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I am trying to visualize multiple 2d trajectories (x, y) in a 3D scatter plot where the z axis is time.

import numpy as np
import pandas as pd
import plotly.express as px

# Sample data: 3 trajectories
t = np.linspace(0, 10, 200)
df = pd.concat([pd.DataFrame({'x': 900 * (1 + np.cos(t + 5 * i)), 'y': 400 * (1 + np.sin(t)), 't': t, 'id': f'id000{i}'}) for i in [0, 1, 2]])
# 3d scatter plot
fig = px.scatter_3d(df, x='x', y='y', z='t', color='id', )
fig.update_traces(marker=dict(size=2))
fig.show()

Original 3D scatter plot

I have a .png file of a map with size: 2000x1000. The (x, y) coordinates of the trajectories correspond to the pixel locations of the map.
I would like to see the image of the map on the "floor" of the 3d scatter plot.

I have tried to add the image with this code:

from scipy import misc

img = misc.imread('images/map_bg.png')
fig2 = px.imshow(img)
fig.add_trace(fig2.data[0])
fig.show()

But the result is having an independent image in the background as a separate plot: Bad result

And I want the image on the "floor" of the scatter plot and moving with the scatter plot, if I rotate/zoom. Here is a mock: enter image description here

Additional note: There can be any number of trajectories and for my application, it is important that each trajectory is automatically plotted with a different color. I am using plotly.express, but I can use other plotly packages, as long as these requirements are met.

Marcos
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1 Answers1

2

I've ran into the same situation where I wanted to use an image as a bottom surface in a 3D scatterplot. With help from two posts here and here, I've been able to create the following 3d scatter plot:

enter image description here

I've used plotly go in my example, so the result is a little bit different than the code from the OP.

import numpy as np
import pandas as pd
from PIL import Image
import plotly.graph_objects as go
from scipy import misc

im = misc.face()
im_x, im_y, im_layers = im.shape
eight_bit_img = Image.fromarray(im).convert('P', palette='WEB', dither=None)
dum_img = Image.fromarray(np.ones((3,3,3), dtype='uint8')).convert('P', palette='WEB')
idx_to_color = np.array(dum_img.getpalette()).reshape((-1, 3))
colorscale=[[i/255.0, "rgb({}, {}, {})".format(*rgb)] for i, rgb in enumerate(idx_to_color)]

# Sample data: 3 trajectories
t = np.linspace(0, 10, 200)
df = pd.concat([pd.DataFrame({'x': 400 * (1 + np.cos(t + 5 * i)), 'y': 400 * (1 + np.sin(t)), 't': t, 'id': f'id000{i}'}) for i in [0, 1, 2]])
# im = im.swapaxes(0, 1)[:, ::-1]
colors=df['t'].to_list()

# # 3d scatter plot
x = np.linspace(0,im_x, im_x)
y = np.linspace(0, im_y, im_y)
z = np.zeros(im.shape[:2])
fig = go.Figure()

fig.add_trace(go.Scatter3d(
    x=df['x'], 
    y=df['y'], 
    z=df['t'],
    marker=dict(
        color=colors,
        size=4,
    )
    ))

fig.add_trace(go.Surface(x=x, y=y, z=z,
    surfacecolor=eight_bit_img, 
    cmin=0, 
    cmax=255,
    colorscale=colorscale,
    showscale=False,
    lighting_diffuse=1,
    lighting_ambient=1,
    lighting_fresnel=1,
    lighting_roughness=1,
    lighting_specular=0.5,

))

fig.update_layout(
    title="My 3D scatter plot",
    width=800,
    height=800,
    scene=dict(xaxis_visible=True,
                yaxis_visible=True, 
                zaxis_visible=True, 
                xaxis_title="X",
                yaxis_title="Y",
                zaxis_title="Z" ,

    ))


fig.show()
Richard
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  • I would add that for the final plot to show the full range of the image, (1024x768) in your code, you can omit setting `x=x, y=y` while creating the `go.Surface`. – Marcos Dec 13 '21 at 16:09
  • hi, What did you use as x and y value in the go.Surface? I would love to remove any lines from my script that are redundant. – Richard Dec 13 '21 at 16:26
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    You do not need to provide `x` and `y` for `go.Surface` to work. Only `z` is required, so you can just remove those arguments, add the trace with `fig.add_trace(go.Surface(z=z,` and leave the rest of the code as it is. – Marcos Dec 13 '21 at 19:11