s1172.py

from research import *
from algebra import Matrix
s=begin(1172,'Reject rank alone as an explanation score','Could a formally smaller numeric dimension conceal a larger description of the source family?',{},['C1171','Strategy §6'])
d=json.loads((ROOT/'model/postflood_native_joint_model.json').read_text());v=d['source_values'];ray=Matrix(v)
data={'diagnostic':'Represent the entire observed56-vector as q*v withq=1','rank':ray.rank(),'stored_coefficients':len(v),'reason_not_preferred':'This stores every output value in the rule and therefore explains none of the source repetitions. Rank alone ignores rule, mask and exception cost.','comparison':'The structured model retains baseline values and simple named shared-amplitude masks; no numerical scoring weights or unique-best-model claim is assigned.'}
a=artifact('model/rank_only_compression_counterexample.json',json.dumps(data,indent=2)+'\n')
finish(s,{'rank_counterexample':a},'A one-dimensional fitted ray can encode every observed value only by placing all56 values in its coefficients. This shows why lower rank is not itself the Strategy’s desired compression; source rules, masks and exceptional choices must be counted.','Establish the algebraic domain of the row moves before using them as a shared operation grammar.',{'ray_rank1':ray.rank()==1,'all56_stored':len(v)==56,'no_score_weights':'no numerical scoring weights' in data['comparison']})