Python 创建3D绘图(非曲面、散点),其中颜色取决于z值

Python 创建3D绘图(非曲面、散点),其中颜色取决于z值,python,matplotlib,3d,figure,Python,Matplotlib,3d,Figure,我想创建并保存一些连续的情节,这样我就可以用这些情节制作一部mp4电影。我希望绘图的颜色取决于z(第三个轴的值): 我正在使用的代码: import matplotlib.pyplot as plt from matplotlib import cm from matplotlib.ticker import LinearLocator import numpy as np file_dir1 = r"C:\Users\files\final_files\B_6_sec\_read.

我想创建并保存一些连续的情节,这样我就可以用这些情节制作一部mp4电影。我希望绘图的颜色取决于z(第三个轴的值):

我正在使用的代码:

import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib.ticker import LinearLocator
import numpy as np

file_dir1 = r"C:\Users\files\final_files\B_6_sec\_read.csv" 


specs23 = pd.read_csv(file_dir1, sep=',')

choose_file   = specs23          # Choose file betwenn specs21, specs22,...

quant         = 0               #  Choose between 0,1,...,according to the following list

column        = ['$\rho$', '$V_{x}$', '$V_{y}$', '$V_{z}$','$B_{x}$', '$B_{y}$','$B_{z}$','$Temperature$']

choose_column = choose_file[column[quant]] 
                               
resolution    = 1024                                       # Specify resolution of grid 

t_steps       = int(len(specs23)/resolution)               # Specify number of timesteps




fig, ax = plt.subplots(subplot_kw={"projection": "3d"},figsize=(15,10))

# Make data.
X = np.arange(0, resolution, 1)
Y = np.arange(0, int(len(specs23)/resolution),1)
X, Y = np.meshgrid(X, Y)

Z = choose_file[column[quant]].values


new_z = np.zeros((t_steps,resolution))   # Selected quantity as a function of x,t
    

###  Plot figure ###


for i in range(0,int(len(choose_file)/resolution)):
    zs = choose_column[i*resolution:resolution*(i+1)].values
    new_z[i] = zs
        

for i in range(len(X)):
    ax.plot(X[i], Y[i], new_z[i]) #%// color binded to "z" values


ax.zaxis.set_major_locator(LinearLocator(10))
# A StrMethodFormatter is used automatically
ax.zaxis.set_major_formatter('{x:.02f}')


plt.show()
我得到的结果如下:

我希望它看起来像这样:

我已使用LineCollection模块创建了第二个绘图。问题是它一次打印所有行,不允许我单独保存每一行来创建电影

您可以在这里找到我用来创建图的数据框:


海报想要两样东西

  • 颜色取决于z值的线
  • 随时间变化的线条动画
  • 为了实现(1)需要将每条线切割成单独的线段,并为每个线段指定一种颜色;为了获得颜色条,我们需要创建一个ScalarMapable对象,该对象知道颜色的外部限制

    要实现2,需要(a)保存动画的每个帧并在存储所有帧后将其合并,或者(b)利用matplotlib中的动画模块。我在下面的示例中使用了后者,并实现了以下目标:


    @我已经试着按照你以前的建议去做了。但是我没能做到!你能举个例子吗?你的意思是什么?为每一行设置颜色。“因为我的例子中的Z值是2D数组,所以我不能这样做。”Jokerp更新了帖子。希望有帮助!我很抱歉,但这没用。我想创建并保存一些连续的情节,这样我就可以用这些情节制作一部mp4电影。使用Line3DCollection无法单独绘制每条线,对吗?
    from mpl_toolkits.mplot3d import axes3d
    import matplotlib.pyplot as plt, numpy as np
    from mpl_toolkits.mplot3d.art3d import Line3DCollection
    
    fig, ax = plt.subplots(subplot_kw = dict(projection = '3d'))
    
    # generate data
    x = np.linspace(-5, 5, 500)
    y = np.linspace(-5, 5, 500)
    z = np.exp(-(x - 2)**2)
    
    # uggly
    segs = np.array([[(x1,y2), (x2, y2), (z1, z2)] for x1, x2, y1, y2, z1, z2 in zip(x[:-1], x[1:], y[:-1], y[1:], z[:-1], z[1:])])
    segs = np.moveaxis(segs, 1, 2)
    
    # setup segments
    
    # get bounds
    bounds_min = segs.reshape(-1, 3).min(0)
    bounds_max = segs.reshape(-1, 3).max(0)
    
    # setup colorbar stuff
    # get bounds of colors
    norm = plt.cm.colors.Normalize(bounds_min[2], bounds_max[2])
    cmap = plt.cm.plasma
    # setup scalar mappable for colorbar
    sm   = plt.cm.ScalarMappable(norm, plt.cm.plasma)
    
    # get average of segment
    avg = segs.mean(1)[..., -1]
    # get colors
    colors = cmap(norm(avg))
    # generate colors
    lc = Line3DCollection(segs, norm = norm, cmap = cmap, colors = colors)
    ax.add_collection(lc)
    
    def update(idx):
        segs[..., -1] = np.roll(segs[..., -1], idx)
        lc.set_offsets(segs)
        return lc
    
    ax.set_xlim(bounds_min[0], bounds_max[0])
    ax.set_ylim(bounds_min[1], bounds_max[1])
    ax.set_zlim(bounds_min[2], bounds_max[2])
    fig.colorbar(sm)
    
    from matplotlib import animation
    frames = np.linspace(0, 30, 10, 0).astype(int)
    ani = animation.FuncAnimation(fig, update, frames = frames)
    ani.save("./test_roll.gif", savefig_kwargs = dict(transparent = False))
    
    fig.show()