physics-labs-collection/labs/51/processor.py

import math
import sys
import os

# defining some constants

r = 32 # round to n digits
column_width = 11 # set column width of final table

# checking if the file is provided correctly

if len(sys.argv) != 2:
    print(f"Please, provide data file\nUsage example: python3 {sys.argv[0]} sample_file.txt")
    sys.exit(1)

if not os.path.exists(sys.argv[1]):
    print("File does not exist")
    sys.exit(1)

# defining functions

def avg(a):
    #print(a)
    return sum(a) / len(a)

def get_max_len(a):
    return max(list(map(lambda x: len(str(x)), a)))

# reading input data from the file

possible_units = {"mass": {"kilogram": 1, "gram": 0.001}}

selected_table = 0

tables = {"1": {"r2": 0, "r1": 0, "norms": {"mass": 1}, "stats": []},
          "2": {"r2": 0, "r1": 0, "norms": {"mass": 1}, "stats": []}}

with open(sys.argv[1]) as source_file:
    for raw_i in source_file:
        i = raw_i.rstrip("\n\r")
        table_line = i.split()
        if len(table_line) > 0:
            if table_line[0] == "#":
                if table_line[1] == "table":
                    selected_table = table_line[2]
                elif table_line[1] == "r1":
                    tables[selected_table]["r1"] = float(table_line[2])
                elif table_line[1] == "r2":
                    tables[selected_table]["r2"] = float(table_line[2])
                elif table_line[1] == "set_unit":
                    if table_line[2] in possible_units and table_line[3] in possible_units[table_line[2]]:
                        tables[selected_table]["norms"][table_line[2]] = possible_units[table_line[2]][table_line[3]]
                    else:
                        print(f"Unsupported unit defined in line: '{i}'")
            else:
                if len(table_line) == 7:
                    new_data = list(map(float, table_line))
                    new_data[0] = round(new_data[0] * tables[selected_table]["norms"]["mass"], r)
                    tables[selected_table]["stats"].append(new_data)

# processing inputs

required_data = {"1": {"stats": [], "Mt": 0, "Imin": 0},
                 "2": {"stats": [], "Mt": 0, "Imin": 0}}

for i in tables:
    for j in tables[i]['stats']:
        new_line = []
        new_line.append(round(j[0]*tables[i]['r1']*9.81, r))
        new_line.append(round(avg(j[1:4]), r))
        new_line.append(round(2/(tables[i]['r1']*(new_line[1]**2)), r))

        new_line.append(round(j[0]*tables[i]['r2']*9.81, r))
        new_line.append(round(avg(j[4:7]), r))
        new_line.append(round(2/(tables[i]['r2']*(new_line[4]**2)), r))

        required_data[i]["stats"].append(new_line)

# printing out the results


'''
for i in tables:
    table_widths = [get_max_len(list(zip(tables[i]['stats']))[0]),
                    get_max_len(list(zip(required_data[i]['stats']))[0]),
                    get_max_len(list(zip(tables[i]['stats']))[1]),
                    get_max_len(list(zip(tables[i]['stats']))[2]),
                    get_max_len(list(zip(tables[i]['stats']))[3]),
                    get_max_len(list(zip(required_data[i]['stats']))[1]),
                    get_max_len(list(zip(required_data[i]['stats']))[2]),

                    get_max_len(list(zip(tables[i]['stats']))[0]),
                    get_max_len(list(zip(required_data[i]['stats']))[3]),
                    get_max_len(list(zip(tables[i]['stats']))[4]),
                    get_max_len(list(zip(tables[i]['stats']))[5]),
                    get_max_len(list(zip(tables[i]['stats']))[6]),
                    get_max_len(list(zip(required_data[i]['stats']))[4]),
                    get_max_len(list(zip(required_data[i]['stats']))[5]),
                    ]
    print("|".join( list(map(lambda x: str(x[0].center(x[1])), zip(["m", "Mi", "t1", "t2", "t3", "❬t❭", "βi"]*2, table_widths)))))
    for j in range(len(required_data[i]['stats'])):
        print("|".join( list(map(lambda x: str(x[0].center(x[1])),
                                 zip([tables[i]['stats'][j][0],
                                      required_data[i]['stats'][j][0],
                                      tables[i]['stats'][j][1],
                                      tables[i]['stats'][j][2],
                                      tables[i]['stats'][j][3],
                                      required_data[i]['stats'][j][1],
                                      required_data[i]['stats'][j][2],
                                      
                                      tables[i]['stats'][j][0],
                                      required_data[i]['stats'][j][3],
                                      tables[i]['stats'][j][4],
                                      tables[i]['stats'][j][5],
                                      tables[i]['stats'][j][6],
                                      required_data[i]['stats'][j][4],
                                      required_data[i]['stats'][j][5]],
                                      table_widths))) ))
'''

for i in tables:
    print(f"Table #{i}")
    print("|".join( list(map(lambda x: str(x).center(11), ["m", "Mi", "t1", "t2", "t3", "❬t❭", "βi"]*2))))
    for j in range(len(required_data[i]['stats'])):
        print("|".join( list(map(lambda x: str(x).center(11),
                                     [tables[i]['stats'][j][0],
                                      required_data[i]['stats'][j][0],
                                      tables[i]['stats'][j][1],
                                      tables[i]['stats'][j][2],
                                      tables[i]['stats'][j][3],
                                      required_data[i]['stats'][j][1],
                                      required_data[i]['stats'][j][2],
                                      
                                      tables[i]['stats'][j][0],
                                      required_data[i]['stats'][j][3],
                                      tables[i]['stats'][j][4],
                                      tables[i]['stats'][j][5],
                                      tables[i]['stats'][j][6],
                                      required_data[i]['stats'][j][4],
                                      required_data[i]['stats'][j][5]])) ))

sigma_beta1 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[2]))) + avg(list(zip(*required_data["1"]['stats']))[2])**2), r)
sigma_beta2 = round(math.sqrt(avg(list(map(lambda x: x**2, list(zip(*required_data["1"]['stats']))[5]))) + avg(list(zip(*required_data["1"]['stats']))[5])**2), r)
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_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_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_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("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]}")