Merge pull request #188 from eEcoLiDAR/development

Development

Author: fnattino

laserchicken/feature_extractor/eigenvals_feature_extractor.py

@@ -60,7 +60,7 @@ def _reorder_vectors(eigen_vectors, new_vector_indices):
         # and reshape and even repeat some indices to get the behavior I'm looking for.
         vects_t = eigen_vectors.transpose([0, 2, 1])  # Eigen vectors used as column vectors. Making row vectors here.
         flattened_vects_t = vects_t.reshape(-1, 3 * 3)  # Flatten the (eigen) vector dimension
-        vect_indices = np.zeros_like(flattened_vects_t, dtype=np.int) + [0, 1, 2, 0, 1, 2, 0, 1, 2]  # 0,1,2 for x,y,z
+        vect_indices = np.zeros_like(flattened_vects_t, dtype=int) + [0, 1, 2, 0, 1, 2, 0, 1, 2]  # 0,1,2 for x,y,z
         vect_indices[:, :3] += new_vector_indices[:, 0:1] * 3  # Because x,y,z, indices have to be increased by 3.
         vect_indices[:, 3:6] += new_vector_indices[:, 1:2] * 3
         vect_indices[:, 6:9] += new_vector_indices[:, 2:3] * 3

laserchicken/feature_extractor/feature_extraction.py

@@ -56,7 +56,7 @@ def compute_features(env_point_cloud, neighborhoods, target_point_cloud, feature
     for feature_name in extended_features:
         target_point_cloud[point][feature_name] = {"type": 'float64',
                                                    "data": np.zeros_like(target_point_cloud[point]['x']['data'],
-                                                                         dtype=np.float64)}
+                                                                         dtype=float)}
 
     if provenance in env_point_cloud:
         utils.add_metadata(target_point_cloud, sys.modules[__name__],
@@ -87,7 +87,7 @@ def _get_point_cloud_size(target_point_cloud):
 
 
 def _calculate_number_of_chunks(chunk_size, n_targets):
-    return int(np.math.ceil(n_targets / chunk_size))
+    return int(np.ceil(n_targets / chunk_size))
 
 
 def _compute_features_for_chunk(features_to_do, env_point_cloud, current_neighborhoods, target_point_cloud,
@@ -124,7 +124,7 @@ def _add_features_from_single_extractor(extractor, env_point_cloud, current_neig
                                      target_indices, volume)
 
     n_targets = len(target_indices)
-    feature_values = [np.empty(n_targets, dtype=np.float64) for _ in range(n_features)]
+    feature_values = [np.empty(n_targets, dtype=float) for _ in range(n_features)]
     if n_features > 1:
         for i in range(n_features):
             feature_values[i] = point_values[i]

laserchicken/filter.py

@@ -5,7 +5,7 @@
 import shapefile
 import shapely
 import sys
-from shapely.geometry import Point
+
 from shapely.errors import WKTReadingError
 from shapely.wkt import loads
 from shapely.geometry import box
@@ -97,11 +97,11 @@ def _check_valid_arguments(attribute, point_cloud):
 
 def select_polygon(point_cloud, polygon_string, read_from_file=False, return_mask=False):
     """
-    Return the selection of the input point cloud that contains only points within a given polygon.
+    Return the selection of the input point cloud that contains only points within the given polygon(s).
 
     :param point_cloud: Input point cloud
-    :param polygon_string: Polygon, either defined in a WKT string or in a file (WKT and ESRI formats supported)
-    :param read_from_file: if true, polygon is expected to be the name of the file where the polygon is defined
+    :param polygon_string: polygon(s), either defined in a WKT string or in a file (WKT and ESRI formats supported)
+    :param read_from_file: if true, polygon is expected to be the name of the file where the geometry is defined
     :param return_mask: if true, return a mask of selected points, rather than point cloud
     :return:
     """
@@ -121,12 +121,12 @@ def select_polygon(point_cloud, polygon_string, read_from_file=False, return_mas
     elif isinstance(polygon,shapely.geometry.multipolygon.MultiPolygon):
         points_in = []
         count=1
-        for poly in polygon:
-            if not(count%200) or count==len(polygon):
-                print('Checking polygon {}/{}...'.format(count, len(polygon)))
+        for poly in polygon.geoms:
+            if not(count%200) or count==len(polygon.geoms):
+                print('Checking polygon {}/{}...'.format(count, len(polygon.geoms)))
             points_in.extend(_contains(point_cloud, poly))
             count=count+1
-        print('{} points found in {} polygons.'.format(len(points_in), len(polygon)))
+        print('{} points found in {} polygons.'.format(len(points_in), len(polygon.geoms)))
     else:
         raise ValueError('It is not a Polygon or Multipolygon.')
 

laserchicken/test_feature_extractor/test_extract_features.py

@@ -38,7 +38,7 @@ def test_extract_multiple_features_ends_up_in_pc():
     @staticmethod
     def test_extract_can_overwrite():
         target = test_tools.ComplexTestData().get_point_cloud()
-        target[keys.point]['test1_a'] = {"type": np.float64, "data": [0.9, 0.99, 0.999, 0.9999]}
+        target[keys.point]['test1_a'] = {"type": float, "data": [0.9, 0.99, 0.999, 0.9999]}
         feature_names = ['test3_a', 'test1_a']
         target = _compute_features(target, feature_names)
         assert all(target[keys.point]['test1_a']['data'] == 0.5 * target[keys.point]['z']['data'])

laserchicken/test_filter.py

@@ -429,8 +429,8 @@ def test_shp_polygons_contains():
         x = pc_out[point]['x']['data']
         y = pc_out[point]['y']['data']
         # Seemingly redundant 'astype' call: since pandas 0.24 Dataframe() doesn't enforce the given dtype as before
-        df_out = pd.DataFrame({'x': x, 'y': y}, dtype=np.int32).astype(dtype=np.int32)
-        df = pd.read_csv("testdata/ahn2_polygon.out", sep=',', header=0, index_col=0, dtype=np.int32)
+        df_out = pd.DataFrame({'x': x, 'y': y}).astype(int)
+        df = pd.read_csv("testdata/ahn2_polygon.out", sep=',', header=0, index_col=0, dtype=int)
         assert (pd.DataFrame.equals(df, df_out))
 
     @staticmethod

laserchicken/test_tools.py

@@ -8,9 +8,9 @@
 
 def generate_tiny_test_point_cloud():
     """Generate a simple but valid point cloud with 3 points."""
-    pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3], dtype=np.float64)},
-                       'y': {'type': 'double', 'data': np.array([2, 3, 4], dtype=np.float64)},
-                       'z': {'type': 'double', 'data': np.array([3, 4, 5], dtype=np.float64)}}}
+    pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3], dtype=float)},
+                       'y': {'type': 'double', 'data': np.array([2, 3, 4], dtype=float)},
+                       'z': {'type': 'double', 'data': np.array([3, 4, 5], dtype=float)}}}
     return pc
 
 
@@ -21,9 +21,9 @@ class SimpleTestData(object):
     def get_point_cloud():
         """Get the point cloud data."""
         # This simple_test_point cloud and the simple_test_header should be in sync. Some tests depend on it.
-        pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3], dtype=np.float64)},
-                           'y': {'type': 'double', 'data': np.array([20, 30, 40], dtype=np.float64)},
-                           'z': {'type': 'double', 'data': np.array([300, 400, 500], dtype=np.float64)}}}
+        pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3], dtype=float)},
+                           'y': {'type': 'double', 'data': np.array([20, 30, 40], dtype=float)},
+                           'z': {'type': 'double', 'data': np.array([300, 400, 500], dtype=float)}}}
         return pc
 
     @staticmethod
@@ -64,10 +64,10 @@ class ComplexTestData(object):
     def get_point_cloud():
         """Get the point cloud data."""
         # This complex_test_point cloud and the complex_test_header should be in sync. Some tests depend on it.
-        pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3, 4, 5], dtype=np.float)},
-                           'y': {'type': 'double', 'data': np.array([2, 3, 4, 5, 6], dtype=np.float)},
-                           'z': {'type': 'double', 'data': np.array([3, 4, 5, 6, 7], dtype=np.float)},
-                           'return': {'type': 'int', 'data': np.array([1, 1, 2, 2, 1], dtype=np.int32)}
+        pc = {keys.point: {'x': {'type': 'double', 'data': np.array([1, 2, 3, 4, 5], dtype=float)},
+                           'y': {'type': 'double', 'data': np.array([2, 3, 4, 5, 6], dtype=float)},
+                           'z': {'type': 'double', 'data': np.array([3, 4, 5, 6, 7], dtype=float)},
+                           'return': {'type': 'int', 'data': np.array([1, 1, 2, 2, 1], dtype=int)}
                            },
               keys.point_cloud: {'offset': {'type': 'double', 'data': 12.1}},
               keys.provenance: [{"module": "filter", "time": str(dt.datetime(2018, 1, 18, 16, 1, 0))},
@@ -131,14 +131,14 @@ def create_point_cloud(x, y, z, normalized_z=None):
     :param normalized_z: optional normalized z attribute values
     :return: point cloud object
     """
-    point_cloud = {keys.point: {'x': {'type': 'double', 'data': np.array(x, dtype=np.float)},
-                                'y': {'type': 'double', 'data': np.array(y, dtype=np.float)},
-                                'z': {'type': 'double', 'data': np.array(z, dtype=np.float)}},
+    point_cloud = {keys.point: {'x': {'type': 'double', 'data': np.array(x, dtype=float)},
+                                'y': {'type': 'double', 'data': np.array(y, dtype=float)},
+                                'z': {'type': 'double', 'data': np.array(z, dtype=float)}},
                    keys.point_cloud: {},
                    keys.provenance: [{'time': (dt.datetime(2018, 1, 18, 16, 1, 0)), 'module': 'filter'}]}
     if normalized_z is not None:
         point_cloud[keys.point][keys.normalized_height] = {'type': 'double',
-                                                           'data': np.array(normalized_z, dtype=np.float)}
+                                                           'data': np.array(normalized_z, dtype=float)}
     return point_cloud
 
 

requirements.txt

@@ -4,7 +4,7 @@ pytest
 mock
 plyfile
 python-dateutil
-shapely
+shapely>=2
 PyShp
 pandas
 click