representation.py 文件源码

def plot2dRegression(x,y, nameX, nameY, namePlot):
    model = LinearRegression()
    linearModel = model.fit(x, y)
    predictModel = linearModel.predict(x)
    plt.scatter(x,y, color='g')
    plt.plot(x, predictModel, color='k')
    plt.xlabel(nameX)
    plt.ylabel(nameY)
    test = stats.linregress(predictModel,y)
    print("The squared of the correlation coefficient R^2 is " + str(test.rvalue**2))
    plt.savefig("plot/loadings/"+namePlot, bbox_inches='tight')
    plt.show()
    return test.rvalue**2

#plot the 2D regression between the performance values and the loadings.
#return the correlation factor: R squared