init

get_data.py

@@ -0,0 +1,29 @@
+import http.client
+
+import json
+
+
+def get_data(raw_data=[100, 101]):
+    conn = http.client.HTTPSConnection("www.zhishuyao.com")
+    payload = "type=jyzs"
+
+    for item in raw_data:
+        payload += f"&val[]={item}"
+
+    headers = {
+        "authority": "www.zhishuyao.com",
+        "content-type": "application/x-www-form-urlencoded",
+        "origin": "https://www.zhishuyao.com",
+    }
+    conn.request("POST", "/decode.php", payload, headers)
+    res = conn.getresponse()
+    data = res.read()
+    return json.loads(data.decode("utf-8"))["data"]
+
+
+if __name__ == "__main__":
+    raw_data = list(range(0, 1001, 20))
+
+    res = get_data(raw_data)
+    for raw, new in zip(raw_data, res):
+        print(raw, new)

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)

test.py

@@ -0,0 +1,18 @@
+import numpy as np
+from get_data import get_data
+
+parm_1000 = [-61.4400001, 1402438300.0, 61.4400001]
+
+
+def reduct(x, parm):
+    a, b, c = parm
+    return a * np.exp(-b * x) + c
+
+
+def check_data(data):
+    fit_data = reduct(data, parm_1000)
+    real_data = get_data([data])
+    print(f"拟合数据: {fit_data}, 实际数据: {real_data}, 误差: {fit_data - real_data}")
+
+
+check_data(1000)

tmp.py

@@ -0,0 +1,37 @@
+import math
+
+
+def calculate_y(x):
+    y = (10 * math.log(x + 1) + 30) * math.sqrt(x)
+    return y
+
+
+def calculate_x(y):
+    # Define the function to find the root of
+    def f(x):
+        return (10 * math.log(x + 1) + 30) * math.sqrt(x) - y
+
+    # Set the initial bounds for the bisection method
+    a = 0
+    b = 1e6
+
+    # Set the tolerance for the root-finding algorithm
+    tol = 1e-6
+
+    # Perform the bisection method to find the root
+    while (b - a) / 2 > tol:
+        c = (a + b) / 2
+        if f(c) == 0:
+            return c
+        elif f(a) * f(c) < 0:
+            b = c
+        else:
+            a = c
+
+    return (a + b) / 2
+
+
+# Example usage
+y = 10000000
+x = calculate_y(y)
+print(x)