Python numpy.ctypeslib.ndpointer() Examples
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Example #1
Source File: test_ctypeslib.py From coffeegrindsize with MIT License | 6 votes |
def test_return(self, dt): """ Test that return values are coerced to arrays """ arr = np.zeros((2, 3), dt) ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) # check that the arrays are equivalent views on the same data arr2 = c_forward_pointer(arr) assert_equal(arr2.dtype, arr.dtype) assert_equal(arr2.shape, arr.shape) assert_equal( arr2.__array_interface__['data'], arr.__array_interface__['data'] )
Example #2
Source File: triangulation.py From s2p with GNU Affero General Public License v3.0 | 6 votes |
def remove_isolated_3d_points(xyz, r, p, n, q=1): """ Discard (in place) isolated (groups of) points in a gridded set of 3D points Discarded points satisfy the following conditions: - they have less than n 3D neighbors in a ball of radius r units (ex: meters); - all their neighboring points of the grid in a square window of size 2q+1 that are closer than r units are also discarded. Args: xyz (array): 3D array of shape (h, w, 3) where each pixel contains the UTM easting, northing, and altitude of a 3D point. r (float): filtering radius, in the unit of the CRS (ex: meters) p (int): filering window radius, in pixels (square window of size 2p+1) n (int): filtering threshold, in number of points q (int): 2nd filtering window radius, in pixels (square of size 2q+1) """ h, w, d = xyz.shape assert d == 3, 'expecting a 3-channels image with shape (h, w, 3)' lib.remove_isolated_3d_points.argtypes = ( ndpointer(dtype=c_float, shape=(h, w, 3)), c_int, c_int, c_float, c_int, c_int, c_int) lib.remove_isolated_3d_points(np.ascontiguousarray(xyz), w, h, r, p, n, q)
Example #3
Source File: test_ctypeslib.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
def test_return(self, dt): """ Test that return values are coerced to arrays """ arr = np.zeros((2, 3), dt) ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) # check that the arrays are equivalent views on the same data arr2 = c_forward_pointer(arr) assert_equal(arr2.dtype, arr.dtype) assert_equal(arr2.shape, arr.shape) assert_equal( arr2.__array_interface__['data'], arr.__array_interface__['data'] )
Example #4
Source File: test_ctypeslib.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
def test_return(self, dt): """ Test that return values are coerced to arrays """ arr = np.zeros((2, 3), dt) ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) # check that the arrays are equivalent views on the same data arr2 = c_forward_pointer(arr) assert_equal(arr2.dtype, arr.dtype) assert_equal(arr2.shape, arr.shape) assert_equal( arr2.__array_interface__['data'], arr.__array_interface__['data'] )
Example #5
Source File: mpi_kmeans.py From opensurfaces with MIT License | 6 votes |
def kmeans(X, nclst, maxiter=0, numruns=1): """Wrapper for Peter Gehlers accelerated MPI-Kmeans routine.""" mpikmeanslib = N.ctypeslib.load_library("libmpikmeans.so", ".") mpikmeanslib.kmeans.restype = c_double mpikmeanslib.kmeans.argtypes = [ndpointer(dtype=c_double, ndim=1, flags='C_CONTIGUOUS'), \ ndpointer(dtype=c_double, ndim=1, flags='C_CONTIGUOUS'), \ ndpointer(dtype=c_uint, ndim=1, flags='C_CONTIGUOUS'), \ c_uint, c_uint, c_uint, c_uint, c_uint ] npts,dim = X.shape assignments=empty( (npts), c_uint ) bestSSE=N.Inf bestassignments=empty( (npts), c_uint) Xvec = array( reshape( X, (-1,) ), c_double ) permutation = N.random.permutation( range(npts) ) # randomize order of points CX = array(X[permutation[:nclst],:], c_double).flatten() SSE = mpikmeanslib.kmeans( CX, Xvec, assignments, dim, npts, min(nclst, npts), maxiter, numruns) return reshape(CX, (nclst,dim)), SSE, (assignments+1)
Example #6
Source File: test_ctypeslib.py From recruit with Apache License 2.0 | 6 votes |
def test_return(self, dt): """ Test that return values are coerced to arrays """ arr = np.zeros((2, 3), dt) ptr_type = ndpointer(shape=arr.shape, dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) # check that the arrays are equivalent views on the same data arr2 = c_forward_pointer(arr) assert_equal(arr2.dtype, arr.dtype) assert_equal(arr2.shape, arr.shape) assert_equal( arr2.__array_interface__['data'], arr.__array_interface__['data'] )
Example #7
Source File: test_ctypeslib.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_ndim(self): p = ndpointer(ndim=0) self.assertTrue(p.from_param(np.array(1))) self.assertRaises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) self.assertRaises(TypeError, p.from_param, np.array(1)) self.assertTrue(p.from_param(np.array([1]))) p = ndpointer(ndim=2) self.assertTrue(p.from_param(np.array([[1]])))
Example #8
Source File: test_ctypeslib.py From recruit with Apache License 2.0 | 5 votes |
def test_ndim(self): p = ndpointer(ndim=0) assert_(p.from_param(np.array(1))) assert_raises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) assert_raises(TypeError, p.from_param, np.array(1)) assert_(p.from_param(np.array([1]))) p = ndpointer(ndim=2) assert_(p.from_param(np.array([[1]])))
Example #9
Source File: test_ctypeslib.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_shape(self): p = ndpointer(shape=(1, 2)) self.assertTrue(p.from_param(np.array([[1, 2]]))) self.assertRaises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) self.assertTrue(p.from_param(np.array(1)))
Example #10
Source File: test_ctypeslib.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_flags(self): x = np.array([[1, 2], [3, 4]], order='F') p = ndpointer(flags='FORTRAN') self.assertTrue(p.from_param(x)) p = ndpointer(flags='CONTIGUOUS') self.assertRaises(TypeError, p.from_param, x) p = ndpointer(flags=x.flags.num) self.assertTrue(p.from_param(x)) self.assertRaises(TypeError, p.from_param, np.array([[1, 2], [3, 4]]))
Example #11
Source File: test_ctypeslib.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_cache(self): a1 = ndpointer(dtype=np.float64) a2 = ndpointer(dtype=np.float64) self.assertEqual(a1, a2)
Example #12
Source File: test_ctypeslib.py From ImageFusion with MIT License | 5 votes |
def test_dtype(self): dt = np.intc p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.array([1], dt))) dt = '<i4' p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.array([1], dt))) dt = np.dtype('>i4') p = ndpointer(dtype=dt) p.from_param(np.array([1], dt)) self.assertRaises(TypeError, p.from_param, np.array([1], dt.newbyteorder('swap'))) dtnames = ['x', 'y'] dtformats = [np.intc, np.float64] dtdescr = {'names' : dtnames, 'formats' : dtformats} dt = np.dtype(dtdescr) p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.zeros((10,), dt))) samedt = np.dtype(dtdescr) p = ndpointer(dtype=samedt) self.assertTrue(p.from_param(np.zeros((10,), dt))) dt2 = np.dtype(dtdescr, align=True) if dt.itemsize != dt2.itemsize: self.assertRaises(TypeError, p.from_param, np.zeros((10,), dt2)) else: self.assertTrue(p.from_param(np.zeros((10,), dt2)))
Example #13
Source File: test_ctypeslib.py From coffeegrindsize with MIT License | 5 votes |
def test_shape(self): p = ndpointer(shape=(1, 2)) assert_(p.from_param(np.array([[1, 2]]))) assert_raises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) assert_(p.from_param(np.array(1)))
Example #14
Source File: triangulation.py From s2p with GNU Affero General Public License v3.0 | 5 votes |
def count_3d_neighbors(xyz, r, p): """ Count 3D neighbors of a gridded set of 3D points. Args: xyz (array): 3D array of shape (h, w, 3) where each pixel contains the UTM easting, northing, and altitude of a 3D point. r (float): filtering radius, in the unit of the CRS (ex: meters) p (int): the filering window has size 2p + 1, in pixels Returns: array of shape (h, w) with the count of the number of 3D points located less than r units from the current 3D point """ h, w, d = xyz.shape assert(d == 3) # define the argument types of the count_3d_neighbors function from disp_to_h.so lib.count_3d_neighbors.argtypes = (ndpointer(dtype=c_int, shape=(h, w)), ndpointer(dtype=c_float, shape=(h, w, 3)), c_int, c_int, c_float, c_int) # call the count_3d_neighbors function from disp_to_h.so out = np.zeros((h, w), dtype='int32') lib.count_3d_neighbors(out, np.ascontiguousarray(xyz), w, h, r, p) return out
Example #15
Source File: test_ctypeslib.py From recruit with Apache License 2.0 | 5 votes |
def test_shape(self): p = ndpointer(shape=(1, 2)) assert_(p.from_param(np.array([[1, 2]]))) assert_raises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) assert_(p.from_param(np.array(1)))
Example #16
Source File: test_ctypeslib.py From coffeegrindsize with MIT License | 5 votes |
def test_dtype(self): dt = np.intc p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = '<i4' p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = np.dtype('>i4') p = ndpointer(dtype=dt) p.from_param(np.array([1], dt)) assert_raises(TypeError, p.from_param, np.array([1], dt.newbyteorder('swap'))) dtnames = ['x', 'y'] dtformats = [np.intc, np.float64] dtdescr = {'names': dtnames, 'formats': dtformats} dt = np.dtype(dtdescr) p = ndpointer(dtype=dt) assert_(p.from_param(np.zeros((10,), dt))) samedt = np.dtype(dtdescr) p = ndpointer(dtype=samedt) assert_(p.from_param(np.zeros((10,), dt))) dt2 = np.dtype(dtdescr, align=True) if dt.itemsize != dt2.itemsize: assert_raises(TypeError, p.from_param, np.zeros((10,), dt2)) else: assert_(p.from_param(np.zeros((10,), dt2)))
Example #17
Source File: test_ctypeslib.py From coffeegrindsize with MIT License | 5 votes |
def test_ndim(self): p = ndpointer(ndim=0) assert_(p.from_param(np.array(1))) assert_raises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) assert_raises(TypeError, p.from_param, np.array(1)) assert_(p.from_param(np.array([1]))) p = ndpointer(ndim=2) assert_(p.from_param(np.array([[1]])))
Example #18
Source File: test_ctypeslib.py From coffeegrindsize with MIT License | 5 votes |
def test_cache(self): assert_(ndpointer(dtype=np.float64) is ndpointer(dtype=np.float64)) # shapes are normalized assert_(ndpointer(shape=2) is ndpointer(shape=(2,))) # 1.12 <= v < 1.16 had a bug that made these fail assert_(ndpointer(shape=2) is not ndpointer(ndim=2)) assert_(ndpointer(ndim=2) is not ndpointer(shape=2))
Example #19
Source File: test_ctypeslib.py From mxnet-lambda with Apache License 2.0 | 5 votes |
def test_dtype(self): dt = np.intc p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.array([1], dt))) dt = '<i4' p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.array([1], dt))) dt = np.dtype('>i4') p = ndpointer(dtype=dt) p.from_param(np.array([1], dt)) self.assertRaises(TypeError, p.from_param, np.array([1], dt.newbyteorder('swap'))) dtnames = ['x', 'y'] dtformats = [np.intc, np.float64] dtdescr = {'names': dtnames, 'formats': dtformats} dt = np.dtype(dtdescr) p = ndpointer(dtype=dt) self.assertTrue(p.from_param(np.zeros((10,), dt))) samedt = np.dtype(dtdescr) p = ndpointer(dtype=samedt) self.assertTrue(p.from_param(np.zeros((10,), dt))) dt2 = np.dtype(dtdescr, align=True) if dt.itemsize != dt2.itemsize: self.assertRaises(TypeError, p.from_param, np.zeros((10,), dt2)) else: self.assertTrue(p.from_param(np.zeros((10,), dt2)))
Example #20
Source File: test_ctypeslib.py From pySINDy with MIT License | 5 votes |
def test_cache(self): a1 = ndpointer(dtype=np.float64) a2 = ndpointer(dtype=np.float64) assert_(a1 == a2)
Example #21
Source File: test_ctypeslib.py From pySINDy with MIT License | 5 votes |
def test_flags(self): x = np.array([[1, 2], [3, 4]], order='F') p = ndpointer(flags='FORTRAN') assert_(p.from_param(x)) p = ndpointer(flags='CONTIGUOUS') assert_raises(TypeError, p.from_param, x) p = ndpointer(flags=x.flags.num) assert_(p.from_param(x)) assert_raises(TypeError, p.from_param, np.array([[1, 2], [3, 4]]))
Example #22
Source File: test_ctypeslib.py From pySINDy with MIT License | 5 votes |
def test_shape(self): p = ndpointer(shape=(1, 2)) assert_(p.from_param(np.array([[1, 2]]))) assert_raises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) assert_(p.from_param(np.array(1)))
Example #23
Source File: test_ctypeslib.py From pySINDy with MIT License | 5 votes |
def test_ndim(self): p = ndpointer(ndim=0) assert_(p.from_param(np.array(1))) assert_raises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) assert_raises(TypeError, p.from_param, np.array(1)) assert_(p.from_param(np.array([1]))) p = ndpointer(ndim=2) assert_(p.from_param(np.array([[1]])))
Example #24
Source File: test_ctypeslib.py From pySINDy with MIT License | 5 votes |
def test_dtype(self): dt = np.intc p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = '<i4' p = ndpointer(dtype=dt) assert_(p.from_param(np.array([1], dt))) dt = np.dtype('>i4') p = ndpointer(dtype=dt) p.from_param(np.array([1], dt)) assert_raises(TypeError, p.from_param, np.array([1], dt.newbyteorder('swap'))) dtnames = ['x', 'y'] dtformats = [np.intc, np.float64] dtdescr = {'names': dtnames, 'formats': dtformats} dt = np.dtype(dtdescr) p = ndpointer(dtype=dt) assert_(p.from_param(np.zeros((10,), dt))) samedt = np.dtype(dtdescr) p = ndpointer(dtype=samedt) assert_(p.from_param(np.zeros((10,), dt))) dt2 = np.dtype(dtdescr, align=True) if dt.itemsize != dt2.itemsize: assert_raises(TypeError, p.from_param, np.zeros((10,), dt2)) else: assert_(p.from_param(np.zeros((10,), dt2)))
Example #25
Source File: test_ctypeslib.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def test_vague_return_value(self): """ Test that vague ndpointer return values do not promote to arrays """ arr = np.zeros((2, 3)) ptr_type = ndpointer(dtype=arr.dtype) c_forward_pointer.restype = ptr_type c_forward_pointer.argtypes = (ptr_type,) ret = c_forward_pointer(arr) assert_(isinstance(ret, ptr_type))
Example #26
Source File: test_ctypeslib.py From recruit with Apache License 2.0 | 5 votes |
def test_flags(self): x = np.array([[1, 2], [3, 4]], order='F') p = ndpointer(flags='FORTRAN') assert_(p.from_param(x)) p = ndpointer(flags='CONTIGUOUS') assert_raises(TypeError, p.from_param, x) p = ndpointer(flags=x.flags.num) assert_(p.from_param(x)) assert_raises(TypeError, p.from_param, np.array([[1, 2], [3, 4]]))
Example #27
Source File: test_ctypeslib.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def test_cache(self): assert_(ndpointer(dtype=np.float64) is ndpointer(dtype=np.float64)) # shapes are normalized assert_(ndpointer(shape=2) is ndpointer(shape=(2,))) # 1.12 <= v < 1.16 had a bug that made these fail assert_(ndpointer(shape=2) is not ndpointer(ndim=2)) assert_(ndpointer(ndim=2) is not ndpointer(shape=2))
Example #28
Source File: test_ctypeslib.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def test_flags(self): x = np.array([[1, 2], [3, 4]], order='F') p = ndpointer(flags='FORTRAN') assert_(p.from_param(x)) p = ndpointer(flags='CONTIGUOUS') assert_raises(TypeError, p.from_param, x) p = ndpointer(flags=x.flags.num) assert_(p.from_param(x)) assert_raises(TypeError, p.from_param, np.array([[1, 2], [3, 4]]))
Example #29
Source File: test_ctypeslib.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def test_shape(self): p = ndpointer(shape=(1, 2)) assert_(p.from_param(np.array([[1, 2]]))) assert_raises(TypeError, p.from_param, np.array([[1], [2]])) p = ndpointer(shape=()) assert_(p.from_param(np.array(1)))
Example #30
Source File: test_ctypeslib.py From ImageFusion with MIT License | 5 votes |
def test_ndim(self): p = ndpointer(ndim=0) self.assertTrue(p.from_param(np.array(1))) self.assertRaises(TypeError, p.from_param, np.array([1])) p = ndpointer(ndim=1) self.assertRaises(TypeError, p.from_param, np.array(1)) self.assertTrue(p.from_param(np.array([1]))) p = ndpointer(ndim=2) self.assertTrue(p.from_param(np.array([[1]])))