'''
Created on April 27, 2018
@author: Edwin Simpson
'''
from evaluation.experiment import Experiment
import data.load_data as load_data
import numpy as np
output_dir = '../../data/bayesian_sequence_combination/output/ner/'
regen_data = False
gt, annos, doc_start, text, gt_nocrowd, doc_start_nocrowd, text_nocrowd, gt_task1_val, gt_val, doc_start_val, text_val, _ = \
load_data.load_ner_data(regen_data)
# ------------------------------------------------------------------------------------------------
exp = Experiment(None, 9, annos.shape[1], None, max_iter=20)
exp.save_results = True
exp.opt_hyper = False #True
best_bac_wm = 'bac_seq' #'unknown' # choose model with best score for the different BAC worker models
best_bac_wm_score = -np.inf
best_nu0factor = 0.1
best_diags = 1
best_factor = 1
best_acc_bias = 0
exp.alpha0_diags = best_diags
exp.alpha0_factor = best_factor
'''
Created on April 27, 2018
@author: Edwin Simpson
'''
from evaluation.experiment import Experiment
import data.load_data as load_data
import numpy as np
import os
gt, annos, doc_start, text, gt_nocrowd, doc_start_nocrowd, text_nocrowd, gt_task1_val, gt_val, doc_start_val, text_val, _ = \
load_data.load_ner_data(False)
# debug with subset -------
# s = 100
# idxs = np.argwhere(gt!=-1)[:s, 0]
# gt = gt[idxs]
# annos = annos[idxs]
# doc_start = doc_start[idxs]
# text = text[idxs]
# gt_task1_val = gt_task1_val[idxs]
# -------------------------
num_reps = 10
batch_frac = 0.03
AL_iters = 10
for rep in range(1, num_reps):
output_dir = '../data/bayesian_sequence_combination/output/ner_al_super_new/'
if not os.path.isdir(output_dir):