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loadCSV.py
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loadCSV.py
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import csv
import numpy as np
from os import listdir
from os.path import isfile, join
def load_one_CSV(file):
adyacence= {}
vector = []
nodes = []
csv.register_dialect('myDialect',
delimiter = ',',
skipinitialspace=True)
with open(file, 'r') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
d = dict(row)
n = d['node']
n = n.replace(" ","")
n = n.lower()
#v = d['vector']
d.pop('node')
adyacence[n]= d
csvfile.close()
#print("\n**",adyacence,"\n**")
return adyacence
def load_multiple_CSV(path):
files = [ f for f in listdir(path) if isfile (join(path,f)) ]
matriza={}
for f in files :
if f[-4:] == ".csv" or f[-4:] == ".CSV":
matrizb = load_one_CSV(f)
addMatriz(matriza,matrizb)
return matriza
def addMatriz(matriza, matrizb):
for i, elements in matrizb.items():
i = i.replace(" ","")
i = i.lower()
if i in matriza:
# Si esta en el vector original se recupera
va = matriza[i]
for j, k in elements.items():
# se recorren los elementos del vector b
# se verifica si j el indice esta en el vector a
# Si esta se suman
if j in va:
#print(va[j])
x = float(va[j])
y = float(elements[j])
va[j]= str(x+y)
# si no se agrega
else :
va[j]=k
else :
matriza[i]=elements
return matriza
def adyacence_to_matrx(dict ):
# dict
key_list =list( dict.keys() )
#key_list = list(map(lambda x : x.replace(" ",""),key_list))
vector = []
#print(key_list)
l = len(key_list)
mat = np.zeros( (l,l) ,dtype=float)
for i, elements in dict.items():
# x --> y mät¨[x][y]
x = key_list.index(i)
v = elements['vector']
elements.pop('vector')
vector.append(v)
for j, k in elements.items():
j = j.replace(" ","")
j = j.lower()
y = key_list.index(j)
mat[x][y] = float (k)
return key_list , mat , vector
def fuzzy_from_csv( path, opc = 'f' ):
if opc == 'f':
adyacence = load_one_CSV(path)
elif opc == 'd':
adyacence = load_multiple_CSV(path)
##print(adyacence)
key_list , mat , vector = adyacence_to_matrx(adyacence)
return key_list , mat , np.array(vector,dtype=float)
#matriz = fuzzy_from_csv(".", 'd' )
#print(matriz)