Säähavainnot

import pandas as pd
from sklearn.linear_model import LinearRegression
import numpy as np
# import matplotlib.pyplot as plt
import random
 
 
data = pd.read_csv(f"data_mod.csv", delimiter=' ')
 
 
 
def calculate_temperature(hours, amount):
  data = pd.read_csv(f"data_mod.csv", delimiter=' ')
 
  x = np.array(data[[str(x) for x in range(24)]])
  y = np.array(data[[str(x) for x in range(24, 36)]])
 
  model = LinearRegression().fit(x, y)
  predictions = model.predict(np.array([hours], dtype=object))
  predictions=predictions[0]
  # predictions = [predictions[0][x] for x in range(amount)]
  return predictions
 
 
def testing(real, prediction):
    # print(len(real))
    # print(len(prediction))
    oikein = 0
    väärin = 0
    ei_dataa = 0
    # if prediction == False:
    #     return (0, 0, 12)
    for i in range(len(real)):
        if prediction[i] == False:
            ei_dataa += 1
        else:
            erotus = abs(real[i]-prediction[i])
            if erotus < 0.75:
                oikein += 1
            elif erotus > 0.7 and erotus < 2.05:
                ei_dataa += 1
            else:
                väärin += 1
    return (oikein, väärin, ei_dataa)
 
 
def setup():
    n = int(input())
    # a = "2.6 2.5 2.3 2.2 2.1 2.1 1.8 1.5 1.2 1.1 1.2 1.1 1 1.3 1.5 1.3 1 1.1 1 0.9 1 0.7 1.1 1.5"
    takas = []
    lista = []
    for i in range(n):
        lista.append([float(x) for x in input().split()])
    for i in lista:
        tulos = [str(x) for x in calculate_temperature(np.array(data.iloc[i][[str(x) for x in range(24)]]), 12)]
        takas.append(" ".join(tulos))
    for i in takas:
        print(i)
 
 
 
def results(amount):
  tulos = (0, 0, 0)
  start = random.randint(1, 4000)
  for i in range(start, start+amount):
    tulos= tuple(map(lambda i, j: i + j, tulos, testing(np.array(data.iloc[i][[str(x) for x in range(24, 36)]]),calculate_temperature(np.array(data.iloc[i][[str(x) for x in range(24)]]), 12))))
  return tulos
 
 
# AMOUNT = 100
# result = results(AMOUNT)
# print(result)
# print(25*(result[0]-result[1])/AMOUNT)

Test 1

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 2

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 3

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 4

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 5

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 6

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 7

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...

Test 8

Verdict: RUNTIME ERROR

Traceback (most recent call last):
  File "/box/input/code.py", line 1, in <module>
    im...