Deferred loading of NumPy and SciPy dependencies

src/compas/data/encoders.py

@@ -14,7 +14,7 @@
 from .exceptions import DecoderError
 
 IDictionary = None
-numpy_support = False
+numpy_support = None  # type: bool | None
 dotnet_support = False
 
 # We don't do this from `compas.IPY` to avoid circular imports
@@ -27,18 +27,15 @@
     except:  # noqa: E722
         pass
 
-try:
-    import numpy as np
-
-    try:
-        np_float = np.float_
-    except AttributeError:
-        np_float = np.float64
-
-    numpy_support = True
-except (ImportError, SyntaxError):
-    numpy_support = False
-
+def _is_numpy_available():  # type (...) -> bool
+    global numpy_support
+    if numpy_support is None:
+        try:
+            import numpy.version  # noqa: F401
+            numpy_support = True
+        except (ImportError, SyntaxError):
+            numpy_support = False
+    return numpy_support
 
 def cls_from_dtype(dtype, inheritance=None):  # type: (...) -> Type[Data]
     """Get the class object corresponding to a COMPAS data type specification.
@@ -144,7 +141,8 @@ def default(self, o):
         if hasattr(o, "__next__"):
             return list(o)
 
-        if numpy_support:
+        if _is_numpy_available():
+            import numpy as np
             if isinstance(o, np.ndarray):
                 return o.tolist()
             if isinstance(
@@ -164,7 +162,9 @@ def default(self, o):
                 ),  # type: ignore
             ):
                 return int(o)
-            if isinstance(o, (np_float, np.float16, np.float32, np.float64)):  # type: ignore
+            if hasattr(np, "float_") and isinstance(o, np.float_):  # type: ignore
+                return float(o)
+            if isinstance(o, (np.float16, np.float32, np.float64)):  # type: ignore
                 return float(o)
             if isinstance(o, np.bool_):
                 return bool(o)

src/compas/geometry/_core/transformations_numpy.py

@@ -1,10 +1,3 @@
-from numpy import asarray
-from numpy import hstack
-from numpy import ones
-from numpy import tile
-from numpy import vectorize
-from scipy.linalg import solve  # type: ignore
-
 from ._algebra import cross_vectors
 
 
@@ -31,6 +24,8 @@ def transform_points_numpy(points, T):
     >>> points_transformed = transform_points_numpy(points, T)
 
     """
+    from numpy import asarray
+
     T = asarray(T)
     points = homogenize_numpy(points, w=1.0)
     return dehomogenize_numpy(points.dot(T.T))
@@ -59,6 +54,8 @@ def transform_vectors_numpy(vectors, T):
     >>> vectors_transformed = transform_vectors_numpy(vectors, T)
 
     """
+    from numpy import asarray
+
     T = asarray(T)
     vectors = homogenize_numpy(vectors, w=0.0)
     return dehomogenize_numpy(vectors.dot(T.T))
@@ -87,6 +84,8 @@ def transform_frames_numpy(frames, T):
     >>> transformed_frames = transform_frames_numpy(frames, T)
 
     """
+    from numpy import asarray
+
     T = asarray(T)
     points_and_vectors = homogenize_and_flatten_frames_numpy(frames)
     return dehomogenize_and_unflatten_frames_numpy(points_and_vectors.dot(T.T))
@@ -117,6 +116,9 @@ def world_to_local_coordinates_numpy(frame, xyz):
     True
 
     """
+    from numpy import asarray
+    from scipy.linalg import solve  # type: ignore
+
     origin = frame[0]
     uvw = [frame[1], frame[2], cross_vectors(frame[1], frame[2])]
     uvw = asarray(uvw).T
@@ -154,6 +156,8 @@ def local_to_world_coordinates_numpy(frame, rst):
     True
 
     """
+    from numpy import asarray
+
     origin = frame[0]
     uvw = [frame[1], frame[2], cross_vectors(frame[1], frame[2])]
 
@@ -191,6 +195,10 @@ def homogenize_numpy(data, w=1.0):
     True
 
     """
+    from numpy import asarray
+    from numpy import hstack
+    from numpy import ones
+
     data = asarray(data)
     data = hstack((data, w * ones((data.shape[0], 1))))
     return data
@@ -216,6 +224,8 @@ def dehomogenize_numpy(data):
     True
 
     """
+    from numpy import asarray
+    from numpy import vectorize
 
     def func(a):
         return a if a else 1.0
@@ -248,6 +258,10 @@ def homogenize_and_flatten_frames_numpy(frames):
     True
 
     """
+    from numpy import asarray
+    from numpy import hstack
+    from numpy import tile
+
     n = len(frames)
     frames = asarray(frames).reshape(n * 3, 3)
     extend = tile(asarray([1, 0, 0]).reshape(3, 1), (n, 1))

src/compas/geometry/bbox_numpy.py

@@ -1,15 +1,3 @@
-from numpy import amax
-from numpy import amin
-from numpy import argmax
-from numpy import argmin
-from numpy import array
-from numpy import asarray
-from numpy import dot
-from numpy import sum
-from numpy import vstack
-from numpy import zeros
-from scipy.spatial import ConvexHull
-
 from compas.geometry import length_vector
 from compas.geometry import local_axes
 from compas.geometry import local_to_world_coordinates_numpy
@@ -78,6 +66,9 @@ def oriented_bounding_box_numpy(points, tol=None):
     True
 
     """
+    from numpy import asarray
+    from numpy import vstack
+
     points = asarray(points)
     n, dim = points.shape
 
@@ -156,6 +147,9 @@ def oriented_bounding_box_xy_numpy(points):
     :func:`compas.geometry.oriented_bounding_box_numpy`
 
     """
+    from numpy import asarray
+    from numpy import zeros
+
     points = asarray(points)
     n, dim = points.shape
 
@@ -192,6 +186,10 @@ def minimum_volume_box(points, return_size=False):
         XYZ coordinates of 8 points defining a box.
 
     """
+    from numpy import amax
+    from numpy import amin
+    from scipy.spatial import ConvexHull
+
     hull = ConvexHull(points)
     xyz = points[hull.vertices]
     boxes = []
@@ -248,6 +246,13 @@ def minimum_area_rectangle_xy(points, return_size=False):
         XYZ coordinates of 4 points defining a rectangle.
 
     """
+    from numpy import argmax
+    from numpy import argmin
+    from numpy import array
+    from numpy import dot
+    from numpy import sum
+    from scipy.spatial import ConvexHull
+
     boxes = []
 
     points = points[:, :2]

src/compas/geometry/bestfit_numpy.py

@@ -1,9 +1,3 @@
-from numpy import asarray
-from numpy import sqrt
-from numpy import zeros
-from numpy.linalg import lstsq
-from scipy.optimize import leastsq
-
 from compas.geometry import local_to_world_coordinates_numpy
 from compas.geometry import pca_numpy
 from compas.geometry import world_to_local_coordinates_numpy
@@ -155,6 +149,9 @@ def bestfit_circle_numpy(points):
            Available at: http://scipy-cookbook.readthedocs.io/items/Least_Squares_Circle.html.
 
     """
+    from numpy import sqrt
+    from scipy.optimize import leastsq
+
     o, uvw, _ = pca_numpy(points)
     frame = [o, uvw[0], uvw[1]]
 
@@ -237,6 +234,10 @@ def bestfit_sphere_numpy(points):
            Available at: https://jekel.me/2015/Least-Squares-Sphere-Fit/.
 
     """
+    from numpy import asarray
+    from numpy import sqrt
+    from numpy import zeros
+    from numpy.linalg import lstsq
 
     # Assemble the A matrix
     spX = asarray([p[0] for p in points])

src/compas/geometry/hull_numpy.py

@@ -1,7 +1,3 @@
-from numpy import asarray
-from scipy.spatial import ConvexHull
-
-
 def convex_hull_numpy(points):
     """Compute the convex hull of a set of points.
 
@@ -34,6 +30,9 @@ def convex_hull_numpy(points):
     with :func:`compas.topology.unify_cycles`.
 
     """
+    from numpy import asarray
+    from scipy.spatial import ConvexHull
+
     points = asarray(points)
     n, dim = points.shape
 
@@ -71,6 +70,9 @@ def convex_hull_xy_numpy(points):
     convex_hull_numpy
 
     """
+    from numpy import asarray
+    from scipy.spatial import ConvexHull
+
     points = asarray(points)
     n, dim = points.shape
 

src/compas/geometry/icp_numpy.py

@@ -1,19 +1,14 @@
-import numpy as np
-from numpy import argmin
-from numpy import asarray
-from numpy.linalg import det
-from numpy.linalg import multi_dot
-from scipy.linalg import norm
-from scipy.linalg import svd
-from scipy.spatial.distance import cdist
-
 from compas.geometry import pca_numpy
 from compas.geometry import transform_points_numpy
 from compas.linalg import normrow
 from compas.tolerance import TOL
 
 
 def bestfit_transform(A, B):
+    import numpy as np
+    from numpy.linalg import det
+    from scipy.linalg import svd
+
     n, m = A.shape
     Am = np.mean(A, axis=0)
     Bm = np.mean(B, axis=0)
@@ -76,6 +71,12 @@ def icp_numpy(source, target, tol=None, maxiter=100):
     The algorithm terminates when the alignment error is below a specified tolerance.
 
     """
+    from numpy import argmin
+    from numpy import asarray
+    from numpy.linalg import multi_dot
+    from scipy.linalg import norm
+    from scipy.spatial.distance import cdist
+
     from compas.geometry import Frame
     from compas.geometry import Transformation
 

src/compas/geometry/pca_numpy.py

@@ -1,7 +1,3 @@
-from numpy import asarray
-from scipy.linalg import svd  # type: ignore
-
-
 def pca_numpy(data):
     """Compute the principle components of a set of data points.
 
@@ -37,6 +33,9 @@ def pca_numpy(data):
     --------
     >>>
     """
+    from numpy import asarray
+    from scipy.linalg import svd  # type: ignore
+
     X = asarray(data)
     n, dim = X.shape
 

src/compas/geometry/trimesh_descent_numpy.py

@@ -1,5 +1,3 @@
-from numpy import asarray
-
 from .trimesh_gradient_numpy import trimesh_gradient_numpy
 
 
@@ -17,6 +15,8 @@ def trimesh_descent_numpy(M):
         The descent directions.
 
     """
+    from numpy import asarray
+
     vertices, faces = M
     V = asarray(vertices)
     F = asarray(faces)

src/compas/geometry/trimesh_gradient_numpy.py

@@ -1,6 +1,3 @@
-import numpy as np
-from scipy.sparse import coo_matrix  # type: ignore
-
 from compas.linalg import normalizerow
 from compas.linalg import normrow
 from compas.linalg import rot90
@@ -29,6 +26,9 @@ def trimesh_gradient_numpy(M, rtype="array"):
     and the coordinate difference vectors associated with the edges
 
     """
+    import numpy as np
+    from scipy.sparse import coo_matrix  # type: ignore
+
     V, F = M
     v = V.shape[0]
     f = F.shape[0]

src/compas/geometry/trimesh_matrices_numpy.py

@@ -1,10 +1,3 @@
-from numpy import asarray
-from numpy import bincount
-from numpy import cross
-from numpy import zeros
-from scipy.sparse import coo_matrix
-from scipy.sparse import spdiags
-
 from compas.geometry import cross_vectors
 from compas.geometry import dot_vectors
 from compas.geometry import length_vector
@@ -107,6 +100,8 @@ def trimesh_cotangent_laplacian_matrix(mesh, rtype="csr"):
         `Laplacian Mesh Optimization <https://igl.ethz.ch/projects/Laplacian-mesh-processing/Laplacian-mesh-optimization/lmo.pdf>`_.
 
     """
+    from scipy.sparse import coo_matrix
+
     vertex_index = mesh.vertex_index()
     n = mesh.number_of_vertices()
     data = []
@@ -173,6 +168,12 @@ def trimesh_vertexarea_matrix(mesh):
     [0.1666, 0.1666, 0.1666]
 
     """
+    from numpy import asarray
+    from numpy import bincount
+    from numpy import cross
+    from numpy import zeros
+    from scipy.sparse import spdiags
+
     vertex_index = mesh.vertex_index()
     xyz = asarray(mesh.vertices_attributes("xyz"), dtype=float)
     tris = asarray(