lenspy 1.1.0

Plot big data with Python.

LensPy: Plot millions of data points

LensPy extends Plotly's Dash to allow you to plot very large datasets (millions of points) while ensuring that figures are still fast, fluid, and responsive.

This is achieved by adjusting the visible data based on the position of the viewport and how zoomed in the figure is. When you're zoomed out, only a subset of the data is shown. When you zoom in, LensPy will render more detail in your plot. By doing this, LensPy can build dynamic figures of very large datasets without overwhelming the browser when viewing the figures.

Contents

• Features
• Installation
• Getting Started
• Jupyter
• Advanced Usage
• License
• Contributing

Features

• Ability to specify number of points to display at once
• Ability to define a custom function for downsampling data
• Ability to run in Jupyter notebooks
• Ability to use with Dash applications

Installation

Install LensPy using pip

pip install lenspy

Getting Started

Use LensPy by passing any Figure to the DynamicPlot constructor.

import numpy as np
import plotly.graph_objects as go
from lenspy import DynamicPlot

# First, let's create a very large figure
x = np.arange(1, 11, 1e-6)
y = 1e-2*np.sin(1e3*x) + np.sin(x) + 1e-3*np.sin(1e10*x)
fig = go.Figure(data=[go.Scattergl(x=x, y=y)])
fig.update_layout(title=f"{len(x):,} Data Points.")

# Use DynamicPlot.show to view the plot
plot = DynamicPlot(fig)
plot.show()

# Plot will be available in the browser at http://127.0.0.1:8050/

You can still access any of the Plotly Figure methods/attributes and modify them as needed.

Jupyter

LensPy starts a Flask web server, therefore plots won't be rendered in your notebook as widget. You can always access your plot in a seperate tab (default url is http://127.0.0.1:8050/)

Advanced Usage

For the full reference and detailed information, please see the documentation.

License

Copyright (c) 2020 Seran Thirugnanam under the MIT License.

Contributing

Help is always welcome. Feel free to open issues or PRs if there is a feature missing, or a bug to be addressed.