[BUG] set viz defaults for LineStrings in lisa_cluster (#140)

* [BUG] add check for `geom_type` in `esda.lisa_cluster`

* different plotting defaults dependent on geom_type

* [TST] add test for LineString adaption in `lisa_cluster`

* [ENH] test for Polygon and MultiPolygon

Co-authored-by: Martin Fleischmann <[email protected]>

* [BUG] check entire gdf for Polygons

* .shape --> .shp

* fix linestring test

Co-authored-by: Martin Fleischmann <[email protected]>
Co-authored-by: James Gaboardi <[email protected]>

splot/_viz_esda_mpl.py

@@ -930,11 +930,18 @@ def lisa_cluster(moran_loc, gdf, p=0.05, ax=None,
         fig, ax = plt.subplots(1, figsize=figsize)
     else:
         fig = ax.get_figure()
-
-    gdf.assign(cl=labels).plot(column='cl', categorical=True,
-                               k=2, cmap=hmap, linewidth=0.1, ax=ax,
-                               edgecolor='white', legend=legend,
-                               legend_kwds=legend_kwds, **kwargs)
+
+    # check for Polygon, else no edgecolor
+    if gdf.geom_type.isin(['Polygon', 'MultiPolygon']).any():
+        gdf.assign(cl=labels).plot(column='cl', categorical=True,
+                                   k=2, cmap=hmap, linewidth=0.1, ax=ax,
+                                   edgecolor='white', legend=legend,
+                                   legend_kwds=legend_kwds, **kwargs)
+    else:
+        gdf.assign(cl=labels).plot(column='cl', categorical=True,
+                                   k=2, cmap=hmap, linewidth=1.5, ax=ax,
+                                   legend=legend,
+                                   legend_kwds=legend_kwds, **kwargs)
     ax.set_axis_off()
     ax.set_aspect('equal')
     return fig, ax
@@ -1355,4 +1362,4 @@ def moran_facet(moran_matrix, figsize=(16,12),
 
             axarr[row, col].set_title('') 
     plt.tight_layout()
-    return fig, axarr
+    return fig, axarr

splot/tests/test_viz_esda_mpl.py

@@ -22,12 +22,27 @@
                                  _moran_bv_scatterplot,
                                  _moran_loc_bv_scatterplot)
 
+
 def _test_data():
     guerry = examples.load_example('Guerry')
     link_to_data = guerry.get_path('guerry.shp')
     gdf = gpd.read_file(link_to_data)
     return gdf
 
+
+def _test_data_columbus():
+    columbus = examples.load_example('Columbus')
+    link_to_data = columbus.get_path('columbus.shp')
+    df = gpd.read_file(link_to_data)
+    return df
+
+
+def _test_LineString():
+    link_to_data = examples.get_path('streets.shp')
+    gdf = gpd.read_file(link_to_data)
+    return gdf
+
+
 def test_moran_scatterplot():
     gdf = _test_data()
     x = gdf['Suicids'].values
@@ -160,9 +175,7 @@ def test_plot_moran_bv():
 
 
 def test_moran_loc_scatterplot():
-    columbus = examples.load_example('Columbus')
-    link_to_data = columbus.get_path('columbus.shp')
-    df = gpd.read_file(link_to_data)
+    df = _test_data_columbus()
 
     x = df['INC'].values
     y = df['HOVAL'].values
@@ -197,31 +210,33 @@ def test_moran_loc_scatterplot():
                  scatter_kwds=dict(c='#4393c3'))
 
 
-def test_lisa_cluster():
-    columbus = examples.load_example('Columbus')
-    link_to_data = columbus.get_path('columbus.shp')
-    df = gpd.read_file(link_to_data)
-
-    y = df['HOVAL'].values
-    w = Queen.from_dataframe(df)
+def _test_calc_moran_loc(gdf, var='HOVAL'):
+    y = gdf[var].values
+    w = Queen.from_dataframe(gdf)
     w.transform = 'r'
 
     moran_loc = Moran_Local(y, w)
+    return moran_loc
+
+
+def test_lisa_cluster():
+    df = _test_data_columbus()
+    moran_loc = _test_calc_moran_loc(df)
 
     fig, _ = lisa_cluster(moran_loc, df)
     plt.close(fig)
 
+    # test LineStrings
+    df_line = _test_LineString()
+    moran_loc = _test_calc_moran_loc(df_line, var="Length")
 
-def test_plot_local_autocorrelation():
-    columbus = examples.load_example('Columbus')
-    link_to_data = columbus.get_path('columbus.shp')
-    df = gpd.read_file(link_to_data)
+    fig, _ = lisa_cluster(moran_loc, df_line)
+    plt.close(fig)
 
-    y = df['HOVAL'].values
-    w = Queen.from_dataframe(df)
-    w.transform = 'r'
 
-    moran_loc = Moran_Local(y, w)
+def test_plot_local_autocorrelation():
+    df = _test_data_columbus()
+    moran_loc = _test_calc_moran_loc(df)
 
     fig, _ = plot_local_autocorrelation(moran_loc, df, 'HOVAL', p=0.05)
     plt.close(fig)
@@ -232,12 +247,13 @@ def test_plot_local_autocorrelation():
                                         aspect_equal=False,
                                         mask=['1', '2', '3'], quadrant=1)
     plt.close(fig)
-    
+
     # also test with quadrant and mask
     raises(ValueError, plot_local_autocorrelation, moran_loc,
                   df, 'HOVAL', p=0.05, region_column='POLYID',
                  mask=['100', '200', '300'], quadrant=1)
 
+
 def test_moran_loc_bv_scatterplot():
     gdf = _test_data()
     x = gdf['Suicids'].values