[英]ValueError: x and y must have same first dimension, but have shapes (50,) and (1, 50)/ Multiprocessing
I am new to multiprocessing and plotting so I wished to make a code that could multi-process a range of heights to get the optimum launch angle for each height through an equation, then plot the results.我是多处理和绘图的新手,所以我希望编写一个可以多处理一系列高度的代码,以通过方程获得每个高度的最佳发射角度,然后是 plot 结果。
My main issue is when attempting to plot the results I run into an error.我的主要问题是在尝试 plot 结果时遇到错误。 My secondary issue is by investigating my code for a while, now I'm beginning to think the multi-process is redundant?
我的次要问题是通过调查我的代码一段时间,现在我开始认为多进程是多余的? I still desire to use a multi-process.
我仍然希望使用多进程。 So any help in regards to that is also appreciated.
因此,对此的任何帮助也将不胜感激。
The equation seems to work fine when I don't wish to plot the results.当我不希望 plot 结果时,该等式似乎工作正常。 But when I attempt to plot them I get "ValueError: x and y must have same first dimension, but have shapes (50,) and (1, 50)" which I don't exactly understand.
但是当我尝试 plot 时,我得到“ValueError:x 和 y 必须具有相同的第一维,但具有形状 (50,) 和 (1, 50)”,我并不完全理解。 I thought they were both just ranges to 50?
我以为他们都只是50的范围?
I've been messing around with it for a while attempting to get it to work.我已经搞砸了一段时间试图让它工作。 I believe its in the "list_h = np.array(range(1))" line since it just doesn't seem right.
我相信它在“list_h = np.array(range(1))”行中,因为它看起来不正确。 But that range seems to just repeat the results if I increase it.
但如果我增加它,这个范围似乎只是重复结果。 leading me to think I've structured this multi-process poorly.
导致我认为我对这个多进程的结构很差。
My code is as follows我的代码如下
import numpy as np
from multiprocessing import Pool
import matplotlib.pyplot as plt
def f(x):
speed = 5
ran0 = (speed*speed)/9.8
array_hght = np.array(range(50))
return ((np.arccos(array_hght/(array_hght+ran0)))/2)*(180/np.pi)
if __name__ == '__main__':
with Pool(5) as p:
list_h = np.array(range(1))
list_angles = p.map(f, list_h)
print(list_angles)
array_h = np.array(range(50))
plt.plot(array_h, list_angles)
plt.show()
Any help is greatly appreciated:).任何帮助是极大的赞赏:)。
You're almost there!!您快到了!! The
pool.map()
method returns the result in a list-form by applying f
over the given input which is list_h
in this case. pool.map()
方法通过将f
应用于给定输入(在本例中为list_h
)以列表形式返回结果。 Since list_h
has only one item, then the result will be a list of just one value.由于
list_h
只有一项,因此结果将是一个只有一个值的列表。
So, all you need to do is to get the first element from list_angles
like so:因此,您需要做的就是从
list_angles
中获取第一个元素,如下所示:
if __name__ == '__main__':
with Pool(5) as p:
list_h = np.array(range(1))
list_angles = p.map(f, list_h)[0] #<--- HERE
array_h = np.array(range(50))
print(array_h.shape)
plt.plot(array_h, list_angles)
plt.show()
And running the previous code will results in the following graph:运行前面的代码会得到下图:
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