Fixed relative import issue for testing

spacv/base_classes.py

@@ -1,7 +1,7 @@
 import numpy as np
 import geopandas as gpd
-from .utils import convert_geoseries, convert_geodataframe
 from sklearn.model_selection import BaseCrossValidator
+from .utils import convert_geoseries, convert_geodataframe
 
 class BaseSpatialCV(BaseCrossValidator):
     """
@@ -15,6 +15,7 @@ def __init__(
     def split(self, XYs, y=None, groups=None):
         XYs = convert_geoseries(XYs).reset_index(drop=True)
         minx, miny, maxx, maxy = XYs.total_bounds
+
         buffer_radius = self.buffer_radius
         if buffer_radius > maxx-minx or buffer_radius > maxy-miny:
             raise ValueError(

spacv/grid_builder.py

@@ -5,8 +5,6 @@
 from sklearn.neighbors import BallTree
 from .utils import convert_geodataframe, geometry_to_2d, convert_numpy
 
-
-
 def construct_blocks(XYs, tiles_x, tiles_y, method='unique', shape='square', 
                      direction='diagonal', data=None, n_groups=5, n_sims=10, 
                      distance_metric='euclidean'):

spacv/spacv.py

@@ -126,13 +126,12 @@ def _iter_test_indices(self, XYs):
                 )
             )
         sloo = len(XYs) == self.n_splits
-        lattice = True
-            
+        lattice = any(XYs.geom_type == 'Polygon') or any(XYs.geom_type == 'MultiPolygon')
+
         # If K = N, SLOO
         if sloo:
             num_samples = XYs.shape[0]
             indices_from_folds = np.arange(num_samples)
-
         else:
             # Partion XYs space into folds
             XYs_to_2d = geometry_to_2d(XYs)
@@ -152,10 +151,10 @@ def _iter_test_indices(self, XYs):
                 fold_polygon = XYs.loc[test_indices].buffer(self.buffer_radius)
             elif lattice:
                 test_indices = np.array(fold_indices)
-                fold_polygon = XYs.loc[test_indices].unary_union.buffer(self.buffer_radius)
-            else:
+                fold_polygon = XYs.loc[test_indices].unary_union.buffer(self.buffer_radius) 
+            else: # skcv
                 test_indices = np.array(fold_indices)
-                fold_polygon = XYs.loc[test_indices].unary_union.convex_hull.buffer(self.radius)
+                fold_polygon = XYs.loc[test_indices].unary_union.convex_hull.buffer(self.buffer_radius)
 
             test_indices, train_exclude = \
                 super()._remove_buffered_indices(XYs, test_indices, 
@@ -185,8 +184,7 @@ def __init__(
             raise ValueError("Number of repetitions must be of Integral type.")
         if n_repeats <= 0:
             raise ValueError("Number of repetitions must be greater than 0.")
-        cv = SKCV
-        self.cv = cv
+        self.cv = SKCV
         self.n_repeats = n_repeats
         self.n_splits = n_splits
         self.kwargs = kwargs
@@ -225,7 +223,6 @@ def _iter_test_indices(self, XYs):
         grid = self.custom_polygons
         grid['grid_id'] = grid.index
         grid_ids = np.unique(grid.grid_id)
-
         XYs = assign_pt_to_grid(XYs, grid, self.distance_metric)
 
         # Yield test indices and optionally training indices within buffer

spacv/tests/test_cv.py

@@ -1,5 +1,3 @@
-import sys, os
-sys.path.append(os.path.abspath("../.."))
 import unittest
 import numpy as np
 import geopandas as gpd
@@ -11,7 +9,7 @@ def setUp(self):
         x = np.random.randint(0, 3000, 30)
         y = np.random.randint(0, 3000, 30)
 
-        self.gdf = gpd.GeoSeries(
+        self.gdf = gpd.GeoDataFrame(
             {'geometry' : gpd.points_from_xy(x,y)}
         )
 
@@ -25,16 +23,15 @@ def setUp(self):
 
     def test_skcv(self):
         np.random.seed(10)
-        scv = spacv.SKCV(folds = 3, buffer_radius = 450, random_state=123)
-        self.assertEqual(scv.folds, 3)
+        scv = spacv.SKCV(n_splits = 3, buffer_radius = 450, random_state=123)
+        self.assertEqual(scv.n_splits, 3)
         self.assertEqual(scv.buffer_radius, 450)
         self.assertEqual(scv.random_state, 123)
 
         fold_train, fold_test = [], []
         for train, test in scv.split(self.gdf):
             fold_train.append(train)
             fold_test.append(test)
-            print(test)
 
         scv_fold_one = fold_test[0]
         scv_fold_two = fold_test[1]

spacv/tests/test_grids.py

@@ -1,5 +1,3 @@
-import sys, os
-sys.path.append(os.path.abspath("../.."))
 import unittest
 import numpy as np
 import geopandas as gpd
@@ -30,7 +28,7 @@ def setUp(self):
         pass
 
     def test_systematic_grid(self):
-
+        pass
 
 suite = unittest.TestSuite()
 test_classes = [SquareUniqueGrid_Tester]

spacv/tests/test_viz.py

@@ -0,0 +1,3 @@
+import matplotlib
+
+matplotlib.use("agg")  # To prevent plots from using display

spacv/utils.py

@@ -10,7 +10,11 @@ def convert_geoseries(XYs):
     if isinstance(XYs, gpd.GeoDataFrame):
         XYs = XYs.geometry
     if isinstance(XYs, np.ndarray):
-        XYs= gpd.GeoSeries( gpd.points_from_xy(XYs) )
+        XYs = gpd.GeoSeries( gpd.points_from_xy(XYs) )
+
+    if isinstance(XYs, gpd.GeoDataFrame):
+        if any(XYs.geom_type == 'Polygon') or any(XYs.geom_type == 'MultiPolygon'):
+            XYs = XYs.geometry.centroid        
     return XYs
 
 def convert_geodataframe(XYs):
@@ -19,7 +23,7 @@ def convert_geodataframe(XYs):
     if isinstance(XYs, np.ndarray):
         XYs = gpd.GeoDataFrame({'geometry': gpd.points_from_xy(XYs) })
     if isinstance(XYs, (Point, Polygon, LineString, MultiPolygon)):
-        XYs = gpd.GeoDataFrame({'geometry': [XYs] })
+        XYs = gpd.GeoDataFrame({'geometry': [XYs] })        
     return XYs
 
 def convert_numpy(X):