Added Python plotting tools using matplotlib and pickle. Updated ANASEN geometry to better reflect the actual detector setup.

.gitignore

@@ -12,6 +12,7 @@
 .DS_Store
 Makefile
 *.make
+__pycache__
 
 
 ###Keep this file###

bin/.gitignore

@@ -1,3 +1,5 @@
 ###keep only the directory, not the contents###
 *
 !.gitignore
+!PyPlotter
+!PyPlotViewer

bin/PyPlotViewer

@@ -0,0 +1,5 @@
+#!/bin/bash
+
+FileName=$1;
+
+./src/Plotters/Python/ViewPyPlots.py ${FileName}

bin/PyPlotter

@@ -0,0 +1,6 @@
+#!/bin/bash
+
+InputFile=$1;
+OutputFile=$2;
+
+./src/Plotters/Python/PyPlotter.py ${InputFile} ${OutputFile}

etc/mass.txt

@@ -2497,5 +2497,4 @@
  157  108  265 Hs  265 129791.799  
  158  108  266 Hs  266 130045.252  
  159  110  269 Ds  269 144751.021  
- 160  110  270 Ds  270 144583.090  
+ 160  110  270 Ds  270 144583.090
-

include/AnasenEfficiency.h

@@ -43,14 +43,15 @@ private:
 	const int n_qqq = 4;
 	const double sx3_length = 0.075;
 	const double sx3_width = 0.04;
-	const double barrel_gap = 0.013 + 0.049; //0.049 is base gap due to frames
+	const double barrel_gap = 0.0254;
-	const double ring1_z = sx3_length/2.0 + barrel_gap/2.0;
+	const double sx3_frame = 0.049; //0.049 is base gap due to frames
-	//const double ring2_z = -0.124 + sx3_length/2.0 + 0.0245 - barrel_gap/2.0;
+	const double ring1_z = sx3_length/2.0 + sx3_frame + barrel_gap/2.0;
-	const double qqq_nom_z = 0.025 + sx3_length + 0.0245 + barrel_gap/2.0;
+	const double ring2_z = (-1.0)*(barrel_gap/2.0 + sx3_length/2.0);
+	const double qqq_nom_z = 0.0125 + sx3_length + sx3_frame + barrel_gap/2.0;
 	const double qqq_rinner = 0.0501;
 	const double qqq_router = 0.0990;
 	const double qqq_deltaphi = 1.52119;
-	const double qqq_z[4] = {qqq_nom_z, qqq_nom_z - 0.00828, qqq_nom_z, qqq_nom_z};
+	const double qqq_z[4] = {qqq_nom_z, qqq_nom_z, qqq_nom_z, qqq_nom_z};
 	const double qqq_phi[4] = {5.49779, 0.785398, 2.35619, 3.92699};
 	const double ring_rho[12] = {0.0890601, 0.0889871, 0.0890354, 0.0890247, 0.0890354, 0.0890354, 0.0890247, 0.0890354, 0.0890354, 0.0890247, 0.0890354, 0.0890354};
 	const double ring_phi[12] = {0.785795, 0.262014, 6.02132, 5.49779, 4.97426, 4.45052, 3.92699, 3.40346, 2.87972, 2.35619, 1.83266, 1.30893};

input.txt

@@ -1,13 +1,14 @@
 ----------Data Information----------
-OutputFile: /data1/gwm17/mask_tests/7Be12C_870keV_beam_50CD2.mask
+OutputFile: /media/gordon/ANASENData/MaskData/Kinematics/7Bedp_870keV_beam_50CD2.mask
 SaveTree: yes
 SavePlots: yes
 ----------Reaction Information----------
-ReactionType: 1
+ReactionType: 2
 Z	A (order is target, projectile, ejectile, break1, break3(if pure decay is target, ejectile))
-6   12
+1   2
-4	7
 4	7
+1	1
+2   4
 ----------Target Information----------
 Name: test_targ
 Layers: 1

premake5.lua

@@ -44,8 +44,8 @@ project	"RootPlot"
 	}
 
 	--User specified path to ROOT CERN libraries--
-	ROOTIncludepath = "/usr/include/root"
+	ROOTIncludepath = "/home/gordon/cern/root-6.22.02/root-install/include"
-	ROOTLibpath = "/usr/lib64/root"
+	ROOTLibpath = "/home/gordon/cern/root-6.22.02/root-install/lib"
 
 	includedirs {
 		"include"

src/Detectors/AnasenEfficiency.cpp

@@ -9,7 +9,7 @@ AnasenEfficiency::AnasenEfficiency() :
 	for(int i=0; i<n_sx3_per_ring; i++) {
 		m_Ring1.emplace_back(4, sx3_length, sx3_width, ring_phi[i], ring1_z, ring_rho[i]);
 		m_Ring1[i].TurnOnRandomizedCoordinates();
-		m_Ring2.emplace_back(4, sx3_length, sx3_width, ring_phi[i], -1.0*ring1_z, ring_rho[i]);
+		m_Ring2.emplace_back(4, sx3_length, sx3_width, ring_phi[i], ring2_z, ring_rho[i]);
 		m_Ring2[i].TurnOnRandomizedCoordinates();
 	}
 	for(int i=0; i<n_qqq; i++) {
@@ -113,11 +113,9 @@ void AnasenEfficiency::DrawDetectorSystem(const std::string& filename) {
 	}
 
 	output<<"ANASEN Geometry File -- Coordinates for Detectors"<<std::endl;
-	output<<"Edges: x y z"<<std::endl;
 	for(unsigned int i=0; i<x.size(); i++) {
 		output<<x[i]<<" "<<y[i]<<" "<<z[i]<<std::endl;
 	}
-	output<<"Centers: x y z"<<std::endl;
 	for(unsigned int i=0; i<cx.size(); i++) {
 		output<<cx[i]<<" "<<cy[i]<<" "<<cz[i]<<std::endl;
 	}

src/Plotters/Python/.gitignore

@@ -0,0 +1,3 @@
+__pycache__
+
+!.gitignore

src/Plotters/Python/MaskFile.py

@@ -0,0 +1,80 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import struct
+
+class MaskFileData :
+	def __init__(self, n):
+		self.Z = np.zeros(n, dtype=int)
+		self.A = np.zeros(n, dtype=int)
+		self.dFlag = np.zeros(n, dtype=bool)
+		self.E = np.zeros(n)
+		self.KE = np.zeros(n)
+		self.p = np.zeros(n)
+		self.theta = np.zeros(n)
+		self.phi = np.zeros(n)
+
+class MaskFile:
+	int_size = 4
+	double_size = 8
+	bool_size = 1
+
+	def __init__(self, filename=""):
+		self.eofFlag = False
+		self.openFlag = False
+		if filename != "" :
+			self.Open(filename)
+
+	def Open(self, filename):
+		self.filename = filename
+		self.file = open(self.filename, mode="rb")
+		if self.file.closed  :
+			self.openFlag = False
+		else:
+			self.openFlag = True
+
+	def ReadHeader(self):
+		data = self.file.read(2*self.int_size)
+
+		(self.nsamples, self.rxntype) = struct.unpack("ii", data)
+		self.datasize = (5*self.double_size+2*self.int_size+self.bool_size)
+		self.datastr = "=ii?ddddd"
+
+		if self.rxntype == 0:
+			self.N_nuclei = 3
+		elif self.rxntype == 1:
+			self.N_nuclei = 4
+		elif self.rxntype == 2:
+			self.N_nuclei = 6
+		elif self.rxntype == 3:
+			self.N_nuclei = 8
+
+	def ReadData(self):
+		data = MaskFileData(self.N_nuclei)
+		for i in range(self.N_nuclei):
+			buffer = self.file.read(self.datasize)
+			(data.Z[i], data.A[i], data.dFlag[i], data.E[i], data.KE[i], data.p[i], data.theta[i], data.phi[i]) = struct.unpack(self.datastr, buffer)
+		if buffer == "":
+			self.eofFlag = True
+
+		return data
+
+	def Close(self):
+		self.file.close()
+
+def main() :
+	file = MaskFile(filename="/data1/gwm17/mask_tests/7Bedp_870keV_beam_50CD2.mask")
+	file.ReadHeader()
+	print("samples: ", file.nsamples, "rxntype:", file.rxntype, "datasize:", file.datasize)
+	count=0
+	for i in range(file.nsamples):
+		file.ReadData()
+		count += 1
+
+	print("count:",count)
+	print("eofFlag:",file.eofFlag)
+
+	file.Close()
+
+if __name__ == '__main__':
+	main()

src/Plotters/Python/NucData.py

@@ -0,0 +1,70 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import requests
+import lxml.html as xhtml
+
+
+class MassTable:
+	def __init__(self):
+		file = open("./etc/mass.txt","r")
+		self.mtable = {}
+		u2mev = 931.4940954
+		me = 0.000548579909 #amu
+		self.etable = {}
+
+		line = file.readline()
+		line = file.readline()
+
+		for line in file:
+			entries = line.split()
+			n = entries[0]
+			z = entries[1]
+			a = entries[2]
+			element = entries[3]
+			massBig = float(entries[4])
+			massSmall = float(entries[5])
+
+			key = '('+z+','+a+')'
+			value = ((massBig+massSmall*1e-6) - float(z)*me)*u2mev
+			self.mtable[key] = value
+			self.etable[key] = element
+		file.close()
+
+	def GetMass(self, z, a):
+		key = '('+str(z)+','+str(a)+')'
+		if key in self.mtable:
+			return self.mtable[key]
+		else:
+			return 0
+
+	def GetSymbol(self, z, a):
+		key = '('+str(z)+','+str(a)+')'
+		if key in self.etable:
+			return str(a)+self.etable[key]
+		else:
+			return 'none'
+
+Masses = MassTable()
+
+def GetExcitations(symbol):
+	levels = np.array(np.empty(0))
+	text = ''
+
+	site = requests.get("https://www.nndc.bnl.gov/nudat2/getdatasetClassic.jsp?nucleus="+symbol+"&unc=nds")
+	contents = xhtml.fromstring(site.content)
+	tables = contents.xpath("//table")
+	rows = tables[2].xpath("./tr")
+	for row in rows[1:-2]:
+		entries = row.xpath("./td")
+		if len(entries) != 0:
+			entry = entries[0]
+			data = entry.xpath("./a")
+			if len(data) == 0:
+				text = entry.text
+			else:
+				text = data[0].text
+			text = text.replace('?', '')
+			text = text.replace('\xa0\xa0≈','')
+			levels = np.append(levels, float(text)/1000.0)
+	return levels

src/Plotters/Python/Nucleus.py

@@ -0,0 +1,106 @@
+#!/usr/bin/env python3
+
+import numpy as np
+from NucData import Masses
+
+class Nucleus:
+	deg2rad = np.pi/180.0
+	def __init__(self, Z=0, A=0):
+		self.Z = Z
+		self.A = A
+		if Z != 0 and A != 0:
+			self.gsMass = Masses.GetMass(self.Z, self.A)
+			self.vec4 = np.zeros(4)
+			self.symbol = Masses.GetSymbol(self.Z, self.A)
+			self.vec4[3] = self.gsMass
+
+	def SetIsotope(self, Z, A):
+		self.gsMass = Masses.GetMass(Z, A)
+		self.symbol = Masses.GetSymbol(Z, A)
+		self.Z = Z
+		self.A = A
+		self.vec4 = np.zeros(4)
+		self.vec4[3] = self.gsMass
+
+	def SetVectorCart(self, px, py, pz, E):
+		self.vec4[0] = px
+		self.vec4[1] = py
+		self.vec4[2] = pz
+		self.vec4[3] = E
+
+	def SetVectorSpher(self, theta, phi, p, E):
+		self.vec4[0] = p*np.sin(theta)*np.cos(phi)
+		self.vec4[1] = p*np.sin(theta)*np.sin(phi)
+		self.vec4[2] = p*np.cos(theta)
+		self.vec4[3] = E
+
+	def __add__(self, other):
+		vec4 = self.vec4 + other.vec4
+		newNuc = Nucleus(self.Z + other.Z, self.A + other.A)
+		newNuc.SetVectorCart(vec4[0], vec4[1], vec4[2], vec4[3])
+		return newNuc
+
+	def __sub__(self, other):
+		vec4 = self.vec4 - other.vec4
+		newNuc = Nucleus(self.Z - other.Z, self.A - other.A)
+		newNuc.SetVectorCart(vec4[0], vec4[1], vec4[2], vec4[3])
+		return newNuc
+
+	def __str__(self):
+		return "Nucleus({0},{1}) with 4-vector({2})".format(self.Z, self.A, self.vec4)
+
+	def GetP(self):
+		return np.sqrt(self.vec4[0]**2.0 + self.vec4[1]**2.0 + self.vec4[2]**2.0)
+
+	def GetInvMass(self):
+		return np.sqrt(self.vec4[3]**2.0 - self.GetP()**2.0)
+
+	def GetKE(self):
+		return self.vec4[3] - self.GetInvMass()
+
+	def GetTheta(self):
+		return np.arccos(self.vec4[2]/self.GetP())
+
+	def GetPhi(self):
+		result = np.arctan2(self.vec4[1], self.vec4[0])
+		if result < 0.0:
+			result += 2.0*np.pi
+		return result
+
+	def GetExcitation(self):
+		return self.GetInvMass() - self.gsMass
+
+	def GetBoostToCMFrame(self):
+		boost_vec = np.zeros(3)
+		boost_vec[0] = self.vec4[0]/self.vec4[3]
+		boost_vec[1] = self.vec4[1]/self.vec4[3]
+		boost_vec[2] = self.vec4[2]/self.vec4[3]
+		return boost_vec
+
+	def ApplyBoost(self, boost_vec):
+		beta2 = np.linalg.norm(boost_vec)**2.0
+		gamma  = 1.0/np.sqrt(1.0 - beta2)
+		bdotp = boost_vec[0]*self.vec4[0] + boost_vec[1]*self.vec4[1] + boost_vec[2]*self.vec4[2]
+		gfactor = (gamma-1.0)/beta2 if beta2 > 0.0 else 0.0
+
+		px = self.vec4[0]+gfactor*bdotp*boost_vec[0]+gamma*boost_vec[0]*self.vec4[3]
+		py = self.vec4[1]+gfactor*bdotp*boost_vec[1]+gamma*boost_vec[1]*self.vec4[3]
+		pz = self.vec4[2]+gfactor*bdotp*boost_vec[2]+gamma*boost_vec[2]*self.vec4[3]
+		E = gamma*(self.vec4[3] + bdotp)
+	
+		self.SetVectorCart(px, py, pz, E);
+
+
+def main():
+	nuc = Nucleus(1,1)
+	print("First",nuc)
+	nuc2 = Nucleus(2,4)
+	print("Second", nuc2)
+	result = nuc + nuc2
+	print("Addition", result)
+	result2 = nuc2 - nuc
+	print("Subtraction", result2)
+
+
+if __name__ == '__main__':
+	main()

src/Plotters/Python/PyPlotter.py

@@ -0,0 +1,135 @@
+#!/usr/bin/env python3
+
+import numpy as np
+import matplotlib.pyplot as plt
+from Nucleus import Nucleus
+from MaskFile import MaskFile, MaskFileData
+from NucData import Masses
+import pickle
+import sys
+
+def PlotData(inputname, outputname):
+	rad2deg = 180.0/np.pi
+
+	datafile = MaskFile(inputname)
+	datafile.ReadHeader()
+
+	print("MaskFile opened -- rxntype:", datafile.rxntype, "number of samples:", datafile.nsamples)
+
+	data = MaskFileData(datafile.N_nuclei)
+
+	ke = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	ke_d = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	theta = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	theta_d = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	phi = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	phi_d = np.zeros((datafile.N_nuclei, datafile.nsamples))
+	detect_mask = np.ones((datafile.N_nuclei, datafile.nsamples), dtype=bool)
+	names = []
+	for i in range(datafile.N_nuclei):
+		names.append(" ")
+
+	nuc = Nucleus()
+
+	for i in range(datafile.nsamples):
+		data = datafile.ReadData()
+
+		if i == 0:
+			for j in range(datafile.N_nuclei):
+				names[j] = Masses.GetSymbol(data.Z[j], data.A[j])
+
+		for j in range(datafile.N_nuclei):
+			nuc.SetIsotope(data.Z[j], data.A[j])
+			nuc.SetVectorSpher(data.theta[j], data.phi[j], data.p[j], data.E[j])
+
+			ke[j][i] = nuc.GetKE()
+			theta[j][i] = data.theta[j]*rad2deg
+			phi[j][i] = data.phi[j]*rad2deg
+			if data.dFlag[j] == True:
+				ke_d[j][i] = data.KE[j]
+				theta_d[j][i] = data.theta[j]*rad2deg
+				phi_d[j][i] = data.phi[j]*rad2deg
+			else:
+				detect_mask[j][i] = False
+
+	datafile.Close()
+
+	#Remove empty values from detection arrays
+	final_theta_d = theta_d[detect_mask]
+	final_phi_d = phi_d[detect_mask]
+	final_ke_d = ke_d[detect_mask]
+
+	#figs = {}
+	#axes = {}
+
+	'''
+	for i in range(len(names)):
+		figs[i], axes[i] = plt.subplots(2,2)
+	'''
+	fig, axes = plt.subplots(len(names)-1,4)
+	fig.set_size_inches(12, 12)
+
+	for i in range(1, len(names)):
+		'''
+		axes[i][0][0].plot(theta[i], ke[i], marker=',', linestyle='None')
+		axes[i][0][0].set_title(names[i]+" KE vs. Theta")
+		axes[i][0][0].set_xlabel(r"$\theta$ (degrees)")
+		axes[i][0][0].set_ylabel("KE (MeV)")
+
+		axes[i][0][1].plot(phi[i], ke[i], marker=",", linestyle='None')
+		axes[i][0][1].set_title(names[i]+" KE vs. Phi")
+		axes[i][0][1].set_xlabel(r"$\phi$ (degrees)")
+		axes[i][0][1].set_ylabel("KE (MeV)")
+
+		axes[i][1][0].plot(theta_d[i], ke_d[i], marker=',', linestyle='None')
+		axes[i][1][0].set_title(names[i]+" KE vs. Theta -- Detected")
+		axes[i][1][0].set_xlabel(r"$\theta$ (degrees)")
+		axes[i][1][0].set_ylabel("KE (MeV)")
+
+		axes[i][1][1].plot(phi_d[i], ke_d[i], marker=",", linestyle='None')
+		axes[i][1][1].set_title(names[i]+" KE vs. Phi -- Detected")
+		axes[i][1][1].set_xlabel(r"$\phi$ (degrees)")
+		axes[i][1][1].set_ylabel("KE (MeV)")
+		'''
+
+		axes[i-1][0].plot(theta[i], ke[i], marker=',', linestyle='None')
+		axes[i-1][0].set_title(names[i]+" KE vs. Theta")
+		axes[i-1][0].set_xlabel(r"$\theta$ (degrees)")
+		axes[i-1][0].set_ylabel("KE (MeV)")
+
+		axes[i-1][1].plot(phi[i], ke[i], marker=",", linestyle='None')
+		axes[i-1][1].set_title(names[i]+" KE vs. Phi")
+		axes[i-1][1].set_xlabel(r"$\phi$ (degrees)")
+		axes[i-1][1].set_ylabel("KE (MeV)")
+
+		axes[i-1][2].plot(theta_d[i], ke_d[i], marker=',', linestyle='None')
+		axes[i-1][2].set_title(names[i]+" KE vs. Theta -- Detected")
+		axes[i-1][2].set_xlabel(r"$\theta$ (degrees)")
+		axes[i-1][2].set_ylabel("KE (MeV)")
+
+		axes[i-1][3].plot(phi_d[i], ke_d[i], marker=",", linestyle='None')
+		axes[i-1][3].set_title(names[i]+" KE vs. Phi -- Detected")
+		axes[i-1][3].set_xlabel(r"$\phi$ (degrees)")
+		axes[i-1][3].set_ylabel("KE (MeV)")
+
+	plt.tight_layout()
+	plt.show(block=True)
+
+	print("Writing figure to file:", outputname)
+	with open(outputname, "wb") as outfile:
+		pickle.dump(fig, outfile)
+		outfile.close()
+
+	print("Finished.")
+
+def main():
+	if len(sys.argv) == 3:
+		PlotData(sys.argv[1], sys.argv[2])
+	else:
+		print("Unable to run PyPlotter, incorrect number of arguments! Need an input datafile name, and an output plot file name")
+
+if __name__ == '__main__':
+	main()
+
+
+

src/Plotters/Python/ViewPyPlots.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python3
+
+import matplotlib.pyplot as plt
+import numpy as np
+import pickle
+import sys
+
+def SetManager(figure):
+	dummy = plt.figure()
+	manager = dummy.canvas.manager
+	manager.canvas.figure = figure
+	figure.set_canvas(manager.canvas)
+
+def ViewPyPlots(filename):
+
+	figure = pickle.load(open(filename, "rb"))
+	SetManager(figure)
+
+	figure.set_size_inches(12, 12)
+	plt.tight_layout()
+
+	plt.show(block=True)
+
+
+def main():
+	if len(sys.argv) == 2:
+		ViewPyPlots(sys.argv[1])
+	else:
+		print("Unable to run ViewPyPlots, incorrect number of commandline arguments -- requires an input pickle file")
+
+if __name__ == '__main__':
+	main()