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%matplotlib inline
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import numpy as np
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import matplotlib.pyplot as plt
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def lecture(name):
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lst_date = []
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lst_conso = []
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lst_t_moy = []
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lst_t_ref = []
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with open(name) as fic:
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fic.readline()
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for ligne in fic:
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date,conso, t_moy, t_ref = ligne.split(';')
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lst_date.append(date)
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lst_conso.append(float(conso))
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lst_t_moy.append(float(t_moy))
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lst_t_ref.append(float(t_ref))
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return(np.array(lst_date), np.array(lst_conso), np.array(lst_t_moy), np.array(lst_t_ref))
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def numero_jour (date):
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return date.split("-")[2]
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def distance (pos1, pos2):
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x1, y1, z1 = pos1
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x2, y2, z2 = pos2
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return np.sqrt(((x1-x2)**2)+((y1-y2)**2)+((z1-z2)**2))
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def kPlusProches(echantillon, donnees, k):
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voisins = []
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for i in range(len(donnees)):
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date, conso, t_moy = donnees[i]
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print(donnees[i])
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d = distance(echantillon, (date, conso, t_moy))
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voisins.append((d, i))
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return [voisins[i][1] for i in range(k)]
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num_jour = []
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dates, consos, t_moys, t_refs = lecture("pic-journalier-consommation.csv")
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for date in dates:
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num_jour.append(numero_jour(date))
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coords = list(zip(num_jour, t_moys, t_refs))
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kPlusProches((13, 21.0, 20.6), coords, 4)
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