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5.31 kB
| """Tail sections of the noise audit (reuses table pf3 built by eda_pairs_full.py).""" | |
| import duckdb, time, os | |
| import pandas as pd | |
| pd.set_option("display.width", 250); pd.set_option("display.max_columns", 60); pd.set_option("display.max_rows", 200); pd.set_option("display.max_colwidth", 60) | |
| R=os.environ.get('ROOT','/opt/dlami/nvme/amlc'); t0=time.time() | |
| con=duckdb.connect(f'{R}/amlc.duckdb'); con.execute(f"SET threads=8; SET memory_limit='20GB'; SET temp_directory='{R}/duck_tmp';") | |
| q=lambda s: con.execute(s).df(); P=lambda *a: print(*a, f"[{time.time()-t0:.0f}s]", flush=True) | |
| print("=== JOINT: how many true pairs are hard on BOTH fields ===") | |
| print(q("SELECT round(avg(CASE WHEN name_j=0 THEN 1 ELSE 0 END),4) name_j0, round(avg(CASE WHEN addr_j=0 OR addr_empty THEN 1 ELSE 0 END),4) addr_j0_or_empty, round(avg(CASE WHEN name_j=0 AND (addr_j=0 OR addr_empty) THEN 1 ELSE 0 END),5) both_zero, round(avg(CASE WHEN name_j<0.34 AND addr_j<0.34 THEN 1 ELSE 0 END),4) both_lt_034, round(avg(CASE WHEN jw_core<0.85 AND addr_j<0.5 THEN 1 ELSE 0 END),4) jw85_addr50 FROM pf3").to_string(index=False)) | |
| print(q("SELECT CASE WHEN name_j=0 THEN 'n=0' WHEN name_j<0.34 THEN 'n<.34' WHEN name_j<0.67 THEN 'n<.67' WHEN name_j<1 THEN 'n<1' ELSE 'n=1' END nb, CASE WHEN addr_empty THEN 'a=empty' WHEN addr_j=0 THEN 'a=0' WHEN addr_j<0.34 THEN 'a<.34' WHEN addr_j<0.67 THEN 'a<.67' WHEN addr_j<1 THEN 'a<1' ELSE 'a=1' END ab, round(count(*)*100.0/(SELECT count(*) FROM pf3),2) pct FROM pf3 GROUP BY 1,2").pivot(index='nb',columns='ab',values='pct').fillna(0).to_string()) | |
| P("joint done") | |
| print("\n=== WITHIN-ENTITY VENDOR DUPLICATES: similarity between two vendor records of the SAME S1 entity ===") | |
| print(q("""SELECT x.src||'-'||y.src kind, count(*) n, round(avg(CASE WHEN x.c2=y.c2 THEN 1 ELSE 0 END),3) core_equal, | |
| round(avg(len(list_intersect(x.t2,y.t2))*1.0/greatest(1,len(list_distinct(list_concat(x.t2,y.t2))))),3) name_j, | |
| round(avg(len(list_intersect(x.at2,y.at2))*1.0/greatest(1,len(list_distinct(list_concat(x.at2,y.at2))))),3) addr_j, | |
| round(avg(CASE WHEN len(list_intersect(x.t2,y.t2))=0 THEN 1 ELSE 0 END),3) name_j0 | |
| FROM (SELECT * FROM pf3 USING SAMPLE 1000000 ROWS (reservoir, 5)) x JOIN pf3 y ON x.a=y.a AND x.b<y.b GROUP BY 1 ORDER BY 1""").to_string(index=False)) | |
| P("collective done") | |
| print("\n=== TRANSLITERATION LEXICON FEASIBILITY (Indic-script vendor names) ===") | |
| print(q("""SELECT src, country, count(*) n, round(avg(CASE WHEN len(string_split(trim(n2),' '))=len(string_split(nn1,' ')) THEN 1 ELSE 0 END),3) same_token_count, | |
| round(avg(len(string_split(trim(n2),' '))),2) v_tokens, round(avg(len(string_split(nn1,' '))),2) s1_tokens, round(avg(addr_j),3) addr_j | |
| FROM pf3 WHERE indic_name GROUP BY 1,2 ORDER BY 1,2""").to_string(index=False)) | |
| print(q("""WITH al AS (SELECT unnest(string_split(trim(n2),' ')) itok, unnest(string_split(nn1,' ')) ltok FROM pf3 WHERE indic_name AND len(string_split(trim(n2),' '))=len(string_split(nn1,' '))) | |
| , c AS (SELECT itok, ltok, count(*) n FROM al GROUP BY 1,2), tot AS (SELECT itok, sum(n) tn FROM c GROUP BY 1) | |
| SELECT c.itok, c.ltok, c.n, round(c.n*1.0/tot.tn,3) purity FROM c JOIN tot USING(itok) QUALIFY row_number() OVER (PARTITION BY c.itok ORDER BY c.n DESC)=1 ORDER BY tot.tn DESC LIMIT 30""").to_string(index=False)) | |
| print("distinct Indic-script vendor tokens:", con.execute("SELECT count(distinct itok) FROM (SELECT unnest(string_split(trim(n2),' ')) itok FROM pf3 WHERE indic_name)").fetchone()[0]) | |
| print("share of Indic tokens (by occurrence) whose best Latin alignment has purity>=0.8:", con.execute("""WITH al AS (SELECT unnest(string_split(trim(n2),' ')) itok, unnest(string_split(nn1,' ')) ltok FROM pf3 WHERE indic_name AND len(string_split(trim(n2),' '))=len(string_split(nn1,' '))), c AS (SELECT itok, ltok, count(*) n FROM al GROUP BY 1,2), tot AS (SELECT itok, sum(n) tn, max(n) mx FROM c GROUP BY 1) SELECT round(sum(CASE WHEN mx*1.0/tn>=0.8 THEN tn ELSE 0 END)/sum(tn),3) FROM tot""").fetchone()[0]) | |
| P("translit done") | |
| print("\n=== COMPLETE RENAMES sample ===") | |
| print(q("SELECT src, country, n1, n2, a1, a2 FROM pf3 WHERE name_j=0 AND NOT indic_name AND NOT domain_form AND NOT former_form USING SAMPLE 16 ROWS (reservoir, 3)").to_string(index=False)) | |
| print("\n=== S1 name collision frequency vs pair difficulty ===") | |
| LEGAL=r"\b(inc|incorporated|corp|corporation|co|company|llc|ltd|limited|llp|pllc|pc|plc|lp|pvt|private|opc|sarl|sas|sasu|eurl|sa|sci|snc|ei|ets|etablissements)\b" | |
| con.execute(f"CREATE OR REPLACE TABLE s1cnt AS SELECT entity_id, count(*) OVER (PARTITION BY country, c) cnt FROM (SELECT entity_id, country, trim(regexp_replace(regexp_replace(regexp_replace(lower(strip_accents(business_name)),'[^a-z0-9]+',' ','g'),'{LEGAL}',' ','g'),'\\s+',' ','g')) c FROM s1)") | |
| print(q("SELECT CASE WHEN cnt=1 THEN '1' WHEN cnt<5 THEN '2-4' WHEN cnt<20 THEN '5-19' ELSE '20+' END s1_name_freq, count(*) n_pairs, round(count(*)*100.0/(SELECT count(*) FROM pf3),1) pct, round(avg(name_j),3) name_j, round(avg(addr_j),3) addr_j FROM pf3 JOIN s1cnt ON s1cnt.entity_id=pf3.a GROUP BY 1 ORDER BY 1").to_string(index=False)) | |
| con.execute(f"COPY (SELECT a,b,src,country,name_j,addr_j,lev_core,jw_core,indic_name,domain_form,former_form,addr_empty FROM pf3) TO '{R}/parquet/pair_audit.parquet' (FORMAT PARQUET)") | |
| P("ALL DONE") | |