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import scipy as sp
import sys, os
try:
import libmr
print ("Imported libmr succesfully")
except ImportError:
print ("Cannot import libmr")
sys.exit()
import pickle
svm_data = {}
svm_data["labels"] = [1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1,
1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1 , -1, -1, -1, -1, -1]
svm_data["scores"] = sp.randn(100).tolist()
fit_data = sp.rand(3)
def main():
mr = libmr.MR()
datasize = len(svm_data["scores"])
mr.fit_svm(svm_data, datasize, 1, 1, 1, 10)
print (fit_data)
print (mr.w_score_vector(fit_data))
mr.mr_save("meta_rec.model")
datadump = {}
datadump = {"data": fit_data}
f = open("data.dump", "w")
pickle.dump(datadump, f)
f.close()
print (dir(mr))
if __name__ == "__main__":
main()
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