2018-10-19¶Link Grammar 5.4.4, test_grammar updated 2018-10-19, server 94.130.238.118.
This notebook is shared as static Child-Directed-Speech-2018-10-19.html
The "All tests" table is shared as 'short_table.txt' in Child-Directed-Speech-2018-10-19 folder
import os, sys, time
module_path = os.path.abspath(os.path.join('..'))
if module_path not in sys.path: sys.path.append(module_path)
from src.grammar_learner.utl import UTC
from src.grammar_learner.read_files import check_dir
from src.grammar_learner.write_files import list2file
from src.grammar_learner.widgets import html_table
from src.grammar_learner.pqa_table import table_rows
tmpath = module_path + '/tmp/'
check_dir(tmpath, True, 'none')
table = []
long_table = []
start = time.time()
print(UTC(), ':: module_path =', module_path)
out_dir = module_path + '/output/Child-Directed-Speech-' + str(UTC())[:10]
runs = (1,1) # (attempts to learn grammar per line, grammar tests per attempt)
if runs != (1,1): out_dir += '-multi'
kwargs = {
'left_wall' : '' ,
'period' : False ,
'word_space' : 'vectors' ,
'clustering' : ('kmeans', 'kmeans++', 10),
'cluster_range' : (120,30,3) , # max, min, proof
'cluster_criteria': 'silhouette',
'cluster_level' : 1 ,
'tmpath' : tmpath ,
'verbose' : 'min' ,
'template_path' : 'poc-turtle',
'linkage_limit' : 1000 ,
'categories_generalization': 'off' }
lines = [
[33, 'CDS-caps-br-text+brent9mos' , 'LG-English' ,0,0, 'none' ],
[34, 'CDS-caps-br-text+brent9mos' , 'LG-English' ,0,0, 'rules' ],
[35, 'CDS-caps-br-text+brent9mos' , 'R=6-Weight=6:R-mst-weight=+1:R' ,0,0, 'none' ],
[36, 'CDS-caps-br-text+brent9mos' , 'R=6-Weight=6:R-mst-weight=+1:R' ,0,0, 'rules' ]]
rp = module_path + '/data/CDS-caps-br-text+brent9mos/LG-English'
cp = rp # corpus path = reference_path :: use 'gold' parses as test corpus
%%capture
kwargs['context'] = 1
kwargs['grammar_rules'] = 1
average21, long21, header = table_rows(lines, out_dir, cp, rp, runs, **kwargs)
table.extend(average21)
long_table.extend(long21)
display(html_table([header]+average21))
%%capture
kwargs['context'] = 1
kwargs['word_space'] = 'vectors'
kwargs['clustering'] = 'kmeans'
kwargs['grammar_rules'] = 2
average22, long22, header = table_rows(lines, out_dir, cp, rp, runs, **kwargs)
table.extend(average22)
long_table.extend(long22)
display(html_table([header]+average22))
%%capture
kwargs['context'] = 2
kwargs['word_space'] = 'vectors'
kwargs['clustering'] = 'kmeans'
kwargs['grammar_rules'] = 2
average23, long23, header = table_rows(lines, out_dir, cp, rp, runs, **kwargs)
table.extend(average23)
long_table.extend(long23)
display(html_table([header]+average23))
%%capture
kwargs['context'] = 2
kwargs['word_space'] = 'discrete'
kwargs['clustering'] = 'group'
kwargs['grammar_rules'] = 2
average24, long24, header = table_rows(lines, out_dir, cp, rp, runs, **kwargs)
table.extend(average24)
long_table.extend(long24)
display(html_table([header]+average24))
display(html_table([header]+long_table))
print(UTC(), ':: finished, elapsed', str(round((time.time()-start)/3600.0, 1)), 'hours')
table_str = list2file(table, out_dir+'/short_table.txt')
if runs == (1,1):
print('Results saved to', out_dir + '/short_table.txt')
else:
long_table_str = list2file(long_table, out_dir+'/long_table.txt')
print('Average results saved to', out_dir + '/short_table.txt\n'
'Detailed results for every run saved to', out_dir + '/long_table.txt')