add code for lab 23

labs/21/README.md

@@ -0,0 +1,15 @@
+# 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

@@ -0,0 +1,51 @@
+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

@@ -0,0 +1,9 @@
+# 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/23/processor.py

@@ -0,0 +1,46 @@
+import prettytable
+
+tables = {}
+active_table_id = 0
+r = 3
+
+def avg(a):
+    return sum(a) / len(a)
+
+with open("sample_data.txt") as f:
+    for l in f:
+        if l.rstrip("\n\r") == '':
+            continue
+
+        if l[0] == "#":
+            sl = l[1:].split()
+
+            if len(sl) == 2:
+                if sl[0] == "table":
+                    new_id = int(sl[1])
+                    tables[new_id] = {"s": [], "C": 0.0}
+                    active_table_id = new_id
+
+                elif sl[0] == "C":
+                    tables[active_table_id]["C"] = float(sl[1])
+
+        else:
+            tables[active_table_id]['s'].append(list(map(float, l.split())))
+
+ti = list(tables.items())
+ti.sort(key = lambda x: x[0])
+
+for i, t in ti:
+    print(f"Table {i}")
+
+    s = t['s']
+    c = t['C']
+
+    avg_n = [avg(a) for a in zip(*s)]
+    print("❬n❭ : " + ", ".join(list(map(lambda x: str(round(x, r)), avg_n))))
+
+    avg_Cix_U = [c * avg_n[2*a] / avg_n[2*a+1] for a in range(2)]
+    print("❬Cix(Ui)❭ : " + ", ".join(list(map(lambda x: str(round(x, r)), avg_Cix_U))))
+
+    avg_Cix_final = avg(avg_Cix_U)
+    print(f"Результат для ❬Сix❭: {avg_Cix_final}\n")

labs/23/sample_data.txt

@@ -0,0 +1,26 @@
+# table 1
+# C 0.82
+
+4.5 1.1 0.6 1.7
+4.3 1.0 0.7 1.6
+
+
+# table 2
+# C 1.5
+
+4.5 2.0 0.6 3.1
+4.3 1.9 0.7 3.0
+
+
+# table 3
+# C 2.7
+
+4.5 3.8 0.6 3.1
+4.3 3.9 0.7 3.0
+
+
+# table 4
+# C 0.22
+
+4.5 2.6 0.6 4.9
+4.3 2.9 0.7 4.6

labs/51/processor.py

@@ -4,7 +4,7 @@ import os
 
 # defining some constants
 
-r = 3 # round to n digits
+r = 32 # round to n digits
 column_width = 11 # set column width of final table
 
 # checking if the file is provided correctly
@@ -144,10 +144,44 @@ 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_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_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_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_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_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_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_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)
+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)
 
-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("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("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("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]}")