Matplotlib中颤抖的阴影箭头太可笑了

Question

我正在创建一个可以模拟电场线的python脚本，但颤抖情节出来的箭头太大了。我试过改变单位和比例尺，但matplotlib上的文档没有意义，我也没有任何意义......这似乎只是一个主要问题，当系统中只有一个电荷时，但箭头仍然略微超大任何数量的费用。在所有情况下，箭头都会变得过大，但只有一个粒子才是最明显的。

import matplotlib.pyplot as plt 
import numpy as np 
import sympy as sym 
import astropy as astro 

k = 9 * 10 ** 9 


def get_inputs(): 
    inputs_loop = False 
    while inputs_loop is False: 
     """" 
     get inputs 
     """ 
     inputs_loop = True 
     particles_loop = False 
     while particles_loop is False: 
      try: 
       particles_loop = True 
       """ 
       get n particles with n charges. 
       """ 
       num_particles = int(raw_input('How many particles are in the system? ')) 
       parts = [] 
       for i in range(num_particles): 
        parts.append([float(raw_input("What is the charge of particle %s in Coulombs? " % (str(i + 1)))), 
            [float(raw_input("What is the x position of particle %s? " % (str(i + 1)))), 
            float(raw_input('What is the y position of particle %s? ' % (str(i + 1))))]]) 
      except ValueError: 
       print 'Could not convert input to proper data type. Please try again.' 
       particles_loop = False 
    return parts 
def vec_addition(vectors): 
    x_sum = 0 
    y_sum = 0 
    for b in range(len(vectors)): 
     x_sum += vectors[b][0] 
     y_sum += vectors[b][1] 
    return [x_sum,y_sum] 

def electric_field(particle, point): 
    if particle[0] > 0: 
     """ 
     Electric field exitation is outwards 

     If the x position of the particle is > the point, then a different calculation must be made than in not. 
     """ 
     field_vector_x = k * (
     particle[0]/np.sqrt((particle[1][0] - point[0]) ** 2 + (particle[1][1] - point[1]) ** 2) ** 2) * \ 
         (np.cos(np.arctan2((point[1] - particle[1][1]), (point[0] - particle[1][0])))) 
     field_vector_y = k * (
     particle[0]/np.sqrt((particle[1][0] - point[0]) ** 2 + (particle[1][1] - point[1]) ** 2) ** 2) * \ 
         (np.sin(np.arctan2((point[1] - particle[1][1]), (point[0] - particle[1][0])))) 
     """ 
     Defining the direction of the components 
     """ 
     if point[1] < particle[1][1] and field_vector_y > 0: 
      print field_vector_y 
      field_vector_y *= -1 
     elif point[1] > particle[1][1] and field_vector_y < 0: 
      print field_vector_y 
      field_vector_y *= -1 
     else: 
      pass 
     if point[0] < particle[1][0] and field_vector_x > 0: 
      print field_vector_x 
      field_vector_x *= -1 
     elif point[0] > particle[1][0] and field_vector_x < 0: 
      print field_vector_x 
      field_vector_x *= -1 
     else: 
      pass 
     """ 
     If the charge is negative 
     """ 
    elif particle[0] < 0: 
     field_vector_x = k * (
      particle[0]/np.sqrt((particle[1][0] - point[0]) ** 2 + (particle[1][1] - point[1]) ** 2) ** 2) * (
          np.cos(np.arctan2((point[1] - particle[1][1]), (point[0] - particle[1][0])))) 
     field_vector_y = k * (
      particle[0]/np.sqrt((particle[1][0] - point[0]) ** 2 + (particle[1][1] - point[1]) ** 2) ** 2) * (
          np.sin(np.arctan2((point[1] - particle[1][1]), (point[0] - particle[1][0])))) 
     """ 
     Defining the direction of the components 
     """ 
     if point[1] > particle[1][1] and field_vector_y > 0: 
      print field_vector_y 
      field_vector_y *= -1 
     elif point[1] < particle[1][1] and field_vector_y < 0: 
      print field_vector_y 
      field_vector_y *= -1 
     else: 
      pass 
     if point[0] > particle[1][0] and field_vector_x > 0: 
      print field_vector_x 
      field_vector_x *= -1 
     elif point[0] < particle[1][0] and field_vector_x < 0: 
      print field_vector_x 
      field_vector_x *= -1 
     else: 
      pass 
    return [field_vector_x, field_vector_y] 

def main(particles): 
    """ 
    Graphs the electrical field lines. 
    :param particles: 
    :return: 
    """ 
    """ 
    plot particle positions 
    """ 
    particle_x = 0 
    particle_y = 0 
    for i in range(len(particles)): 
     if particles[i][0]<0: 
      particle_x = particles[i][1][0] 
      particle_y = particles[i][1][1] 
      plt.plot(particle_x,particle_y,'r+',linewidth=1.5) 
     else: 
      particle_x = particles[i][1][0] 
      particle_y = particles[i][1][1] 
      plt.plot(particle_x,particle_y,'r_',linewidth=1.5) 
    """ 
    Plotting out the quiver plot. 
    """ 
    parts_x = [particles[i][1][0] for i in range(len(particles))] 
    graph_x_min = min(parts_x) 
    graph_x_max = max(parts_x) 
    x,y = np.meshgrid(np.arange(graph_x_min-(graph_x_max-graph_x_min),graph_x_max+(graph_x_max-graph_x_min)), 
         np.arange(graph_x_min-(graph_x_max-graph_x_min),graph_x_max+(graph_x_max-graph_x_min))) 
    if len(particles)<2: 
     for x_pos in range(int(particles[0][1][0]-10),int(particles[0][1][0]+10)): 
      for y_pos in range(int(particles[0][1][0]-10),int(particles[0][1][0]+10)): 
       vecs = [] 
       for particle_n in particles: 
        vecs.append(electric_field(particle_n, [x_pos, y_pos])) 
       final_vector = vec_addition(vecs) 
       distance = np.sqrt((final_vector[0] - x_pos) ** 2 + (final_vector[1] - y_pos) ** 2) 
       plt.quiver(x_pos, y_pos, final_vector[0], final_vector[1], distance, angles='xy', scale_units='xy', 
          scale=1, width=0.05) 
     plt.axis([particles[0][1][0]-10,particles[0][1][0]+10, 
        particles[0][1][0] - 10, particles[0][1][0] + 10]) 
    else: 
     for x_pos in range(int(graph_x_min-(graph_x_max-graph_x_min)),int(graph_x_max+(graph_x_max-graph_x_min))): 
      for y_pos in range(int(graph_x_min-(graph_x_max-graph_x_min)),int(graph_x_max+(graph_x_max-graph_x_min))): 
       vecs = [] 
       for particle_n in particles: 
        vecs.append(electric_field(particle_n,[x_pos,y_pos])) 
       final_vector = vec_addition(vecs) 
       distance = np.sqrt((final_vector[0]-x_pos)**2+(final_vector[1]-y_pos)**2) 
       plt.quiver(x_pos,y_pos,final_vector[0],final_vector[1],distance,angles='xy',units='xy') 
     plt.axis([graph_x_min-(graph_x_max-graph_x_min),graph_x_max+(graph_x_max-graph_x_min),graph_x_min-(graph_x_max-graph_x_min),graph_x_max+(graph_x_max-graph_x_min)]) 
    plt.grid() 
    plt.show() 



g = get_inputs() 
main(g)} 

Answer 1

你可以设置刻度，使得其大致对应于u和v载体。

plt.quiver(x_pos, y_pos, final_vector[0], final_vector[1], scale=1e9, units="xy") 

这将导致这样的事情：

如果我正确interprete它，你想画领域向量的点电荷。回顾其他人如何做到这一点，可以找到例如由Christian Hill提供的this blog entry。他使用streamplot而不是quiver，但我们可能需要计算字段并替换图的代码。

在任何情况下，我们都不想要也不需要100个不同的颤抖图，就像问题的代码一样，但是只有一个颤动图绘制整个场。如果我们想要场矢量的长度表示场强度，我们当然会遇到问题，因为幅度随粒子的距离乘以3的幂而变化。解决方案可能是在绘图之前以对数方式缩放场，使得箭头长度仍然以某种方式可见，即使在距粒子一定距离处也是如此。然后可以使用quiver绘图的比例参数来调整箭头的长度，以便它们以某种方式适合其他绘图参数。

""" Original code by Christian Hill 
    http://scipython.com/blog/visualizing-a-vector-field-with-matplotlib/ 
    Changes made to display the field as a quiver plot instead of streamlines 
""" 
import numpy as np 
import matplotlib.pyplot as plt 
from matplotlib.patches import Circle 

def E(q, r0, x, y): 
    """Return the electric field vector E=(Ex,Ey) due to charge q at r0.""" 
    den = ((x-r0[0])**2 + (y-r0[1])**2)**1.5 
    return q * (x - r0[0])/den, q * (y - r0[1])/den 

# Grid of x, y points 
nx, ny = 32, 32 
x = np.linspace(-2, 2, nx) 
y = np.linspace(-2, 2, ny) 
X, Y = np.meshgrid(x, y) 


charges = [[5.,[-1,0]],[-5.,[+1,0]]] 


# Electric field vector, E=(Ex, Ey), as separate components 
Ex, Ey = np.zeros((ny, nx)), np.zeros((ny, nx)) 
for charge in charges: 
    ex, ey = E(*charge, x=X, y=Y) 
    Ex += ex 
    Ey += ey 

fig = plt.figure() 
ax = fig.add_subplot(111) 

f = lambda x:np.sign(x)*np.log10(1+np.abs(x)) 

ax.quiver(x, y, f(Ex), f(Ey), scale=33) 

# Add filled circles for the charges themselves 
charge_colors = {True: 'red', False: 'blue'} 
for q, pos in charges: 
    ax.add_artist(Circle(pos, 0.05, color=charge_colors[q>0])) 

ax.set_xlabel('$x$') 
ax.set_ylabel('$y$') 
ax.set_xlim(-2,2) 
ax.set_ylim(-2,2) 
ax.set_aspect('equal') 
plt.show() 

（请注意这里的领域是不以任何方式进行规范，这应该无论可视化的。）

不同的选项是看如this code这也从点收费绘制场线。