__author__ = "ponomarevandrew"
import recs
import dataModel
import numpy as np
dirs = ["BC"]
for dir in dirs:
prefs_test, data_test, matrix_test = dataModel.loadMovielens("/u1.test", matrix=dir)
b_u = np.loadtxt(dir + "/b_u.txt")
b_v = np.loadtxt(dir + "/b_v.txt")
u_f = np.loadtxt(dir + "/u_f.txt")
v_f = np.loadtxt(dir + "/v_f.txt")
f = open(dir + "/mu.txt", "r")
mu = float(f.read())
mae = recs.maeSVD(prefs_test, mu, b_u, b_v, u_f, v_f)
f = open(dir + "/mae_stoch_svd.txt", "w")
f.write(str(mae))
print "!233131"
__author__ = 'ponomarevandrew'
import dataModel
import recs
import numpy as np
a = np.arange(111)
np.savetxt("A/sims.txt", a)
b = np.loadtxt("A/sims.txt")
dirs = ["A","C","BC"]
for dir in dirs:
prefs,data,matrix = dataModel.loadMovielens('/u1.base',matrix = dir)
#matrix_A = recs.get_similarity_matrix(matrix, method ='knn' )
#np.savetxt(dir+"/sims_knn_user.txt",matrix_A)
matrix_B = recs.get_similarity_matrix(matrix, method ='knn_svd' )
np.savetxt(dir+"/sims_knn_svd.txt",matrix_B)
matrix_C = recs.get_similarity_matrix(matrix, method ='knn_nmf' )
np.savetxt(dir+"/sims_knn_nmf.txt",matrix_C)
#matrix_D = recs.get_similarity_matrix(matrix, method ='knn_item' )
#np.savetxt(dir+"/sims_knn_item.txt",matrix_D)
print 'aaaaa'
__author__ = 'ponomarevandrew'
import recs
import dataModel
import numpy as np
dirs = ["A","BC","C"]
names = ["knn_user", "knn_svd" , "knn_nmf", "knn_item"]
for dir in dirs:
for name in names:
prefs_trainig,data,matrix_training = dataModel.loadMovielens('/u1.base',matrix=dir)
prefs_test, data_test, matrix_test = dataModel.loadMovielens('/u1.test',matrix=dir)
sim_matrix = np.loadtxt(dir+ "/sims_"+ name + ".txt")
mae = recs.mae(prefs_test,prefs_trainig,sim_matrix)
f = open(dir +'/mae_' + name, 'w')
f.write(str(mae))
print "Aaaa"
