Plotly adding two sliders in python

Question

I have read plotly slider instruction:https://plotly.com/python/sliders/, but still can't find a way to create two sliders in one graph. I'm new to plotly so any kind of advice will be helpful.

Answer 1

Apparently it's not possible (see plotly community post) - but since this post is from '18, there might be a solution by now (that I'm not aware of). If you are working in a Jupyter notebook, you could use FigureWidget (as suggested in the post) as follows:

import plotly.graph_objects as go 
import numpy as np

def linear_function(a,b,x):
    return a*x+b

a0 = 0.1
b0 = 0.1
x = np.arange(-10,10,0.1)

data = [go.Scatter(x=x,y=linear_function(a=a0,b=b0,x=x))]

fig = go.FigureWidget(data=data)
fig.update_yaxes(autorange=False,range=(-3,3))

@interact(a=(0, 1, 0.1), b=(0, 1, 0.1))
def update(a=a0, b=b0):
    with fig.batch_update():
        fig.data[0].y = linear_function(a=a,b=b,x=x)
    return fig

However, there is sometimes a significant delay in rendering when using interact. Therefore, I would like to point out that in many cases it may be the better solution to fix one variable and only set the other variable interactively:

# Fixing a
a = 0.1

fig = go.Figure()
fig.update_layout(title = f"Linear function a*x+b with a fixed at {a} and b adjustable")
fig.update_yaxes(autorange=False,range=(-3,3))
parameters = np.arange(0, 5, 0.1)

for b in parameters:
    fig.add_trace(
        go.Scatter(
            visible=False,
            x=x,
            y=linear_function(a=a,b=b,x=x),
        ))

# Make 0th trace visible
fig.data[0].visible = True

# Create and add slider
steps = []
for i in range(len(fig.data)):
    step = dict(
        method="update",
        label=f"{parameters[i]: .2f}",
        args=[{"visible": [False] * len(fig.data)}],  
    )
    step["args"][0]["visible"][i] = True  
    steps.append(step)

sliders = [dict(
    active=0,
    pad={"t": 50},
    steps=steps
)]

fig.update_layout(
    sliders=sliders
)

fig.show()

I hope this helped!