Structurization + 120 and 117 prak

1 files changed, 0 insertions, 93 deletions

diff --git a/vtek2.py b/vtek2.py
deleted file mode 100755
index 5f58823..0000000
--- a/vtek2.py
+++ /dev/null
@@ -1,93 +0,0 @@
-#!/home/main/coding/py/venv/bin/python3
-
-from prak2 import *
-from math import pow, sqrt 
-
-
-PI = 3.141592657 # ;)
-
-def main():
-    timer = [];
-    photo = [];
-    Ns = [];
-    Tsqs = [];
-    STsqs = [];
-    H = float(input('Введите H и погрешность H: '))
-    H_err = float(input())
-    m0 = int(input('Введите m0 (количество измерений): '))
-    n = float(input('Введите n (количество колебаний на 1 измерение): '))
-    subj_err = 0.3
-
-    print('\n', '-' * 35, "\nОБРАБОТКА С РУЧНЫМИ ЧАСАМИ\n", '-' * 35);
-    for i in range(m0 + 1):
-        print("введите t_1, t_2, t_3 для N  = ", i);
-        list = [float(input()) for _ in range(3)];
-        mean = avg(list);
-        dev = stddev(list);
-        mean_err = sqrt(dev * dev + pow(1e-3 * mean, 2) + subj_err*subj_err);
-        T = mean / n;
-        T_err = mean_err / n;
-        tsq = T * T;
-        tsq_err = 2 * T * T_err;
-        timer.append((i, tsq, tsq_err));
-        print(f"avg = {mean}; err = {mean_err}; T = {T} ± {T_err}\nT^2 = {tsq} ± {tsq_err}");
-    Ns = np.array([i[0] for i in timer]);
-    Tsqs = np.array([i[1] for i in timer]);
-    STsqs = np.array([i[2] for i in timer]);
-    res = mnk(Ns, Tsqs, STsqs);
-    print(f"A = {res['a']} ± {res['sa']}\nB = {res['b']} ± {res['sb']}");
-    g = 4 * PI * PI * H / res['a'] / m0;
-    g_err = g * sqrt(pow(res['sa'] / res['a'], 2) + pow(H_err / H, 2));
-    l = res['b'] * g / 4 / PI / PI;
-    l_err = l * sqrt(pow(res['sb'] / res['b'], 2) + pow(g_err/g , 2));
-    print(f"g = {g} ± {g_err}\nl = {l} ± {l_err}");
-
-
-    print('\n', '-' * 35, "\nОБРАБОТКА С ФОТОДАТЧИКАМИ\n", '-' * 35);
-    for i in range(m0 + 1):
-        print("Введите t, St для N = ", i);
-        mean = float(input())
-        dev = float(input())
-        mean_err = sqrt(dev * dev + pow(1e-3 * mean, 2));
-        T = 2 * mean;
-        T_err = 2 * mean_err;
-        tsq = T * T;
-        tsq_err = 2 * T * T_err;
-        photo.append((i, tsq, tsq_err));
-        print(f"T = {T} ± {T_err}\nT^2 = {tsq} ± {tsq_err}");
-    Ns = np.array([i[0] for i in photo]);
-    Tsqs = np.array([i[1] for i in photo]);
-    STsqs = np.array([i[2] for i in photo]);
-    res = mnk(Ns, Tsqs, STsqs);
-    print(f"A = {res['a']} ± {res['sa']}\nB = {res['b']} ± {res['sb']}");
-    g = 4 * PI * PI * H / res['a'] / m0;
-    g_err = g * sqrt(pow(res['sa'] / res['a'], 2) + pow(H_err / H, 2));
-    l = res['b'] * g / 4 / PI / PI;
-    l_err = l * sqrt(pow(res['sb'] / res['b'], 2) + pow(g_err/g , 2));
-    print(f"g = {g} ± {g_err}\nl = {l} ± {l_err}");
-    
-    print('\n', '-' * 35, "\nОБРАБОТКА ВТОРОГО УПРАЖНЕНИЯ\n", '-' * 35);
-    omegas = [];
-    Us = [0.3 * (i+1) for i in range(6)];
-    U_errs = [0.003 * i + 0.002 for i in Us];
-    U_errs[0] -= 0.0015;
-    for U, U_err in zip(Us, U_errs):
-        tg = float(input('Введите t_д: '));
-        tg_err = float(input('Введите погрешность t_д: '));
-        omega = 2*PI / tg;
-        omega_err = omega * tg_err / tg;
-        omegas.append((U, omega, U_err, omega_err));
-        print(f"\nomega = {omega} ± {omega_err}");
-    with open("outputU.data", "w+") as f:
-        for a, b, c, d in omegas:
-            f.write(f"{a} {b} {c} {d}\n");
-    with open("outputT2_timer.data", "w+") as f:
-        for a, b, c in timer:
-            f.write(f"{a} {b} {c}\n")
-    with open("outputT2_photo.data", "w+") as f:
-        for a, b, c in photo:
-            f.write(f"{a} {b} {c}\n")
-
-
-if __name__ == "__main__": main();
-