TrajectoryData
Package providing the TrajectoryData class that allows to manage data for observables from a large number of quantum trajectory simulations
Development of TrajectoryData happens on Github.
Installation
To install the latest released version of TrajectoryData, run this command in your terminal:
$ pip install trajectorydataThis is the preferred method to install TrajectoryData, as it will always install the most recent stable release.
If you don’t have pip installed, this Python installation guide can guide you through the process.
To install the latest development version of TrajectoryData from the from the Github.
$ pip install git+https://github.com/goerz/trajectorydata.git@master#egg=trajectorydataUsage
To use TrajectoryData in a project:
import trajectorydata
History
0.1.0 (2018-03-25)
Initial release
1 maintainer
Release files for trajectorydata 0.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| trajectorydata-0.1.0-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Release files / trajectorydata-0.1.0-py2.py3-none-any.whl
| Download URL | trajectorydata-0.1.0-py2.py3-none-any.whl |
|---|---|
| Size | 12.5 kB |
| Tags | Python 2 Python 3 |
|
SHA-256 checksum How to use checksums |
57f601f77438cde7414bfe5772e8b029f6b849d6ba13d9a0df8bc2158eacd539
|
|
BLAKE2b-256 checksum How to use checksums |
fa0dac2031f183613457efc4d2307170adec6e3af4b891799312e0da39bcc809
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
