From 5c17cf027a782ddcbac70039e3c41b7adc8adbea Mon Sep 17 00:00:00 2001
From: justanothercatgirl <sotov2070@gmail.com>
Date: Thu, 10 Oct 2024 08:30:19 +0300
Subject: initial commit

---
 prak2.py | 96 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 96 insertions(+)
 create mode 100755 prak2.py

(limited to 'prak2.py')

diff --git a/prak2.py b/prak2.py
new file mode 100755
index 0000000..8be1a5f
--- /dev/null
+++ b/prak2.py
@@ -0,0 +1,96 @@
+#!/home/main/coding/py/venv/bin/python3
+
+import math 
+import numpy as np
+
+def getvarbyval(var, ls):
+    for name, value in ls.items():
+        if value is var:
+            return name
+
+def avg(l): 
+    return sum(l)/len(l)
+
+def stddev(l):
+    s = len(l)
+    a = avg(l)
+    return math.sqrt(sum(( (i - a)**2 for i in l )) / s / (s-1))
+
+def sigsum(stddev, sig_sist):
+    return math.sqrt(stddev**2 + sig_sist**2)
+
+def sigma(func, args, sigmas):
+    s = 0
+    dx = 1e-7
+    for i in range(len(args)):
+        argsdx = args.copy()
+        argsdx[i] += dx
+        s += ( sigmas[i] * (func(*argsdx) - func(*args))/dx )**2
+    return math.sqrt(s)
+
+def mnk(xs, ys, ss):
+    sss = ss*ss
+    d = np.sum(xs*xs/sss)*np.sum(1/sss) - np.sum(xs/sss)**2
+    da = np.sum(xs*ys/sss)*np.sum(1/sss) - np.sum(xs/sss)*np.sum(ys/sss)
+    db = np.sum(xs*xs/sss)*np.sum(ys/sss) - np.sum(xs/sss)*np.sum(xs*ys/sss)
+    a = da/d
+    b = db/d
+    sa = math.sqrt(np.sum(1/sss)/d)
+    sb = math.sqrt(np.sum(xs*xs/sss)/d)
+    return {"a": a, "b": b, "sa": sa, "sb": sb}
+
+def v(l, t): return l/t
+def v2(l, t): return (l/t)**2
+def a_teor(dh2, L): return 9.807 * dh2 / L
+
+def main():
+    print("Введите L1-L3 (м), l1-l3 (м), M1-M3 (г)")
+    Ls = [float(input()) for _ in range(3)]
+    ls = [float(input()) for _ in range(3)]
+    Ms = [float(input())/1000.0 for _ in range(3)]
+    
+    for i in Ls, ls, Ms:
+        sig_sist = float(input(f"сист. погрешность для {getvarbyval(i, locals())}(м/Кг): "))
+        print(f"{getvarbyval(i, locals())}: mean={avg(i)}; stddev={stddev(i)}; sigma={sigsum(sig_sist, stddev(i))}")
+        i.append(sigsum(sig_sist, stddev(i)))
+
+    print("Введите 3 массы тележек");
+    h = 6 # mm
+    rest = {float(input())/1000.0 : [[round(0.2 * (j+1), 1), 0, 0] for j in range(5)] for i in range(3)}
+    for m in sorted(rest.keys()):
+        for x in rest[m]:
+            print(f"введите t1, t2, t3 для dh=6mm, m={m*1000}г, x={x[0]}м")
+            ts = [float(input()) for _ in range(3)]
+            x[1] = avg(ts)
+            x[2] = stddev(ts)
+            print(f"t_avg = {x[1]}, t_dev = {x[2]}")
+    
+    l = avg(ls[:-1]); sl = ls[-1]
+    resv = {i : [np.zeros((5,), dtype=float) for _ in range(4)] for i in sorted(rest.keys())}
+    for m in sorted(rest.keys()):
+        for i, x in enumerate(rest[m]):
+            args = [l, x[1]]
+            sigmas = [sl, x[2]]
+            _v = v(*args)
+            _v2 = v2(*args)
+            _v2s = sigma(v2, args, sigmas)
+            resv[m][0][i] = x[0]
+            resv[m][1][i] = _v
+            resv[m][2][i] = _v2
+            resv[m][3][i] = _v2s
+            print(f"для m={m*1000}г, x={x[0]}м: v={_v}, v^2={_v2}, sigma_v={_v2s}")
+    for m in sorted(resv.keys()):
+        data = resv[m]
+        d = mnk(data[0], data[2], data[3])
+        A = d['a']; 
+        sA = d['sa']
+        B = d['b']; sB = d['sb']
+        a = A/2; sa = sA/2
+        a_t = a_teor(h / 1e3, avg(Ls[:-1]))
+        sa_t = sigma(a_teor, [h/1e3, avg(Ls[:-1])], [float(input("Введите погрешность dh_2: ")), Ls[-1]])
+        print(f"A = {A}+-{sA}\nB = {B}+-{sB}\na = {a}+-{sa}\na_teor = {a_t}, sigma_a_teor = {sa_t}")
+
+if __name__ == "__main__":
+    main()
+
+
-- 
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