ + 'color': MUTED, 'fontSize': '11px', 'fontWeight': '700', + 'letterSpacing': '0.1em', 'marginBottom': '10px', + }), + dcc.Input( + id='my-input', + value='initial value', + type='text', + debounce=False, + style={ + 'backgroundColor': BG, + 'border': f'1px solid {ACCENT}', + 'borderRadius': '6px', + 'color': TEXT, + 'padding': '10px 14px', + 'fontSize': '15px', + 'width': '100%', + 'outline': 'none', + 'boxSizing': 'border-box', + }, + ), + html.P('Try changing this value — the output below updates instantly.', + style={'color': MUTED, 'fontSize': '12px', 'marginTop': '8px', 'marginBottom': 0}), + ]), + + # Arrow indicator + html.Div('↓', style={ + 'color': ACCENT, 'fontSize': '24px', 'textAlign': 'center', + 'margin': '4px 0', 'lineHeight': 1, + }), + + # Output section + html.Div(style={ + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '10px', + 'padding': '20px', + }, children=[ + html.Div('OUTPUT', style={ + 'color': MUTED, 'fontSize': '11px', 'fontWeight': '700', + 'letterSpacing': '0.1em', 'marginBottom': '10px', + }), + html.Div(id='my-output', style={ + 'color': ACCENT, + 'fontSize': '22px', + 'fontWeight': '600', + 'minHeight': '32px', + }), + ]), +]) + + +@callback( + Output('my-output', 'children'), + Input('my-input', 'value'), +) +def update_output(input_value): + return f'Output: {input_value}' + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/callbacks/02_gapminder_slider.py b/investments-dashboard/demos/callbacks/02_gapminder_slider.py new file mode 100644 index 0000000..89d2731 --- /dev/null +++ b/investments-dashboard/demos/callbacks/02_gapminder_slider.py @@ -0,0 +1,75 @@ +from dash import Dash, dcc, html, Input, Output, callback +import plotly.express as px +import pandas as pd + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +df = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/gapminderDataFiveYear.csv') + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '24px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('GDP vs Life Expectancy', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Drag the year slider — the chart animates smoothly between years.', + style={'color': MUTED, 'marginBottom': '16px'}), + + dcc.Graph(id='graph-with-slider'), + + html.Div(style={'padding': '8px 40px 0 40px'}, children=[ + html.Div('Year', style={ + 'color': MUTED, 'fontSize': '11px', 'fontWeight': '600', + 'letterSpacing': '0.08em', 'textTransform': 'uppercase', 'marginBottom': '8px', + }), + dcc.Slider( + df['year'].min(), + df['year'].max(), + step=None, + value=df['year'].min(), + marks={ + str(year): { + 'label': str(year), + 'style': {'color': MUTED, 'fontSize': '11px'}, + } + for year in df['year'].unique() + }, + id='year-slider', + ), + ]), +]) + + +@callback( + Output('graph-with-slider', 'figure'), + Input('year-slider', 'value')) +def update_figure(selected_year): + filtered_df = df[df.year == selected_year] + + fig = px.scatter( + filtered_df, + x='gdpPercap', y='lifeExp', + size='pop', color='continent', + hover_name='country', + log_x=True, size_max=55, + template=TEMPLATE, + ) + fig.update_layout( + transition_duration=500, + plot_bgcolor=CARD, + paper_bgcolor=CARD, + margin=dict(l=40, r=40, t=20, b=20), + ) + return fig + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/callbacks/03_multiple_inputs.py b/investments-dashboard/demos/callbacks/03_multiple_inputs.py new file mode 100644 index 0000000..2e3c0ad --- /dev/null +++ b/investments-dashboard/demos/callbacks/03_multiple_inputs.py @@ -0,0 +1,121 @@ +from dash import Dash, dcc, html, Input, Output, callback +import plotly.express as px +import pandas as pd + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +df = pd.read_csv('https://plotly.github.io/datasets/country_indicators.csv') + +label_style = { + 'color': MUTED, + 'fontSize': '11px', + 'fontWeight': '600', + 'letterSpacing': '0.08em', + 'textTransform': 'uppercase', + 'marginBottom': '6px', +} + +radio_label_style = {'marginRight': '12px', 'marginTop': '6px', 'color': TEXT, 'fontSize': '13px'} + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '24px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('Multiple Inputs → One Output', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Any of the 5 controls below triggers the callback and updates the chart.', + style={'color': MUTED, 'marginBottom': '20px'}), + + # Controls row + html.Div(style={'display': 'flex', 'gap': '24px', 'marginBottom': '16px'}, children=[ + html.Div(style={'flex': 1}, children=[ + html.Div('X Axis Indicator', style=label_style), + dcc.Dropdown( + df['Indicator Name'].unique(), + 'Fertility rate, total (births per woman)', + id='xaxis-column', + style={'backgroundColor': CARD, 'color': TEXT}, + ), + dcc.RadioItems( + ['Linear', 'Log'], 'Linear', + id='xaxis-type', + inline=True, + labelStyle=radio_label_style, + ), + ]), + html.Div(style={'flex': 1}, children=[ + html.Div('Y Axis Indicator', style=label_style), + dcc.Dropdown( + df['Indicator Name'].unique(), + 'Life expectancy at birth, total (years)', + id='yaxis-column', + style={'backgroundColor': CARD, 'color': TEXT}, + ), + dcc.RadioItems( + ['Linear', 'Log'], 'Linear', + id='yaxis-type', + inline=True, + labelStyle=radio_label_style, + ), + ]), + ]), + + dcc.Graph(id='indicator-graphic'), + + html.Div(style={'padding': '8px 40px 0 40px'}, children=[ + html.Div('Year', style=label_style), + dcc.Slider( + df['Year'].min(), + df['Year'].max(), + step=None, + id='year--slider', + value=df['Year'].max(), + marks={ + str(year): { + 'label': str(year), + 'style': {'color': MUTED, 'fontSize': '11px'}, + } + for year in df['Year'].unique() + }, + ), + ]), +]) + + +@callback( + Output('indicator-graphic', 'figure'), + Input('xaxis-column', 'value'), + Input('yaxis-column', 'value'), + Input('xaxis-type', 'value'), + Input('yaxis-type', 'value'), + Input('year--slider', 'value')) +def update_graph(xaxis_col, yaxis_col, xaxis_type, yaxis_type, year_value): + dff = df[df['Year'] == year_value] + + fig = px.scatter( + x=dff[dff['Indicator Name'] == xaxis_col]['Value'], + y=dff[dff['Indicator Name'] == yaxis_col]['Value'], + hover_name=dff[dff['Indicator Name'] == yaxis_col]['Country Name'], + template=TEMPLATE, + ) + fig.update_layout( + plot_bgcolor=CARD, + paper_bgcolor=CARD, + margin=dict(l=40, b=40, t=20, r=20), + hovermode='closest', + ) + fig.update_xaxes(title=xaxis_col, type='linear' if xaxis_type == 'Linear' else 'log') + fig.update_yaxes(title=yaxis_col, type='linear' if yaxis_type == 'Linear' else 'log') + return fig + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/callbacks/04_state_button.py b/investments-dashboard/demos/callbacks/04_state_button.py new file mode 100644 index 0000000..81de034 --- /dev/null +++ b/investments-dashboard/demos/callbacks/04_state_button.py @@ -0,0 +1,118 @@ +from dash import Dash, dcc, html, Input, Output, State, callback + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +ACCENT = '#7c3aed' + +app = Dash(__name__) + +input_style = { + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '6px', + 'color': TEXT, + 'padding': '10px 14px', + 'fontSize': '15px', + 'width': '100%', + 'outline': 'none', + 'boxSizing': 'border-box', + 'marginBottom': '12px', +} + +label_style = { + 'color': MUTED, + 'fontSize': '11px', + 'fontWeight': '600', + 'letterSpacing': '0.08em', + 'textTransform': 'uppercase', + 'marginBottom': '6px', + 'display': 'block', +} + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '48px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', + 'maxWidth': '560px', + 'margin': '0 auto', +}, children=[ + html.H2('State vs Input', style={'color': TEXT, 'marginBottom': '4px'}), + html.P( + 'Typing in the fields does nothing. Only clicking Submit fires the callback.', + style={'color': MUTED, 'marginBottom': '32px'}, + ), + + html.Div(style={ + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '10px', + 'padding': '24px', + 'marginBottom': '16px', + }, children=[ + html.Span('City', style=label_style), + dcc.Input( + id='input-1-state', + type='text', + value='Montréal', + placeholder='Enter a city', + style=input_style, + ), + + html.Span('Country', style=label_style), + dcc.Input( + id='input-2-state', + type='text', + value='Canada', + placeholder='Enter a country', + style=input_style, + ), + + html.Button( + 'Submit', + id='submit-button-state', + n_clicks=0, + style={ + 'backgroundColor': ACCENT, + 'color': '#fff', + 'border': 'none', + 'borderRadius': '6px', + 'padding': '10px 24px', + 'fontSize': '14px', + 'fontWeight': '600', + 'cursor': 'pointer', + 'width': '100%', + 'marginTop': '4px', + }, + ), + ]), + + html.Div(id='output-state', style={ + 'color': TEXT, + 'fontSize': '15px', + 'padding': '16px 20px', + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '10px', + 'minHeight': '56px', + }), +]) + + +@callback( + Output('output-state', 'children'), + Input('submit-button-state', 'n_clicks'), + State('input-1-state', 'value'), + State('input-2-state', 'value'), +) +def update_output(n_clicks, city, country): + if n_clicks == 0: + return html.Span('Waiting for submission…', style={'color': MUTED}) + return f'Submitted {n_clicks} time{"s" if n_clicks != 1 else ""}. City: {city}, Country: {country}.' + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/interactive-graphing/01_debug_interactions.py b/investments-dashboard/demos/interactive-graphing/01_debug_interactions.py new file mode 100644 index 0000000..f7f6484 --- /dev/null +++ b/investments-dashboard/demos/interactive-graphing/01_debug_interactions.py @@ -0,0 +1,115 @@ +from dash import Dash, dcc, html, Input, Output, callback +import plotly.express as px +import pandas as pd +import json + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +df = pd.DataFrame({ + "x": [1, 2, 1, 2], + "y": [1, 2, 3, 4], + "customdata": [1, 2, 3, 4], + "fruit": ["apple", "apple", "orange", "orange"] +}) + +fig = px.scatter(df, x="x", y="y", color="fruit", custom_data=["customdata"], + template=TEMPLATE, color_discrete_map={"apple": "#7c3aed", "orange": "#f97316"}) +fig.update_layout( + plot_bgcolor=CARD, + paper_bgcolor=CARD, + clickmode='event+select', + margin=dict(l=40, r=40, t=40, b=40), +) +fig.update_traces(marker_size=20) + +pre_style = { + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'color': TEXT, + 'borderRadius': '8px', + 'padding': '12px', + 'overflowX': 'auto', + 'fontSize': '12px', + 'minHeight': '180px', +} + +label_style = { + 'color': MUTED, + 'fontSize': '11px', + 'fontWeight': '600', + 'letterSpacing': '0.08em', + 'textTransform': 'uppercase', + 'marginBottom': '8px', +} + +panel_style = { + 'flex': 1, + 'minWidth': 0, +} + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '24px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('Graph Interaction Data', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Hover, click, select, or zoom the chart to see the interaction data.', + style={'color': MUTED, 'marginBottom': '24px'}), + + dcc.Graph( + id='basic-interactions', + figure=fig, + style={'marginBottom': '24px'}, + ), + + html.Div(style={'display': 'flex', 'gap': '16px'}, children=[ + html.Div(style=panel_style, children=[ + html.Div('Hover Data', style=label_style), + html.Pre(id='hover-data', style=pre_style), + ]), + html.Div(style=panel_style, children=[ + html.Div('Click Data', style=label_style), + html.Pre(id='click-data', style=pre_style), + ]), + html.Div(style=panel_style, children=[ + html.Div('Selection Data', style=label_style), + html.Pre(id='selected-data', style=pre_style), + ]), + html.Div(style=panel_style, children=[ + html.Div('Zoom / Relayout Data', style=label_style), + html.Pre(id='relayout-data', style=pre_style), + ]), + ]), +]) + + +@callback(Output('hover-data', 'children'), Input('basic-interactions', 'hoverData')) +def display_hover(hoverData): + return json.dumps(hoverData, indent=2) + + +@callback(Output('click-data', 'children'), Input('basic-interactions', 'clickData')) +def display_click(clickData): + return json.dumps(clickData, indent=2) + + +@callback(Output('selected-data', 'children'), Input('basic-interactions', 'selectedData')) +def display_selected(selectedData): + return json.dumps(selectedData, indent=2) + + +@callback(Output('relayout-data', 'children'), Input('basic-interactions', 'relayoutData')) +def display_relayout(relayoutData): + return json.dumps(relayoutData, indent=2) + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/interactive-graphing/02_hover_timeseries.py b/investments-dashboard/demos/interactive-graphing/02_hover_timeseries.py new file mode 100644 index 0000000..df99904 --- /dev/null +++ b/investments-dashboard/demos/interactive-graphing/02_hover_timeseries.py @@ -0,0 +1,183 @@ +from dash import Dash, html, dcc, Input, Output, callback +import pandas as pd +import plotly.express as px + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +df = pd.read_csv('https://plotly.github.io/datasets/country_indicators.csv') + +dropdown_style = { + 'backgroundColor': CARD, + 'color': TEXT, +} + +label_style = { + 'color': MUTED, + 'fontSize': '11px', + 'fontWeight': '600', + 'letterSpacing': '0.08em', + 'textTransform': 'uppercase', + 'marginBottom': '6px', +} + +radio_style = { + 'color': TEXT, + 'fontSize': '13px', +} + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '24px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('World Indicators Explorer', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Hover over a country in the scatter plot to see its historical trend.', + style={'color': MUTED, 'marginBottom': '20px'}), + + # Controls row + html.Div(style={'display': 'flex', 'gap': '24px', 'marginBottom': '16px'}, children=[ + html.Div(style={'flex': 1}, children=[ + html.Div('X Axis Indicator', style=label_style), + dcc.Dropdown( + df['Indicator Name'].unique(), + 'Fertility rate, total (births per woman)', + id='crossfilter-xaxis-column', + style=dropdown_style, + ), + dcc.RadioItems( + ['Linear', 'Log'], 'Linear', + id='crossfilter-xaxis-type', + inline=True, + style=radio_style, + labelStyle={'marginRight': '12px', 'marginTop': '6px'}, + ), + ]), + html.Div(style={'flex': 1}, children=[ + html.Div('Y Axis Indicator', style=label_style), + dcc.Dropdown( + df['Indicator Name'].unique(), + 'Life expectancy at birth, total (years)', + id='crossfilter-yaxis-column', + style=dropdown_style, + ), + dcc.RadioItems( + ['Linear', 'Log'], 'Linear', + id='crossfilter-yaxis-type', + inline=True, + style=radio_style, + labelStyle={'marginRight': '12px', 'marginTop': '6px'}, + ), + ]), + ]), + + # Charts row + html.Div(style={'display': 'flex', 'gap': '16px'}, children=[ + html.Div(style={'flex': '0 0 55%'}, children=[ + dcc.Graph( + id='crossfilter-indicator-scatter', + hoverData={'points': [{'customdata': 'Japan'}]}, + ), + ]), + html.Div(style={'flex': 1}, children=[ + dcc.Graph(id='x-time-series'), + dcc.Graph(id='y-time-series'), + ]), + ]), + + # Year slider + html.Div(style={'marginTop': '8px', 'paddingRight': '24px', 'width': '55%'}, children=[ + html.Div('Year', style=label_style), + dcc.Slider( + df['Year'].min(), + df['Year'].max(), + step=None, + id='crossfilter-year--slider', + value=df['Year'].max(), + marks={str(year): {'label': str(year), 'style': {'color': MUTED, 'fontSize': '11px'}} + for year in df['Year'].unique()}, + ), + ]), +]) + + +@callback( + Output('crossfilter-indicator-scatter', 'figure'), + Input('crossfilter-xaxis-column', 'value'), + Input('crossfilter-yaxis-column', 'value'), + Input('crossfilter-xaxis-type', 'value'), + Input('crossfilter-yaxis-type', 'value'), + Input('crossfilter-year--slider', 'value')) +def update_scatter(xaxis_col, yaxis_col, xaxis_type, yaxis_type, year): + dff = df[df['Year'] == year] + fig = px.scatter( + x=dff[dff['Indicator Name'] == xaxis_col]['Value'], + y=dff[dff['Indicator Name'] == yaxis_col]['Value'], + hover_name=dff[dff['Indicator Name'] == yaxis_col]['Country Name'], + template=TEMPLATE, + ) + fig.update_traces( + customdata=dff[dff['Indicator Name'] == yaxis_col]['Country Name'], + marker=dict(size=8, opacity=0.8), + ) + fig.update_xaxes(title=xaxis_col, type='linear' if xaxis_type == 'Linear' else 'log') + fig.update_yaxes(title=yaxis_col, type='linear' if yaxis_type == 'Linear' else 'log') + fig.update_layout( + plot_bgcolor=CARD, + paper_bgcolor=CARD, + margin=dict(l=40, b=40, t=20, r=20), + hovermode='closest', + ) + return fig + + +def create_time_series(dff, axis_type, title): + fig = px.scatter(dff, x='Year', y='Value', template=TEMPLATE) + fig.update_traces(mode='lines+markers', marker=dict(size=5), line=dict(color='#7c3aed')) + fig.update_xaxes(showgrid=False) + fig.update_yaxes(type='linear' if axis_type == 'Linear' else 'log') + fig.add_annotation( + x=0, y=0.85, xanchor='left', yanchor='bottom', + xref='paper', yref='paper', showarrow=False, align='left', + text=title, font=dict(size=11, color=MUTED), + ) + fig.update_layout( + height=225, + plot_bgcolor=CARD, + paper_bgcolor=CARD, + margin=dict(l=20, b=30, r=10, t=10), + ) + return fig + + +@callback( + Output('x-time-series', 'figure'), + Input('crossfilter-indicator-scatter', 'hoverData'), + Input('crossfilter-xaxis-column', 'value'), + Input('crossfilter-xaxis-type', 'value')) +def update_x_timeseries(hoverData, xaxis_col, axis_type): + country = hoverData['points'][0]['customdata'] + dff = df[(df['Country Name'] == country) & (df['Indicator Name'] == xaxis_col)] + return create_time_series(dff, axis_type, f'{country}
{xaxis_col}') + + +@callback( + Output('y-time-series', 'figure'), + Input('crossfilter-indicator-scatter', 'hoverData'), + Input('crossfilter-yaxis-column', 'value'), + Input('crossfilter-yaxis-type', 'value')) +def update_y_timeseries(hoverData, yaxis_col, axis_type): + country = hoverData['points'][0]['customdata'] + dff = df[(df['Country Name'] == country) & (df['Indicator Name'] == yaxis_col)] + return create_time_series(dff, axis_type, yaxis_col) + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/interactive-graphing/03_crossfilter.py b/investments-dashboard/demos/interactive-graphing/03_crossfilter.py new file mode 100644 index 0000000..70663b9 --- /dev/null +++ b/investments-dashboard/demos/interactive-graphing/03_crossfilter.py @@ -0,0 +1,111 @@ +from dash import Dash, dcc, html, Input, Output, callback +import numpy as np +import pandas as pd +import plotly.express as px + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +ACCENT = '#7c3aed' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +np.random.seed(0) +df = pd.DataFrame({"Col " + str(i + 1): np.random.rand(30) for i in range(6)}) + + +def get_figure(df, x_col, y_col, selectedpoints, selectedpoints_local): + if selectedpoints_local and selectedpoints_local.get("range"): + ranges = selectedpoints_local["range"] + selection_bounds = { + "x0": ranges["x"][0], "x1": ranges["x"][1], + "y0": ranges["y"][0], "y1": ranges["y"][1], + } + else: + selection_bounds = { + "x0": np.min(df[x_col]), "x1": np.max(df[x_col]), + "y0": np.min(df[y_col]), "y1": np.max(df[y_col]), + } + + fig = px.scatter(df, x=df[x_col], y=df[y_col], text=df.index, template=TEMPLATE) + fig.update_traces( + selectedpoints=selectedpoints, + customdata=df.index, + mode="markers+text", + marker={"color": ACCENT, "size": 16, "opacity": 0.9}, + unselected={ + "marker": {"opacity": 0.15, "color": MUTED}, + "textfont": {"color": "rgba(0,0,0,0)"}, + }, + selected={ + "marker": {"color": ACCENT, "opacity": 1.0}, + }, + textfont={"size": 9, "color": MUTED}, + ) + fig.update_layout( + plot_bgcolor=CARD, + paper_bgcolor=CARD, + margin={"l": 20, "r": 10, "b": 20, "t": 30}, + dragmode="select", + hovermode=False, + newselection_mode="gradual", + xaxis_title=x_col, + yaxis_title=y_col, + ) + fig.add_shape(dict( + type="rect", + line={"width": 1, "dash": "dot", "color": MUTED}, + **selection_bounds, + )) + return fig + + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '24px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('Crossfilter', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Lasso or box-select points in any chart — the selection filters across all three.', + style={'color': MUTED, 'marginBottom': '24px'}), + + html.Div(style={'display': 'flex', 'gap': '16px'}, children=[ + dcc.Graph(id='g1', config={'displayModeBar': True, 'modeBarButtonsToKeep': ['select2d', 'lasso2d']}, + style={'flex': 1}), + dcc.Graph(id='g2', config={'displayModeBar': True, 'modeBarButtonsToKeep': ['select2d', 'lasso2d']}, + style={'flex': 1}), + dcc.Graph(id='g3', config={'displayModeBar': True, 'modeBarButtonsToKeep': ['select2d', 'lasso2d']}, + style={'flex': 1}), + ]), +]) + + +@callback( + Output('g1', 'figure'), + Output('g2', 'figure'), + Output('g3', 'figure'), + Input('g1', 'selectedData'), + Input('g2', 'selectedData'), + Input('g3', 'selectedData'), +) +def update_charts(sel1, sel2, sel3): + selectedpoints = df.index + for sel in [sel1, sel2, sel3]: + if sel and sel['points']: + selectedpoints = np.intersect1d( + selectedpoints, + [p['customdata'] for p in sel['points']] + ) + return [ + get_figure(df, 'Col 1', 'Col 2', selectedpoints, sel1), + get_figure(df, 'Col 3', 'Col 4', selectedpoints, sel2), + get_figure(df, 'Col 5', 'Col 6', selectedpoints, sel3), + ] + + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/layout/01_hello_dash.py b/investments-dashboard/demos/layout/01_hello_dash.py new file mode 100644 index 0000000..61f68ae --- /dev/null +++ b/investments-dashboard/demos/layout/01_hello_dash.py @@ -0,0 +1,54 @@ +from dash import Dash, html, dcc +import plotly.express as px +import pandas as pd + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +TEMPLATE = 'plotly_dark' + +app = Dash(__name__) + +df = pd.DataFrame({ + "Fruit": ["Apples", "Oranges", "Bananas", "Apples", "Oranges", "Bananas"], + "Amount": [4, 1, 2, 2, 4, 5], + "City": ["SF", "SF", "SF", "Montreal", "Montreal", "Montreal"], +}) + +fig = px.bar(df, x="Fruit", y="Amount", color="City", barmode="group", template=TEMPLATE) +fig.update_layout(plot_bgcolor=CARD, paper_bgcolor=CARD, margin=dict(l=40, r=40, t=40, b=40)) + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '32px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H1('Hello Dash', style={'color': TEXT, 'marginBottom': '4px'}), + + html.Div('Dash: A web application framework for your data.', style={ + 'color': MUTED, + 'fontSize': '15px', + 'marginBottom': '24px', + }), + + dcc.Graph(id='example-graph', figure=fig), + + html.P( + '✏️ Try editing the H1 title above in the code, save the file, and watch the browser update automatically.', + style={ + 'color': MUTED, + 'fontSize': '12px', + 'marginTop': '16px', + 'border': f'1px solid {BORDER}', + 'borderRadius': '6px', + 'padding': '10px 14px', + 'backgroundColor': CARD, + }, + ), +]) + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/layout/02_styled_layout.py b/investments-dashboard/demos/layout/02_styled_layout.py new file mode 100644 index 0000000..25c3a2e --- /dev/null +++ b/investments-dashboard/demos/layout/02_styled_layout.py @@ -0,0 +1,47 @@ +from dash import Dash, dcc, html +import plotly.express as px +import pandas as pd + +# style dict — the pattern from the docs, upgraded to our palette +colors = { + 'background': '#0f1117', + 'card': '#1a1d27', + 'text': '#e2e8f0', + 'muted': '#94a3b8', + 'accent': '#7c3aed', +} + +app = Dash(__name__) + +df = pd.DataFrame({ + "Fruit": ["Apples", "Oranges", "Bananas", "Apples", "Oranges", "Bananas"], + "Amount": [4, 1, 2, 2, 4, 5], + "City": ["SF", "SF", "SF", "Montreal", "Montreal", "Montreal"], +}) + +fig = px.bar(df, x="Fruit", y="Amount", color="City", barmode="group", template='plotly_dark') +fig.update_layout( + plot_bgcolor=colors['card'], + paper_bgcolor=colors['card'], + font_color=colors['text'], + margin=dict(l=40, r=40, t=40, b=40), +) + +app.layout = html.Div( + style={'backgroundColor': colors['background'], 'padding': '32px', + 'fontFamily': 'Inter, system-ui, sans-serif', 'minHeight': '100vh'}, + children=[ + html.H1( + 'Hello Dash', + style={'textAlign': 'center', 'color': colors['accent']}, + ), + html.Div( + 'Dash: A web application framework for your data.', + style={'textAlign': 'center', 'color': colors['muted'], 'marginBottom': '24px'}, + ), + dcc.Graph(id='example-graph-2', figure=fig), + ], +) + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/demos/layout/03_core_components.py b/investments-dashboard/demos/layout/03_core_components.py new file mode 100644 index 0000000..b385345 --- /dev/null +++ b/investments-dashboard/demos/layout/03_core_components.py @@ -0,0 +1,109 @@ +from dash import Dash, html, dcc + +BG = '#0f1117' +CARD = '#1a1d27' +BORDER = '#2d3148' +TEXT = '#e2e8f0' +MUTED = '#94a3b8' +ACCENT = '#7c3aed' + +app = Dash(__name__) + +label_style = { + 'color': MUTED, + 'fontSize': '11px', + 'fontWeight': '700', + 'letterSpacing': '0.08em', + 'textTransform': 'uppercase', + 'marginBottom': '8px', + 'marginTop': '20px', + 'display': 'block', +} + +section_style = { + 'backgroundColor': CARD, + 'border': f'1px solid {BORDER}', + 'borderRadius': '10px', + 'padding': '20px 24px', + 'flex': 1, + 'minWidth': 0, +} + +app.layout = html.Div(style={ + 'backgroundColor': BG, + 'padding': '32px', + 'fontFamily': 'Inter, system-ui, sans-serif', + 'minHeight': '100vh', +}, children=[ + html.H2('Core Components', style={'color': TEXT, 'marginBottom': '4px'}), + html.P('Every dcc component is declared entirely through keyword arguments — fully declarative.', + style={'color': MUTED, 'marginBottom': '24px'}), + + html.Div(style={'display': 'flex', 'gap': '16px'}, children=[ + + # Left column + html.Div(style=section_style, children=[ + html.Span('Dropdown', style=label_style), + dcc.Dropdown( + ['New York City', 'Montréal', 'San Francisco'], + 'Montréal', + ), + + html.Span('Multi-Select Dropdown', style=label_style), + dcc.Dropdown( + ['New York City', 'Montréal', 'San Francisco'], + ['Montréal', 'San Francisco'], + multi=True, + ), + + html.Span('Radio Items', style=label_style), + dcc.RadioItems( + ['New York City', 'Montréal', 'San Francisco'], + 'Montréal', + labelStyle={'color': TEXT, 'marginRight': '12px', 'fontSize': '14px'}, + ), + ]), + + # Right column + html.Div(style=section_style, children=[ + html.Span('Checkboxes', style=label_style), + dcc.Checklist( + ['New York City', 'Montréal', 'San Francisco'], + ['Montréal', 'San Francisco'], + labelStyle={'color': TEXT, 'marginRight': '12px', 'fontSize': '14px'}, + ), + + html.Span('Text Input', style=label_style), + dcc.Input( + value='MTL', + type='text', + style={ + 'backgroundColor': BG, + 'border': f'1px solid {BORDER}', + 'borderRadius': '6px', + 'color': TEXT, + 'padding': '8px 12px', + 'fontSize': '14px', + 'outline': 'none', + }, + ), + + html.Span('Slider', style=label_style), + dcc.Slider( + min=0, + max=9, + marks={ + i: { + 'label': f'Label {i}' if i == 1 else str(i), + 'style': {'color': MUTED, 'fontSize': '11px'}, + } + for i in range(1, 6) + }, + value=5, + ), + ]), + ]), +]) + +if __name__ == '__main__': + app.run(debug=True) diff --git a/investments-dashboard/pages/__init__.py b/investments-dashboard/pages/__init__.py new file mode 100644 index 0000000..8b13789 --- /dev/null +++ b/investments-dashboard/pages/__init__.py @@ -0,0 +1 @@ + diff --git a/investments-dashboard/pages/dashboard.py b/investments-dashboard/pages/dashboard.py new file mode 100644 index 0000000..3fd279a --- /dev/null +++ b/investments-dashboard/pages/dashboard.py @@ -0,0 +1,293 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify + +from components.charts import create_hypothetical_growth_chart, create_sparkline +from components.tables import create_fund_facts_table +from utils.data_loader import get_fund_metrics, df_fund_facts + +metrics = get_fund_metrics() + +SYMBOLS = ["AAPL", "GOOGL", "MSFT", "AMZN", "TSLA"] +INITIAL_PRICES = {"AAPL": 189.50, "GOOGL": 176.30, "MSFT": 420.15, "AMZN": 185.60, "TSLA": 178.90} + +def create_kpi_card(id_prefix, title, value, trend=None, trend_positive=True, subtitle=None, icon=None): + """Create a KPI card with IDs for callback updates""" + trend_color = "teal" if trend_positive else "red" + + return dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Text(title, size="sm", c="dimmed", fw=500, id=f"{id_prefix}-title"), + DashIconify(icon=icon, width=20, color="gray") if icon else None, + ], justify="space-between"), + dmc.Group([ + dmc.Text(value, size="xl", fw=700, id=f"{id_prefix}-value"), + dmc.Text( + trend if trend else "", + size="sm", + c=trend_color, + fw=500, + id=f"{id_prefix}-trend", + style={"display": "block" if trend else "none"} + ), + ], justify="space-between", mt="xs"), + dmc.Text(subtitle, size="xs", c="dimmed", mt=4, id=f"{id_prefix}-subtitle") if subtitle else None, + ], gap="xs"), + p="md", + radius="md", + withBorder=True, + style={"minWidth": "200px"} + ) + +def create_risk_row(id_prefix, label, value, progress_value, color): + """Create a risk metric row with IDs for dynamic updates""" + return dmc.Group([ + dmc.Text(label, size="sm", w=100), + dmc.Progress(value=progress_value, color=color, size="lg", style={"flex": 1}, id=f"{id_prefix}-bar"), + dmc.Text(value, size="sm", fw=500, w=60, id=f"{id_prefix}-value"), + ], gap="sm") + +layout = dmc.Stack([ + # Page Header + dmc.Group([ + dmc.Stack([ + dmc.Title("Executive Dashboard", order=2), + dmc.Text("Fund performance overview and key metrics", c="dimmed"), + ], gap=4), + dmc.Group([ + dmc.SegmentedControl( + id="dashboard-period", + data=[ + {"value": "1Y", "label": "1Y"}, + {"value": "3Y", "label": "3Y"}, + {"value": "5Y", "label": "5Y"}, + {"value": "10Y", "label": "10Y"}, + {"value": "All", "label": "All"}, + ], + value="1Y", + size="sm", + ), + dmc.Select( + id="dashboard-fund-select", + data=[ + {"value": "500", "label": "500 Index Fund Inv"}, + {"value": "calibre", "label": "Calibre Index Fund"}, + ], + value="500", + w=200, + ), + dmc.Switch( + id="benchmark-toggle", + label="Benchmark", + checked=True, + size="sm", + ), + dmc.NumberInput( + id="investment-amount", + value=10000, + min=1000, + max=1000000, + step=1000, + prefix="$", + thousandSeparator=",", + w=130, + size="sm", + ), + ], gap="sm"), + ], justify="space-between", mb="lg"), + + # KPI Cards Row + dmc.SimpleGrid([ + create_kpi_card( + "kpi-nav", + "Net Asset Value", + f"${metrics['nav']:.2f}", + trend=f"↑ {metrics['ytd_return']:.1f}% YTD", + trend_positive=metrics['ytd_return'] > 0, + icon="tabler:currency-dollar" + ), + create_kpi_card( + "kpi-period", + "1 Year Return", + f"{metrics['1y_return']:.2f}%", + subtitle="vs S&P 500", + icon="tabler:chart-line" + ), + create_kpi_card( + "kpi-expense", + "Expense Ratio", + metrics['expense_ratio'], + trend="↓ 85% lower", + trend_positive=True, + subtitle="vs 0.99% category avg", + icon="tabler:percentage" + ), + create_kpi_card( + "kpi-category", + "Category", + metrics['category'], + subtitle=metrics['asset_class'], + icon="tabler:category" + ), + ], cols={"base": 1, "sm": 2, "lg": 4}, spacing="md"), + + # Main Charts Row + dmc.Grid([ + dmc.GridCol([ + dcc.Store(id="live-streaming", data=True), + dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Group([ + dmc.Text("Live Market Prices", fw=600, size="lg"), + html.Div( + style={ + "width": 8, "height": 8, "borderRadius": "50%", + "backgroundColor": "#40c057", + "animation": "pulse 1.5s ease-in-out infinite", + }, + id="live-indicator", + ), + dmc.Badge("LIVE", color="green", size="sm", variant="light"), + ], gap="xs"), + dmc.Switch( + id="live-toggle", + label="Stream", + checked=True, + size="sm", + ), + ], justify="space-between"), + dmc.Divider(), + dmc.Stack([ + dmc.Group([ + dmc.Text(sym, size="sm", fw=600, w=60), + dmc.Text( + f"${INITIAL_PRICES[sym]:.2f}", + size="sm", fw=700, ff="monospace", + id=f"live-price-{sym}", + ), + dmc.Text( + "+0.00 (0.00%)", + size="xs", c="dimmed", ff="monospace", + id=f"live-change-{sym}", + ), + ], justify="space-between") + for sym in SYMBOLS + ], gap="xs"), + dmc.Divider(), + dmc.Select( + id="sparkline-symbol", + data=[{"value": s, "label": s} for s in SYMBOLS], + value="AAPL", + size="xs", + w=120, + ), + dcc.Graph( + id="sparkline-chart", + figure=create_sparkline([INITIAL_PRICES["AAPL"]], "AAPL"), + config={"displayModeBar": False}, + style={"height": "120px"}, + ), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 7}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dcc.Graph( + id="growth-chart", + figure=create_hypothetical_growth_chart(), + config={"displayModeBar": False}, + style={"height": "350px"} + ), + ]), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 5}), + ], gutter="md"), + + # Fund Facts and Quick Stats Row + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Fund Facts", fw=600, size="lg"), + create_fund_facts_table(df_fund_facts), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 4}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Quick Comparison", fw=600, size="lg"), + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("1Y RETURN", size="xs", c="dimmed", fw=600), + dmc.Text(f"{metrics['1y_return']:.2f}%", size="lg", fw=600, id="quick-1y"), + dmc.Text("Fund", size="xs", c="dimmed"), + ], gap=4), + p="sm", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("3Y RETURN", size="xs", c="dimmed", fw=600), + dmc.Text(f"{metrics['3y_return']:.2f}%", size="lg", fw=600, id="quick-3y"), + dmc.Text("Fund", size="xs", c="dimmed"), + ], gap=4), + p="sm", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("5Y RETURN", size="xs", c="dimmed", fw=600), + dmc.Text(f"{metrics['5y_return']:.2f}%", size="lg", fw=600, id="quick-5y"), + dmc.Text("Fund", size="xs", c="dimmed"), + ], gap=4), + p="sm", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("MIN INVESTMENT", size="xs", c="dimmed", fw=600), + dmc.Text(metrics['min_investment'].replace('"', ''), size="lg", fw=600, id="quick-min"), + ], gap=4), + p="sm", radius="sm", withBorder=True, + ), + ], cols=2, spacing="sm"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 4}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Risk Overview", fw=600, size="lg"), + dmc.Stack([ + create_risk_row("risk-volatility", "Volatility", "Medium", 45, "blue"), + create_risk_row("risk-beta", "Beta", "1.00", 100, "green"), + create_risk_row("risk-sharpe", "Sharpe Ratio", "0.85", 70, "teal"), + create_risk_row("risk-alpha", "Alpha", "-0.02", 50, "yellow"), + ], gap="md", mt="sm"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + h="100%", + ) + ], span={"base": 12, "md": 4}), + ], gutter="md"), + +], gap="md") diff --git a/investments-dashboard/pages/fees.py b/investments-dashboard/pages/fees.py new file mode 100644 index 0000000..145ef7a --- /dev/null +++ b/investments-dashboard/pages/fees.py @@ -0,0 +1,333 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify +import plotly.graph_objects as go + +from components.charts import create_fee_comparison_chart, create_dividend_timeline, CHART_COLORS, CHART_LAYOUT +from components.tables import create_data_table, create_dividend_table +from utils.data_loader import ( + df_expenses, df_minimums, get_dividend_history, + df_realized, df_unrealized +) + +dividend_data = get_dividend_history() + +def create_fee_waterfall(): + """Create fee breakdown waterfall chart""" + fig = go.Figure(go.Waterfall( + orientation="v", + measure=["absolute", "relative", "relative", "relative", "total"], + x=["Management Fee", "Admin Fee", "12b-1 Fee", "Other", "Total Expense"], + y=[0.10, 0.02, 0.00, 0.02, 0], + connector={"line": {"color": "rgb(63, 63, 63)"}}, + decreasing={"marker": {"color": CHART_COLORS['secondary']}}, + increasing={"marker": {"color": CHART_COLORS['danger']}}, + totals={"marker": {"color": CHART_COLORS['primary']}}, + text=["+0.10%", "+0.02%", "+0.00%", "+0.02%", "0.14%"], + textposition="outside", + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Expense Ratio Breakdown', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'title': 'Percentage', 'ticksuffix': '%'}, + showlegend=False, + ) + + return fig + +def create_cost_impact_chart(initial=10000, years=30): + """Show cost impact over time""" + year_range = list(range(1, years + 1)) + + fund_values = [initial * (1.07 - 0.0014) ** y for y in year_range] + avg_values = [initial * (1.07 - 0.0099) ** y for y in year_range] + + fig = go.Figure() + + fig.add_trace(go.Scatter( + x=year_range, + y=avg_values, + name='Category Avg (0.99%)', + line={'color': CHART_COLORS['gray'], 'width': 2}, + )) + + fig.add_trace(go.Scatter( + x=year_range, + y=fund_values, + name='This Fund (0.14%)', + line={'color': CHART_COLORS['primary'], 'width': 2}, + fill='tonexty', + fillcolor='rgba(34, 139, 230, 0.1)', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Long-Term Cost Impact (7% annual return)', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + xaxis={'title': 'Years'}, + yaxis={'title': 'Portfolio Value', 'tickprefix': '$', 'tickformat': ','}, + legend={'orientation': 'h', 'y': -0.15}, + ) + + return fig + +def create_dividend_calendar(): + """Create dividend payment calendar visualization""" + months = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec'] + dividends = [0, 0, 0.96, 0, 0, 0.96, 0, 0, 1.13, 0, 0, 1.13] + + fig = go.Figure() + + fig.add_trace(go.Bar( + x=months, + y=dividends, + marker_color=[CHART_COLORS['primary'] if d > 0 else CHART_COLORS['gray'] for d in dividends], + text=[f'${d:.2f}' if d > 0 else '' for d in dividends], + textposition='outside', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Dividend Payment Calendar', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'title': 'Dividend per Share', 'tickprefix': '$'}, + xaxis={'title': 'Month'}, + ) + + return fig + +layout = dmc.Stack([ + # Page Header + dmc.Group([ + dmc.Stack([ + dmc.Title("Fees & Distributions", order=2), + dmc.Text("Expense analysis, dividend history, and capital gains", c="dimmed"), + ], gap=4), + dmc.Group([ + ], gap="sm"), + ], justify="space-between", mb="lg"), + + # Fee Calculator Section + dmc.Paper( + dmc.Stack([ + dmc.Text("Fee Impact Calculator", fw=600, size="lg"), + dmc.Text("Adjust investment amount and time horizon to see the impact of fees", size="sm", c="dimmed"), + dmc.Grid([ + dmc.GridCol([ + dmc.Stack([ + dmc.Text("Investment Amount", size="sm", fw=500), + dmc.NumberInput( + id="investment-amount", + value=10000, + min=1000, + max=1000000, + step=1000, + prefix="$", + thousandSeparator=",", + w="100%", + ), + ], gap="xs"), + ], span={"base": 12, "sm": 6, "md": 3}), + dmc.GridCol([ + dmc.Stack([ + dmc.Text("Time Horizon (Years)", size="sm", fw=500), + dmc.Slider( + id="time-horizon", + value=10, + min=1, + max=30, + step=1, + marks=[ + {"value": 1, "label": "1"}, + {"value": 10, "label": "10"}, + {"value": 20, "label": "20"}, + {"value": 30, "label": "30"}, + ], + mt="md", + ), + dmc.Space(h=20), + ], gap="xs"), + ], span={"base": 12, "sm": 6, "md": 5}), + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Stack([ + dmc.Text("Your Savings", size="xs", c="dimmed", tt="uppercase", fw=500), + dmc.Text("$1,913", size="28px", fw=700, c="teal", id="savings-amount"), + dmc.Text("vs category average", size="xs", c="dimmed"), + ], gap=2, align="center"), + dmc.Divider(), + dmc.Group([ + dmc.Stack([ + dmc.Text("This Fund", size="xs", c="dimmed"), + dmc.Text("$19,672", size="lg", fw=600, c="teal", id="final-value-fund"), + ], gap=2, align="center"), + dmc.Divider(orientation="vertical", h=40), + dmc.Stack([ + dmc.Text("Category Avg", size="xs", c="dimmed"), + dmc.Text("$17,759", size="lg", fw=600, c="gray", id="final-value-avg"), + ], gap=2, align="center"), + ], justify="center", gap="xl"), + ], gap="sm"), + p="md", + radius="md", + bg="var(--mantine-color-gray-0)", + style={"border": "1px dashed var(--mantine-color-gray-4)"}, + ), + ], span={"base": 12, "md": 4}), + ], gutter="md", align="center"), + ], gap="md"), + p="md", + radius="md", + withBorder=True, + ), + + # Fee Highlight Cards + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Expense Ratio", size="sm", c="dimmed"), + dmc.Group([ + dmc.Text("0.14%", size="xl", fw=700, c="green"), + dmc.Badge("85% below avg", color="green", size="sm"), + ], gap="sm"), + dmc.Text("Category average: 0.99%", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Distribution Yield", size="sm", c="dimmed"), + dmc.Text("1.77%", size="xl", fw=700), + dmc.Text("Annual yield based on distributions", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("SEC Yield", size="sm", c="dimmed"), + dmc.Text("1.77%", size="xl", fw=700), + dmc.Text("30-day SEC yield", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Annual Fee", size="sm", c="dimmed"), + dmc.Text("$14", size="xl", fw=700, c="green"), + dmc.Text("Per $10,000 invested", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + + # Fee Charts Row + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dcc.Graph( + id="fee-comparison-chart", + figure=create_fee_comparison_chart(), + config={"displayModeBar": False}, + style={"height": "350px"} + ), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dcc.Graph( + figure=create_fee_waterfall(), + config={"displayModeBar": False}, + style={"height": "350px"} + ), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + # Long-term Cost Impact + dmc.Paper( + dcc.Graph( + id="cost-impact-chart", + figure=create_cost_impact_chart(), + config={"displayModeBar": False}, + style={"height": "350px"} + ), + p="md", + radius="md", + withBorder=True, + ), + + # Distributions Section + dmc.Title("Distributions", order=3, mt="lg"), + + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dcc.Graph( + figure=create_dividend_calendar(), + config={"displayModeBar": False}, + style={"height": "300px"} + ), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Recent Distributions", fw=600, size="lg"), + create_data_table(dividend_data.head(5)), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + # Capital Gains Section + dmc.Title("Capital Gains", order=3, mt="lg"), + + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Realized Gains", fw=600, size="lg"), + create_data_table(df_realized), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Unrealized Appreciation", fw=600, size="lg"), + create_data_table(df_unrealized), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + +], gap="md") diff --git a/investments-dashboard/pages/performance.py b/investments-dashboard/pages/performance.py new file mode 100644 index 0000000..28ccb3c --- /dev/null +++ b/investments-dashboard/pages/performance.py @@ -0,0 +1,364 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify +import plotly.graph_objects as go + +from components.charts import create_performance_line_chart, CHART_COLORS, CHART_LAYOUT +from utils.data_loader import ( + get_time_series_data, get_returns_data, + df_current_prices, df_avg_returns, df_after_tax, df_recent_returns +) + +ts_data = get_time_series_data() +returns_data = get_returns_data() + +def create_returns_table(df): + """Create properly formatted returns table from raw CSV data""" + data = df.values.tolist() + + if len(data) < 2: + return dmc.Text("No data available", c="dimmed") + + headers = [str(h).replace("'-", "").strip() or "Fund" for h in data[0]] + rows_data = data[1:] + + header = dmc.TableThead( + dmc.TableTr([ + dmc.TableTh(col, style={'fontWeight': 600, 'fontSize': '13px'}) for col in headers + ]) + ) + + rows = [] + for row in rows_data: + cells = [] + for i, val in enumerate(row): + val_str = str(val).replace("'-", "—").strip() + style = {'fontSize': '13px'} + + if '%' in val_str and val_str not in ['—', '']: + try: + num = float(val_str.replace('%', '')) + style['color'] = '#40c057' if num > 0 else '#fa5252' if num < 0 else None + style['fontWeight'] = 500 + except: + pass + + if i == 0: + style['fontWeight'] = 500 + + cells.append(dmc.TableTd(val_str if val_str else "—", style=style)) + rows.append(dmc.TableTr(cells)) + + body = dmc.TableTbody(rows) + + return dmc.ScrollArea( + dmc.Table( + [header, body], + striped=True, + highlightOnHover=True, + withTableBorder=True, + withColumnBorders=False, + verticalSpacing="xs", + ), + type="auto" + ) + +def create_drawdown_chart(df): + """Calculate and plot drawdown""" + prices = df['Calibre Index Fund'].values + peak = prices[0] + drawdowns = [] + + for price in prices: + if price > peak: + peak = price + drawdown = (price - peak) / peak * 100 + drawdowns.append(drawdown) + + fig = go.Figure() + fig.add_trace(go.Scatter( + x=df['Date'], + y=drawdowns, + fill='tozeroy', + line={'color': CHART_COLORS['danger'], 'width': 1}, + fillcolor='rgba(250, 82, 82, 0.2)', + name='Drawdown', + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Drawdown Analysis', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + yaxis={'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)', 'ticksuffix': '%'}, + showlegend=False, + ) + return fig + +initial_total_return = ((ts_data['Calibre Index Fund'].iloc[-1] - ts_data['Calibre Index Fund'].iloc[0]) / ts_data['Calibre Index Fund'].iloc[0] * 100) + +layout = dmc.Stack([ + # Page Header + dmc.Stack([ + dmc.Group([ + dmc.Stack([ + dmc.Title("Price Performance", order=2), + dmc.Text("Historical prices, returns analysis, and benchmark comparison", c="dimmed"), + ], gap=4), + ], justify="space-between"), + + # Filter Row + dmc.Paper( + dmc.Group([ + dmc.Group([ + dmc.Text("Period", size="xs", fw=500, c="dimmed"), + dmc.SegmentedControl( + id="performance-period", + data=["1M", "3M", "6M", "1Y", "3Y", "5Y", "All"], + value="All", + size="xs", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Benchmarks", size="xs", fw=500, c="dimmed"), + dmc.MultiSelect( + id="benchmark-selector", + data=[ + {"value": "calibre", "label": "Calibre Index Fund"}, + {"value": "msci", "label": "MSCI EAFE Index"}, + {"value": "sp500", "label": "S&P 500"}, + ], + value=["calibre", "msci", "sp500"], + w=220, + clearable=True, + size="xs", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Display", size="xs", fw=500, c="dimmed"), + dmc.Switch( + id="normalize-toggle", + label="Normalize", + checked=True, + size="xs", + ), + dmc.Switch( + id="log-scale-toggle", + label="Log Scale", + checked=False, + size="xs", + ), + ], gap=8), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Overlay", size="xs", fw=500, c="dimmed"), + dmc.Select( + id="ma-selector", + data=[ + {"value": "none", "label": "No MA"}, + {"value": "20", "label": "20-day"}, + {"value": "50", "label": "50-day"}, + {"value": "200", "label": "200-day"}, + ], + value="none", + w=100, + size="xs", + ), + ], gap=6), + ], gap="md", align="center"), + p="sm", + radius="md", + withBorder=True, + ), + ], gap="sm", mb="md"), + + # 1. Stats Cards Row (TOP) + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Period High", size="sm", c="dimmed"), + dmc.Text( + f"${ts_data['Calibre Index Fund'].max():.2f}", + size="xl", fw=700, c="green", + id="period-high-value" + ), + dmc.Text( + ts_data.loc[ts_data['Calibre Index Fund'].idxmax(), 'Date'].strftime('%Y-%m-%d'), + size="xs", c="dimmed", + id="period-high-date" + ), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Period Low", size="sm", c="dimmed"), + dmc.Text( + f"${ts_data['Calibre Index Fund'].min():.2f}", + size="xl", fw=700, c="red", + id="period-low-value" + ), + dmc.Text( + ts_data.loc[ts_data['Calibre Index Fund'].idxmin(), 'Date'].strftime('%Y-%m-%d'), + size="xs", c="dimmed", + id="period-low-date" + ), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Current Price", size="sm", c="dimmed"), + dmc.Text( + f"${ts_data['Calibre Index Fund'].iloc[-1]:.2f}", + size="xl", fw=700, + id="current-price-value" + ), + dmc.Text("Latest available", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Total Return", size="sm", c="dimmed"), + dmc.Text( + f"{initial_total_return:.1f}%", + size="xl", fw=700, + c="green" if initial_total_return > 0 else "red", + id="total-return-value" + ), + dmc.Text("For selected period", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + + # 2. Performance Metrics Row (SECOND) + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Volatility (Ann.)", size="sm", c="dimmed"), + dmc.Text("0.0%", size="xl", fw=700, id="perf-volatility"), + dmc.Text("Std deviation of returns", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Max Drawdown", size="sm", c="dimmed"), + dmc.Text("0.0%", size="xl", fw=700, c="red", id="perf-max-drawdown"), + dmc.Text("Worst peak-to-trough", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Sharpe Ratio", size="sm", c="dimmed"), + dmc.Text("0.00", size="xl", fw=700, id="perf-sharpe"), + dmc.Text("Risk-adjusted return", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Best / Worst Day", size="sm", c="dimmed"), + dmc.Group([ + dmc.Text("+0.0%", size="lg", fw=700, c="green", id="perf-best-day"), + dmc.Text("/", size="lg", c="dimmed"), + dmc.Text("-0.0%", size="lg", fw=700, c="red", id="perf-worst-day"), + ], gap=4), + dmc.Text("Single-day extremes", size="xs", c="dimmed"), + ], gap=4), + p="md", + radius="md", + withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + + # 3. Returns Tables and Analysis Charts Row (THIRD) + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Tabs([ + dmc.TabsList([ + dmc.TabsTab("Average Returns", value="avg"), + dmc.TabsTab("After Tax", value="tax"), + dmc.TabsTab("Recent Returns", value="recent"), + ]), + dmc.TabsPanel(create_returns_table(df_avg_returns), value="avg", pt="md"), + dmc.TabsPanel(create_returns_table(df_after_tax), value="tax", pt="md"), + dmc.TabsPanel(create_returns_table(df_recent_returns), value="recent", pt="md"), + ], value="avg"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Tabs([ + dmc.TabsList([ + dmc.TabsTab("Drawdown", value="drawdown"), + dmc.TabsTab("Rolling Returns", value="rolling"), + ]), + dmc.TabsPanel( + dcc.Graph( + id="drawdown-chart", + figure=create_drawdown_chart(ts_data), + config={"displayModeBar": False}, + style={"height": "300px"} + ), + value="drawdown", pt="md" + ), + dmc.TabsPanel( + dcc.Graph( + id="rolling-returns-chart", + figure=go.Figure(), + config={"displayModeBar": False}, + style={"height": "300px"} + ), + value="rolling", pt="md" + ), + ], value="drawdown", id="analysis-tabs"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + # 4. Main Performance Chart (BOTTOM) + dmc.Paper( + dmc.Stack([ + dcc.Graph( + id="performance-chart", + figure=create_performance_line_chart(ts_data), + config={"displayModeBar": False}, + style={"height": "400px"} + ), + ]), + p="md", + radius="md", + withBorder=True, + ), + +], gap="md") diff --git a/investments-dashboard/pages/portfolio.py b/investments-dashboard/pages/portfolio.py new file mode 100644 index 0000000..557f38e --- /dev/null +++ b/investments-dashboard/pages/portfolio.py @@ -0,0 +1,414 @@ +import dash_mantine_components as dmc +from dash_iconify import DashIconify +from dash import dcc, html +import plotly.graph_objects as go +import plotly.express as px + +from components.charts import create_sector_donut_chart, CHART_COLORS, CHART_LAYOUT +from components.tables import create_data_table +from utils.data_loader import get_sector_allocation, df_equity_char, df_equity_diver + +sector_data = get_sector_allocation() + +def create_style_box(): + """Create 3x3 investment style box""" + fig = go.Figure() + + labels = [ + ['Large Value', 'Large Blend', 'Large Growth'], + ['Mid Value', 'Mid Blend', 'Mid Growth'], + ['Small Value', 'Small Blend', 'Small Growth'] + ] + + for i in range(3): + for j in range(3): + color = '#228be6' if (i == 0 and j == 1) else '#f1f3f5' + opacity = 1 if (i == 0 and j == 1) else 0.5 + + fig.add_shape( + type="rect", + x0=j, x1=j+1, y0=2-i, y1=3-i, + fillcolor=color, + opacity=opacity, + line={'color': '#dee2e6', 'width': 1}, + ) + + fig.add_annotation( + x=j+0.5, y=2.5-i, + text=labels[i][j], + showarrow=False, + font={'size': 10, 'color': '#fff' if (i == 0 and j == 1) else '#495057'}, + ) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Investment Style', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + xaxis={'visible': False, 'range': [-0.1, 3.1]}, + yaxis={'visible': False, 'range': [-0.1, 3.1]}, + height=300, + ) + + return fig + +def create_sector_comparison_bar(): + """Create horizontal bar chart comparing fund vs benchmark sectors""" + fig = go.Figure() + + fig.add_trace(go.Bar( + y=sector_data['Sector'], + x=sector_data['Fund'], + name='Fund', + orientation='h', + marker_color=CHART_COLORS['primary'], + )) + + fig.add_trace(go.Bar( + y=sector_data['Sector'], + x=sector_data['Benchmark'], + name='Benchmark', + orientation='h', + marker_color=CHART_COLORS['gray'], + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Sector Allocation vs Benchmark', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + barmode='group', + bargap=0.3, + legend={'orientation': 'h', 'y': -0.15}, + xaxis={'title': 'Allocation %', 'ticksuffix': '%'}, + yaxis={'title': ''}, + height=450, + ) + + return fig + +def create_risk_return_scatter(): + """Create risk/return scatter plot""" + funds = ['500 Index Fund', 'MSCI EAFE', 'Growth Fund', 'Value Fund', 'Bond Fund'] + returns = [16.94, 14.2, 19.5, 12.3, 5.2] + risk = [15.2, 18.5, 22.1, 14.8, 6.3] + sizes = [100, 80, 60, 70, 50] + + fig = go.Figure() + + fig.add_trace(go.Scatter( + x=risk, + y=returns, + mode='markers+text', + marker={'size': sizes, 'color': px.colors.qualitative.Set2[:5], 'opacity': 0.7}, + text=funds, + textposition='top center', + hovertemplate='%{text}
Risk: %{x:.1f}%
Return: %{y:.1f}%' + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Risk vs Return', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + xaxis={'title': 'Risk (Std Dev %)', 'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)'}, + yaxis={'title': 'Return %', 'showgrid': True, 'gridcolor': 'rgba(0,0,0,0.05)'}, + height=350, + ) + + return fig + +def create_donut_with_click(): + """Create donut chart configured for click events""" + colors = px.colors.qualitative.Set3[:len(sector_data)] + + fig = go.Figure(go.Pie( + labels=sector_data['Sector'], + values=sector_data['Fund'], + hole=0.6, + marker={'colors': colors}, + textinfo='percent', + textposition='outside', + hovertemplate='%{label}
%{value:.1f}%' + )) + + fig.update_layout( + **CHART_LAYOUT, + title={'text': 'Sector Allocation (Click to highlight)', 'x': 0, 'font': {'size': 16, 'weight': 600}}, + showlegend=True, + legend={'orientation': 'v', 'x': 1.05, 'y': 0.5}, + annotations=[{ + 'text': 'Sectors', + 'x': 0.5, 'y': 0.5, + 'font': {'size': 14, 'weight': 600}, + 'showarrow': False + }] + ) + + return fig + +# Allocation View Content +allocation_view = html.Div([ + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dcc.Graph( + id="sector-donut", + figure=create_donut_with_click(), + config={"displayModeBar": False}, + style={"height": "400px"} + ), + dmc.Text("Click on a sector to see details", size="sm", c="dimmed", ta="center", id="sector-detail-text"), + ]), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Stack([ + dmc.Paper( + dcc.Graph( + figure=create_style_box(), + config={"displayModeBar": False}, + ), + p="md", + radius="md", + withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Portfolio Style Summary", fw=600), + dmc.Group([ + dmc.Badge("Large Cap", color="blue", size="lg"), + dmc.Badge("Blend", color="gray", size="lg"), + dmc.Badge("Domestic", color="green", size="lg"), + ]), + dmc.Text( + "This fund tracks the S&P 500 Index, providing broad exposure to large-cap U.S. equities across value, blend, and growth styles.", + size="sm", c="dimmed", mt="xs" + ), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ), + ], gap="md"), + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + dmc.Paper( + dcc.Graph( + id="sector-bar-chart", + figure=create_sector_comparison_bar(), + config={"displayModeBar": False}, + ), + p="md", + radius="md", + withBorder=True, + mt="md", + ), +], id="allocation-view") + +# Characteristics View Content +characteristics_view = html.Div([ + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Equity Characteristics", fw=600, size="lg"), + create_data_table(df_equity_char), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Sector Diversification", fw=600, size="lg"), + create_data_table(df_equity_diver), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + dmc.Paper( + dmc.Stack([ + dmc.Text("Key Metrics Comparison", fw=600, size="lg"), + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("P/E Ratio", size="sm", c="dimmed"), + dmc.Text("21.4", size="xl", fw=700), + dmc.Text("vs 22.1 benchmark", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("P/B Ratio", size="sm", c="dimmed"), + dmc.Text("3.2", size="xl", fw=700), + dmc.Text("vs 3.4 benchmark", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Dividend Yield", size="sm", c="dimmed"), + dmc.Text("1.8%", size="xl", fw=700), + dmc.Text("vs 1.7% benchmark", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Earnings Growth", size="sm", c="dimmed"), + dmc.Text("12.5%", size="xl", fw=700), + dmc.Text("5-year average", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + mt="md", + ), +], id="characteristics-view", style={"display": "none"}) + +# Risk Analysis View Content +risk_view = html.Div([ + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dcc.Graph( + figure=create_risk_return_scatter(), + config={"displayModeBar": False}, + style={"height": "400px"} + ), + p="md", + radius="md", + withBorder=True, + ) + ], span={"base": 12, "md": 6}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Risk Metrics", fw=600, size="lg"), + dmc.Stack([ + dmc.Group([ + dmc.Text("Standard Deviation", size="sm", w=150), + dmc.Progress(value=65, color="blue", size="lg", style={"flex": 1}), + dmc.Text("15.2%", size="sm", fw=500, w=60), + ], gap="sm"), + dmc.Group([ + dmc.Text("Beta", size="sm", w=150), + dmc.Progress(value=100, color="green", size="lg", style={"flex": 1}), + dmc.Text("1.00", size="sm", fw=500, w=60), + ], gap="sm"), + dmc.Group([ + dmc.Text("Sharpe Ratio", size="sm", w=150), + dmc.Progress(value=70, color="teal", size="lg", style={"flex": 1}), + dmc.Text("0.85", size="sm", fw=500, w=60), + ], gap="sm"), + dmc.Group([ + dmc.Text("Sortino Ratio", size="sm", w=150), + dmc.Progress(value=75, color="cyan", size="lg", style={"flex": 1}), + dmc.Text("1.12", size="sm", fw=500, w=60), + ], gap="sm"), + dmc.Group([ + dmc.Text("Max Drawdown", size="sm", w=150), + dmc.Progress(value=35, color="red", size="lg", style={"flex": 1}), + dmc.Text("-33.8%", size="sm", fw=500, w=60), + ], gap="sm"), + dmc.Group([ + dmc.Text("Tracking Error", size="sm", w=150), + dmc.Progress(value=10, color="gray", size="lg", style={"flex": 1}), + dmc.Text("0.04%", size="sm", fw=500, w=60), + ], gap="sm"), + ], gap="md", mt="md"), + ], gap="sm"), + p="md", + radius="md", + withBorder=True, + h="100%", + ) + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + dmc.Paper( + dmc.Stack([ + dmc.Text("Risk Analysis Summary", fw=600, size="lg"), + dmc.Alert( + "This fund closely tracks its benchmark (S&P 500) with minimal tracking error. The risk profile is consistent with broad market exposure.", + title="Low Tracking Error", + color="blue", + ), + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Upside Capture", size="sm", c="dimmed"), + dmc.Text("99.8%", size="xl", fw=700, c="green"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Downside Capture", size="sm", c="dimmed"), + dmc.Text("100.2%", size="xl", fw=700, c="red"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Information Ratio", size="sm", c="dimmed"), + dmc.Text("-0.12", size="xl", fw=700), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("R-Squared", size="sm", c="dimmed"), + dmc.Text("99.9%", size="xl", fw=700, c="green"), + ], gap=4), + p="md", radius="sm", withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + ], gap="md"), + p="md", + radius="md", + withBorder=True, + mt="md", + ), +], id="risk-view", style={"display": "none"}) + +layout = dmc.Stack([ + # Page Header + dmc.Group([ + dmc.Stack([ + dmc.Title("Portfolio Analysis", order=2), + dmc.Text("Asset allocation, sector breakdown, and portfolio characteristics", c="dimmed"), + ], gap=4), + dmc.Group([ + dmc.SegmentedControl( + id="portfolio-view", + data=[ + {"value": "allocation", "label": "Allocation"}, + {"value": "characteristics", "label": "Characteristics"}, + {"value": "risk", "label": "Risk Analysis"}, + ], + value="allocation", + ), + ], gap="sm"), + ], justify="space-between", mb="lg"), + + # View Containers + allocation_view, + characteristics_view, + risk_view, + +], gap="md") diff --git a/investments-dashboard/requirements.txt b/investments-dashboard/requirements.txt new file mode 100644 index 0000000..634cddf --- /dev/null +++ b/investments-dashboard/requirements.txt @@ -0,0 +1,10 @@ +dash[fastapi]==4.2.0 +dash-mantine-components>=0.14.0 +dash-iconify>=0.1.2 +pandas>=2.0.0 +plotly>=5.18.0 +uvicorn[standard] +reportlab>=4.0.0 +kaleido==0.2.1 +PyPDF2>=3.0.0 +Pillow>=10.0.0 diff --git a/investments-dashboard/scripts/dash-callbacks-intro.md b/investments-dashboard/scripts/dash-callbacks-intro.md new file mode 100644 index 0000000..a6e7bca --- /dev/null +++ b/investments-dashboard/scripts/dash-callbacks-intro.md @@ -0,0 +1,102 @@ +# Video Script: Basic Dash Callbacks — Dash Fundamentals Chapter 2 +**Target length:** Under 5 minutes +**Format:** Screen recording with voiceover, code running live +**Narration word count:** ~510 words (~4 min at 130 wpm + visual pauses) + +--- + +## Beat 1 — Hook `[0:00–0:20]` + +**[VISUAL]** Open on the gapminder scatter plot with the year slider. Drag the slider — the chart animates smoothly through decades of data. + +**[NARRATION]** +> "In the last chapter, we built a Dash layout. It looked great — but it didn't do anything. This is what happens when you add callbacks. One slider, one chart, fully connected. Let me show you how it works." + +--- + +## Beat 2 — The Why: Reactive Programming `[0:20–0:55]` + +**[VISUAL]** Stay on the gapminder app, or cut to a simple spreadsheet visual. + +**[NARRATION]** +> "The mental model here is a spreadsheet. When you change a cell, every cell that depends on it updates automatically. You don't call a function — the dependency is declared, and the system handles the rest. +> +> Dash works exactly the same way. You declare: when this input changes, call this function and put the result in that output. Dash handles the wiring. This is reactive programming — and it's the entire foundation of how Dash apps become interactive." + +--- + +## Beat 3 — Anatomy of a Callback `[0:55–2:10]` + +**[VISUAL]** Open the simple text input example in the editor. Highlight each section as you talk through it. + +**[NARRATION]** +> "Let's start with the simplest possible example. A text box and a div — typing in the box updates the div. +> +> The layout is what you already know: a `dcc.Input` with an `id`, and an empty `html.Div` with an `id`. No value set on the div — we'll let the callback populate it. +> +> Now the callback. The `@callback` decorator is where the wiring happens. `Output` is what you want to update — the `children` property of `my-output`. `Input` is what triggers it — the `value` property of `my-input`. +> +> The function underneath receives the current value of the input and returns whatever should go in the output. That's it. +> +> A few things worth noting: the `id` in the decorator must match exactly the `id` in your layout. And the decorator has to sit directly above the function — no blank lines between them." + +**[VISUAL]** Run the app, type in the text box, show the div updating live. + +--- + +## Beat 4 — Real Demo: Slider → Graph `[2:10–3:05]` + +**[VISUAL]** Open the gapminder `app.py`. Highlight the `@callback` and then the function body. + +**[NARRATION]** +> "Now let's look at a real example. The `dcc.Slider` has an `id` of `year-slider`, and its `value` property is the input. The `dcc.Graph` is the output — specifically its `figure` property. +> +> Whenever the slider moves, Dash calls `update_figure` with the selected year. The function filters the dataframe down to that year, builds a new Plotly scatter plot, and returns it. Dash puts it in the graph. +> +> Notice `fig.update_layout(transition_duration=500)` — that's what gives the smooth animation between years. One line." + +--- + +## Beat 5 — Multiple Inputs `[3:05–3:30]` + +**[VISUAL]** Show the multi-input example's `@callback` decorator — 5 inputs listed. + +**[NARRATION]** +> "You're not limited to one input. This example drives a chart from two dropdowns, two radio buttons, and a slider — five inputs, one output. +> +> The pattern is the same: just list more `Input` items in the decorator. The callback receives them as positional arguments, in the same order. Any one of them changing triggers the function." + +--- + +## Beat 6 — State `[3:30–4:15]` + +**[VISUAL]** Open the State / button example. Show both the `Input` and `State` lines in the decorator. + +**[NARRATION]** +> "Now let's talk about `State`. Sometimes you want to read a value without that value triggering the callback. Classic example: a form with a Submit button. +> +> Here, the two text inputs are `State` — Dash reads their values, but typing in them does nothing. The `html.Button` is the `Input` — clicking it fires the callback. Dash passes all the `State` values into the function automatically. +> +> The rule is simple: `Input` triggers, `State` reads. Everything else about the function is the same." + +--- + +## Beat 7 — Summary + CTA `[4:15–4:30]` + +**[VISUAL]** Quick cut back to the gapminder app with the slider moving. + +**[NARRATION]** +> "Callbacks are the engine of every Dash app. Declare your inputs and outputs, write a Python function, and Dash handles the rest. One input or five, one output or many — the pattern doesn't change. +> +> Chapter 3 goes deeper: clicking on charts to drive other charts. Interactive graphing. Link's in the description." + +--- + +## Production Notes +- Beat 1: actually drag the slider on camera — the animation is the hook +- Beat 3: slow down here — this is the first time the viewer sees a decorator. Hover over `Output` then `Input` as you name them +- Beat 3 live demo: type something in the text box slowly, pause so the viewer sees the div react +- Beat 4: pause after showing `transition_duration=500` — it's a satisfying "one line does this" moment +- Beat 5: you don't need to run this app — just show the decorator in the editor. The point is the pattern, not the demo +- Beat 6: live demo here is useful — type in the text boxes, show nothing happens, then click Submit, show it fires +- Outro card: link to [Dash Fundamentals Part 3: Interactive Graphing](https://dash.plotly.com/docs/interactive-graphing) diff --git a/investments-dashboard/scripts/dash-interactive-graphing-intro.md b/investments-dashboard/scripts/dash-interactive-graphing-intro.md new file mode 100644 index 0000000..6cb3006 --- /dev/null +++ b/investments-dashboard/scripts/dash-interactive-graphing-intro.md @@ -0,0 +1,90 @@ +# Video Script: Interactive Visualizations — Dash Fundamentals Chapter 3 +**Target length:** Under 5 minutes +**Format:** Screen recording with voiceover, code running live +**Narration word count:** ~490 words (~3:45–4:00 at 130 wpm + visual pauses) + +--- + +## Beat 1 — Hook `[0:00–0:20]` + +**[VISUAL]** World indicators app running — scatter plot on the left, two time series on the right. Slowly move the mouse over different country dots. The time series update in real time with each hover. + +**[NARRATION]** +> "In the last chapter, callbacks reacted to controls — dropdowns, sliders, buttons. This chapter goes further. Here, the chart itself is the input. Hover over a country, and the graphs on the right update instantly. Let me show you how this works." + +--- + +## Beat 2 — The Why: Charts as Inputs `[0:20–0:50]` + +**[VISUAL]** Stay on the world indicators app, or briefly show a traditional BI tool for contrast. + +**[NARRATION]** +> "Most charting tools are one-way: data goes in, chart comes out. Dash flips this. Every interaction a user has with a chart — hovering over a point, clicking it, drawing a selection box, zooming — all of that is data you can feed into a callback. +> +> This is how you build crossfiltered dashboards and linked charts. Not with a specialized tool — just callbacks." + +--- + +## Beat 3 — The 4 Interactive Properties `[0:50–1:40]` + +**[VISUAL]** Show the debug app running. Hover over points, click points, use the lasso tool, zoom — watch the JSON panels update on screen. + +**[NARRATION]** +> "The `dcc.Graph` component has four properties that update through user interaction: `hoverData`, `clickData`, `selectedData`, and `relayoutData`. +> +> This debug app prints them live so you can see exactly what you're working with. Hover over a point — `hoverData` gets the coordinates, the point index, and any custom data you attached. Click — same thing in `clickData`. Draw a selection — `selectedData` gives you every point inside the box. Zoom or pan — `relayoutData` captures the new axis ranges. +> +> Any of these can be an `Input` in a callback." + +--- + +## Beat 4 — Hover → Time Series `[1:40–3:05]` + +**[VISUAL]** Open the world indicators `app.py`. Highlight the scatter callback first, then the `update_x_timeseries` callback. + +**[NARRATION]** +> "Let's look at the hover example. The scatter plot on the left has `id='crossfilter-indicator-scatter'`. The two time series have their own IDs. +> +> The key line is here — `hoverData` of the scatter is an `Input`. Whenever the mouse moves to a new point, this callback fires. +> +> Now, how does the callback know which country was hovered? That's what `customdata` is for. When building the scatter, we attach the country name to each point with `fig.update_traces(customdata=...)`. Then inside the callback, we pull it out with `hoverData['points'][0]['customdata']`. +> +> From there it's just pandas filtering and returning a new figure — the same pattern as Chapter 2, just with hover as the trigger instead of a slider." + +**[VISUAL]** Show the `create_time_series` helper function briefly. + +> "The `create_time_series` function is a reusable helper — the kind of thing you build once and call from multiple callbacks. Clean Python." + +--- + +## Beat 5 — Crossfilter Pattern `[3:05–3:45]` + +**[VISUAL]** Switch to the 3-chart crossfilter app running. Use the lasso tool to select a cluster of points in one chart. Show the other two charts dim the unselected points and update the dashed selection rectangle. + +**[NARRATION]** +> "Here's the crossfilter pattern. Three scatter plots, each with `selectedData` as an input to a shared callback. Select a region in any chart, and all three update — the selected points stay highlighted, everything else fades. +> +> The callback takes the intersection of all three selections and rerenders all three figures. The charts are both inputs and outputs at the same time. +> +> You don't need a BI tool for this. It's a Python function." + +--- + +## Beat 6 — Summary + CTA `[3:45–4:00]` + +**[VISUAL]** Quick cut back to the hover → time series demo. + +**[NARRATION]** +> "Dash charts expose hover, click, selection, and zoom as callback inputs. Same decorator, same Python function — you just use the chart as the trigger instead of a control. +> +> Chapter 4 covers something that comes up quickly in real apps: sharing data between callbacks without running the same query twice. Link's in the description." + +--- + +## Production Notes +- Beat 1: move the mouse slowly and deliberately over 3–4 countries — let the time series settle between moves so the update is clear +- Beat 3: use the debug app for this beat — it's the best way to show what `hoverData` actually contains; pause on the hover JSON so viewers can read it +- Beat 4: hover over the `customdata` line in the code and also the `hoverData['points'][0]['customdata']` extraction — this is the non-obvious part +- Beat 5: start the crossfilter demo with no selection (all bright), then lasso select — the visual contrast of highlighted vs dimmed is the whole story +- Beat 5: don't walk through the crossfilter code — the running demo is enough; the docs page has the full code for reference +- Outro card: link to [Dash Fundamentals Part 4: Sharing Data Between Callbacks](https://dash.plotly.com/docs/sharing-data-between-callbacks) diff --git a/investments-dashboard/scripts/dash-layout-intro.md b/investments-dashboard/scripts/dash-layout-intro.md new file mode 100644 index 0000000..2ab130e --- /dev/null +++ b/investments-dashboard/scripts/dash-layout-intro.md @@ -0,0 +1,108 @@ +# Video Script: Dash Layout — Dash Fundamentals Chapter 1 +**Target length:** Under 5 minutes +**Format:** Screen recording with voiceover, code running live +**Narration word count:** ~515 words (~4 min at 130 wpm + visual pauses) + +--- + +## Beat 1 — Hook `[0:00–0:20]` + +**[VISUAL]** Open on the finished bar chart app already running at `localhost:8050` — fruits grouped by city, interactive, polished. + +**[NARRATION]** +> "This is a Dash app. Interactive, browser-based, deployable anywhere — and we just built it in about 20 lines of Python. No JavaScript. No HTML files. No CSS from scratch. Let me show you how." + +--- + +## Beat 2 — The Why `[0:20–0:55]` + +**[VISUAL]** Briefly show a terminal with pandas output, or a static matplotlib plot — the kind of thing you'd share as a screenshot. + +**[NARRATION]** +> "If you work with data in Python, you've probably hit this wall. You've got a great analysis — a dataframe, a Plotly chart — but getting it in front of someone else means emailing a screenshot or sending a CSV and hoping they run the same environment. +> +> Building a proper web app means learning a frontend framework, and suddenly you're context-switching between Python and JavaScript. +> +> Dash is the bridge. You stay in Python, and Dash handles the web layer." + +--- + +## Beat 3 — Your First App `[0:55–2:00]` + +**[VISUAL]** Open `app.py` in the editor — the bar chart example. Highlight each section as you mention it. + +**[NARRATION]** +> "Let's look at what we're actually writing. Three things happen here. +> +> First, we create data — just a standard pandas DataFrame. +> +> Then we create a Plotly figure with `px.bar`. Standard Plotly Express. +> +> And then comes the Dash part: `app.layout`. This is where you describe what your app looks like — a tree of Python component objects. +> +> `html.Div` is a wrapper. `html.H1` is a heading. `dcc.Graph` takes our Plotly figure and renders it as an interactive chart in the browser. +> +> Run it with `python app.py`, open localhost:8050, and there it is." + +**[VISUAL]** Terminal running, browser opens to the app. + +> "Notice `debug=True` — that turns on hot reload. Change the title, save the file — your browser updates instantly. No restart needed." + +--- + +## Beat 4 — Styling with HTML Components `[2:00–2:50]` + +**[VISUAL]** Switch to the dark-mode styled app. Show the `style={}` dict in the editor. + +**[NARRATION]** +> "Now let's customize it. Every `dash.html` component maps to an HTML tag, and you control it entirely through Python keyword arguments. +> +> The `style` property works like inline HTML styles — except it's a Python dictionary. Keys are camelCase: `textAlign` instead of `text-align`, `backgroundColor` instead of `background-color`. And `class` becomes `className`. +> +> That's it. Every HTML attribute you know works the same way, just in Python syntax." + +--- + +## Beat 5 — Core Components `[2:50–3:40]` + +**[VISUAL]** Show the components showcase app — dropdowns, sliders, radio items, checkboxes all visible. + +**[NARRATION]** +> "Beyond HTML wrappers, Dash gives you `dash.dcc` — the Dash Core Components. Dropdowns, sliders, radio buttons, text inputs, graphs — all ready to go. +> +> These aren't plain HTML. They're React components under the hood, which is why they're interactive out of the box. +> +> Everything is declarative. Every option is a keyword argument. And if you ever want to know what's available, just run `help(dcc.Dropdown)` in your Python console — it lists every parameter with a description." + +--- + +## Beat 6 — Reusable Components `[3:40–4:10]` + +**[VISUAL]** Show the `generate_table()` function from the table example. + +**[NARRATION]** +> "Here's something that doesn't get talked about enough. Because your layout is Python, you can write functions that generate UI. +> +> This function takes a pandas DataFrame and returns a fully-formed HTML table component — no template language, no Jinja, no string interpolation. Just Python. +> +> That's the real unlock here: you can compose, loop, and abstract your UI the same way you write any other Python code." + +--- + +## Beat 7 — Summary + CTA `[4:10–4:30]` + +**[VISUAL]** Quick cut back to the running bar chart app. + +**[NARRATION]** +> "So: a Dash layout is a tree of Python components. `dash.html` gives you HTML tags. `dash.dcc` gives you interactive components. And because it's all Python, you can compose it like any other code. +> +> This is chapter one. The app looks good — but it doesn't do anything yet. In part two, we wire up callbacks to make it actually interactive. Link's in the description." + +--- + +## Production Notes +- Keep a brisk pace through code — don't read every line, just call out what matters +- For Beat 3, hover or highlight `app.layout`, `html.Div`, `dcc.Graph` as each is mentioned +- Hot reload demo in Beat 3: actually make a live edit on screen — change `'Hello Dash'` to something, save, show the browser update +- Beat 5: interact with the dropdowns and slider briefly to show they work before the narration +- Outro card: link to [Dash Fundamentals Part 2: Basic Callbacks](https://dash.plotly.com/docs/basic-callbacks) diff --git a/investments-dashboard/utils/__init__.py b/investments-dashboard/utils/__init__.py new file mode 100644 index 0000000..dab3080 --- /dev/null +++ b/investments-dashboard/utils/__init__.py @@ -0,0 +1 @@ +from .data_loader import * diff --git a/investments-dashboard/utils/data_loader.py b/investments-dashboard/utils/data_loader.py new file mode 100644 index 0000000..b09a915 --- /dev/null +++ b/investments-dashboard/utils/data_loader.py @@ -0,0 +1,135 @@ +import pandas as pd +import pathlib + +PATH = pathlib.Path(__file__).parent.parent +DATA_PATH = PATH.joinpath("data").resolve() + +def load_csv(filename): + return pd.read_csv(DATA_PATH.joinpath(filename)) + +# Fund data +df_fund_facts = load_csv("df_fund_facts.csv") +df_price_perf = load_csv("df_price_perf.csv") + +# Price data +df_current_prices = load_csv("df_current_prices.csv") +df_hist_prices = load_csv("df_hist_prices.csv") +df_graph = load_csv("df_graph.csv") + +# Returns data +df_avg_returns = load_csv("df_avg_returns.csv") +df_after_tax = load_csv("df_after_tax.csv") +df_recent_returns = load_csv("df_recent_returns.csv") + +# Portfolio data +df_equity_char = load_csv("df_equity_char.csv") +df_equity_diver = load_csv("df_equity_diver.csv") + +# Fees data +df_expenses = load_csv("df_expenses.csv") +df_minimums = load_csv("df_minimums.csv") + +# Distribution data +df_dividend = load_csv("df_dividend.csv") +df_realized = load_csv("df_realized.csv") +df_unrealized = load_csv("df_unrealized.csv") + +def get_time_series_data(): + """Process df_graph for time series charts""" + df = df_graph.copy() + df['Date'] = pd.to_datetime(df['Date']) + return df + +def get_sector_allocation(): + """Process sector diversification data for charts""" + df = df_equity_diver.copy() + df.columns = ['Sector', 'Fund', 'Benchmark'] + df = df.iloc[1:] # Skip header row + df['Fund'] = df['Fund'].str.replace('%', '').astype(float) + df['Benchmark'] = df['Benchmark'].apply(lambda x: 0 if x == '—' else float(str(x).replace('%', ''))) + return df + +def get_returns_data(): + """Process average returns for comparison charts""" + df = df_avg_returns.copy() + df.columns = ['Entity', '1Y', '3Y', '5Y', '10Y', 'Since_Inception'] + df = df.iloc[1:] # Skip header + for col in ['1Y', '3Y', '5Y', '10Y']: + df[col] = df[col].str.replace('%', '').astype(float) + return df + +def get_dividend_history(): + """Process dividend data""" + df = df_dividend.copy() + df.columns = ['Type', 'Amount', 'Record_Date', 'Reinvest_Date', + 'Payable_Date', 'Reinvest_Price', 'Dist_Yield', 'SEC_Yield'] + df = df.iloc[1:] # Skip header + return df + +def get_fund_metrics(): + """Extract key fund metrics for KPI cards""" + facts = dict(zip(df_fund_facts['label'], df_fund_facts['value'])) + + ts = get_time_series_data() + latest_price = ts['Calibre Index Fund'].iloc[-1] + first_price = ts['Calibre Index Fund'].iloc[0] + ytd_return = ((latest_price - first_price) / first_price) * 100 + + returns = get_returns_data() + fund_returns = returns[returns['Entity'].str.contains('500 Index Fund', na=False)].iloc[0] + + return { + 'nav': latest_price, + 'ytd_return': ytd_return, + 'expense_ratio': facts.get('Expense ratio as of 04/27/2017', '0.14%'), + 'category': facts.get('Category', 'Large Blend'), + 'asset_class': facts.get('Asset Class', 'Domestic Stock'), + 'min_investment': facts.get('Minimum investment', '$3,000'), + '1y_return': fund_returns['1Y'], + '3y_return': fund_returns['3Y'], + '5y_return': fund_returns['5Y'], + } + +def calculate_risk_metrics(fund_id, period="1Y"): + """Calculate risk metrics (volatility, beta, sharpe, alpha) for a fund and period""" + ts = get_time_series_data() + + fund_col = 'Calibre Index Fund' + benchmark_col = '"S&P 500 Index, y"' + + period_days = {"1Y": 252, "3Y": 756, "5Y": 1260, "10Y": 2520, "All": len(ts)} + lookback = min(period_days.get(period, 252), len(ts) - 1) + + data = ts[fund_col].iloc[-lookback:] + benchmark = ts[benchmark_col].iloc[-lookback:] + + returns = data.pct_change().dropna() + bench_returns = benchmark.pct_change().dropna() + + volatility = returns.std() * (252 ** 0.5) * 100 + + covariance = returns.cov(bench_returns) + bench_variance = bench_returns.var() + beta = covariance / bench_variance if bench_variance > 0 else 1.0 + + excess_return = returns.mean() * 252 - 0.02 + sharpe = excess_return / (returns.std() * (252 ** 0.5)) if returns.std() > 0 else 0 + + alpha = (returns.mean() * 252) - (0.02 + beta * (bench_returns.mean() * 252 - 0.02)) + + volatility_pct = min(max(volatility / 40 * 100, 10), 100) + beta_pct = min(max(beta * 50, 10), 100) + sharpe_pct = min(max((sharpe + 1) / 3 * 100, 10), 100) + alpha_pct = min(max((alpha * 100 + 5) / 10 * 100, 10), 100) + + return { + 'volatility': volatility, + 'volatility_level': "Low" if volatility < 10 else "Medium" if volatility < 20 else "High", + 'volatility_pct': volatility_pct, + 'beta': beta, + 'beta_pct': beta_pct, + 'sharpe': sharpe, + 'sharpe_pct': sharpe_pct, + 'alpha': alpha * 100, + 'alpha_pct': alpha_pct, + } diff --git a/investments-dashboard/utils/pdf_export.py b/investments-dashboard/utils/pdf_export.py new file mode 100644 index 0000000..58373c0 --- /dev/null +++ b/investments-dashboard/utils/pdf_export.py @@ -0,0 +1,85 @@ +import copy +import io +from datetime import datetime + +import plotly.io as pio +from PIL import Image as PILImage, ImageDraw +from reportlab.lib import colors +from reportlab.lib.pagesizes import A4, landscape, portrait +from reportlab.lib.units import inch +from reportlab.lib.utils import ImageReader +from reportlab.pdfgen import canvas +from PyPDF2 import PdfWriter, PdfReader + + +def figure_to_image_bytes(figure, width=1000, height=600): + try: + fig = copy.deepcopy(figure) + if isinstance(fig, dict): + fig.setdefault('layout', {}) + fig['layout']['paper_bgcolor'] = 'white' + fig['layout']['plot_bgcolor'] = 'white' + return pio.to_image(fig, format="png", width=width, height=height) + except Exception as e: + img = PILImage.new("RGB", (width, height), color=(220, 220, 220)) + draw = ImageDraw.Draw(img) + draw.text((width // 2 - 100, height // 2), f"Render failed: {e}", fill="black") + buf = io.BytesIO() + img.save(buf, format="PNG") + return buf.getvalue() + + +def create_pdf_report(figures, titles=None, report_title="Financial Report"): + if titles is None: + titles = [f"Chart {i + 1}" for i in range(len(figures))] + + portrait_w, portrait_h = portrait(A4) + landscape_w, landscape_h = landscape(A4) + + out = io.BytesIO() + writer = PdfWriter() + + # Title page + p_buf = io.BytesIO() + cp = canvas.Canvas(p_buf, pagesize=portrait(A4)) + cp.setFillColor(colors.HexColor("#2563eb")) + cp.rect(0, portrait_h - 2 * inch, portrait_w, 2 * inch, fill=1, stroke=0) + cp.setFillColor(colors.white) + cp.setFont("Helvetica-Bold", 28) + cp.drawCentredString(portrait_w / 2, portrait_h - 1.2 * inch, report_title) + cp.setFont("Helvetica", 14) + cp.drawCentredString( + portrait_w / 2, + portrait_h - 1.8 * inch, + f"Generated on {datetime.now().strftime('%B %d, %Y')}", + ) + cp.setFillColor(colors.HexColor("#666666")) + cp.setFont("Helvetica", 10) + cp.drawCentredString(portrait_w / 2, 0.5 * inch, "Confidential — not for redistribution") + cp.save() + p_buf.seek(0) + writer.add_page(PdfReader(p_buf).pages[0]) + + # One landscape page per figure + for figure, chart_title in zip(figures, titles): + fig_img = figure_to_image_bytes(figure) + l_buf = io.BytesIO() + cl = canvas.Canvas(l_buf, pagesize=landscape(A4)) + cl.setFillColor(colors.HexColor("#2563eb")) + cl.setFont("Helvetica-Bold", 20) + cl.drawString(1 * inch, landscape_h - 0.8 * inch, chart_title) + img_reader = ImageReader(io.BytesIO(fig_img)) + chart_w, chart_h = 10 * inch, 6 * inch + x = (landscape_w - chart_w) / 2 + y = (landscape_h - chart_h) / 2 - 0.5 * inch + cl.drawImage(img_reader, x, y, width=chart_w, height=chart_h) + cl.setFillColor(colors.HexColor("#666666")) + cl.setFont("Helvetica", 8) + cl.drawCentredString(landscape_w / 2, 0.5 * inch, "CONFIDENTIAL") + cl.save() + l_buf.seek(0) + writer.add_page(PdfReader(l_buf).pages[0]) + + writer.write(out) + out.seek(0) + return out.getvalue() diff --git a/medical-imaging-demo/.gitignore b/medical-imaging-demo/.gitignore new file mode 100644 index 0000000..b9c0379 --- /dev/null +++ b/medical-imaging-demo/.gitignore @@ -0,0 +1,7 @@ + +# Dolt database files (added by bd init) +.dolt/ +*.db + +# AgentOps session artifacts +.agents/ diff --git a/medical-imaging-demo/Procfile b/medical-imaging-demo/Procfile new file mode 100644 index 0000000..673048e --- /dev/null +++ b/medical-imaging-demo/Procfile @@ -0,0 +1 @@ +web: uvicorn app:server --host 0.0.0.0 --port 8000 diff --git a/medical-imaging-demo/README.md b/medical-imaging-demo/README.md new file mode 100644 index 0000000..ad12595 --- /dev/null +++ b/medical-imaging-demo/README.md @@ -0,0 +1,69 @@ +# VitalSight — Clinical Intelligence Platform + +A Plotly Dash demonstration of clinical data visualization, built to mirror the architecture of `dash-financial-report-v2`. + +> **IMPORTANT:** All patient data is **synthetic and de-identified**. X-ray images are algorithmically generated grayscale placeholders. This application is for demonstration purposes only and is not intended for clinical use. + +## Features + +- **Clinical Dashboard** — Census KPIs + live ICU vitals streaming via WebSocket (mirrors the financial app's live stock feed) +- **Patient Vitals** — Multi-vital time-series with normal-range bands, moving averages, and period selectors +- **Cohort Explorer** — Crossfilter linked-brushing across 3 biomarker scatter plots (port of the crossfilter demo) +- **Imaging Workstation** — Interactive X-ray annotation (draw rectangles, lines, circles), window/level controls, AI-assist suggested findings, and radiology report PDF export + +## Setup + +```bash +python -m venv venv +source venv/bin/activate +pip install -r requirements.txt + +# Generate synthetic data and X-ray images +python scripts/generate_data.py +python scripts/generate_xrays.py + +# Run the app +python app.py +# or for production +uvicorn app:server --host 0.0.0.0 --port 8000 +``` + +App runs at http://localhost:8050 (debug) or http://localhost:8000 (uvicorn). + +## Project Structure + +``` +medical-demo-app/ +├── app.py Main entry point +├── pages/ One layout module per page +│ ├── dashboard.py +│ ├── vitals.py +│ ├── cohort.py +│ └── imaging.py +├── callbacks/ One callback module per page +│ ├── dashboard.py Includes live vitals WebSocket +│ ├── vitals.py +│ ├── cohort.py +│ ├── imaging.py +│ └── export_all.py PDF export +├── components/ Reusable Plotly/Mantine components +│ ├── charts.py +│ ├── kpi_cards.py +│ ├── tables.py +│ └── imaging.py +├── utils/ +│ ├── data_loader.py +│ └── pdf_export.py +├── data/ Generated CSVs (run generate_data.py) +├── assets/ +│ ├── styles.css +│ └── xrays/ Generated X-ray PNGs (run generate_xrays.py) +└── scripts/ + ├── generate_data.py + └── generate_xrays.py +``` + +## Attribution + +X-ray image generation is inspired by the NIH ChestX-ray14 dataset structure (CC0 Public Domain). +NIH Clinical Center: https://nihcc.app.box.com/v/ChestXray-NIHCC diff --git a/medical-imaging-demo/app.py b/medical-imaging-demo/app.py new file mode 100644 index 0000000..e1ade1f --- /dev/null +++ b/medical-imaging-demo/app.py @@ -0,0 +1,209 @@ +import dash +from dash import html, dcc, Input, Output, callback, ctx +import dash_mantine_components as dmc +from dash_iconify import DashIconify + +from pages import cohort, imaging +from callbacks import ( + cohort as cohort_callbacks, + imaging as imaging_callbacks, + export_all as export_all_callbacks, +) + +app = dash.Dash( + __name__, + backend="fastapi", + suppress_callback_exceptions=True, + external_stylesheets=dmc.styles.ALL, + title="Medical Imaging Demo", +) +server = app.server + + +# ── Header ───────────────────────────────────────────────────────────────────── +# (label, href, nav_id, leftSection) +NAV_LINKS = [ + ("Imaging Workstation", "/imaging", "nav-imaging", + DashIconify(icon="tabler:x-ray", width=15)), + ("Cohort Explorer", "/cohort", "nav-cohort", None), +] + +_NAV_BTN_STYLES = { + "root": { + "paddingLeft": 14, "paddingRight": 18, + "fontWeight": 500, "height": 34, + "fontSize": "13px", + }, +} + + + +def create_header(): + brand = dmc.Group([ + html.Img(src="/assets/DE-logo.png", height=36, + style={"opacity": "0.92"}), + html.Div(style={ + "width": "1px", "height": "20px", + "backgroundColor": "#d1d5db", + "flexShrink": 0, + }), + dmc.Title("Medical Imaging Demo", order=3, + style={"color": "#1e2433", "letterSpacing": "-0.5px", + "fontSize": "16px", "fontWeight": 600}), + ], gap=10, wrap="nowrap", align="center") + + nav_center = dmc.Group([ + dcc.Link( + dmc.Button( + label, + id=nav_id, + leftSection=left, + variant="subtle", + color="navy", + size="sm", + radius="md", + styles=_NAV_BTN_STYLES, + ), + href=href, + style={"textDecoration": "none"}, + ) + for label, href, nav_id, left in NAV_LINKS + ], gap=4, wrap="nowrap") + + actions = dmc.Group([ + html.Div( + dmc.Group([ + DashIconify(icon="tabler:building-hospital", width=12, + color="#6b7280"), + dmc.Text("General Hospital", size="xs", fw=500, + style={"color": "#6b7280", "letterSpacing": "0.01em"}), + html.Div(style={ + "width": "3px", "height": "3px", + "borderRadius": "50%", + "backgroundColor": "#c2c6cc", + "flexShrink": 0, + }), + dmc.Text("325 beds", size="xs", + style={"color": "#6b7280"}), + html.Div(style={ + "width": "3px", "height": "3px", + "borderRadius": "50%", + "backgroundColor": "#c2c6cc", + "flexShrink": 0, + }), + dmc.Text("ICU 25", size="xs", fw=600, + style={"color": "#1e3a8a"}), + ], gap=6, wrap="nowrap"), + style={ + "display": "flex", "alignItems": "center", + "padding": "4px 12px", + "borderRadius": "20px", + "backgroundColor": "#eef0f2", + "border": "1px solid #e1e3e7", + }, + ), + dmc.Tooltip( + label="Hide toolbar", withArrow=True, + children=dmc.ActionIcon( + DashIconify(icon="tabler:layout-navbar-collapse", width=18), + id="header-collapse-btn", variant="subtle", color="navy", + size="lg", + ), + ), + ], gap="sm", wrap="nowrap", justify="flex-end") + + # Three-column grid: brand | nav (centered) | actions + return html.Div( + [brand, nav_center, actions], + style={ + "display": "grid", + "gridTemplateColumns": "1fr auto 1fr", + "alignItems": "center", + "height": "100%", + "padding": "0 24px", + "backgroundColor": "#fcfcfb", + "borderBottom": "1px solid #e1e3e7", + }, + ) + + +# Floating button (overlays the page) to restore the header once collapsed. +_EXPAND_STYLE = {"position": "fixed", "top": "10px", "right": "14px", + "zIndex": 3000, "display": "none"} + + +# ── App layout ───────────────────────────────────────────────────────────────── +app.layout = dmc.MantineProvider( + id="mantine-provider", + forceColorScheme="light", + theme={ + "primaryColor": "cyan", + # Register the imaging "navy" ramp app-wide so the shared header's + # navy-colored controls resolve (cohort accents stay on cyan). + "colors": {"navy": imaging.NAVY_RAMP}, + "fontFamily": "Inter, -apple-system, BlinkMacSystemFont, sans-serif", + }, + children=[ + dcc.Location(id="url", refresh=False), + dcc.Download(id="download-pdf-all"), + html.Div(id="pdf-status-all", style={"display": "none"}), + dmc.AppShell( + [ + dmc.AppShellHeader(create_header()), + dmc.AppShellMain( + html.Div(id="page-content", style={"width": "100%"}), + ), + ], + id="app-shell", + header={"height": 64}, + padding=0, + ), + dmc.Tooltip( + label="Show toolbar", withArrow=True, + children=dmc.ActionIcon( + DashIconify(icon="tabler:layout-navbar-expand", width=18), + id="header-expand-btn", variant="filled", color="navy", + size="lg", style=_EXPAND_STYLE, + ), + ), + ] +) + + +# ── Routing ──────────────────────────────────────────────────────────────────── +@callback( + Output("page-content", "children"), + Input("url", "pathname"), +) +def display_page(pathname): + # Imaging Workstation is the landing page ("/" and "/imaging"). + if pathname == "/cohort": + return cohort.layout + return imaging.layout + + +@callback( + [Output(nav_id, "variant") for _, _, nav_id, _ in NAV_LINKS], + Input("url", "pathname"), +) +def update_nav_active(pathname): + hrefs = [href for _, href, _, _ in NAV_LINKS] + active = pathname if pathname in hrefs else "/imaging" + return ["filled" if active == h else "subtle" for h in hrefs] + + +@callback( + Output("app-shell", "header"), + Output("header-expand-btn", "style"), + Input("header-collapse-btn", "n_clicks"), + Input("header-expand-btn", "n_clicks"), + prevent_initial_call=True, +) +def toggle_header(_collapse, _expand): + collapsed = ctx.triggered_id == "header-collapse-btn" + return ({"height": 64, "collapsed": collapsed}, + {**_EXPAND_STYLE, "display": "flex" if collapsed else "none"}) + + +if __name__ == "__main__": + app.run(debug=True, port=8051) diff --git a/medical-imaging-demo/assets/DE-logo.png b/medical-imaging-demo/assets/DE-logo.png new file mode 100644 index 0000000000000000000000000000000000000000..a0375905a3f3c3e6b871fe36c682a07be4338dda GIT binary patch literal 24095 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background-color: #eef0f2; + color: #1e2433; +} +.mantine-AppShell-header .mantine-Button-root[data-variant="filled"] { + color: #1e3a8a; + background-color: rgba(30, 58, 138, 0.1); +} + +/* Scrollbars */ +::-webkit-scrollbar { width: 7px; height: 7px; } +::-webkit-scrollbar-track { background: rgba(0,0,0,0.04); border-radius: 4px; } +::-webkit-scrollbar-thumb { background: rgba(0,0,0,0.18); border-radius: 4px; } +::-webkit-scrollbar-thumb:hover { background: rgba(0,0,0,0.28); } + +/* Modebar */ +.js-plotly-plot .plotly .modebar { top: 4px !important; right: 4px !important; } +.js-plotly-plot .plotly .modebar-btn { font-size: 13px !important; } + +/* Table */ +.mantine-Table-table { font-size: 0.85rem; } +.mantine-Table-th { background-color: rgba(0,0,0,0.02); } + +/* NavLink active */ +.mantine-NavLink-root[data-active="true"] { font-weight: 600; } + +/* Paper hover */ +.mantine-Paper-root { transition: box-shadow 0.18s ease; } +.mantine-Paper-root:hover { box-shadow: 0 2px 10px rgba(0,0,0,0.07); } + +/* Pulse animation for live indicator */ +@keyframes pulse { + 0%, 100% { opacity: 1; transform: scale(1); } + 50% { opacity: 0.35; transform: scale(0.85); } +} + +/* Fade-in for KPI cards */ +@keyframes fadeInUp { + from { opacity: 0; transform: translateY(8px); } + to { opacity: 1; transform: translateY(0); } +} + +/* Imaging study cards */ +.study-card:hover { border-color: #1e3a8a !important; } + +/* Print styles */ +@media print { + .mantine-AppShell-header, + .mantine-AppShell-navbar, + .mantine-Button-root, + .mantine-Select-root, + .mantine-MultiSelect-root { display: none !important; } + .mantine-Paper-root { + break-inside: avoid; + box-shadow: none !important; + border: 1px solid #e2e8f0 !important; + } +} + +/* Responsive */ +@media (max-width: 768px) { + .mantine-AppShell-navbar { display: none; } + .mantine-Container-root { padding: 0.5rem; } +} + +/* Progress bar background */ +.mantine-Progress-root { background-color: rgba(0,0,0,0.05); } + +/* 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z7=LhuCowLD7a-YZg6q~nqDR&Qm#p4DkrhyImz%7BD|E2=U8%8K8BB8aN!(9`>6EBs z`=FpXkGK`Y@fvE6A{i5Wz`{JQEzd+$QM2RD4bDqZ*<*);0UsctuKauXe!^L`$jeD# zz>|1t1PT#oCj2GtLK^H7R)awkX*@J3^v+qiEg}12goXI3uQH8JR-y?^FyP+Adk9ZI zX16Bak;J@;*^6;LlW%Y>7;RoOgb^ps+8l~>4mcOi;8B1J6Xo7 zf)j&rw^|ZNx0hm->yN>O4F1RX-6fJmxUT}OVA#!Sl{numg@%JC)IiUFjM0v+6A(hiQDIt zB?1wGXSpy*AT{zXTG{-rG4RuY&^M*ZQ+C)w)mP>>+gpJ~JVqI?o`_|W0QVy%%_8DA zB8(Q9CE?^ZvztQjE;H8wfDp{iy6qDmkUuMGrgks0DE^0#Jrh%ww_5DYj60=$4yTfC zD2dX1AV9%EbzrrOhdB>yWpVUCW2oBjh$IKD50ckW?4$_=3bwReqW&py%p{t$o~hPq z9bWw7U}Wm)QnOX|;CyBii}kq#F??ox_f%QDgGHupNtg)c7Yr=&a52_As|gbarx(uy ztT(<=Hw3!k4hiRZ zci3?l9H>zI9tkY}&m3MRgOmGI*RqR=ufg`noy(X;fWpG3b~9A-=y^VoT+FPct#s3eXwxys&=ahv20000= 95 else "#f59e0b" if s >= 90 else "#ef4444" + +def _bp_color(sbp): + return "#22c55e" if sbp <= 140 else "#f59e0b" if sbp <= 160 else "#ef4444" + + +# ── Toggle streaming ────────────────────────────────────────────────────────── +@callback( + Output("live-streaming", "data"), + Input("icu-live-toggle", "checked"), +) +def toggle_streaming(checked): + return checked + + +# ── Admissions chart update ─────────────────────────────────────────────────── +@callback( + Output("admissions-chart", "figure"), + Input("dashboard-dept", "value"), + Input("dashboard-period", "value"), +) +def update_admissions(dept, period): + df = get_admissions_data(department=dept, period=period) + return create_admissions_chart(df, department=dept) + + +# ── Persistent WebSocket: stream ICU vitals ─────────────────────────────────── +@callback(persistent=True) +async def stream_patient_vitals(): + ws = ctx.websocket + + vitals = {pid: dict(v) for pid, v in ICU_BASE.items()} + history = {pid: [vitals[pid]["hr"]] for pid in PIDS} + + while not ws.is_shutdown: + streaming = await ws.get_prop("live-streaming", "data") + + if streaming: + for pid in PIDS: + v = vitals[pid] + base = ICU_BASE[pid] + + # Mean-reverting Ornstein–Uhlenbeck drift + v["hr"] = max(40, min(200, round(v["hr"] + 0.15*(base["hr"] -v["hr"]) + random.gauss(0, 1.2), 1))) + v["spo2"]= max(85, min(100, round(v["spo2"]+ 0.20*(base["spo2"]-v["spo2"])+ random.gauss(0, 0.25), 1))) + v["sbp"] = max(70, min(220, round(v["sbp"] + 0.10*(base["sbp"]-v["sbp"]) + random.gauss(0, 2.0), 1))) + v["dbp"] = max(40, min(130, round(v["dbp"] + 0.10*(base["dbp"]-v["dbp"]) + random.gauss(0, 1.5), 1))) + v["rr"] = max(8, min(40, round(v["rr"] + 0.15*(base["rr"] -v["rr"]) + random.gauss(0, 0.4), 1))) + + history[pid].append(v["hr"]) + if len(history[pid]) > 40: + history[pid] = history[pid][-40:] + + set_props(f"live-hr-{pid}", { + "children": f"{v['hr']:.0f}", + "style": {"fontFamily": "monospace", "fontWeight": 700, + "color": _hr_color(v["hr"])}, + }) + set_props(f"live-spo2-{pid}", { + "children": f"{v['spo2']:.1f}%", + "style": {"fontFamily": "monospace", "fontWeight": 700, + "color": _spo2_color(v["spo2"])}, + }) + set_props(f"live-bp-{pid}", { + "children": f"{int(v['sbp'])}/{int(v['dbp'])}", + "style": {"fontFamily": "monospace", "fontWeight": 700, + "color": _bp_color(v["sbp"])}, + }) + set_props(f"live-rr-{pid}", { + "children": f"{v['rr']:.0f}", + "style": {"fontFamily": "monospace", "fontWeight": 700, + "color": "#94a3b8"}, + }) + + # ECG sparkline for selected patient + selected = await ws.get_prop("ecg-patient-select", "value") + if selected and selected in history and len(history[selected]) > 1: + fig = create_ecg_sparkline(history[selected], selected) + set_props("ecg-sparkline-chart", {"figure": fig}) + + await asyncio.sleep(1) + else: + await asyncio.sleep(0.5) diff --git a/medical-imaging-demo/callbacks/export_all.py b/medical-imaging-demo/callbacks/export_all.py new file mode 100644 index 0000000..fb0b64a --- /dev/null +++ b/medical-imaging-demo/callbacks/export_all.py @@ -0,0 +1,33 @@ +from datetime import datetime + +from dash import callback, Input, Output, State, dcc + +from utils.pdf_export import create_radiology_report +from utils.data_loader import get_study, get_patient +from components.imaging import annotation_to_finding_dict + + +@callback( + Output("download-radiology-pdf", "data"), + Input("export-radiology-btn", "n_clicks"), + State("xray-graph", "figure"), + State("xray-annotations", "data"), + State("current-study-id", "data"), + prevent_initial_call=True, +) +def export_radiology_report(n_clicks, xray_figure, annotations, study_id): + if not n_clicks: + return None + + study = get_study(study_id) if study_id else {} + patient = get_patient(study.get("patient_id", "")) if study else {} + findings = [annotation_to_finding_dict(a) for a in (annotations or [])] + + pdf_bytes = create_radiology_report( + xray_figure = xray_figure, + findings = findings, + patient_info = patient, + study_info = study, + ) + fname = f"radiology_report_{study_id}_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf" + return dcc.send_bytes(pdf_bytes, fname) diff --git a/medical-imaging-demo/callbacks/imaging.py b/medical-imaging-demo/callbacks/imaging.py new file mode 100644 index 0000000..dfb0410 --- /dev/null +++ b/medical-imaging-demo/callbacks/imaging.py @@ -0,0 +1,192 @@ +from dash import callback, ctx, Input, Output, State, ALL, no_update, Patch + +from components.imaging import (load_xray_b64, create_xray_figure, + get_ai_shapes, XRAY_DIR, _make_shape, + newshape_for, severity_color) +from components.tables import create_findings_table +from utils.data_loader import get_studies, get_study +from pages.imaging import (_patient_banner_content, _image_overlays, + _status_bar, _pending_tag, + BG_INSET, BORDER, ACCENT, + CARD_ACTIVE_BG, CARD_ACTIVE_SHADOW) + +df_studies = get_studies() +STUDY_IDS = df_studies["study_id"].tolist() + + +# ── Select study via thumbnail buttons ──────────────────────────────────────── +@callback( + Output("current-study-id", "data"), + Input({"type": "study-thumb", "index": ALL}, "n_clicks"), + prevent_initial_call=True, +) +def select_study(n_clicks_list): + if not ctx.triggered_id or not any(n_clicks_list): + return no_update + # Don't clear annotations — update_xray loads this study's saved set. + return ctx.triggered_id["index"] + + +# ── Highlight the active study card ─────────────────────────────────────────── +_INACTIVE_STYLE = { + "width": "100%", "padding": "10px 12px", + "backgroundColor": BG_INSET, + "border": f"1px solid {BORDER}", + "borderRadius": "8px", "textAlign": "left", + "transition": "border-color 0.15s ease, background-color 0.15s ease", +} +_ACTIVE_STYLE = { + **_INACTIVE_STYLE, + "backgroundColor": CARD_ACTIVE_BG, + "border": f"1px solid {ACCENT}", + "boxShadow": CARD_ACTIVE_SHADOW, +} + +@callback( + Output({"type": "study-thumb", "index": ALL}, "style"), + Input("current-study-id", "data"), + State({"type": "study-thumb", "index": ALL}, "id"), +) +def highlight_active_study(active_id, ids): + return [_ACTIVE_STYLE if i["index"] == active_id else _INACTIVE_STYLE + for i in ids] + + +# ── Main imaging callback ───────────────────────────────────────────────────── +@callback( + Output("xray-graph", "figure"), + Output("xray-annotations", "data"), + Output("annotations-store", "data"), + Output("findings-table-container","children"), + Output("findings-count", "children"), + Input("xray-graph", "relayoutData"), + Input("current-study-id", "data"), + Input("window-slider", "value"), + Input("level-slider", "value"), + Input("invert-toggle", "checked"), + Input("reset-annotations-btn", "n_clicks"), + Input("draw-mode-select", "value"), + State("xray-annotations", "data"), + State("annotations-store", "data"), + State("finding-label-select", "value"), + State("severity-select", "value"), + State("annotation-note", "value"), + prevent_initial_call=True, +) +def update_xray(relayout, study_id, window, level, invert, + reset_clicks, draw_mode, + stored, by_study, label, severity, note): + triggered = ctx.triggered_id + stored = stored or [] + by_study = dict(by_study or {}) + study = get_study(study_id) if study_id else {} + key = study_id or "" + + drawing_event = False + + if triggered == "reset-annotations-btn": + stored = [] + + elif triggered == "current-study-id": + # Switched study — load this study's saved annotations (persisted), + # do NOT clear. New studies start empty. + stored = list(by_study.get(key, [])) + + elif triggered == "xray-graph" and relayout: + if "shapes" in relayout: + drawing_event = True + raw_shapes = relayout["shapes"] + n_raw = len(raw_shapes) + n_stored = len(stored) + if n_raw > n_stored: + new_raw = raw_shapes[-1] + sev = severity or "Medium" + color = severity_color(sev) + width = 3 if sev == "High" else 2 + stored = stored + [{ + **new_raw, + "line": {"color": color, "width": width}, + "_label": label or "Unspecified", + "_severity": sev, + "_note": note or "", + }] + elif n_raw < n_stored: + stored = stored[:n_raw] + elif n_raw == n_stored and n_raw > 0: + updated = [] + for raw, old in zip(raw_shapes, stored): + updated.append({**raw, + "_label": old.get("_label", "Unspecified"), + "_severity": old.get("_severity", "Medium"), + "_note": old.get("_note", "")}) + stored = updated + else: + # Pan/zoom relayout — nothing to update + return (no_update,) * 5 + + # Persist this study's annotations into the keyed store + by_study[key] = stored + findings_table = create_findings_table(stored) + count = str(len(stored)) + + if drawing_event: + # Shape already rendered on canvas; skip figure rebuild to avoid flicker + return no_update, stored, by_study, findings_table, count + + img_path = XRAY_DIR / study.get("image_file", "xray_01.png") + img_b64 = load_xray_b64(img_path, + window=float(window or 220), + level =float(level or 128), + invert=bool(invert)) + fig = create_xray_figure(img_b64, shapes=stored) + fig.update_layout(dragmode=draw_mode or "drawrect", + newshape=newshape_for(severity)) + + return fig, stored, by_study, findings_table, count + + +# ── Live annotation styling: severity drives the pen colour ─────────────────── +@callback( + Output("xray-graph", "figure", allow_duplicate=True), + Output("pending-annotation", "children"), + Input("severity-select", "value"), + Input("finding-label-select","value"), + Input("annotation-note", "value"), + prevent_initial_call=True, +) +def update_pen_style(severity, finding, note): + """Update the next-shape style + pending badge as the user changes controls. + + Uses a Patch so the X-ray image is not reloaded on every keystroke. + """ + patch = Patch() + patch["layout"]["newshape"] = newshape_for(severity) + return patch, _pending_tag(finding, severity, note) + + +# ── Patient banner follows the selected study ───────────────────────────────── +@callback( + Output("patient-banner", "children"), + Input("current-study-id", "data"), +) +def update_patient_banner(study_id): + if not study_id: + return no_update + return _patient_banner_content(get_study(study_id)) + + +# ── Image chrome: DICOM corner overlays + status bar ────────────────────────── +@callback( + Output("image-overlays", "children"), + Output("image-status-bar", "children"), + Input("current-study-id", "data"), + Input("window-slider", "value"), + Input("level-slider", "value"), + Input("invert-toggle", "checked"), + Input("draw-mode-select", "value"), +) +def update_image_chrome(study_id, window, level, invert, draw_mode): + study = get_study(study_id) if study_id else {} + overlays = _image_overlays(study, window, level, invert) + status = _status_bar(draw_mode, window, level, invert) + return overlays, status diff --git a/medical-imaging-demo/callbacks/vitals.py b/medical-imaging-demo/callbacks/vitals.py new file mode 100644 index 0000000..992d0a2 --- /dev/null +++ b/medical-imaging-demo/callbacks/vitals.py @@ -0,0 +1,74 @@ +from dash import callback, Input, Output +import dash_mantine_components as dmc + +from components.charts import (create_vitals_chart, create_vitals_variability, + VITAL_RANGES) +from utils.data_loader import get_vitals + +UNITS = {"HR": "bpm", "SpO2": "%", "Temp": "°C", + "SysBP": "mmHg", "DiaBP": "mmHg", "RR": "/min"} + + +@callback( + Output("vitals-trend-chart", "figure"), + Output("vitals-var-chart", "figure"), + Output("stat-current-hr", "children"), + Output("stat-high-hr", "children"), + Output("stat-low-hr", "children"), + Output("stat-current-spo2", "children"), + Output("stat-abnormal", "children"), + Output("vitals-summary-grid","children"), + Input("vitals-patient-select","value"), + Input("vitals-period", "value"), + Input("vitals-select", "value"), + Input("vitals-ref-toggle", "checked"), + Input("vitals-ma-select", "value"), +) +def update_vitals(patient_id, period, vitals, show_ref, ma): + vitals = vitals or ["HR", "SpO2"] + df = get_vitals(patient_id, period) + + if df.empty: + empty = dmc.Text("No data", c="dimmed") + return empty, empty, "—", "—", "—", "—", "—", [] + + trend_fig = create_vitals_chart(df, vitals, show_reference=show_ref, ma_days=ma or "none") + var_fig = create_vitals_variability(df, vitals) + + # Stat cards + hr_cur = f"{df['HR'].iloc[-1]:.0f} bpm" if "HR" in df.columns else "—" + hr_hi = f"{df['HR'].max():.0f}" if "HR" in df.columns else "—" + hr_lo = f"{df['HR'].min():.0f}" if "HR" in df.columns else "—" + spo_cur = f"{df['SpO2'].iloc[-1]:.1f}%" if "SpO2" in df.columns else "—" + + # Count readings outside reference range + abnormal = 0 + for v in vitals: + if v in df.columns and v in VITAL_RANGES: + lo, hi = VITAL_RANGES[v] + abnormal += int(((df[v] < lo) | (df[v] > hi)).sum()) + abn_str = str(abnormal) + + # Summary grid: one mini-card per vital + cards = [] + for v in vitals: + if v not in df.columns: + continue + col = df[v] + lo_r, hi_r = VITAL_RANGES.get(v, (None, None)) + current_val = col.iloc[-1] + in_range = (lo_r is None or lo_r <= current_val <= hi_r) + badge_color = "teal" if in_range else "red" + cards.append(dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Text(v, size="xs", fw=600), + dmc.Badge("OK" if in_range else "!", color=badge_color, size="xs"), + ], justify="space-between"), + dmc.Text(f"{current_val:.1f} {UNITS.get(v,'')}", size="sm", fw=700), + dmc.Text(f"↓{col.min():.1f} ↑{col.max():.1f}", size="xs", c="dimmed"), + ], gap=2), + p="xs", radius="sm", withBorder=True, + )) + + return trend_fig, var_fig, hr_cur, hr_hi, hr_lo, spo_cur, abn_str, cards diff --git a/medical-imaging-demo/components/__init__.py b/medical-imaging-demo/components/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/medical-imaging-demo/components/charts.py b/medical-imaging-demo/components/charts.py new file mode 100644 index 0000000..eab4fff --- /dev/null +++ b/medical-imaging-demo/components/charts.py @@ -0,0 +1,287 @@ +import plotly.graph_objects as go +import plotly.express as px +import pandas as pd +import numpy as np + +COLORS = { + "primary": "#0d9488", # teal + "secondary": "#2563eb", # blue + "danger": "#ef4444", + "warning": "#f59e0b", + "success": "#22c55e", + "gray": "#94a3b8", + "purple": "#8b5cf6", +} + +NAVY = "#1e3a8a" # deep navy accent (matches app theme highlight) + +VITAL_COLORS = { + "HR": "#ef4444", + "SpO2": "#2563eb", + "Temp": "#f59e0b", + "SysBP": "#8b5cf6", + "DiaBP": "#a78bfa", + "RR": "#22c55e", +} + +VITAL_RANGES = { + "HR": (60, 100), + "SpO2": (95, 100), + "Temp": (36.1, 37.8), + "SysBP": (90, 130), + "DiaBP": (60, 90), + "RR": (12, 20), +} + +BASE_LAYOUT = { + "paper_bgcolor": "rgba(0,0,0,0)", + "plot_bgcolor": "rgba(0,0,0,0)", + "font": {"family": "Inter, sans-serif"}, + "margin": {"l": 48, "r": 24, "t": 48, "b": 40}, + "hovermode": "x unified", + "hoverlabel": { + "bgcolor": "white", + "bordercolor": "#e2e8f0", + "font": {"family": "Inter, sans-serif", "size": 12}, + }, +} + + +# ── Admissions area chart ───────────────────────────────────────────────────── +def create_admissions_chart(df: pd.DataFrame, department: str = "All") -> go.Figure: + df = df.copy() + df["date"] = pd.to_datetime(df["date"]) + + if department == "All": + agg = df.groupby("date")["admissions"].sum().reset_index() + fig = go.Figure(go.Scatter( + x=agg["date"], y=agg["admissions"], + fill="tozeroy", + line={"color": COLORS["primary"], "width": 2}, + fillcolor="rgba(13,148,136,0.15)", + name="Total Admissions", + hovertemplate="%{y} admissions", + )) + else: + sub = df[df["department"] == department] + fig = go.Figure(go.Scatter( + x=sub["date"], y=sub["admissions"], + fill="tozeroy", + line={"color": COLORS["secondary"], "width": 2}, + fillcolor="rgba(37,99,235,0.12)", + name=department, + hovertemplate="%{y} admissions", + )) + + fig.update_layout( + **BASE_LAYOUT, + title={"text": "Daily Admissions", "x": 0, "font": {"size": 15, "weight": 600}}, + xaxis={"showgrid": False}, + yaxis={"showgrid": True, "gridcolor": "rgba(0,0,0,0.05)", "title": "Patients"}, + showlegend=False, + ) + return fig + + +# ── Vitals time-series with reference bands ─────────────────────────────────── +def create_vitals_chart(df: pd.DataFrame, vitals: list, + show_reference: bool = True, + ma_days: str = "none") -> go.Figure: + fig = go.Figure() + df = df.copy() + df["timestamp"] = pd.to_datetime(df["timestamp"]) + + ma_window = {"20": 20, "50": 50, "none": None}.get(ma_days) + + for v in vitals: + if v not in df.columns: + continue + color = VITAL_COLORS.get(v, COLORS["primary"]) + series = df[v] + if ma_window: + series = series.rolling(ma_window, min_periods=1).mean() + + fig.add_trace(go.Scatter( + x=df["timestamp"], y=series, + name=v, line={"color": color, "width": 1.8}, + hovertemplate=f"{v}: %{{y}}", + )) + + if show_reference and v in VITAL_RANGES: + lo, hi = VITAL_RANGES[v] + fig.add_hrect(y0=lo, y1=hi, fillcolor=color, + opacity=0.06, layer="below", line_width=0) + + fig.update_layout( + **{**BASE_LAYOUT, "margin": {"l": 48, "r": 24, "t": 16, "b": 40}}, + legend={"orientation": "h", "y": -0.18}, + xaxis={ + "showgrid": True, "gridcolor": "rgba(0,0,0,0.04)", + "rangeslider": {"visible": False}, + }, + yaxis={"showgrid": True, "gridcolor": "rgba(0,0,0,0.04)"}, + ) + return fig + + +# ── Vitals variability (box plot per vital) ─────────────────────────────────── +def create_vitals_variability(df: pd.DataFrame, vitals: list) -> go.Figure: + fig = go.Figure() + for v in vitals: + if v not in df.columns: + continue + fig.add_trace(go.Box( + y=df[v], name=v, + marker_color=VITAL_COLORS.get(v, COLORS["primary"]), + boxmean="sd", + )) + fig.update_layout( + **BASE_LAYOUT, + title={"text": "Vital Sign Distribution", "x": 0, + "font": {"size": 15, "weight": 600}}, + yaxis={"showgrid": True, "gridcolor": "rgba(0,0,0,0.04)"}, + showlegend=False, + ) + return fig + + +# ── ECG-style HR sparkline ──────────────────────────────────────────────────── +def create_ecg_sparkline(hr_history: list, patient_id: str = "") -> go.Figure: + fig = go.Figure(go.Scatter( + y=hr_history, + mode="lines", + line={"color": COLORS["success"], "width": 2}, + hovertemplate="%{y} bpm", + )) + fig.update_layout( + paper_bgcolor="rgba(0,0,0,0)", + plot_bgcolor="rgba(0,0,0,0)", + font={"family": "Inter, sans-serif"}, + margin={"l": 0, "r": 0, "t": 12, "b": 0}, + xaxis={"visible": False}, + yaxis={"visible": False, "range": [35, 165]}, + showlegend=False, + title={"text": patient_id, "x": 0, "font": {"size": 12, "weight": 600}}, + ) + return fig + + +# ── Diagnosis donut (cohort demographics) ───────────────────────────────────── +def create_diagnosis_donut(df: pd.DataFrame) -> go.Figure: + counts = df["diagnosis"].value_counts().reset_index() + counts.columns = ["diagnosis", "count"] + fig = go.Figure(go.Pie( + labels=counts["diagnosis"], + values=counts["count"], + hole=0.58, + textinfo="percent", + textposition="outside", + marker={"colors": px.colors.qualitative.Pastel[:len(counts)]}, + hovertemplate="%{label}
      %{value} patients (%{percent})", + )) + fig.update_layout( + **BASE_LAYOUT, + title={"text": "Diagnosis Distribution", "x": 0, + "font": {"size": 15, "weight": 600}}, + legend={"orientation": "v", "x": 1.02, "y": 0.5}, + annotations=[{"text": "Cohort", "x": 0.5, "y": 0.5, + "font": {"size": 13, "weight": 600}, "showarrow": False}], + ) + return fig + + +# ── Age-sex bar chart (cohort demographics) ─────────────────────────────────── +def create_age_sex_chart(df: pd.DataFrame) -> go.Figure: + bins = [20, 30, 40, 50, 60, 70, 80, 90] + labels = ["20-29","30-39","40-49","50-59","60-69","70-79","80+"] + df = df.copy() + df["age_group"] = pd.cut(df["age"], bins=bins, labels=labels, right=False) + grp = df.groupby(["age_group", "gender"], observed=True).size().reset_index(name="count") + fig = go.Figure() + for gender, color in [("M", COLORS["secondary"]), ("F", COLORS["primary"])]: + sub = grp[grp["gender"] == gender] + fig.add_trace(go.Bar( + x=sub["age_group"].astype(str), y=sub["count"], + name="Male" if gender == "M" else "Female", + marker_color=color, + )) + fig.update_layout( + **BASE_LAYOUT, + title={"text": "Age & Sex Distribution", "x": 0, + "font": {"size": 15, "weight": 600}}, + barmode="group", + xaxis={"title": "Age Group"}, + yaxis={"title": "Patients", "showgrid": True, "gridcolor": "rgba(0,0,0,0.04)"}, + legend={"orientation": "h", "y": -0.18}, + ) + return fig + + +# ── Risk stratification bar chart ───────────────────────────────────────────── +def create_risk_strat_chart(df: pd.DataFrame) -> go.Figure: + risk_diag = df.groupby(["diagnosis", "risk_level"]).size().reset_index(name="count") + color_map = {"High": COLORS["danger"], "Medium": COLORS["warning"], "Low": COLORS["success"]} + fig = go.Figure() + for level in ["High", "Medium", "Low"]: + sub = risk_diag[risk_diag["risk_level"] == level] + fig.add_trace(go.Bar( + x=sub["diagnosis"], y=sub["count"], + name=level, marker_color=color_map[level], + )) + fig.update_layout( + **BASE_LAYOUT, + title={"text": "Risk Stratification by Diagnosis", "x": 0, + "font": {"size": 15, "weight": 600}}, + barmode="stack", + xaxis={"tickangle": -30}, + yaxis={"title": "Patients"}, + legend={"orientation": "h", "y": -0.22}, + ) + return fig + + +# ── Crossfilter scatter ─────────────────────────────────────────────────────── +SCATTER_LIGHT = { + "paper_bgcolor": "rgba(0,0,0,0)", + "plot_bgcolor": "rgba(0,0,0,0)", + "font": {"family": "Inter, sans-serif", "color": "#1e2433"}, + "margin": {"l": 40, "r": 16, "t": 40, "b": 36}, + "hovermode": False, + "newselection_mode": "gradual", +} + +def create_crossfilter_scatter(df: pd.DataFrame, x_col: str, y_col: str, + selected_ids=None) -> go.Figure: + all_ids = df.index.tolist() + if selected_ids is None: + selected_ids = all_ids + + risk_colors = {"High": "#ef4444", "Medium": "#f59e0b", "Low": "#22c55e"} + marker_colors = [risk_colors.get(r, "#94a3b8") for r in df["risk_level"]] + + fig = px.scatter(df, x=x_col, y=y_col, template="plotly_white") + fig.update_traces( + selectedpoints=selected_ids, + customdata=df.index, + mode="markers", + marker={ + "color": marker_colors, + "size": 8, + "opacity": 0.9, + "line": {"width": 0.6, "color": "#ffffff"}, + }, + unselected={"marker": {"opacity": 0.15, "color": "#cbd5e1"}}, + selected={"marker": {"opacity": 1.0, "size": 9}}, + ) + grid = {"showgrid": True, "gridcolor": "rgba(0,0,0,0.06)", + "zeroline": False, "linecolor": "rgba(0,0,0,0.12)"} + fig.update_layout( + **SCATTER_LIGHT, + dragmode="select", + activeselection={"fillcolor": "rgba(30,58,138,0.08)"}, + xaxis={**grid, "title": x_col}, + yaxis={**grid, "title": y_col}, + title={"text": f"{x_col} vs {y_col}", + "font": {"size": 13, "color": NAVY, "weight": 600}}, + ) + return fig diff --git a/medical-imaging-demo/components/imaging.py b/medical-imaging-demo/components/imaging.py new file mode 100644 index 0000000..c393d23 --- /dev/null +++ b/medical-imaging-demo/components/imaging.py @@ -0,0 +1,172 @@ +"""X-ray figure builder and annotation helpers.""" +import base64 +import io +import pathlib + +import numpy as np +import plotly.graph_objects as go +from PIL import Image, ImageEnhance, ImageOps + +XRAY_DIR = pathlib.Path(__file__).parent.parent / "assets" / "xrays" + +# Approximate bounding boxes (in 512×512 space) for each finding type +FINDING_AI_BOXES = { + "Cardiomegaly": {"x0": 155, "y0": 192, "x1": 345, "y1": 368, "color": "#f59e0b"}, + "Pleural Effusion":{"x0": 308, "y0": 295, "x1": 460, "y1": 425, "color": "#3b82f6"}, + "Pneumothorax": {"x0": 18, "y0": 40, "x1": 178, "y1": 260, "color": "#ef4444"}, + "Nodule": {"x0": 345, "y0": 135, "x1": 400, "y1": 195, "color": "#8b5cf6"}, + "Mass": {"x0": 315, "y0": 155, "x1": 430, "y1": 285, "color": "#8b5cf6"}, + "Atelectasis": {"x0": 155, "y0": 295, "x1": 380, "y1": 340, "color": "#f97316"}, + "Pneumonia": {"x0": 310, "y0": 258, "x1": 460, "y1": 360, "color": "#eab308"}, + "Consolidation": {"x0": 300, "y0": 250, "x1": 465, "y1": 370, "color": "#eab308"}, + "Infiltration": {"x0": 145, "y0": 230, "x1": 310, "y1": 340, "color": "#eab308"}, + "Cardiomegaly": {"x0": 155, "y0": 192, "x1": 345, "y1": 368, "color": "#f59e0b"}, +} + +IMG_W = IMG_H = 512 + +# Severity → annotation colour (Low=green, Medium=amber, High=red) +# Darkened one step for legibility on the light cream theme. +SEVERITY_COLORS = {"Low": "#16a34a", "Medium": "#d97706", "High": "#dc2626"} + + +def severity_color(severity: str) -> str: + """Hex colour for a severity level, defaulting to Medium amber.""" + return SEVERITY_COLORS.get(severity or "Medium", SEVERITY_COLORS["Medium"]) + + +def newshape_for(severity: str) -> dict: + """Plotly `newshape` style for the next-drawn shape, keyed by severity. + + High findings draw with a thicker line so urgency reads at a glance. + """ + color = severity_color(severity) + width = 3 if severity == "High" else 2 + return { + "line": {"color": color, "width": width}, + "fillcolor": f"rgba({_hex_to_rgb(color)},0.08)", + } + + +def load_xray_b64(image_path: pathlib.Path, + window: float = 255, + level: float = 128, + invert: bool = False) -> str: + """Load grayscale X-ray PNG, apply window/level, return data-URI.""" + try: + img = Image.open(image_path).convert("L").resize((IMG_W, IMG_H), Image.LANCZOS) + except Exception: + img = Image.new("L", (IMG_W, IMG_H), 60) + + arr = np.array(img, dtype=np.float32) + lo = max(0.0, level - window / 2) + hi = min(255.0, level + window / 2) + if hi > lo: + arr = (arr - lo) / (hi - lo) * 255.0 + arr = np.clip(arr, 0, 255).astype(np.uint8) + img = Image.fromarray(arr, mode="L") + + if invert: + img = ImageOps.invert(img) + + buf = io.BytesIO() + img.save(buf, format="PNG") + b64 = base64.b64encode(buf.getvalue()).decode() + return f"data:image/png;base64,{b64}" + + +def create_xray_figure(img_b64: str, shapes: list = None) -> go.Figure: + """Build a Plotly figure that shows an X-ray with drawing tools.""" + fig = go.Figure() + + fig.add_layout_image( + source=img_b64, + xref="x", yref="y", + x=0, y=IMG_H, + xanchor="left", yanchor="top", + sizex=IMG_W, sizey=IMG_H, + sizing="stretch", + layer="below", + ) + + fig.update_layout( + xaxis=dict(range=[0, IMG_W], showgrid=False, zeroline=False, + showticklabels=False, fixedrange=False), + yaxis=dict(range=[0, IMG_H], showgrid=False, zeroline=False, + showticklabels=False, scaleanchor="x", fixedrange=False), + plot_bgcolor="#e7e9ec", + paper_bgcolor="#eef0f2", + margin=dict(l=0, r=0, t=0, b=0), + dragmode="drawrect", + newshape=dict( + line={"color": "#1e3a8a", "width": 2}, + fillcolor="rgba(30,58,138,0.08)", + ), + modebar=dict( + bgcolor="#eef0f2", + color="#6b7280", + activecolor="#1e3a8a", + ), + ) + + if shapes: + fig.layout.shapes = [_make_shape(s) for s in shapes] + + return fig + + +def _make_shape(s: dict) -> dict: + """Convert stored annotation dict to Plotly layout shape dict.""" + line = s.get("line") if isinstance(s.get("line"), dict) else {} + color = line.get("color", "#1e3a8a") + width = line.get("width", 2) + return { + "type": s.get("type", "rect"), + "x0": s.get("x0", 0), + "y0": s.get("y0", 0), + "x1": s.get("x1", 10), + "y1": s.get("y1", 10), + "line": {"color": color, "width": width}, + "fillcolor": f"rgba({_hex_to_rgb(color)},0.09)", + } + + +def _hex_to_rgb(hex_color: str) -> str: + h = hex_color.lstrip("#") + if len(h) == 6: + r, g, b = int(h[0:2],16), int(h[2:4],16), int(h[4:6],16) + return f"{r},{g},{b}" + return "30,58,138" + + +def get_ai_shapes(finding_labels_str: str) -> list: + """Return a list of stored annotation dicts from finding-label string.""" + shapes = [] + for f in finding_labels_str.split("|"): + f = f.strip() + box = FINDING_AI_BOXES.get(f) + if box: + shapes.append({ + "type": "rect", + "x0": box["x0"], "y0": IMG_H - box["y1"], + "x1": box["x1"], "y1": IMG_H - box["y0"], + "line": {"color": box["color"], "width": 2}, + "fillcolor": "rgba(0,0,0,0)", + "_label": f, + "_severity": "Medium", + "_note": "AI suggested", + }) + return shapes + + +def annotation_to_finding_dict(ann: dict) -> dict: + """Convert stored annotation to finding dict for PDF export.""" + x0, y0 = ann.get("x0", 0), ann.get("y0", 0) + x1, y1 = ann.get("x1", 0), ann.get("y1", 0) + return { + "label": ann.get("_label", "Unspecified"), + "location": f"({int(x0)},{int(y0)})→({int(x1)},{int(y1)})", + "shape_type": ann.get("type", "rect"), + "severity": ann.get("_severity", "—"), + "note": ann.get("_note", ""), + } diff --git a/medical-imaging-demo/components/kpi_cards.py b/medical-imaging-demo/components/kpi_cards.py new file mode 100644 index 0000000..57ef2a5 --- /dev/null +++ b/medical-imaging-demo/components/kpi_cards.py @@ -0,0 +1,61 @@ +import dash_mantine_components as dmc +from dash_iconify import DashIconify + + +def create_kpi_card(id_prefix, title, value, trend=None, + trend_positive=True, subtitle=None, icon=None, + alert_color=None): + """Clinical KPI card, optionally coloured for alert state.""" + trend_color = "teal" if trend_positive else "red" + border_color = {"red": "#ef4444", "yellow": "#f59e0b", "green": "#22c55e"}.get(alert_color) + style = {"minWidth": "200px"} + if border_color: + style["borderLeft"] = f"4px solid {border_color}" + + return dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Text(title, size="sm", c="dimmed", fw=500, id=f"{id_prefix}-title"), + DashIconify(icon=icon, width=20, color="gray") if icon else None, + ], justify="space-between"), + dmc.Group([ + dmc.Text(value, size="xl", fw=700, id=f"{id_prefix}-value"), + dmc.Text( + trend or "", + size="sm", + c=trend_color, + fw=500, + id=f"{id_prefix}-trend", + style={"display": "block" if trend else "none"}, + ), + ], justify="space-between", mt="xs"), + dmc.Text(subtitle, size="xs", c="dimmed", mt=4, + id=f"{id_prefix}-subtitle") if subtitle else None, + ], gap="xs"), + p="md", + radius="md", + withBorder=True, + style=style, + ) + + +def create_stat_card(label, value, description=None, value_color=None): + return dmc.Paper( + dmc.Stack([ + dmc.Text(label, size="xs", c="dimmed", tt="uppercase", fw=600), + dmc.Text(value, size="lg", fw=600, c=value_color or "default"), + dmc.Text(description, size="xs", c="dimmed") if description else None, + ], gap=4), + p="sm", + radius="sm", + withBorder=True, + ) + + +def create_risk_row(id_prefix, label, value, progress_value, color): + return dmc.Group([ + dmc.Text(label, size="sm", w=120), + dmc.Progress(value=progress_value, color=color, size="lg", + style={"flex": 1}, id=f"{id_prefix}-bar"), + dmc.Text(value, size="sm", fw=500, w=55, id=f"{id_prefix}-value"), + ], gap="sm") diff --git a/medical-imaging-demo/components/tables.py b/medical-imaging-demo/components/tables.py new file mode 100644 index 0000000..311f44f --- /dev/null +++ b/medical-imaging-demo/components/tables.py @@ -0,0 +1,110 @@ +import dash_mantine_components as dmc +import pandas as pd + + +def create_data_table(df: pd.DataFrame, title: str = None, + striped: bool = True, highlight_flags: bool = False): + """Generic Mantine table from a DataFrame.""" + cols = df.columns.tolist() + header = dmc.TableThead( + dmc.TableTr([dmc.TableTh(c, style={"fontWeight": 600}) for c in cols]) + ) + rows = [] + for _, row in df.iterrows(): + cells = [] + for col, val in zip(cols, row): + style = {} + val_str = str(val) if not pd.isna(val) else "—" + if highlight_flags and col == "flag": + color = {"H": "#ef4444", "L": "#3b82f6"}.get(val_str, "#22c55e") + style["color"] = color + style["fontWeight"] = 600 + cells.append(dmc.TableTd(val_str, style=style)) + rows.append(dmc.TableTr(cells)) + body = dmc.TableTbody(rows) + table = dmc.Table( + [header, body], + striped=striped, + highlightOnHover=True, + withTableBorder=True, + withColumnBorders=True, + ) + if title: + return dmc.Stack([ + dmc.Text(title, fw=600, size="lg"), + dmc.ScrollArea(table, type="auto"), + ], gap="sm") + return dmc.ScrollArea(table, type="auto") + + +def create_findings_table(annotations: list): + """Build a findings table from a list of annotation dicts.""" + if not annotations: + return dmc.Text("No annotations yet. Draw on the X-ray to add findings.", + size="sm", c="dimmed", ta="center", py="md") + + headers = ["#", "Finding", "Severity", "Location (px)", "Size (px²)", "Note"] + header = dmc.TableThead( + dmc.TableTr([dmc.TableTh(h, style={"fontWeight": 600, "fontSize": "12px"}) + for h in headers]) + ) + + sev_color = {"High": "#ef4444", "Medium": "#f59e0b", "Low": "#22c55e"} + rows = [] + for i, ann in enumerate(annotations, 1): + x0 = ann.get("x0", 0) + y0 = ann.get("y0", 0) + x1 = ann.get("x1", 0) + y1 = ann.get("y1", 0) + area = abs((x1 - x0) * (y1 - y0)) + sev = ann.get("_severity", "—") + rows.append(dmc.TableTr([ + dmc.TableTd(str(i), style={"fontSize": "12px"}), + dmc.TableTd(ann.get("_label", "Unspecified"), + style={"fontWeight": 500, "fontSize": "12px"}), + dmc.TableTd( + dmc.Badge(sev, color={"High":"red","Medium":"yellow","Low":"teal"}.get(sev,"gray"), + size="sm"), + ), + dmc.TableTd(f"({int(x0)},{int(y0)})→({int(x1)},{int(y1)})", + style={"fontFamily": "monospace", "fontSize": "11px"}), + dmc.TableTd(f"{int(area):,}", style={"fontSize": "12px"}), + dmc.TableTd(ann.get("_note", ""), style={"fontSize": "12px"}), + ])) + + return dmc.ScrollArea( + dmc.Table([header, dmc.TableTbody(rows)], + striped=True, highlightOnHover=True, + withTableBorder=True, withColumnBorders=False, + verticalSpacing="xs"), + type="auto", + ) + + +def create_patient_table(df: pd.DataFrame, cols=None): + """Patient roster table with coloured risk badges.""" + if cols is None: + cols = ["patient_id", "name", "age", "gender", "diagnosis", "ward", "risk_score"] + df = df[cols].copy() + header = dmc.TableThead( + dmc.TableTr([dmc.TableTh(c.replace("_"," ").title(), + style={"fontWeight": 600, "fontSize": "12px"}) + for c in cols]) + ) + rows = [] + for _, row in df.iterrows(): + cells = [] + for col in cols: + val = row[col] + if col == "risk_score": + color = "red" if val > 70 else "yellow" if val > 40 else "teal" + cells.append(dmc.TableTd( + dmc.Badge(f"{val:.0f}", color=color, size="sm"))) + else: + cells.append(dmc.TableTd(str(val), style={"fontSize": "12px"})) + rows.append(dmc.TableTr(cells)) + return dmc.ScrollArea( + dmc.Table([header, dmc.TableTbody(rows)], + striped=True, highlightOnHover=True, withTableBorder=True), + type="auto", h=280, + ) diff --git a/medical-imaging-demo/data/admissions.csv b/medical-imaging-demo/data/admissions.csv new file mode 100644 index 0000000..bfaba6c --- /dev/null +++ b/medical-imaging-demo/data/admissions.csv @@ -0,0 +1,211 @@ +date,department,admissions +2026-05-17,Cardiology,6 +2026-05-17,Pulmonology,5 +2026-05-17,Neurology,6 +2026-05-17,General Medicine,16 +2026-05-17,Surgery,8 +2026-05-17,Nephrology,4 +2026-05-17,Oncology,2 +2026-05-18,Cardiology,11 +2026-05-18,Pulmonology,6 +2026-05-18,Neurology,7 +2026-05-18,General Medicine,20 +2026-05-18,Surgery,11 +2026-05-18,Nephrology,3 +2026-05-18,Oncology,2 +2026-05-19,Cardiology,12 +2026-05-19,Pulmonology,3 +2026-05-19,Neurology,0 +2026-05-19,General Medicine,22 +2026-05-19,Surgery,8 +2026-05-19,Nephrology,5 +2026-05-19,Oncology,4 +2026-05-20,Cardiology,14 +2026-05-20,Pulmonology,7 +2026-05-20,Neurology,5 +2026-05-20,General Medicine,18 +2026-05-20,Surgery,11 +2026-05-20,Nephrology,6 +2026-05-20,Oncology,6 +2026-05-21,Cardiology,9 +2026-05-21,Pulmonology,12 +2026-05-21,Neurology,5 +2026-05-21,General Medicine,19 +2026-05-21,Surgery,10 +2026-05-21,Nephrology,3 +2026-05-21,Oncology,3 +2026-05-22,Cardiology,14 +2026-05-22,Pulmonology,10 +2026-05-22,Neurology,6 +2026-05-22,General Medicine,22 +2026-05-22,Surgery,10 +2026-05-22,Nephrology,4 +2026-05-22,Oncology,2 +2026-05-23,Cardiology,7 +2026-05-23,Pulmonology,4 +2026-05-23,Neurology,7 +2026-05-23,General Medicine,16 +2026-05-23,Surgery,10 +2026-05-23,Nephrology,4 +2026-05-23,Oncology,1 +2026-05-24,Cardiology,10 +2026-05-24,Pulmonology,8 +2026-05-24,Neurology,5 +2026-05-24,General Medicine,12 +2026-05-24,Surgery,4 +2026-05-24,Nephrology,5 +2026-05-24,Oncology,2 +2026-05-25,Cardiology,12 +2026-05-25,Pulmonology,6 +2026-05-25,Neurology,6 +2026-05-25,General Medicine,17 +2026-05-25,Surgery,10 +2026-05-25,Nephrology,6 +2026-05-25,Oncology,5 +2026-05-26,Cardiology,9 +2026-05-26,Pulmonology,8 +2026-05-26,Neurology,4 +2026-05-26,General Medicine,23 +2026-05-26,Surgery,11 +2026-05-26,Nephrology,5 +2026-05-26,Oncology,8 +2026-05-27,Cardiology,10 +2026-05-27,Pulmonology,7 +2026-05-27,Neurology,7 +2026-05-27,General Medicine,24 +2026-05-27,Surgery,12 +2026-05-27,Nephrology,6 +2026-05-27,Oncology,2 +2026-05-28,Cardiology,10 +2026-05-28,Pulmonology,9 +2026-05-28,Neurology,3 +2026-05-28,General Medicine,20 +2026-05-28,Surgery,11 +2026-05-28,Nephrology,2 +2026-05-28,Oncology,5 +2026-05-29,Cardiology,13 +2026-05-29,Pulmonology,7 +2026-05-29,Neurology,5 +2026-05-29,General Medicine,16 +2026-05-29,Surgery,9 +2026-05-29,Nephrology,1 +2026-05-29,Oncology,2 +2026-05-30,Cardiology,8 +2026-05-30,Pulmonology,3 +2026-05-30,Neurology,2 +2026-05-30,General Medicine,12 +2026-05-30,Surgery,9 +2026-05-30,Nephrology,3 +2026-05-30,Oncology,5 +2026-05-31,Cardiology,8 +2026-05-31,Pulmonology,5 +2026-05-31,Neurology,3 +2026-05-31,General Medicine,9 +2026-05-31,Surgery,8 +2026-05-31,Nephrology,3 +2026-05-31,Oncology,3 +2026-06-01,Cardiology,7 +2026-06-01,Pulmonology,7 +2026-06-01,Neurology,5 +2026-06-01,General Medicine,20 +2026-06-01,Surgery,9 +2026-06-01,Nephrology,4 +2026-06-01,Oncology,5 +2026-06-02,Cardiology,14 +2026-06-02,Pulmonology,7 +2026-06-02,Neurology,3 +2026-06-02,General Medicine,17 +2026-06-02,Surgery,10 +2026-06-02,Nephrology,7 +2026-06-02,Oncology,0 +2026-06-03,Cardiology,9 +2026-06-03,Pulmonology,7 +2026-06-03,Neurology,1 +2026-06-03,General Medicine,19 +2026-06-03,Surgery,10 +2026-06-03,Nephrology,5 +2026-06-03,Oncology,3 +2026-06-04,Cardiology,11 +2026-06-04,Pulmonology,5 +2026-06-04,Neurology,2 +2026-06-04,General Medicine,19 +2026-06-04,Surgery,10 +2026-06-04,Nephrology,5 +2026-06-04,Oncology,6 +2026-06-05,Cardiology,12 +2026-06-05,Pulmonology,9 +2026-06-05,Neurology,6 +2026-06-05,General Medicine,23 +2026-06-05,Surgery,9 +2026-06-05,Nephrology,6 +2026-06-05,Oncology,4 +2026-06-06,Cardiology,10 +2026-06-06,Pulmonology,6 +2026-06-06,Neurology,4 +2026-06-06,General Medicine,15 +2026-06-06,Surgery,8 +2026-06-06,Nephrology,5 +2026-06-06,Oncology,5 +2026-06-07,Cardiology,9 +2026-06-07,Pulmonology,3 +2026-06-07,Neurology,4 +2026-06-07,General Medicine,14 +2026-06-07,Surgery,6 +2026-06-07,Nephrology,3 +2026-06-07,Oncology,1 +2026-06-08,Cardiology,7 +2026-06-08,Pulmonology,10 +2026-06-08,Neurology,5 +2026-06-08,General Medicine,16 +2026-06-08,Surgery,10 +2026-06-08,Nephrology,6 +2026-06-08,Oncology,3 +2026-06-09,Cardiology,9 +2026-06-09,Pulmonology,5 +2026-06-09,Neurology,10 +2026-06-09,General Medicine,17 +2026-06-09,Surgery,6 +2026-06-09,Nephrology,4 +2026-06-09,Oncology,5 +2026-06-10,Cardiology,15 +2026-06-10,Pulmonology,7 +2026-06-10,Neurology,5 +2026-06-10,General Medicine,17 +2026-06-10,Surgery,12 +2026-06-10,Nephrology,4 +2026-06-10,Oncology,3 +2026-06-11,Cardiology,12 +2026-06-11,Pulmonology,8 +2026-06-11,Neurology,5 +2026-06-11,General Medicine,22 +2026-06-11,Surgery,6 +2026-06-11,Nephrology,5 +2026-06-11,Oncology,4 +2026-06-12,Cardiology,11 +2026-06-12,Pulmonology,9 +2026-06-12,Neurology,7 +2026-06-12,General Medicine,22 +2026-06-12,Surgery,9 +2026-06-12,Nephrology,4 +2026-06-12,Oncology,5 +2026-06-13,Cardiology,8 +2026-06-13,Pulmonology,2 +2026-06-13,Neurology,6 +2026-06-13,General Medicine,11 +2026-06-13,Surgery,8 +2026-06-13,Nephrology,8 +2026-06-13,Oncology,4 +2026-06-14,Cardiology,7 +2026-06-14,Pulmonology,5 +2026-06-14,Neurology,5 +2026-06-14,General Medicine,14 +2026-06-14,Surgery,9 +2026-06-14,Nephrology,6 +2026-06-14,Oncology,5 +2026-06-15,Cardiology,9 +2026-06-15,Pulmonology,8 +2026-06-15,Neurology,6 +2026-06-15,General Medicine,23 +2026-06-15,Surgery,10 +2026-06-15,Nephrology,3 +2026-06-15,Oncology,4 diff --git a/medical-imaging-demo/data/cohort.csv b/medical-imaging-demo/data/cohort.csv new file mode 100644 index 0000000..51b12e7 --- /dev/null +++ b/medical-imaging-demo/data/cohort.csv @@ -0,0 +1,201 @@ +patient_id,age,gender,bmi,systolic_bp,ldl,hba1c,egfr,diagnosis,risk_level +CO2001,46,F,25.9,167.0,161.8,8.3,87.7,CAD,High +CO2002,46,M,24.0,146.0,114.1,6.9,67.9,CKD,Low +CO2003,32,M,20.3,189.0,112.1,8.3,55.8,Asthma,High +CO2004,52,M,30.2,167.0,81.4,6.0,73.5,CKD,Medium +CO2005,76,F,33.3,105.0,56.4,6.8,72.2,Heart Failure,Low +CO2006,26,M,29.4,115.0,141.2,6.1,65.8,Asthma,Low +CO2007,59,M,16.0,149.0,122.4,10.4,72.2,Type 2 Diabetes,Medium +CO2008,50,F,31.2,133.0,71.1,6.3,21.1,CKD,Medium +CO2009,32,M,29.7,142.0,89.7,5.6,42.6,CKD,Medium +CO2010,49,M,32.0,93.0,54.6,5.9,53.5,Heart Failure,Low +CO2011,68,M,31.8,151.0,154.2,9.2,72.9,CKD,Medium +CO2012,57,F,26.9,131.0,119.0,8.3,78.6,Type 2 Diabetes,Medium +CO2013,55,F,16.0,134.0,124.1,7.3,43.1,Type 2 Diabetes,Medium +CO2014,50,M,29.5,115.0,166.2,4.5,85.6,Heart Failure,Low +CO2015,84,F,20.7,114.0,148.7,6.1,48.0,Hypertension,Low +CO2016,23,M,24.2,132.0,40.0,7.1,5.0,Obesity,Medium +CO2017,24,M,34.5,201.0,81.8,7.6,78.5,Hyperlipidemia,Medium +CO2018,36,M,16.0,110.0,132.6,7.1,61.4,Atrial Fibrillation,Low +CO2019,76,F,24.4,120.0,113.0,7.8,77.0,Hyperlipidemia,Low +CO2020,59,F,20.8,120.0,139.9,5.8,67.6,Hyperlipidemia,Low +CO2021,25,F,33.9,108.0,192.7,8.7,15.6,CAD,High +CO2022,52,F,28.6,126.0,162.8,5.0,69.6,Hyperlipidemia,Low +CO2023,84,M,42.4,125.0,150.1,4.5,25.2,Type 2 Diabetes,Medium +CO2024,82,M,25.7,110.0,95.4,6.4,86.7,Hyperlipidemia,Low +CO2025,22,F,25.6,124.0,102.0,7.3,38.6,Asthma,Medium +CO2026,46,M,26.2,160.0,147.0,7.0,31.8,Atrial Fibrillation,Medium +CO2027,48,F,30.0,103.0,171.0,7.6,62.8,Type 2 Diabetes,Low +CO2028,37,F,29.0,133.0,50.5,7.4,98.1,CKD,Low +CO2029,36,F,34.9,145.0,72.1,7.3,85.4,COPD,Low +CO2030,63,F,30.2,182.0,144.1,8.0,102.9,Hyperlipidemia,Medium +CO2031,81,F,33.4,124.0,70.2,6.6,42.8,COPD,Medium +CO2032,30,M,20.0,171.0,126.7,7.5,65.5,Heart Failure,Medium +CO2033,80,M,28.1,122.0,119.7,9.9,49.3,Heart Failure,Medium +CO2034,34,F,33.2,136.0,112.0,8.8,51.7,CAD,Medium +CO2035,61,F,25.5,144.0,81.3,8.4,38.1,Atrial Fibrillation,High +CO2036,51,M,26.7,117.0,143.2,5.3,111.1,Asthma,Low +CO2037,74,M,27.6,107.0,93.4,5.2,98.2,CKD,Low +CO2038,53,F,26.3,124.0,107.1,6.0,70.7,CKD,Low +CO2039,26,F,28.0,108.0,139.5,6.9,50.2,CKD,Low +CO2040,50,F,20.5,128.0,103.8,6.0,84.3,Asthma,Low +CO2041,59,M,28.6,138.0,70.8,8.3,51.1,Heart Failure,Medium +CO2042,20,F,17.1,135.0,95.8,7.6,45.3,Atrial Fibrillation,Low +CO2043,35,M,24.5,166.0,133.0,4.5,33.4,Atrial Fibrillation,High +CO2044,52,F,25.7,147.0,91.0,6.3,60.0,Type 2 Diabetes,Low +CO2045,62,M,33.4,106.0,124.9,6.5,18.9,Atrial Fibrillation,Medium +CO2046,48,F,39.7,138.0,156.9,6.6,65.7,CAD,Low +CO2047,45,F,34.5,161.0,52.5,6.1,127.1,Obesity,Medium +CO2048,53,F,30.3,148.0,153.1,9.5,59.4,Obesity,Medium +CO2049,71,M,19.8,145.0,60.7,4.5,73.6,COPD,Low +CO2050,50,M,28.6,131.0,118.0,6.8,70.3,Hypertension,Low +CO2051,33,F,26.5,92.0,141.4,7.6,120.3,Hypertension,Low +CO2052,76,F,23.4,80.0,118.8,5.5,47.6,Heart Failure,Low +CO2053,55,M,25.9,91.0,126.8,4.5,60.5,CKD,Low +CO2054,60,M,24.8,115.0,169.0,6.5,47.9,Obesity,Low +CO2055,67,M,31.3,204.0,113.6,8.6,94.2,Type 2 Diabetes,High +CO2056,80,F,23.5,126.0,161.9,7.0,31.9,CKD,Medium +CO2057,36,F,21.1,132.0,58.8,4.6,96.2,Hypertension,Low +CO2058,72,F,20.8,153.0,83.0,4.5,67.9,CKD,Low +CO2059,58,M,26.9,124.0,138.2,8.8,60.8,Asthma,Medium +CO2060,50,F,16.0,140.0,40.0,7.1,47.9,COPD,Low +CO2061,36,M,29.4,135.0,64.8,8.0,75.3,CAD,Medium +CO2062,50,M,28.2,107.0,87.7,6.8,100.1,CKD,Low +CO2063,54,F,30.6,104.0,132.6,6.9,111.6,Hyperlipidemia,Low +CO2064,23,M,34.1,120.0,96.5,6.8,53.1,Atrial Fibrillation,Low +CO2065,42,F,38.8,155.0,95.0,4.5,67.0,Hyperlipidemia,Low +CO2066,52,M,22.1,165.0,134.2,7.1,71.6,Obesity,Medium +CO2067,28,M,19.9,149.0,139.3,6.7,64.6,CAD,Low +CO2068,74,F,28.2,134.0,134.2,7.4,65.1,Type 2 Diabetes,Low +CO2069,65,M,28.3,99.0,92.8,6.9,48.9,Type 2 Diabetes,Low +CO2070,60,F,29.3,133.0,143.4,8.2,86.0,Atrial Fibrillation,Medium +CO2071,34,M,16.0,156.0,108.7,5.0,79.3,Asthma,Low +CO2072,55,M,27.3,80.0,144.6,8.2,77.6,Type 2 Diabetes,Medium +CO2073,32,F,21.0,123.0,119.5,7.6,79.8,Hyperlipidemia,Low +CO2074,58,F,32.7,99.0,105.7,7.7,60.5,CAD,Low +CO2075,28,F,26.8,94.0,74.9,6.0,55.5,COPD,Low +CO2076,46,F,26.6,121.0,106.2,6.1,68.5,Hypertension,Low +CO2077,83,F,22.6,152.0,45.0,6.5,70.4,CAD,Low +CO2078,23,M,30.4,125.0,84.4,8.1,89.2,Obesity,Medium +CO2079,77,F,31.9,119.0,157.6,7.4,69.5,COPD,Low +CO2080,71,M,21.7,146.0,95.9,7.4,114.3,CKD,Low +CO2081,36,M,24.9,139.0,164.4,8.8,69.1,Obesity,Medium +CO2082,45,M,17.9,138.0,61.6,5.2,75.9,Type 2 Diabetes,Low +CO2083,55,M,34.2,127.0,82.3,6.7,93.7,Heart Failure,Low +CO2084,48,F,27.0,150.0,89.7,8.0,70.6,Type 2 Diabetes,Low +CO2085,70,M,31.6,130.0,130.6,7.9,81.0,Obesity,Low +CO2086,74,F,22.1,147.0,98.0,6.7,57.5,Hyperlipidemia,Low +CO2087,30,M,23.1,132.0,129.1,5.6,38.1,Hypertension,Medium +CO2088,50,F,16.0,144.0,103.5,6.5,59.8,Hyperlipidemia,Low +CO2089,38,F,29.4,148.0,152.4,7.6,33.5,Heart Failure,Medium +CO2090,75,M,28.1,109.0,97.4,8.1,81.1,Heart Failure,Medium +CO2091,26,F,26.1,90.0,181.4,6.0,57.5,Asthma,Low +CO2092,40,F,25.5,135.0,87.3,6.2,64.3,CKD,Low +CO2093,84,F,30.4,133.0,79.0,8.1,76.8,COPD,Medium +CO2094,75,F,27.8,162.0,103.6,4.9,57.2,Type 2 Diabetes,Medium +CO2095,42,M,36.2,123.0,40.0,5.4,31.0,Heart Failure,Medium +CO2096,31,M,33.2,150.0,181.9,4.9,22.3,COPD,Medium +CO2097,76,F,38.3,143.0,161.8,10.8,65.1,Hypertension,High +CO2098,45,M,24.6,176.0,187.4,6.8,118.8,Asthma,Medium +CO2099,54,M,36.9,80.0,113.9,6.4,90.9,Type 2 Diabetes,Low +CO2100,74,F,25.4,140.0,109.2,4.5,69.2,CKD,Low +CO2101,74,F,33.5,139.0,150.7,4.8,83.2,Type 2 Diabetes,Low +CO2102,44,F,24.3,99.0,169.7,5.3,80.7,COPD,Low +CO2103,64,F,29.5,117.0,162.1,6.2,23.4,Hyperlipidemia,Medium +CO2104,62,F,30.9,102.0,99.3,9.2,110.2,Obesity,Medium +CO2105,50,F,38.4,132.0,149.1,4.5,29.0,Hypertension,Medium +CO2106,51,F,23.8,117.0,142.6,5.3,110.0,CKD,Low +CO2107,43,M,35.4,154.0,105.0,5.6,88.3,COPD,Low +CO2108,22,M,31.5,178.0,83.8,8.0,70.3,CKD,High +CO2109,53,F,34.3,114.0,68.6,6.1,95.8,Hypertension,Low +CO2110,42,F,38.9,159.0,106.7,8.2,40.0,COPD,High +CO2111,42,F,31.1,122.0,152.4,8.5,49.0,Obesity,Medium +CO2112,75,F,25.0,148.0,149.6,5.7,31.2,CKD,Medium +CO2113,57,F,31.5,108.0,87.9,8.1,79.7,Hyperlipidemia,Medium +CO2114,56,F,29.8,190.0,117.5,6.9,88.5,Asthma,Medium +CO2115,21,M,28.2,92.0,148.9,5.4,69.7,Heart Failure,Low +CO2116,26,M,30.1,157.0,79.2,5.4,92.5,CKD,Low +CO2117,68,M,25.3,143.0,141.9,8.2,89.8,Hyperlipidemia,Medium +CO2118,40,M,35.1,124.0,139.9,7.7,90.9,Hyperlipidemia,Low +CO2119,56,M,28.2,127.0,146.8,5.1,44.0,CKD,Medium +CO2120,63,F,37.1,147.0,67.8,5.9,100.7,Hypertension,Low +CO2121,79,M,28.9,122.0,79.9,7.3,80.0,Type 2 Diabetes,Low +CO2122,25,F,28.1,184.0,146.3,6.4,46.8,Heart Failure,Medium +CO2123,28,M,22.2,108.0,69.0,8.4,64.0,Hypertension,Medium +CO2124,64,F,27.5,130.0,155.2,5.9,98.0,Hypertension,Low +CO2125,75,M,16.0,120.0,49.6,4.5,98.6,Hypertension,Low +CO2126,38,F,17.2,136.0,65.6,5.4,85.8,Hyperlipidemia,Low +CO2127,74,M,29.0,124.0,161.7,5.1,37.1,Heart Failure,Medium +CO2128,62,M,27.2,130.0,82.4,6.4,103.5,Atrial Fibrillation,Low +CO2129,37,F,25.6,178.0,55.9,6.1,72.5,Obesity,Medium +CO2130,53,M,27.1,141.0,85.6,5.9,93.3,CKD,Low +CO2131,22,F,30.5,145.0,99.0,6.7,54.7,Heart Failure,Low +CO2132,38,F,36.4,146.0,133.1,6.5,51.7,Heart Failure,Low +CO2133,35,F,38.1,161.0,68.8,8.7,34.4,Heart Failure,High +CO2134,43,F,25.5,137.0,93.5,4.5,24.6,Hypertension,Medium +CO2135,80,M,16.6,143.0,89.2,4.5,101.8,Obesity,Low +CO2136,69,F,23.0,80.0,128.0,8.5,27.8,Hypertension,High +CO2137,55,F,33.0,85.0,117.4,7.8,50.3,Heart Failure,Low +CO2138,43,F,24.3,136.0,116.1,4.9,70.0,COPD,Low +CO2139,29,F,29.4,125.0,171.4,8.0,58.9,Hyperlipidemia,Low +CO2140,72,F,25.9,118.0,113.3,8.4,59.8,Type 2 Diabetes,Medium +CO2141,47,M,22.1,143.0,97.7,8.2,114.7,COPD,Medium +CO2142,58,F,24.5,106.0,113.0,8.6,55.3,CKD,Medium +CO2143,63,M,33.4,144.0,139.9,7.4,45.9,Hyperlipidemia,Low +CO2144,63,F,29.4,132.0,174.8,4.9,59.1,CKD,Low +CO2145,28,F,31.2,155.0,176.9,4.5,46.9,Hyperlipidemia,Low +CO2146,62,M,21.1,139.0,115.4,7.1,62.3,Asthma,Low +CO2147,74,F,29.3,94.0,114.0,4.5,113.2,Hypertension,Low +CO2148,40,F,24.7,135.0,142.9,8.9,69.6,Atrial Fibrillation,Medium +CO2149,62,F,26.0,150.0,158.3,9.5,42.0,Hypertension,High +CO2150,69,M,36.5,120.0,178.2,5.4,105.2,CAD,Medium +CO2151,78,F,29.2,145.0,52.6,7.1,39.6,Type 2 Diabetes,Medium +CO2152,32,M,28.2,126.0,120.6,7.7,85.4,Heart Failure,Low +CO2153,33,F,34.6,115.0,71.4,6.4,29.0,Atrial Fibrillation,Medium +CO2154,44,F,33.9,122.0,226.6,8.8,67.2,Hyperlipidemia,Medium +CO2155,24,F,34.8,173.0,102.5,6.5,88.1,Heart Failure,Medium +CO2156,40,F,37.4,112.0,132.6,8.5,68.3,COPD,Medium +CO2157,36,M,16.0,144.0,49.9,5.0,46.1,CAD,Low +CO2158,82,F,34.2,130.0,175.7,8.2,58.8,Heart Failure,Medium +CO2159,42,M,27.5,125.0,139.8,5.9,75.7,Hyperlipidemia,Low +CO2160,46,M,22.0,110.0,134.5,4.5,63.4,Obesity,Low +CO2161,58,F,22.9,150.0,172.1,4.7,106.5,Hypertension,Low +CO2162,54,F,26.0,136.0,52.1,6.7,81.7,Atrial Fibrillation,Low +CO2163,57,M,23.5,179.0,87.9,5.7,62.8,Type 2 Diabetes,Medium +CO2164,23,M,27.4,126.0,61.4,5.8,79.3,Heart Failure,Low +CO2165,31,M,18.9,92.0,127.8,8.8,130.0,Obesity,Medium +CO2166,84,M,25.0,110.0,149.5,8.2,88.7,COPD,Medium +CO2167,74,F,28.8,122.0,144.3,8.1,63.0,CAD,Medium +CO2168,50,M,33.6,132.0,53.1,7.4,86.2,Asthma,Low +CO2169,27,F,16.0,126.0,40.8,6.6,68.1,Heart Failure,Low +CO2170,49,F,23.2,147.0,115.1,7.4,68.2,Obesity,Low +CO2171,25,F,31.8,118.0,112.9,5.5,50.0,CKD,Low +CO2172,34,M,39.2,143.0,148.9,7.0,55.0,Obesity,Low +CO2173,82,F,21.5,91.0,163.0,6.7,45.5,COPD,Low +CO2174,21,M,30.8,154.0,124.3,5.5,114.5,Heart Failure,Low +CO2175,34,M,25.7,101.0,98.7,9.1,73.7,COPD,Medium +CO2176,62,F,23.9,145.0,135.3,8.9,97.6,Obesity,Medium +CO2177,44,F,22.3,136.0,138.4,4.5,88.5,Hypertension,Low +CO2178,32,M,27.9,106.0,40.0,6.4,63.4,Heart Failure,Low +CO2179,33,M,28.8,139.0,84.7,4.5,62.8,COPD,Low +CO2180,34,F,26.1,119.0,109.4,8.9,88.2,Type 2 Diabetes,Medium +CO2181,70,M,25.1,109.0,140.4,4.5,42.7,CKD,Medium +CO2182,53,M,25.0,132.0,100.9,7.9,72.6,Heart Failure,Low +CO2183,66,F,19.0,110.0,181.2,5.1,87.0,Heart Failure,Low +CO2184,75,F,27.3,146.0,107.0,7.7,103.4,Type 2 Diabetes,Low +CO2185,28,M,34.7,177.0,120.6,5.6,70.8,Asthma,Medium +CO2186,38,F,30.9,126.0,128.5,6.5,46.7,Obesity,Low +CO2187,82,F,21.4,153.0,115.1,7.2,63.4,Obesity,Low +CO2188,31,M,26.0,127.0,150.3,7.7,71.3,Hyperlipidemia,Low +CO2189,35,F,33.9,151.0,89.2,7.2,91.1,CAD,Low +CO2190,31,M,30.0,116.0,114.9,6.2,108.1,Heart Failure,Low +CO2191,37,M,33.6,112.0,105.7,10.2,54.5,Heart Failure,Medium +CO2192,53,M,23.3,80.0,154.7,4.8,70.3,Obesity,Low +CO2193,65,M,40.6,123.0,126.9,6.9,82.0,CKD,Low +CO2194,73,F,35.3,149.0,94.7,5.9,77.3,Hypertension,Low +CO2195,20,M,41.7,123.0,74.9,6.3,53.7,Heart Failure,Low +CO2196,55,M,28.1,145.0,106.8,7.7,64.2,Obesity,Low +CO2197,82,F,38.9,138.0,106.9,5.4,30.5,Asthma,Medium +CO2198,70,M,38.4,141.0,88.6,6.6,38.4,Obesity,Medium +CO2199,81,F,21.2,134.0,163.7,6.7,122.1,Hypertension,Low +CO2200,52,F,41.7,183.0,80.8,6.3,27.2,CKD,High diff --git a/medical-imaging-demo/data/labs.csv b/medical-imaging-demo/data/labs.csv new file mode 100644 index 0000000..c9a9491 --- /dev/null +++ b/medical-imaging-demo/data/labs.csv @@ -0,0 +1,201 @@ +patient_id,date,test,value,unit,reference_low,reference_high,flag +PT1001,2026-06-15,WBC,11.298,10³/µL,4.5,11.0,H +PT1001,2026-06-15,Hemoglobin,14.334,g/dL,12.0,17.5,N +PT1001,2026-06-15,Platelets,222.4,10³/µL,150.0,400.0,N +PT1001,2026-06-15,Sodium,140.412,mEq/L,136.0,145.0,N +PT1001,2026-06-15,Potassium,3.957,mEq/L,3.5,5.0,N +PT1001,2026-06-15,Creatinine,1.149,mg/dL,0.7,1.3,N +PT1001,2026-06-15,BUN,12.525,mg/dL,7.0,25.0,N +PT1001,2026-06-15,Glucose,96.633,mg/dL,70.0,100.0,N +PT1001,2026-06-15,Lactate,1.473,mmol/L,0.5,2.0,N +PT1001,2026-06-15,Troponin,0.028,ng/mL,0.0,0.04,N +PT1002,2026-06-15,WBC,9.094,10³/µL,4.5,11.0,N +PT1002,2026-06-15,Hemoglobin,16.156,g/dL,12.0,17.5,N +PT1002,2026-06-15,Platelets,251.797,10³/µL,150.0,400.0,N +PT1002,2026-06-15,Sodium,137.859,mEq/L,136.0,145.0,N +PT1002,2026-06-15,Potassium,4.036,mEq/L,3.5,5.0,N +PT1002,2026-06-15,Creatinine,1.167,mg/dL,0.7,1.3,N +PT1002,2026-06-15,BUN,6.461,mg/dL,7.0,25.0,L +PT1002,2026-06-15,Glucose,67.004,mg/dL,70.0,100.0,L +PT1002,2026-06-15,Lactate,1.351,mmol/L,0.5,2.0,N +PT1002,2026-06-15,Troponin,0.03,ng/mL,0.0,0.04,N +PT1003,2026-06-15,WBC,9.661,10³/µL,4.5,11.0,N +PT1003,2026-06-15,Hemoglobin,13.181,g/dL,12.0,17.5,N +PT1003,2026-06-15,Platelets,186.533,10³/µL,150.0,400.0,N +PT1003,2026-06-15,Sodium,138.647,mEq/L,136.0,145.0,N +PT1003,2026-06-15,Potassium,4.073,mEq/L,3.5,5.0,N +PT1003,2026-06-15,Creatinine,0.94,mg/dL,0.7,1.3,N +PT1003,2026-06-15,BUN,16.654,mg/dL,7.0,25.0,N +PT1003,2026-06-15,Glucose,97.651,mg/dL,70.0,100.0,N +PT1003,2026-06-15,Lactate,1.223,mmol/L,0.5,2.0,N +PT1003,2026-06-15,Troponin,0.031,ng/mL,0.0,0.04,N +PT1004,2026-06-15,WBC,9.027,10³/µL,4.5,11.0,N +PT1004,2026-06-15,Hemoglobin,13.578,g/dL,12.0,17.5,N +PT1004,2026-06-15,Platelets,323.232,10³/µL,150.0,400.0,N +PT1004,2026-06-15,Sodium,142.051,mEq/L,136.0,145.0,N +PT1004,2026-06-15,Potassium,4.25,mEq/L,3.5,5.0,N +PT1004,2026-06-15,Creatinine,1.031,mg/dL,0.7,1.3,N +PT1004,2026-06-15,BUN,15.688,mg/dL,7.0,25.0,N +PT1004,2026-06-15,Glucose,75.172,mg/dL,70.0,100.0,N +PT1004,2026-06-15,Lactate,2.315,mmol/L,0.5,2.0,H +PT1004,2026-06-15,Troponin,0.033,ng/mL,0.0,0.04,N +PT1005,2026-06-15,WBC,8.778,10³/µL,4.5,11.0,N +PT1005,2026-06-15,Hemoglobin,14.081,g/dL,12.0,17.5,N +PT1005,2026-06-15,Platelets,268.115,10³/µL,150.0,400.0,N +PT1005,2026-06-15,Sodium,137.337,mEq/L,136.0,145.0,N +PT1005,2026-06-15,Potassium,4.461,mEq/L,3.5,5.0,N +PT1005,2026-06-15,Creatinine,1.061,mg/dL,0.7,1.3,N +PT1005,2026-06-15,BUN,14.885,mg/dL,7.0,25.0,N +PT1005,2026-06-15,Glucose,85.269,mg/dL,70.0,100.0,N +PT1005,2026-06-15,Lactate,1.116,mmol/L,0.5,2.0,N +PT1005,2026-06-15,Troponin,0.014,ng/mL,0.0,0.04,N +PT1006,2026-06-15,WBC,6.236,10³/µL,4.5,11.0,N +PT1006,2026-06-15,Hemoglobin,13.066,g/dL,12.0,17.5,N +PT1006,2026-06-15,Platelets,222.357,10³/µL,150.0,400.0,N +PT1006,2026-06-15,Sodium,138.812,mEq/L,136.0,145.0,N +PT1006,2026-06-15,Potassium,4.74,mEq/L,3.5,5.0,N +PT1006,2026-06-15,Creatinine,0.889,mg/dL,0.7,1.3,N +PT1006,2026-06-15,BUN,5.016,mg/dL,7.0,25.0,L +PT1006,2026-06-15,Glucose,87.625,mg/dL,70.0,100.0,N +PT1006,2026-06-15,Lactate,1.531,mmol/L,0.5,2.0,N +PT1006,2026-06-15,Troponin,0.032,ng/mL,0.0,0.04,N +PT1007,2026-06-15,WBC,8.074,10³/µL,4.5,11.0,N +PT1007,2026-06-15,Hemoglobin,12.869,g/dL,12.0,17.5,N +PT1007,2026-06-15,Platelets,215.08,10³/µL,150.0,400.0,N +PT1007,2026-06-15,Sodium,142.12,mEq/L,136.0,145.0,N +PT1007,2026-06-15,Potassium,4.907,mEq/L,3.5,5.0,N +PT1007,2026-06-15,Creatinine,0.794,mg/dL,0.7,1.3,N +PT1007,2026-06-15,BUN,17.144,mg/dL,7.0,25.0,N +PT1007,2026-06-15,Glucose,80.006,mg/dL,70.0,100.0,N +PT1007,2026-06-15,Lactate,0.879,mmol/L,0.5,2.0,N +PT1007,2026-06-15,Troponin,0.02,ng/mL,0.0,0.04,N +PT1008,2026-06-15,WBC,7.489,10³/µL,4.5,11.0,N +PT1008,2026-06-15,Hemoglobin,11.409,g/dL,12.0,17.5,L +PT1008,2026-06-15,Platelets,290.119,10³/µL,150.0,400.0,N +PT1008,2026-06-15,Sodium,141.386,mEq/L,136.0,145.0,N +PT1008,2026-06-15,Potassium,4.586,mEq/L,3.5,5.0,N +PT1008,2026-06-15,Creatinine,0.897,mg/dL,0.7,1.3,N +PT1008,2026-06-15,BUN,7.426,mg/dL,7.0,25.0,N +PT1008,2026-06-15,Glucose,81.208,mg/dL,70.0,100.0,N +PT1008,2026-06-15,Lactate,1.568,mmol/L,0.5,2.0,N +PT1008,2026-06-15,Troponin,0.019,ng/mL,0.0,0.04,N +PT1009,2026-06-15,WBC,9.406,10³/µL,4.5,11.0,N +PT1009,2026-06-15,Hemoglobin,12.604,g/dL,12.0,17.5,N +PT1009,2026-06-15,Platelets,335.907,10³/µL,150.0,400.0,N +PT1009,2026-06-15,Sodium,141.172,mEq/L,136.0,145.0,N +PT1009,2026-06-15,Potassium,4.09,mEq/L,3.5,5.0,N +PT1009,2026-06-15,Creatinine,1.193,mg/dL,0.7,1.3,N +PT1009,2026-06-15,BUN,17.296,mg/dL,7.0,25.0,N +PT1009,2026-06-15,Glucose,76.142,mg/dL,70.0,100.0,N +PT1009,2026-06-15,Lactate,1.692,mmol/L,0.5,2.0,N +PT1009,2026-06-15,Troponin,0.017,ng/mL,0.0,0.04,N +PT1010,2026-06-15,WBC,7.822,10³/µL,4.5,11.0,N +PT1010,2026-06-15,Hemoglobin,13.326,g/dL,12.0,17.5,N +PT1010,2026-06-15,Platelets,271.124,10³/µL,150.0,400.0,N +PT1010,2026-06-15,Sodium,137.946,mEq/L,136.0,145.0,N +PT1010,2026-06-15,Potassium,4.173,mEq/L,3.5,5.0,N +PT1010,2026-06-15,Creatinine,1.006,mg/dL,0.7,1.3,N +PT1010,2026-06-15,BUN,19.271,mg/dL,7.0,25.0,N +PT1010,2026-06-15,Glucose,72.341,mg/dL,70.0,100.0,N +PT1010,2026-06-15,Lactate,1.701,mmol/L,0.5,2.0,N +PT1010,2026-06-15,Troponin,0.032,ng/mL,0.0,0.04,N +PT1011,2026-06-15,WBC,7.381,10³/µL,4.5,11.0,N +PT1011,2026-06-15,Hemoglobin,14.963,g/dL,12.0,17.5,N +PT1011,2026-06-15,Platelets,297.989,10³/µL,150.0,400.0,N +PT1011,2026-06-15,Sodium,140.725,mEq/L,136.0,145.0,N +PT1011,2026-06-15,Potassium,4.522,mEq/L,3.5,5.0,N +PT1011,2026-06-15,Creatinine,0.93,mg/dL,0.7,1.3,N +PT1011,2026-06-15,BUN,11.895,mg/dL,7.0,25.0,N +PT1011,2026-06-15,Glucose,88.854,mg/dL,70.0,100.0,N +PT1011,2026-06-15,Lactate,0.563,mmol/L,0.5,2.0,N +PT1011,2026-06-15,Troponin,0.027,ng/mL,0.0,0.04,N +PT1012,2026-06-15,WBC,9.159,10³/µL,4.5,11.0,N +PT1012,2026-06-15,Hemoglobin,13.459,g/dL,12.0,17.5,N +PT1012,2026-06-15,Platelets,381.657,10³/µL,150.0,400.0,N +PT1012,2026-06-15,Sodium,139.552,mEq/L,136.0,145.0,N +PT1012,2026-06-15,Potassium,4.053,mEq/L,3.5,5.0,N +PT1012,2026-06-15,Creatinine,0.882,mg/dL,0.7,1.3,N +PT1012,2026-06-15,BUN,18.42,mg/dL,7.0,25.0,N +PT1012,2026-06-15,Glucose,81.478,mg/dL,70.0,100.0,N +PT1012,2026-06-15,Lactate,0.603,mmol/L,0.5,2.0,N +PT1012,2026-06-15,Troponin,0.024,ng/mL,0.0,0.04,N +PT1013,2026-06-15,WBC,7.182,10³/µL,4.5,11.0,N +PT1013,2026-06-15,Hemoglobin,16.542,g/dL,12.0,17.5,N +PT1013,2026-06-15,Platelets,298.158,10³/µL,150.0,400.0,N +PT1013,2026-06-15,Sodium,141.219,mEq/L,136.0,145.0,N +PT1013,2026-06-15,Potassium,4.707,mEq/L,3.5,5.0,N +PT1013,2026-06-15,Creatinine,1.029,mg/dL,0.7,1.3,N +PT1013,2026-06-15,BUN,20.224,mg/dL,7.0,25.0,N +PT1013,2026-06-15,Glucose,79.151,mg/dL,70.0,100.0,N +PT1013,2026-06-15,Lactate,1.991,mmol/L,0.5,2.0,N +PT1013,2026-06-15,Troponin,0.023,ng/mL,0.0,0.04,N +PT1014,2026-06-15,WBC,5.407,10³/µL,4.5,11.0,N +PT1014,2026-06-15,Hemoglobin,14.977,g/dL,12.0,17.5,N +PT1014,2026-06-15,Platelets,289.0,10³/µL,150.0,400.0,N +PT1014,2026-06-15,Sodium,140.837,mEq/L,136.0,145.0,N +PT1014,2026-06-15,Potassium,3.215,mEq/L,3.5,5.0,L +PT1014,2026-06-15,Creatinine,0.901,mg/dL,0.7,1.3,N +PT1014,2026-06-15,BUN,8.533,mg/dL,7.0,25.0,N +PT1014,2026-06-15,Glucose,72.685,mg/dL,70.0,100.0,N +PT1014,2026-06-15,Lactate,1.325,mmol/L,0.5,2.0,N +PT1014,2026-06-15,Troponin,0.013,ng/mL,0.0,0.04,N +PT1015,2026-06-15,WBC,7.041,10³/µL,4.5,11.0,N +PT1015,2026-06-15,Hemoglobin,13.273,g/dL,12.0,17.5,N +PT1015,2026-06-15,Platelets,378.448,10³/µL,150.0,400.0,N +PT1015,2026-06-15,Sodium,140.608,mEq/L,136.0,145.0,N +PT1015,2026-06-15,Potassium,3.565,mEq/L,3.5,5.0,N +PT1015,2026-06-15,Creatinine,1.116,mg/dL,0.7,1.3,N +PT1015,2026-06-15,BUN,14.15,mg/dL,7.0,25.0,N +PT1015,2026-06-15,Glucose,95.743,mg/dL,70.0,100.0,N +PT1015,2026-06-15,Lactate,1.246,mmol/L,0.5,2.0,N +PT1015,2026-06-15,Troponin,0.012,ng/mL,0.0,0.04,N +PT1016,2026-06-15,WBC,6.693,10³/µL,4.5,11.0,N +PT1016,2026-06-15,Hemoglobin,14.086,g/dL,12.0,17.5,N +PT1016,2026-06-15,Platelets,311.732,10³/µL,150.0,400.0,N +PT1016,2026-06-15,Sodium,138.38,mEq/L,136.0,145.0,N +PT1016,2026-06-15,Potassium,4.81,mEq/L,3.5,5.0,N +PT1016,2026-06-15,Creatinine,1.066,mg/dL,0.7,1.3,N +PT1016,2026-06-15,BUN,17.212,mg/dL,7.0,25.0,N +PT1016,2026-06-15,Glucose,85.657,mg/dL,70.0,100.0,N +PT1016,2026-06-15,Lactate,1.241,mmol/L,0.5,2.0,N +PT1016,2026-06-15,Troponin,0.005,ng/mL,0.0,0.04,N +PT1017,2026-06-15,WBC,8.32,10³/µL,4.5,11.0,N +PT1017,2026-06-15,Hemoglobin,17.927,g/dL,12.0,17.5,H +PT1017,2026-06-15,Platelets,326.887,10³/µL,150.0,400.0,N +PT1017,2026-06-15,Sodium,141.684,mEq/L,136.0,145.0,N +PT1017,2026-06-15,Potassium,3.559,mEq/L,3.5,5.0,N +PT1017,2026-06-15,Creatinine,1.196,mg/dL,0.7,1.3,N +PT1017,2026-06-15,BUN,20.334,mg/dL,7.0,25.0,N +PT1017,2026-06-15,Glucose,95.507,mg/dL,70.0,100.0,N +PT1017,2026-06-15,Lactate,0.843,mmol/L,0.5,2.0,N +PT1017,2026-06-15,Troponin,0.015,ng/mL,0.0,0.04,N +PT1018,2026-06-15,WBC,4.853,10³/µL,4.5,11.0,N +PT1018,2026-06-15,Hemoglobin,12.159,g/dL,12.0,17.5,N +PT1018,2026-06-15,Platelets,231.731,10³/µL,150.0,400.0,N +PT1018,2026-06-15,Sodium,141.763,mEq/L,136.0,145.0,N +PT1018,2026-06-15,Potassium,4.063,mEq/L,3.5,5.0,N +PT1018,2026-06-15,Creatinine,0.88,mg/dL,0.7,1.3,N +PT1018,2026-06-15,BUN,17.833,mg/dL,7.0,25.0,N +PT1018,2026-06-15,Glucose,55.821,mg/dL,70.0,100.0,L +PT1018,2026-06-15,Lactate,1.006,mmol/L,0.5,2.0,N +PT1018,2026-06-15,Troponin,0.024,ng/mL,0.0,0.04,N +PT1019,2026-06-15,WBC,6.963,10³/µL,4.5,11.0,N +PT1019,2026-06-15,Hemoglobin,16.894,g/dL,12.0,17.5,N +PT1019,2026-06-15,Platelets,225.403,10³/µL,150.0,400.0,N +PT1019,2026-06-15,Sodium,138.901,mEq/L,136.0,145.0,N +PT1019,2026-06-15,Potassium,3.806,mEq/L,3.5,5.0,N +PT1019,2026-06-15,Creatinine,0.864,mg/dL,0.7,1.3,N +PT1019,2026-06-15,BUN,17.496,mg/dL,7.0,25.0,N +PT1019,2026-06-15,Glucose,92.273,mg/dL,70.0,100.0,N +PT1019,2026-06-15,Lactate,2.22,mmol/L,0.5,2.0,H +PT1019,2026-06-15,Troponin,0.027,ng/mL,0.0,0.04,N +PT1020,2026-06-15,WBC,5.453,10³/µL,4.5,11.0,N +PT1020,2026-06-15,Hemoglobin,16.799,g/dL,12.0,17.5,N +PT1020,2026-06-15,Platelets,311.535,10³/µL,150.0,400.0,N +PT1020,2026-06-15,Sodium,140.577,mEq/L,136.0,145.0,N +PT1020,2026-06-15,Potassium,4.73,mEq/L,3.5,5.0,N +PT1020,2026-06-15,Creatinine,1.426,mg/dL,0.7,1.3,H +PT1020,2026-06-15,BUN,14.979,mg/dL,7.0,25.0,N +PT1020,2026-06-15,Glucose,77.503,mg/dL,70.0,100.0,N +PT1020,2026-06-15,Lactate,1.847,mmol/L,0.5,2.0,N +PT1020,2026-06-15,Troponin,0.052,ng/mL,0.0,0.04,H diff --git a/medical-imaging-demo/data/patients.csv b/medical-imaging-demo/data/patients.csv new file mode 100644 index 0000000..888ce80 --- /dev/null +++ b/medical-imaging-demo/data/patients.csv @@ -0,0 +1,61 @@ +patient_id,name,age,gender,diagnosis,ward,department,admitted_date,los_days,risk_score,sepsis_risk,fall_risk,readmit_risk,deterioration_risk,is_icu +PT1001,Mark White,82,M,Trauma,ICU,Pulmonology,2026-06-03,7,41.6,7.3,47.3,11.1,36.9,True +PT1002,Robert Jones,72,M,Acute MI,MICU,Cardiology,2026-06-07,2,12.5,4.9,17.3,52.1,13.3,True +PT1003,Matthew Nelson,61,M,Cellulitis,CCU,Pulmonology,2026-06-15,5,32.5,6.9,8.2,33.6,21.8,True +PT1004,Daniel Allen,83,F,Acute MI,ICU,Neurology,2026-06-12,8,55.2,15.0,28.8,73.9,14.1,True +PT1005,Charles Hall,49,F,Pulmonary Embolism,MICU,Surgery,2026-06-14,9,34.7,7.7,16.5,14.2,43.2,True +PT1006,Nancy Wilson,73,M,Atrial Fibrillation,MICU,Cardiology,2026-06-10,4,51.9,11.3,33.3,44.5,29.2,True +PT1007,Jessica Harris,80,F,Cellulitis,Step-Down,Neurology,2026-06-04,12,6.9,3.2,14.6,54.3,2.0,False +PT1008,Anthony Allen,30,M,COPD Exacerbation,ED Obs,Neurology,2026-06-03,4,26.9,20.5,44.1,9.6,24.6,False +PT1009,Charles Hall,43,F,Atrial Fibrillation,ICU,Nephrology,2026-06-06,13,40.6,22.7,60.2,24.5,24.2,True +PT1010,Robert Thompson,46,F,Respiratory Failure,Step-Down,Nephrology,2026-06-10,3,17.8,4.3,32.0,43.7,11.7,False +PT1011,Jessica Jackson,36,F,Sepsis,General Med,Pulmonology,2026-06-07,6,25.1,13.2,2.4,31.6,30.6,False +PT1012,Betty Walker,83,M,Respiratory Failure,Step-Down,Cardiology,2026-06-12,5,4.1,21.5,66.6,23.8,25.6,False +PT1013,Karen Moore,40,F,Pneumonia,ED Obs,Surgery,2026-06-13,4,25.4,32.5,18.1,43.5,14.1,False +PT1014,Barbara Scott,55,M,GI Bleed,Step-Down,Oncology,2026-06-04,10,34.1,21.5,15.7,23.4,9.6,False +PT1015,Sandra Lewis,34,M,COPD Exacerbation,ED Obs,Cardiology,2026-06-04,12,43.5,36.4,22.3,19.5,11.5,False +PT1016,Betty Anderson,38,M,Stroke,General Med,Oncology,2026-06-14,13,32.2,1.9,15.9,58.2,4.0,False +PT1017,Sarah Baker,79,F,Diabetic Ketoacidosis,Step-Down,Surgery,2026-06-15,9,28.4,5.9,3.0,21.6,12.0,False +PT1018,Robert Harris,78,M,Diabetic Ketoacidosis,General Med,Pulmonology,2026-06-08,6,67.1,0.8,15.8,11.5,1.9,False +PT1019,Daniel King,54,F,Pneumonia,ICU,Pulmonology,2026-06-15,1,55.3,6.6,15.7,43.5,9.5,True +PT1020,James Martin,53,F,Diabetic Ketoacidosis,CCU,Oncology,2026-06-08,7,15.8,10.7,11.7,39.3,1.0,True +PT1021,Jennifer Smith,51,M,Pulmonary Embolism,Step-Down,Neurology,2026-06-01,5,14.4,1.5,53.8,60.3,30.0,False +PT1022,Charles Young,42,M,Sepsis,General Med,General Medicine,2026-06-10,13,32.0,5.5,13.4,37.5,14.2,False +PT1023,Betty Jackson,80,F,COPD Exacerbation,General Med,Oncology,2026-06-03,7,56.2,1.8,21.8,41.9,21.1,False +PT1024,Charles Moore,62,M,Stroke,General Med,General Medicine,2026-06-10,2,45.9,24.6,32.7,53.7,0.7,False +PT1025,Patricia Young,41,M,Diabetic Ketoacidosis,ED Obs,Oncology,2026-06-01,10,22.0,38.2,32.9,67.0,16.9,False +PT1026,Mary Anderson,56,M,UTI,ED Obs,Nephrology,2026-06-12,13,35.8,20.1,38.3,5.9,9.0,False +PT1027,Susan Walker,72,M,COPD Exacerbation,Step-Down,Nephrology,2026-06-06,3,4.9,11.2,22.8,32.2,33.1,False +PT1028,Nancy White,50,F,Acute MI,MICU,Surgery,2026-06-15,4,31.4,1.7,19.4,12.8,34.3,True +PT1029,Margaret Scott,30,F,COPD Exacerbation,MICU,Surgery,2026-06-14,8,25.5,6.4,3.4,22.5,8.6,True +PT1030,Anthony Young,75,F,GI Bleed,ICU,Oncology,2026-06-04,6,11.5,18.2,17.1,28.2,22.7,True +PT1031,Charles Thompson,22,F,COPD Exacerbation,General Med,Oncology,2026-06-02,2,2.6,13.0,32.7,15.8,24.7,False +PT1032,Charles Smith,29,F,COPD Exacerbation,General Med,Nephrology,2026-06-08,14,14.0,22.0,40.0,12.8,1.9,False +PT1033,Mary Walker,65,M,Heart Failure,General Med,Pulmonology,2026-06-06,12,41.5,35.7,7.7,5.2,8.2,False +PT1034,Jennifer Green,61,F,Diabetic Ketoacidosis,ED Obs,Surgery,2026-06-09,5,9.1,23.8,25.3,8.7,20.0,False +PT1035,Karen Young,83,M,Cellulitis,ICU,Neurology,2026-06-02,9,19.4,39.2,25.4,3.4,3.8,True +PT1036,Christopher Martin,46,F,GI Bleed,General Med,General Medicine,2026-06-15,11,37.4,19.5,39.6,6.9,3.3,False +PT1037,Thomas Brown,46,M,Sepsis,Step-Down,Cardiology,2026-06-13,10,16.4,21.8,26.9,16.3,20.7,False +PT1038,Joseph Martin,89,F,Hypertensive Crisis,ICU,Pulmonology,2026-06-05,13,33.2,14.2,19.3,22.3,11.6,True +PT1039,Karen Scott,82,M,Pulmonary Embolism,General Med,Neurology,2026-06-02,2,40.7,4.7,39.7,29.9,47.3,False +PT1040,Betty Thompson,58,F,Cellulitis,General Med,General Medicine,2026-06-05,13,52.6,3.7,8.6,27.2,18.1,False +PT1041,William Thomas,79,M,COPD Exacerbation,MICU,Oncology,2026-06-07,10,36.8,5.9,39.0,21.8,42.5,True +PT1042,Margaret White,58,M,Stroke,Step-Down,General Medicine,2026-06-04,4,38.6,3.1,7.7,19.8,23.4,False +PT1043,Mark Taylor,53,F,Respiratory Failure,General Med,Nephrology,2026-06-04,6,7.3,10.3,44.2,63.9,5.5,False +PT1044,Karen Jackson,36,M,Atrial Fibrillation,ED Obs,Nephrology,2026-06-07,1,36.7,3.3,23.7,15.0,30.0,False +PT1045,Elizabeth Wright,67,F,Respiratory Failure,MICU,Nephrology,2026-06-06,12,35.8,14.6,20.6,27.3,14.8,True +PT1046,Michael Wilson,29,F,Sepsis,ED Obs,General Medicine,2026-06-14,4,39.2,22.2,64.2,6.9,20.4,False +PT1047,Joseph Smith,28,F,Pneumonia,ICU,Nephrology,2026-06-05,10,59.8,9.7,69.1,14.8,3.3,True +PT1048,Elizabeth Jackson,23,M,Acute MI,MICU,Surgery,2026-06-06,13,17.9,7.4,19.3,40.0,37.4,True +PT1049,Elizabeth Nelson,22,M,Heart Failure,General Med,Neurology,2026-06-12,1,58.1,1.4,23.8,58.7,21.7,False +PT1050,Sarah King,64,F,Sepsis,Step-Down,Cardiology,2026-06-02,13,9.6,35.5,7.8,34.5,10.0,False +PT1051,Christopher Harris,90,M,Pulmonary Embolism,General Med,Nephrology,2026-06-12,2,44.6,17.8,32.4,48.9,7.4,False +PT1052,Thomas Martin,56,F,Stroke,General Med,Pulmonology,2026-06-11,3,45.8,20.2,35.1,71.2,32.0,False +PT1053,Joseph Wright,57,M,COPD Exacerbation,ICU,Oncology,2026-06-04,5,8.9,21.1,35.0,33.2,6.6,True +PT1054,Elizabeth King,66,F,Respiratory Failure,General Med,Neurology,2026-06-13,7,18.8,20.6,19.2,27.9,28.6,False +PT1055,Elizabeth Johnson,54,M,Acute MI,CCU,Cardiology,2026-06-06,5,7.7,42.8,66.1,44.4,42.9,True +PT1056,Patricia Thomas,70,F,Sepsis,Step-Down,General Medicine,2026-06-05,12,8.4,21.0,19.0,34.9,4.4,False +PT1057,Jessica Anderson,38,F,Diabetic Ketoacidosis,General Med,General Medicine,2026-06-03,14,18.1,27.8,22.1,48.3,6.1,False +PT1058,Daniel Scott,89,F,Trauma,Step-Down,Nephrology,2026-06-03,6,36.3,11.2,28.7,15.5,14.9,False +PT1059,Mark Lewis,24,M,GI Bleed,General Med,Nephrology,2026-06-09,13,33.6,36.6,22.7,13.0,17.2,False +PT1060,Charles Miller,37,F,Pneumonia,Step-Down,General Medicine,2026-06-04,7,26.8,5.8,47.1,51.5,4.8,False diff --git a/medical-imaging-demo/data/studies.csv b/medical-imaging-demo/data/studies.csv new file mode 100644 index 0000000..9dd92e8 --- /dev/null +++ b/medical-imaging-demo/data/studies.csv @@ -0,0 +1,9 @@ +study_id,patient_id,patient_name,age,gender,view_position,finding_labels,study_date,accession,image_file,referrer +ST0001,PT1001,Mark White,45,M,PA,No Finding,2026-06-15,ACC515886,xray_01.png,Dr. Smith +ST0002,PT1002,Robert Jones,67,F,PA,Cardiomegaly,2026-06-15,ACC382218,xray_02.png,Dr. Baker +ST0003,PT1003,Matthew Nelson,72,M,AP,Pleural Effusion|Cardiomegaly,2026-06-15,ACC381137,xray_03.png,Dr. Williams +ST0004,PT1004,Daniel Allen,58,F,PA,Pneumonia|Consolidation,2026-06-15,ACC526207,xray_04.png,Dr. Baker +ST0005,PT1005,Charles Hall,81,M,AP,Atelectasis,2026-06-15,ACC802856,xray_05.png,Dr. King +ST0006,PT1006,Nancy Wilson,63,F,PA,Nodule,2026-06-15,ACC224291,xray_06.png,Dr. King +ST0007,PT1007,Jessica Harris,34,M,AP,Pneumothorax,2026-06-15,ACC124300,xray_07.png,Dr. Wilson +ST0008,PT1008,Anthony Allen,69,F,PA,Mass,2026-06-15,ACC206818,xray_08.png,Dr. Harris diff --git a/medical-imaging-demo/data/vitals.csv b/medical-imaging-demo/data/vitals.csv new file mode 100644 index 0000000..c6a7082 --- /dev/null +++ b/medical-imaging-demo/data/vitals.csv @@ -0,0 +1,2305 @@ +patient_id,timestamp,HR,SpO2,Temp,SysBP,DiaBP,RR +PT1001,2026-06-14 00:00:00,70.7,98.9,37.4,119.6,76.7,13.5 +PT1001,2026-06-14 00:15:00,70.2,98.6,37.1,120.6,74.6,13.2 +PT1001,2026-06-14 00:30:00,72.8,98.5,37.2,119.7,75.7,12.7 +PT1001,2026-06-14 00:45:00,74.3,98.4,37.0,121.7,76.1,12.4 +PT1001,2026-06-14 01:00:00,73.8,98.4,36.4,122.1,77.0,12.6 +PT1001,2026-06-14 01:15:00,73.7,98.0,37.1,121.5,76.8,13.0 +PT1001,2026-06-14 01:30:00,74.0,98.2,37.1,124.0,76.7,13.1 +PT1001,2026-06-14 01:45:00,73.3,98.0,37.5,119.4,75.0,12.4 +PT1001,2026-06-14 02:00:00,73.5,98.0,37.2,118.0,75.1,12.0 +PT1001,2026-06-14 02:15:00,73.8,97.8,36.9,116.2,76.5,12.0 +PT1001,2026-06-14 02:30:00,73.4,97.5,37.8,116.1,77.8,12.0 +PT1001,2026-06-14 02:45:00,73.9,97.6,36.5,114.3,77.4,11.7 +PT1001,2026-06-14 03:00:00,75.0,97.4,37.0,112.7,77.7,11.9 +PT1001,2026-06-14 03:15:00,75.0,97.6,36.7,112.0,78.2,11.2 +PT1001,2026-06-14 03:30:00,75.7,97.3,36.9,112.5,78.0,11.1 +PT1001,2026-06-14 03:45:00,76.8,97.8,36.7,113.1,78.4,10.8 +PT1001,2026-06-14 04:00:00,76.7,97.5,36.8,109.6,79.7,11.1 +PT1001,2026-06-14 04:15:00,77.0,97.8,37.5,110.0,77.9,11.0 +PT1001,2026-06-14 04:30:00,77.3,97.9,37.2,110.6,76.6,10.8 +PT1001,2026-06-14 04:45:00,78.2,98.2,36.8,108.9,77.2,11.3 +PT1001,2026-06-14 05:00:00,80.0,98.6,37.3,114.2,77.6,11.4 +PT1001,2026-06-14 05:15:00,80.9,98.9,36.8,115.7,77.4,11.8 +PT1001,2026-06-14 05:30:00,80.9,99.3,37.2,113.2,76.4,12.1 +PT1001,2026-06-14 05:45:00,79.8,99.2,37.6,110.9,77.9,12.0 +PT1001,2026-06-14 06:00:00,79.8,99.1,37.9,110.3,77.5,12.1 +PT1001,2026-06-14 06:15:00,79.4,99.0,37.2,110.4,79.1,11.5 +PT1001,2026-06-14 06:30:00,78.4,99.2,37.2,109.4,75.7,11.6 +PT1001,2026-06-14 06:45:00,77.6,99.0,36.8,106.8,76.8,12.0 +PT1001,2026-06-14 07:00:00,77.0,99.0,37.2,111.3,77.7,11.6 +PT1001,2026-06-14 07:15:00,75.3,99.2,36.9,114.7,80.2,11.9 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22:15:00,86.7,98.8,37.3,116.7,121.6,19.1 +PT1008,2026-06-16 22:30:00,87.5,98.6,37.1,118.1,121.4,19.1 +PT1008,2026-06-16 22:45:00,90.0,98.4,36.9,120.4,123.6,19.4 +PT1008,2026-06-16 23:00:00,92.0,98.3,37.3,121.8,123.7,19.3 +PT1008,2026-06-16 23:15:00,94.2,98.3,36.7,125.8,123.5,19.3 +PT1008,2026-06-16 23:30:00,93.5,98.2,37.0,125.1,122.0,19.0 +PT1008,2026-06-16 23:45:00,94.9,97.9,37.3,121.0,119.4,18.7 diff --git a/medical-imaging-demo/pages/__init__.py b/medical-imaging-demo/pages/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/medical-imaging-demo/pages/cohort.py b/medical-imaging-demo/pages/cohort.py new file mode 100644 index 0000000..d8ee78f --- /dev/null +++ b/medical-imaging-demo/pages/cohort.py @@ -0,0 +1,214 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify +import numpy as np + +from components.charts import (create_crossfilter_scatter, create_diagnosis_donut, + create_age_sex_chart, create_risk_strat_chart, + create_vitals_chart) +from components.tables import create_patient_table +from utils.data_loader import get_cohort, get_vitals, df_patients + +df_cohort = get_cohort() + +VITALS_ALL = ["HR", "SpO2", "Temp", "SysBP", "DiaBP", "RR"] +PATIENT_OPTIONS = [ + {"value": row["patient_id"], "label": f"{row['patient_id']} — {row['name']}"} + for _, row in df_patients.head(8).iterrows() +] +_default_patient = PATIENT_OPTIONS[0]["value"] +_df_vitals0 = get_vitals(_default_patient, "24h") + +_cf1 = create_crossfilter_scatter(df_cohort, "age", "bmi") +_cf2 = create_crossfilter_scatter(df_cohort, "systolic_bp","ldl") +_cf3 = create_crossfilter_scatter(df_cohort, "hba1c", "egfr") + +SCATTER_CONFIG = { + "displayModeBar": True, + "modeBarButtonsToRemove": [ + "zoom2d", "pan2d", "zoomIn2d", "zoomOut2d", + "autoScale2d", "toImage", "hoverClosestCartesian", + "hoverCompareCartesian", "toggleSpikelines", + ], + "displaylogo": False, +} + +crossfilter_view = html.Div([ + dmc.Alert( + "Lasso or box-select points on any chart — the selection propagates across all three plots.", + color="navy", variant="light", + icon=DashIconify(icon="tabler:filter"), + mb="md", + ), + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dcc.Graph(id="cf-scatter1", figure=_cf1, + config=SCATTER_CONFIG, + style={"height": "320px"}), + p=0, radius="md", withBorder=True, + style={"overflow": "hidden"}, + ), + ], span={"base": 12, "md": 4}), + dmc.GridCol([ + dmc.Paper( + dcc.Graph(id="cf-scatter2", figure=_cf2, + config=SCATTER_CONFIG, + style={"height": "320px"}), + p=0, radius="md", withBorder=True, + style={"overflow": "hidden"}, + ), + ], span={"base": 12, "md": 4}), + dmc.GridCol([ + dmc.Paper( + dcc.Graph(id="cf-scatter3", figure=_cf3, + config=SCATTER_CONFIG, + style={"height": "320px"}), + p=0, radius="md", withBorder=True, + style={"overflow": "hidden"}, + ), + ], span={"base": 12, "md": 4}), + ], gutter="md"), + + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Cohort Summary", fw=600, size="lg"), + dmc.Divider(), + dmc.SimpleGrid(id="cf-summary-grid", cols=3, spacing="sm"), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 4}), + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Filtered Patients", fw=600, size="lg"), + html.Div(id="cf-patient-table"), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 8}), + ], gutter="md", mt="md"), + + # ── Vital Signs Trend (per-patient) ────────────────────────────────────── + dmc.Divider(mt="xl", mb="md"), + dmc.Group([ + DashIconify(icon="tabler:activity-heartbeat", width=20, color="#1e3a8a"), + dmc.Text("Vital Signs Trend", fw=600, size="lg"), + dmc.Text("per selected patient", c="dimmed", size="sm"), + ], gap=8, align="center", mb="md"), + dmc.Paper( + dmc.Group([ + dmc.Group([ + dmc.Text("Patient", size="xs", fw=500, c="dimmed"), + dmc.Select( + id="cohort-vitals-patient", + data=PATIENT_OPTIONS, + value=_default_patient, + w=260, size="xs", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Period", size="xs", fw=500, c="dimmed"), + dmc.SegmentedControl( + id="cohort-vitals-period", + data=["6h", "12h", "24h", "48h", "72h"], + value="24h", size="xs", color="navy", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Vitals", size="xs", fw=500, c="dimmed"), + dmc.MultiSelect( + id="cohort-vitals-select", + data=[{"value": v, "label": v} for v in VITALS_ALL], + value=["HR", "SpO2"], + w=260, size="xs", clearable=True, + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Display", size="xs", fw=500, c="dimmed"), + dmc.Switch(id="cohort-vitals-ref-toggle", label="Reference bands", + checked=True, size="xs", color="navy"), + dmc.Select( + id="cohort-vitals-ma", + data=[{"value": "none", "label": "No smoothing"}, + {"value": "20", "label": "20-pt MA"}, + {"value": "50", "label": "50-pt MA"}], + value="none", w=130, size="xs", + ), + ], gap=8), + ], gap="md", align="center"), + p="sm", radius="md", withBorder=True, mb="md", + ), + dmc.Paper( + dcc.Graph( + id="cohort-vitals-trend-chart", + figure=create_vitals_chart(_df_vitals0, ["HR", "SpO2"]), + config={"displayModeBar": False}, + style={"height": "420px"}, + ), + p="md", radius="md", withBorder=True, + ), +], id="crossfilter-view") + + +# ── Combined Demographics & Risk view ──────────────────────────────────────── +overview_view = html.Div([ + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dcc.Graph(id="demo-donut", + figure=create_diagnosis_donut(df_cohort), + config={"displayModeBar": False}, + style={"height": "380px"}), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 6}), + dmc.GridCol([ + dmc.Paper( + dcc.Graph(id="demo-agesex", + figure=create_age_sex_chart(df_cohort), + config={"displayModeBar": False}, + style={"height": "380px"}), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 6}), + ], gutter="md"), + dmc.Paper( + dcc.Graph(id="risk-strat-chart", + figure=create_risk_strat_chart(df_cohort), + config={"displayModeBar": False}, + style={"height": "420px"}), + p="md", radius="md", withBorder=True, mt="md", + ), +], id="overview-view", style={"display": "none"}) + + +layout = dmc.Box( + dmc.Stack([ + dmc.Group([ + dmc.Stack([ + dmc.Title("Cohort Explorer", order=2), + dmc.Text("200-patient biomarker cohort — linked crossfilter brushing", + c="dimmed"), + ], gap=4), + dmc.SegmentedControl( + id="cohort-view", + data=[ + {"value": "crossfilter", "label": "Crossfilter"}, + {"value": "overview", "label": "Demographics & Risk"}, + ], + value="crossfilter", color="navy", size="sm", radius="md", + ), + ], justify="space-between", mb="lg"), + + crossfilter_view, + overview_view, + ], gap="md"), + p="md", +) diff --git a/medical-imaging-demo/pages/dashboard.py b/medical-imaging-demo/pages/dashboard.py new file mode 100644 index 0000000..b1f75c7 --- /dev/null +++ b/medical-imaging-demo/pages/dashboard.py @@ -0,0 +1,286 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify + +from components.charts import create_admissions_chart, create_ecg_sparkline +from components.kpi_cards import create_kpi_card, create_risk_row +from utils.data_loader import get_census_metrics, get_risk_overview, get_admissions_data + +metrics = get_census_metrics() +risk = get_risk_overview() +adm_df = get_admissions_data() + +# ── 5 hardcoded ICU patients that the websocket callback streams ────────────── +ICU_PATIENTS = [ + {"id": "PT1001", "name": "J. Smith", "dx": "Sepsis"}, + {"id": "PT1002", "name": "M. Johnson", "dx": "Heart Failure"}, + {"id": "PT1003", "name": "R. Williams", "dx": "COPD Exacerbation"}, + {"id": "PT1004", "name": "P. Brown", "dx": "Hypertensive Crisis"}, + {"id": "PT1005", "name": "J. Garcia", "dx": "Pneumonia"}, +] + +# ── Alert thresholds ────────────────────────────────────────────────────────── +ICU_BASE = { + "PT1001": {"hr": 72, "spo2": 98.5, "sbp": 118, "dbp": 76, "rr": 14}, + "PT1002": {"hr": 92, "spo2": 96.8, "sbp": 148, "dbp": 90, "rr": 18}, + "PT1003": {"hr": 88, "spo2": 93.5, "sbp": 108, "dbp": 68, "rr": 21}, + "PT1004": {"hr": 78, "spo2": 99.1, "sbp": 168, "dbp": 97, "rr": 16}, + "PT1005": {"hr": 66, "spo2": 98.9, "sbp": 125, "dbp": 80, "rr": 13}, +} + + +def _vital_badge(value_str: str, pid: str, vital: str) -> html.Span: + return html.Span(value_str, id=f"live-{vital}-{pid}", + style={"fontFamily": "monospace", "fontWeight": 700}) + + +def _icu_row(p: dict) -> dmc.Paper: + pid = p["id"] + base = ICU_BASE[pid] + return dmc.Paper( + dmc.Group([ + dmc.Stack([ + dmc.Text(p["name"], size="sm", fw=600), + dmc.Text(p["dx"], size="xs", c="dimmed"), + ], gap=2, w=120), + dmc.Divider(orientation="vertical"), + dmc.Stack([ + dmc.Text("HR", size="xs", c="dimmed"), + _vital_badge(str(base["hr"]), pid, "hr"), + dmc.Text("bpm", size="xs", c="dimmed"), + ], gap=1, align="center"), + dmc.Stack([ + dmc.Text("SpO₂", size="xs", c="dimmed"), + _vital_badge(f"{base['spo2']}%", pid, "spo2"), + ], gap=1, align="center"), + dmc.Stack([ + dmc.Text("BP", size="xs", c="dimmed"), + _vital_badge(f"{base['sbp']}/{base['dbp']}", pid, "bp"), + dmc.Text("mmHg", size="xs", c="dimmed"), + ], gap=1, align="center"), + dmc.Stack([ + dmc.Text("RR", size="xs", c="dimmed"), + _vital_badge(str(base["rr"]), pid, "rr"), + dmc.Text("/min", size="xs", c="dimmed"), + ], gap=1, align="center"), + ], gap="lg", align="center"), + p="xs", + radius="sm", + withBorder=True, + style={"backgroundColor": "rgba(0,0,0,0.01)"}, + ) + + +layout = dmc.Stack([ + # ── Header ──────────────────────────────────────────────────────────────── + dmc.Group([ + dmc.Stack([ + dmc.Title("Clinical Dashboard", order=2), + dmc.Text("Real-time census, ICU vitals, and risk overview", c="dimmed"), + ], gap=4), + dmc.Group([ + dmc.SegmentedControl( + id="dashboard-period", + data=[{"value": v, "label": v} + for v in ["7d","14d","30d"]], + value="30d", + size="sm", + ), + dmc.Select( + id="dashboard-dept", + data=[{"value": "All", "label": "All Departments"}] + + [{"value": d, "label": d} for d in + ["Cardiology","Pulmonology","Neurology", + "General Medicine","Surgery","Nephrology","Oncology"]], + value="All", + w=200, + size="sm", + ), + ], gap="sm"), + ], justify="space-between", mb="lg"), + + # ── KPI Cards ───────────────────────────────────────────────────────────── + dmc.SimpleGrid([ + create_kpi_card("kpi-total", "Total Patients", + str(metrics["total_patients"]), + icon="tabler:users"), + create_kpi_card("kpi-icu", "ICU Occupancy", + f"{metrics['icu_occupancy']:.1f}%", + trend="25 beds", + trend_positive=True, + icon="tabler:activity"), + create_kpi_card("kpi-los", "Avg Length of Stay", + f"{metrics['avg_los']} days", + icon="tabler:clock"), + create_kpi_card("kpi-alerts", "Critical Alerts", + str(metrics["critical_alerts"]), + trend="Risk score > 70", + trend_positive=False, + icon="tabler:alert-triangle", + alert_color="red"), + ], cols={"base": 1, "sm": 2, "lg": 4}, spacing="md"), + + # ── Main Row: Live Vitals + Admissions chart ─────────────────────────────── + dmc.Grid([ + # Live ICU vitals panel + dmc.GridCol([ + dcc.Store(id="live-streaming", data=True), + dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Group([ + dmc.Text("Live ICU Monitor", fw=600, size="lg"), + html.Div( + style={ + "width": 8, "height": 8, + "borderRadius": "50%", + "backgroundColor": "#22c55e", + "animation": "pulse 1.5s ease-in-out infinite", + }, + id="live-indicator", + ), + dmc.Badge("LIVE", color="green", size="sm", variant="light"), + ], gap="xs"), + dmc.Switch(id="icu-live-toggle", label="Stream", + checked=True, size="sm"), + ], justify="space-between"), + dmc.Divider(), + + dmc.Stack([_icu_row(p) for p in ICU_PATIENTS], gap="xs"), + + dmc.Divider(), + dmc.Group([ + dmc.Text("ECG — ", size="xs", c="dimmed"), + dmc.Select( + id="ecg-patient-select", + data=[{"value": p["id"], "label": p["name"]} + for p in ICU_PATIENTS], + value="PT1001", + size="xs", w=150, + ), + ], gap=4), + dcc.Graph( + id="ecg-sparkline-chart", + figure=create_ecg_sparkline([72], "PT1001"), + config={"displayModeBar": False}, + style={"height": "100px"}, + ), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 6}), + + # Admissions chart + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dcc.Graph( + id="admissions-chart", + figure=create_admissions_chart(adm_df), + config={"displayModeBar": False}, + style={"height": "360px"}, + ), + ]), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 6}), + ], gutter="md"), + + # ── Bottom Row: Risk Overview + Quick Stats ──────────────────────────────── + dmc.Grid([ + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Population Risk Overview", fw=600, size="lg"), + dmc.Text("Average risk scores across all admitted patients", + size="xs", c="dimmed"), + dmc.Divider(my="sm"), + dmc.Stack([ + create_risk_row("risk-sepsis", "Sepsis Risk", + f"{risk['sepsis']:.1f}%", + risk["sepsis"], "red"), + create_risk_row("risk-fall", "Fall Risk", + f"{risk['fall']:.1f}%", + risk["fall"], "orange"), + create_risk_row("risk-readmit", "Readmission", + f"{risk['readmit']:.1f}%", + risk["readmit"], "yellow"), + create_risk_row("risk-deterioration", "Deterioration", + f"{risk['deterioration']:.1f}%", + risk["deterioration"], "grape"), + ], gap="md", mt="sm"), + ], gap="sm"), + p="md", radius="md", withBorder=True, h="100%", + ), + ], span={"base": 12, "md": 4}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Department Snapshot", fw=600, size="lg"), + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text(dept, size="xs", c="dimmed", fw=600), + dmc.Text(str(count), size="lg", fw=700), + dmc.Text("admitted today", size="xs", c="dimmed"), + ], gap=4), + p="sm", radius="sm", withBorder=True, + ) + for dept, count in [ + ("Cardiology", 12), ("Pulmonology", 8), + ("Neurology", 6), ("Surgery", 10), + ("Nephrology", 5), ("Oncology", 4), + ] + ], cols=2, spacing="sm"), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + ], span={"base": 12, "md": 4}), + + dmc.GridCol([ + dmc.Paper( + dmc.Stack([ + dmc.Text("System Status", fw=600, size="lg"), + dmc.Stack([ + dmc.Group([ + DashIconify(icon="tabler:circle-filled", + width=10, color="#22c55e"), + dmc.Text("EMR System", size="sm"), + dmc.Text("Online", size="sm", c="teal", fw=500, + style={"marginLeft": "auto"}), + ]), + dmc.Group([ + DashIconify(icon="tabler:circle-filled", + width=10, color="#22c55e"), + dmc.Text("PACS Imaging", size="sm"), + dmc.Text("Online", size="sm", c="teal", fw=500, + style={"marginLeft": "auto"}), + ]), + dmc.Group([ + DashIconify(icon="tabler:circle-filled", + width=10, color="#22c55e"), + dmc.Text("Lab Interface", size="sm"), + dmc.Text("Online", size="sm", c="teal", fw=500, + style={"marginLeft": "auto"}), + ]), + dmc.Group([ + DashIconify(icon="tabler:circle-filled", + width=10, color="#f59e0b"), + dmc.Text("ICU Monitoring", size="sm"), + dmc.Text("Degraded", size="sm", c="yellow", fw=500, + style={"marginLeft": "auto"}), + ]), + ], gap="md", mt="sm"), + dmc.Divider(my="sm"), + dmc.Alert( + "All patient data is synthetic and for demonstration only.", + color="blue", variant="light", icon=DashIconify(icon="tabler:info-circle"), + ), + ], gap="sm"), + p="md", radius="md", withBorder=True, h="100%", + ), + ], span={"base": 12, "md": 4}), + ], gutter="md"), + +], gap="md") diff --git a/medical-imaging-demo/pages/imaging.py b/medical-imaging-demo/pages/imaging.py new file mode 100644 index 0000000..da76c9e --- /dev/null +++ b/medical-imaging-demo/pages/imaging.py @@ -0,0 +1,557 @@ +import dash_mantine_components as dmc +from dash import dcc, html +from dash_iconify import DashIconify + +from components.imaging import (load_xray_b64, create_xray_figure, XRAY_DIR, + SEVERITY_COLORS, severity_color, newshape_for) +from components.charts import create_ecg_sparkline +from utils.data_loader import (get_studies, get_patient, get_labs, + get_vitals, get_vitals_stats) + +df_studies = get_studies() +STUDIES = df_studies.to_dict("records") + +# ── Palette (scoped to this page) — light cream + deep navy ───────────────────── +BG_DEEP = "#f4f3ef" # off-white, faint cream wash (page backdrop — minimal cream) +BG_SURFACE = "#fcfcfb" # clean near-white (panels / Paper) +BG_INSET = "#eef0f2" # very light cool grey (cards, toolbars, insets) +BORDER = "#e1e3e7" # neutral grey border +TEXT_HI = "#1e2433" # charcoal (primary text) +TEXT_DIM = "#6b7280" # cool slate (secondary text) +ACCENT = "#1e3a8a" # deep navy highlight +ACCENT_DK = "#172554" # deepest navy (top accent borders) + +# Custom Mantine "navy" color ramp (shade 9 = ACCENT) +NAVY_RAMP = ["#eef2fb", "#d9e1f4", "#b3c2e8", "#8aa1db", "#6886d0", + "#5274c9", "#456bc6", "#37539e", "#27407f", "#1e3a8a"] + +# Active study-card tint (replaces the old cyan glow) +CARD_ACTIVE_BG = "#e6eaf5" # pale navy +CARD_ACTIVE_SHADOW = "0 0 0 1px rgba(30,58,138,0.2)" +# Neutral light grey behind the X-ray canvas (light viewport) +VIEWPORT_BG = "#e7e9ec" +# DICOM corner overlays render ON TOP of the (inherently dark) X-ray image, +# so they keep light text regardless of the light chrome around them. +OVERLAY_HI = "#eef2f8" # near-white +OVERLAY_DIM = "#aab4c5" # light slate +OVERLAY_ACCENT = "#7da2e8" # light navy (legible on the dark X-ray) + + +# Key labs → one-line clinical interpretation when flagged abnormal +_LAB_INTERPRETATION = { + "WBC": "infection / pneumonia", + "Troponin": "cardiac injury", + "Lactate": "sepsis / hypoperfusion", + "Creatinine": "renal function", + "BUN": "renal function", + "Hemoglobin": "anemia / bleeding", + "Glucose": "glycemic control", + "Potassium": "electrolyte imbalance", + "Sodium": "electrolyte imbalance", +} + + +def _risk_badge(patient: dict): + """Coloured risk badge from a patient's risk_score.""" + score = patient.get("risk_score") + if score is None: + return None + color = "red" if score > 70 else "yellow" if score > 40 else "teal" + return dmc.Badge(f"Risk {score:.0f}", color=color, variant="light", size="sm") + + +# ── Premium PACS chrome: patient banner, image overlays, status bar ─────────── +_MONO = "ui-monospace, SFMono-Regular, Menlo, monospace" + +_DRAW_LABELS = { + "drawrect": "Rectangle", "drawline": "Line", + "drawcircle": "Circle", "drawopenpath": "Freehand", +} + + +def _meta_chip(label: str, value, mono: bool = False): + """A compact label/value pair for the banner identity row.""" + return dmc.Group([ + dmc.Text(label, size="9px", c=TEXT_DIM, tt="uppercase", + style={"letterSpacing": "0.6px", "fontWeight": 700}), + dmc.Text(str(value), size="xs", fw=600, c=TEXT_HI, + style={"fontFamily": _MONO} if mono else None), + ], gap=5, wrap="nowrap") + + +def _vitals_tile(pid: str): + """HR/SpO₂ readout + HR sparkline for the banner.""" + df_vit = get_vitals(pid, "24h") + if df_vit.empty: + return dmc.Text("No vitals", size="xs", c=TEXT_DIM) + hr = get_vitals_stats(pid, "HR", "24h") + spo2 = get_vitals_stats(pid, "SpO2", "24h") + spark = create_ecg_sparkline(df_vit["HR"].tolist()) + return dmc.Group([ + dmc.Stack([ + dmc.Text(f"HR {hr.get('current', '—')}", size="sm", fw=700, c="#22c55e"), + dmc.Text(f"SpO₂ {spo2.get('current', '—')}%", size="xs", fw=600, c=ACCENT), + ], gap=2), + html.Div( + dcc.Graph(figure=spark, config={"displayModeBar": False}, + style={"height": "34px", "width": "96px"}), + style={"width": "96px"}, + ), + ], gap=8, wrap="nowrap", align="center") + + +def _lab_chip(test: str, value, unit: str, flag: str): + up = flag == "H" + color = "#dc2626" if up else ACCENT + return dmc.Tooltip( + label=f"{test} {value:.1f} {unit} — {_LAB_INTERPRETATION.get(test, 'abnormal')}", + withArrow=True, position="bottom", color="dark", + children=dmc.Group([ + dmc.Text(test, size="xs", fw=700, c=TEXT_HI), + DashIconify(icon="tabler:arrow-up" if up else "tabler:arrow-down", + width=13, color=color), + ], gap=3, wrap="nowrap", + style={"padding": "3px 9px", "borderRadius": "6px", + "backgroundColor": BG_INSET, + "border": f"1px solid {color}55"}), + ) + + +def _patient_banner_content(study: dict): + """Full-width PACS banner: identity (left) + clinical signal (right).""" + if not study: + return dmc.Text("No study selected.", size="sm", c=TEXT_DIM) + pid = study.get("patient_id") + patient = get_patient(pid) if pid else {} + + # Identity ──────────────────────────────────────────────────────────────── + identity = dmc.Stack([ + dmc.Group([ + dmc.Text(study.get("patient_name", "—"), size="lg", fw=700, c=TEXT_HI), + (_risk_badge(patient) or html.Span()), + (dmc.Text(patient.get("diagnosis", ""), size="xs", c=TEXT_DIM) + if patient.get("diagnosis") else html.Span()), + ], gap=10, align="center", wrap="nowrap"), + dmc.Group([ + _meta_chip("MRN", pid or "—", mono=True), + _meta_chip("Age/Sex", f"{study.get('age', '—')}/{study.get('gender', '—')}"), + _meta_chip("Modality", f"CXR {study.get('view_position', '')}".strip()), + _meta_chip("Acc", study.get("accession", "—"), mono=True), + _meta_chip("Date", study.get("study_date", "—"), mono=True), + ], gap=18, wrap="nowrap"), + ], gap=8) + + # Clinical signal ─────────────────────────────────────────────────────────── + df_labs = get_labs(pid) if pid else None + abnormal = (df_labs[df_labs["flag"] != "N"] + if df_labs is not None and not df_labs.empty else None) + if abnormal is None or abnormal.empty: + lab_block = dmc.Text("Labs WNL", size="xs", c="#22c55e", fw=600) + else: + lab_block = dmc.Group( + [_lab_chip(r["test"], r["value"], r["unit"], r["flag"]) + for _, r in abnormal.iterrows()], + gap=8, wrap="nowrap", + ) + + clinical = dmc.Group([ + dmc.Stack([ + dmc.Text("ABNORMAL LABS", size="9px", c=TEXT_DIM, tt="uppercase", + style={"letterSpacing": "0.6px", "fontWeight": 700}), + lab_block, + ], gap=4), + dmc.Divider(orientation="vertical", color=BORDER), + dmc.Stack([ + dmc.Text("VITALS · 24H", size="9px", c=TEXT_DIM, tt="uppercase", + style={"letterSpacing": "0.6px", "fontWeight": 700}), + _vitals_tile(pid) if pid else dmc.Text("—", size="xs", c=TEXT_DIM), + ], gap=4), + ], gap=16, wrap="nowrap", align="center") + + return dmc.Group( + [identity, clinical], + justify="space-between", align="center", wrap="nowrap", + style={"flex": 1}, + ) + + +def _corner(children, vertical: str, horizontal: str, align: str): + # A subtle dark "scrim" chip keeps the light DICOM text legible whether it + # falls over the dark X-ray or the light letterbox margins. + style = {"position": "absolute", vertical: "10px", horizontal: "12px", + "pointerEvents": "none", "textAlign": align, + "fontFamily": _MONO, "fontSize": "10px", "lineHeight": "1.5", + "color": OVERLAY_DIM, + "backgroundColor": "rgba(15,23,42,0.62)", + "padding": "5px 9px", "borderRadius": "6px", + "backdropFilter": "blur(1.5px)"} + return html.Div(children, style=style) + + +def _image_overlays(study: dict, window, level, invert: bool): + """DICOM-style text overlaid in the four corners of the image.""" + study = study or {} + tl = [html.Div(study.get("patient_name", "—"), + style={"color": OVERLAY_HI, "fontWeight": 700}), + html.Div(f"MRN {study.get('patient_id', '—')}"), + html.Div(f"{study.get('age', '—')}/{study.get('gender', '—')}")] + tr = [html.Div(f"ACC {study.get('accession', '—')}", + style={"color": OVERLAY_HI, "fontWeight": 700}), + html.Div(f"{study.get('view_position', '—')} · {study.get('study_date', '—')}")] + bl = [html.Div(f"W: {int(window or 0)} L: {int(level or 0)}", + style={"color": OVERLAY_ACCENT}), + html.Div(f"Invert: {'ON' if invert else 'OFF'}")] + br = [html.Div("CXR", style={"color": OVERLAY_HI, "fontWeight": 700}), + html.Div("General Hospital"), + html.Div(study.get("referrer", ""))] + return [ + _corner(tl, "top", "left", "left"), + _corner(tr, "top", "right", "right"), + _corner(bl, "bottom", "left", "left"), + _corner(br, "bottom", "right", "right"), + ] + + +def _status_bar(draw_mode, window, level, invert: bool): + """Thin professional readout strip under the image.""" + def seg(label, value, accent=False): + return dmc.Group([ + dmc.Text(label, size="10px", c=TEXT_DIM, tt="uppercase", + style={"letterSpacing": "0.5px"}), + dmc.Text(str(value), size="11px", fw=600, + c=ACCENT if accent else TEXT_HI, + style={"fontFamily": _MONO}), + ], gap=5, wrap="nowrap") + + return dmc.Group([ + dmc.Group([ + DashIconify(icon="tabler:pencil", width=13, color=TEXT_DIM), + seg("Tool", _DRAW_LABELS.get(draw_mode, "Rectangle")), + ], gap=6, wrap="nowrap"), + seg("Window", int(window or 0), accent=True), + seg("Level", int(level or 0), accent=True), + seg("Invert", "On" if invert else "Off"), + seg("Matrix", "512×512"), + ], gap=20, wrap="nowrap", + style={"padding": "6px 14px", "backgroundColor": BG_DEEP, + "borderTop": f"1px solid {BORDER}"}) + + +def _study_card(study: dict) -> dmc.UnstyledButton: + sid = study["study_id"] + name = study.get("patient_name", sid) + age_sex = f"{study.get('age', '—')} / {study.get('gender', '—')}" + view = study.get("view_position", "") + finding = study.get("finding_labels", "").split("|")[0] + is_normal = finding.lower() in ("no finding", "") + badge_color = "gray" if is_normal else "navy" + + return dmc.UnstyledButton( + dmc.Stack([ + dmc.Group([ + dmc.Text(sid, size="xs", c=TEXT_DIM, ff="monospace", fw=600), + dmc.Badge(view, size="xs", variant="outline", + color="gray", radius="sm"), + ], justify="space-between", wrap="nowrap"), + dmc.Text(name, size="sm", fw=600, c=TEXT_HI, truncate=True), + dmc.Group([ + dmc.Text(age_sex, size="xs", c=TEXT_DIM), + dmc.Badge(finding or "—", size="xs", variant="light", + color=badge_color, radius="sm"), + ], justify="space-between", wrap="nowrap"), + ], gap=6), + id={"type": "study-thumb", "index": sid}, + className="study-card", + style={ + "width": "100%", + "padding": "10px 12px", + "backgroundColor": BG_INSET, + "border": f"1px solid {BORDER}", + "borderRadius": "8px", + "textAlign": "left", + "transition": "border-color 0.15s ease, background-color 0.15s ease", + }, + ) + + +# ── Defaults ─────────────────────────────────────────────────────────────────── +_default = STUDIES[0] +_img_path = XRAY_DIR / _default["image_file"] +_img_b64 = load_xray_b64(_img_path) +_fig0 = create_xray_figure(_img_b64) +_fig0.update_layout(newshape=newshape_for("Medium")) # match default severity + +DRAW_TOOLS = [ + {"value": "drawrect", "label": "Rect"}, + {"value": "drawline", "label": "Line"}, + {"value": "drawcircle", "label": "Circle"}, + {"value": "drawopenpath", "label": "Path"}, +] + +FINDING_OPTIONS = [{"value": v, "label": v} for v in [ + "Nodule", "Mass", "Effusion", "Cardiomegaly", "Pneumothorax", + "Atelectasis", "Consolidation", "Pneumonia", "Infiltration", + "Fibrosis", "Fracture", "Foreign Body", "Unspecified", +]] + + +_panel_style = { + "backgroundColor": BG_SURFACE, + "border": f"1px solid {BORDER}", +} + +_section_label = lambda text: dmc.Text( + text, size="xs", fw=700, c=TEXT_DIM, tt="uppercase", + style={"letterSpacing": "0.6px"}, +) + + +# ── Studies panel ────────────────────────────────────────────────────────────── +studies_panel = dmc.Paper( + dmc.Stack([ + dmc.Group([ + _section_label("Studies"), + dmc.Badge(str(len(STUDIES)), size="sm", color="navy", + variant="light"), + ], justify="space-between"), + dmc.Divider(color=BORDER), + dmc.ScrollArea( + dmc.Stack([_study_card(s) for s in STUDIES], gap="xs"), + type="auto", offsetScrollbars=True, + style={"height": "calc(100vh - 200px)"}, + ), + ], gap="sm"), + p="md", radius="md", + style={**_panel_style, "height": "100%"}, +) + + +# ── Viewport toolbar ─────────────────────────────────────────────────────────── +def _slider_control(label, slider_id, mn, mx, val, step=5): + return dmc.Group([ + dmc.Text(label, size="xs", fw=600, c=TEXT_DIM, w=52), + html.Div( + dmc.Slider( + id=slider_id, min=mn, max=mx, step=step, value=val, + color="navy", size="sm", + label=None, + showLabelOnHover=False, + marks=[], + ), + style={"width": "150px"}, + ), + ], gap=8, wrap="nowrap") + + +viewport_toolbar = dmc.Group([ + dmc.Group([ + _slider_control("Window", "window-slider", 30, 255, 220), + _slider_control("Level", "level-slider", 10, 245, 128), + dmc.Switch( + id="invert-toggle", + label="Invert", + checked=False, + size="sm", color="navy", + styles={"label": {"color": TEXT_HI, "fontSize": "12px"}}, + ), + ], gap="lg", wrap="nowrap"), + dmc.Group([ + dmc.SegmentedControl( + id="draw-mode-select", + data=DRAW_TOOLS, + value="drawrect", + size="xs", color="navy", + styles={ + "root": {"backgroundColor": BG_INSET, + "border": f"1px solid {BORDER}"}, + }, + ), + dmc.Button( + "Reset", + id="reset-annotations-btn", + size="xs", variant="subtle", color="gray", + leftSection=DashIconify(icon="tabler:rotate-clockwise", width=14), + ), + ], gap="sm", wrap="nowrap"), +], justify="space-between", align="center", wrap="wrap", + style={"padding": "10px 14px", + "backgroundColor": BG_INSET, + "borderBottom": f"1px solid {BORDER}", + "borderRadius": "8px 8px 0 0"}) + + +def _severity_dot(level: str): + return dmc.Group([ + html.Div(style={"width": 8, "height": 8, "borderRadius": "50%", + "backgroundColor": SEVERITY_COLORS[level]}), + dmc.Text(level, size="xs", c=TEXT_DIM), + ], gap=4, wrap="nowrap") + + +def _pending_tag(finding="Nodule", severity="Medium", note=""): + """Live badge showing how the next-drawn shape will be tagged.""" + children = [ + DashIconify(icon="tabler:pencil-plus", width=13, + color=severity_color(severity)), + dmc.Text("Next:", size="xs", c=TEXT_DIM), + dmc.Text(f"{finding or 'Unspecified'} · {severity or 'Medium'}", + size="xs", fw=700, c=severity_color(severity)), + ] + if note: + children.append(dmc.Text(f"“{note}”", size="xs", c=TEXT_DIM, + style={"fontStyle": "italic"}, truncate=True)) + return dmc.Group(children, gap=6, wrap="nowrap") + + +severity_legend = dmc.Group( + [dmc.Text("Severity", size="xs", fw=600, c=TEXT_DIM)] + + [_severity_dot(l) for l in ("Low", "Medium", "High")], + gap=10, wrap="nowrap", +) + + +annotation_bar = dmc.Stack([ + dmc.Group([ + dmc.Select( + id="finding-label-select", + data=FINDING_OPTIONS, + value="Nodule", + placeholder="Finding", + size="xs", w=150, + leftSection=DashIconify(icon="tabler:tag", width=14), + ), + dmc.Select( + id="severity-select", + data=[{"value": v, "label": v} for v in ["Low", "Medium", "High"]], + value="Medium", size="xs", w=100, + ), + dmc.TextInput( + id="annotation-note", + placeholder="Note (optional)", + size="xs", + style={"flex": 1, "minWidth": "80px"}, + leftSection=DashIconify(icon="tabler:note", width=14), + ), + ], gap="sm", wrap="wrap"), + dmc.Group([ + html.Div(id="pending-annotation", children=_pending_tag()), + severity_legend, + ], justify="space-between", align="center", wrap="nowrap"), +], gap=8, + style={"padding": "10px 14px", + "backgroundColor": BG_INSET, + "borderTop": f"1px solid {BORDER}", + "borderRadius": "0 0 8px 8px"}) + + +viewport_panel = dmc.Paper( + dmc.Stack([ + dcc.Store(id="xray-annotations", data=[]), + dcc.Store(id="annotations-store", data={}), # {study_id: [annotations]} + dcc.Store(id="current-study-id", data=_default["study_id"]), + viewport_toolbar, + html.Div([ + dcc.Graph( + id="xray-graph", + figure=_fig0, + config={ + "displayModeBar": "hover", + "modeBarButtonsToAdd": [ + "drawrect", "drawline", + "drawcircle", "drawopenpath", "eraseshape", + ], + "modeBarButtonsToRemove": ["toImage"], + "scrollZoom": True, + "displaylogo": False, + }, + style={"height": "520px", + "backgroundColor": VIEWPORT_BG}, + ), + html.Div( + id="image-overlays", + children=_image_overlays(_default, 220, 128, False), + style={"position": "absolute", "inset": 0, + "pointerEvents": "none"}, + ), + ], style={"position": "relative", "backgroundColor": VIEWPORT_BG}), + html.Div(id="image-status-bar", + children=_status_bar("drawrect", 220, 128, False)), + annotation_bar, + ], gap=0), + p=0, radius="md", + style={**_panel_style, "overflow": "hidden"}, +) + + +# ── Right detail panel — Findings (primary focus) ───────────────────────────── +detail_panel = dmc.Paper( + dmc.Stack([ + dmc.Group([ + dmc.Group([ + DashIconify(icon="tabler:list-search", width=16, color=ACCENT), + _section_label("Findings"), + ], gap=8), + dmc.Badge(id="findings-count", children="0", + color="navy", variant="light", size="sm"), + ], justify="space-between"), + dmc.Divider(color=BORDER), + html.Div( + id="findings-table-container", + children=dmc.Text( + "No annotations yet. Draw on the X-ray to add findings.", + size="sm", c=TEXT_DIM, ta="center", py="md", + ), + ), + ], gap="sm"), + p="md", radius="md", + style={**_panel_style, "height": "100%", + "borderTop": f"2px solid {ACCENT_DK}"}, +) + + +# ── Full layout (scoped dark provider, full-bleed) ──────────────────────────── +layout = dmc.MantineProvider( + forceColorScheme="light", + theme={ + "primaryColor": "navy", + "primaryShade": 9, + "colors": {"navy": NAVY_RAMP}, + "fontFamily": "Inter, -apple-system, BlinkMacSystemFont, sans-serif", + "components": { + "Paper": {"defaultProps": {"shadow": "none"}}, + }, + }, + children=dmc.Box( + dmc.Stack([ + dcc.Download(id="download-radiology-pdf"), + + # ── PACS patient banner ────────────────────────────────────────── + dmc.Paper( + dmc.Group([ + html.Div(id="patient-banner", + children=_patient_banner_content(_default), + style={"flex": 1, "minWidth": 0}), + dmc.Button( + "Export", + id="export-radiology-btn", + size="xs", variant="subtle", color="navy", + leftSection=DashIconify(icon="tabler:file-type-pdf", width=15), + ), + ], gap="md", wrap="nowrap", align="center"), + px="lg", py="sm", radius="md", + style={**_panel_style, "borderTop": f"2px solid {ACCENT_DK}"}, + ), + + dmc.Grid([ + dmc.GridCol(studies_panel, span={"base": 12, "md": 2}), + dmc.GridCol(viewport_panel, span={"base": 12, "md": 6}), + dmc.GridCol(detail_panel, span={"base": 12, "md": 4}), + ], gutter="md", align="stretch"), + ], gap="md", p="md"), + style={ + "backgroundColor": BG_DEEP, + "minHeight": "calc(100vh - 64px)", + "color": TEXT_HI, + }, + ), +) diff --git a/medical-imaging-demo/pages/vitals.py b/medical-imaging-demo/pages/vitals.py new file mode 100644 index 0000000..ec5d337 --- /dev/null +++ b/medical-imaging-demo/pages/vitals.py @@ -0,0 +1,176 @@ +import dash_mantine_components as dmc +from dash import dcc +from dash_iconify import DashIconify + +from components.charts import create_vitals_chart, create_vitals_variability +from utils.data_loader import get_vitals, df_patients + +VITALS_ALL = ["HR", "SpO2", "Temp", "SysBP", "DiaBP", "RR"] +UNITS = {"HR": "bpm", "SpO2": "%", "Temp": "°C", + "SysBP": "mmHg", "DiaBP": "mmHg", "RR": "/min"} + +PATIENT_OPTIONS = [ + {"value": row["patient_id"], "label": f"{row['patient_id']} — {row['name']}"} + for _, row in df_patients.head(8).iterrows() +] + +DEFAULT_PATIENT = PATIENT_OPTIONS[0]["value"] +DEFAULT_VITALS = ["HR", "SpO2"] +DEFAULT_PERIOD = "24h" + +_df0 = get_vitals(DEFAULT_PATIENT, DEFAULT_PERIOD) + +layout = dmc.Stack([ + # ── Page Header ──────────────────────────────────────────────────────────── + dmc.Group([ + dmc.Stack([ + dmc.Title("Patient Vitals", order=2), + dmc.Text("Vital-sign trends with normal-range reference bands", + c="dimmed"), + ], gap=4), + ], justify="space-between", mb="md"), + + # ── Filter bar ───────────────────────────────────────────────────────────── + dmc.Paper( + dmc.Group([ + dmc.Group([ + dmc.Text("Patient", size="xs", fw=500, c="dimmed"), + dmc.Select( + id="vitals-patient-select", + data=PATIENT_OPTIONS, + value=DEFAULT_PATIENT, + w=260, size="xs", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Period", size="xs", fw=500, c="dimmed"), + dmc.SegmentedControl( + id="vitals-period", + data=["6h", "12h", "24h", "48h", "72h"], + value=DEFAULT_PERIOD, size="xs", + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Vitals", size="xs", fw=500, c="dimmed"), + dmc.MultiSelect( + id="vitals-select", + data=[{"value": v, "label": v} for v in VITALS_ALL], + value=DEFAULT_VITALS, + w=260, size="xs", clearable=True, + ), + ], gap=6), + dmc.Divider(orientation="vertical", style={"alignSelf": "stretch"}), + dmc.Group([ + dmc.Text("Display", size="xs", fw=500, c="dimmed"), + dmc.Switch(id="vitals-ref-toggle", label="Reference bands", + checked=True, size="xs"), + dmc.Select( + id="vitals-ma-select", + data=[{"value": "none", "label": "No smoothing"}, + {"value": "20", "label": "20-pt MA"}, + {"value": "50", "label": "50-pt MA"}], + value="none", w=130, size="xs", + ), + ], gap=8), + ], gap="md", align="center"), + p="sm", radius="md", withBorder=True, + ), + + # ── Stat Cards ───────────────────────────────────────────────────────────── + dmc.SimpleGrid([ + dmc.Paper( + dmc.Stack([ + dmc.Text("Current HR", size="sm", c="dimmed"), + dmc.Text( + f"{_df0['HR'].iloc[-1]:.0f} bpm" if not _df0.empty else "—", + size="xl", fw=700, id="stat-current-hr", + ), + dmc.Text("Latest reading", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="md", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Period High / Low", size="sm", c="dimmed"), + dmc.Group([ + dmc.Text( + f"{_df0['HR'].max():.0f}" if not _df0.empty else "—", + size="xl", fw=700, c="red", id="stat-high-hr", + ), + dmc.Text("/", size="xl", c="dimmed"), + dmc.Text( + f"{_df0['HR'].min():.0f}" if not _df0.empty else "—", + size="xl", fw=700, c="blue", id="stat-low-hr", + ), + ], gap=4), + dmc.Text("bpm", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="md", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Current SpO₂", size="sm", c="dimmed"), + dmc.Text( + f"{_df0['SpO2'].iloc[-1]:.1f}%" if not _df0.empty else "—", + size="xl", fw=700, id="stat-current-spo2", + ), + dmc.Text("Latest reading", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="md", withBorder=True, + ), + dmc.Paper( + dmc.Stack([ + dmc.Text("Abnormal Readings", size="sm", c="dimmed"), + dmc.Text("—", size="xl", fw=700, c="red", id="stat-abnormal"), + dmc.Text("Outside reference range", size="xs", c="dimmed"), + ], gap=4), + p="md", radius="md", withBorder=True, + ), + ], cols={"base": 2, "md": 4}, spacing="md"), + + # ── Charts with tabs ─────────────────────────────────────────────────────── + dmc.Paper( + dmc.Stack([ + dmc.Tabs([ + dmc.TabsList([ + dmc.TabsTab("Trend", value="trend"), + dmc.TabsTab("Variability", value="var"), + ]), + dmc.TabsPanel( + dcc.Graph( + id="vitals-trend-chart", + figure=create_vitals_chart(_df0, DEFAULT_VITALS), + config={"displayModeBar": False}, + style={"height": "400px"}, + ), + value="trend", pt="md", + ), + dmc.TabsPanel( + dcc.Graph( + id="vitals-var-chart", + figure=create_vitals_variability(_df0, DEFAULT_VITALS), + config={"displayModeBar": False}, + style={"height": "400px"}, + ), + value="var", pt="md", + ), + ], value="trend"), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + + # ── Vitals Summary Table ─────────────────────────────────────────────────── + dmc.Paper( + dmc.Stack([ + dmc.Text("Vitals Summary", fw=600, size="lg"), + dmc.Text("Min / Mean / Max for the selected period", + size="xs", c="dimmed"), + dmc.Divider(my="xs"), + dmc.SimpleGrid(id="vitals-summary-grid", cols=3, spacing="sm"), + ], gap="sm"), + p="md", radius="md", withBorder=True, + ), + +], gap="md") diff --git a/medical-imaging-demo/requirements.txt b/medical-imaging-demo/requirements.txt new file mode 100644 index 0000000..54a2459 --- /dev/null +++ b/medical-imaging-demo/requirements.txt @@ -0,0 +1,13 @@ +dash[fastapi]==4.2.0rc3 +dash-mantine-components>=0.14.0 +dash-iconify>=0.1.2 +pandas>=2.0.0 +plotly>=5.18.0 +numpy>=1.24.0 +uvicorn[standard] +reportlab>=4.0.0 +kaleido==0.2.1 +PyPDF2>=3.0.0 +Pillow>=10.0.0 +requests>=2.31.0 +scipy>=1.11.0 diff --git a/medical-imaging-demo/scripts/generate_data.py b/medical-imaging-demo/scripts/generate_data.py new file mode 100644 index 0000000..4c204e5 --- /dev/null +++ b/medical-imaging-demo/scripts/generate_data.py @@ -0,0 +1,216 @@ +"""Generate all synthetic clinical CSVs for the demo.""" +import numpy as np +import pandas as pd +from pathlib import Path +from datetime import datetime, timedelta + +np.random.seed(42) +ROOT = Path(__file__).parent.parent +DATA = ROOT / "data" +DATA.mkdir(exist_ok=True) + +# ── Names ──────────────────────────────────────────────────────────────────── +FIRST = ["James","Mary","Robert","Patricia","John","Jennifer","Michael","Linda", + "David","Barbara","William","Elizabeth","Richard","Susan","Joseph", + "Jessica","Thomas","Sarah","Charles","Karen","Christopher","Lisa", + "Daniel","Nancy","Matthew","Betty","Anthony","Margaret","Mark","Sandra"] +LAST = ["Smith","Johnson","Williams","Brown","Jones","Garcia","Miller","Davis", + "Wilson","Moore","Taylor","Anderson","Thomas","Jackson","White","Harris", + "Martin","Thompson","Young","Lewis","Walker","Hall","Allen","King", + "Wright","Scott","Green","Baker","Adams","Nelson"] + +DIAGNOSES = ["Pneumonia","Sepsis","COPD Exacerbation","Heart Failure","Acute MI", + "Stroke","Trauma","UTI","GI Bleed","Pulmonary Embolism", + "Hypertensive Crisis","Diabetic Ketoacidosis","Cellulitis", + "Atrial Fibrillation","Respiratory Failure"] +WARDS = ["ICU","MICU","CCU","Step-Down","General Med","ED Obs"] +DEPARTMENTS = ["Cardiology","Pulmonology","Neurology","General Medicine", + "Surgery","Nephrology","Oncology"] + +# ── Patient roster ──────────────────────────────────────────────────────────── +N = 60 +rows = [] +for i in range(N): + ward = np.random.choice(WARDS, p=[0.10,0.08,0.07,0.15,0.45,0.15]) + rows.append({ + "patient_id": f"PT{i+1001}", + "name": f"{np.random.choice(FIRST)} {np.random.choice(LAST)}", + "age": int(np.random.randint(22, 91)), + "gender": np.random.choice(["M","F"]), + "diagnosis": np.random.choice(DIAGNOSES), + "ward": ward, + "department": np.random.choice(DEPARTMENTS), + "admitted_date": (datetime(2026,6,1) + timedelta(days=int(np.random.randint(0,15)))).strftime("%Y-%m-%d"), + "los_days": int(np.random.randint(1,15)), + "risk_score": round(float(np.random.beta(2,5)*100), 1), + "sepsis_risk": round(float(np.random.beta(1.5,8)*100), 1), + "fall_risk": round(float(np.random.beta(2,6)*100), 1), + "readmit_risk": round(float(np.random.beta(2,5)*100), 1), + "deterioration_risk": round(float(np.random.beta(1.5,7)*100), 1), + "is_icu": ward in ("ICU","MICU","CCU"), + }) + +df_patients = pd.DataFrame(rows) +# Ensure first 5 are ICU patients for the live panel +for i in range(5): + df_patients.at[i, "ward"] = ["ICU","MICU","CCU","ICU","MICU"][i] + df_patients.at[i, "is_icu"] = True +df_patients.to_csv(DATA / "patients.csv", index=False) +print(f"patients.csv — {len(df_patients)} rows") + +# ── Vitals time series (72 h, 15-min intervals, 8 ICU patients) ─────────────── +ICU_BASES = [ + {"patient_id":"PT1001","base_hr":72,"base_spo2":98.5,"base_sbp":118,"base_dbp":76,"base_rr":14}, + {"patient_id":"PT1002","base_hr":92,"base_spo2":96.8,"base_sbp":148,"base_dbp":90,"base_rr":18}, + {"patient_id":"PT1003","base_hr":88,"base_spo2":93.5,"base_sbp":108,"base_dbp":68,"base_rr":21}, + {"patient_id":"PT1004","base_hr":78,"base_spo2":99.1,"base_sbp":168,"base_dbp":97,"base_rr":16}, + {"patient_id":"PT1005","base_hr":66,"base_spo2":98.9,"base_sbp":125,"base_dbp":80,"base_rr":13}, + {"patient_id":"PT1006","base_hr":95,"base_spo2":95.2,"base_sbp":135,"base_dbp":82,"base_rr":20}, + {"patient_id":"PT1007","base_hr":74,"base_spo2":97.8,"base_sbp":120,"base_dbp":75,"base_rr":15}, + {"patient_id":"PT1008","base_hr":82,"base_spo2":96.0,"base_sbp":142,"base_dbp":88,"base_rr":17}, +] + +base_time = datetime(2026, 6, 14, 0, 0, 0) +vitals_rows = [] +for p in ICU_BASES: + pid = p["patient_id"] + hr = float(p["base_hr"]) + spo = float(p["base_spo2"]) + sbp = float(p["base_sbp"]) + dbp = float(p["base_dbp"]) + rr = float(p["base_rr"]) + for i in range(72 * 4): + t = base_time + timedelta(minutes=15*i) + hour = t.hour + # Gentle circadian drift + hr = float(np.clip(hr + np.random.normal(-0.05*(hr-p["base_hr"])*0.1, 1.2), 40, 200)) + spo = float(np.clip(spo + np.random.normal(-0.05*(spo-p["base_spo2"])*0.1, 0.25), 85, 100)) + sbp = float(np.clip(sbp + np.random.normal(0, 2.0), 70, 220)) + dbp = float(np.clip(dbp + np.random.normal(0, 1.5), 40, 130)) + rr = float(np.clip(rr + np.random.normal(0, 0.4), 8, 40)) + vitals_rows.append({ + "patient_id": pid, + "timestamp": t.strftime("%Y-%m-%d %H:%M:%S"), + "HR": round(hr, 1), + "SpO2": round(spo, 1), + "Temp": round(np.random.normal(37.1, 0.3), 1), + "SysBP": round(sbp, 1), + "DiaBP": round(dbp, 1), + "RR": round(rr, 1), + }) + +df_vitals = pd.DataFrame(vitals_rows) +df_vitals.to_csv(DATA / "vitals.csv", index=False) +print(f"vitals.csv — {len(df_vitals)} rows") + +# ── Cohort biomarkers (200 patients) ───────────────────────────────────────── +COH_DIAG = ["Type 2 Diabetes","Hypertension","COPD","Heart Failure","CKD", + "Obesity","CAD","Asthma","Hyperlipidemia","Atrial Fibrillation"] +cohort = [] +for i in range(200): + age = int(np.random.randint(20, 85)) + bmi = float(np.clip(np.random.normal(28, 6), 16, 55)) + sbp = float(np.clip(np.random.normal(130, 22), 80, 220)) + ldl = float(np.clip(np.random.normal(115, 38), 40, 260)) + hba1c= float(np.clip(np.random.normal(6.8, 1.6), 4.5, 14)) + egfr = float(np.clip(np.random.normal(68, 26), 5, 130)) + + score = (int(sbp>160)*2 + int(ldl>160) + int(hba1c>8)*2 + + int(egfr<45)*2 + int(bmi>35)) + risk = "High" if score >= 4 else "Medium" if score >= 2 else "Low" + cohort.append({ + "patient_id": f"CO{i+2001}", + "age": age, + "gender": np.random.choice(["M","F"]), + "bmi": round(bmi, 1), + "systolic_bp": round(sbp, 0), + "ldl": round(ldl, 1), + "hba1c": round(hba1c, 1), + "egfr": round(egfr, 1), + "diagnosis": np.random.choice(COH_DIAG), + "risk_level": risk, + }) + +df_cohort = pd.DataFrame(cohort) +df_cohort.to_csv(DATA / "cohort.csv", index=False) +print(f"cohort.csv — {len(df_cohort)} rows") + +# ── Admissions time series (30 days) ───────────────────────────────────────── +BASE_COUNT = {"Cardiology":12,"Pulmonology":8,"Neurology":6, + "General Medicine":20,"Surgery":10,"Nephrology":5,"Oncology":4} +adm_rows = [] +for d in range(30): + dt = datetime(2026,5,17) + timedelta(days=d) + for dept, base in BASE_COUNT.items(): + # Weekend dip + weekend = dt.weekday() >= 5 + count = max(0, int(np.random.normal(base * (0.75 if weekend else 1.0), 2))) + adm_rows.append({"date": dt.strftime("%Y-%m-%d"), "department": dept, "admissions": count}) + +pd.DataFrame(adm_rows).to_csv(DATA / "admissions.csv", index=False) +print(f"admissions.csv — {len(adm_rows)} rows") + +# ── Labs (20 patients) ──────────────────────────────────────────────────────── +LAB_TESTS = { + "WBC": (4.5, 11.0, "10³/µL"), + "Hemoglobin": (12.0, 17.5, "g/dL"), + "Platelets": (150, 400, "10³/µL"), + "Sodium": (136, 145, "mEq/L"), + "Potassium": (3.5, 5.0, "mEq/L"), + "Creatinine": (0.7, 1.3, "mg/dL"), + "BUN": (7, 25, "mg/dL"), + "Glucose": (70, 100, "mg/dL"), + "Lactate": (0.5, 2.0, "mmol/L"), + "Troponin": (0.0, 0.04, "ng/mL"), +} +lab_rows = [] +for _, pat in df_patients.head(20).iterrows(): + for test, (lo, hi, unit) in LAB_TESTS.items(): + mid = (lo + hi) / 2 + val = round(float(np.clip(np.random.normal(mid, (hi-lo)*0.3), lo*0.5, hi*2)), 3) + flag = "H" if val > hi else "L" if val < lo else "N" + lab_rows.append({ + "patient_id": pat["patient_id"], + "date": "2026-06-15", + "test": test, + "value": val, + "unit": unit, + "reference_low": lo, + "reference_high": hi, + "flag": flag, + }) + +pd.DataFrame(lab_rows).to_csv(DATA / "labs.csv", index=False) +print(f"labs.csv — {len(lab_rows)} rows") + +# ── Imaging studies metadata ────────────────────────────────────────────────── +STUDIES = [ + {"study_id":"ST0001","findings":"No Finding", "age":45,"gender":"M","view":"PA"}, + {"study_id":"ST0002","findings":"Cardiomegaly", "age":67,"gender":"F","view":"PA"}, + {"study_id":"ST0003","findings":"Pleural Effusion|Cardiomegaly","age":72,"gender":"M","view":"AP"}, + {"study_id":"ST0004","findings":"Pneumonia|Consolidation", "age":58,"gender":"F","view":"PA"}, + {"study_id":"ST0005","findings":"Atelectasis", "age":81,"gender":"M","view":"AP"}, + {"study_id":"ST0006","findings":"Nodule", "age":63,"gender":"F","view":"PA"}, + {"study_id":"ST0007","findings":"Pneumothorax", "age":34,"gender":"M","view":"AP"}, + {"study_id":"ST0008","findings":"Mass", "age":69,"gender":"F","view":"PA"}, +] +pat_names = df_patients["name"].tolist() +study_rows = [] +for i, s in enumerate(STUDIES): + study_rows.append({ + "study_id": s["study_id"], + "patient_id": f"PT{i+1001}", + "patient_name": pat_names[i], + "age": s["age"], + "gender": s["gender"], + "view_position":s["view"], + "finding_labels":s["findings"], + "study_date": "2026-06-15", + "accession": f"ACC{np.random.randint(100000,999999)}", + "image_file": f"xray_{i+1:02d}.png", + "referrer": "Dr. " + np.random.choice(LAST), + }) + +pd.DataFrame(study_rows).to_csv(DATA / "studies.csv", index=False) +print(f"studies.csv — {len(study_rows)} rows") +print("\nAll data generated.") diff --git a/medical-imaging-demo/scripts/generate_xrays.py b/medical-imaging-demo/scripts/generate_xrays.py new file mode 100644 index 0000000..16fd90a --- /dev/null +++ b/medical-imaging-demo/scripts/generate_xrays.py @@ -0,0 +1,164 @@ +"""Generate synthetic chest X-ray-like grayscale PNG images for the demo.""" +import numpy as np +from PIL import Image, ImageFilter +from pathlib import Path + +ROOT = Path(__file__).parent.parent +OUTDIR = ROOT / "assets" / "xrays" +OUTDIR.mkdir(parents=True, exist_ok=True) + +STUDIES = [ + ("xray_01.png", [], 42), + ("xray_02.png", ["Cardiomegaly"], 43), + ("xray_03.png", ["Pleural Effusion","Cardiomegaly"], 44), + ("xray_04.png", ["Pneumonia","Consolidation"], 45), + ("xray_05.png", ["Atelectasis"], 46), + ("xray_06.png", ["Nodule"], 47), + ("xray_07.png", ["Pneumothorax"], 48), + ("xray_08.png", ["Mass"], 49), +] + + +def generate_xray(width: int = 512, height: int = 512, + findings: list = None, seed: int = 42) -> Image.Image: + """Return a PIL grayscale image resembling a chest X-ray PA view.""" + np.random.seed(seed) + if findings is None: + findings = [] + + W, H = width, height + cx, cy = W / 2, H / 2 + img = np.zeros((H, W), dtype=np.float32) + + yy, xx = np.mgrid[0:H, 0:W] + + # ── Chest outline ───────────────────────────────────────────────────────── + chest = ((xx - cx) ** 2 / (cx * 0.88) ** 2 + + (yy - cy * 0.96) ** 2 / (cy * 0.92) ** 2) < 1 + img[chest] = 35 + + # ── Lung fields (darker — air) ──────────────────────────────────────────── + lL = ((xx - cx * 0.57) ** 2 / (cx * 0.26) ** 2 + + (yy - cy * 0.84) ** 2 / (cy * 0.36) ** 2) < 1 + rL = ((xx - cx * 1.43) ** 2 / (cx * 0.26) ** 2 + + (yy - cy * 0.84) ** 2 / (cy * 0.36) ** 2) < 1 + img[lL] = 14 + img[rL] = 14 + + # ── Mediastinum / heart ─────────────────────────────────────────────────── + heart = ((xx - cx * 0.91) ** 2 / (cx * 0.19) ** 2 + + (yy - cy * 1.06) ** 2 / (cy * 0.22) ** 2) < 1 + img[heart] = 125 + + # ── Aortic knob ─────────────────────────────────────────────────────────── + aorta = ((xx - cx * 0.84) ** 2 + (yy - cy * 0.60) ** 2) < (W * 0.05) ** 2 + img[aorta] = 145 + + # ── Trachea ─────────────────────────────────────────────────────────────── + trachea = (np.abs(xx - cx) < W * 0.025) & (yy < cy * 0.58) + img[trachea] = 8 + + # ── Spine ───────────────────────────────────────────────────────────────── + spine = (np.abs(xx - cx) < W * 0.025) & (yy > cy * 0.38) & (yy < cy * 1.65) + img[spine] = np.maximum(img[spine], 195) + + # ── Clavicles ───────────────────────────────────────────────────────────── + for x in range(int(cx * 0.20), int(cx)): + cy_clav = int(cy * 0.27 - cy * 0.09 * (x - cx * 0.20) / (cx * 0.80)) + if 0 <= cy_clav < H: + img[max(0, cy_clav - 2):cy_clav + 3, x] = 210 + for x in range(int(cx), int(cx * 1.80)): + cy_clav = int(cy * 0.27 + cy * 0.09 * (x - cx) / (cx * 0.80)) + if 0 <= cy_clav < H: + img[max(0, cy_clav - 2):cy_clav + 3, x] = 210 + + # ── Ribs ────────────────────────────────────────────────────────────────── + for i in range(12): + rib_y0 = cy * 0.24 + i * cy * 0.12 + rw = 2 + for side, x0, x1, xref, sign in [ + ("L", int(cx*0.22), int(cx*0.88), cx*0.22, 1), + ("R", int(cx*1.12), int(cx*1.78), cx*1.78, -1), + ]: + span = abs(x1 - x0) + for x in range(x0, x1): + arc = int(rib_y0 + cy * 0.07 * np.sin(np.pi * abs(x - xref) / span)) + if 0 <= arc - rw and arc + rw < H: + img[arc - rw:arc + rw + 1, x] = np.maximum( + img[arc - rw:arc + rw + 1, x], 195) + + # ── Diaphragm ───────────────────────────────────────────────────────────── + for x in range(int(cx * 0.22), int(cx * 0.90)): + d = int(cy * 1.36 - cy * 0.10 * np.sin(np.pi * (x - cx*0.22) / (cx*0.68))) + if 0 <= d < H: + img[d:min(H, d+3), x] = 190 + for x in range(int(cx * 1.10), int(cx * 1.78)): + d = int(cy * 1.42 - cy * 0.09 * np.sin(np.pi * (cx*1.78 - x) / (cx*0.68))) + if 0 <= d < H: + img[d:min(H, d+3), x] = 190 + + # ── Pulmonary vascular markings ─────────────────────────────────────────── + for lung_mask, x_base in [(lL, cx * 0.40), (rL, cx * 1.30)]: + for _ in range(18): + vx = int(np.random.uniform(x_base * 0.8, x_base * 1.2)) + vy = int(np.random.uniform(cy * 0.28, cy * 0.65)) + ln = int(np.random.uniform(25, 90)) + ang = np.random.uniform(-0.5, 0.5) + intens = float(np.random.uniform(28, 65)) + for j in range(ln): + px_ = int(vx + j * np.sin(ang)) + py_ = int(vy + j * np.cos(ang)) + if (0 <= px_ < W and 0 <= py_ < H and lung_mask[py_, px_]): + img[py_, px_] = min(255, img[py_, px_] + intens * (1 - j / ln)) + + # ── Findings ────────────────────────────────────────────────────────────── + for f in findings: + if f == "Cardiomegaly": + hc = ((xx - cx * 0.88) ** 2 / (cx * 0.28) ** 2 + + (yy - cy * 1.03) ** 2 / (cy * 0.26) ** 2) < 1 + img[hc] = np.maximum(img[hc], 118) + + elif f == "Pleural Effusion": + eff = (yy > cy * 1.22) & rL + img[eff] = 155 + + elif f == "Pneumothorax": + ptx = (xx < cx * 0.38) & lL + img[ptx] = 5 + line_x = int(cx * 0.39) + img[int(cy*0.22):int(cy*0.88), line_x:line_x+3] = 205 + + elif f in ("Nodule", "Mass"): + sz = 11 if f == "Nodule" else 32 + nx, ny = int(cx * 1.50), int(cy * 0.57) + nod = ((xx - nx) ** 2 + (yy - ny) ** 2) < sz ** 2 + img[nod] = 170 + + elif f == "Atelectasis": + atel_y0 = int(cy * 1.20) + atel_y1 = int(cy * 1.27) + img[atel_y0:atel_y1, int(cx*0.35):int(cx*0.82)] = 145 + + elif f in ("Pneumonia", "Consolidation"): + con = ((xx - cx * 1.42) ** 2 / (cx * 0.24) ** 2 + + (yy - cy * 1.12) ** 2 / (cy * 0.20) ** 2) < 1 + img[con] = np.where(img[con] < 132, 132, img[con]) + + elif f == "Infiltration": + inf = ((xx - cx * 0.60) ** 2 / (cx * 0.20) ** 2 + + (yy - cy * 1.05) ** 2 / (cy * 0.18) ** 2) < 1 + img[inf] = np.where(img[inf] < 120, 120, img[inf]) + + # ── Noise + blur ────────────────────────────────────────────────────────── + img = np.clip(img + np.random.normal(0, 5.5, img.shape), 0, 255).astype(np.uint8) + pil = Image.fromarray(img, mode="L").filter(ImageFilter.GaussianBlur(radius=1.2)) + return pil + + +if __name__ == "__main__": + for fname, findings, seed in STUDIES: + out = OUTDIR / fname + img = generate_xray(512, 512, findings=findings, seed=seed) + img.save(out) + print(f" {fname} findings={findings or ['No Finding']}") + print(f"\n{len(STUDIES)} X-ray images written to {OUTDIR}") diff --git a/medical-imaging-demo/utils/__init__.py b/medical-imaging-demo/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/medical-imaging-demo/utils/data_loader.py b/medical-imaging-demo/utils/data_loader.py new file mode 100644 index 0000000..93993af --- /dev/null +++ b/medical-imaging-demo/utils/data_loader.py @@ -0,0 +1,104 @@ +import pandas as pd +import pathlib + +ROOT = pathlib.Path(__file__).parent.parent +DATA_PATH = ROOT / "data" + +def _csv(name: str) -> pd.DataFrame: + return pd.read_csv(DATA_PATH / name) + +# Cached loads +df_patients = _csv("patients.csv") +df_vitals = _csv("vitals.csv") +df_cohort = _csv("cohort.csv") +df_admissions = _csv("admissions.csv") +df_labs = _csv("labs.csv") +df_studies = _csv("studies.csv") + + +# ── Census / dashboard metrics ──────────────────────────────────────────────── +def get_census_metrics() -> dict: + total = len(df_patients) + icu_total = df_patients["is_icu"].sum() + icu_cap = 25 # beds + avg_los = round(float(df_patients["los_days"].mean()), 1) + critical = int((df_patients["risk_score"] > 70).sum()) + return { + "total_patients": total, + "icu_occupancy": round(icu_total / icu_cap * 100, 1), + "avg_los": avg_los, + "critical_alerts":critical, + } + +def get_risk_overview() -> dict: + return { + "sepsis": round(float(df_patients["sepsis_risk"].mean()), 1), + "fall": round(float(df_patients["fall_risk"].mean()), 1), + "readmit": round(float(df_patients["readmit_risk"].mean()), 1), + "deterioration":round(float(df_patients["deterioration_risk"].mean()), 1), + } + + +# ── Admissions ──────────────────────────────────────────────────────────────── +def get_admissions_data(department: str = "All", period: str = "30d") -> pd.DataFrame: + df = df_admissions.copy() + df["date"] = pd.to_datetime(df["date"]) + days = {"7d": 7, "14d": 14, "30d": 30}.get(period, 30) + df = df[df["date"] >= df["date"].max() - pd.Timedelta(days=days-1)] + if department != "All": + df = df[df["department"] == department] + return df + + +# ── Vitals ──────────────────────────────────────────────────────────────────── +PERIOD_HOURS = {"6h": 6, "12h": 12, "24h": 24, "48h": 48, "72h": 72} + +def get_vitals(patient_id: str, period: str = "24h") -> pd.DataFrame: + df = df_vitals[df_vitals["patient_id"] == patient_id].copy() + df["timestamp"] = pd.to_datetime(df["timestamp"]) + df = df.sort_values("timestamp") + hours = PERIOD_HOURS.get(period, 24) + cutoff = df["timestamp"].max() - pd.Timedelta(hours=hours) + return df[df["timestamp"] >= cutoff].reset_index(drop=True) + +def get_vitals_stats(patient_id: str, vital: str, period: str = "24h") -> dict: + df = get_vitals(patient_id, period) + if df.empty or vital not in df.columns: + return {} + col = df[vital] + return { + "current": round(float(col.iloc[-1]), 1), + "min": round(float(col.min()), 1), + "max": round(float(col.max()), 1), + "mean": round(float(col.mean()), 1), + } + + +# ── Cohort ──────────────────────────────────────────────────────────────────── +def get_cohort() -> pd.DataFrame: + return df_cohort.copy() + + +# ── Labs ────────────────────────────────────────────────────────────────────── +def get_labs(patient_id: str) -> pd.DataFrame: + return df_labs[df_labs["patient_id"] == patient_id].copy() + + +# ── Studies ─────────────────────────────────────────────────────────────────── +def get_studies() -> pd.DataFrame: + return df_studies.copy() + +def get_study(study_id: str) -> dict: + row = df_studies[df_studies["study_id"] == study_id] + if row.empty: + return {} + return row.iloc[0].to_dict() + + +# ── Patient helpers ─────────────────────────────────────────────────────────── +def get_patient(patient_id: str) -> dict: + row = df_patients[df_patients["patient_id"] == patient_id] + return row.iloc[0].to_dict() if not row.empty else {} + +def get_icu_patients() -> pd.DataFrame: + return df_patients[df_patients["is_icu"]].head(5).copy() diff --git a/medical-imaging-demo/utils/pdf_export.py b/medical-imaging-demo/utils/pdf_export.py new file mode 100644 index 0000000..9e99c10 --- /dev/null +++ b/medical-imaging-demo/utils/pdf_export.py @@ -0,0 +1,214 @@ +import copy +import io +from datetime import datetime + +import plotly.io as pio +from PIL import Image as PILImage, ImageDraw, ImageFont +from reportlab.lib import colors +from reportlab.lib.pagesizes import A4, landscape, portrait +from reportlab.lib.units import inch +from reportlab.lib.utils import ImageReader +from reportlab.pdfgen import canvas as rl_canvas +from PyPDF2 import PdfWriter, PdfReader + + +def figure_to_image_bytes(figure, width: int = 1100, height: int = 650) -> bytes: + try: + fig = copy.deepcopy(figure) + if isinstance(fig, dict): + fig.setdefault("layout", {}) + fig["layout"]["paper_bgcolor"] = "white" + fig["layout"]["plot_bgcolor"] = "white" + return pio.to_image(fig, format="png", width=width, height=height) + except Exception as e: + img = PILImage.new("RGB", (width, height), color=(220, 220, 220)) + ImageDraw.Draw(img).text((20, height // 2), f"Render error: {e}", fill="black") + buf = io.BytesIO() + img.save(buf, format="PNG") + return buf.getvalue() + + +def create_radiology_report( + xray_figure, + findings: list, + patient_info: dict, + study_info: dict, +) -> bytes: + """ + Build a PDF radiology report with: + - Title page (patient + study info) + - Full-page annotated X-ray image + - Findings table + """ + port_w, port_h = portrait(A4) + land_w, land_h = landscape(A4) + + out = io.BytesIO() + writer = PdfWriter() + + # ── Title page ───────────────────────────────────────────────────────────── + tp = io.BytesIO() + cp = rl_canvas.Canvas(tp, pagesize=portrait(A4)) + + # Header band + cp.setFillColor(colors.HexColor("#0d9488")) + cp.rect(0, port_h - 2.2 * inch, port_w, 2.2 * inch, fill=1, stroke=0) + + cp.setFillColor(colors.white) + cp.setFont("Helvetica-Bold", 26) + cp.drawCentredString(port_w / 2, port_h - 1.0 * inch, "VitalSight Radiology Report") + cp.setFont("Helvetica", 13) + cp.drawCentredString(port_w / 2, port_h - 1.65 * inch, + f"Generated: {datetime.now().strftime('%B %d, %Y %H:%M')}") + + # Patient / study info table + info_y = port_h - 3.2 * inch + items = [ + ("Patient Name", patient_info.get("name", "—")), + ("Patient ID", patient_info.get("patient_id", "—")), + ("Age / Gender", f"{patient_info.get('age','—')} / {patient_info.get('gender','—')}"), + ("Study ID", study_info.get("study_id", "—")), + ("Accession", study_info.get("accession", "—")), + ("Study Date", study_info.get("study_date", "—")), + ("View", study_info.get("view_position", "—")), + ("Referring Physician", study_info.get("referrer", "—")), + ] + cp.setFont("Helvetica-Bold", 10) + cp.setFillColor(colors.HexColor("#1e293b")) + for label, value in items: + cp.setFont("Helvetica-Bold", 10) + cp.setFillColor(colors.HexColor("#475569")) + cp.drawString(1.0 * inch, info_y, f"{label}:") + cp.setFont("Helvetica", 10) + cp.setFillColor(colors.HexColor("#1e293b")) + cp.drawString(3.0 * inch, info_y, str(value)) + info_y -= 0.32 * inch + + # Disclaimer + cp.setFont("Helvetica-Oblique", 8) + cp.setFillColor(colors.HexColor("#94a3b8")) + cp.drawCentredString(port_w / 2, 0.6 * inch, + "SYNTHETIC DATA — FOR DEMONSTRATION PURPOSES ONLY") + cp.save() + tp.seek(0) + writer.add_page(PdfReader(tp).pages[0]) + + # ── Annotated X-ray page ─────────────────────────────────────────────────── + xr = io.BytesIO() + cl = rl_canvas.Canvas(xr, pagesize=landscape(A4)) + + cl.setFillColor(colors.HexColor("#0d9488")) + cl.setFont("Helvetica-Bold", 16) + cl.drawString(0.8 * inch, land_h - 0.7 * inch, "Imaging Study") + + xray_bytes = figure_to_image_bytes(xray_figure, width=1100, height=750) + reader = ImageReader(io.BytesIO(xray_bytes)) + img_w, img_h = 10 * inch, 6.8 * inch + x_off = (land_w - img_w) / 2 + y_off = (land_h - img_h) / 2 - 0.3 * inch + cl.drawImage(reader, x_off, y_off, width=img_w, height=img_h) + + cl.setFont("Helvetica", 7) + cl.setFillColor(colors.HexColor("#94a3b8")) + cl.drawCentredString(land_w / 2, 0.35 * inch, + "SYNTHETIC — NOT FOR CLINICAL USE") + cl.save() + xr.seek(0) + writer.add_page(PdfReader(xr).pages[0]) + + # ── Findings table page ──────────────────────────────────────────────────── + if findings: + ft = io.BytesIO() + fp = rl_canvas.Canvas(ft, pagesize=portrait(A4)) + + fp.setFillColor(colors.HexColor("#0d9488")) + fp.rect(0, port_h - 1.2 * inch, port_w, 1.2 * inch, fill=1, stroke=0) + fp.setFillColor(colors.white) + fp.setFont("Helvetica-Bold", 18) + fp.drawCentredString(port_w / 2, port_h - 0.75 * inch, "Findings") + + headers = ["#", "Finding", "Location (px)", "Type", "Severity", "Note"] + col_w = [0.3, 2.0, 2.2, 1.0, 1.0, 1.5] + col_x = [1.0 * inch] + for w in col_w[:-1]: + col_x.append(col_x[-1] + w * inch) + + row_y = port_h - 1.7 * inch + fp.setFont("Helvetica-Bold", 9) + fp.setFillColor(colors.HexColor("#1e293b")) + for i, h in enumerate(headers): + fp.drawString(col_x[i], row_y, h) + row_y -= 0.05 * inch + fp.setStrokeColor(colors.HexColor("#e2e8f0")) + fp.line(0.8 * inch, row_y, port_w - 0.8 * inch, row_y) + row_y -= 0.28 * inch + + fp.setFont("Helvetica", 9) + for idx, finding in enumerate(findings, 1): + if row_y < 1.5 * inch: + break + fp.setFillColor(colors.HexColor("#1e293b") if idx % 2 else colors.HexColor("#f8fafc")) + fp.rect(0.8*inch, row_y-0.05*inch, port_w-1.6*inch, 0.28*inch, fill=1, stroke=0) + fp.setFillColor(colors.HexColor("#1e293b")) + cells = [ + str(idx), + finding.get("label", "Unspecified"), + finding.get("location", "—"), + finding.get("shape_type", "rect"), + finding.get("severity", "—"), + finding.get("note", ""), + ] + for i, cell in enumerate(cells): + fp.drawString(col_x[i], row_y, str(cell)[:28]) + row_y -= 0.28 * inch + + fp.setFont("Helvetica-Oblique", 7) + fp.setFillColor(colors.HexColor("#94a3b8")) + fp.drawCentredString(port_w / 2, 0.5 * inch, "SYNTHETIC — NOT FOR CLINICAL USE") + fp.save() + ft.seek(0) + writer.add_page(PdfReader(ft).pages[0]) + + writer.write(out) + out.seek(0) + return out.getvalue() + + +def create_summary_pdf(figures: list, titles: list, report_title: str = "Clinical Report") -> bytes: + """Multi-figure PDF (for future use).""" + port_w, port_h = portrait(A4) + land_w, land_h = landscape(A4) + out = io.BytesIO() + writer = PdfWriter() + + tp = io.BytesIO() + cp = rl_canvas.Canvas(tp, pagesize=portrait(A4)) + cp.setFillColor(colors.HexColor("#0d9488")) + cp.rect(0, port_h - 2*inch, port_w, 2*inch, fill=1, stroke=0) + cp.setFillColor(colors.white) + cp.setFont("Helvetica-Bold", 26) + cp.drawCentredString(port_w/2, port_h - 1.1*inch, report_title) + cp.setFont("Helvetica", 12) + cp.drawCentredString(port_w/2, port_h - 1.7*inch, + datetime.now().strftime("%B %d, %Y")) + cp.save() + tp.seek(0) + writer.add_page(PdfReader(tp).pages[0]) + + for fig, title in zip(figures, titles): + pb = io.BytesIO() + cl = rl_canvas.Canvas(pb, pagesize=landscape(A4)) + cl.setFillColor(colors.HexColor("#0d9488")) + cl.setFont("Helvetica-Bold", 18) + cl.drawString(1*inch, land_h - 0.75*inch, title) + img_bytes = figure_to_image_bytes(fig) + reader = ImageReader(io.BytesIO(img_bytes)) + iw, ih = 10*inch, 6*inch + cl.drawImage(reader, (land_w-iw)/2, (land_h-ih)/2-0.4*inch, width=iw, height=ih) + cl.save() + pb.seek(0) + writer.add_page(PdfReader(pb).pages[0]) + + writer.write(out) + out.seek(0) + return out.getvalue()

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