labs/21/README.md

@@ -1,15 +0,0 @@
-# Як користуватися
-
-Необхідно клонувати цей репозиторій, наприклад:
-```
-git clone http://10.1.1.1:3000/dymik739/physics-labs-collection.git
-```
-
-Далі потрібно перейти у папку зі скриптом
-```
-cd physics-labs-collection/labs/21/
-```
-та запустити скрипт, вказавши файл зі вхідними даними, наприклад:
-```
-python3 processor.py sample_data.txt
-```

labs/21/processor.py

@@ -1,51 +0,0 @@
-import sys
-import math
-
-def avg(a):
-    return sum(a) / len(a)
-
-resistances = []
-
-settings = {'r': 4, "R2": 0.0, "R3": 0.0}
-
-for raw_i in open(sys.argv[1], "r"):
-    i = raw_i.rstrip("\r\n")
-
-    if len(i) > 0:
-        if i[0] == "#":
-            cmd = i[1:].split()
-            if cmd[0] in settings:
-                settings[cmd[0]] = cmd[1]
-        else:
-            resistances.append([i.split()[0]] + [float(j.replace(',', '.')) for j in i.split()[1:]])
-
-table_data = []
-
-for i in resistances:
-    Rxi = [round(r*float(settings["R2"])/float(settings["R3"]), int(settings['r'])) for r in i[1:]]
-    R_avg = round(avg(Rxi), int(settings['r']))
-
-    table_data.append([i[0]] + Rxi + [R_avg])
-
-from prettytable import PrettyTable
-
-pt = PrettyTable()
-
-pt.add_column("", list(range(1, len(table_data[0][1:-1]) + 1)) + ["❬Rx❭"])
-
-for i in table_data:
-    pt.add_column(i[0], i[1:])
-
-print(pt)
-
-#print(table_data)
-
-print("Обчислюємо значення S для кожного стовпця:")
-for j in table_data:
-    s = math.sqrt( sum([ (i - j[-1])**2 for i in j[1:-1] ]) / (len(j[1:-1])*(len(j[1:-1])-1)) )
-    print(f"S ❬{j[0]}❭ = {round(s, int(settings['r']))}")
-
-print("\nОбчислюємо значення σ для кожного стовпця:")
-for j in table_data:
-    sigma = math.sqrt(avg([i**2 for i in j[1:-1]]) - avg(j[1:-1])**2)
-    print(f"σ ❬{j[0]}❭ = {round(sigma, int(settings['r']))}")

labs/21/sample_data.txt

@@ -1,9 +0,0 @@
-# R2 35000
-# R3 4600
-# r 15
-
-R1x 3403,1 3400,0 3402,9 3403,1 3401,1
-R2x 34,1 33,4 33,3 33,5 34,2
-R3x 1771,7 1772,2 1772,2 1771,8 1771,5
-R4x 740,0 741,0 740,7 741,2 740,8
-R5x 2530,0 2533,0 2532,0 2532,9 2531,0

labs/51/processor.py

@@ -4,7 +4,7 @@ import os
 
 # defining some constants
 
-r = 32 # round to n digits
+r = 3 # round to n digits
 column_width = 11 # set column width of final table
 
 # checking if the file is provided correctly
@@ -144,44 +144,10 @@ sigma_beta2 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_da
 sigma_beta3 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[2]))) + avg(list(zip(*required_data["2"]['stats']))[2])**2), r)
 sigma_beta4 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[5]))) + avg(list(zip(*required_data["2"]['stats']))[5])**2), r)
 
-sigma_M1 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[0]))) + avg(list(zip(*required_data["1"]['stats']))[0])**2), r)
+sigma_t1 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[1]))) + avg(list(zip(*required_data["1"]['stats']))[1])**2), r)
-sigma_M2 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[3]))) + avg(list(zip(*required_data["1"]['stats']))[3])**2), r)
+sigma_t2 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[3]))) + avg(list(zip(*required_data["1"]['stats']))[3])**2), r)
-sigma_M3 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[0]))) + avg(list(zip(*required_data["2"]['stats']))[0])**2), r)
+sigma_t3 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[1]))) + avg(list(zip(*required_data["2"]['stats']))[1])**2), r)
-sigma_M4 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[3]))) + avg(list(zip(*required_data["2"]['stats']))[3])**2), r)
+sigma_t4 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["2"]['stats']))[3]))) + avg(list(zip(*required_data["2"]['stats']))[3])**2), r)
 
-#print("σβ (1-4) (DO NOT USE):", sigma_beta1/avg(list(zip(*required_data["1"]['stats']))[2]), sigma_beta2/avg(list(zip(*required_data["1"]['stats']))[5]), sigma_beta3/avg(list(zip(*required_data["2"]['stats']))[2]), sigma_beta4/avg(list(zip(*required_data["2"]['stats']))[5]))
+print("σβ (1-4) (DO NOT USE):", sigma_beta1/avg(list(zip(*required_data["1"]['stats']))[2]), sigma_beta2/avg(list(zip(*required_data["1"]['stats']))[5]), sigma_beta3/avg(list(zip(*required_data["2"]['stats']))[2]), sigma_beta4/avg(list(zip(*required_data["2"]['stats']))[5]))
-#print("σM (1-4) (DO NOT USE):", sigma_t1/avg(list(zip(*required_data["1"]['stats']))[0]), sigma_t2/avg(list(zip(*required_data["1"]['stats']))[3]), sigma_t3/avg(list(zip(*required_data["2"]['stats']))[0]), sigma_t4/avg(list(zip(*required_data["2"]['stats']))[3]))
+print("σt (1-4) (DO NOT USE):", sigma_t1/avg(list(zip(*required_data["1"]['stats']))[1]), sigma_t2/avg(list(zip(*required_data["1"]['stats']))[3]), sigma_t3/avg(list(zip(*required_data["2"]['stats']))[1]), sigma_t4/avg(list(zip(*required_data["2"]['stats']))[3]))
-
-print("σβ:", avg([math.sqrt(sigma_beta1), math.sqrt(sigma_beta2), math.sqrt(sigma_beta3), math.sqrt(sigma_beta4)]))
-print("σM:", avg([math.sqrt(sigma_M1), math.sqrt(sigma_M2), math.sqrt(sigma_M3), math.sqrt(sigma_M4)]))
-
-print(required_data)
-'''
-for t in required_data:
-    I_values_r1 = [(i[0] / i[1]) for i in zip(list(zip(*required_data[t]['stats']))[0], list(zip(*required_data[t]['stats']))[2])]
-    Mt1 = required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][0] - (min(I_values_r1) * required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][2])
-    print(f"Таблиця {t}, стовпець 1: Imin = {required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][0]} / {required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][2]} = {round(min(I_values_r1), r)}; Mт = {required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][0]} - {min(I_values_r1)}*{required_data[t]['stats'][I_values_r1.index(min(I_values_r1))][2]} = {round(Mt1, r)} (за мінімальний узято рядок {I_values_r1.index(min(I_values_r1))})")
-
-    I_values_r2 = [(i[0] / i[1]) for i in zip(list(zip(*required_data[t]['stats']))[3], list(zip(*required_data[t]['stats']))[5])]
-    Mt2 = required_data[t]['stats'][I_values_r2.index(min(I_values_r2))][3] - (min(I_values_r2) * required_data[t]['stats'][I_values_r2.index(min(I_values_r2))][5])
-    print(f"Таблиця {t}, стовпець 2: Imin = {round(min(I_values_r2), r)}; Mт = {round(Mt2, r)}")
-    #i_min_2 = min([(i[0] / i[1]) for i in zip(list(zip(*required_data[t]['stats']))[3], list(zip(*required_data[t]['stats']))[5])])
-    #print(f"Imin for {t}-2: {round(i_min_2, r)}")
-'''
-for t in required_data:
-    I_values_r1 = []
-    M_and_beta = list(zip(list(zip(*required_data[t]['stats']))[0], list(zip(*required_data[t]['stats']))[2]))
-    print(M_and_beta)
-    for i in range(5):
-        print((M_and_beta[i+1][0] - M_and_beta[i][0]) / (M_and_beta[i+1][1] - M_and_beta[i][1]))
-        I_values_r1.append((M_and_beta[i+1][0] - M_and_beta[i][0]) / (M_and_beta[i+1][1] - M_and_beta[i][1]))
-
-    print(f"Таблиця {t}, стовпець 1: Imin = {min(I_values_r1)}; Mт = {M_and_beta[I_values_r1.index(min(I_values_r1))][0] - min(I_values_r1)*M_and_beta[I_values_r1.index(min(I_values_r1))][1]}")
-    
-    I_values_r2 = []
-    M_and_beta = list(zip(list(zip(*required_data[t]['stats']))[3], list(zip(*required_data[t]['stats']))[5]))
-    for i in range(5):
-        print((M_and_beta[i+1][0] - M_and_beta[i][0]) / (M_and_beta[i+1][1] - M_and_beta[i][1]))
-        I_values_r2.append((M_and_beta[i+1][0] - M_and_beta[i][0]) / (M_and_beta[i+1][1] - M_and_beta[i][1]))
-
-    print(f"Таблиця {t}, стовпець 2: Imin = {min(I_values_r2)}; Mт = {M_and_beta[I_values_r2.index(min(I_values_r2))][0] - min(I_values_r2)*M_and_beta[I_values_r2.index(min(I_values_r2))][1]}")