A python package for transient time series
Project description
trimes
trimes (transient time series) is a python package for transient time series data in pandas format. The application is actually for all time series data where the time vector has a numerical format (e.g numpy's float64) - as opposed to the frequently used DateTime format. To the best of our knowledge, there is currently no other python package focusing on transient time series data as described and the mentioned DateTime format is not convenient for transient time series.
trimes provides functionality for pandas DataFrames (in the format mentioned above) for the following use cases:
- get data points
- interpolation
- resampling
- regression
- signal generation (harmonics, symmetrical components)
- comparison of times series (difference, boundaries, envelopes)
- metrics (e.g. root mean squared error)
- step response analysis
- plotting
and more.
Have a look at the documentation to get started.
Installation
pip install trimes
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file trimes-0.0.4.tar.gz
.
File metadata
- Download URL: trimes-0.0.4.tar.gz
- Upload date:
- Size: 512.7 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f5f89a8b9476aef2fb17b3d4130bf946d60563e876fa433ca8954598377bbbd |
|
MD5 | 67f00820a25ec0508698c516770e9a9e |
|
BLAKE2b-256 | 4a1bd573bd2d70d7cf655cbbd76b70398fdbece9086a902513a2d8484096b349 |
File details
Details for the file trimes-0.0.4-py3-none-any.whl
.
File metadata
- Download URL: trimes-0.0.4-py3-none-any.whl
- Upload date:
- Size: 19.4 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/5.0.0 CPython/3.11.7
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | a6eb07fb682f78ef574a811335d01605283f211d9f41f995ca9fedfd5c19cd62 |
|
MD5 | 2e44136fcb3664b1ebffc6759b679774 |
|
BLAKE2b-256 | 5571df497cbf40cedd15f2d0db0fcddf0d896f386816859f469a2bfa41d5d598 |