Randomly generates data and uses Plotly to create a visualization HTML

generate_large_html

#%%

import numpy as np
import matplotlib.pyplot as plt
import random
import plotly.graph_objects as go
from plotly.subplots import make_subplots

#%% 

def generate_data(sec = 10, Hz = 32000):
    time = np.arange(0, sec, 1/Hz)
    amplitude = (np.random.random(time.shape) - 0.5) * random.randint(10, 25)
    return time, amplitude

#%%
colors = [
    '#1f77b4',  # muted blue
    '#ff7f0e',  # safety orange
    '#2ca02c',  # cooked asparagus green
    '#d62728',  # brick red
    '#9467bd',  # muted purple
    '#8c564b',  # chestnut brown
    '#e377c2',  # raspberry yogurt pink
    '#7f7f7f',  # middle gray
    '#bcbd22',  # curry yellow-green
    '#17becf'  # blue-teal
    ]

channels = 3

fig = make_subplots(rows=channels, cols=1)

for i in range(channels):
    ts, amp = generate_data()
    
    fig.append_trace(go.Scatter(x=ts, y=amp,
                        line=dict(color=colors[i % 10]),                                
                        mode='lines',
                        name='Random Data ' + str(i)), row=i+1, col=1)       

fig.update_layout(
title="Random Data Plots",
font=dict(
    family="Courier New, monospace",
    size=18,
    color="#7f7f7f"
    )
)

fig.write_html("index.html")