Merge pull request #97 from mwong009/1.10.0-beta

1.10.0 beta

.github/workflows/linting.yml

@@ -10,6 +10,7 @@ jobs:
       - uses: psf/black@stable
         with:
           src: "."
+          version: "23.11.0"
 
   isort:
     runs-on: ubuntu-latest

.github/workflows/tests.yml

@@ -35,7 +35,7 @@ jobs:
       - name: Xcode check (macos)
         if: matrix.os == 'macos-latest'
         run: |
-          clang -- version
+          clang --version
           xcrun --show-sdk-path
       
       - name: Test pycmtensor import

README.md

@@ -5,6 +5,8 @@
 [![Licence](https://img.shields.io/badge/Licence-MIT-blue)](about/licence.md)
 ![](https://img.shields.io/pypi/pyversions/pycmtensor) 
 [![PyPI version](https://badge.fury.io/py/pycmtensor.svg)](https://badge.fury.io/py/pycmtensor) 
+![Conda-Forge|downloads](https://img.shields.io/conda/d/conda-forge/pycmtensor)
+
 [![codecov](https://codecov.io/gh/mwong009/pycmtensor/branch/master/graph/badge.svg?token=LFwgggDyjS)](https://codecov.io/gh/mwong009/pycmtensor) 
 [![Downloads](https://static.pepy.tech/personalized-badge/pycmtensor?period=month&units=international_system&left_color=grey&right_color=orange&left_text=downloads/month)](https://pepy.tech/project/pycmtensor) 
 [![DOI](https://zenodo.org/badge/460802394.svg)](https://zenodo.org/badge/latestdoi/460802394)

docs/examples/mixed_mnl.ipynb

@@ -88,7 +88,7 @@
     "\n",
     "\n",
     "# estimate the model\n",
-    "from pycmtensor.models import train\n",
+    "from pycmtensor import train\n",
     "train(mymodel, ds)"
    ]
   },

docs/examples/mnl.ipynb

@@ -62,7 +62,7 @@
     "\n",
     "\n",
     "# estimate the model\n",
-    "from pycmtensor.models import train\n",
+    "from pycmtensor import train\n",
     "train(mymodel, ds)"
    ]
   },

docs/getting_started/overview.md

@@ -146,7 +146,7 @@ Output:
 ## Estimating the model
 
 ```python
-from pycmtensor.models import train
+from pycmtensor import train
 from pycmtensor.optimizers import Adam
 from pycmtensor.scheduler import ConstantLR
 
@@ -348,7 +348,7 @@ U = [U_walk, U_cycle, U_pt, U_drive]
 mymodel = pycmtensor.models.MNL(ds=ds, params=locals(), utility=U, av=None)
 
 
-from pycmtensor.models import train
+from pycmtensor import train
 from pycmtensor.optimizers import Adam
 from pycmtensor.scheduler import ConstantLR
 

pycmtensor/__init__.py

@@ -34,6 +34,7 @@
 # shortcuts for importing commonly used classes
 from pycmtensor.dataset import Dataset
 from pycmtensor.regularizers import Regularizers
+from pycmtensor.run import compute, train
 
 config = defaultconfig.config
 

pycmtensor/expressions.py

@@ -1,5 +1,10 @@
 """
-The code snippet is a part of the PyCMTensor expressions module. It defines a base class for parsing and manipulating Aesara tensor expressions. The class provides methods for parsing a tensor expression to remove parentheses and tensor operators, and returns a clean list of keywords found in the expression. It also defines a base class for expression objects, which includes overloaded operators for tensor operations such as addition, subtraction, multiplication, division, and comparison.
+The code snippet is a part of the PyCMTensor expressions module. It defines a base 
+class for parsing and manipulating Aesara tensor expressions. The class provides 
+methods for parsing a tensor expression to remove parentheses and tensor operators, and 
+returns a clean list of keywords found in the expression. It also defines a base class 
+for expression objects, which includes overloaded operators for tensor operations such 
+as addition, subtraction, multiplication, division, and comparison.
 """
 from typing import Union
 
@@ -51,7 +56,8 @@ def __init__(self, expression=None):
         """Base class for parsing and manipulating Aesara tensor expressions.
 
         Args:
-            expression (TensorVariable, optional): The tensor expression to parse. Defaults to None.
+            expression (TensorVariable, optional): The tensor expression to parse.
+            Defaults to None.
         """
         if expression is not None:
             self.expression = str(pprint(expression))
@@ -153,7 +159,7 @@ def __mul__(self, other):
             return self() * other()
         else:
             raise TypeError(
-                f"__mul__ {other} must be a TensorVariable or TensorShared Variable object"
+                f"__mul__ {other} must be a TensorVariable or TensorShared Variable"
             )
 
     def __rmul__(self, other):
@@ -399,8 +405,10 @@ def __init__(self, name: str, draw_type: str, n_draws: int):
 
         Args:
             name (str): The name of the RandomDraw object.
-            draw_type (str): The distribution of the draw. Can be "normal", "lognormal", "gumbel", "exponential", "gamma", or "poisson".
-            n_draws (int): The number of draws, which determines the size of the shared tensor.
+            draw_type (str): The distribution of the draw. Can be "normal",
+            "lognormal", "gumbel", "exponential", "gamma", or "poisson".
+            n_draws (int): The number of draws, which determines the size of the shared
+            tensor.
 
         Raises:
             NotImplementedError: If an unsupported draw_type is provided.
@@ -447,7 +455,8 @@ def __init__(self, name, size, value=None):
         Args:
             name (str): The name of the parameter.
             size (Union[tuple,list]): The size of the array in 1 dimension.
-            value (numpy.ndarray): The initial values of the parameter. If `None` is given, it defaults to `0`.
+            value (numpy.ndarray): The initial values of the parameter. If `None` is
+            given, it defaults to `0`.
         """
         Param.__init__(self, name, lb=None, ub=None)
 
@@ -496,7 +505,8 @@ def __init__(self, name, size, value=None, init_type=None):
         Args:
             name (str): name of the parameter
             size (Union[tuple,list]): size of the array
-            value (numpy.ndarray): initial values of the parameter. Defaults to `random.uniform(-0.1, 0.1, size)`
+            value (numpy.ndarray): initial values of the parameter. Defaults to `random.
+            uniform(-0.1, 0.1, size)`
             init_type (str): initialization type, see notes
 
         Note:
@@ -510,8 +520,14 @@ def __init__(self, name, size, value=None, init_type=None):
             * `"glorot"`: initialization method that maintains the variance for
               symmetric activation functions, e.g. sigm, tanh [^2]
 
-            [^1] He, K., Zhang, X., Ren, S. and Sun, J., 2015. Delving deep into rectifiers: Surpassing human-level performance on imagenet classification. In Proceedings of the IEEE international conference on computer vision (pp. 1026-1034).
-            [^2] Glorot, X. and Bengio, Y., 2010, March. Understanding the difficulty of training deep feedforward neural networks. In Proceedings of the thirteenth international conference on artificial intelligence and statistics (pp. 249-256). JMLR Workshop and Conference Proceedings.
+            [^1] He, K., Zhang, X., Ren, S. and Sun, J., 2015. Delving deep into
+            rectifiers: Surpassing human-level performance on imagenet classification.
+            In Proceedings of the IEEE international conference on computer vision (pp.
+            1026-1034).
+            [^2] Glorot, X. and Bengio, Y., 2010, March. Understanding the difficulty
+            of training deep feedforward neural networks. In Proceedings of the
+            thirteenth international conference on artificial intelligence and
+            statistics (pp. 249-256). JMLR Workshop and Conference Proceedings.
 
         !!! example
             Specifying a weight array:
@@ -566,3 +582,46 @@ def T(self):
 
     def __repr__(self):
         return f"Weight({self.name}, {self.shape})"
+
+
+class Gamma(Param):
+    def __init__(self, name, size):
+        """Class object for Gamma parameter
+
+        Args:
+            name (str): The name of the parameter.
+            size (Union[tuple,list]): The size of the parameter.
+        """
+        Param.__init__(self, name)
+        value = np.ones(size, dtype=FLOATX)
+
+        self._init_value = value
+        self._param_type = "Gamma"
+        self.shared_var = aesara.shared(self.init_value, name=name, borrow=True)
+
+    @property
+    def T(self):
+        return self.shared_var.T
+
+    @property
+    def init_type(self):
+        return self._param_type
+
+    def __repr__(self):
+        return f"Gamma({self.name}, {self.shape})"
+
+    def __rmul__(self, other):
+        if isinstance(other, (TensorVariable, TensorSharedVariable)):
+            g = aet.atleast_Nd(self(), n=other.ndim, left=False)
+            return g * other
+
+        else:
+            return super().__rmul__(other)
+
+    def __mul__(self, other):
+        if isinstance(other, (TensorVariable, TensorSharedVariable)):
+            g = aet.atleast_Nd(self(), n=other.ndim, left=False)
+            return g * other
+
+        else:
+            return super().__mul__(other)

pycmtensor/logger.py

@@ -18,7 +18,8 @@
 ```
 
 ## Inputs
-- `level` (int): The level of the logger to be set. It can be one of the predefined levels: `DEBUG`, `INFO`, `WARNING`, `ERROR`, or `CRITICAL`.
+- `level` (int): The level of the logger to be set. It can be one of the predefined 
+  levels: `DEBUG`, `INFO`, `WARNING`, `ERROR`, or `CRITICAL`.
 
 ## Outputs
 - None

pycmtensor/models/MNL.py

@@ -18,7 +18,7 @@
 
 class MNL(BaseModel):
     def __init__(self, ds, variables, utility, av=None, **kwargs):
-        """Defines a Multinomial Logit model
+        """Initialize the Multinomial Logit model with the given dataset, variables, utility function, and availability.
 
         Args:
             ds (pycmtensor.Data): the database object
@@ -136,12 +136,6 @@ def reset_values(self) -> None:
     def build_cost_fn(self):
         """Constructs Aesara functions for calculating the cost and prediction errors of the Multinomial Logit model.
 
-        Inputs:
-        - None
-
-        Outputs:
-        - None
-
         Example Usage:
         ```python
         # Create an instance of the MNL class