fixed memory issues and dual plotting
This commit is contained in:
James Szalkie
parent
b1a53e9047
commit
f001bb21e0
File diff suppressed because it is too large
Load Diff
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@ -8,16 +8,12 @@ Created on Wed May 20 13:32:14 2026
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import numpy as np
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import pandas as pd
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from scipy.interpolate import interp1d
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import argparse
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import uproot
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import pycatima as catima
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from scipy.integrate import cumulative_trapezoid
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import matplotlib
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matplotlib.use("Agg")
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import matplotlib.pyplot as plt
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import threading
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import time
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import sys
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import cmd
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import shlex
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import textwrap
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@ -26,17 +22,18 @@ import atexit
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import os
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import periodictable as pt
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import re
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from matplotlib.colors import PowerNorm
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#Run program from terminal or IDE, and prompts will provide user steps
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histfile = os.path.expanduser("~/.uproot_shell_history")
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#histfile = os.path.expanduser("~/.uproot_shell_history")
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try:
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readline.read_history_file(histfile)
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except FileNotFoundError:
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pass
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#try:
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# readline.read_history_file(histfile)
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#except FileNotFoundError:
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# pass
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atexit.register(readline.write_history_file, histfile)
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#atexit.register(readline.write_history_file, histfile)
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#data = [z, mass_u, maximum MeV, name]
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alpha_data = [2, 4.0026, 40, "alpha"]
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@ -253,6 +250,69 @@ def resolve_particle(name):
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except Exception:
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raise ValueError(f"Unknown particle/isotope: {name}")
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def update_plot_data(name, values):
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for i, (existing_name, _) in enumerate(plot_data):
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if existing_name == name:
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plot_data[i] = (name, values)
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return
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plot_data.append((name, values))
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def process_file(filename):
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tree = uproot.open(filename)["tree"]
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branches = ["Tb", "thetab", "sx3Z"]
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data = tree.arrays(branches, library="np")
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Ei = data["Tb"]
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theta = np.radians(data["thetab"])
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sx3Z = data["sx3Z"]
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mask = np.sin(theta) != 0
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Ei = Ei[mask]
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theta = theta[mask]
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sx3Z = sx3Z[mask]
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sin_theta = np.sin(theta)
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radii = np.array([3.2, 4.2, 6.6])
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dA = radii[0] / sin_theta
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dC = radii[1] / sin_theta
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dsx3 = radii[2] / sin_theta
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# Determine particle from filename
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lower = filename.lower()
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if "proton" in lower:
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particle = "proton"
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elif "alpha" in lower:
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particle = "alpha"
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else:
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particle = "proton"
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print(f"Computing energies for {particle}...")
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EA = energy_loss(particle, Ei, dA)
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EC = energy_loss(particle, Ei, dC)
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Esx3 = energy_loss(particle, Ei, dsx3)
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Elost = Ei - Esx3
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Eprop = EA - EC
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return {
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"particle": particle,
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"Ei": Ei,
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"sx3Z": sx3Z,
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"EA": EA,
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"EC": EC,
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"Esx3": Esx3,
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"Elost": Elost,
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"Eprop": Eprop
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}
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class MyInteractiveApp(cmd.Cmd):
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def __init__(self):
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@ -405,11 +465,28 @@ class MyInteractiveApp(cmd.Cmd):
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plt.figure(figsize=(8,6))
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plt.plot(x, E)
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plt.xlabel("Distance (cm)")
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plt.ylabel("Energy (MeV)")
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plt.title(f"Energy Loss Curve {label.capitalize()}")
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plt.grid(True)
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plt.show()
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textstr = f"T = {self.T:.2f} K\nP = {self.P:.2f} Torr"
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plt.gca().text(
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0.02, 0.02,
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textstr,
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transform=plt.gca().transAxes,
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fontsize=10,
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verticalalignment='bottom',
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bbox=dict(boxstyle="round", facecolor="white", alpha=0.7)
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)
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plt.tight_layout()
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filename = f"Energy_Loss_Curve_{label}.png"
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plt.savefig(filename, dpi=300, bbox_inches="tight")
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plt.close()
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print(f"Saved plot: {filename}")
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except Exception as e:
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print(f"Error in make_table: {e}")
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@ -755,6 +832,10 @@ class MyInteractiveApp(cmd.Cmd):
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def do_make_plots(self, arg):
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import os
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global plot_data
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plot_data = []
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args = shlex.split(arg)
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@ -782,6 +863,9 @@ class MyInteractiveApp(cmd.Cmd):
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Ei = Ei[mask]
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theta = theta[mask]
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sx3Z = sx3Z[mask]
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update_plot_data(f"{particle}_Ei", Ei)
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update_plot_data(f"{particle}_sx3Z", sx3Z)
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sin_theta = np.sin(theta)
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@ -799,6 +883,12 @@ class MyInteractiveApp(cmd.Cmd):
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Elost = Ei - Esx3
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Eprop = EA - EC
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update_plot_data(f"{particle}_EA", EA)
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update_plot_data(f"{particle}_EC", EC)
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update_plot_data(f"{particle}_Esx3", Esx3)
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update_plot_data(f"{particle}_Elost", Elost)
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update_plot_data(f"{particle}_Eprop", Eprop)
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base = f"{particle}_plots"
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os.makedirs(base, exist_ok=True)
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@ -810,29 +900,29 @@ class MyInteractiveApp(cmd.Cmd):
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plt.hist(Elost, bins=200)
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plt.xlabel("Energy Loss (MeV)")
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plt.ylabel("Counts")
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plt.title("Total Energy Loss Distribution")
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plt.title(f"{particle} Total Energy Loss Distribution")
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plt.grid(True)
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plt.tight_layout()
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plt.savefig(f"{base}/Elost_hist.png", dpi=300)
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plt.close()
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# 2. Histogram: sx3Z
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#Histogram: sx3Z
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plt.figure(figsize=(7,5))
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plt.hist(sx3Z, bins=100)
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plt.xlabel("SX3 Z")
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plt.ylabel("Counts")
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plt.title("SX3 Position Distribution")
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plt.title(f"{particle} SX3 Position Distribution")
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plt.grid(True)
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plt.tight_layout()
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plt.savefig(f"{base}/sx3Z_hist.png", dpi=300)
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plt.close()
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# 3. 2D: Elost vs sx3Z
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#2D: Elost vs sx3Z
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plt.figure(figsize=(7,6))
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plt.hist2d(Elost, sx3Z, bins=200)
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plt.xlabel("Energy Loss (MeV)")
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plt.ylabel("SX3 Z")
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plt.title("Energy Loss vs SX3 Position")
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plt.hist2d(sx3Z, Elost, bins=200)
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plt.ylabel("Energy Loss (MeV)")
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plt.xlabel("SX3 Z")
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plt.title(f"{particle} Energy Loss vs SX3 Position")
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plt.colorbar(label="Counts")
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plt.tight_layout()
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plt.savefig(f"{base}/Elost_vs_sx3Z.png", dpi=300)
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@ -843,7 +933,7 @@ class MyInteractiveApp(cmd.Cmd):
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plt.hist2d(EA, Esx3, bins=200)
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plt.xlabel("EA (MeV)")
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plt.ylabel("Esx3 (MeV)")
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plt.title("Anode vs SX3 Energy")
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plt.title(f"{particle} Anode vs SX3 Energy")
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plt.colorbar(label="Counts")
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plt.tight_layout()
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plt.savefig(f"{base}/EA_vs_Esx3.png", dpi=300)
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@ -854,14 +944,214 @@ class MyInteractiveApp(cmd.Cmd):
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plt.hist2d(Eprop, sx3Z, bins=200)
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plt.xlabel("EA - EC (MeV)")
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plt.ylabel("SX3 Z")
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plt.title("Energy Propagation Difference vs Position")
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plt.title(f"{particle} Energy Propagation Difference vs Position")
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plt.colorbar(label="Counts")
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plt.tight_layout()
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plt.savefig(f"{base}/Eprop_vs_sx3Z.png", dpi=300)
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plt.close()
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plt.figure(figsize=(7,6))
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plt.hist2d(Esx3, Eprop, bins=200)
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plt.ylabel("PCEnergy")
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plt.xlabel("SX3 Energy (MeV)")
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plt.title(f"{particle} Energy Propagation Difference vs sx3 Energy")
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plt.colorbar(label="Counts")
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plt.xlim(0,30)
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plt.ylim(0,.45)
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plt.tight_layout()
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plt.savefig(f"{base}/Eprop_vs_Esx3.png", dpi=300)
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plt.close()
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print("Plotting complete.")
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def do_dual_plotter(self, arg):
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args = shlex.split(arg)
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if len(args) < 2:
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print("Usage: make dual plots proton_data.root alpha_data.root")
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return
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file1 = args[0]
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file2 = args[1]
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#Helper function
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#Process both files
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data1 = process_file(f"../Armory/{file1}")
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data2 = process_file(f"../Armory/{file2}")
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outdir = "dual_plots"
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os.makedirs(outdir, exist_ok=True)
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print(f"Saving plots to: {outdir}")
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#Overlay histogram: Elost
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plt.figure(figsize=(8,6))
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plt.hist(
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data1["Elost"],
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bins=200,
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histtype='step',
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linewidth=2,
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density=True,
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label=data1["particle"]
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)
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plt.hist(
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data2["Elost"],
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bins=200,
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histtype='step',
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linewidth=2,
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density=True,
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label=data2["particle"]
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)
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plt.xlabel("Energy Loss (MeV)")
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plt.ylabel("Normalized Counts")
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plt.title("Energy Loss Comparison")
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plt.legend()
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plt.grid(True)
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plt.tight_layout()
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plt.savefig(f"{outdir}/Elost_overlay.png", dpi=300)
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plt.close()
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#Overlay histogram: sx3Z
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plt.figure(figsize=(8,6))
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plt.hist(
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data1["sx3Z"],
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bins=150,
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histtype='step',
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linewidth=2,
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density=True,
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label=data1["particle"]
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)
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plt.hist(
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data2["sx3Z"],
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bins=150,
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histtype='step',
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linewidth=2,
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density=True,
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label=data2["particle"]
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)
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plt.xlabel("SX3 Z")
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plt.ylabel("Normalized Counts")
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plt.title("SX3 Position Comparison")
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plt.legend()
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plt.grid(True)
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plt.tight_layout()
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plt.savefig(f"{outdir}/sx3Z_overlay.png", dpi=300)
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plt.close()
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#Side-by-side 2D plots
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fig, axes = plt.subplots(1, 2, figsize=(14,6))
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h1 = axes[0].hist2d(
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data1["sx3Z"],
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data1["Elost"],
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bins=200
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)
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axes[0].set_title(f'{data1["particle"]} Elost vs SX3')
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axes[0].set_xlabel("SX3 Z")
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axes[0].set_ylabel("Energy Loss (MeV)")
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h2 = axes[1].hist2d(
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data2["sx3Z"],
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data2["Elost"],
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bins=200
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)
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axes[1].set_title(f'{data2["particle"]} Elost vs SX3')
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axes[1].set_xlabel("SX3 Z")
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axes[1].set_ylabel("Energy Loss (MeV)")
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fig.colorbar(h1[3], ax=axes[0], label="Counts")
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fig.colorbar(h2[3], ax=axes[1], label="Counts")
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plt.tight_layout()
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plt.savefig(f"{outdir}/Elost_vs_sx3_comparison.png", dpi=300)
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plt.close()
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#EA vs Esx3 overlay scatter
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plt.figure(figsize=(8,6))
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plt.scatter(
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data1["EA"],
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data1["Esx3"],
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s=1,
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alpha=0.3,
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label=data1["particle"]
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)
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plt.scatter(
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data2["EA"],
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data2["Esx3"],
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s=1,
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alpha=0.3,
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label=data2["particle"]
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)
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plt.xlabel("EA (MeV)")
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plt.ylabel("Esx3 (MeV)")
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plt.title("Anode vs SX3 Energy")
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plt.legend()
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plt.grid(True)
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plt.tight_layout()
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plt.savefig(f"{outdir}/EA_vs_Esx3_overlay.png", dpi=300)
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plt.close()
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#PCE vs SiE
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combined_Esx3 = np.concatenate([
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data1["Esx3"],
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data2["Esx3"]
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])
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combined_Eprop = np.concatenate([
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data1["Eprop"],
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data2["Eprop"]
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])
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plt.figure(figsize=(7,6))
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plt.hist2d(
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combined_Esx3,
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combined_Eprop,
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bins=100,
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range=[[0,30],[0,0.45]],
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cmap='viridis' # same default matplotlib style
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)
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plt.ylabel("PCEnergy")
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plt.xlabel("SX3 Energy (MeV)")
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plt.title(
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f'{data1["particle"]} + {data2["particle"]} '
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'Energy Propagation Difference vs SX3 Energy'
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)
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plt.colorbar(label="Counts")
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plt.xlim(0,30)
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plt.ylim(0,0.45)
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plt.tight_layout()
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plt.savefig(f"{outdir}/Combined_Eprop_vs_Esx3.png", dpi=300)
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plt.close()
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print("Dual plotting complete.")
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#exec(open("PCEnergyAnalysis.py").read())
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if __name__ == "__main__":
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