Public
Edited
Feb 3, 2020
vega_embed({
data: {values: df_filtered},
width: 400,
height: 200,
mark: "point",
encoding: {
x: {field: "num_filtered_out_per_comparison", type: "quantitative"},
y: {field: "sensitivity", type: "quantitative"},
color: colour_by_options[colour_by],
row: facet_by_options[facet_by],
tooltip: [{"field": "precision"},
{"field": "sensitivity"},
{"field": "num_filtered_out_per_comparison"},
{"field": "feature_type"},
{"field": "jointhreshold"},
{"field": "num_features"},
{"field": "num_hash_tables"},
{"field": "maxdf"},
]
},
title: `Number of records filtered out by LSH, by sensitivity(recall)`,
})
html`<style>.vega-embed-wrapper {overflow: hidden}`
md`## Data imports`
df = d3.csv("https://gist.githubusercontent.com/RobinL/157687cd746412056c92243a8c083b51/raw/290a25f61671198e8526d8f143b87ed6c69098f9/param_space_results_10000_2.csv", d3.autoType)
df2 = {
return df.map(d => {
d["num_filtered_out_per_comparison"] = d["total_potential_comparisons"]/d["num_actual_comparisons"]
return d
})
}
md`## Modules and imports`
import { autoSelect, select, slider } from "@jashkenas/inputs"
d3 = require("d3")
vega_embed = require("vega-embed")
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.
