代码看起来非常好。如果只绘制 4 个点(n=2
):
半径(几乎)恰好是r=0.5
您想要的坐标单位。等待,almost?!是的,问题是您在绘图之前确定坐标单位到图形点的大小,所以before设置限制,这会影响坐标单位,但不会影响整体图形大小......
听起来很奇怪?也许。最重要的是,您可以使用默认轴限制((0,1)
x (0,1)
)然后将它们放大到(-0.75, 15.75)
x(-0.75, 15.75)
...但是您没有减小标记大小。
所以要么将限制设置为已知大小before绘图:
ax.set_xlim((0,n-1))
ax.set_ylim((0,n-1))
完整的代码是:
import matplotlib.pyplot as plt
from numpy import pi
n = 16
# create a n x n square with a marker at each point as dummy data
x_data = []
y_data = []
for x in range(n):
for y in range(n):
x_data.append(x)
y_data.append(y)
# open figure
fig,ax = plt.subplots(figsize=[7,7])
# set limits BEFORE plotting
ax.set_xlim((0,n-1))
ax.set_ylim((0,n-1))
# radius in data coordinates:
r = 0.5 # units
# radius in display coordinates:
r_ = ax.transData.transform([r,0])[0] - ax.transData.transform([0,0])[0] # points
# marker size as the area of a circle
marker_size = pi * r_**2
# plot
ax.scatter(x_data, y_data, s=marker_size, edgecolors='black')
plt.show()
...或根据新的限制缩放标记的大小(您需要了解它们或再次进行绘图)
# plot with invisible color
ax.scatter(x_data, y_data, s=marker_size, color=(0,0,0,0))
# calculate scaling
scl = ax.get_xlim()[1] - ax.get_xlim()[0]
# plot correctly (with color)
ax.scatter(x_data, y_data, s=marker_size/scl**2, edgecolors='blue',color='red')
这是一个相当乏味的想法,因为您需要绘制数据两次,但保持轴的自动调整大小......
显然还留有一些间距。这是由于对以下内容的误解area的标记。我们不是在讨论符号的面积(在本例中是圆形),而是在讨论标记的边界框(想象一下,您想要控制作为标记的星星或星号的大小......人们永远不会计算符号的实际面积)。
所以计算面积不是pi * r_**2
而是一个正方形:(2*r_)**2
# open figure
fig,ax = plt.subplots(figsize=[7,7])
# setting the limits
ax.set_xlim((0,n-1))
ax.set_ylim((0,n-1))
# radius in data coordinates:
r = 0.5 # units
# radius in display coordinates:
r_ = ax.transData.transform([r,0])[0] - ax.transData.transform([0,0])[0] # points
# marker size as the area of a circle
marker_size = (2*r_)**2
# plot
ax.scatter(x_data, y_data, s=marker_size,linewidths=1)
#ax.plot(x_data, y_data, "o",markersize=2*r_)
plt.show()
As soon as you add an edge (so a non-zero border around the markers), they will overlap:
如果你使用的话会变得更加混乱plot
(如果所有标记的大小都与标记的大小相同,则速度会更快docs注明为“注释”)。这markersize
只是标记的宽度(不是面积):
ax.plot(x_data, y_data, "o",markersize=2*r_,color='magenta')