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import numpy as np
import matplotlib.pyplot as plt
import os
import argparse
def extract_x0_values(filename):
"""Extract x0 values from a single file"""
x0_values = []
counter = 0
with open(filename, 'r') as file:
for line in file:
if '| 0 Average Material' in line:
counter += 1
items = [item.strip() for item in line.split('|')]
x0_value = float(items[1].split()[10])
x0_values.append(x0_value)
print(f"Processing file {filename}: ", counter, " x0: ", x0_value)
return x0_values
def process_multiple_files(file_list, bins, bias):
"""Process multiple files and return their x0 matrices"""
theta_bins = bins + 1
phi_bins = bins*2 + 1
range_theta = [bias, theta_bins-bias]
matrices = []
for file in file_list:
x0_values = extract_x0_values(file)
x0_matrix = np.array(x0_values).reshape(theta_bins, phi_bins)[range_theta[0]:range_theta[1], :]
matrices.append(x0_matrix)
return matrices
def plot_accumulated_projections(matrices, output_file, bins, bias, labels):
"""Plot accumulated projections"""
theta_bins = bins + 1
phi_bins = bins*2 + 1
range_theta = [bias, theta_bins-bias]
# Create angle arrays
phi = np.linspace(-180, 180, phi_bins)
theta = np.linspace(range_theta[0]*180/theta_bins, range_theta[1]*180/theta_bins, range_theta[1]-range_theta[0])
# Create figure
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20, 8))
# Accumulation data
accumulated_theta = np.zeros_like(theta)
accumulated_phi = np.zeros_like(phi)
colors = plt.cm.viridis(np.linspace(0, 1, len(matrices)))
# Plot phi projection
for i, matrix in enumerate(matrices):
phi_projection = np.sum(matrix, axis=0) / (range_theta[1]-range_theta[0])
accumulated_phi += phi_projection
ax1.fill_between(phi, accumulated_phi, accumulated_phi - phi_projection,
label=labels[i], color=colors[i], alpha=0.6)
# Plot theta projection
for i, matrix in enumerate(matrices):
theta_projection = np.sum(matrix, axis=1) / phi_bins
accumulated_theta += theta_projection
ax2.fill_between(theta, accumulated_theta, accumulated_theta - theta_projection,
label=labels[i], color=colors[i], alpha=0.6)
# Set phi projection plot
ax1.set_title('Accumulated Projection along Phi', fontsize=14, pad=10)
ax1.set_xlabel('Phi (degree)', fontsize=12)
ax1.set_ylabel('Accumulated X/X0', fontsize=12)
ax1.grid(True, linestyle='--', alpha=0.7)
ax1.legend(fontsize=10)
ax1.spines['top'].set_visible(False)
ax1.spines['right'].set_visible(False)
# Set theta projection plot
ax2.set_title('Accumulated Projection along Theta', fontsize=14, pad=10)
ax2.set_xlabel('Theta (degree)', fontsize=12)
ax2.set_ylabel('Accumulated X/X0', fontsize=12)
ax2.grid(True, linestyle='--', alpha=0.7)
ax2.legend(fontsize=10)
ax2.spines['top'].set_visible(False)
ax2.spines['right'].set_visible(False)
plt.suptitle('Detector Material Budget Accumulation Analysis', fontsize=16, y=0.95)
plt.tight_layout()
plt.savefig(output_file, dpi=600, bbox_inches='tight')
plt.show()
def main():
parser = argparse.ArgumentParser(description='Process multiple material scan data and generate accumulated distribution plots.')
parser.add_argument('--input_files', nargs='+', required=True,
help='List of input files in order')
parser.add_argument('--labels', nargs='+', required=True,
help='Labels for each input file')
parser.add_argument('--output_file', default='accumulated_material_budget.png',
help='Output PNG file path')
parser.add_argument('--bins', type=int, default=100,
help='theta bins is "bins"+1, phi bins is "bins"*2+1, (default: 100)')
parser.add_argument('--bias', type=int, default=0,
help='Bias value for theta range (default: 0)')
args = parser.parse_args()
if len(args.input_files) != len(args.labels):
raise ValueError("Number of input files must match number of labels!")
# Process all input files
matrices = process_multiple_files(args.input_files, args.bins, args.bias)
# Plot accumulated graphs
plot_accumulated_projections(matrices, args.output_file, args.bins, args.bias, args.labels)
if __name__ == '__main__':
main()