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fixed memory issues and dual plotting

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This commit is contained in:
James Szalkie 2026-05-26 10:55:34 -04:00
parent b1a53e9047
commit f001bb21e0
2 changed files with 811 additions and 521 deletions
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1000
ELoss/E_vs_x_proton.dat
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332
ELoss/PCEnergyAnalysis.py
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@ -8,16 +8,12 @@ Created on Wed May 20 13:32:14 2026
import numpy as np
import pandas as pd
from scipy.interpolate import interp1d
import argparse
import uproot
import pycatima as catima
from scipy.integrate import cumulative_trapezoid
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import threading
import time
import sys
import cmd
import shlex
import textwrap
@ -26,17 +22,18 @@ import atexit
import os
import periodictable as pt
import re
from matplotlib.colors import PowerNorm
#Run program from terminal or IDE, and prompts will provide user steps
histfile = os.path.expanduser("~/.uproot_shell_history")
#histfile = os.path.expanduser("~/.uproot_shell_history")
try:
readline.read_history_file(histfile)
except FileNotFoundError:
pass
#try:
# readline.read_history_file(histfile)
#except FileNotFoundError:
# pass
atexit.register(readline.write_history_file, histfile)
#atexit.register(readline.write_history_file, histfile)
#data = [z, mass_u, maximum MeV, name]
alpha_data = [2, 4.0026, 40, "alpha"]
@ -254,6 +251,69 @@ def resolve_particle(name):
raise ValueError(f"Unknown particle/isotope: {name}")
def update_plot_data(name, values):
for i, (existing_name, _) in enumerate(plot_data):
if existing_name == name:
plot_data[i] = (name, values)
return
plot_data.append((name, values))
def process_file(filename):
tree = uproot.open(filename)["tree"]
branches = ["Tb", "thetab", "sx3Z"]
data = tree.arrays(branches, library="np")
Ei = data["Tb"]
theta = np.radians(data["thetab"])
sx3Z = data["sx3Z"]
mask = np.sin(theta) != 0
Ei = Ei[mask]
theta = theta[mask]
sx3Z = sx3Z[mask]
sin_theta = np.sin(theta)
radii = np.array([3.2, 4.2, 6.6])
dA = radii[0] / sin_theta
dC = radii[1] / sin_theta
dsx3 = radii[2] / sin_theta
# Determine particle from filename
lower = filename.lower()
if "proton" in lower:
particle = "proton"
elif "alpha" in lower:
particle = "alpha"
else:
particle = "proton"
print(f"Computing energies for {particle}...")
EA = energy_loss(particle, Ei, dA)
EC = energy_loss(particle, Ei, dC)
Esx3 = energy_loss(particle, Ei, dsx3)
Elost = Ei - Esx3
Eprop = EA - EC
return {
"particle": particle,
"Ei": Ei,
"sx3Z": sx3Z,
"EA": EA,
"EC": EC,
"Esx3": Esx3,
"Elost": Elost,
"Eprop": Eprop
}
class MyInteractiveApp(cmd.Cmd):
def __init__(self):
super().__init__()
@ -405,11 +465,28 @@ class MyInteractiveApp(cmd.Cmd):
plt.figure(figsize=(8,6))
plt.plot(x, E)
plt.xlabel("Distance (cm)")
plt.ylabel("Energy (MeV)")
plt.title(f"Energy Loss Curve {label.capitalize()}")
plt.grid(True)
plt.show()
textstr = f"T = {self.T:.2f} K\nP = {self.P:.2f} Torr"
plt.gca().text(
0.02, 0.02,
textstr,
transform=plt.gca().transAxes,
fontsize=10,
verticalalignment='bottom',
bbox=dict(boxstyle="round", facecolor="white", alpha=0.7)
)
plt.tight_layout()
filename = f"Energy_Loss_Curve_{label}.png"
plt.savefig(filename, dpi=300, bbox_inches="tight")
plt.close()
print(f"Saved plot: {filename}")
except Exception as e:
print(f"Error in make_table: {e}")
@ -756,6 +833,10 @@ class MyInteractiveApp(cmd.Cmd):
import os
global plot_data
plot_data = []
args = shlex.split(arg)
particle = args[0] if len(args) > 0 else "proton"
@ -783,6 +864,9 @@ class MyInteractiveApp(cmd.Cmd):
theta = theta[mask]
sx3Z = sx3Z[mask]
update_plot_data(f"{particle}_Ei", Ei)
update_plot_data(f"{particle}_sx3Z", sx3Z)
sin_theta = np.sin(theta)
radii = np.array([3.2, 4.2, 6.6])
@ -800,6 +884,12 @@ class MyInteractiveApp(cmd.Cmd):
Elost = Ei - Esx3
Eprop = EA - EC
update_plot_data(f"{particle}_EA", EA)
update_plot_data(f"{particle}_EC", EC)
update_plot_data(f"{particle}_Esx3", Esx3)
update_plot_data(f"{particle}_Elost", Elost)
update_plot_data(f"{particle}_Eprop", Eprop)
base = f"{particle}_plots"
os.makedirs(base, exist_ok=True)
@ -810,29 +900,29 @@ class MyInteractiveApp(cmd.Cmd):
plt.hist(Elost, bins=200)
plt.xlabel("Energy Loss (MeV)")
plt.ylabel("Counts")
plt.title("Total Energy Loss Distribution")
plt.title(f"{particle} Total Energy Loss Distribution")
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{base}/Elost_hist.png", dpi=300)
plt.close()
# 2. Histogram: sx3Z
#Histogram: sx3Z
plt.figure(figsize=(7,5))
plt.hist(sx3Z, bins=100)
plt.xlabel("SX3 Z")
plt.ylabel("Counts")
plt.title("SX3 Position Distribution")
plt.title(f"{particle} SX3 Position Distribution")
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{base}/sx3Z_hist.png", dpi=300)
plt.close()
# 3. 2D: Elost vs sx3Z
#2D: Elost vs sx3Z
plt.figure(figsize=(7,6))
plt.hist2d(Elost, sx3Z, bins=200)
plt.xlabel("Energy Loss (MeV)")
plt.ylabel("SX3 Z")
plt.title("Energy Loss vs SX3 Position")
plt.hist2d(sx3Z, Elost, bins=200)
plt.ylabel("Energy Loss (MeV)")
plt.xlabel("SX3 Z")
plt.title(f"{particle} Energy Loss vs SX3 Position")
plt.colorbar(label="Counts")
plt.tight_layout()
plt.savefig(f"{base}/Elost_vs_sx3Z.png", dpi=300)
@ -843,7 +933,7 @@ class MyInteractiveApp(cmd.Cmd):
plt.hist2d(EA, Esx3, bins=200)
plt.xlabel("EA (MeV)")
plt.ylabel("Esx3 (MeV)")
plt.title("Anode vs SX3 Energy")
plt.title(f"{particle} Anode vs SX3 Energy")
plt.colorbar(label="Counts")
plt.tight_layout()
plt.savefig(f"{base}/EA_vs_Esx3.png", dpi=300)
@ -854,14 +944,214 @@ class MyInteractiveApp(cmd.Cmd):
plt.hist2d(Eprop, sx3Z, bins=200)
plt.xlabel("EA - EC (MeV)")
plt.ylabel("SX3 Z")
plt.title("Energy Propagation Difference vs Position")
plt.title(f"{particle} Energy Propagation Difference vs Position")
plt.colorbar(label="Counts")
plt.tight_layout()
plt.savefig(f"{base}/Eprop_vs_sx3Z.png", dpi=300)
plt.close()
plt.figure(figsize=(7,6))
plt.hist2d(Esx3, Eprop, bins=200)
plt.ylabel("PCEnergy")
plt.xlabel("SX3 Energy (MeV)")
plt.title(f"{particle} Energy Propagation Difference vs sx3 Energy")
plt.colorbar(label="Counts")
plt.xlim(0,30)
plt.ylim(0,.45)
plt.tight_layout()
plt.savefig(f"{base}/Eprop_vs_Esx3.png", dpi=300)
plt.close()
print("Plotting complete.")
def do_dual_plotter(self, arg):
args = shlex.split(arg)
if len(args) < 2:
print("Usage: make dual plots proton_data.root alpha_data.root")
return
file1 = args[0]
file2 = args[1]
#Helper function
#Process both files
data1 = process_file(f"../Armory/{file1}")
data2 = process_file(f"../Armory/{file2}")
outdir = "dual_plots"
os.makedirs(outdir, exist_ok=True)
print(f"Saving plots to: {outdir}")
#Overlay histogram: Elost
plt.figure(figsize=(8,6))
plt.hist(
data1["Elost"],
bins=200,
histtype='step',
linewidth=2,
density=True,
label=data1["particle"]
)
plt.hist(
data2["Elost"],
bins=200,
histtype='step',
linewidth=2,
density=True,
label=data2["particle"]
)
plt.xlabel("Energy Loss (MeV)")
plt.ylabel("Normalized Counts")
plt.title("Energy Loss Comparison")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{outdir}/Elost_overlay.png", dpi=300)
plt.close()
#Overlay histogram: sx3Z
plt.figure(figsize=(8,6))
plt.hist(
data1["sx3Z"],
bins=150,
histtype='step',
linewidth=2,
density=True,
label=data1["particle"]
)
plt.hist(
data2["sx3Z"],
bins=150,
histtype='step',
linewidth=2,
density=True,
label=data2["particle"]
)
plt.xlabel("SX3 Z")
plt.ylabel("Normalized Counts")
plt.title("SX3 Position Comparison")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{outdir}/sx3Z_overlay.png", dpi=300)
plt.close()
#Side-by-side 2D plots
fig, axes = plt.subplots(1, 2, figsize=(14,6))
h1 = axes[0].hist2d(
data1["sx3Z"],
data1["Elost"],
bins=200
)
axes[0].set_title(f'{data1["particle"]} Elost vs SX3')
axes[0].set_xlabel("SX3 Z")
axes[0].set_ylabel("Energy Loss (MeV)")
h2 = axes[1].hist2d(
data2["sx3Z"],
data2["Elost"],
bins=200
)
axes[1].set_title(f'{data2["particle"]} Elost vs SX3')
axes[1].set_xlabel("SX3 Z")
axes[1].set_ylabel("Energy Loss (MeV)")
fig.colorbar(h1[3], ax=axes[0], label="Counts")
fig.colorbar(h2[3], ax=axes[1], label="Counts")
plt.tight_layout()
plt.savefig(f"{outdir}/Elost_vs_sx3_comparison.png", dpi=300)
plt.close()
#EA vs Esx3 overlay scatter
plt.figure(figsize=(8,6))
plt.scatter(
data1["EA"],
data1["Esx3"],
s=1,
alpha=0.3,
label=data1["particle"]
)
plt.scatter(
data2["EA"],
data2["Esx3"],
s=1,
alpha=0.3,
label=data2["particle"]
)
plt.xlabel("EA (MeV)")
plt.ylabel("Esx3 (MeV)")
plt.title("Anode vs SX3 Energy")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.savefig(f"{outdir}/EA_vs_Esx3_overlay.png", dpi=300)
plt.close()
#PCE vs SiE
combined_Esx3 = np.concatenate([
data1["Esx3"],
data2["Esx3"]
])
combined_Eprop = np.concatenate([
data1["Eprop"],
data2["Eprop"]
])
plt.figure(figsize=(7,6))
plt.hist2d(
combined_Esx3,
combined_Eprop,
bins=100,
range=[[0,30],[0,0.45]],
cmap='viridis' # same default matplotlib style
)
plt.ylabel("PCEnergy")
plt.xlabel("SX3 Energy (MeV)")
plt.title(
f'{data1["particle"]} + {data2["particle"]} '
'Energy Propagation Difference vs SX3 Energy'
)
plt.colorbar(label="Counts")
plt.xlim(0,30)
plt.ylim(0,0.45)
plt.tight_layout()
plt.savefig(f"{outdir}/Combined_Eprop_vs_Esx3.png", dpi=300)
plt.close()
print("Dual plotting complete.")
#exec(open("PCEnergyAnalysis.py").read())
if __name__ == "__main__":