python - 填充多边形外部 |索引超出圆形边界的掩码数组？

Question

我使用 plot(x,y,'r') 绘制一个红色圆圈。 x 和 y 是这样的数组，当作为 (x,y) 配对并绘制时，所有点形成一条圆线。

fill(x,y,'r') 绘制一个用红色填充(或着色)的红色圆圈。

如何让圆圈内部保持白色，但在圆圈外部填充到轴边界？

我研究过使用 fill_between(x_array, y1_array, y2_array, where) 但在试用了一下之后，我认为它不适用于我的 x,y 数组。我想 fill_between() 在圆外，在由轴边界定义的正方形内，但我不认为 fill_between() 有能力……我我确信我可以将它变成一个整数类型的问题，其中 delta x 和 delta y 将变为零，但我不愿意。

如果有人看到我在 fill_between() 中遗漏了什么，请告诉我。

我真正需要做的就是屏蔽掉位于由 x 和 y 创建的圆的边界之外的二维数组中的数字，这样当二维数组被视为内部的彩色图或轮廓时圆圈是图像，外面是白色的。

这可以通过二维阵列的掩蔽技术来实现吗？就像使用 masked_where() 一样？我还没有调查过，但会的。

有什么想法吗？谢谢

编辑 1:这是我有权展示的内容，我认为可以解释我的问题。

from pylab import *
from matplotlib.path import Path
from matplotlib.patches import PathPatch

f=Figure()
a=f.add_subplot(111)

# x,y,z are 2d arrays

# sometimes i plot a color plot
# im = a.pcolor(x,y,z)
a.pcolor(x,y,z)

# sometimes i plot a contour
a.contour(x,y,z)

# sometimes i plot both using a.hold(True)

# here is the masking part.
# sometimes i just want to see the boundary drawn without masking
# sometimes i want to see the boundary drawn with masking inside of the boundary
# sometimes i want to see the boundary drawn with masking outside of the boundary

# depending on the vectors that define x_bound and y_bound, sometimes the boundary
# is a circle, sometimes it is not.

path=Path(vpath)
patch=PathPatch(path,facecolor='none')
a.add_patch(patch) # just plots boundary if anything has been previously plotted on a
if ('I want to mask inside'):
    patch.set_facecolor('white') # masks(whitens) inside if pcolor is currently on a,
    # but if contour is on a, the contour part is not whitened out. 
else: # i want to mask outside 
    im.set_clip_path(patch) # masks outside only when im = a.pcolor(x,y,z)
    # the following commands don't update any masking but they don't produce errors?
    # patch.set_clip_on(True)
    # a.set_clip_on(True)
    # a.set_clip_path(patch)

a.show()

Answer 1

All I am really needing to do is mask out numbers in a 2d array that are located beyond this boundary of the circle created with x and y, such that when the 2D array is viewed as a color plot, or contour, inside the circle will be the image, and outside will be white-ed out.

你有两个选择:

首先，您可以为图像使用掩码数组。这更复杂，但更安全。要屏蔽圆外的阵列，从中心点生成距离图，并屏蔽距离大于半径的位置。

更简单的选择是在绘制图像后使用 im.set_clip_path() 剪切补丁之外的区域。

参见 this example from the matplotlib gallery .不幸的是，根据我的经验，对于某些轴(非笛卡尔轴)，这可能有点小问题。不过，在所有其他情况下，它应该都能完美运行。

编辑:顺便说一句，this is how to do what you originally asked :绘制一个内部有孔的多边形。不过，如果您只想遮盖图像，最好选择上述两个选项之一。

Edit2:只是举一个简单的例子来说明这两种方式......

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.patches as patches

def main():
    # Generate some random data
    nx, ny = 100, 100
    data = np.random.random((ny,nx))

    # Define a circle in the center of the data with a radius of 20 pixels
    radius = 20
    center_x = nx // 2
    center_y = ny // 2

    plot_masked(data, center_x, center_y, radius)
    plot_clipped(data, center_x, center_y, radius)
    plt.show()

def plot_masked(data, center_x, center_y, radius):
    """Plots the image masked outside of a circle using masked arrays"""
    # Calculate the distance from the center of the circle
    ny, nx = data.shape
    ix, iy = np.meshgrid(np.arange(nx), np.arange(ny))
    distance = np.sqrt((ix - center_x)**2 + (iy - center_y)**2)

    # Mask portions of the data array outside of the circle
    data = np.ma.masked_where(distance > radius, data)

    # Plot
    plt.figure()
    plt.imshow(data)
    plt.title('Masked Array')

def plot_clipped(data, center_x, center_y, radius):
    """Plots the image clipped outside of a circle by using a clip path"""
    fig = plt.figure()
    ax = fig.add_subplot(111)

    # Make a circle
    circ = patches.Circle((center_x, center_y), radius, facecolor='none')
    ax.add_patch(circ) # Plot the outline

    # Plot the clipped image
    im = ax.imshow(data, clip_path=circ, clip_on=True)

    plt.title('Clipped Array')

main()

编辑 2:在原始图上绘制 mask 多边形:这里有一些关于如何绘制一个多边形的更多细节，该多边形在当前绘图上掩盖了它之外的所有内容。显然，没有更好的方法来裁剪等高线图(无论如何我都能找到...)。

import numpy as np
import matplotlib.pyplot as plt

def main():
    # Contour some regular (fake) data
    grid = np.arange(100).reshape((10,10))
    plt.contourf(grid)

    # Verticies of the clipping polygon in counter-clockwise order
    #  (A triange, in this case)
    poly_verts = [(2, 2), (5, 2.5), (6, 8), (2, 2)]

    mask_outside_polygon(poly_verts)

    plt.show()

def mask_outside_polygon(poly_verts, ax=None):
    """
    Plots a mask on the specified axis ("ax", defaults to plt.gca()) such that
    all areas outside of the polygon specified by "poly_verts" are masked.  

    "poly_verts" must be a list of tuples of the verticies in the polygon in
    counter-clockwise order.

    Returns the matplotlib.patches.PathPatch instance plotted on the figure.
    """
    import matplotlib.patches as mpatches
    import matplotlib.path as mpath

    if ax is None:
        ax = plt.gca()

    # Get current plot limits
    xlim = ax.get_xlim()
    ylim = ax.get_ylim()

    # Verticies of the plot boundaries in clockwise order
    bound_verts = [(xlim[0], ylim[0]), (xlim[0], ylim[1]), 
                   (xlim[1], ylim[1]), (xlim[1], ylim[0]), 
                   (xlim[0], ylim[0])]

    # A series of codes (1 and 2) to tell matplotlib whether to draw a line or 
    # move the "pen" (So that there's no connecting line)
    bound_codes = [mpath.Path.MOVETO] + (len(bound_verts) - 1) * [mpath.Path.LINETO]
    poly_codes = [mpath.Path.MOVETO] + (len(poly_verts) - 1) * [mpath.Path.LINETO]

    # Plot the masking patch
    path = mpath.Path(bound_verts + poly_verts, bound_codes + poly_codes)
    patch = mpatches.PathPatch(path, facecolor='white', edgecolor='none')
    patch = ax.add_patch(patch)

    # Reset the plot limits to their original extents
    ax.set_xlim(xlim)
    ax.set_ylim(ylim)

    return patch

if __name__ == '__main__':
    main()