tensap.tensor_algebra.tools package¶
Submodules¶
tensap.tensor_algebra.tools.truncator module¶
Module truncator.
-
class
tensap.tensor_algebra.tools.truncator.Truncator(tolerance=1e-08, max_rank=inf, thresholding_type='hard', thresholding_parameter=None)¶ Bases:
objectClass Truncator.
- Attributes
- tolerancefloat
The relative tolerance for the truncation.
- max_rankint
The maximum rank for the truncation.
- thresholding_typestr
The thresholding type (‘hard’ or ‘soft’).
- thresholding_parameterfloat
The thresholding parameter.
Methods
hosvd(tensor)Compute the truncated hosvd of tensor.
hsvd(tensor[, tree, is_active_node])Compute the truncated svd in tree-based tensor format of tensor.
svd(tensor)Compute the truncated svd of an order-2 tensor.
trunc_svd(matrix[, tolerance, power])Compute the truncated svd of the matrix x with relative precision self.tolerance (or tolerance if provided) in Schatten p-norm (with p given by the input power) and maximal rank self.max_rank.
truncate(tensor)Compute the truncation of the tensor with relative precision self.tolerance and maximal rank self.max_rank.
ttsvd(tensor)Compute the truncated svd in tensor-train format of tensor.
-
hosvd(tensor)¶ Compute the truncated hosvd of tensor.
- Parameters
- tensornp.ndarray or tensap.FullTensor or tensap.TreeBasedTensor
The tensor to truncate.
- Returns
- outtensap.CanonicalTensor or tensap.TreeBasedTensor
The truncated tensor.
- Raises
- ValueError
If the input tensor is of the wrong type.
-
hsvd(tensor, tree=None, is_active_node=None)¶ Compute the truncated svd in tree-based tensor format of tensor.
- Parameters
- tensortensap.FullTensor or tensap.TreeBasedTensor
The tensor to truncate.
- treetensap.DimensionTree, optional
The tree of the output tree-based tensor. The default is None, indicating if tensor is a tensap.TreeBasedTensor to take tensor.tree.
- is_active_nodenumpy.ndarray, optional
Logical array indicating if the nodes are active.. The default is None, indicating if tensor is a tensap.TreeBasedTensor to take tensor.is_active_node.
- Returns
- outtensap.TreeBasedTensor
The truncated tensor in tree-based tensor format.
- Raises
- ValueError
If the wrong value of the atttribude _hsvd_type is provided.
- NotImplementedError
If the method is not implemented for the format.
-
svd(tensor)¶ Compute the truncated svd of an order-2 tensor.
- Parameters
- tensornumpy.ndarray or tensap.FullTensor or tensorflow.Tensor or
- tensap.TreeBasedTensor
The tensor to truncate.
- Returns
- outtensap.CanonicalTensor or tensap.TreeBasedTensor
The truncated tensor.
- Raises
- NotImplementedError
If the method is not implemented.
-
trunc_svd(matrix, tolerance=None, power=2)¶ Compute the truncated svd of the matrix x with relative precision self.tolerance (or tolerance if provided) in Schatten p-norm (with p given by the input power) and maximal rank self.max_rank.
- Parameters
- matrixnumpy.ndarray
The matrix to truncate.
- tolerancefloat, optional
The relative tolerance for the truncation. The default is self.tolerance.
- powerint or ‘inf’ or float(‘inf’) or numpy.inf, optional
The integer p of the Schatten-p norm (1 <= p <= inf, p = 2 for Frobenius). The default is 2.
- Returns
- tensap.CanonicalTensor
The truncated matrix.
-
truncate(tensor)¶ Compute the truncation of the tensor with relative precision self.tolerance and maximal rank self.max_rank.
- Parameters
- tensornumpy.ndarray or tensap.FullTensor or tensorflow.Tensor or
- tensap.TreeBasedTensor
The tensor to truncate.
- Returns
- outtensap.CanonicalTensor or tensap.TreeBasedTensor
The truncated tensor.
- Raises
- NotImplementedError
If the decomposition is not implemented for the tensor format.
- ValueError
If the tensor is of order 1.
-
ttsvd(tensor)¶ Compute the truncated svd in tensor-train format of tensor.
- Parameters
- tensortensap.FullTensor or tensap.TreeBasedTensor
The tensor to truncate.
- Returns
- tensap.TreeBasedTensor
The truncated tensor in tree-based tensor format with a linear tree.