Add xtensor docs

Author: ricardoV94

pytensor/xtensor/readme.md renamed to doc/library/xtensor/index.md

@@ -1,15 +1,25 @@
+(libdoc_xtensor)=
 # XTensor Module
 
+:::{toctree}
+:maxdepth: 1
+xtensor/linalg
+xtensor/math
+xtensor/random
+xtensor/type
+:::
+
 This module implements as abstraction layer on regular tensor operations, that behaves like Xarray.
 
-A new type `XTensorType`, generalizes the `TensorType` with the addition of a `dims` attribute, 
-that labels the dimensions of the tensor. 
+A new type :class:`pytensor.xtensor.type.XTensorType`, generalizes the :class:`pytensor.tensor.type.TensorType` 
+with the addition of a `dims` attribute, that labels the dimensions of the tensor. 
 
-Variables of `XTensorType` (i.e.,  `XTensorVariable`s) are the symbolic counterpart to xarray DataArray objects.
+Variables of XTensorType (i.e.,  :class:`pytensor.xtensor.type.XTensorVariable`s) are the symbolic counterpart
+to xarray DataArray objects.
 
-The module implements several PyTensor operations `XOp`s, whose signature mimics that of xarray (and xarray_einstants) DataArray operations.
-These operations, unlike most regular PyTensor operations, cannot be directly evaluated, but require a rewrite (lowering) into
-a regular tensor graph that can itself be evaluated as usual.
+The module implements several PyTensor operations :class:`pytensor.xtensor.basic.XOp`s, whose signature mimics that of 
+xarray (and xarray_einstants) DataArray operations. These operations, unlike most regular PyTensor operations, cannot 
+be directly evaluated, but require a rewrite (lowering) into a regular tensor graph that can itself be evaluated as usual.
 
 Like regular PyTensor, we don't need an Op for every possible method or function in the public API of xarray.
 If the existing XOps can be composed to produce the desired result, then we can use them directly.
@@ -23,16 +33,16 @@ Coords involve aspects of Pandas/database query and joining that are not trivial
 
 ```python
 import pytensor.tensor as pt
-import pytensor.xtensor as px
+import pytensor.xtensor as ptx
 
 a = pt.tensor("a", shape=(3,))
 b = pt.tensor("b", shape=(4,))
 
-ax = px.as_xtensor(a, dims=["x"])
-bx = px.as_xtensor(b, dims=["y"])
+ax = ptx.as_xtensor(a, dims=["x"])
+bx = ptx.as_xtensor(b, dims=["y"])
 
 zx = ax + bx
-assert zx.type == px.type.XTensorType("float64", dims=["x", "y"], shape=(3, 4))
+assert zx.type == ptx.type.XTensorType("float64", dims=["x", "y"], shape=(3, 4))
 
 z = zx.values
 z.dprint()
@@ -64,6 +74,3 @@ fn.dprint()
 #  └─ ExpandDims{axis=0} [id D] 0
 #     └─ b [id E]
 ```
-
-
-

doc/library/xtensor/linalg.md

@@ -0,0 +1,9 @@
+(libdoc_xtensor_linalg)=
+## XTensor linalg operations
+
+```{eval-rst}
+.. automodule:: pytensor.xtensor.linalg
+.. autosummary::
+   :toctree: generated/
+   :members:
+```

doc/library/xtensor/math.md

@@ -0,0 +1,9 @@
+(libdoc_xtensor_math)=
+## XTensor math operations
+
+```{eval-rst}
+.. automodule:: pytensor.xtensor.math
+.. autosummary::
+   :toctree: generated/
+   :members:
+```

doc/library/xtensor/module_functions.md

@@ -0,0 +1,11 @@
+(libdoc_xtensor_module_function)=
+## XTensor module operations
+
+```{eval-rst}
+.. automodule:: pytensor.xtensor
+.. autosummary::
+   :toctree: generated/
+
+   concat
+   dot
+```

doc/library/xtensor/random.md

@@ -0,0 +1,9 @@
+(libdoc_xtensor_random)=
+## XTensor random operations
+
+```{eval-rst}
+.. automodule:: pytensor.xtensor.random
+.. autosummary::
+   :toctree: generated/
+   :members:
+```

doc/library/xtensor/type.md

@@ -0,0 +1,30 @@
+(libdoc_xtenor_type)=
+
+# XTensor Type and Variable
+
+## XTensorVariable creation functions
+
+```{eval-rst}
+.. currentmodule:: pytensor.xtensor.type
+.. autosummary::
+   :toctree: generated/
+
+   xtensor
+   xtensor_constant
+   as_xtensor
+```
+
+## XTensor Type and Variable classes
+
+```{eval-rst}
+.. currentmodule:: pytensor.xtensor.type
+.. autosummary::
+   :toctree: generated/
+
+
+   XTensorType
+   XTensorVariable
+   XTensorConstant
+```
+
+