How to control different traces with more sliders

📊 Plotly Python
1

Hello,
I’ve created two sliders and I’m trying to control two traces with them, but each of them affect all traces (so i can’t control traces separately). Is there a way to do it?
Here a sample of my code:

import numpy as np
import sys

PATH = '/Users/jacopo/Desktop/Spectra_Data/Atomic_Lines_NIST/Argon_I.csv'

data=np.loadtxt(PATH)

xcoords = data[:,0]
ycoords = data[:,1]

xmin = np.amin(xcoords)
xmax = np.amax(xcoords)
ymin = np.amin(ycoords)
ymax = np.amax(ycoords)

name=PATH.split("/")[6].replace(".csv","")


file=sys.argv[1]

wavelegth_array=np.loadtxt(file, skiprows=1, dtype=np.float32)
lambda_array = np.loadtxt(file, skiprows=1, dtype=np.float32)[:,1:]

print ("Rows:",len(lambda_array))
print ("Columns:", len(lambda_array[0]))

x_array = wavelegth_array[:,0]
y_array = lambda_array[:,]



#--------------Interactive plot with plotly: Sliders

import plotly.graph_objects as go
  
def SumGauss(x, mu, sigma, intensity = 1):

    sumgaussian = sum([intensity[i] * np.exp(-0.5*((x-mu[i])/sigma)**2) for i in range (len(mu))])
    
    return sumgaussian

np.seterr(divide='ignore', invalid='ignore')

# Spectrum parameters

sigma_a1 = 0.04
x_range =  np.linspace(xmin, xmax, 60000)


gauss_a = SumGauss(x_range, xcoords, sigma_a1, ycoords)


# Create figure
fig = go.Figure()


#Add trace for simulated spectra
new_array=np.arange(0.01, 1, 0.01)

for sigma in np.arange(0.01, 1, 0.01):
    fig.add_trace(go.Scatter( visible=False,
            line=dict(color="green", width=2), 
            name="σ = " + str(sigma),
            x=x_range,
            y=SumGauss(x_range, xcoords, sigma, ycoords)
            ))

# Add trace for experimental spectra
for step in range(len(lambda_array[0])):
    fig.add_trace(
        go.Scatter(
            visible=False,
            line=dict(color="#00CED1", width=2),
            name="time = " + str(step)+ " ms",
            x=x_array,
            y=y_array[:,int(step)]
                     ))

 
# Make 100th trace visible
fig.data[100].visible = True


#Set y range manually
fig.update_yaxes(range=[np.amin(y_array),np.amax(y_array)+50])# shift on max y value to display spectrum in a better way


#Add atomic lines shape
for k in data:
    fig.add_shape(type="line", xref='x', yref='y',
    x0=k[0], y0=0, x1=k[0], y1=k[1],
    line=dict(color="red",width=1))
    

# Create and add slider
steps = []
for i in range(len(lambda_array[0])):
    step = dict(#label="time = " + str(i)+ " ms",
        method="update",
        args=[{"visible": [False] * len(lambda_array[0])}]
              #{"title": "Spectra at time: " + str(i) + " ms"}],  #layout attribute
    )
    step["args"][0]["visible"][i] = True  #Toggle i'th trace to "visible"
    #print(step)
    steps.append(step)

newsteps = []
for j in range(len(new_array)):
    stip = dict(#label="σ = " + str(j),
        method="update",
        args=[{"visible": [False] * len(new_array)}]
              #{"title": "Spectra at time: " + str(i) + " ms"}],  #layout attribute
    )
    stip["args"][0]["visible"][j] = True  #Toggle i'th trace to "visible"
    #print(stips)
    newsteps.append(stip)
    
#--------------TWO SLIDER WITH TIME AND SIGMA

sliders = [dict(
    active=20,
    currentvalue={"prefix": "Time: "},
    pad={"t": 50},
    y=-0.1,
    steps=steps),
    dict(
    active=4,
    currentvalue={"prefix": "Sigma: "},
    pad={"t": 50},
    y=-0.3,
    steps=newsteps)
    ]


fig.update_layout(showlegend=False,
    sliders=sliders,
    width=1300,
    height=900,
    title_text="Atomic lines of {} ".format(name)+"in range: {:.2f}-{:.2f}".format(xmin,xmax)+" nm",
                  title_font_size=30, xaxis_title="Wavelength [nm]",
    yaxis_title="Intensity"
)

fig.show()
2

@Listerico. I’d be interested in knowing an answer for this too, did you manage to get this to work in the end?

1 Like