Dependencies
Make sure you have install the fbprophet and NeuralProphet
fbprophet version == 0.7.1
Steps to install fbprophet
conda env -n test_env python==3.8.5
conda install -c anaconda ephem
conda install -c conda-forge pystan
conda install -c conda-forge fbprophet
if error degrade to pystan==2.19.1.1
###Steps to install NeuralProphet
pip install neuralprophet ==0.3.0
#import
from auto_ts_ensemble_rupakbob import auto_ts_ensemble
#call the package function 1
results = auto_ts_ensemble.neural_analysis(data,freq="H")
###access the model
neural_prophet = results[0]
###access the metrics
metrics = results[1]
###access the predictions
predictions = results[2]
####plot the components
neural_prophet.plot_components(predictions)
#call the package function 2
results2 = auto_ts_ensemble.ts_analysis(data,n_future=7)
#access the model
ts_model = results2[0]
#access the predictions
predictions2 = results2[1]
#plot the components
ts_model.plot_components(predictions2)
#call the package function 3 ensemble
ensemble_predictions = auto_ts_ensemble.ensemble_analysis(predictions,predictions2)
Metadata
Release files for auto-ts-ensemble 0.0.6
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 | |
|---|---|---|---|---|
| auto_ts_ensemble-0.0.6.tar.gz | 3.5 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| auto_ts_ensemble-0.0.6-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.5 kB
Release files / auto_ts_ensemble-0.0.6.tar.gz
| Download URL | auto_ts_ensemble-0.0.6.tar.gz |
|---|---|
| Size | 3.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
794c810df5db3417e3eaa0f9a76b20433acffd689a71a2edcd1951aba583cd99
|
|
BLAKE2b-256 checksum How to use checksums |
63f056042a21748c2546834dd480289c7b12d873d1aba6a770e04c279cb17e9d
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.3
|
Release files / auto_ts_ensemble-0.0.6-py3-none-any.whl
| Download URL | auto_ts_ensemble-0.0.6-py3-none-any.whl |
|---|---|
| Size | 4.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
743783f31c8d97e11db0d5a6c12687e505cce04d4f6fdfddcd0c6ca6c9ba3ec4
|
|
BLAKE2b-256 checksum How to use checksums |
7ff87abd6f5215a286373fdb7e277a711bfc3e399e6e0461e6758476070de296
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.3
|
Security for auto-ts-ensemble 0.0.6
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.