👨💻 Modelling consultant
🧮 numbers 📊 actuarial
📈 viz, interactivity, transparency
Public
Edited
Sep 14, 2024
data = viz.data("data_0") //.filter((d) => d.sw != 5)
function stops(n, color) {
return _.range(0, n).map((d) => ({
offset: d / n,
color: !(d % 3) ? color : "transparent"
}));
}
function cashflows_spec_patch() {
return (spec) => {
//debugger
spec.legends[0].encode.symbols.update.shape = { value: "square" };
spec.legends[0].encode.symbols.update.stroke = null;
spec.legends[0].encode.symbols.update.opacity = { value: 1 };
//const grid = spec.signals.findIndex((d) => d.name == "grid_t_in");
spec.signals.push({ name: "panOffset", value: 0 });
spec.marks[0].marks[0].signals;
const a = spec.marks[0].marks[0].signals.findIndex(
(d) => d.name == "grid_t_in"
);
const b = spec.marks[0].marks[0].signals.findIndex(
(d) => d.name == "grid_translate_anchor"
);
const c = spec.marks[0].marks[0].signals.findIndex(
(d) => d.name == "grid_zoom_anchor"
);
const d = spec.scales.findIndex((d) => d.name == "concat_0_concat_0_x");
spec.scales[d].domainRaw.signal =
'grid["t_in"] ? [grid["t_in"][0]+panOffset,grid["t_in"][1]+panOffset] : null';
spec.marks[0].marks[0].signals[a].on[2] /*should paramaterise*/.update =
'zoomLinear([domain("concat_0_concat_0_x")[0]-panOffset,domain("concat_0_concat_0_x")[1]-panOffset], grid_zoom_anchor.x, grid_zoom_delta)';
spec.marks[0].marks[0].signals[b].on[0] /*should paramaterise*/.update =
'{x: x(unit), y: y(unit), extent_x: [domain("concat_0_concat_0_x")[0]-panOffset,domain("concat_0_concat_0_x")[1]-panOffset], extent_y: domain("concat_0_concat_0_y")}';
spec.marks[0].marks[0].signals[c].on[0] /*should paramaterise*/.update =
'{x: invert("concat_0_concat_0_x", x(unit))-panOffset, y: invert("concat_0_concat_0_y", y(unit))}';
/*spec.scales[s].domainRaw = {
signal:
'grid["t_in"] ? [grid["t_in"][0]+panOffset,grid["t_in"][1]+panOffset] : null'
};*/
/*spec.signals[grid].on = [
{
events: { signal: "panOffset" },
update:
"grid_t_in ? [grid_t_in[0]+panOffset, grid_t_in[1]+panOffset] : [x_domain[0]+panOffset,x_domain[1]+panOffset]"
}
];*/
//'{"t_in": grid_t_in ? [grid_t_in[0]+panOffset,grid_t_in[1]+panOffset] : null, "value": grid_value}'; //'{"t_in": [grid_t_in[0],grid_t_in[1]], "value": grid_value}';
return spec;
};
}
{
//viz.signal("grid", { t_in: [10], value: [10] }).run();
//viz.signal("grid_t_in", [10]);
//viz.signal("grid_value", [10]).run();
}
{
vizz.signal("grid_translate_anchor", {
x: 55.8125,
y: 12,
extent_x: [75, 150],
extent_y: [20, 40]
});
vizz.signal("grid_translate_delta", { x: x, y: 12 }).run();
}
viewof vizz = embed({
data: { url: "data/cars.json" },
params: [
{
name: "grid",
select: "interval",
bind: "scales"
}
],
mark: "circle",
encoding: {
x: {
field: "Horsepower",
type: "quantitative",
scale: { domain: [75, 150] }
},
y: {
field: "Miles_per_Gallon",
type: "quantitative",
scale: { domain: [20, 40] }
},
size: { field: "Cylinders", type: "quantitative" }
}
})
viz.getState({ data: (d) => false, signals: (d) => true })
/*viz
.setState(
[viz.getState({ data: (d) => false, signals: (d) => true })].map(
(state) => {
state.subcontext["0"].subcontext["0"].signals.grid_translate_anchor = {
x: 0,
y: 0,
extent_x: viz.signal("x_domain"),
extent_y: viz.signal("y_domain") //[0, 200]
//extent_y: [-premiums * 1.5, premiums * 1.5] // but I need dynamic values
};
state.subcontext["0"].subcontext["0"].signals.grid_translate_delta = {
x: viz.signal("x_diff") * x,
y: 0
};
return state;
}
)[0]
)
.run()*/
viz.signal("x_range")
viz.signal("x_one") // scale(x,1) pos of 1 on x scale in pixels (so the amount I want to pan by each time)
viz.signal("x_diff")
viz.getState().subcontext["0"].subcontext["0"].signals.grid_zoom_anchor
viz
.signal(
"panOffset",
x
//"grid_t_in",
//[viz.signal("x_domain")].map(([a, b]) => [a + 1, b + 1])[0] // better to add an offset in patch?
)
.run()
viewof viz = embed(cashflows_spec({ premiums }), {
renderer: "svg",
actions: true,
patch: cashflows_spec_patch()
})
viz.signal("highlighting", true).run()
viz.getState()
{
viz.signal("grid_translate_anchor", {
x: 55.8125,
y: 12,
extent_x: [75, 150],
extent_y: [20, 40]
});
//viz.signal("grid", { t_in: [10], value: [10] }).run();
//viz.signal("grid_t_in", [10]);
//viz.signal("grid_value", [10]).run();
}
viz.signal("marker", 20).run()
cursor
cfs = await calcudata({
models: [model.js],
input_cursors: [cursor, { ...cursor, mort_rate_factor_in }],
//input_cursors: [{...cursor, stress_in: 'none',duration_mth_in:0},{...cursor, stress_in: 'none'}],
input_domains: {
t_in: _.range(
-model.js.duration_mth({ ...cursor, t_in: 0 }),
model.js.proj_len(cursor) + 0.1,
1
)
},
outputs: ["pv_premiums", "pv_claims", "pv_commissions", "pv_expenses"]
})
cfs_impacts = cashflows_summary_and_keep_add_subtract({
cfs,
offset: duration_mth_in,
singular: false
}).toArrow()
viz.data("source_0", cfs_impacts.toArray()).run()
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
