diff --git a/tfields/core.py b/tfields/core.py
index 2e6669768b76b0823d8cd0e4fdd59051e657e734..71b6dde0ef1230d174075643d7c1ca38ed6e8a10 100644
--- a/tfields/core.py
+++ b/tfields/core.py
@@ -1186,17 +1186,17 @@ class TensorFields(Tensors):
>>> assert masked.fields[0].equal([42, 10.5])
>>> assert masked.fields[1].equal([1, 3])
+ Iteration
+ >>> _ = [point for point in scalarField]
+
"""
item = super(TensorFields, self).__getitem__(index)
try:
if issubclass(type(item), TensorFields):
if isinstance(index, tuple):
index = index[0]
- if isinstance(index, slice):
+ if item.fields:
item.fields = [field.__getitem__(index) for field in item.fields]
- else:
- if item.fields:
- item.fields = [field.__getitem__(index) for field in item.fields]
except IndexError as err:
warnings.warn("Index error occured for field.__getitem__. Error "
"message: {err}".format(**locals()))
@@ -1330,6 +1330,86 @@ class TensorMaps(TensorFields):
obj.maps = maps
return obj
+ def __getitem__(self, index):
+ """
+ In addition to the usual, also slice fields
+
+ Examples:
+ >>> import tfields
+ >>> import numpy as np
+ >>> vectors = tfields.Tensors([[0, 0, 0], [0, 0, 1], [0, -1, 0],
+ ... [1, 1, 1], [-1, -1, -1]])
+ >>> maps=[tfields.TensorFields([[0, 1, 2], [0, 1, 3], [2, 3, 4]],
+ ... [[1, 2], [3, 4], [5, 6]]),
+ ... tfields.TensorFields([[0], [1], [2], [3], [4]])]
+ >>> mesh = tfields.TensorMaps(vectors,
+ ... [42, 21, 10.5, 1, 1],
+ ... [1, 2, 3, 3, 3],
+ ... maps=maps)
+
+ Slicing
+ >>> sliced = mesh[2:]
+ >>> assert isinstance(sliced, tfields.TensorMaps)
+ >>> assert isinstance(sliced.fields[0], tfields.Tensors)
+ >>> assert isinstance(sliced.maps[0], tfields.TensorFields)
+ >>> assert sliced.fields[0].equal([10.5, 1, 1])
+ >>> assert sliced.maps[0].equal([[0, 1, 2]])
+ >>> assert sliced.maps[0].fields[0].equal([[5, 6]])
+
+ Picking
+ >>> picked = mesh[1]
+ >>> assert np.array_equal(picked, [0, 0, 1])
+ >>> assert np.array_equal(picked.maps[0], np.empty((0, 3)))
+ >>> assert np.array_equal(picked.maps[1], [[0]])
+
+ Masking
+ >>> masked = mesh[[True, False, True, True, True]]
+ >>> assert masked.equal([[0, 0, 0], [0, -1, 0], [1, 1, 1], [-1, -1, -1]])
+ >>> assert masked.fields[0].equal([42, 10.5, 1, 1])
+ >>> assert masked.fields[1].equal([1, 3, 3, 3])
+ >>> assert masked.maps[0].equal([[1, 2, 3]])
+ >>> assert masked.maps[1].equal([[0], [1], [2], [3]])
+
+ Iteration
+ >>> _ = [vertex for vertex in mesh]
+
+ """
+ item = super(TensorMaps, self).__getitem__(index)
+ try:
+ if issubclass(type(item), TensorMaps):
+ item.maps = [mp.copy() for mp in item.maps]
+ if isinstance(index, tuple):
+ index = index[0]
+ if item.maps:
+ indices = np.array(range(len(self)))
+ keep_indices = indices[index]
+ if isinstance(keep_indices, int):
+ keep_indices = [keep_indices]
+ delete_indices = set(indices).difference(set(keep_indices))
+
+ # correct all maps that contain deleted indices
+ for mp_idx in range(len(self.maps)):
+ # build mask, where the map should be deleted
+ map_delete_mask = np.full((len(self.maps[mp_idx]),), False, dtype=bool)
+ for i, mp in enumerate(self.maps[mp_idx]):
+ for index in mp:
+ if index in delete_indices:
+ map_delete_mask[i] = True
+ break
+ map_mask = ~map_delete_mask
+
+ # build the correction counters
+ move_up_counter = np.zeros(self.maps[mp_idx].shape, dtype=int)
+ for p in delete_indices:
+ move_up_counter[self.maps[mp_idx] > p] -= 1
+
+ item.maps[mp_idx] = (self.maps[mp_idx] + move_up_counter)[map_mask]
+ except IndexError as err:
+ warnings.warn("Index error occured for field.__getitem__. Error "
+ "message: {err}".format(**locals()))
+
+ return item
+
@classmethod
def merged(cls, *objects, **kwargs):
if not all([isinstance(o, cls) for o in objects]):
@@ -1345,12 +1425,12 @@ class TensorMaps(TensorFields):
for map_field in o.maps:
map_field = map_field + cum_tensor_lengths[i]
try:
- map_index = dims.index(map_field.dim)
+ mp_idx = dims.index(map_field.dim)
except ValueError:
maps.append(map_field)
dims.append(map_field.dim)
else:
- maps[map_index] = TensorFields.merged(maps[map_index], map_field)
+ maps[mp_idx] = TensorFields.merged(maps[mp_idx], map_field)
kwargs['maps'] = maps
obj = super(TensorMaps, cls).merged(*objects, **kwargs)
@@ -1424,16 +1504,14 @@ class TensorMaps(TensorFields):
... [3,3,3], [4,4,4], [5,6,7]],
... maps=[mp1, mp2])
- # >>> c = tm.cleaned()
- # >>> assert c.equal([[0., 0., 0.],
- # ... [1., 1., 1.],
- # ... [2., 2., 2.],
- # ... [3., 3., 3.],
- # ... [4., 4., 4.]])
- # >>> c.maps
- # [array([[0, 1, 2],
- # [0, 3, 4]]),
- # array([[0], [0]])]
+ >>> c = tm.cleaned()
+ >>> assert c.equal([[0., 0., 0.],
+ ... [1., 1., 1.],
+ ... [2., 2., 2.],
+ ... [3., 3., 3.],
+ ... [4., 4., 4.]])
+ >>> assert np.array_equal(c.maps[0], [[0, 1, 2], [0, 3, 4]])
+ >>> assert np.array_equal(c.maps[1], [[0], [0]])
Returns:
@@ -1453,11 +1531,11 @@ class TensorMaps(TensorFields):
if duplicate_index != tensor_index:
stale_mask[tensor_index] = True
# redirect maps
- for map_index in range(len(self.maps)):
- for f in range(self.maps[map_index].shape[0]):
- if tensor_index in self.maps[f]:
- index = tfields.index(self.maps[map_index][f], tensor_index)
- inst.maps[map_index][f][index] = duplicate_index
+ for mp_idx in range(len(self.maps)):
+ for f in range(len(self.maps[mp_idx])):
+ if tensor_index in self.maps[mp_idx][f]:
+ index = tfields.index(self.maps[mp_idx][f], tensor_index)
+ inst.maps[mp_idx][f][index] = duplicate_index
return inst.removed(stale_mask)
@@ -1475,7 +1553,7 @@ class TensorMaps(TensorFields):
... [3, 4, 6]],
... [1, 3, 5, 7, 9],
... [2, 4, 6, 8, 0])])
- >>> c = m.removed([True, True, True, False, False, False, False])
+ >>> c = m.keep([False, False, False, True, True, True, True])
>>> c.equal([[0, 0, 0],
... [3, 3, 3],
... [4, 4, 4],
@@ -1489,20 +1567,51 @@ class TensorMaps(TensorFields):
"""
remove_condition = np.array(remove_condition)
- # built instance that only contains the vaild points
- inst = self[~remove_condition].copy()
- delete_indices = np.arange(self.shape[0])[remove_condition]
- face_keep_masks = self.to_maps_masks(~remove_condition)
+ # # built instance that only contains the vaild points
+ # inst = self[~remove_condition].copy()
+ # delete_indices = np.arange(self.shape[0])[remove_condition]
+ # face_keep_masks = self.to_maps_masks(~remove_condition)
- for map_index, face_keep_mask in enumerate(face_keep_masks):
- moveUpCounter = np.zeros(self.maps[map_index].shape, dtype=int)
+ # for mp_idx, face_keep_mask in enumerate(face_keep_masks):
+ # move_up_counter = np.zeros(self.maps[mp_idx].shape, dtype=int)
- # correct map:
- for p in delete_indices:
- moveUpCounter[self.maps[map_index] > p] -= 1
+ # # correct map:
+ # for p in delete_indices:
+ # move_up_counter[self.maps[mp_idx] > p] -= 1
- inst.maps[map_index] = (self.maps[map_index] + moveUpCounter)[face_keep_mask]
- return inst
+ # inst.maps[mp_idx] = (self.maps[mp_idx] + move_up_counter)[face_keep_mask]
+ # return inst
+ return self[~remove_condition]
+
+ def keep(self, keep_condition):
+ """
+ Return copy of self with vertices where keep_condition is True
+ Copy because self is immutable
+
+ Examples:
+ >>> import tfields
+ >>> m = tfields.TensorMaps([[0,0,0], [1,1,1], [2,2,2], [0,0,0],
+ ... [3,3,3], [4,4,4], [5,5,5]],
+ ... maps=[tfields.TensorFields([[0, 1, 2], [0, 1, 3],
+ ... [3, 4, 5], [3, 4, 1],
+ ... [3, 4, 6]],
+ ... [1, 3, 5, 7, 9],
+ ... [2, 4, 6, 8, 0])])
+ >>> c = m.removed([True, True, True, False, False, False, False])
+ >>> c.equal([[0, 0, 0],
+ ... [3, 3, 3],
+ ... [4, 4, 4],
+ ... [5, 5, 5]])
+ True
+ >>> c.maps[0]
+ TensorFields([[0, 1, 2],
+ [0, 1, 3]])
+ >>> assert c.maps[0].fields[0].equal([5, 9])
+ >>> assert c.maps[0].fields[1].equal([6, 0])
+
+ """
+ keep_condition = np.array(keep_condition)
+ return self[keep_condition]
def to_maps_masks(self, mask):
"""
@@ -1510,24 +1619,30 @@ class TensorMaps(TensorFields):
>>> from tfields import TensorMaps
>>> import numpy as np
>>> m = TensorMaps([[1,2,3], [3,3,3], [0,0,0], [5,6,7]],
- ... maps=[[[0, 1, 2], [1, 2, 3]]])
+ ... maps=[[[0, 1, 2], [1, 2, 3]],
+ ... [[0], [3]]])
>>> from sympy.abc import x,y,z
>>> vertexMask = m.evalf(z < 6)
>>> faceMask = m.to_maps_masks(vertexMask)
- >>> assert np.array_equal(faceMask, [[True, False]])
+ >>> assert np.array_equal(faceMask, [[True, False], [True, False]])
+ >>> index_face_mask = m.to_maps_masks(0)
+ >>> assert np.array_equal(index_face_mask, [[False, False], [True, False]])
Returns:
- mask of faces with all vertices in mask
+ masks of maps with all vertices in mask
"""
-
- indices = np.array(range(len(mask)))
- delete_indices = indices[~mask]
- delete_indices = set(delete_indices) # set speeds up everything enormously
+ indices = np.array(range(len(self)))
+ keep_indices = indices[mask]
+ if isinstance(keep_indices, int):
+ keep_indices = [keep_indices]
+ delete_indices = set(indices).difference(set(keep_indices))
+ # delete_indices = indices[~mask]
+ # delete_indices = set(delete_indices) # set speeds up everything enormously
masks = []
- for map_index in range(len(self.maps)):
- map_delete_mask = np.full((len(self.maps[map_index]),), False, dtype=bool)
- for i, mp in enumerate(self.maps[map_index]):
+ for mp_idx in range(len(self.maps)):
+ map_delete_mask = np.full((len(self.maps[mp_idx]),), False, dtype=bool)
+ for i, mp in enumerate(self.maps[mp_idx]):
for index in mp:
if index in delete_indices:
map_delete_mask[i] = True
@@ -1539,6 +1654,10 @@ class TensorMaps(TensorFields):
if __name__ == '__main__': # pragma: no cover
import doctest
doctest.testmod()
+ # doctest.run_docstring_examples(TensorFields.__getitem__, globals())
+ # doctest.run_docstring_examples(TensorMaps.__getitem__, globals())
+ # doctest.run_docstring_examples(TensorMaps.keep, globals())
+ # doctest.run_docstring_examples(TensorMaps.to_maps_masks, globals())
# doctest.run_docstring_examples(TensorMaps, globals())
# doctest.run_docstring_examples(TensorFields, globals())
# doctest.run_docstring_examples(AbstractNdarray.copy, globals())
diff --git a/tfields/mesh3D.py b/tfields/mesh3D.py
index 7ccb8442d38ef21b81b6fe36652545f443057d71..9b9ea64a0a0b7caffb1e2584e7da13b2c52d7d1b 100644
--- a/tfields/mesh3D.py
+++ b/tfields/mesh3D.py
@@ -119,7 +119,7 @@ class Mesh3D(tfields.TensorMaps):
raise ValueError("Conflicting options maps and faces")
if maps is not None:
kwargs['maps'] = maps
- if faceScalars:
+ if len(faceScalars) > 0:
map_fields = scalars_to_fields(faceScalars)
else:
map_fields = []
@@ -133,6 +133,61 @@ class Mesh3D(tfields.TensorMaps):
raise ValueError("Face dimension should be 3")
return obj
+ @classmethod
+ def plane(cls, *base_vectors, **kwargs):
+ vertices = tfields.Tensors.grid(*base_vectors)
+ fix_coord = None
+ for coord in range(3):
+ if len(base_vectors[coord]) > 1:
+ continue
+ if len(base_vectors[coord]) == 0:
+ continue
+ fix_coord = coord
+
+ var_coords = list(range(3))
+ var_coords.pop(var_coords.index(fix_coord))
+
+ faces = []
+ base0, base1 = base_vectors[var_coords[0]], base_vectors[var_coords[1]]
+ for i1 in range(len(base1) - 1):
+ for i0 in range(len(base0) - 1):
+ idx_top_left = len(base1) * (i0 + 0) + (i1 + 0)
+ idx_top_right = len(base1) * (i0 + 0) + (i1 + 1)
+ idx_bot_left = len(base1) * (i0 + 1) + (i1 + 0)
+ idx_bot_right = len(base1) * (i0 + 1) + (i1 + 1)
+ faces.append([idx_top_left, idx_top_right, idx_bot_left])
+ faces.append([idx_top_right, idx_bot_left, idx_bot_right])
+ inst = cls.__new__(cls, vertices, faces=faces, **kwargs)
+ return inst
+
+ @classmethod
+ def grid(cls, *base_vectors, **kwargs):
+ if not len(base_vectors) == 3:
+ raise AttributeError("3 base_vectors vectors required")
+
+ indices = [0, -1]
+ coords = range(3)
+ baseLengthsAbove1 = [len(b) > 1 for b in base_vectors]
+ # if one plane is given: rearrange indices and coords
+ if not all(baseLengthsAbove1):
+ indices = [0]
+ for i, b in enumerate(baseLengthsAbove1):
+ if not b:
+ coords = [i]
+ break
+
+ base_vectors = list(base_vectors)
+ planes = []
+ for ind in indices:
+ for coord in coords:
+ basePart = base_vectors[:]
+ basePart[coord] = np.array([base_vectors[coord][ind]],
+ dtype=float)
+
+ planes.append(cls.plane(*basePart))
+ inst = cls.merged(*planes, **kwargs)
+ return inst
+
@property
def faces(self):
return maps_to_faces(self.maps)
@@ -330,108 +385,6 @@ class Mesh3D(tfields.TensorMaps):
return ~faceDeleteMask
- def getRemovedVertices(self, vertexDeleteMask):
- """
- Return copy of self without vertices where vertexDeleteMask is True
- Copy because self is immutable
-
- Examples:
- >>> m = tfields.Mesh3D([[0,0,0], [1,1,1], [2,2,2], [0,0,0],
- ... [3,3,3], [4,4,4], [5,5,5]],
- ... [[0, 1, 2], [0, 1, 3], [3, 4, 5], [3, 4, 1],
- ... [3, 4, 6]],
- ... faceScalars=[[1,2], [3,4], [5,6], [7,8], [9,0]])
- >>> c = m.getRemovedVertices([True, True, True, False, False,
- ... False, False])
- >>> c
- Mesh3D([[ 0., 0., 0.],
- [ 3., 3., 3.],
- [ 4., 4., 4.],
- [ 5., 5., 5.]])
- >>> c.faces
- array([[0, 1, 2],
- [0, 1, 3]])
- >>> c.faceScalars
- array([[ 5., 6.],
- [ 9., 0.]])
-
- """
- log = logger.new()
- vertexDeleteMask = np.array(vertexDeleteMask)
- log.verbose("Remove {0} vertices.".format(vertexDeleteMask.sum()))
- # built instance that only contains the vaild points
- inst = self[~vertexDeleteMask].copy()
-
- moveUpCounter = np.zeros(self.faces.shape, dtype=int)
-
- # correct faces:
- deleteIndices = np.arange(len(self))[vertexDeleteMask]
- for p in deleteIndices:
- moveUpCounter[self.faces > p] -= 1
-
- faceKeepMask = self.getFaceMask(~vertexDeleteMask)
- inst.faces = (self.faces + moveUpCounter)[faceKeepMask]
- inst.faceScalars = self.faceScalars[faceKeepMask]
- return inst
-
- def cleaned(self, stale=True, duplicates=True):
- """
- Args:
- stale (bool): remove stale vertices
- duplicates (bool): replace duplicate vertices by originals
- Examples:
- >>> m = tfields.Mesh3D([[0,0,0], [1,1,1], [2,2,2], [0,0,0],
- ... [3,3,3], [4,4,4], [5,6,7]],
- ... [[0, 1, 2], [3, 4, 5]],
- ... faceScalars=[[1,2,3,4,5], [6,7,8,9,0]])
- >>> c = m.clean()
- >>> c
- Mesh3D([[ 0., 0., 0.],
- [ 1., 1., 1.],
- [ 2., 2., 2.],
- [ 3., 3., 3.],
- [ 4., 4., 4.]])
- >>> c.faces
- array([[0, 1, 2],
- [0, 3, 4]])
-
- Returns:
- copy of self without stale vertices and duplicat points
- """
- log = logger.new()
- log.verbose("Cleaning up.")
- # remove stale vertices
- if stale:
- vertexDeleteMask = self.staleVertices()
- else:
- vertexDeleteMask = np.full(self.shape[0], False, dtype=bool)
- # remove duplicates in order to not have any artificial separations
- inst = self
- if duplicates:
- inst = self.copy()
- log.verbose("Finding Duplicates")
- dups = tfields.duplicates(self, axis=0)
- for i, dupi in zip(range(self.shape[0]), dups):
- if dupi != i:
- log.verbose("Found Duplicate point @ index {0}".format(i))
- vertexDeleteMask[i] = True
- # redirect faces
- log.verbose("Run trough all faces to let it point to the"
- "original")
- for f in range(self.nfaces()):
- if i in self.faces[f]:
- index = tfields.index(self.faces[f], i)
- inst.faces[f][index] = dupi
-
- return inst.getRemovedVertices(vertexDeleteMask)
-
- def clean(self, *args, **kwargs):
- """
- Deprecated
- """
- warnings.warn("Name clean is deprecated. take cleaned instead", DeprecationWarning)
- return self.cleaned(*args, **kwargs)
-
def getScalarMap(self, mask):
"""
Return copy of self without vertices where mask is True
@@ -568,7 +521,7 @@ class Mesh3D(tfields.TensorMaps):
else False
for i in faceIndices]
mesh.removeFaces(faceDeleteMask)
- mesh = mesh.getRemovedVertices(mesh.staleVertices())
+ mesh = mesh.cleaned(duplicates=False)
parts.append(mesh)
return parts
@@ -628,7 +581,7 @@ class Mesh3D(tfields.TensorMaps):
>>> base = [np.linspace(0, 1, 10),
... np.linspace(0, 1, 10),
... np.linspace(0, 1, 10)]
- >>> mesh = tfields.Mesh3D.createMeshGrid(*base).cleaned()
+ >>> mesh = tfields.Mesh3D.grid(*base).cleaned()
Some small mistake occured in the test. Check that.
# Select the first face as a seedFace
@@ -688,7 +641,7 @@ class Mesh3D(tfields.TensorMaps):
>>> base = [np.linspace(0, 1, 2),
... np.linspace(0, 1, 4),
... np.linspace(0, 1, 4)]
- >>> mesh = tfields.Mesh3D.createMeshGrid(*base).cleaned()
+ >>> mesh = tfields.Mesh3D.grid(*base).cleaned()
Select the first face as a seedFace
>>> faceGroups = mesh.getSides([[1,0,0],[0,1,0],[0,0,1]])
@@ -903,9 +856,9 @@ class Mesh3D(tfields.TensorMaps):
return self.copy(), self.copy()
# mask for points that do not fulfill the cut expression
- mask = self.evalf(expression, coordSys=coordSys)
+ mask = self.evalf(expression)
# remove the points
- inst = self.getRemovedVertices(~mask)
+ inst = self[mask].copy()
scalarMap = self.getScalarMap(mask)
scalarMap = scalarMap.reshape((-1, 1)).astype(float)
@@ -1057,9 +1010,10 @@ class Mesh3D(tfields.TensorMaps):
>>> from sympy.abc import x,y,z
>>> cutExpr = x > 1.5
- >>> m = tfields.Mesh3D.createMeshGrid(np.linspace(0,3,4),
- ... np.linspace(0,3,4),
- ... np.linspace(0, 0, 1), faceScalars=np.linspace(4, 8, 18))
+ >>> m = tfields.Mesh3D.grid((0,3,4),
+ ... (0,3,4),
+ ... (0, 0, 1))
+ >>> m.faceScalars = np.linspace(4, 8, 18)
>>> mNew = m.cut(cutExpr)
>>> len(mNew)
8
@@ -1085,7 +1039,7 @@ class Mesh3D(tfields.TensorMaps):
copy of cut mesh
"""
- with self.tmp_transform(coordSys):
+ with self.tmp_transform(coordSys or self.coordSys):
if isinstance(expression, Mesh3D):
obj = self._cut_template(expression)
else: