Difference between revisions of "Pyleoclim"
(Update version) |
(→Previous versions: Update versions) |
||
| (One intermediate revision by the same user not shown) | |||
| Line 45: | Line 45: | ||
=== Previous versions === | === Previous versions === | ||
| + | * 0.2.3: Freeze LiPD version to 1.2 to avoid conflicts with 1.3 | ||
| + | * 0.2.2: Change progressbar to tqdm and add standardization function | ||
| + | * 0.2.1: Update package requirements | ||
* 0.2.0: Restructure the package so that the main functions can be called without the use of a LiPD files and associated timeseries objects. | * 0.2.0: Restructure the package so that the main functions can be called without the use of a LiPD files and associated timeseries objects. | ||
* 0.1.4: Rename function using camel case and consistency with LiPD utilities version 0.1.8.5 | * 0.1.4: Rename function using camel case and consistency with LiPD utilities version 0.1.8.5 | ||
| Line 71: | Line 74: | ||
== Requirements == | == Requirements == | ||
| − | * LiPD | + | * LiPD >=0.2.0.2, <=0.2.1.9 |
* pandas v0.19+ | * pandas v0.19+ | ||
* numpy v1.12+ | * numpy v1.12+ | ||
| Line 80: | Line 83: | ||
* seaborn>=0.7.0 | * seaborn>=0.7.0 | ||
* scikit-learn>=0.17.1 | * scikit-learn>=0.17.1 | ||
| − | * | + | * tqdm>=4.14.0 |
The installer will automatically check for the needed updates | The installer will automatically check for the needed updates | ||
Latest revision as of 16:08, 27 June 2017
Python Package for the Analysis of Paleoclimate Data
Current version : 0.2.3
Contents
What is it?
Pyleoclim is a Python package primarily geared towards the analysis and visualization of paleoclimate data. Such data often come in the form of timeseries with missing values and age uncertainties, and the package includes several low-level methods to deal with these issues, as well as high-level methods that re-use those to perform scientific workflows.
The package assumes that data are stored in the Linked Paleo Data (LiPD) format and makes extensive use of the LiPD utilities. The package is aware of age ensembles stored via LiPD and uses them for time-uncertain analyses very much like GeoChronR.
Current Capabilities
- binning
- interpolation
- plotting maps, timeseries, and basic age model information
- paleo-aware correlation analysis (isopersistent, isospectral and classical t-test)
Future Capabiltities
- paleo-aware singular spectrum analysis (AR(1) null eigenvalue identification, missing data)
- spectral analysis (Multi-Taper Method, Lomb-Scargle)
- weighted wavelet Z transform (WWZ)
- cross-wavelet analysis
- index reconstruction
- climate reconstruction
- ensemble methods for most of the above
If you have specific requests, please contact us.
Version Information
Versioning System
The Pyleoclim versioning system follows the x.y.z nomeclature where x represents major package update (version 1.0.0 will correspond to the package where most of the capabitlites listed above are included), y represents a package update offering new functionalities, and z represents changes due to reported bugs or to maintain compatibilities with the dependecies.
Previous versions
- 0.2.3: Freeze LiPD version to 1.2 to avoid conflicts with 1.3
- 0.2.2: Change progressbar to tqdm and add standardization function
- 0.2.1: Update package requirements
- 0.2.0: Restructure the package so that the main functions can be called without the use of a LiPD files and associated timeseries objects.
- 0.1.4: Rename function using camel case and consistency with LiPD utilities version 0.1.8.5
- 0.1.3: Compatible with LiPD utilities version 0.1.8.5. Function openLiPD() renamed openLiPDs()
- 0.1.2: Compatible with LiPD utilities version 0.1.8.3. Uses basemap instead of cartopy
- 0.1.1: Freezes the package prior to version 0.1.8.2 of LiPD utilities
- 0.1.0: First release
Installation
Python v3.5 is required. Not fully compatible with Python v3.6
Pyleoclim is published through PyPi and easily installed via `pip`
pip install pyleoclim
QuickStart Guide
- Open your command line application (Terminal or Command Prompt).
- Install with command: `pip install pyleoclim`.
- Wait for installation to complete, then:
- Import the package into your favorite Python environment (we recommend the use of Spyder, which comes standard with the Anaconda package)
- Use Jupyter Notebook to go through the tutorial contained in the `PyleoclimQuickstart.ipynb` Notebook, which can be downloaded here.
- Help with functionalities can be found in the Documentation folder on our GitHub repositoryand on Pypi.
Requirements
- LiPD >=0.2.0.2, <=0.2.1.9
- pandas v0.19+
- numpy v1.12+
- matplotlib v2.0+
- Basemap v1.0.7+
- scipy >=0.19.0
- statsmodel>=0.8.0
- seaborn>=0.7.0
- scikit-learn>=0.17.1
- tqdm>=4.14.0
The installer will automatically check for the needed updates
Note: Some of the Pyleoclim dependencies are not supported on Windows
Further Information
GitHub: https://github.com/LinkedEarth/Pyleoclim_util
Python and Anaconda: http://conda.pydata.org/docs/test-drive.html
Jupyter Notebook: http://jupyter.org
Contact
Please report issues to linkedearth@gmail.com.
License
The project is licensed under the GNU Public License.
Disclaimer
This material is based upon work supported by the National Science Foundation under Grant Number ICER-1541029. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the investigators and do not necessarily reflect the views of the National Science Foundation.
