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LDA/05-getscore.py
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import numpy as np
import shelve
import sys
import glob
from collections import defaultdict
from tinydb import TinyDB, Query
from mako.template import Template
import time
def get_best(x):
argbest=np.argmax(x[1])
maxdev=x[1][argbest]
maxtrain=np.max(x[0])
maxtest=np.max(x[2])
besttest=x[2][argbest]
return ( maxtrain,maxdev,maxtest,besttest)
template = '''
${name}
========================
LDA likelihood : ${lb}
-----------------------
MLP scores :
-------------------
| LDA RAW | train | dev |max test| best test|
| ASR | - | ${mlp_lda_asr[0]} | - | ${mlp_lda_asr[1]} |
| TRS | - | ${mlp_lda_trs[0]} | - | ${mlp_lda_trs[1]} |
| AE ASR | train | dev |max test| best test|
% for cpt,line in enumerate(models["AE"]["ASR"]):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
| AE TRS | train | dev |max test| best test|
% for cpt,line in enumerate(models["AE"]["TRS"]):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
| AE SPE | train | dev |max test| best test|
% for cpt,line in enumerate(models["AE"]["SPE"]):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
| SAE ARS | train | dev |max test| best test|
% for cpt,line in enumerate(models["SAE"]['ASR']):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
| SAE TRS | train | dev |max test| best test|
% for cpt,line in enumerate(models["SAE"]["TRS"]):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
| SAE SPE | train | dev |max test| best test|
% for cpt,line in enumerate(models["SAE"]["SPE"]):
| ${cpt} | ${line[0]} | ${line[1]} |${line[2]} | ${line[3]} |
% endfor
'''
# ae_model.shelve
def get_folder_file(x):
folder=x.split("/")[1]
shelve_file = ".".join(x.split(".")[:-1])
return(folder,shelve_file)
in_folder = sys.argv[1]
folder_list = [ x.strip() for x in open("{}/ordered_model.txt".format(in_folder)).readlines() ][0:51]
models = defaultdict(dict)
db = TinyDB("{}/t4.db".format(in_folder))
for folder in folder_list :
try :
q = Query()
lb = db.search(q.name == folder)[0]["asr"]
mlp_shelve = shelve.open("{}/{}/mlp_scores.shelve".format(in_folder,folder))
mlp_lda_asr=mlp_shelve["ASR"][1]
mlp_lda_trs=mlp_shelve["TRS"][1]
ae_model_list = glob.glob("{}/{}/*/ae_model.shelve.dir".format(in_folder,folder))
ae_model_list= map(get_folder_file,ae_model_list)
for name , shelve_file in ae_model_list :
opened_shelve = shelve.open(shelve_file)
working_key = None
if "AE" in opened_shelve.keys():
working_key = "AE"
elif "SAE" in opened_shelve.keys():
working_key = "SAE"
for key in opened_shelve[working_key].keys():
models[working_key][key] = [ get_best(x) for x in opened_shelve[working_key][key] ]
print(Template(template).render(name=folder,lb=lb,mlp_lda_asr=mlp_lda_asr,mlp_lda_trs=mlp_lda_trs,models=models))
except :
print >>sys.stderr, "Erreur model {} ".format(folder)
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