将散点图分配给特定箱时出错 [重复]

Question

我正在尝试count 在特定的分箱区域中scatter points 的数量。当我使用 XY 数据中的单个 row 时，code 有效，但是当我尝试使用 iterate 相同的 script 超过众多 rows 时，TypeError 被返回：

TypeError: only length-1 arrays can be converted to Python scalars

例子：

import math
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np

np.random.seed(42)
X = np.random.randint(-80, 80, size=(100, 10))
Y = np.random.randint(0, 120, size=(100, 10))  

fig, ax = plt.subplots()

BIN_23_X = 0 
ang1 = -60, 60
ang2 = 60, 60
angle = math.degrees(math.acos(2/9.15))
E_xy = 0,60

Halfway = mpl.lines.Line2D((BIN_23_X,BIN_23_X), (0,125), color = 'white', lw = 1.5, alpha = 0.8, zorder = 1)
arc1 = mpl.patches.Arc(ang1, 70, 110, angle = 0, theta2 = angle, theta1 = 360-angle, color = 'white', lw = 2)
arc2 = mpl.patches.Arc(ang2, 70, 110, angle = 0, theta2 = 180+angle, theta1 = 180-angle, color = 'white', lw = 2)
Oval = mpl.patches.Ellipse(E_xy, 160, 130, lw = 3, edgecolor = 'black', color = 'white', alpha = 0.2)

ax.add_line(Halfway)
ax.add_patch(arc1)
ax.add_patch(arc2)
ax.add_patch(Oval)

ov1 = mpl.patches.Ellipse(ang1, 70, 110, alpha=0)
ov2 = mpl.patches.Ellipse(ang2, 70, 110, alpha=0)
ax.add_patch(ov1)
ax.add_patch(ov2)

for px, py in zip(X, Y):
    #Error occurs in the line below
    in_oval = Oval.contains_point(ax.transData.transform(([px, py])), 0)
    in_left = ov1.contains_point(ax.transData.transform(([px, py])), 0)
    in_right = ov2.contains_point(ax.transData.transform(([px, py])), 0)
    on_left = px < 0
    on_right = px > 0
    if in_oval:
        if in_left:
            n_bin = 1
        elif in_right:
            n_bin = 4
        elif on_left:
            n_bin = 2
        elif on_right:
            n_bin = 3
        else:
            n_bin = -1
    else:
        n_bin = -1

def bin_counts(xA, yA):
    bc = dict()
    E = Oval.contains_points(ax.transData.transform(np.array([xA, yA]).T), 0)
    E_l = ov1.contains_points(ax.transData.transform(np.array([xA, yA]).T), 0)
    E_r = ov2.contains_points(ax.transData.transform(np.array([xA, yA]).T), 0)
    L = np.array(xA) < 0
    R = np.array(xA) > 0
    bc[1] = np.sum(E & E_l)
    bc[2] = np.sum(E & L & ~E_l)
    bc[3] = np.sum(E & R & ~E_r)
    bc[4] = np.sum(E & E_r)
    return bc        

for xr, yr in zip(X, Y):
    print(bin_counts(xr, yr))

此行出现错误

in_oval = Oval.contains_point(ax.transData.transform(([px, py])), 0)

追溯：

Studies/Datasets/codes/untitled4.py", line 73, in <module>
    in_oval = Oval.contains_point(ax.transData.transform(([px, py])), 0)

  File "/Users/jeremyalexander/anaconda/lib/python3.6/site-packages/matplotlib/patches.py", line 154, in contains_point
radius)

  File "/Users/jeremyalexander/anaconda/lib/python3.6/site-packages/matplotlib/path.py", line 493, in contains_point
return _path.point_in_path(point[0], point[1], radius, self, transform)

TypeError: only length-1 arrays can be converted to Python scalars

Answer 1

我复制并粘贴了您的代码，得到了这个回溯 - 完整的回溯，而不仅仅是最后两行！

Traceback (most recent call last):
  File "stack52695533.py", line 35, in <module>
    in_oval = Oval.contains_point(ax.transData.transform(([px, py])), 0)
  File "/usr/local/lib/python3.6/dist-packages/matplotlib/patches.py", line 154, in contains_point
    radius)
  File "/usr/local/lib/python3.6/dist-packages/matplotlib/path.py", line 493, in contains_point
    return _path.point_in_path(point[0], point[1], radius, self, transform)
TypeError: only size-1 arrays can be converted to Python scalars

看到patches.py 中关于contains_point 的行了吗？只是按名称我猜它需要一分。所以现在我们需要测试它的输入。

添加

print(px, py)
print(ax.transData.transform(([px, py])))

就在问题行之前，产生：

[ 22  12 -66  26  -9 -60  22  41  -6   7] [111  67   4 119  36  71 105 112  91  30]
[[ 10992.    4488. ]
 [-32656.    9662.4]
 [ -4384.  -22123.2]
 [ 10992.   15206.4]
 [ -2896.    2640. ]
 [ 55136.   24816. ]
 [  2064.   44035.2]
 [ 17936.   26294.4]
 [ 52160.   41448. ]
 [ 45216.   11140.8]]

正如我所怀疑的，您正在尝试测试多个点，而不是一次测试一个点。

X 和 Y 是 (100,10);您在第一个维度上进行迭代，但仍将 10 个值传递给 transform。

幸运的是，您提供了一个可运行的示例，否则我仍在等待您对我上一条评论的回复。