Modern Phys Lab

statics/physics/modern-phys-lab/counting/run.py

@@ -1,5 +1,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
+from matplotlib import colors
+import scipy
 
 def read_file(file: str) -> np.typing.ArrayLike:
     with open(f'{file}.csv', 'r') as file:
@@ -12,7 +14,7 @@ all_data = {
     '40': sum([read_file(f'40-{i}') for i in range(1, 6)])
 }
 
-fig, axs = plt.subplots(len(all_data), sharex='all')
+fig, axs = plt.subplots(len(all_data), 1, sharex='col')
 i = 0
 
 for dwell_time in all_data:
@@ -41,15 +43,47 @@ for dwell_time in all_data:
     print(f'Found {times_dev_more_than_P} / {N} ({times_dev_more_than_P / N * 100:0.2f}%) samples deviating from the mean more than P {P:0.2f}')
 
     ax = axs[i]
+    ax.set_xlabel('Run Count')
+    ax.set_ylabel('Events Measured')
+    ax.set_title('Raw Data')
+    ax.scatter(np.arange(1, len(data)+1), data, s=4)
+    ax.legend(['\n'.join([
+        f'Mean: {mean:0.2f}',
+        f'Sample Sd. Dev: {stdev:0.2f}',
+        f'P: {P:0.2f}',
+        f'Events > sigma: {times_dev_more_than_s} ({times_dev_more_than_s / N * 100:0.2f}%)',
+        f'Events > P: {times_dev_more_than_P} ({times_dev_more_than_P / N * 100:0.2f}%)'
+    ])])
+
+    # ax = axs[i][1]
+    # ax.set_visible(False)
+
+    # ax.set_title(f'Cumulative Average ({dwell_time}ms Dwell time)')
+    # ax.set_xlabel('After N Runs')
+    # ax.set_ylabel('Cumulative Average')
+
+    # sample_num = np.arange(1, N + 1)
+    # cumulative_average = np.cumsum(data) / sample_num
+    # ax.plot(sample_num, cumulative_average, label=f'Final Value: {cumulative_average[-1]:0.2f}')
+    # ax.legend()
+
+
+    # ax = axs[i]
+    # N, bins, patches = ax.hist(data, density=True, bins=32, label='Measured Data')
+
+    # fracs = N / N.max()
+    # norm = colors.Normalize(fracs.min(), fracs.max())
+    # for thisfrac, thispatch in zip(fracs, patches):
+    #     color = plt.cm.viridis(norm(thisfrac))
+    #     thispatch.set_facecolor(color)
+
+    # ax.set_xlabel('Event Count')
+    # ax.set_ylabel('Frequency')
+
+    # linspace = np.arange(bins.min(), bins.max())
+    # gaussian = scipy.stats.norm.pdf(linspace, mean, stdev)
+    # ax.plot(linspace, gaussian, label='Fitted Gaussian')
+    # ax.legend()
+
     i += 1
-
-    ax.set_title(f'Cumulative Average ({dwell_time}ms Dwell time)')
-    ax.set_xlabel('After N Runs')
-    ax.set_ylabel('Cumulative Average')
-
-    sample_num = np.arange(1, N + 1)
-    cumulative_average = np.cumsum(data) / sample_num
-    ax.plot(sample_num, cumulative_average, label=f'Final Value: {cumulative_average[-1]:0.2f}')
-    ax.legend()
-
 plt.show()

statics/physics/modern-phys-lab/diffraction.py

@@ -6,7 +6,7 @@ voltages = np.array(np.arange(2500, 5000 + 1, +500)) #+1 to include 5000
 voltages_inv_sqrt = 1 / np.sqrt(voltages)
 
 # New units: m
-diameter_measured_error = 0.002
+diameter_measured_error = 0.001
 
 # Average inner and outer
 # New format: d[0 = small, 1 = large][voltage]