Density.py 文件源码

def displayDataset(self, dataset):
        eps = 0.00001
        linewidth = dataset.linewidth
        if np.var(dataset.values) < eps:
            linewidth += 2
            mean = np.mean(dataset.values)
            x = np.arange(0, 1, 0.1)
            x = np.sort(np.append(x, [mean, mean-eps, mean+eps]))
            density = [1 if v == mean else 0 for v in x]
        else:
            self.kde.fit(np.asarray([[x] for x in dataset.values]))
            ## Computes the x axis
            x_max = np.amax(dataset.values)
            x_min = np.amin(dataset.values)
            delta = x_max - x_min
            density_delta = 1.1 * delta
            x = np.arange(x_min, x_max, density_delta / self.num_points)
            x_density = [[y] for y in x]
            ## kde.score_samples returns the 'log' of the density
            log_density = self.kde.score_samples(x_density).tolist()
            density = map(math.exp, log_density)
        self.ax.plot(x, density, label = dataset.label, color = dataset.color,
                linewidth = linewidth, linestyle = dataset.linestyle)