def plot3D(data, width=700, height=500, pointSize=1.2, client=False):
c3 = inlib.histo_c3d('xyz')
[c3.fill(float(row[0]), float(row[1]), float(row[2]), 1) for row in data]
#plotter
if not client:
plotter = window.gui_plotter(inlib.get_cout(), 1, 1, 0, 0, width,
height)
else:
import inexlib_client
style_file = os.path.join(os.environ['EXLIB_RES_DIR'], "ioda.style")
plotter = inexlib_client.plotter(inlib.get_cout(), 1, 1, "127.0.0.1",
50800, style_file)
#scen graph plotter
sgp = plotter.plot_cloud3D(c3)
sgp.shape.value(inlib.sg_plotter.xyz)
sgp.shape_automated.value(False)
sgp.infos_style().visible.value(False)
sgp.points_style(0).color.value(inlib.colorf_black())
#sgp.points_style(0).color.value(inlib.colorf_yellow())
#sgp.points_style(0).modeling.value(inlib.modeling_points())
sgp.points_style(0).marker_style.value(inlib.marker_dot)
sgp.points_style(0).point_size.value(pointSize)
if not client:
plotter.show()
plotter.steer()
else:
print("clearing scene")
plotter.send_clear_static_scene()
print("sending data to 127.0.0.1:50800 ...")
plotter.send_plots()
del plotter
del c3
parser.add_argument('-vis_host', dest='vis_host',required=False,help='host to display on')
parser.add_argument('-vis_port', dest='vis_port',required=False,help='port to display on')
parser.add_argument('-vis_format', dest='vis_format',required=False,help='format for output')
args = parser.parse_args(None)
file_name = args.file_name
verbose = False
if args.verbose == "True" : verbose = True
#////////////////////////////////////////////////////////////
#/// create and fill a 3D cloud with the csv file : /////////
#////////////////////////////////////////////////////////////
import inlib
c3 = inlib.histo_c3d('from csv')
import csv
file = open(file_name)
csv_reader = csv.reader(file, delimiter=',')
first_line = False
line_count = 0
for row in csv_reader:
if 0 <= line_count :
#if 0 <= line_count and line_count < 180000 :
#if 0 <= line_count and line_count < 360000 :
#if 0 <= line_count and line_count < 540000 :
#if 60000 <= line_count and line_count < 120000 :
#if 120000 <= line_count and line_count < 180000 :
#if 180000 <= line_count and line_count < 360000 :
#if 360000 <= line_count and line_count < 540000 :
", expected " + str(len_data_ref))
exit()
ntuple = data[0]
#print("len(ntuple) : "+str(len(ntuple))+". Should be 2.")
#print(ntuple[0].__class__.__name__) # ndarray
#print(ntuple[1].__class__.__name__) # int
#print("data[0][1] : "+str(ntuple[1])+". Should be 77.")
#///////////////////////////////////////////////////////////////////////////////////////
#/// plotting : /////////////////////////////////////////////////////////////////////////
#///////////////////////////////////////////////////////////////////////////////////////
import inlib
c3 = inlib.histo_c3d('xyz')
[
c3.fill(ntuple[0][0], ntuple[0][1], ntuple[0][2], 1) for ntuple in data
if ntuple[0] is not None
]
#print("inlib::histo::c3d entries : "+str(c3.entries()))
#print(" mean x = "+str(c3.mean_x())+", rms x = "+str(c3.rms_x()))
#print(" mean y = "+str(c3.mean_y())+", rms y = "+str(c3.rms_y()))
#print(" mean z = "+str(c3.mean_z())+", rms z = "+str(c3.rms_z()))
if args.vis_mode == "window":
#print("plot (window) ...")
import window
p = window.plotter(inlib.get_cout(), 1, 1, 0, 0, 700, 500)
p.plot_cloud3D(c3)
#//////////////////////////////////////////////////////////
c2 = inlib.histo_c2d('Rand gauss/BW')
rg = inlib.rgaussd(0, 1)
rbw = inlib.rbwd(0, 1)
for I in range(0, 10000):
c2.fill(rg.shoot(), rbw.shoot(), 1)
del rg
del rbw
#print c2.entries(),c2.mean_y(),c2.rms_y()
#//////////////////////////////////////////////////////////
#/// create and fill a 3D cloud : /////////////////////////
#//////////////////////////////////////////////////////////
c3 = inlib.histo_c3d('Rand gauss/BW/gauss')
rg = inlib.rgaussd(0, 1)
rbw = inlib.rbwd(0, 1)
for I in range(0, number_of_points):
c3.fill(rg.shoot(), rbw.shoot(), rg.shoot(), 1)
del rg
del rbw
if verbose == True:
print("inlib::histo::c3d entries : " + str(c3.entries()))
print(" mean x = " + str(c3.mean_x()) + ", rms x = " + str(c3.rms_x()))
print(" mean y = " + str(c3.mean_y()) + ", rms y = " + str(c3.rms_y()))
print(" mean z = " + str(c3.mean_z()) + ", rms z = " + str(c3.rms_z()))
#///////////////////////////////////////////////////////////////////////////////////////
#file.close()
#exit
#///////////////////////////////////////////////////////////////////////////////////////
#/// plottting : ///////////////////////////////////////////////////////////////////////
#///////////////////////////////////////////////////////////////////////////////////////
#print("fill c2d ...")
#c2 = inlib.histo_c2d('radec')
#[c2.fill(row[0],row[1],1) for row in data]
#print("inlib::histo::c2d entries : "+str(c2.entries()))
#print(" mean x = "+str(c2.mean_x())+", rms x = "+str(c2.rms_x()))
#print(" mean y = "+str(c2.mean_y())+", rms y = "+str(c2.rms_y()))
c3 = inlib.histo_c3d('radec_z')
if do_cut == True:
[fill_cut(c3, file, row[0], row[1], row[2]) for row in data]
else:
[c3.fill(row[0], row[1], row[2], 1) for row in data]
#print("inlib::histo::c3d entries : "+str(c3.entries()))
#print(" mean x = "+str(c3.mean_x())+", rms x = "+str(c3.rms_x()))
#print(" mean y = "+str(c3.mean_y())+", rms y = "+str(c3.rms_y()))
#print(" mean z = "+str(c3.mean_z())+", rms z = "+str(c3.rms_z()))
#print("fill h2d ...")
#h2 = inlib.histo_h2d('radec',100,0,360,100,-90,90)
#h2 = inlib.histo_h2d('radec',200,c2.mean_x()-2*c2.rms_x(),c2.mean_x()+2*c2.rms_x(),\
# 200,c2.mean_y()-2*c2.rms_y(),c2.mean_y()+2*c2.rms_y())