successor 
Uses pre-trained tensorflow models to predict the next k entries in a sequence
Install
pip install successor
You may get better performance by first installing tensorflow following the instructions and perhaps reading this thread.
Use
See basic_use
# 1. Import a skater
from successor.skaters.scalarskaters.scalartsaskaters import successor_tsa_aggressive_d0_ensemble as f
# 2. Univariate data
import numpy as np
y = list(np.cumsum(np.random.randn(1000)))
# 3. Initialize state to empty dict
s = {}
# 4. Give it some data (observations) one at a time, each time passing it back the state s
for yi in y:
x, x_std, s = f(y=yi,s=s,k=1)
Skaters follow the convention established by the timemachines library and you are encouraged to read the description of the "skater" signature if anything is confusing.
Benchmarking
See Elo ratings
1 maintainer
Metadata
1 maintainer
Release files for successor 0.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| successor-0.2.0.tar.gz | 8.8 kB | Without provenance | Details for successor-0.2.0.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| successor-0.2.0-py3-none-any.whl | Python 3 | none | any | Details for successor-0.2.0-py3-none-any.whl |
Total release size: 19.3 kB
Release files / successor-0.2.0.tar.gz
| Download URL | successor-0.2.0.tar.gz |
|---|---|
| Size | 8.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
bb9861ab7fec4bf8a735e59788ceefc14c2b06091f849fd596ccf8c89cb916ec
|
|
BLAKE2b-256 checksum How to use checksums |
f4abbe2252b3393d83bc3e54f8d5787840773570f057f723776081ee9beb00b7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|
Release files / successor-0.2.0-py3-none-any.whl
| Download URL | successor-0.2.0-py3-none-any.whl |
|---|---|
| Size | 10.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
8ba69bb78da985556c7a3ae59df9d9d6f85470930369bde489319245ba737072
|
|
BLAKE2b-256 checksum How to use checksums |
a9e8817d45d55d38804dc9860b52281407116775a72430ceac672a5ff7ff6a10
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.4.2 importlib_metadata/4.8.1 pkginfo/1.7.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7
|
Security for successor 0.2.0
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
