Python package to Create, Read, Write, Edit, and Visualize GSFLOW models

Overview

pyGSFLOW logo

pygsflow continuous integration codecov PyPI

pygsflow

pyGSFLOW is a python package to Create, Read, Write, Edit, and Visualize GSFLOW models

API Documentation

pyGSFLOW API documentation can be found @

https://pygsflow.github.io/pygsflowdocs/

Examples

Ipython notebook example problems can be found in the examples directory.
https://github.com/pygsflow/pygsflow/tree/master/examples

Installation

The pygsflow repository can be installed using pip. To install the most recent release version, open a command prompt or anaconda prompt terminal and type:

pip install pygsflow

or

pip install https://github.com/pygsflow/pygsflow/zipball/master

Or to install the development version with the most recent updates

pip install https://github.com/pygsflow/pygsflow/zipball/develop

Alternatively the user can download a copy of the repository, open a command prompt or anaconda promt terminal, cd into the trunk directory and type:

pip install .

Authors

Ayman Alzraiee, Joshua Larsen, Donald Martin, Rich Niswonger

How to Cite

Larsen, J. D., Alzraiee, A., Niswonger, R., 2021, pyGSFLOW v1.0.0: U.S. Geological Survey Software Release, 2 July 2021, https://doi.org/10.5066/P9NPZ5AD

Bugs

The code is in active development and although there is a testing infrastructure set up we cannot catch all the software bugs without the help of users. If you find a bug or have an issue, please report it by opening a new issue. You can open a new issue by clicking the issues tab near the top of the page.

Project History

This project is a refinement and continuation of the original pygsflow repository at:

https://github.com/aymanalz/pygsflow

Disclaimer

This software is preliminary or provisional and is subject to revision. It is being provided to meet the need for timely best science. The software has not received final approval by the U.S. Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S. Government as to the functionality of the software and related material nor shall the fact of release constitute any such warranty. The software is provided on the condition that neither the USGS nor the U.S. Government shall be held liable for any damages resulting from the authorized or unauthorized use of the software

Comments
  • JOSS review feedback

    JOSS review feedback

    Hello pygsflow team! I'm a reviewer for your submission to JOSS tracked here. I'll use this issue to track my feedback on the paper and software -- feel free to split out my comments into separate issues if that helps your workflow.

    README.md

    • [x] #13

    Paper

    • [x] #18
    • [x] Paragraph starting on line 62: since you mention external sensitivity analysis software, it could be useful for readers to cite the calibration software typically used in GSFLOW applications

    Jupyter notebooks

    • [x] #15
    • [x] #16
    • [x] #17
    • [x] #14
    • [x] Just wanted to say that the plots in the stream vector notebook are really nice looking!
    opened by thurber 4
  • remove_record() method does not recognize parameter names

    remove_record() method does not recognize parameter names

    I am trying to remove parameters from the control file.

    I can get_record(name='soilzone_module'):

    soilzone_module 1 4 soilzone

    But I can't remove_record(name='soilzone_module'):

    /home/mrush/miniconda3/lib/python3.8/site-packages/gsflow/param_base.py:211: UserWarning: The record does not exist: soilzone_module warnings.warn("The record does not exist: {}".format(name),

    opened by mrush-usgs 2
  • Typo in pyGSFLOW documentation

    Typo in pyGSFLOW documentation

    Greetings, pyGSFLOW documentation site has a typo in its text as well as in its page title. It states "Welocme" instead of "Welcome".

    PoC: https://pygsflow.github.io/pygsflowdocs/#welocme-to-the-pygsflow-documentation

    opened by ccalvocm 1
  • JOSS review feedback 2

    JOSS review feedback 2

    Hi all, this checklist will contain feedback related to your JOSS Review. I will continue to update this checklist as I move through my review:

    Installation

    • [x] Indicate which python versions are supported in the README.
    • [x] Installation fails from develop branch on Python3.6 with EnvironmentError("pyGSFLOW is only supported with python 3.7 and above"). Please indicate that Python3.6 is not supported in the README.
    • [x] Installation fails from develop branch on Python3.7 due to dependency error ERROR: Could not find a version that satisfies the requirement flopy>=3.3.5
    • [x] Installation fails from develop branch on Python3.8 due to dependency error ERROR: Could not find a version that satisfies the requirement flopy>=3.3.5
    • [x] Installation fails from develop branch on Python3.9 due to dependency error ERROR: Could not find a version that satisfies the requirement flopy>=3.3.5
    • [x] Installation fails from develop branch on Python3.10 due to dependency error: ERROR: Could not find a version that satisfies the requirement flopy>=3.3.5
    • [x] #24
    • [x] #25

    Documentation

    • [x] Cannot find contributing guidelines in README.
    • [x] #23
    • [x] #22

    Misc

    • [x] 'Dependency' issue tag is misspelled.
    • [x] #21
    • [x] #20
    opened by mdbartos 1
  • Parameter 'Width' Integers Not Required in Parameter File

    Parameter 'Width' Integers Not Required in Parameter File

    prms_parameter.py currently prints the parameter 'width' attribute (default 10) to the parameter file. These numbers are not required for prms/gsflow.

    https://github.com/pygsflow/pygsflow/blob/master/gsflow/prms/prms_parameter.py

    Lines 535 and 584

    opened by mrush-usgs 1
  • Adding building Parameters with JSON - Defaults

    Adding building Parameters with JSON - Defaults

    I added the build by default for parameters in the JSON file. I think I am missing a default file that I can upload later, but I put different cases with different dimensions for parameters in the docs of the function

    opened by jonathanqv 0
  • NetCDF4 and Rasterio conflict: HDF error when trying to write Dataset

    NetCDF4 and Rasterio conflict: HDF error when trying to write Dataset

    The rasterio wheels on PyPI include HDF5 and netCDF4 shared libraries and they can create conflicts with the netCDF4 wheel.

    The proposed workaround is to install rasterio from the source distribution instead of from binary wheel.

    pip install netcdf4
    pip install --no-binary rasterio rasterio
    

    This method works on all tested sytems (ubuntu, macos, and windows) to avoid binary library conflicts.

    opened by jlarsen-usgs 0
Releases(1.1.0)
Owner
pyGSFLOW
pyGSFLOW is a python package for GSFLOW integrated models
pyGSFLOW
This GitHub Repository contains Data Analysis projects that I have completed so far! While most of th project are focused on Data Analysis, some of them are also put here to show off other skills that I have learned.

Welcome to my Data Analysis projects page! This GitHub Repository contains Data Analysis projects that I have completed so far! While most of th proje

Kyle Dini 1 Jan 31, 2022
🗾 Streamlit Component for rendering kepler.gl maps

streamlit-keplergl 🗾 Streamlit Component for rendering kepler.gl maps in a streamlit app. 🎈 Live Demo 🎈 Installation pip install streamlit-keplergl

Christoph Rieke 39 Dec 14, 2022
Type-safe YAML parser and validator.

StrictYAML StrictYAML is a type-safe YAML parser that parses and validates a restricted subset of the YAML specification. Priorities: Beautiful API Re

Colm O'Connor 1.2k Jan 04, 2023
Monochromatic colorscheme for matplotlib with opinionated sensible default

Monochromatic colorscheme for matplotlib with opinionated sensible default If you need a simple monochromatic colorscheme for your matplotlib figures,

Aria Ghora Prabono 2 May 06, 2022
A streamlit component for bi-directional communication with bokeh plots.

Streamlit Bokeh Events A streamlit component for bi-directional communication with bokeh plots. Its just a workaround till streamlit team releases sup

Ashish Shukla 123 Dec 25, 2022
Library for exploring and validating machine learning data

TensorFlow Data Validation TensorFlow Data Validation (TFDV) is a library for exploring and validating machine learning data. It is designed to be hig

688 Jan 03, 2023
Bcc2telegraf: An integration that sends ebpf-based bcc histogram metrics to telegraf daemon

bcc2telegraf bcc2telegraf is an integration that sends ebpf-based bcc histogram

Peter Bobrov 2 Feb 17, 2022
Plot-configurations for scientific publications, purely based on matplotlib

TUEplots Plot-configurations for scientific publications, purely based on matplotlib. Usage Please have a look at the examples in the example/ directo

Nicholas Krämer 487 Jan 08, 2023
Leyna's Visualizing Data With Python

Leyna's Visualizing Data Below is information on the number of bilingual students in three school districts in Massachusetts. You will also find infor

11 Oct 28, 2021
Missing data visualization module for Python.

missingno Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities tha

Aleksey Bilogur 3.4k Dec 29, 2022
Visualizations of some specific solutions of different differential equations.

Diff_sims Visualizations of some specific solutions of different differential equations. Heat Equation in 1 Dimension (A very beautiful and elegant ex

2 Jan 13, 2022
A programming language built on top of Python to easily allow Swahili speakers to get started with programming without ever knowing English

pyswahili A programming language built over Python to easily allow swahili speakers to get started with programming without ever knowing english pyswa

Jordan Kalebu 72 Dec 15, 2022
Tandem Mass Spectrum Prediction with Graph Transformers

MassFormer This is the original implementation of MassFormer, a graph transformer for small molecule MS/MS prediction. Check out the preprint on arxiv

Röst Lab 13 Oct 27, 2022
Geospatial Data Visualization using PyGMT

Example script to visualize topographic data, earthquake data, and tomographic data on a map

Utpal Kumar 2 Jul 30, 2022
Visualizations for machine learning datasets

Introduction The facets project contains two visualizations for understanding and analyzing machine learning datasets: Facets Overview and Facets Dive

PAIR code 7.1k Jan 07, 2023
Practical-statistics-for-data-scientists - Code repository for O'Reilly book

Code repository Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python by Peter Bruce, Andrew Bruce, and Peter Gedeck Pub

1.7k Jan 04, 2023
Rockstar - Makes you a Rockstar C++ Programmer in 2 minutes

Rockstar Rockstar is one amazing library, which will make you a Rockstar Programmer in just 2 minutes. In last decade, people learned C++ in 21 days.

4k Jan 05, 2023
Color maps for POV-Ray v3.7 from the Plasma, Inferno, Magma and Viridis color maps in Python's Matplotlib

POV-Ray-color-maps Color maps for POV-Ray v3.7 from the Plasma, Inferno, Magma and Viridis color maps in Python's Matplotlib. The include file Color_M

Tor Olav Kristensen 1 Apr 05, 2022
Python package for the analysis and visualisation of finite-difference fields.

discretisedfield Marijan Beg1,2, Martin Lang2, Samuel Holt3, Ryan A. Pepper4, Hans Fangohr2,5,6 1 Department of Earth Science and Engineering, Imperia

ubermag 12 Dec 14, 2022
Keir&'s Visualizing Data on Life Expectancy

Keir's Visualizing Data on Life Expectancy Below is information on life expectancy in the United States from 1900-2017. You will also find information

9 Jun 06, 2022