########################
# Build the reco testing here
########################
labels = []
labels = pc.kdtree_radius(dataset)
datasetidx_holder = lh.label_to_idxholder(labels,20) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
print 'out of the tree for good'
# Make a json to view
if make_jsons:
dh.MakeJson_Objects(dataset,datasetidx_holder,labels,jdir,jcount,'kd_tree', mc_dl)
print ' AT THE END'
#if len(dataset)>=15000 or len(dataset)==0:
#labels = pc.walker(dataset,6,20) # Runs clustering and returns labels list
#else:
#labels = pc.crawlernn(dataset, 6, 20 ) # Runs clustering and returns labels list
#datasetidx_holder = lh.label_to_idxholder(labels,20) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
#######
wlabels = []
#trackidx_holder = []
#showeridx_holder = []
#wlabels = pc.walker(dataset,8,20) # Runs clustering and returns labels list
wlabels = pc.walker(dataset, nn_dist,
mincluster) # Runs clustering and returns labels list
wdatasetidx_holder = lh.label_to_idxholder(
wlabels, mincluster
) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
if make_jsons:
dh.MakeJson_Objects(dataset, wdatasetidx_holder, wlabels, jdir, jcount,
'Walker', mc_dl)
#minclusterlength = 10
for gap_dist in xrange(120, 121, 30):
#for gap_dist in xrange(30,150,30):
for k_radius in xrange(8, 13, 2):
#for k_radius in xrange(10,40,10):
for angle_error in xrange(8, 9, 8):
#for angle_error in xrange(8,25,8):
for min_pdelta in xrange(2, 6, 3):
#for min_pdelta in xrange(2,5,3):
# Make a fresh labels and dataholder
labels = [x for x in wlabels]
datasetidx_holder = [x for x in wdatasetidx_holder]
if make_jsons:
dh.MakeJsonReco(f, jdir, jcount, 'AlgSPT', mc_dl)
#######
labels = []
labels = pc.walker(dataset, nn_dist,
mincluster) # Runs clustering and returns labels list
datasetidx_holder = lh.label_to_idxholder(
labels, mincluster
) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
if make_jsons:
dh.MakeJson_Objects(dataset, datasetidx_holder, labels, jdir, jcount,
'Walker', mc_dl)
d, labels = st.Track_Stitcher_epts(dataset, datasetidx_holder, labels,
gap_dist, k_radius, min_pdelta, AE,
min_clust_length)
datasetidx_holder = lh.label_to_idxholder(
labels, mincluster
) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
#if make_jsons:
# dh.MakeJson_Objects(dataset,datasetidx_holder,labels,jdir,jcount,'Stitcher', mc_dl)
# Now run T_S and see how things look... do we need a sweep... and if so what do we sweep on
showeridx_holder, trackidx_holder = tss.cluster_first_length(
dataset, datasetidx_holder, 0.998, 20, 10)
#######
labels = []
#trackidx_holder = []
#showeridx_holder = []
#wlabels = pc.walker(dataset,8,20) # Runs clustering and returns labels list
labels = pc.walker(dataset, nn_dist,
mincluster) # Runs clustering and returns labels list
datasetidx_holder = lh.label_to_idxholder(
labels, mincluster
) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
if make_jsons:
dh.MakeJson_Objects(dataset, datasetidx_holder, labels, jdir, jcount,
'Walker', mc_dl)
d, labels = st.Track_Stitcher_epts(dataset, datasetidx_holder, labels,
gap_dist, k_radius, min_pdelta, AE,
min_clust_length)
datasetidx_holder = lh.label_to_idxholder(
labels, mincluster
) # Converts the labels list into a list of indexvalues for datasets [ [ list of index], [list of indexes].. [] ]
if make_jsons:
dh.MakeJson_Objects(dataset, datasetidx_holder, labels, jdir, jcount,
'Stitcher', mc_dl)
# Now run T_S and see how things look... do we need a sweep... and if so what do we sweep on
fshoweridx_holder, ftrackidx_holder = tss.cluster_first_length(
dataset, datasetidx_holder, 0.998, 20, 10)
########### Rebase the dataset for reclustering ###############
#####################################################################
#####################################################################
rebase_dataset = Erc.rebase_spts(f, dataset, showeridx_holder, ROI_list, 6,
1000.)
rebase_labels = [5 for x in range(len(rebase_dataset))]
rebaseidx_holder = [[x for x in range(len(rebase_dataset))]]
end_Rtime = datetime.now()
delta_Rt = end_Rtime - start_Rtime
print 'RTIME', str(delta_Rt.seconds) + ' rebase_dataset'
start_Rtime = datetime.now()
if make_jsons:
dh.MakeJson_Objects(rebase_dataset, rebaseidx_holder, rebase_labels,
jdir, jcount, 'REBASE_ROI', mc_dl)
end_Rtime = datetime.now()
delta_Rt = end_Rtime - start_Rtime
print 'RTIME', str(delta_Rt.seconds) + ' make_rebasejson'
start_Rtime = datetime.now()
rtrackidx_holder, rshoweridx_holder, rlabels = Er.rebase_Full_reco(
rebase_dataset, mc_dl, jdir, jcount)
#rtrackidx_holder , rshoweridx_holder , rlabels =Er.rebase_Full_reco(rebase_dataset,mc_dl,jdir,jcount,make_jsons,timer=True)
end_Rtime = datetime.now()
delta_Rt = end_Rtime - start_Rtime
print 'RTIME ', str(delta_Rt.seconds) + ' run_rebase_Full_reco'
start_Rtime = datetime.now()
#print rebase_dataset