GitHub – pysal/giddy: Geospatial Distribution Dynamics

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Giddy is an open-source python library for the evaluation of dynamics of
longitudinal spatial knowledge. Originating from the spatial dynamics module
in PySAL (Python Spatial Evaluation Library), it’s underneath lively growth
for the inclusion of newly proposed analytics that contemplate the
function of area within the evolution of distributions over time.

Beneath are six choropleth maps of US state per-capita incomes from 1929 to 2004 at a fifteen-year interval.

us_qunitile_maps

Documentation

On-line documentation is offered right here.

Options

  • Directional LISA, inference and visualization as rose diagram

rose_conditional

Above exhibits the rose diagram (directional LISAs) for US states incomes throughout 1969-2009 conditional on relative incomes in 1969.

  • Spatially specific Markov strategies:
    • Spatial Markov and inference
    • LISA Markov and inference
  • Spatial decomposition of alternate mobility measure (rank strategies):
    • World indicator of mobility affiliation (GIMA) and inference
    • Inter- and intra-regional decomposition of mobility affiliation and inference
    • Native indicator of mobility affiliation (LIMA)
      • Neighbor set LIMA and inference
      • Neighborhood set LIMA and inference

us_neigborsetLIMA

Examples

Set up

Set up the steady model launched on the Python Bundle Index from the command line:

pip set up giddy

Set up the event model on pysal/giddy:

pip set up https://github.com/pysal/giddy/archive/grasp.zip

Necessities

  • scipy>=1.3.0
  • libpysal>=4.0.1
  • mapclassify>=2.1.1
  • esda>=2.1.1
  • quantecon>=0.4.7

Contribute

PySAL-giddy is underneath lively growth and contributors are welcome.

When you have any suggestion, characteristic request, or bug report, please open a brand new difficulty on GitHub. To submit patches, please comply with the PySAL growth pointers and open a pull request. As soon as your adjustments get merged, you’ll robotically be added to the Contributors Record.

Assist

If you’re having points, please discuss to us within the gitter room.

License

The challenge is licensed underneath the BSD license.

BibTeX Quotation

@software program{wei_kang_2020_3887455,
  creator       = {Wei Kang and
                  Sergio Rey and
                  Philip Stephens and
                  Nicholas Malizia and
                  James Gaboardi and
                  Stefanie Lumnitz and
                  Levi John Wolf and
                  Charles Schmidt and
                  Jay Laura and
                  Eli Knaap},
  title        = {pysal/giddy: Launch v2.3.3},
  month        = jun,
  12 months         = 2020,
  writer    = {Zenodo},
  model      = {v2.3.3},
  doi          = {10.5281/zenodo.3887455},
  url          = {https://doi.org/10.5281/zenodo.3887455}
}

Funding

Award #1421935 New Approaches to Spatial Distribution Dynamics

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