2f:T4fd,splink_settings_1 = { return { proportion_of_matches: 1 / 100, comparison_columns: [ { num_levels: 3, col_name: "fname", u_probabilities: [0.8, 0.2], m_probabilities: [0.2, 0.8], case_expression: (row) => { if (row.fname_l == row.fname_r) { return 1; } else { return 0; } } }, { num_levels: 3, col_name: "sname", u_probabilities: [0.9, 0.1], m_probabilities: [0.2, 0.8], case_expression: (row) => { if (row.sname_l == row.sname_r) { return 1; } else { return 0; } } }, { col_name: "dob", u_probabilities: [0.99, 0.01], m_probabilities: [0.2, 0.8], case_expression: (row) => { if (row.dob_l == row.dob_r) { return 1; } else { return 0; } } }, { col_name: "town", u_probabilities: [0.7, 0.3], m_probabilities: [0.3, 0.7], case_expression: (row) => { if (row.town_l == row.town_r) { return 1; } else { return 0; } } } ] }; }30:[] 2d:{"title":"Charts and Figures (Introduction)","cells":[{"id":0,"value":"md`# Charts and Figures (Introduction)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4,"value":"import { Record, RecordComparison } from \"ef62bc8f8c0d577e\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":43,"value":"import { get_waterfall_chart } from \"843cb6e82d7c3d9b\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"example_record_1_l = new Record({\n first_name: \"John\",\n surname: \"Smith\",\n date_of_birth: \"1989-03-02\",\n town: \"Bristol\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":8,"value":"example_record_1_r = new Record({\n first_name: \"John\",\n surname: \"Smith\",\n date_of_birth: \"1989-03-02\",\n town: \"Bath\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":14,"value":"example_1_comparison = new RecordComparison(\n example_record_1_l,\n example_record_1_r\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":37,"value":"splink_settings = {\n return {\n proportion_of_matches: 1 / 100,\n comparison_columns: [\n {\n num_levels: 3,\n col_name: \"first_name\",\n u_probabilities: [0.8, 0.2],\n m_probabilities: [0.2, 0.8]\n },\n {\n num_levels: 3,\n col_name: \"surname\",\n u_probabilities: [0.9, 0.1],\n m_probabilities: [0.2, 0.8]\n },\n {\n col_name: \"date_of_birth\",\n u_probabilities: [0.99, 0.01],\n m_probabilities: [0.2, 0.8]\n },\n {\n col_name: \"town\",\n u_probabilities: [0.7, 0.3],\n m_probabilities: [0.3, 0.7]\n }\n ]\n };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":98,"value":"example_1_row_with_gammas = {\n let row = example_1_comparison.as_wide().objects()[0];\n\n Object.keys(example_record_1_l.as_dict()).forEach((k) => {\n if (row[k + \"_l\"] == row[k + \"_r\"]) {\n row[\"𝛾_\" + k] = 1;\n } else {\n row[\"𝛾_\" + k] = 0;\n }\n });\n return row;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":49,"value":"overrides = {\n return {\n title: {\n text:\n \"Match weights and their cumulative contribution to match probability\",\n subtitle: \"\"\n },\n height: 200\n };\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"intro_simple_waterfall = get_waterfall_chart(\n example_1_row_with_gammas,\n splink_settings,\n overrides,\n true\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":127,"value":"md`# Charts and Figures (Mathematical Model)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":142,"value":"import { get_df_comparison, get_df_gammas } from \"d25176b0fe784ad0\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":209,"value":"function parseTableData(table) {\n const data = [];\n\n const replace_lookup = {\n \"unique id\": \"uid\",\n \"first name\": \"fname\",\n surname: \"sname\",\n \"date of birth\": \"dob\",\n town: \"town\"\n };\n\n table.querySelectorAll(\"tr\").forEach((row, i) => {\n let cells = row.cells;\n let row_data = [];\n\n for (let cell of cells) {\n let value = cell.innerText;\n value = value.trim();\n value = value.toLowerCase();\n if (value == \"\") {\n value = null;\n }\n row_data.push(value);\n }\n data.push(row_data);\n });\n\n const formattedData = data.reduce((accumulator, row, i) => {\n if (i == 0) {\n row = row.map((d) => replace_lookup[d]);\n accumulator.properties = row;\n } else {\n const rowObject = {};\n\n accumulator.properties.forEach((key, i) => {\n rowObject[key] = row[i];\n });\n accumulator.push(rowObject);\n }\n return accumulator;\n }, []);\n return formattedData;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":213,"value":"records_l = Generators.observe((notify) => {\n const keyinput = (event) => notify(parseTableData(table_l));\n table_l.addEventListener(\"input\", keyinput, false);\n notify(parseTableData(table_l));\n return () => window.removeEventListener(\"input\", keyinput);\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":193,"value":"table_l = html`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Unique ID	First name	Surname	Date of Birth	Town
1_l	John	Smith	1989-03-02	Bristol
2_l	Emma	Jones	1956-07-09	Hull
3_l	David	Smith	1981-08-21	London

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":190,"value":"table_r = html`\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

Unique ID	First name	Surname	Date of Birth	Town
1_r	Jonathan	Smith	1989-03-02	Bristol
2_r	David	Smith	1981-08-21	Peckham

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":148,"value":"records_r = Generators.observe((notify) => {\n const keyinput = (event) => notify(parseTableData(table_r));\n table_r.addEventListener(\"input\", keyinput, false);\n notify(parseTableData(table_r));\n return () => window.removeEventListener(\"input\", keyinput);\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":154,"value":"df_1_l = aq.from(records_l)","pinned":false,"hidden":false,"mode":"ojs"},{"id":155,"value":"df_1_r = aq.from(records_r)","pinned":false,"hidden":false,"mode":"ojs"},{"id":160,"value":"df_comparisons_1 = get_df_comparison(records_l, records_r)","pinned":false,"hidden":false,"mode":"ojs"},{"id":163,"value":"df_gammas_1 = get_df_gammas(df_comparisons_1, splink_settings_1)","pinned":false,"hidden":false,"mode":"ojs"},{"id":171,"value":"df_gammas_only_1 = {\n let uids = [\"uid_l\", \"uid_r\"];\n let colnames = df_gammas_1.columnNames();\n colnames = colnames.filter((d) => d.includes(\"𝛾_\"));\n colnames = uids.concat(colnames);\n return df_gammas_1.select(colnames);\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":164,"value":"$2f","pinned":false,"hidden":false,"mode":"ojs"},{"id":129,"value":"example_record_2_l = new Record({\n first_name: \"Tom\",\n surname: \"Hanks\",\n month_of_birth: \"July\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":131,"value":"example_record_2_r = new Record({\n first_name: \"Tom\",\n surname: \"Hanks\",\n month_of_birth: \"June\"\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":140,"value":"example_2_comparison = new RecordComparison(\n example_record_2_l,\n example_record_2_r\n)","pinned":false,"hidden":false,"mode":"ojs"},{"id":158,"value":"import { aq, op } from \"@uwdata/arquero@209\"","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W30","stdlib":"1","titling":"auto"}