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plot_event.py
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135 lines (129 loc) · 5.59 KB
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import numpy as np
import matplotlib as mpl
from mpl_toolkits.axes_grid1 import make_axes_locatable
mpl.use('TkAgg')
import matplotlib.pyplot as plt
import h5py
import matplotlib.ticker as mtick
def div_5(x, *args):
"""
The function that will you be applied to your y-axis ticks.
"""
x = float(x)/5.0
return "{:.1f}".format(x)
lpv=15
#Event to plot
file='/mnt/extraspace/exet4487/pointrun3/265260186.hdf5'
inputdata = h5py.File(file, 'r')
trainarr = np.asarray(inputdata['peak_times'][:, :, :, :])
trainarr = trainarr[:, :, 8:40, 8:40]
chargearr = np.asarray(inputdata['squared_training'][:, :, :, :])
chargearr = chargearr[:, :, 8:40, 8:40]
rtarr = np.asarray(inputdata['RT'][:, :, :, :])
rtarr = rtarr[:, :, 8:40, 8:40]
ftarr = np.asarray(inputdata['FT'][:, :, :, :])
ftarr = ftarr[:, :, 8:40, 8:40]
fwhmarr = np.asarray(inputdata['FWHM'][:, :, :, :])
fwhmarr = fwhmarr[:, :, 8:40, 8:40]
amparr = np.asarray(inputdata['waveform_amplitude'][:, :, :, :])
amparr = amparr[:, :, 8:40, 8:40]
meanarr = np.asarray(inputdata['waveform_mean'][:, :, :, :])
meanarr = meanarr[:, :, 8:40, 8:40]
rmsarr = np.asarray(inputdata['waveform_rms'][:, :, :, :])
rmsarr = rmsarr[:, :, 8:40, 8:40]
labelsarr = np.asarray(inputdata['event_label'][:])
idarr = np.asarray(inputdata['id'][:])
energy=np.asarray(inputdata['mc_energy'][:].tolist())
inputdata.close()
print(np.where(energy==np.amax(energy)))
eventno=np.where(energy>40000)[0][0]
lendat=len(idarr)
trainarr = np.reshape(trainarr, (lendat, 4, 32, 32, 1))
chargearr = np.reshape(chargearr, (lendat, 4, 32, 32, 1))
rtarr = np.reshape(rtarr, (lendat, 4, 32, 32, 1))
ftarr = np.reshape(ftarr, (lendat, 4, 32, 32, 1))
fwhmarr = np.reshape(fwhmarr, (lendat, 4, 32, 32, 1))
amparr = np.reshape(amparr, (lendat, 4, 32, 32, 1))
meanarr = np.reshape(meanarr, (lendat, 4, 32, 32, 1))
rmsarr = np.reshape(rmsarr, (lendat, 4, 32, 32, 1))
fig,axes=plt.subplots(nrows=2,ncols=4,figsize=(16,8))
# Code to plot waveform parameters.
print(labelsarr[eventno],energy[eventno])
squared=chargearr[eventno,0,:,:,0]
squared=0.01525723*squared-6.20419852
im=axes[0,0].imshow(squared)
axes[0,0].set_title('Charge',size='x-large')
axes[0,0].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[0,0].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
#axes[0,0].axis('off')
cbar=fig.colorbar(im,ax=axes[0,0],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (p.e.)', rotation=270,labelpad=lpv,size='x-large')
ptimes=trainarr[eventno,0,:,:,0]
im=axes[0,1].imshow(ptimes)
axes[0,1].set_title('Peak Time',size='x-large')
axes[0,1].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[0,1].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
#axes[0,1].axis('off')
cbar=fig.colorbar(im,ax=axes[0,1],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Sample)', rotation=270,labelpad=lpv,size='x-large')
meanmat=meanarr[eventno,0,:,:,0]
meanmat=0.01525723*meanmat
im=axes[0,2].imshow(meanmat)
axes[0,2].set_title('Mean Amplitude',size='x-large')
axes[0,2].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[0,2].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
#axes[0,2].axis('off')
cbar=fig.colorbar(im,ax=axes[0,2],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Sample/p.e.)', rotation=270,labelpad=lpv,size='x-large')
ampmat=amparr[eventno,0,:,:,0]
ampmat=0.01525723*ampmat
im=axes[0,3].imshow(ampmat)
axes[0,3].set_title('Peak Amplitude',size='x-large')
#axes[0,3].axis('off')
axes[0,3].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[0,3].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
cbar=fig.colorbar(im,ax=axes[0,3],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Sample/p.e.)', rotation=270,labelpad=lpv,size='x-large')
rmsmat=rmsarr[eventno,0,:,:,0]
rmsmat=0.01525723*rmsmat
im=axes[1,0].imshow(rmsmat)
axes[1,0].set_title('RMS',size='x-large')
#axes[1,0].axis('off')
axes[1,0].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[1,0].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
cbar=fig.colorbar(im,ax=axes[1,0],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Sample/p.e.)', rotation=270,labelpad=lpv,size='x-large')
fwhmmat=fwhmarr[eventno,0,:,:,0]
im=axes[1,1].imshow(fwhmmat)
axes[1,1].set_title('FWHM',size='x-large')
#axes[1,1].axis('off')
axes[1,1].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[1,1].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
cbar=fig.colorbar(im,ax=axes[1,1],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Samples)', rotation=270,labelpad=lpv,size='x-large')
rtmat=rtarr[eventno,0,:,:,0]
im=axes[1,2].imshow(rtmat)
axes[1,2].set_title('RT',size='x-large')
#axes[1,2].axis('off')
axes[1,2].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[1,2].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
cbar=fig.colorbar(im,ax=axes[1,2],fraction=0.046, pad=0.04)
cbar.ax.set_ylabel('Value (Samples)', rotation=270,labelpad=lpv,size='x-large')
ftmat=ftarr[eventno,0,:,:,0]
im=axes[1,3].imshow(ftmat)
axes[1,3].set_title('FT',size='x-large')
cbar=fig.colorbar(im,ax=axes[1,3],fraction=0.046, pad=0.04)
#axes[1,3].axis('off')
cbar.ax.set_ylabel('Value (Samples)', rotation=270,labelpad=lpv,size='x-large')
axes[1,3].yaxis.set_major_formatter(mtick.FuncFormatter(div_5))
axes[1,3].xaxis.set_major_formatter(mtick.FuncFormatter(div_5))
for i, row in enumerate(axes):
for j, cell in enumerate(row):
if i == len(axes) - 1:
cell.set_xlabel("Angular Size ($^\circ$)".format(j + 1),size='x-large')
if j == 0:
cell.set_ylabel("Angular Size ($^\circ$)".format(i + 1),size='x-large')
plt.tight_layout(0.8)
#plt.subplots_adjust(hspace=0.35,
# wspace=0.6)
plt.savefig('56tgamma3.png')