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Nick/tenmat docs #294

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Nick/tenmat docs #294

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e5d45ec
Add copy constructor for tenmat.
ntjohnson1 Nov 24, 2023
744e1cb
SPTENMAT: Remove from_data. Merge with __init__
ntjohnson1 Nov 24, 2023
f413df9
SPTENMAT: Move from_tensor_type to to_sptenmat
ntjohnson1 Nov 24, 2023
4220272
Pull out some common code ahead of tenmat constructor refactor.
ntjohnson1 Nov 24, 2023
fa4d029
TENMAT: Decouple from_data and from_tensor
ntjohnson1 Dec 12, 2023
7abe49d
TENMAT: Merge from_data into default constructor
ntjohnson1 Dec 13, 2023
40ffa4b
TENMAT: Move from_tensor to to_tenmat
ntjohnson1 Dec 13, 2023
d16efd7
Update tutorials to match new constructors.
ntjohnson1 Dec 13, 2023
8a04061
Improve some documentation for updated constructors/methods.
ntjohnson1 Dec 13, 2023
8eebfa7
BUILD: Temporarily pin ruff to unblock
ntjohnson1 Dec 13, 2023
5e24ab8
TENMAT: Add doctest example for every method.
ntjohnson1 Dec 16, 2023
1da704b
SPTENMAT: Add doctest example for every method.
ntjohnson1 Dec 16, 2023
5bf9895
TENMAT: Add copy argument to give option to try and optimize views.
ntjohnson1 Dec 16, 2023
ae7ef78
SPTENMAT: Add copy argument to give option to try and optimize views.
ntjohnson1 Dec 16, 2023
9a12c93
PROFILING: Updating our profiling workflow.
ntjohnson1 Dec 16, 2023
db20ae4
TENMAT: Replace tt_to_dense_matrix usages with tenmat.
ntjohnson1 Dec 16, 2023
d2577d4
TENMAT: Remove tt_from_dense_matrix since tenmat exists.
ntjohnson1 Dec 16, 2023
4f7bbcb
Merge branch 'main' into nick/tenmat_docs
ntjohnson1 Apr 11, 2024
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Update tutorials to match new constructors.
  • Loading branch information
@ntjohnson1
ntjohnson1 committed Dec 13, 2023
commit d16efd7172255d5556a7f875c120f11f7a4ac4ea
36 changes: 12 additions & 24 deletions docs/source/tutorial/class_sptenmat.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -70,7 +70,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(X, np.array([0])) # Mode-0 matricization\n",
"A = X.to_sptenmat(np.array([0])) # Mode-0 matricization\n",
"A"
]
},
Expand All @@ -81,7 +81,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(X, np.array([1, 2])) # Multiple modes mapped to rows.\n",
"A = X.to_sptenmat(np.array([1, 2])) # Multiple modes mapped to rows.\n",
"A"
]
},
Expand All @@ -92,9 +92,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, cdims=np.array([1, 2])\n",
") # Specify column dimensions.\n",
"A = X.to_sptenmat(cdims=np.array([1, 2])) # Specify column dimensions.\n",
"A"
]
},
Expand All @@ -105,9 +103,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, np.arange(4)\n",
") # All modes mapped to rows, i.e., vectorize.\n",
"A = X.to_sptenmat(np.arange(4)) # All modes mapped to rows, i.e., vectorize.\n",
"A"
]
},
Expand All @@ -118,9 +114,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, np.array([1])\n",
") # By default, columns are ordered as [0, 2, 3]\n",
"A = X.to_sptenmat(np.array([1])) # By default, columns are ordered as [0, 2, 3]\n",
"A"
]
},
Expand All @@ -131,9 +125,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, np.array([1]), np.array([3, 0, 2])\n",
") # Specify explicit ordering\n",
"A = X.to_sptenmat(np.array([1]), np.array([3, 0, 2])) # Specify explicit ordering\n",
"A"
]
},
Expand All @@ -144,9 +136,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"fc\"\n",
") # Forward cyclic column ordering\n",
"A = X.to_sptenmat(np.array([1]), cdims_cyclic=\"fc\") # Forward cyclic column ordering\n",
"A"
]
},
Expand All @@ -157,9 +147,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic column ordering\n",
"A = X.to_sptenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic column ordering\n",
"A"
]
},
Expand Down Expand Up @@ -236,7 +224,7 @@
"metadata": {},
"outputs": [],
"source": [
"B = ttb.sptenmat.from_data(\n",
"B = ttb.sptenmat(\n",
" A.subs, A.vals, A.rdims, A.cdims, A.tshape\n",
") # Effectively copies A\n",
"B"
Expand All @@ -257,7 +245,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.sptenmat.from_data(\n",
"A = ttb.sptenmat(\n",
" rdims=A.rdims, cdims=A.cdims, tshape=A.tshape\n",
") # An empty sptenmat\n",
"A"
Expand Down Expand Up @@ -298,7 +286,7 @@
"outputs": [],
"source": [
"X = ttb.sptenrand((10, 10, 10, 10), nonzeros=10) # Create sptensor\n",
"A = ttb.sptenmat.from_tensor_type(X, np.array([0])) # Convert to an sptenmat\n",
"A = X.to_sptenmat(np.array([0])) # Convert to an sptenmat\n",
"A"
]
},
Expand Down Expand Up @@ -328,7 +316,7 @@
"metadata": {},
"outputs": [],
"source": [
"B = ttb.sptenmat.from_tensor_type(ttb.sptenrand((3, 3, 3), nonzeros=3), np.array([0]))\n",
"B = ttb.sptenrand((3, 3, 3), nonzeros=3).to_sptenmat(np.array([0]))\n",
"B"
]
},
Expand Down
70 changes: 20 additions & 50 deletions docs/source/tutorial/class_tenmat.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@
"outputs": [],
"source": [
"# Dims [0,1] map to rows, [2,3] to columns.\n",
"A = ttb.tenmat.from_tensor_type(X, np.array([0, 1]), np.array([2, 3]))\n",
"A = X.to_tenmat(np.array([0, 1]), np.array([2, 3]))\n",
"A"
]
},
Expand All @@ -63,7 +63,7 @@
"metadata": {},
"outputs": [],
"source": [
"B = ttb.tenmat.from_tensor_type(X, np.array([1, 0]), np.array([2, 3])) # Order matters!\n",
"B = X.to_tenmat(np.array([1, 0]), np.array([2, 3])) # Order matters!\n",
"B"
]
},
Expand All @@ -73,7 +73,7 @@
"metadata": {},
"outputs": [],
"source": [
"C = ttb.tenmat.from_tensor_type(X, np.array([0, 1]), np.array([3, 2]))\n",
"C = X.to_tenmat(np.array([0, 1]), np.array([3, 2]))\n",
"C"
]
},
Expand All @@ -92,9 +92,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1])\n",
") # np.array([1]) passed to the `rdims` parameter\n",
"A = X.to_tenmat(np.array([1])) # np.array([1]) passed to the `rdims` parameter\n",
"A"
]
},
Expand All @@ -114,7 +112,7 @@
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"# Same as A = ttb.tenmat.from_tensor_type(X, np.array([0,3]), np.array([1,2]))\n",
"A = ttb.tenmat.from_tensor_type(X, cdims=np.array([1, 2]))\n",
"A = X.to_tenmat(cdims=np.array([1, 2]))\n",
"A"
]
},
Expand All @@ -132,9 +130,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, cdims=np.arange(0, 4)\n",
") # Map all the dimensions to the columns\n",
"A = X.to_tenmat(cdims=np.arange(0, 4)) # Map all the dimensions to the columns\n",
"A"
]
},
Expand All @@ -153,9 +149,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([2])\n",
") # By default, columns are ordered as [0, 1, 3].\n",
"A = X.to_tenmat(np.array([2])) # By default, columns are ordered as [0, 1, 3].\n",
"A"
]
},
Expand All @@ -166,9 +160,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), np.array([2, 0, 3])\n",
") # Explicit specification.\n",
"A = X.to_tenmat(np.array([1]), np.array([2, 0, 3])) # Explicit specification.\n",
"A"
]
},
Expand All @@ -178,9 +170,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"fc\"\n",
") # Forward cyclic, [2,3,0].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"fc\") # Forward cyclic, [2,3,0].\n",
"A"
]
},
Expand All @@ -190,9 +180,7 @@
"metadata": {},
"outputs": [],
"source": [
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A"
]
},
Expand All @@ -210,9 +198,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A.data # The 2D numpy array itself."
]
},
Expand Down Expand Up @@ -257,10 +243,8 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"B = ttb.tenmat.from_data(A.data, A.rindices, A.cindices, A.tshape)\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"B = ttb.tenmat(A.data, A.rindices, A.cindices, A.tshape)\n",
"B # Recreates A."
]
},
Expand Down Expand Up @@ -295,9 +279,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A.double() # Converts A to a standard 2D numpy array."
]
},
Expand All @@ -315,9 +297,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"Y = A.to_tensor()\n",
"Y"
]
Expand All @@ -336,9 +316,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A.shape # 2D numpy array shape."
]
},
Expand All @@ -365,9 +343,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A[1, 0] # Returns the (1,0) element of the 2D numpy array"
]
},
Expand All @@ -385,9 +361,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A[0:2, 0:2] = np.ones((2, 2))\n",
"A"
]
Expand Down Expand Up @@ -422,9 +396,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"A.norm() # Norm of the 2D numpy array."
]
},
Expand Down Expand Up @@ -488,9 +460,7 @@
"outputs": [],
"source": [
"X = ttb.tensor(np.arange(1, 25), shape=(3, 2, 2, 2)) # Create a tensor.\n",
"A = ttb.tenmat.from_tensor_type(\n",
" X, np.array([1]), cdims_cyclic=\"bc\"\n",
") # Backward cyclic, [0,3,2].\n",
"A = X.to_tenmat(np.array([1]), cdims_cyclic=\"bc\") # Backward cyclic, [0,3,2].\n",
"B = A * A.ctranspose() # Tenmat that is the product of two tenmats.\n",
"B"
]
Expand Down