matplotlib动画：更新轴tick ticks

发布于 2025-02-03 03:10:38 字数 708 浏览 1 评论 0原文

我正在创建一个图像的动画，其轴值随时间变化。

all_data是一个矩阵，其中包含一个斧头时间框架中的一个矩阵，有3个Quatities是经度的纬度和像素值因此，

lon = All_data[0,0] #-> lon is a 2D nxm matrix
lat = All_data[0,1] #-> lat is a 2D nxm matrix
I = All_data[0,2]    #-> I   is a 2D nxm matrix
im = axis.pcolormesh(lon,lat,I)
def animate(i):
    im.set_array(All_data[i,2])
    #code to add here to update axis too
    return im

ani = FuncAnimation.....etc

问题在于，此代码不会更新我的X和Y（经度和态度）轴。有什么方法可以使用PCOLOR或PCOLORMESH甚至IMShow更新图像的轴值？结果显示在图像中显示，因为您看到轴的值没有更改

原文

I'm creating an animation of an image with axis values varying over time.

All_data is a matrix that contains in one axe time frames inside there are 3 quatities which are longitude latitude and pixel values
so

lon = All_data[0,0] #-> lon is a 2D nxm matrix
lat = All_data[0,1] #-> lat is a 2D nxm matrix
I = All_data[0,2]    #-> I   is a 2D nxm matrix
im = axis.pcolormesh(lon,lat,I)
def animate(i):
    im.set_array(All_data[i,2])
    #code to add here to update axis too
    return im

ani = FuncAnimation.....etc

The problem is that this code will not update my X and Y (longitude and attitude) axis.
is there any way to update the axis values with images using pcolor or pcolormesh or even imshow?
The results are shown in the image as you see the values of the axis are not changing

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大海や 2025-02-10 03:10:38

我尚未使用您的代码进行测试（问题可以使用 mwe ），但是您可能能够做类似的事情：

# Form relative steps in coordinates between frames for each frame
dlon = np.r_[0, All_data[1:, 0] - All_data[:-1, 0]]
dlat = np.r_[0, All_data[1:, 1] - All_data[:-1, 1]]

def animate(i):
    im.set_array(All_data[i, 2])
    new_coords = im.properties()['coordinates']  # N x M x 2 array
    new_coords[..., 0] += dlon[i]
    new_coords[..., 1] += dlat[i]
    im._coordinates = new_coords  # is there a public interface?

    return im

I haven't tested this with your code (the question could use an MWE), but you might be able to do something like:

# Form relative steps in coordinates between frames for each frame
dlon = np.r_[0, All_data[1:, 0] - All_data[:-1, 0]]
dlat = np.r_[0, All_data[1:, 1] - All_data[:-1, 1]]

def animate(i):
    im.set_array(All_data[i, 2])
    new_coords = im.properties()['coordinates']  # N x M x 2 array
    new_coords[..., 0] += dlon[i]
    new_coords[..., 1] += dlat[i]
    im._coordinates = new_coords  # is there a public interface?

    return im

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