Merge pull request #97 from jacquelinegarrahan/doc-cleanup

Doc cleanup

docs/BokehServer.md

@@ -24,15 +24,15 @@ Create a new file named `model.py`. Set up out model:
 ```python
 import numpy as np
 from lume_model.variables import ScalarInputVariable, ImageOutputVariable
-from lume_model.models import SurrogateModel
+from lume_model.models import BaseModel
 from lume_model.utils import save_variables
 ```
 
 Next, define the demo model. Here, we define the input and output variables as keyword arguments. In order for the evaluate method to execute correctly, these
 passed variables must be dictionaries of variables with corresponding types and names. These could also be defined as class attributes.
 
 ```python
-class DemoModel(SurrogateModel):
+class DemoModel(BaseModel):
     def __init__(self, input_variables=None, output_variables=None):
         self.input_variables = input_variables
         self.output_variables = output_variables

docs/index.md

@@ -40,14 +40,14 @@ output = ScalarOutputVariable(name="output")
 
 ### Defining the model
 
-[LUME-model](https://github.com/slaclab/lume-model) includes a SurrogateModel base class to enforce the defined class's compatability with the lume-epics server. The primary function of this base class is to force the implementation of an evaluate method. This method must accept a list of `lume-model` input variables, execute the model, and return a list of `lume-model` output variables. Input variables and output variables must be defined as class attributes. They may be defined directly as class attributes or assigned in __init__.
+[LUME-model](https://github.com/slaclab/lume-model) includes a BaseModel base class to enforce the defined class's compatability with the lume-epics server. The primary function of this base class is to force the implementation of an evaluate method. This method must accept a list of `lume-model` input variables, execute the model, and return a list of `lume-model` output variables. Input variables and output variables must be defined as class attributes. They may be defined directly as class attributes or assigned in __init__.
 
 For our model, we will construct a class that accepts and stores our input and output variables on initialization. Then, we implement an `evaluate` method that accepts an updated list of input variables, executes the model, and updates the output variable value appropriately. Place the following code in a file named `server.py`.
 ```python
-from lume_epics.model import SurrogateModel
+from lume_epics.model import BaseModel
 import numpy as np
 
-class ExampleModel(SurrogateModel):
+class ExampleModel(BaseModel):
     def __init__(self, input_variables = [], output_variables = []):
         self.input_variables = input_variables
         self.output_variables = output_variables
@@ -112,11 +112,11 @@ These are then loaded during server construction:
 from lume_epics.epics_server import Server
 from lume_model.utils import variables_from_yaml
 from lume_epics.utils import config_from_yaml
-from lume_epics.model import SurrogateModel
+from lume_epics.model import BaseModel
 import numpy as np
 
 
-class ExampleModel(SurrogateModel):
+class ExampleModel(BaseModel):
     def __init__(self, input_variables = [], output_variables = []):
         self.input_variables = input_variables
         self.output_variables = output_variables
@@ -278,12 +278,12 @@ In `server.py`:
 ```python
 import numpy as np
 from lume_model.variables import ScalarInputVariable, ImageOutputVariable
-from lume_model.models import SurrogateModel
+from lume_model.models import BaseModel
 from lume_model.utils import save_variables
 from lume_model.utils import variables_from_yaml
 from lume_epics.utils import config_from_yaml
 
-class ExampleModel(SurrogateModel):
+class ExampleModel(BaseModel):
     def __init__(self, input_variables: dict=None, output_variables:dict=None):
         self.input_variables = input_variables
         self.output_variables = output_variables

examples/read_only/model.py

@@ -4,11 +4,11 @@
     ImageOutputVariable,
     ScalarOutputVariable,
 )
-from lume_model.models import SurrogateModel
+from lume_model.models import BaseModel
 from lume_model.utils import save_variables
 
 
-class DemoModel(SurrogateModel):
+class DemoModel(BaseModel):
     def __init__(self, input_variables=None, output_variables=None):
         self.input_variables = input_variables
         self.output_variables = output_variables

lume_epics/epics_pva_server.py

@@ -540,7 +540,7 @@ def __init__(self, pvname: str, is_constant: bool, server: PVAServer):
 
     def put(self, pv: SharedPV, op: ServOpWrap) -> None:
         """Updates the global input process variable state, posts the input process
-        variable value change, runs the thread local OnlineSurrogateModel instance
+        variable value change, runs the thread local BaseModel instance
         using the updated global input process variable states, and posts the model
         output values to the output process variables.
 

lume_epics/model.py

@@ -1,8 +1,8 @@
 """
-This module is used for executing callbacks on the user's SurrogateModel class for use
-with the EPICS server defined in lume_epics.epics_server. The SurrogateModel must be
+This module is used for executing callbacks on the user's BaseModel subclass for use
+with the EPICS server defined in lume_epics.epics_server. The BaseModel must be
 defined using the guidelines outlined in the lume_model.models module to be surfaced
-using the OnlineSurrogateModel class.
+using the BaseModel class.
 
 """
 
@@ -23,15 +23,18 @@ class OnlineModel:
     Class for executing surrogate model.
 
     Attributes:
-        model (SurrogateModel): Model for execution.
+        model (BaseModel): Model for execution.
 
         input_variables (Dict[str, InputVariable]): List of lume-model variables to use as inputs.
 
         ouput_variables (Dict[str, OutputVariable]): List of lume-model variables to use as outputs.
 
     """
 
-    def __init__(self, model: BaseModel,) -> None:
+    def __init__(
+        self,
+        model: BaseModel,
+    ) -> None:
         """
         Initialize OnlineModel with the base model class.
 

lume_epics/tests/launch_server.py

@@ -3,7 +3,7 @@
 import logging
 import sys
 from lume_epics import epics_server
-from lume_model.models import SurrogateModel
+from lume_model.models import BaseModel
 from lume_model.variables import (
     ScalarInputVariable,
     ImageInputVariable,
@@ -18,15 +18,23 @@
 logger.setLevel("DEBUG")
 
 
-class TestModel(SurrogateModel):
+class TestModel(BaseModel):
     input_variables = {
         "input1": ScalarInputVariable(name="input1", default=1.0, range=[0.0, 5.0]),
         "input2": ScalarInputVariable(
             name="input2", default=2.0, range=[0.0, 5.0], is_constant=True
         ),
         "input3": ImageInputVariable(
             name="input3",
-            default=np.array([[1, 6,], [4, 1]]),
+            default=np.array(
+                [
+                    [
+                        1,
+                        6,
+                    ],
+                    [4, 1],
+                ]
+            ),
             value_range=[1, 10],
             axis_labels=["count_1", "count_2"],
             x_min=0,
@@ -43,7 +51,8 @@ class TestModel(SurrogateModel):
         "output1": ScalarOutputVariable(name="output1"),
         "output2": ScalarOutputVariable(name="output2"),
         "output3": ImageOutputVariable(
-            name="output3", axis_labels=["count_1", "count_2"],
+            name="output3",
+            axis_labels=["count_1", "count_2"],
         ),
         "output4": ArrayOutputVariable(name="output4"),
     }

lume_epics/tests/test_server.py

@@ -16,7 +16,7 @@
     ImageOutputVariable,
 )
 from lume_epics import epics_server
-from lume_model.models import SurrogateModel
+from lume_model.models import BaseModel
 from lume_epics.tests.conftest import PVA_CONFIG