def execute_query_fast(hs, qdat, qcxs, dcxs):
'''Executes a query and assumes qdat has all precomputed information'''
# Nearest neighbors
neighbs = mf.nearest_neighbors(hs, qcxs, qdat)
# Nearest neighbors weighting and scoring
weights, filt2_meta = mf.weight_neighbors(hs, neighbs, qdat)
# Thresholding and weighting
nnfiltFILT = mf.filter_neighbors(hs, neighbs, weights, qdat)
# Nearest neighbors to chip matches
matchesFILT = mf.build_chipmatches(hs, neighbs, nnfiltFILT, qdat)
# Spatial verification
matchesSVER = mf.spatial_verification(hs, matchesFILT, qdat)
# Query results format
result_list = [
mf.chipmatch_to_resdict(hs, matchesSVER, filt2_meta, qdat),
]
return result_list
def execute_query_fast(hs, qdat, qcxs, dcxs):
'''Executes a query and assumes qdat has all precomputed information'''
# Nearest neighbors
neighbs = mf.nearest_neighbors(hs, qcxs, qdat)
# Nearest neighbors weighting and scoring
weights, filt2_meta = mf.weight_neighbors(hs, neighbs, qdat)
# Thresholding and weighting
nnfiltFILT = mf.filter_neighbors(hs, neighbs, weights, qdat)
# Nearest neighbors to chip matches
matchesFILT = mf.build_chipmatches(hs, neighbs, nnfiltFILT, qdat)
# Spatial verification
matchesSVER = mf.spatial_verification(hs, matchesFILT, qdat)
# Query results format
result_list = [
mf.chipmatch_to_resdict(hs, matchesSVER, filt2_meta, qdat),
]
return result_list
def get_qfx2_gtkrank(hs, qcx, q_cfg):
'''Finds how deep possibily correct matches are in the ANN structures'''
import matching_functions as mf
dx2_cx = q_cfg.data_index.ax2_cx
gt_cxs = hs.get_other_cxs(qcx)
qcx2_nns = mf.nearest_neighbors(hs, [qcx], q_cfg)
filt2_weights = mf.weight_neighbors(hs, qcx2_nns, q_cfg)
K = q_cfg.nn_cfg.K
(qfx2_dx, _) = qcx2_nns[qcx]
qfx2_weights = filt2_weights['lnbnn'][qcx]
qfx2_cx = dx2_cx[qfx2_dx[:, 0:K]]
qfx2_gt = np.in1d(qfx2_cx.flatten(), gt_cxs)
qfx2_gt.shape = qfx2_cx.shape
qfx2_gtkrank = np.array([helpers.npfind(isgt) for isgt in qfx2_gt])
qfx2_gtkweight = [0 if rank == -1 else weights[rank]
for weights, rank in zip(qfx2_weights, qfx2_gtkrank)]
qfx2_gtkweight = np.array(qfx2_gtkweight)
return qfx2_gtkrank, qfx2_gtkweight