def phase1_dump(taname, setname):
dfTa = feat_select.load_feat(taname, setname)
(phase1, phase2, phase3) = feat_select.split_dates(dfTa)
dfmetas = feat_select.flat_metas(feat_select.get_metas(phase1))
outdir = os.path.join(root, "data", "feat_select", "phase1_dump")
if not os.path.exists(outdir):
os.makedirs(outdir)
dfmetas.to_pickle(os.path.join(outdir, "%s_%s.pkl" % (setname, taname)))
def phase1_dump(taname, setname):
dfTa = feat_select.load_feat(taname, setname)
(phase1, phase2, phase3) = feat_select.split_dates(dfTa)
dfmetas = feat_select.flat_metas(feat_select.get_metas(phase1))
outdir = os.path.join(root, "data", "feat_select", "phase1_dump")
if not os.path.exists(outdir):
os.makedirs(outdir)
dfmetas.to_pickle(os.path.join(outdir, "%s_%s.pkl" % (setname, taname)))
def work(setname, start, end, depth, thresh, scorename):
"""
"""
phase1 = base.get_merged("base1", getattr(yeod, "get_%s" % setname)(), start, end)
print phase1.shape
phase1.reset_index(drop=True, inplace=True)
phase1 = score.agn_rank_score(phase1)
phase1 = score.agn_rank_score(phase1, interval=5, threshold=0.55)
phase1 = score.agn_label_score(phase1, interval=5, threshold=1.0)
meta = feat_select.flat_metas(phase1, depth, 100000, scorename)
print meta[["fname", "c_p"]]
meta = extract_meta(meta, thresh)
meta.reset_index(drop=True, inplace=True)
meta.to_pickle("./data/model/meta_base1_%s_%s_%s_%s_%d_100000.pkl" % (setname, scorename, start, end, depth))
return meta
def work(setname, start, end, depth, thresh, scorename):
"""
"""
phase1 = base.get_merged("base1",
getattr(yeod, "get_%s" % setname)(), start, end)
print phase1.shape
phase1.reset_index(drop=True, inplace=True)
phase1 = score.agn_rank_score(phase1)
phase1 = score.agn_rank_score(phase1, interval=5, threshold=0.55)
phase1 = score.agn_label_score(phase1, interval=5, threshold=1.0)
meta = feat_select.flat_metas(phase1, depth, 100000, scorename)
print meta[["fname", "c_p"]]
meta = extract_meta(meta, thresh)
meta.reset_index(drop=True, inplace=True)
meta.to_pickle("./data/model/meta_base1_%s_%s_%s_%s_%d_100000.pkl" %
(setname, scorename, start, end, depth))
return meta
