Python：我不断收到广播错误，但我不知道如何解决它

我正在尝试调整此链接中接受的答案代码以达到我的目的：使用 plt 在热图上绘制渐变箭头

我正在从事一个项目，该项目要求我以 .csv 文件的形式拍摄热图像，然后从 .csv 文件中获取数据以制作箭头（通过 quiverplot streamplot 等）来显示热流的方向从图像上的最热点（最高像素值）开始。我认为这可以使用图像的渐变来实现，但我不确定如何实现。

这是我的代码：

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

directory = os.chdir(r'user_directory') #Set folder to look in
file = 'data.csv'
data = np.genfromtxt(file, delimiter = ',')

horizontal_min, horizontal_max, horizontal_stepsize = 0, 100, 0.3
vertical_min, vertical_max, vertical_stepsize = 0, 100, 0.5

horizontal_dist = horizontal_max-horizontal_min
vertical_dist = vertical_max-vertical_min

horizontal_stepsize = horizontal_dist / float(math.ceil(horizontal_dist/float(horizontal_stepsize)))
vertical_stepsize = vertical_dist / float(math.ceil(vertical_dist/float(vertical_stepsize)))

xv, yv = np.meshgrid(np.arange(horizontal_min, horizontal_max, horizontal_stepsize),
                 np.arange(vertical_min, vertical_max, vertical_stepsize))
xv+=horizontal_stepsize/2.0
yv+=vertical_stepsize/2.0

result_matrix = np.asmatrix(data)
yd, xd = np.gradient(result_matrix)

def func_to_vectorize(x, y, dx, dy, scaling=0.01):
    plt.arrow(x, y, dx*scaling, dy*scaling), fc="k", ec="k", head_width=0.06, 
head_length=0.1)

vectorized_arrow_drawing = np.vectorize(func_to_vectorize)

plt.imshow(np.flip(result_matrix,0), extent=[horizontal_min, horizontal_max, vertical_min, 
vertical_max])
vectorized_arrow_drawing(xv, yv, xd, yd, 0.1)
plt.colorbar()
plt.show()

这是我得到的错误：

ValueError: operands could not be broadcast together with shapes (200,335) (200,335) (100,100) (100,100) ()

ValueError                                Traceback (most recent call last)
<ipython-input-95-25a8b7e2dff8> in <module>
     46 
     47 plt.imshow(np.flip(result_matrix,0), extent=[horizontal_min, 



horizontal_max, vertical_min, vertical_max])
---> 48 vectorized_arrow_drawing(xv, yv, xd, yd, 0.1)
     49 plt.colorbar()
     50 plt.show()

~\Anaconda3\lib\site-packages\numpy\lib\function_base.py in __call__(self, 
*args, **kwargs)
   1970             vargs.extend([kwargs[_n] for _n in names])
   1971 
-> 1972         return self._vectorize_call(func=func, args=vargs)
   1973 
   1974     def _get_ufunc_and_otypes(self, func, args):

~\Anaconda3\lib\site-packages\numpy\lib\function_base.py in 
_vectorize_call(self, func, args)
   2046                       for a in args]
   2047 
-> 2048             outputs = ufunc(*inputs)
   2049 
   2050             if ufunc.nout == 1:

ValueError: operands could not be broadcast together with shapes (100,168) 
(100,168) (100,100) (100,100) ()