如何控制Matplotlib绘图中箭头标记的点间距与行间距？

你当前的需求是消除箭头间的水平空隙、减小行间距，同时保留x轴显示箭头数量的特性。问题出在Matplotlib默认的自动坐标轴缩放会给元素周围预留空白，仅调整figsize无法解决，我们需要通过手动控制坐标轴范围和布局来实现紧密排列。

以下是具体的解决方案和修改后的代码：

核心修改点 #

• 使用matplotlib.axes.Axes对象替代全局plt调用，获得更精细的布局控制
• 手动设置x/y轴的显示范围，让箭头标记紧密贴合
• 调整子图边距，去除多余空白
• 可选：调整y轴刻度的间距进一步压缩行空间

修改后的完整代码 #

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

def arrowplot(path, max_LU=0, names=""):
    if isinstance(path[0], int):
        # There is only one sequence in "subpaths"
        path = [path]
    # get discrete colormap
    colors_rainbow = cm.hsv(np.linspace(0, 1, max_LU))
    # Find the row that has the most amount of triangles.
    longest_path = max([len(x) for x in path])
    num_paths = len(path)
    
    # 使用子图对象进行精细控制
    fig, ax = plt.subplots(figsize=(longest_path, num_paths*1))  # 调整figsize的垂直比例
    for i in range(num_paths):
        for j in range(len(path[i])):
            colour = colors_rainbow[abs(path[i][j]) - 1]
            if path[i][j] >= 0:
                ax.scatter(j, i, color=colour, marker=">", s=100, edgecolor="black")
            else:
                ax.scatter(j, i, color=colour, marker="<", s=100, edgecolor="black")
    
    # 设置坐标轴范围，消除空隙：每个点(j,i)位于网格中心，范围从-0.5到对应最大值-0.5
    ax.set_xlim(-0.5, longest_path - 0.5)
    ax.set_ylim(-0.5, num_paths - 0.5)
    
    # 设置y轴刻度
    if names == "":
        names = range(num_paths)
    ax.set_yticks(ticks=range(num_paths), labels=names)
    
    # 保留x轴显示箭头数量的特性，设置x轴刻度为0到longest_path-1
    ax.set_xticks(ticks=range(longest_path))
    
    # 调整子图边距，去除多余空白
    plt.tight_layout()
    
    plt.savefig("arrowplot.png", format="png", dpi=200, bbox_inches='tight')
    plt.show()
    plt.close()
    return None

# 示例测试
A = [1,2,3,9,4,5]
B = [2,3,5,-1,7,4,5]
arrowplot([A,B], names=["A", "B"], max_LU=9)

# 另一个示例
ref = list(range(1, 45, 1))
A2 = [1, 2, 3, 4, 5, 6, 7, -13, -12, -1, -44, -43, -42, -41, -40, 39, -38, -37, -36, 8, 9, 11, 14, 15, 16, 17, 19, 20, 21, -37, -36, 19, 20, 14, 15, 16, -24, -23, -22, 17, 18, -31, -30, -29, -28, -27, -26, -25, -24, -23, -22, -21, -20, -19, -17, -16, -15, -14, -11, -10, -9, -8, 36, 37, 38, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, -18, -17, 22, 23, 24, -16, -15, -14, -20, -19, 36, 37, 38, -39, 40, 41, 42, 43, 44]
B2 = [1, 2, 3, 4, 5, 6, 7, -13, -12, -1, -44, -43, -42, -41, -40, 39, -38, -37, -36, 8, 9, 11, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, -18, -17, 22, 23, 24, -16, -15, -14, -20, -19, 36, 37, -21, -20, -19, -17, -38, -37, -36, 8, 9, 10, 11, 14, 15, 16, 17, 19, 20, 21, 22, 23, 24, 25, 26, 27, 29, 30, 31, -18, -17, 22, 23, 24, -16, -15, -14, -20, -19, 36, 37, 38, -39, 40, 41, 42, 43, 44]
names = ["A", "B", "C"]
arrowplot([ref, A2, B2], max_LU=44, names=names)

关键修改解释 #

1. 坐标轴范围设置：ax.set_xlim(-0.5, longest_path - 0.5)和ax.set_ylim(-0.5, num_paths - 0.5)让每个箭头标记刚好填满对应的网格单元，消除了水平和垂直方向的空隙。
2. 子图边距调整：plt.tight_layout()和bbox_inches='tight'确保保存图片时没有多余的空白区域。
3. figsize垂直比例调整：把len(path)*1.5改为num_paths*1，进一步压缩垂直方向的布局空间，你可以根据需要微调这个系数。
4. 保留x轴计数特性：ax.set_xticks(ticks=range(longest_path))确保x轴显示所有箭头的位置序号，符合你的需求。

内容的提问来源于stack exchange，提问作者Marco Monti