def run():
# import data and plotting packages
fig1 = plt.figure(1)
ax1 = fig1.add_subplot(111,projection='3d')
fig2 = plt.figure(2)
ax2 = fig2.add_subplot(111,projection='3d')
fig3 = plt.figure(3)
ax3 = fig3.add_subplot(111,projection='3d')
def fittedline(xo,yo,zo,xn,yn,zn):
x = np.linspace(xo,xn,100)
y = np.linspace(yo,yn,100)
z = np.linspace(zo,zn,100)
ax2.plot(x, y, z, c='b', linewidth = 2)
ax3.plot(x, y, z, c='b', linewidth = 2)
# ========================================
#hp_filter=2 # high pass filter takes out points with adc< value
# user input: event
prompt1 = 'Hi!\nEnter number of event (from 0 to 99) you would like to see:\n >'
event = int(raw_input(prompt1))
#event=4
# ========================================
event_lists = ef.separateData(event, pkg, 'NIFFTE-alphas.dat')
xi,yi,zi =[],[],[]
xs,ys,zs=[],[],[]
i = 0
points_fitted_start=[]
points_fitted_end=[]
for i in range(0,len(event_lists)): # for each point in event
if len(event_lists[i]) > 4:
(A,B) = fl.bestline(event_lists[i],acc=0.01,partition=4,recurse='half')
points_fitted_start.append(A)
points_fitted_end.append(B)
ii=0
while ii < len(points_fitted_start):
fittedline(points_fitted_start[ii].x,points_fitted_start[ii].y,points_fitted_start[ii].z,points_fitted_end[ii].x,points_fitted_end[ii].y,points_fitted_end[ii].z)
ii += 1
xm,ym,zm=[],[],[]
for q in range(len(pkg[event])):
xm.append(pkg[event][q].x)
ym.append(pkg[event][q].y)
zm.append(pkg[event][q].z)
# plotting these new scatter points
ax1.scatter(xm,ym,zm,c='g',marker='^')
ax1.set_xlim(-6, 6)
ax1.set_ylim(-6, 6)
ax1.set_zlim(-6, 6)
ax1.set_xlabel('X (cm)')
ax1.set_ylabel('Y (cm)')
ax1.set_zlabel('Z (cm)')
ax1.set_title('Event '+str(event)+' all data')
for q in range(len(event_lists)):
for i in range(len(event_lists[q])):
xs.append(event_lists[q][i].x)
ys.append(event_lists[q][i].y)
zs.append(event_lists[q][i].z)
# plotting these new scatter points
ax2.scatter(xs,ys,zs,c='k',marker='o')
ax3.scatter(xs,ys,zs,c='k',marker='o')
#ax2.set_xlim(-.01, .01)
#ax2.set_ylim(-.01, .01)
#ax2.set_zlim(-.01, .01)
ax2.set_xlim(-6, 6)
ax2.set_ylim(-6, 6)
ax2.set_zlim(-6, 6)
ax2.set_xlabel('X (cm)')
ax2.set_ylabel('Y (cm)')
ax2.set_zlabel('Z (cm)')
ax2.set_title('Event '+str(event) + ' fitted')
ax3.set_title('Event '+str(event) + ' zoomed')
print 'Event',event,'\n'
print len(xm), len(xs)
print "x range =",min(xm),",", max(xm)
print "y range =",min(ym),",", max(ym)
print "z range =",min(zm),",", max(zm)
print '==================================\n'
print "Data is given as 2 points on the fit line"
print "Format (x, y, z, 0.00)"
iii=0
while iii < len(points_fitted_start):
print "Fit #",iii, points_fitted_start[iii],points_fitted_end[iii]
iii += 1
pfs = points_fitted_start
pfe = points_fitted_end
filenme = 'output' + str(event) + '.txt'
FILE = open(filenme,'w')
ev = '##### Event ' + str(event) +'\n'
FILE.write(ev)
sp = ' '
nl = '\n'
index = 0
for i in range(len(event_lists)):
if len(event_lists[i]) > 4:
tempstr = '####Fit list #' + str(index + 1) + '\n'
FILE.write(tempstr)
tempstr = '####Fit points: \n'
FILE.write(tempstr)
tempstr = '###(' + str(pfs[index].x) + ',' + str(pfs[index].y) + ',' + str(pfs[index].z) + ')\n'
FILE.write(tempstr)
tempstr = '###(' + str(pfe[index].x) + ',' + str(pfe[index].y) + ',' + str(pfe[index].z) + ')\n'
FILE.write(tempstr)
tempstr = '#Data!\n'
FILE.write(tempstr)
for j in range(len(event_lists[i])):
dg = str(event_lists[i][j].x) + sp + str(event_lists[i][j].y) + sp + str(event_lists[i][j].z) + sp + str(event_lists[i][j].adc) + nl
FILE.write(dg)
index += 1
f = FILE.close()
plt.show()
def run():
# import data and plotting packages
fig1 = plt.figure(1)
ax1 = fig1.add_subplot(111,projection='3d')
fig2 = plt.figure(2)
ax2 = fig2.add_subplot(111,projection='3d')
def fittedline(xo,yo,zo,xn,yn,zn):
x = np.linspace(xo,xn,100)
y = np.linspace(yo,yn,100)
z = np.linspace(zo,zn,100)
ax2.plot(x, y, z, c='b')
# ========================================
#hp_filter=2 # high pass filter takes out points with adc< value
# user input: event
prompt1 = 'Hi!\nEnter number of event (from 0 to 99) you would like to see:\n >'
event = int(raw_input(prompt1))
#event=4
# ========================================
event_lists = ef.separateData(event, pkg, 'NIFFTE-alphas.dat')
xi,yi,zi =[],[],[]
xs,ys,zs=[],[],[]
i = 0
points_fitted_start=[]
points_fitted_end=[]
for i in range(0,len(event_lists)): # for each point in event
(A,B) = fl.bestline(event_lists[i],acc=0.01,partition=4,recurse='half')
points_fitted_start.append(A)
points_fitted_end.append(B)
ii=0
while ii < len(event_lists):
fittedline(points_fitted_start[ii].x,points_fitted_start[ii].y,points_fitted_start[ii].z,points_fitted_end[ii].x,points_fitted_end[ii].y,points_fitted_end[ii].z)
ii += 1
xm,ym,zm=[],[],[]
for q in range(len(pkg[event])):
xm.append(pkg[event][q].x)
ym.append(pkg[event][q].y)
zm.append(pkg[event][q].z)
# plotting these new scatter points
ax1.scatter(xm,ym,zm,c='g',marker='^')
ax1.set_xlim(-6, 6)
ax1.set_ylim(-6, 6)
ax1.set_zlim(-6, 6)
ax1.set_xlabel('X (cm)')
ax1.set_ylabel('Y (cm)')
ax1.set_zlabel('Z (cm)')
ax1.set_title('Event '+str(event))
for q in range(len(event_lists)):
xs.append(event_lists[0][q].x)
ys.append(event_lists[0][q].y)
zs.append(event_lists[0][q].z)
# plotting these new scatter points
ax2.scatter(xm,ym,zm,c='r',marker='o')
#ax2.set_xlim(-.01, .01)
#ax2.set_ylim(-.01, .01)
#ax2.set_zlim(-.01, .01)
ax2.set_xlim(-6, 6)
ax2.set_ylim(-6, 6)
ax2.set_zlim(-6, 6)
ax2.set_xlabel('X (cm)')
ax2.set_ylabel('Y (cm)')
ax2.set_zlabel('Z (cm)')
ax2.set_title('Event '+str(event))
print 'Event',event,'\n'
print "x range =",min(xm),",", max(xm)
print "y range =",min(ym),",", max(ym)
print "z range =",min(zm),",", max(zm)
plt.show()
