from PlottingFunctions import plot_single_resolution
from PlottingFunctions import plot_energy_slices
from PlottingFunctions import plot_distributions
plot_single_resolution(Y_energy[energy_cc],reco_energy[energy_cc],bins=100, use_fraction=fractional,\
save=True,savefolder=save_folder_name,\
variable="Energy", units = "GeV")
plot_single_resolution(Y_coszenith[energy_cc],reco_coszenith[energy_cc],bins=100, use_fraction=fractional,\
save=True,savefolder=save_folder_name,\
variable="CosZenith", units = "")
plot_energy_slices(Y_energy[energy_cc], reco_energy[energy_cc], \
use_fraction = fractional, \
bins=10,min_val=5.,max_val=100.,\
save=True,savefolder=save_folder_name)
plot_energy_slices(Y_coszenith[energy_cc], reco_coszenith[energy_cc], \
use_fraction = fractional,
bins=10,min_val=-1.,max_val=1.,\
save=True,savefolder=save_folder_name,\
variable="CosZenith",units="")
plot_distributions(Y_energy[energy_cc], reco_energy[energy_cc],\
save=True,savefolder=save_folder_name,\
variable="Energy",units="GeV")
plot_distributions(Y_coszenith[energy_cc], reco_coszenith[energy_cc],\
save=True,savefolder=save_folder_name,\
variable="CozZenith",units="")
weights=weights2_value,alpha=0.5)
plt.xscale('log')
plt.title("Energy Distribution Weighted for %s events"%len(true2_value),fontsize=25)
plt.xlabel("Energy (GeV)",fontsize=20)
plt.xticks(fontsize=15)
plt.yticks(fontsize=15)
plt.axvline(5,linewidth=3,linestyle="--",color='k',label="Cut at 5 GeV")
plt.legend(loc='upper left',fontsize=15)
plt.savefig("%s/%sLogEnergyDist_ZoomInLE.png"%(save_folder_name,name2.replace(" ","")))
"""
if make_distributions:
plot_distributions(true1_value_fullAnalysis,
reco1_value_fullAnalysis,
weights=weights1_value_fullAnalysis,
save=save, savefolder=save_folder_name,
cnn_name = name1, variable=plot_name,
units= plot_units,
minval=minval,maxval=maxval,
bins=bins,true_name=energy_type)
if input_file2 is not None:
plot_distributions(true2_value_fullAnalysis,
old_reco=reco2_value_fullAnalysis,
weights=weights2_value_fullAnalysis,
save=save, savefolder=save_folder_name,
reco_name = name2, variable=plot_name,
units= plot_units,
minval=minval,maxval=maxval,
bins=bins,true_name=energy_type)
if make_2d_hist:
old_reco = retro_energy[cuts],\
use_fraction = True, bins=syst_bin, min_val=minval, max_val=maxval,\
save=save, savefolder=save_folder_name,\
variable=plot_name, units=plot_units, reco_name="Retro")
plot_vertex(true_r[cuts],true_z[cuts])
plot_bin_slices(true_energy[cuts], cnn_energy[cuts], old_reco = retro_energy[cuts],\
weights=weights[cuts],energy_truth=true_r[cuts],\
xvariable="Starting Vertex R Position",xunits="(m)",
use_fraction = True, bins=syst_bin, min_val=0, max_val=maxval*3,\
save=save, savefolder=save_folder_name,\
variable=plot_name, units=plot_units, reco_name="Retro")
"""
"""
plot_distributions(true_energy,cnn_energy,save=save,savefolder=save_folder_name,old_reco=retro_energy)
plot_distributions(true_energy,cnn_energy,save=save,savefolder=save_folder_name,old_reco=retro_energy,minval=1,maxval=150,bins=150)
plot_2D_prediction(true_energy, cnn_energy, save, save_folder_name,bins=bins,\
minval=minval, maxval=maxval, cut_truth=True, axis_square=True,\
variable=plot_name, units=plot_units, reco_name="CNN")
plot_2D_prediction(true_energy, retro_energy, save, save_folder_name,bins=bins,\
minval=minval, maxval=maxval, cut_truth=True, axis_square=True,\
variable=plot_name, units=plot_units, reco_name="Retro")
plot_single_resolution(true_energy, cnn_energy, use_old_reco = True, old_reco = retro_energy,\
minaxis=-maxval, maxaxis=maxval, bins=bins,\
save=save, savefolder=save_folder_name,\
variable=plot_name, units=plot_units, reco_name="Retro")
plot_bin_slices(true_energy, cnn_energy, old_reco = retro_energy,\
use_fraction = True, bins=15, min_val=minval, max_val=maxval,\
save=save, savefolder=save_folder_name,\
#print(plot_name, plot_units, minval, maxval, syst_bin, bins)
#print(max(true_val), max(cnn_val), max(retro_val))
#print(true_val[:10], cnn_val[:10], retro_val[:10])
if nu_type == "NuMu" or nu_type == "numu":
dist_title = r'$\nu_\mu$ '
elif nu_type == "NuE" or nu_type == "nue":
dist_title = r'for $\nu_e$ '
else:
dist_title += nu_type
dist_title += sample_name
if plot_main:
plot_distributions(true_val, cnn_val,
old_reco=retro_val,old_reco_weights=retro_weights,\
save=save, savefolder=save_folder_name, weights=true_weights,\
reco_name = reco_name, variable=plot_name, units= plot_units,
minval=minval,maxval=maxval,bins=bins)
plot_distributions(true_val, cnn_val,
old_reco=retro_val,old_reco_weights=retro_weights,\
save=save, savefolder=save_folder_name, weights=true_weights,\
reco_name = reco_name, variable=plot_name, units= plot_units,
minval=min(true_val), maxval=max(true_val))
if plot_others:
plot_distributions(true_r[cuts], reco_r[cuts],\
save=save, savefolder=save_folder_name, weights=true_weights,\
cnn_name = reco_name,
variable="Radial Vertex", units= "(m)",log=True)
plot_distributions(true_z[cuts], reco_z[cuts],\
save=save, savefolder=save_folder_name,
weights=true_weights,cnn_name = reco_name,
else:
weights_plot = weights[cuts]
print("Working on %s"%folder_name)
save_folder_name = save_base_name + "/%s/"%folder_name
if os.path.isdir(save_folder_name) != True:
os.mkdir(save_folder_name)
print(truth[:10], cnn[:10])
#plot_NDOMS(true_ndoms[cuts],true_r[cuts])
#plot_NDOMS(true_ndoms[cuts],true_r[cuts],cut=0)
plot_distributions(truth, cnn, old_reco=old_reco,\
save=save, savefolder=save_folder_name, weights=weights_plot,\
reco_name = "Retro", variable=plot_name, units= plot_units,
minval=minval,maxval=maxval,bins=bins)
plot_distributions(truth, cnn, old_reco=old_reco,\
save=save, savefolder=save_folder_name, weights=weights_plot,\
reco_name = "Retro", variable=plot_name, units= plot_units)
if reco is not None:
plot_distributions(true_r[cuts], reco_r[cuts],\
save=save, savefolder=save_folder_name, weights=weights_plot,\
cnn_name = "Retro", variable="Radial Vertex", units= "(m)",log=True)
plot_distributions(true_z[cuts], reco_z[cuts],\
save=save, savefolder=save_folder_name, weights=weights_plot,\
cnn_name = "Retro", variable="Z Vertex", units= "(m)",log=True)
plot_2D_prediction(truth, cnn,weights=weights_plot,\
save=save, savefolder=save_folder_name,bins=bins,
variable=plot_name, units=plot_units, reco_name="CNN")
else:
reco_class = retro_PID_full
print("Working on %s" % folder_name)
save_folder_name = save_base_name + "/%s/" % folder_name
if os.path.isdir(save_folder_name) != True:
os.mkdir(save_folder_name)
print(true_energy[cuts][:10], cnn_energy[cuts][:10])
#plot_NDOMS(true_ndoms[cuts],true_r[cuts])
#plot_NDOMS(true_ndoms[cuts],true_r[cuts],cut=0)
plot_distributions(true_energy[cuts], cnn_energy[cuts], old_reco=retro_energy[cuts],\
save=save, savefolder=save_folder_name, weights=true_weights,\
reco_name = "Retro", variable=plot_name, units= plot_units,
minval=minval,maxval=maxval,bins=bins)
#plot_distributions(true_energy[cuts], cnn_energy[cuts], old_reco=retro_energy[cuts],\
# save=save, savefolder=save_folder_name, weights=true_weights,\
# reco_name = "Retro", variable=plot_name, units= plot_units)
#plot_distributions(true_r[cuts], reco_r[cuts],\
# save=save, savefolder=save_folder_name, weights=true_weights,\
# cnn_name = "Retro", variable="Radial Vertex", units= "(m)",log=True)
plot_distributions(true_z[cuts], reco_z[cuts],\
save=save, savefolder=save_folder_name, weights=true_weights,\
cnn_name = "Retro", variable="Z Vertex", units= "(m)",log=True)
switch = False
plot_2D_prediction(true_energy[cuts], cnn_energy[cuts],weights=true_weights,\
save=save, savefolder=save_folder_name,bins=bins, switch_axis=switch,
variable=plot_name, units=plot_units, reco_name="CNN")
plot_2D_prediction(true_energy[cuts], retro_energy[cuts], weights=true_weights,
plot_2D_prediction(Y_test_use[:,true_index]*maxabs_factor,\
Y_test_predicted[:,NN_index]*maxabs_factor,\
save,save_folder_name,bins=bins,\
minval=minval,maxval=maxval,\
variable=plot_name,units=plot_units)
plot_2D_prediction(Y_test_use[:,true_index]*maxabs_factor, Y_test_predicted[:,NN_index]*maxabs_factor,\
save,save_folder_name,bins=bins,\
minval=None,maxval=None,\
variable=plot_name,units=plot_units)
plot_single_resolution(Y_test_use[:,true_index]*maxabs_factor,\
Y_test_predicted[:,NN_index]*maxabs_factor,\
minaxis=-2*maxval,maxaxis=maxval*2,
save=save,savefolder=save_folder_name,\
variable=plot_name,units=plot_units)
plot_distributions(Y_test_use[:,true_index]*maxabs_factor, Y_test_predicted[:,NN_index]*maxabs_factor,\
save,save_folder_name,\
variable=plot_name,units=plot_units)
plot_bin_slices(Y_test_use[:,true_index]*maxabs_factor, Y_test_predicted[:,NN_index]*maxabs_factor,\
use_fraction = use_frac,\
bins=10,min_val=minval,max_val=maxval,\
save=True,savefolder=save_folder_name,\
variable=plot_name,units=plot_units)
if first_var == "energy" and num ==0:
plot_2D_prediction_fraction(Y_test_use[:,true_index]*maxabs_factor,\
Y_test_predicted[:,NN_index]*maxabs_factor,\
save,save_folder_name,bins=bins,\
minval=0,maxval=2,\
variable=plot_name,units=plot_units)
if num > 0 or first_var == "zenith":
plot_bin_slices(Y_test_use[:,true_index], Y_test_predicted[:,NN_index], \
min_energy = min_energy, max_energy=max_energy, true_energy=Y_test_use[:,0]*max_energy, \