tdc_gpx2/scripts/plottdc.py

import numpy as np
import matplotlib.pyplot as plt

# Open the file and read in the data
with open('../data/test02.dat', 'r') as f:
    lines = f.readlines()

# Extract the second column of data
data = []
for line in lines:
    values = line.strip().split()
    data.append(float(values[1]))

#determine histrange from data
hist_range = 5  * np.std(data)
hist_mean = np.mean(data)
hist_start = hist_mean - hist_range
hist_end = hist_mean +  hist_range

# Create the histogram with range
hist, bins, _ = plt.hist(data, bins=100, range=(hist_start,hist_end))

# Calculate the mean and RMS
bin_centers = 0.5 * (bins[:-1] + bins[1:])

# Set the x-axis label and title
plt.xlabel('Data')
plt.title('Histogram of Data')

# Show the plot
plt.show()

# Print the mean and RMS
print(f"Mean: {np.mean(data):.3g}")
print(f"RMS: {np.std(data):.3g}")