nimgs = flow_v.size()
print("number of flow crops: ", nimgs)
print("number of adc crops: ", cropped_v.size())
c = rt.TCanvas("c", "LArFlow", 1500, 400)
c.Divide(3, 1)
for iset in xrange(nimgs):
srcimg = cropped_v.at(iset * 3 + 2)
if flowdir == 'y2u':
tarimg = cropped_v.at(iset * 3 + 0)
else:
tarimg = cropped_v.at(iset * 3 + 1)
hsrc = larcv.as_th2d(srcimg, "hsrc_set{}".format(iset))
htar = larcv.as_th2d(tarimg, "htar_set{}".format(iset))
hsrc.GetZaxis().SetRangeUser(0, 100)
htar.GetZaxis().SetRangeUser(0, 100)
hsrc.SetTitle("Source Plane Y: Set {};wire;tick".format(iset))
if flowdir == 'y2u':
htar.SetTitle("Target Plane U: Set {};wire;tick".format(iset))
else:
htar.SetTitle("Target Plane V: Set {};wire;tick".format(iset))
# prepare flow image
flow = flow_v.at(iset)
src_np = larcv.as_ndarray(srcimg)
flow_np = larcv.as_ndarray(flow).astype(np.int)
colidx = np.arange(src_np.shape[0], dtype=np.int)
for row in xrange(src_np.shape[1]):
import ROOT as rt
from larcv import larcv
larcv.load_rootutil()
rt.gStyle.SetOptStat(0)
rfile = sys.argv[1]
tree = sys.argv[2]
entry = int(sys.argv[3])
index = int(sys.argv[4])
io = larcv.IOManager(larcv.IOManager.kREAD)
io.add_in_file(rfile)
io.initialize()
io.read_entry(entry)
evimg2d = io.get_data(larcv.kProductImage2D, tree)
img = evimg2d.as_vector().at(index)
c = rt.TCanvas("c", "c", 1000, 400)
c.Draw()
himg = larcv.as_th2d(img, "tree_%d_%d" % (entry, index))
himg.Draw("COLZ")
c.Update()
print "Printed"
raw_input()
nplanes = wholeview_v.size()
ncrops = 0
crop_v = []
crop_meta_v = []
crop_img2d_v = []
c = rt.TCanvas("c", "c", 800, 600)
for plane in xrange(nplanes):
if plane not in [2]:
continue
wholeimg = wholeview_v.at(plane)
for roi in roi_v:
bbox = roi.BB(plane)
#std::cout << "crop from the whole image" << std::endl;
crop = wholeimg.crop(bbox)
h2d = larcv.as_th2d(crop, "roi%d" % (ncrops))
c.Draw()
h2d.Draw("colz")
c.Update()
print "[enter to continue]"
raw_input()
crop_np = larcv.as_ndarray(crop)
np.nan_to_num(crop_np, copy=False)
crop_np[crop_np < 10.0] = 0.0
crop_np[crop_np > 100.0] = 100.0
print crop_np.shape, ":", crop.meta().dump()
#crop_np = np.transpose( crop_np, (0,1,3,2))
if debug_w_png:
scipy.misc.toimage(crop_np, cmin=0.0, cmax=100.0).\
save("adc_crop%d.png"%(ncrops))
for p in xrange(3):
cropped_adc_v.push_back( adc_v.at( 3*i + p ) )
hvis = std.vector("TH2D")()
#lfcrop_algo.check_cropped_images( 2, cropped_adc_v, ev_status,
# thresholds_v, cropped_flow_v, cropped_visi_v, hvis, has_visi, vis_check )
flow_vv.append( cropped_flow_v )
if VIS_FLOWS:
# first row and column: ADC images
h_v = {}
canvspot = [1,2,0]
htitle = ["TARGET1","TARGET2","SOURCE"]
for j in range(3):
cflow.cd(canvspot[j]+1)
h_v[j] = larcv.as_th2d( cropped_adc_v.at(j), "test%d_%d"%(i,j) )
h_v[j].GetZaxis().SetRangeUser(-10,250)
h_v[j].SetTitle("%s"%(htitle[j]))
h_v[j].Draw("COLZ")
# first col as well for matrix
cflow.cd(3+1)
h_v[2].Draw("COLZ")
cflow.cd(6+1)
h_v[2].Draw("COLZ")
# second row, the flows
for j in xrange(0,2):
cflow.cd(3+j+2)
h_v[3+j] = larcv.as_th2d( cropped_flow_v.at(j), "flow%d_%d"%(i,j) )
h_v[3+j].GetZaxis().SetRangeUser(-832,832)
h_v[3+j].Draw("COLZ")
IMAGE_HEIGHT, IMAGE_WIDTH, 2)
srcmetas.append(meta)
meta = larcv.ImageMeta(srcmeta[b, 0, 0, 0], srcmeta[b, 0, 0, 1],
srcmeta[b, 0, 0, 2], srcmeta[b, 0, 0, 3],
IMAGE_HEIGHT, IMAGE_WIDTH, 2)
targetumetas.append(meta)
meta = larcv.ImageMeta(srcmeta[b, 1, 0, 0], srcmeta[b, 1, 0, 1],
srcmeta[b, 1, 0, 2], srcmeta[b, 1, 0, 3],
IMAGE_HEIGHT, IMAGE_WIDTH, 2)
targetvmetas.append(meta)
# check image2d input
img_adc = larcv.as_image2d_meta(
source[0, 0, :, :].detach().cpu().numpy().transpose((1, 0)),
srcmetas[0])
hadc = larcv.as_th2d(img_adc, "hadc_input")
c.cd(1)
hadc.SetTitle("source y")
hadc.Draw("COLZ")
c.Update()
#c.SaveAs("hadc_input_%d.png"%(ientry))
#cv.imwrite( "cvadc_input_%d.png"%(ientry), source[0,0,:,:].detach().cpu().numpy() )
img_targetu = larcv.as_image2d_meta(
target1[0, 0, :, :].detach().cpu().numpy().transpose((1, 0)),
targetumetas[0])
htargetu = larcv.as_th2d(img_targetu, "htargetu_input")
c.cd(2)
htargetu.SetTitle("target u")
htargetu.Draw("COLZ")
io = larcv.IOManager(larcv.IOManager.kREAD)
io.add_in_file("out_dense_ublarflow_test.root")
#io.add_in_file( "flowtest.root" )
io.initialize()
io.read_entry(0)
#cfg = larcv.CreatePSetFromFile( "ubsplit.cfg","UBSplitDetector")
#splitalgo = ublarcvapp.UBSplitDetector()
#splitalgo.configure(cfg)
#splitalgo.initialize()
ev_larflow_y2u = io.get_data(larcv.kProductImage2D, "larflow_y2u")
y2u_v = ev_larflow_y2u.as_vector()
ncrops = y2u_v.size()
print "num crops: ", ncrops
c = rt.TCanvas("c", "c", 800, 600)
c.Draw()
for iimg in xrange(ncrops):
print "IMG: ", iimg
img = y2u_v.at(iimg)
c.Clear()
hist = larcv.as_th2d(img, "y2u_%02d" % (iimg))
hist.Draw("COLZ")
c.Update()
raw_input()