如何使用matplotlib在python中绘制向量

How to plot vectors in python using matplotlib

提问by Shravan Kumar

I am taking a course on linear algebra and I want to visualize the vectors in action, such as vector addition, normal vector, so on.

我正在修一门关于线性代数的课程，我想可视化正在运行的向量，例如向量加法、法向量等。

For instance:

例如：

V = np.array([[1,1],[-2,2],[4,-7]])

In this case I want to plot 3 vectors V1 = (1,1), M2 = (-2,2), M3 = (4,-7).

在这种情况下，我想绘制 3 个向量V1 = (1,1), M2 = (-2,2), M3 = (4,-7)。

Then I should be able to add V1,V2 to plot a new vector V12(all together in one figure).

然后我应该能够添加 V1,V2 来绘制一个新的向量 V12（一起在一个图中）。

when I use the following code, the plot is not as intended

当我使用以下代码时，情节不符合预期

import numpy as np
import matplotlib.pyplot as plt
M = np.array([[1,1],[-2,2],[4,-7]])

print("vector:1")
print(M[0,:])
# print("vector:2")
# print(M[1,:])
rows,cols = M.T.shape
print(cols)

for i,l in enumerate(range(0,cols)):
    print("Iteration: {}-{}".format(i,l))
    print("vector:{}".format(i))
    print(M[i,:])
    v1 = [0,0],[M[i,0],M[i,1]]
    # v1 = [M[i,0]],[M[i,1]]
    print(v1)
    plt.figure(i)
    plt.plot(v1)
    plt.show()

采纳答案by Shravan Kumar

Thanks to everyone, each of your posts helped me a lot. rbiermancode was pretty straight for my question, I have modified a bit and created a function to plot vectors from given arrays. I'd love to see any suggestions to improve it further.

谢谢大家，你的每一篇文章都对我有很大帮助。 rbierman代码对我的问题非常直接，我做了一些修改并创建了一个函数来绘制给定数组中的向量。我很乐意看到任何建议以进一步改进它。

import numpy as np
import matplotlib.pyplot as plt
def plotv(M):
    rows,cols = M.T.shape
    print(rows,cols)

    #Get absolute maxes for axis ranges to center origin
    #This is optional
    maxes = 1.1*np.amax(abs(M), axis = 0)
    colors = ['b','r','k']
    fig = plt.figure()
    fig.suptitle('Vectors', fontsize=10, fontweight='bold')

    ax = fig.add_subplot(111)
    fig.subplots_adjust(top=0.85)
    ax.set_title('Vector operations')

    ax.set_xlabel('x')
    ax.set_ylabel('y')

    for i,l in enumerate(range(0,cols)):
        # print(i)
        plt.axes().arrow(0,0,M[i,0],M[i,1],head_width=0.2,head_length=0.1,zorder=3)

        ax.text(M[i,0],M[i,1], str(M[i]), style='italic',
            bbox={'facecolor':'red', 'alpha':0.5, 'pad':0.5})

    plt.plot(0,0,'ok') #<-- plot a black point at the origin
    # plt.axis('equal')  #<-- set the axes to the same scale
    plt.xlim([-maxes[0],maxes[0]]) #<-- set the x axis limits
    plt.ylim([-maxes[1],maxes[1]]) #<-- set the y axis limits

    plt.grid(b=True, which='major') #<-- plot grid lines
    plt.show()

r = np.random.randint(4,size=[2,2])
print(r[0,:])
print(r[1,:])
r12 = np.add(r[0,:],r[1,:])
print(r12)
plotv(np.vstack((r,r12)))

Vector addition performed on random vectors

对随机向量执行向量加法

回答by Aziz Alto

How about something like

怎么样的东西

import numpy as np
import matplotlib.pyplot as plt

V = np.array([[1,1],[-2,2],[4,-7]])
origin = [0], [0] # origin point

plt.quiver(*origin, V[:,0], V[:,1], color=['r','b','g'], scale=21)
plt.show()

Then to add up any two vectors and plot them to the same figure, do so before you call plt.show(). Something like:

然后要将任意两个向量相加并将它们绘制为同一个图形，请在调用plt.show(). 就像是：

plt.quiver(*origin, V[:,0], V[:,1], color=['r','b','g'], scale=21)
v12 = V[0] + V[1] # adding up the 1st (red) and 2nd (blue) vectors
plt.quiver(*origin, v12[0], v12[1])
plt.show()

NOTE: in Python2 use origin[0], origin[1]instead of *origin

注意：在 Python2 中使用origin[0], origin[1]代替*origin

回答by fuglede

This may also be achieved using matplotlib.pyplot.quiver, as noted in the linked answer;

这也可以使用 来实现matplotlib.pyplot.quiver，如链接的答案中所述；

plt.quiver([0, 0, 0], [0, 0, 0], [1, -2, 4], [1, 2, -7], angles='xy', scale_units='xy', scale=1)
plt.xlim(-10, 10)
plt.ylim(-10, 10)
plt.show()

回答by juanpa.arrivillaga

What did you expect the following to do?

您希望以下人员做什么？

v1 = [0,0],[M[i,0],M[i,1]]
v1 = [M[i,0]],[M[i,1]]

This is making two different tuples, and you overwrite what you did the first time... Anyway, matplotlibdoes not understand what a "vector" is in the sense you are using. You have to be explicit, and plot "arrows":

这是制作两个不同的元组，你覆盖了你第一次做的事情......无论如何，matplotlib不明白你正在使用的意义上的“向量”是什么。你必须明确，并绘制“箭头”：

In [5]: ax = plt.axes()

In [6]: ax.arrow(0, 0, *v1, head_width=0.05, head_length=0.1)
Out[6]: <matplotlib.patches.FancyArrow at 0x114fc8358>

In [7]: ax.arrow(0, 0, *v2, head_width=0.05, head_length=0.1)
Out[7]: <matplotlib.patches.FancyArrow at 0x115bb1470>

In [8]: plt.ylim(-5,5)
Out[8]: (-5, 5)

In [9]: plt.xlim(-5,5)
Out[9]: (-5, 5)

In [10]: plt.show()

Result:

结果：

回答by mitoRibo

Your main problem is you create new figures in your loop, so each vector gets drawn on a different figure. Here's what I came up with, let me know if it's still not what you expect:

您的主要问题是您在循环中创建新图形，因此每个向量都绘制在不同的图形上。这是我想出的，如果它仍然不是您所期望的，请告诉我：

CODE:

代码：

import numpy as np
import matplotlib.pyplot as plt
M = np.array([[1,1],[-2,2],[4,-7]])

rows,cols = M.T.shape

#Get absolute maxes for axis ranges to center origin
#This is optional
maxes = 1.1*np.amax(abs(M), axis = 0)

for i,l in enumerate(range(0,cols)):
    xs = [0,M[i,0]]
    ys = [0,M[i,1]]
    plt.plot(xs,ys)

plt.plot(0,0,'ok') #<-- plot a black point at the origin
plt.axis('equal')  #<-- set the axes to the same scale
plt.xlim([-maxes[0],maxes[0]]) #<-- set the x axis limits
plt.ylim([-maxes[1],maxes[1]]) #<-- set the y axis limits
plt.legend(['V'+str(i+1) for i in range(cols)]) #<-- give a legend
plt.grid(b=True, which='major') #<-- plot grid lines
plt.show()

OUTPUT:

输出：

EDIT CODE:

编辑代码：

import numpy as np
import matplotlib.pyplot as plt
M = np.array([[1,1],[-2,2],[4,-7]])

rows,cols = M.T.shape

#Get absolute maxes for axis ranges to center origin
#This is optional
maxes = 1.1*np.amax(abs(M), axis = 0)
colors = ['b','r','k']


for i,l in enumerate(range(0,cols)):
    plt.axes().arrow(0,0,M[i,0],M[i,1],head_width=0.05,head_length=0.1,color = colors[i])

plt.plot(0,0,'ok') #<-- plot a black point at the origin
plt.axis('equal')  #<-- set the axes to the same scale
plt.xlim([-maxes[0],maxes[0]]) #<-- set the x axis limits
plt.ylim([-maxes[1],maxes[1]]) #<-- set the y axis limits
plt.grid(b=True, which='major') #<-- plot grid lines
plt.show()

EDIT OUTPUT:

编辑输出：

回答by muon

All nice solutions, borrowing and improvising for special case -> If you want to add a label near the arrowhead:

所有不错的解决方案，为特殊情况借用和即兴创作 -> 如果您想在箭头附近添加标签：

    arr = [2,3]
    txt = “Vector X”
    ax.annotate(txt, arr)
    ax.arrow(0, 0, *arr, head_width=0.05, head_length=0.1)