对于类似的问题，以前有一些答案（例如https://stackoverflow.com/a/22081678/325565），但他们推荐了一种次优方法。
前面的大多数答案都建议在pcolormesh填充上绘制一个白色多边形。这并不理想，原因有两个：
1.轴的背景不能是透明的，因为有一个填充的多边形覆盖它

1. pcolormesh的绘制速度相当慢，而且插值不平滑。
   这是一个触摸更多的工作，但有一个方法，绘制速度更快，并提供了更好的视觉效果：设置与imshow绘制的图像的剪辑路径。
   例如：

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.patches import Polygon
np.random.seed(1977)

def main():
    for _ in range(5):
        gradient_fill(*generate_data(100))
    plt.show()

def generate_data(num):
    x = np.linspace(0, 100, num)
    y = np.random.normal(0, 1, num).cumsum()
    return x, y

def gradient_fill(x, y, fill_color=None, ax=None, **kwargs):
    """
    Plot a line with a linear alpha gradient filled beneath it.

    Parameters
    ----------
    x, y : array-like
        The data values of the line.
    fill_color : a matplotlib color specifier (string, tuple) or None
        The color for the fill. If None, the color of the line will be used.
    ax : a matplotlib Axes instance
        The axes to plot on. If None, the current pyplot axes will be used.
    Additional arguments are passed on to matplotlib's ``plot`` function.

    Returns
    -------
    line : a Line2D instance
        The line plotted.
    im : an AxesImage instance
        The transparent gradient clipped to just the area beneath the curve.
    """
    if ax is None:
        ax = plt.gca()

    line, = ax.plot(x, y, **kwargs)
    if fill_color is None:
        fill_color = line.get_color()

    zorder = line.get_zorder()
    alpha = line.get_alpha()
    alpha = 1.0 if alpha is None else alpha

    z = np.empty((100, 1, 4), dtype=float)
    rgb = mcolors.colorConverter.to_rgb(fill_color)
    z[:,:,:3] = rgb
    z[:,:,-1] = np.linspace(0, alpha, 100)[:,None]

    xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
    im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
                   origin='lower', zorder=zorder)

    xy = np.column_stack([x, y])
    xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]])
    clip_path = Polygon(xy, facecolor='none', edgecolor='none', closed=True)
    ax.add_patch(clip_path)
    im.set_clip_path(clip_path)

    ax.autoscale(True)
    return line, im

main()

• 请注意，Joe Kington在这里应该得到最大的荣誉;我唯一的贡献是zfunc。* 他的方法为许多渐变/模糊/阴影效果打开了大门。例如，为了使线条具有均匀模糊的底面，您可以使用PIL构建一个alpha层，该层靠近线条为1，靠近底部边缘为0。

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
import matplotlib.patches as patches
from PIL import Image
from PIL import ImageDraw
from PIL import ImageFilter

np.random.seed(1977)
def demo_blur_underside():
    for _ in range(5):
        # gradient_fill(*generate_data(100), zfunc=None) # original
        gradient_fill(*generate_data(100), zfunc=zfunc)
    plt.show()

def generate_data(num):
    x = np.linspace(0, 100, num)
    y = np.random.normal(0, 1, num).cumsum()
    return x, y

def zfunc(x, y, fill_color='k', alpha=1.0):
    scale = 10
    x = (x*scale).astype(int)
    y = (y*scale).astype(int)
    xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()

    w, h = xmax-xmin, ymax-ymin
    z = np.empty((h, w, 4), dtype=float)
    rgb = mcolors.colorConverter.to_rgb(fill_color)
    z[:,:,:3] = rgb

    # Build a z-alpha array which is 1 near the line and 0 at the bottom.
    img = Image.new('L', (w, h), 0)  
    draw = ImageDraw.Draw(img)
    xy = np.column_stack([x, y])
    xy -= xmin, ymin
    # Draw a blurred line using PIL
    draw.line(list(map(tuple, xy)), fill=255, width=15)
    img = img.filter(ImageFilter.GaussianBlur(radius=100))
    # Convert the PIL image to an array
    zalpha = np.asarray(img).astype(float) 
    zalpha *= alpha/zalpha.max()
    # make the alphas melt to zero at the bottom
    n = zalpha.shape[0] // 4
    zalpha[:n] *= np.linspace(0, 1, n)[:, None]
    z[:,:,-1] = zalpha
    return z

def gradient_fill(x, y, fill_color=None, ax=None, zfunc=None, **kwargs):
    if ax is None:
        ax = plt.gca()

    line, = ax.plot(x, y, **kwargs)
    if fill_color is None:
        fill_color = line.get_color()

    zorder = line.get_zorder()
    alpha = line.get_alpha()
    alpha = 1.0 if alpha is None else alpha

    if zfunc is None:
        h, w = 100, 1
        z = np.empty((h, w, 4), dtype=float)
        rgb = mcolors.colorConverter.to_rgb(fill_color)
        z[:,:,:3] = rgb
        z[:,:,-1] = np.linspace(0, alpha, h)[:,None]
    else:
        z = zfunc(x, y, fill_color=fill_color, alpha=alpha)
    xmin, xmax, ymin, ymax = x.min(), x.max(), y.min(), y.max()
    im = ax.imshow(z, aspect='auto', extent=[xmin, xmax, ymin, ymax],
                   origin='lower', zorder=zorder)

    xy = np.column_stack([x, y])
    xy = np.vstack([[xmin, ymin], xy, [xmax, ymin], [xmin, ymin]])
    clip_path = patches.Polygon(xy, facecolor='none', edgecolor='none', closed=True)
    ax.add_patch(clip_path)
    im.set_clip_path(clip_path)
    ax.autoscale(True)
    return line, im

demo_blur_underside()

收益率

我试过了：

import matplotlib.pyplot as plt
import numpy as np

fig = plt.figure()

xData = range(100)
yData = range(100)
plt.plot(xData, yData)

NbData = len(xData)
MaxBL = [[MaxBL] * NbData for MaxBL in range(100)]
Max = [np.asarray(MaxBL[x]) for x in range(100)]

for x in range (50, 100):
  plt.fill_between(xData, Max[x], yData, where=yData >Max[x], facecolor='red', alpha=0.02)

for x in range (0, 50):
  plt.fill_between(xData, yData, Max[x], where=yData <Max[x], facecolor='green', alpha=0.02)

plt.fill_between([], [], [], facecolor='red', label="x > 50")
plt.fill_between([], [], [], facecolor='green', label="x < 50")

plt.legend(loc=4, fontsize=12)
plt.show()
fig.savefig('graph.png')

结果是

当然，通过改变feel_between函数的范围，梯度可以下降到0。