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)