tdc_gpx2/scripts/plottdc.py
2023-08-11 14:09:43 +02:00

36 lines
873 B
Python

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}")