Python 雷达图中的置信区间（区域未关闭）

我试图在雷达图中绘制包含置信区间的数据

我遵循matplotlib文档并进行了更改以添加错误区域，但它显示了Cat.1和Cat.9之间的空白区域，如图所示。 当我在θ计算中将端点设置为true时，我丢失了一个数据点

如何在不丢失数据点的情况下修复它

以下是修改后的代码：

import numpy as np

import matplotlib.pyplot as plt
from matplotlib.patches import Circle, RegularPolygon
from matplotlib.path import Path
from matplotlib.projections.polar import PolarAxes
from matplotlib.projections import register_projection
from matplotlib.spines import Spine
from matplotlib.transforms import Affine2D


def radar_factory(num_vars, frame='circle'):
    """
    Create a radar chart with `num_vars` axes.

    This function creates a RadarAxes projection and registers it.

    Parameters
    ----------
    num_vars : int
        Number of variables for radar chart.
    frame : {'circle', 'polygon'}
        Shape of frame surrounding axes.

    """
    # calculate evenly-spaced axis angles
    theta = np.linspace(0, 2*np.pi, num_vars, endpoint=False)

    class RadarAxes(PolarAxes):

        name = 'radar'
        # use 1 line segment to connect specified points
        RESOLUTION = 1

        def __init__(self, *args, **kwargs):
            super().__init__(*args, **kwargs)
            # rotate plot such that the first axis is at the top
            self.set_theta_zero_location('N')

        def fill(self, *args, closed=True, **kwargs):
            """Override fill so that line is closed by default"""
            return super().fill(closed=closed, *args, **kwargs)


        def plot(self, *args, **kwargs):
            """Override plot so that line is closed by default"""
            lines = super().plot(*args, **kwargs)
            for line in lines:
                self._close_line(line)

        def _close_line(self, line):
            x, y = line.get_data()
            # FIXME: markers at x[0], y[0] get doubled-up
            if x[0] != x[-1]:
                x = np.append(x, x[0])
                y = np.append(y, y[0])
                line.set_data(x, y)

        def set_varlabels(self, labels):
            self.set_thetagrids(np.degrees(theta), labels)

        def _gen_axes_patch(self):
            # The Axes patch must be centered at (0.5, 0.5) and of radius 0.5
            # in axes coordinates.
            if frame == 'circle':
                return Circle((0.5, 0.5), 0.5)
            elif frame == 'polygon':
                return RegularPolygon((0.5, 0.5), num_vars,
                                      radius=.5, edgecolor="k")
            else:
                raise ValueError("Unknown value for 'frame': %s" % frame)

        def _gen_axes_spines(self):
            if frame == 'circle':
                return super()._gen_axes_spines()
            elif frame == 'polygon':
                # spine_type must be 'left'/'right'/'top'/'bottom'/'circle'.
                spine = Spine(axes=self,
                              spine_type='circle',
                              path=Path.unit_regular_polygon(num_vars))
                # unit_regular_polygon gives a polygon of radius 1 centered at
                # (0, 0) but we want a polygon of radius 0.5 centered at (0.5,
                # 0.5) in axes coordinates.
                spine.set_transform(Affine2D().scale(.5).translate(.5, .5)
                                    + self.transAxes)
                return {'polar': spine}
            else:
                raise ValueError("Unknown value for 'frame': %s" % frame)

    register_projection(RadarAxes)
    return theta


def example_data():
    data = [
        ['Cat. 1', 'Cat. 2', 'Cat. 3', 'Cat. 4', 'Cat. 5', 'Cat. 6', 'Cat. 7', 'Cat. 8', 'Cat. 9'],
        ('mean1', [
            [5, 5, 5, 5, 5, 5, 5, 5, 5]]),
        ('upper1', [
            [6, 6, 6, 6, 6, 6, 6, 6, 6]]),
        ('lower1', [
            [4, 4, 4, 4, 4, 4, 4, 4, 4]]),
        
        ('mean2', [
            [2, 2, 2, 2, 2, 2, 2, 2, 2]]),
        ('upper2', [
            [3, 3, 3, 3, 3, 3, 3, 3, 3]]),
        ('lower2', [
            [1, 1, 1, 1, 1, 1, 1, 1, 1]])


         ]
    return data


if __name__ == '__main__':
    N = 9
    theta = radar_factory(N, frame='circle')

    data = example_data()
    labels = data.pop(0)
    mean_data=[data[0][1], data[3][1]]
    upper_data=[data[1][1], data[4][1]]
    lower_data=[data[2][1], data[5][1]]



    fig, axs = plt.subplots(figsize=(9, 9), nrows=1, ncols=1,
                            subplot_kw=dict(projection='radar'))
    
    fig.subplots_adjust(wspace=0.25, hspace=0.20, top=0.85, bottom=0.05)

    colors = ['b', 'r']
    # Plot the two cases from the example data on separate axes
    for d, u, l, color in zip(mean_data, upper_data, lower_data, colors):
        axs.plot(theta, d[0], color=color)
        axs.fill_between(theta, u[0], l[0], facecolor=color, alpha=0.2)
    axs.set_varlabels(labels)

    # add legend relative to top-left plot
    labels = ('Factor 1', 'Factor 2')
    legend = axs.legend(labels, loc=(0.9, .95),
                              labelspacing=0.1, fontsize='small')

    plt.show()

---

我修改了前面提到的代码，添加了置信区间，它可以正常工作，请参见

categories =['Cat. 1', 'Cat. 2', 'Cat. 3', 'Cat. 4', 'Cat. 5', 'Cat. 6', 'Cat. 7', 'Cat. 8', 'Cat. 9']
categories = [*categories, categories[0]]

mean =  [5, 5, 5, 5, 5, 5, 5, 5, 5]
upper = [6, 6, 6, 6, 6, 6, 6, 6, 6]
lower =  [4, 4, 4, 4, 4, 4, 4, 4, 4]

mean = [*mean, mean[0]]
upper = [*upper, upper[0]]
lower = [*lower, lower[0]]

mean1= [2, 2, 2, 2, 2, 2, 2, 2, 2]
upper1=[3, 3, 3, 3, 3, 3, 3, 3, 3]
lower1=[1, 1, 1, 1, 1, 1, 1, 1, 1]

mean1 = [*mean1, mean1[0]]
upper1 = [*upper1, upper1[0]]
lower1 = [*lower1, lower1[0]]

label_loc = np.linspace(start=0, stop=2 * np.pi, num=len(mean))

plt.figure(figsize=(8, 8))
plt.subplot(polar=True)
plt.plot(label_loc, mean, label='Factor 1',color='b')
plt.fill_between(label_loc, upper, lower, facecolor='b', alpha=0.2)

plt.subplot(polar=True)
plt.plot(label_loc, mean1, label='Factor 2',color='r')
plt.fill_between(label_loc, upper1, lower1, facecolor='r', alpha=0.2)


lines, labels = plt.thetagrids(np.degrees(label_loc), labels=categories)
plt.legend()
plt.show()