Time series downsampling in rust
Project description
tsdownsample
📈 Time series downsampling algorithms for visualization
Features ✨
- Fast: written in rust with pyo3 bindings
- leverages optimized argminmax - which is SIMD accelerated with runtime feature detection
- scales linearly with the number of data points
- scales multi-threaded with rayon (rust)
- Efficient: memory efficient
- works on views of the data (no copies)
- no intermediate data structures are created
- Flexible: works on any type of data
- supported datatypes are
f16,f32,f64,i16,i32,i64,u16,u32,u64
!! 🚀f16argminmax is 200-300x faster than numpy
- supported datatypes are
- Easy to use: simple API
Install
❗🚨❗ This package is currently under development - no stable release yet ❗🚨❗
pip install tsdownsample
Usage
import tsdownsample as tsds
import pandas as pd; import numpy as np
# Create a time series
y = np.random.randn(10_000_000)
s = pd.Series(y)
# Downsample to 1000 points
s_ds = tsds.minmaxlttb(s, n_out=1000)
👤 Jeroen Van Der Donckt
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