def testRiemannMDM(mult_donnees):
print("debut test riemann MDM")
result = []
for r, donnees in mult_donnees.items():
print("r = " + str(r))
m = GenericModele(pyriemann.classification.MDM(), donnees)
m.dataToCov()
s = m.f1Score()
result.append([r, s])
print("reactionTime,f1score : " + str(result))
return result
def testRiemannKNN(mult_donnees,mesDonnees_test):
print("debut test riemann KNN")
result=[]
for r,donnees in mult_donnees.items():
print("r = "+str(r))
m = GenericModele(pyriemann.classification.KNearestNeighbor(n_neighbors=3),donnees)
m.dataToCov()
m.fit()
s = m.score(mesDonnees_test[r].data,mesDonnees_test[r].labels)
result.append([r,s])
print("reactionTime,f1score : "+str(result))
return result
def testCovSVM(mult_donnees):
print("debut test cov SVM")
result = []
for r, donnees in mult_donnees.items():
print("r = " + str(r))
clf = SVC(gamma='auto', probability=True, max_iter=100, verbose=1)
m = GenericModele(clf, donnees)
m.dataToCov()
m.vectorize()
s = m.f1Score()
result.append([r, s])
print("reactionTime,f1score : " + str(result))
return result
import pyriemann
import csv
def saveResult(name, result):
myfile = open(name, 'w')
wr = csv.writer(myfile, quoting=csv.QUOTE_ALL)
wr.writerow(["Time(second)", "F1 Score"])
for r in result:
wr.writerow(r)
reactTimeToTest = [1, 0.1, 0.04]
for r in reactTimeToTest:
print(r)
result = []
for k in range(1, 50, 2):
m = GenericModele(
r, pyriemann.classification.KNearestNeighbor(n_neighbors=k))
m.load_data_from_file("data/subject1/Session1/1.gdf")
m.dataToCov()
s = m.f1Score()
result.append([k, s])
plt.clf()
f = plt.figure()
plt.plot([re[0] for re in result], [re[1] for re in result])
name = "resultats/riemannKNN_valeur_de_k_pour_time_" + str(r)
f.savefig(name + ".pdf", bbox_inches='tight')
saveResult(name + ".csv", result)
