with open(path, action, encoding="utf-8") as f: # open the file to write
f.write(data)
# function to pass dictionary to text
def dictToStr(dict):
strDict = ''
for k, v in dict.items():
strDict += f'{str(k)} -> {str(v)}\n'
return strDict
# Join dataSets and normalize
coord = Coordinator()
# joinedDS = coord.join(pathA, pathB)
# normalize joined Dataset
initPf = pd.read_csv(initPath, delimiter=';', encoding="ISO-8859-1")
initPf[initPf < 0] = 0
# initPf[(np.abs(stats.zscore(initPf)) < 3).all(axis=1)]
normPf = coord.normalize(initPf)
print('normPf ', str(normPf))
writeToFile(str(normPf), initNormed, 'w')
# # Run Spectral clustering for k 2 to k 10
labelsList = coord.runConfig(normPf.head(100))
# Run best k spectral clustering
resultDict = coord.run(normPf.head(100), 3, labelsList)
strResDict = dictToStr(resultDict)
writeToFile(strResDict, resultsPath, 'w')
