def SSSTSR_search(whole_ts, left_idx, right_idx, query, sequence, ts, rtv_len, uuid, invariance):
# TODO: remove the hardcode
somooth_window_len = -1
zero_thresh=0.000005 # 3b00277d-d513-43a7-a54f-942a402c507e
zero_thresh=0.001
minSize = 5
a = SSSTSR_Class(ts=whole_ts, smooth_window_len = somooth_window_len, zero_thresh=zero_thresh)
a.build_seg(plotSwitch = False, minSize=minSize)
a.seg_enhance_represent()
print "Number of segments: " + str(len(a.enhance_seg))
# b = SSSTSR_Class(ts=query, smooth_window_len = somooth_window_len, zero_thresh=zero_thresh, scale_train_ts = a)
# b.build_seg(plotSwitch = False, minSize=minSize)
# b.seg_enhance_represent()
seg_left_idx = a.get_seg_num_from_idx(left_idx)
seg_right_idx = a.get_seg_num_from_idx(right_idx)
knn_candidates_segmentwise = segmentwise_match_invariance(a.enhance_seg[seg_left_idx:seg_right_idx+1], a.enhance_seg[:seg_left_idx], 1, 3,
offset_inv = invariance['offset'],
longitude_inv=invariance['longitudinal'],
amplitude_inv=invariance['amplitude'],
lineardrift_inv=invariance['linear'])
output = {}
output['n'] = 3
output['list'] = []
# add query ts
query_dict = {}
query_dict['ts'] = sample_sensor_data(ts[left_idx:right_idx], rtv_len)
query_dict['start_time'] = ts[left_idx][0]
query_dict['end_time'] = ts[right_idx-1][0]
output['query'] = query_dict
segs = a.get_seg_ts()
for i, candidate in enumerate(knn_candidates_segmentwise):
dist = candidate[1]
pos = candidate[0]
len_matched_word = seg_right_idx - seg_left_idx + 1
match_str_startpos = (segs[pos])[0]
match_str_endpos = (segs[pos+len_matched_word-1])[1]
search_ts = sample_sensor_data(ts[match_str_startpos:match_str_endpos], rtv_len)
rtv = {}
print dist
rtv['dist'] = dist
rtv['ts'] = search_ts
rtv['start_time'] = search_ts[0][0]
rtv['end_time'] = search_ts[-1][0]
output['list'].append(copy.deepcopy(rtv))
return output
def SSSTSR_DTW_search(whole_ts, left_idx, right_idx, query, sequence, ts, rtv_len, uuid, invariance):
# TODO: remove the hardcode
somooth_window_len = -1
zero_thresh=0.000005 # 3b00277d-d513-43a7-a54f-942a402c507e
zero_thresh=0.001
minSize = 5
a = SSSTSR_Class(ts=whole_ts, smooth_window_len = somooth_window_len, zero_thresh=zero_thresh)
a.build_seg(plotSwitch = False, minSize=minSize)
a.seg_enhance_represent()
print len(a.enhance_seg)
# b = SSSTSR_Class(ts=query, smooth_window_len = somooth_window_len, zero_thresh=zero_thresh, scale_train_ts = a)
# b.build_seg(plotSwitch = False, minSize=minSize)
# b.seg_enhance_represent()
seg_left_idx = a.get_seg_num_from_idx(left_idx)
seg_right_idx = a.get_seg_num_from_idx(right_idx)
match_pos_list, matching_words, match_dist_list, search_path = DTW_seg_match(a.enhance_seg[seg_left_idx:seg_right_idx+1], a.enhance_seg[:seg_left_idx],3,
offset_inv = invariance['offset'],
longitude_inv=invariance['longitudinal'],
amplitude_inv=invariance['amplitude'],
lineardrift_inv=invariance['linear'])
output = {}
output['n'] = 3
output['list'] = []
# add query ts
query_dict = {}
query_dict['ts'] = sample_sensor_data(ts[left_idx:right_idx], rtv_len)
query_dict['start_time'] = ts[left_idx][0]
query_dict['end_time'] = ts[right_idx-1][0]
output['query'] = query_dict
segs = a.get_seg_ts()
for i in range(len(match_pos_list)):
len_matched_word = len(matching_words[i])
pos = match_pos_list[i]
dist = match_dist_list[i]
match_str_startpos = (segs[pos])[0]
match_str_endpos = (segs[pos+len_matched_word-1])[1]
search_ts = sample_sensor_data(ts[match_str_startpos:match_str_endpos], rtv_len)
rtv = {}
rtv['dist'] = dist
rtv['ts'] = search_ts
rtv['start_time'] = search_ts[0][0]
rtv['end_time'] = search_ts[-1][0]
output['list'].append(copy.deepcopy(rtv))
return output
