Hello, there is the possibility to color the y-values according to their value in matplotlib like
import matplotlib.pyplot as plt
import numpy as np
from matplotlib import cm
x = np.linspace(0, 2*np.pi, 1000)
y = np.sin(2*x)
plt.scatter(x,y, c=cm.hot(np.abs(y)), edgecolor='none')
plt.show()
What is the corresponding way to do it in plotly?
import plotly.graph_objects as go
import numpy as np
N = 1000
t = np.linspace(0,10,100)
y = np.sin(t)
fig = go.Figure(
data = [go.Scatter(x=t,y=y,mode = "lines")]
)
fig.show()
@ud.schn
You can plot lines colored according to y-values, but not with scatter mode="lines", but "markers", and with a sufficiently high density of points. (the density is also influenced by layout width and height)
import plotly.graph_objects as go
import numpy as np
N = 700
t = np.linspace(0,2*np.pi,N) #N sufficiently big to ensure high marker density
y = np.sin(t)
fig = go.Figure(go.Scatter(x=t,y=y,mode = "markers", marker=dict(color=y, size=3,
colorscale="matter_r", colorbar_thickness=25)))
fig.update_layout(width=600, height=400)
fig.show()
I’ve tried your script and indeed it works… then I try to apply it to a script of mine that plots a 3D surface by Delaunay triangulation (since my data are irregularly scattered): when trying to display projection curves (of the 3D surface) onto the vertical planes (that is, XZ and YZ) coloring them according to the z value (of heatmap-type, that is cmap=plt.cm.jet), I get curves whose color is not proportional to the z value. I’ve tried
