Public
Edited
Nov 17, 2023
dataset[0]
features = ["LogP", "LogVP", "BP [°C]", "MP [°C]", "MW [g/mol]", "LogS [M/L]"]
target_column = "LLNA EC3 (%)"
dataset = fetch_dataset_to_array(dataset_url, query_options)
query_options = {
return {
method: 'POST',
body: JSON.stringify({
condition: {
gt: [{tanimotoSimilarity: [targetSmiles, { column: ["SMILES"] }]}, tanimoto_threshold]
},
orderBy: [
{expression: {tanimotoSimilarity: [targetSmiles, { column: ["SMILES"] }]}, ordering: "descending"}
]
})
}
}
dataset_url = base_url_edelweiss + dataset_id + "/versions/latest/data"
dataset_id = '3f68e739-5d30-4a6b-b4f2-7301f8c584cb'
base_url_edelweiss = 'https://api.edelweissdata.com/datasets/'
function fetch_dataset_to_array(dataset_url, query_options) {
return fetch(dataset_url, query_options).then(response_dataset => {
if (!response_dataset.ok) throw new Error(response_dataset.status);
return response_dataset.json();}).then(json => json.results.map(x => x.data));
}
function get_svg_from_smiles(smiles) {
const safeSmiles = encodeURIComponent(smiles);
const svg_url = "https://chemidconvert.cloud.douglasconnect.com/v1/asSvg?width=200&height=200&smiles=" + safeSmiles;
return fetch(svg_url).then(response => response.text());
}
import {Select, Range, Toggle, Table} from "@observablehq/inputs"
import {select, textarea, text, slider} from "@jashkenas/inputs"
import {vl} from "@vega/vega-lite-api"
import {render_data_table, table_styles, displayImage, displayCaution} from '@info474/utilities'
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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.
