init

nh.py

@@ -0,0 +1,75 @@
+import numpy as np
+from scipy.optimize import curve_fit
+
+
+# Define the function to fit
+def func(x, a, b, c):
+    return a * np.exp(-b * x) + c
+
+
+# Load the data
+data = np.array(
+    [
+        [0, 0],
+        [20, 0],
+        [40, 1],
+        [60, 2],
+        [80, 3],
+        [100, 5],
+        [120, 6],
+        [140, 7],
+        [160, 9],
+        [180, 11],
+        [200, 13],
+        [220, 15],
+        [240, 17],
+        [260, 19],
+        [280, 21],
+        [300, 23],
+        [320, 26],
+        [340, 28],
+        [360, 31],
+        [380, 34],
+        [400, 36],
+        [420, 39],
+        [440, 42],
+        [460, 45],
+        [480, 48],
+        [500, 52],
+        [520, 55],
+        [540, 58],
+        [560, 62],
+        [580, 65],
+        [600, 69],
+        [620, 72],
+        [640, 76],
+        [660, 80],
+        [680, 84],
+        [700, 88],
+        [720, 92],
+        [740, 96],
+        [760, 100],
+        [780, 104],
+        [800, 108],
+        [820, 112],
+        [840, 117],
+        [860, 121],
+        [880, 126],
+        [900, 130],
+        [920, 135],
+        [940, 140],
+        [960, 145],
+        [980, 150],
+        [1000, 154],
+    ]
+)
+
+# Separate the data into x and y arrays
+xdata = data[:, 0]
+ydata = data[:, 1]
+
+# Fit the curve to the data
+popt, pcov = curve_fit(func, xdata, ydata)
+
+# Print the fitted parameters
+print(popt)