GeoDa 1.22 alpha

@lanselin @jkoschinsky Here are the installers of GeoDa 1.22 alpha:
Installers:

• Mac OS: https://github.com/GeoDaCenter/geoda/actions/runs/5546182155
• Windows: https://github.com/GeoDaCenter/geoda/actions/runs/5546182154
• Ubuntu: https://github.com/GeoDaCenter/geoda/actions/runs/5546182158

Please let me know of any issues and questions. Thanks!

GeoDa 1.20.0.36

Fix MST and order issue in HCluster
Fix windows wxwidgets debug msg

GeoDa V1.20.0.22

Fix: date field in table property editor crash windows #2403
Fix: did save bug + Portuguese #2399
Fix: restore proj4 db files for windows/ubuntu #2388

GeoDa v1.20.0.12

Fixes:

update 5/15/2022

• fix: map not displayed in Unique Value map w/ join count option #2387
• Fix: proj4 doesn't work on macos #2386
• Fix windows installer for multiusers #2379
• remove osm blackandwhite basemap #2378
• fix: cartogram initial canvas offset #2377
• fix: windows dll registry issue #2376
• fix: 3D plot and windows installer #2360
• fix dbf read issue; treat EMPTY as NULL value in string type column #2355
• fix weights creation dialog UI issue on ubuntu #2348

GeoDa v1.20

Features:

1. Spatial validation

Spatial validation provides a collection of validation measures including (1) fragmentations (entropy, simpson), (2) join count ratio, (3) compactness (isoperimeter quotient) and (4) diameter.

Fragmentation is a measure of spatial validation of clusters. It includes:

1. entropy, which measures the fraction of observations in each cluster
2. entropy*, which is the standardized entropy measure
3. simpson, which is an index for diversity measure in each cluster
4. simpson*, which is the standardized simpson measure

For non-spatially constrained clusters, the validation also reports cluster_fragmentation, which is a list of Fragmentation objects for each cluster, or None for spatially constrained clusters.

JoinCountRatio is measure of join counts (the number of times a category is surrounded by neighbors of the same category) over the total number of neighbors after converting each category to a dummy variable. It includes:

1. neighbors, the total number of neighbors of elements in a cluster
2. join count, the total join count of elements in a cluster
3. ratio: the ratio of total join count over total neighbors

Compactness is a measure of isoperimeter quotient for each spatially constrained cluster. It includes:

1. area, the area of a cluster. For points, the convex hull is used to compute the area.
2. perimeter, the perimeter of a cluster. For points, the convex hull is used to compute the perimeter
3. isoperimeter_quotient, (4 * pi * area) / (perimeter^2)

Diameter is a measure of the longest shortest distance between any pairs in a cluster. It includes:

1. steps, the longest shortest distance between any pairs
2. ratio, the ratio of steps over the number of elements in the cluster

2. Make Spatial

Make spatially constrained clusters from spatially non-constrained clusters using the contiguity information from the input weights

3. SC K Means

Spatially constrained K Means clustering algorithm implemented.

4. Join Count Ratio for Unique Value Maps

Add join count ratio option for unique value maps

5. Block Weights

Add block weights option in the contiguity weights creation

6. Cluster Map Match

Compare two clustering results using cluster map match.

7. Windows Installer for lab environment

Create installer for Windows 7+, which can be used in a Windows Lab Environment.

8. Add installer for Apple M1

Fixes:

• Weights creation from polygons wrong: double precision epsilon was not handled in weights creation code.
• fix issue that 3D plot doesn't work on Mac OS with version > 1.18.0.6
• Update GeoDa-win7+.iss for issue MS 2015-2019 Redist problems #2360

GeoDa 1.18

Note: Version 1.18.0.0 with major updates on spatially constrained clustering (Hierarchical Methods, Partitioning Methods)
Please download version 1.18.0.0 from: https://geodacenter.github.io/download.html

See the latest lab notes by Dr. Luc Anselin:

• Spatial Clustering (1) - Spatializing Classic Clustering Methods https://geodacenter.github.io/workbook/9a_spatial1/lab9a.html
• Spatial Clustering (2) - Spatially Constrained Clustering, Hierarchical Methods https://geodacenter.github.io/workbook/9c_spatial3/lab9c.html
• Spatial Clustering (3) - Spatially Constrained Clustering, Partitioning Methods https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html

New/updated features:

1. AZP Updates:

• AZP: add ARiSeL #2266 (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#arisel)
• AZP Tabu search (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#tabu-search-1)
• AZP Simulated Annealing (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#simulated-annealing)
• Update Minimum Bound on AZP

2. Max-p Updates:

• Reimplement max-p based on AZP (parallelized)
• max-p Greedy (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#greedy)
• max-p Tabu Search (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#tabu-search-2)
• max-p Simulated Annealing (see https://geodacenter.github.io/workbook/9d_spatial4/lab9d.html#simulated-annealing-2)

3. Spatially Constrained Hierarchical Clustering (SCHC) Updates:
(see https://geodacenter.github.io/workbook/9c_spatial3/lab9c.html#spatially-constrained-hierarchical-clustering-schc)

Add/update SCHC using Single/Average/Complete/Wards-linkage
The algorithm has been reimplemented based on Skater/Redcap

4. REDCAP Updates:
(see https://geodacenter.github.io/workbook/9c_spatial3/lab9c.html#redcap)

Add/update: FullOrder-WardsLinkage, FullOrder-SingleLinkage, Fullorder-AverageLinkage, Fullorder-CompleteLinkage, Firstorder-SingleLinkage

5. Language updates:
Spanish language (Thanks to Coro)
Russian language (Thanks to Venera Timiryanova)

Fixes:

1. Update Windows installer with Chinese language
2. Fix crash when using an empty column #2261
3. Fix "Heat Map" on Windows and Ubuntu #2263
4. Load incompatible Mat file in weights dialog will crash GeoDa #2265
5. Fix conditional boxplot crashes with time-grouped variables #2279
6. Fix a crash: when loading csv with empty coordinates as the second layer

GeoDa 1.16.0.16

Download version 1.16.0.16: https://geodacenter.github.io/download.html

bugfixes and some enhancement:

1. #2241 Add “Set as Unique Value” option in the conditional histogram
2. #2242 Quantile Lisa negative spatial autocorrelation; add more check to bivariate and co-location join count

GeoDa 1.16.0.12

Download version 1.16.0.12: https://geodacenter.github.io/download.html

bugfixes and some enhancement:

1. • Variable name contains "%" will crash LISA maps [Windows only] bug
2. • Heat Map behaves differently on Windows bug
3. • add Median spatial lag to the Spatial Lag tab in the Calculator enhancement
4. • [Distance Scatter Plot] Update LOESS setup UI enhancement
5. • Missing [OK] button in 'Spatial Assign' and 'Spatial Count' on Windows only bug
6. • bug: Save Spanning Tree does not work in REDCAP bug
7. • Change Map Transparency for basemap impacts the highlighting transparency enhancement
8. • bug: regression report with undefined/empty values

GeoDa 1.16

Download: https://geodacenter.github.io/download.html

Many bug fixes for 1.14 and

New features:

GIS features

1. Reprojection (specify projection when save)

2. Minimum Spanning Tree (MST)

3. Spatial Dissolve

4. Multi-Layer Support (Linked Multi-Layers, Automatic reprojection)

5. Spatial Assign/Spatial Count/ Spatial Join (multi-variables)

6. Heat map

Spatial Weights

7. Create weights from variables

8. Make (mutual) Symmetric weights

Local Spatial Autocorrelation

9. Median Local Moran

10. Univariate Quantile LISA

11. Multivariate Quantile LISA

12. Local Neighbor Match Test

Map/Plots/Table

13. Conditional Box plot

14. Distance Scatter plot with loess

15. Render numeric labels on map

16. Data transform: Standarize(MAD)/ Range Adjust/ Range Standardize

Dimension Reduction Methods

17. Multidimensional Scaling (MDS) 2D/3D, SMACOF

18. Spatial weights from MDS scatter plot

19. t-SNE (animation)

Cluster Analysis

20. K Medoids (FastPAM, FastCLARA, FastCLARANS)

21. Spectral Clustering with large scale sparse eigenvalue solver (k-nn, mutual k-nn, gaussian)

22. DBScan & DBScan*

23. Hierarchical DBScan (with linking Condensed Tree graph)

24. Spatial Constrained Hierarchical Clustering (SCHC)

25. AZP (greedy, simulated annealing, tabu search)

26. Skater/Redcap with max-p-regions solver

Internationalization

27. Russian

GeoDa 1.14.0.2

Note: add an emergent release 1.14.0.4 for macOS https://github.com/GeoDaCenter/geoda/releases/download/1.14.0.2/GeoDa1.14.0.4-Installer.dmg
This release includes a fix for an issue that GeoDa can't drag-n-drop to open a ESRI shapefile on macOS Catalina (10.15)

1.14.0.2 Release Notes:

1. Fix an issue of specifying CRS when exporting:
   When there is no projection information of the current dataset (e.g. no .prj file, or create points from a CSV table), specifying CRS when exporting to a vector data format doesn't generate a .prj file or related projection information.

2. Add Russian language support

3. Enhancement: some Chinese translations

4. Update Ubuntu build scripts for version Disco Dingo

5. Enhancement: allow resizing the Preference dialog, for low screen resolutions (e.g. 1024x768)