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
!! 🚀f16
argminmax 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
Project details
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Algorithm | Hash digest | |
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SHA256 | 37f777ac8c2da1f13dcf0e5290554e95156c237e39cf4ec821fc4981ae81a3b2 |
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MD5 | fac3a338bba6a196980d7fd497b0372f |
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BLAKE2b-256 | 51aa5d36ceb3aaadb125bdc8e5e356c5a0c9d03ee014f3746d767b4fa324bab3 |
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Hashes for tsdownsample-0.1.0a1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 96fef7d15d26ed494bac732ad6581d916e1865f1413a5ac4b4ea4ddea102c22e |
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MD5 | e3e328936967ee1994c225e4979445df |
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BLAKE2b-256 | 504fcae226e1868bf219406c600a222ef3ed81188a9ee9abcd4c29cb05be6280 |
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Hashes for tsdownsample-0.1.0a1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
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SHA256 | 9980fa4ec6e895efd77b4b0553aeb79f17aaa8b6c3d2121227d5cb495d523062 |
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MD5 | f5efea47aceb42746d40a8dae5ab9e0e |
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BLAKE2b-256 | 81987fdc556137e0f88f34b1fb0f6a08195cbd5224e691fce684c9df371aef9d |
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Hashes for tsdownsample-0.1.0a1-cp38-cp38-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm | Hash digest | |
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SHA256 | 83610ad2e4767a8b4fad3f27c0ecaa9f4a4c825fa1fbc1d270c4ee52578fb6ff |
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MD5 | 5ac4f85aaa78e100ff0e09ff8bb893e3 |
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BLAKE2b-256 | 616307d00d5640a3d82a38e6a3cce6806680556c07cfbc31e1241cba727c1729 |
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Hashes for tsdownsample-0.1.0a1-cp38-cp38-macosx_10_9_arm64.whl
Algorithm | Hash digest | |
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SHA256 | 247c962e387e04f17d1d534c3dfe02f358f37ea2dc3f036d0c72a0a85389256c |
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MD5 | 9988aa8da825ed0eeccd6ee1081cfbf9 |
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BLAKE2b-256 | 7ce508a5d0183533c5ead68db767c041d5ac6f3efb87f8e57a3ec4af19570c43 |
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Hashes for tsdownsample-0.1.0a1-cp38-cp38-macosx_10_7_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 2dc6cf2ffd5b3a5ad177aa9d0d26012780b7d2240948a70a5b7fb14afbc642cd |
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MD5 | 232d347769907b8a802a92a6f43ad6da |
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BLAKE2b-256 | d6ff7370a903898d18af83b688c64234c564675b32623a7a4e4761c04898a453 |
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Hashes for tsdownsample-0.1.0a1-cp37-none-win_amd64.whl
Algorithm | Hash digest | |
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SHA256 | 02de174cae2e0004f1b677769d2010da1c911dad389f95f13b2b835132731fd4 |
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MD5 | 7fca52ba8f0a8923c7ea0924f06b92e4 |
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BLAKE2b-256 | b73f1debcad94e5ce5873771c8af235532c0752553b80065de2db50355821b8e |
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Hashes for tsdownsample-0.1.0a1-cp37-none-win32.whl
Algorithm | Hash digest | |
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SHA256 | 41f17f697a7d0974618a71096d650c54491042f5b0321965d5a7f4e74addcfc4 |
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MD5 | 5a669fce945474600f3f60ce05e27299 |
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BLAKE2b-256 | 747dd4a12835cd2b56fd8e0be5bb5f50c514b4d57cbd981dc8767173760cc6b9 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm | Hash digest | |
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SHA256 | 9dc444997ecc0ec12f51dc79277aba1fd22c1201206725ae6a322de74d6d4f46 |
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MD5 | 97392f54cc7013c5fe7bca74e71f3984 |
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BLAKE2b-256 | f4a67a977e4897b3a0e6a4ec12006ac30011fec4bf652efb26fdb878f694812d |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-musllinux_1_1_aarch64.whl
Algorithm | Hash digest | |
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SHA256 | b4c3bf5662ea90d9841bfaf73f353c59e743f560d3e2f63f17b52da017a50647 |
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MD5 | b1cd1d22d67e74399f57f55dbebf8613 |
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BLAKE2b-256 | 95c3ca7e56336b89fc8f8058f21f5c07f379ab8f79c54e3083bb0da9bab9dff1 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_24_s390x.whl
Algorithm | Hash digest | |
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SHA256 | acba40ae54d0596f5188a2e0dee77eaf9035dac085bcc0c51129d84f9f60fbc6 |
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MD5 | 7f4adf073ea05d66abdc968d07123075 |
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BLAKE2b-256 | d0619a9ed7a879f7c62138860165951b98ba9858a26c29399319bf5af25420a4 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_24_ppc64le.whl
Algorithm | Hash digest | |
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SHA256 | a97e465f1c8853de50daeab7643b5c607b2b09f833886c3652085d24d1d4af6b |
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MD5 | 193ce860212a44efcbf893be0cf52995 |
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BLAKE2b-256 | 109717ca5c9bcd3e40dbd4ea205d2b1a2f7e0bcba993fa67450031693a3a2d89 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_24_armv7l.whl
Algorithm | Hash digest | |
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SHA256 | 9ec14b30e675990ff10ff33d080670b9ec42628c7fe6df8be20f7313ef8c2c54 |
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MD5 | 92dda6fb9aeb278c996b1ebb6c7faa20 |
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BLAKE2b-256 | 4f4af5c7268aa0a149947093e733a208cdfc0719fd86e506298ca9dff2a8a658 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | e510a60b72bf72e1644a430b2ba6c4de7c1e162bd56ae02ee4d343825d7966c4 |
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MD5 | 6f2a4e4c9c9e14fea477306f80ab5193 |
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BLAKE2b-256 | b22dde7fa2ea2b3b73123e73bbc3ce88df0a510fc840293d51935b26b0288f7a |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm | Hash digest | |
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SHA256 | f63d6fa8b324df8e8afe4ba810e716da7ce7b1d89fb86839a06f0ebbf442f064 |
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MD5 | d0b4e561e946bc6614dc99523172b7ad |
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BLAKE2b-256 | e0ea87f62577164c167246f5998117003a0e0fd516468d5e706d578989c949a4 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-manylinux_2_12_i686.manylinux2010_i686.whl
Algorithm | Hash digest | |
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SHA256 | f442cca8d264a3c0da46b83b207ffd2309b9910237fd52a89ca8e44d9177ffe1 |
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MD5 | 8ba64c7b7abdc5f0ab83f29061409ffd |
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BLAKE2b-256 | fda7b7b484c50a39cbbbd9a7be68ae9745b1dc8af5e904dbaa0b3ecccea8bb84 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-macosx_10_9_arm64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | cc209a5ca2d6c82aed0a9529d24375afef5837f47f08556b92745256123a9b5e |
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MD5 | 28a8393af2e4f379b2ed6a5983e4ee40 |
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BLAKE2b-256 | ae98db04827d11d2ec626657cc9e7d0bbfd345140ac42a2e6116bb0d96f28729 |
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Hashes for tsdownsample-0.1.0a1-cp37-cp37m-macosx_10_7_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 96135d2d653154e6fc320261691e99913ff638aaec2ac1412f8839a8ee9fa694 |
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MD5 | c477cab406b3b3e21a0779a3bdfcfc16 |
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BLAKE2b-256 | aaf1a187edcb4baf15415002cf8a14564c7899db753f7db9bd36fe73cbcd7b64 |