使用连续标准化颜色图填充函数下的区域

Fill area under function with a continuous normalized colormap

这是取自 Mathematica 的示例。

Plot[Abs[Exp[2 I x - x^2/2]], {x, -4, 4}, Filling -> Axis,
FillingStyle -> Automatic,
ColorFunction -> Function[{x, y}, Hue[Rescale[Arg[Exp[2 I x - x^2/2]], {-Pi, Pi}]]],
ColorFunctionScaling -> False]

即产生下图

我想在 python 中制作一个等效的情节。 matplotlib 是否有等效的颜色函数选项?

这不像您的 Mathematica 示例那么优雅,但以下代码在 matplotlib 中复制了您的示例。基本思想是将函数绘制为不可见的多边形,显示归一化颜色图的图像(使用自定义范数函数将值包装在 ±pi/2 之外),然后将函数多边形作为剪贴蒙版应用于该图像.

代码:

# Function (improve smoothness of plot by increasing samples from 500)
x = np.linspace(-4,4,500)
y = abs(np.e**(2j*x - x**2/2))

# Set up figure
fig, ax = plt.subplots()
ax.set_ylim(ymin=0, ymax=1)

# Plot line without fill
line, = ax.fill(x, y, facecolor='none')

# Reshape x data for applying cmap
img_data = x.reshape(1, x.size)

# Set up norm between + and - pi/2
norm = mpl.colors.Normalize(vmin=-np.pi/2, vmax=np.pi/2)

# Use hsv cmap (cyclic rainbow)
cmap=plt.cm.hsv

# Function to apply norm cyclicly
def f(x):
    return norm(x)%1

# Apply modified norm to img_data
cmap_data = f(img_data)

# Get limits
xmin, xmax = np.min(x), np.max(x)
ymin, ymax = np.min(y), np.max(y)

# Show cmap image
im = ax.imshow(cmap_data, aspect='auto', cmap=cmap, extent=[xmin,xmax,ymin,ymax])

# Clip image along line
im.set_clip_path(line)

输出: