60 remove multi dim categoricals

CHANGELOG.md

@@ -13,6 +13,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Changed
 * fixed DataBool (#68)
 * fixed GetOneSample (#68)
+* removed option to specify dimensions in DataBool and DataCategorical components (#60), to align with bug fixes in AIXD
 
 ### Removed
 

docs/documentation.rst

@@ -15,13 +15,12 @@ DataBool
 	:height: 24
 	:width: 24
 
-Defines a boolean variable.
+Defines a boolean variable (`True` or `False`).
 
 
 **Inputs**
 
 - **name** *(str)* -- Name of the variable.
-- **dim** *(int)* -- Dimension of the variable.
 
 **Outputs**
 
@@ -34,13 +33,12 @@ DataCategorical
 	:height: 24
 	:width: 24
 
-Defines a categorical variable.
+Defines a categorical variable (for example, represening labels or classes).
 
 
 **Inputs**
 
 - **name** *(str)* -- Name of the variable.
-- **dim** *(int)* -- Dimension of the variable.
 - **options** *[List of (str)]* -- Options: list of possible categories, as strings.
 
 **Outputs**
@@ -128,7 +126,8 @@ DatasetGenerator
 	:height: 24
 	:width: 24
 
-Provides instructions on how to generate random samples for the dataset.
+Provides instructions on how to generate random samples for the dataset by harnessing the parametric model found in the current Grasshopper file. 
+See Tutorial for more information on how to prepare the inputs and outputs of the parametric model.
 
 
 **Outputs**
@@ -160,7 +159,8 @@ DatasetOneSample
 	:height: 24
 	:width: 24
 
-Retrieves one sample from the dataset (at a given or random index) and instantiates it in the parametric model.
+Retrieves one sample from the dataset (at a given or random index) and instantiates it in the parametric model. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -200,7 +200,8 @@ DatasetSummary
 	:height: 24
 	:width: 24
 
-Provides a summary of the dataset.
+Provides a summary of the dataset. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -218,7 +219,8 @@ Generator
 	:height: 24
 	:width: 24
 
-Runs a generation campaing to create new designs using the trained model.
+Runs a generation campaing to create new designs using the trained model. 
+Requires a dataset and a trained model to be loaded.
 
 
 **Inputs**
@@ -241,7 +243,8 @@ ModelDimensions
 	:height: 24
 	:width: 24
 
-Retrieves dimensions of the model's input and output layers.
+Retrieves dimensions of the model's input and output layers. 
+Requires that a model has been set up or loaded.
 
 
 **Inputs**
@@ -259,7 +262,8 @@ ModelLoad
 	:height: 24
 	:width: 24
 
-Loads an existing, pre-traind neural network model from a checkpoint.
+Loads an existing, pre-traind neural network model from a checkpoint. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -280,7 +284,8 @@ ModelSetup
 	:height: 24
 	:width: 24
 
-Sets up an autoencoder model of the specified type with the given parameters.
+Sets up an autoencoder model of the specified type with the given parameters. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -305,7 +310,8 @@ ModelSummary
 	:height: 24
 	:width: 24
 
-Provides a summary of the autoencoder model's architecture.
+Provides a summary of the autoencoder model's architecture. 
+Requires that a model has been set up or loaded.
 
 
 **Inputs**
@@ -324,7 +330,8 @@ ModelTrain
 	:height: 24
 	:width: 24
 
-Runs a training campaign.
+Runs a training campaign. 
+Requires that a model has been set up (to train from scratch) or loaded (to continue training).
 
 
 **Inputs**
@@ -345,7 +352,9 @@ PlotContours
 	:height: 24
 	:width: 24
 
-Plots the distribution contours for each pair of variables from the data in the dataset.
+Plots the distribution contours for each pair of variables from the data in the dataset. 
+Launches an interactive plot in a browser. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -360,7 +369,9 @@ PlotContoursRequest
 	:height: 24
 	:width: 24
 
-Plots the predicted values of the requested designs against the distribution contours for each pair of the corresponding variables.
+Plots the predicted values of the requested designs against the distribution contours for each pair of the corresponding variables. 
+Launches an interactive plot in a browser. 
+Requires that a request has been made and designs have been generated.
 
 
 **Inputs**
@@ -374,7 +385,9 @@ PlotCorrelations
 	:height: 24
 	:width: 24
 
-Plots correlation matrix for the given variables from the data in the dataset.
+Plots correlation matrix for the given variables from the data in the dataset. 
+Launches an interactive plot in a browser. 
+Requires a dataset to be loaded.
 
 
 **Inputs**
@@ -389,7 +402,9 @@ PlotDistribution
 	:height: 24
 	:width: 24
 
-Plots the distribution of the given variables from the data in the dataset.
+Plots the distribution of the given variables from the data in the dataset. 
+Launches an interactive plot in a browser. 
+Requires a dataset to be loaded.
 
 
 **Inputs**

src/aixd_ara/components/ara_DataBool/code.py

@@ -1,11 +1,8 @@
 # flake8: noqa
 from aixd_ara.wrappers import WrapperShallowDataObject
 
-if not dim or dim < 1:
-    dim = 1
 
-
-dobj = {"datatype": "DataBool", "name": name, "dim": dim}
+dobj = {"datatype": "DataBool", "name": name, "dim": 1}
 
 
 dataobject = WrapperShallowDataObject(dobj)

src/aixd_ara/components/ara_DataBool/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "DataBool",
     "category": "ARA",
     "subcategory": "1 Data",
-    "description": "Defines a boolean variable.",
+    "description": "Defines a boolean variable (`True` or `False`).",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,
@@ -14,14 +14,7 @@
                 "description": "Name of the variable.",
                 "typeHintID": "str",
                 "scriptParamAccess": 0
-            },
-            {
-                "name": "dim",
-                "description": "Dimension of the variable.",
-                "typeHintID": "int",
-                "scriptParamAccess": 0
             }
-
         ],
 
         "outputParameters": [

src/aixd_ara/components/ara_DataCat/code.py

@@ -1,15 +1,13 @@
 # flake8: noqa
 from aixd_ara.wrappers import WrapperShallowDataObject
 
-if not dim or dim < 1:
-    dim = 1
 
 if not options:
     options = None
 else:
     options = [str(x) for x in options]
 
 
-dobj = {"datatype": "DataCategorical", "name": name, "dim": dim, "domain": options}
+dobj = {"datatype": "DataCategorical", "name": name, "dim": 1, "domain": options}
 
 dataobject = WrapperShallowDataObject(dobj)

src/aixd_ara/components/ara_DataCat/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "DataCat",
     "category": "ARA",
     "subcategory": "1 Data",
-    "description": "Defines a categorical variable.",
+    "description": "Defines a categorical variable (for example, represening labels or classes).",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,
@@ -15,12 +15,6 @@
                 "typeHintID": "str",
                 "scriptParamAccess": 0
             },
-            {
-                "name": "dim",
-                "description": "Dimension of the variable.",
-                "typeHintID": "int",
-                "scriptParamAccess": 0
-            },
             {
                 "name": "options",
                 "description": "Options: list of possible categories, as strings.",

src/aixd_ara/components/ara_DatasetCreate/code.py

@@ -1,5 +1,6 @@
 # flake8: noqa
 from scriptcontext import sticky as st
+from Grasshopper.Kernel.GH_RuntimeMessageLevel import Warning
 
 from aixd_ara.gh_ui import create_dataset_object
 from aixd_ara.gh_ui_helper import component_id
@@ -17,3 +18,5 @@
 
 if cid in st.keys():
     msg = st[cid]["msg"]
+    if st[cid]["status"]=="warning":
+        ghenv.Component.AddRuntimeMessage(Warning, msg)

src/aixd_ara/components/ara_DatasetGenerator/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "DatasetGen",
     "category": "ARA",
     "subcategory": "2 Dataset",
-    "description": "Provides instructions on how to generate random samples for the dataset.",
+    "description": "Provides instructions on how to generate random samples for the dataset by harnessing the parametric model found in the current Grasshopper file. \nSee Tutorial for more information on how to prepare the inputs and outputs of the parametric model.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_DatasetOneSample/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "DatasetOneSample",
     "category": "ARA",
     "subcategory": "2 Dataset",
-    "description": "Retrieves one sample from the dataset (at a given or random index) and instantiates it in the parametric model.",
+    "description": "Retrieves one sample from the dataset (at a given or random index) and instantiates it in the parametric model. \nRequires a dataset to be loaded.",
     "exposure": 4,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_DatasetSummary/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "DatasetSummary",
     "category": "ARA",
     "subcategory": "2 Dataset",
-    "description": "Provides a summary of the dataset.",
+    "description": "Provides a summary of the dataset. \nRequires a dataset to be loaded.",
     "exposure": 4,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_Generator/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "Generator",
     "category": "ARA",
     "subcategory": "4 Generator",
-    "description": "Runs a generation campaing to create new designs using the trained model.",
+    "description": "Runs a generation campaing to create new designs using the trained model. \nRequires a dataset and a trained model to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_ModelDims/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "ModelDims",
     "category": "ARA",
     "subcategory": "3 Model",
-    "description": "Retrieves dimensions of the model's input and output layers.",
+    "description": "Retrieves dimensions of the model's input and output layers. \nRequires that a model has been set up or loaded.",
     "exposure": 4,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_ModelLoad/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "ModelLoad",
     "category": "ARA",
     "subcategory": "3 Model",
-    "description": "Loads an existing, pre-traind neural network model from a checkpoint.",
+    "description": "Loads an existing, pre-traind neural network model from a checkpoint. \nRequires a dataset to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_ModelSetup/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "ModelSetup",
     "category": "ARA",
     "subcategory": "3 Model",
-    "description": "Sets up an autoencoder model of the specified type with the given parameters.",
+    "description": "Sets up an autoencoder model of the specified type with the given parameters. \nRequires a dataset to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_ModelSummary/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "ModelSummary",
     "category": "ARA",
     "subcategory": "3 Model",
-    "description": "Provides a summary of the autoencoder model's architecture.",
+    "description": "Provides a summary of the autoencoder model's architecture. \nRequires that a model has been set up or loaded.",
     "exposure": 4,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_ModelTrain/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "ModelTrain",
     "category": "ARA",
     "subcategory": "3 Model",
-    "description": "Runs a training campaign.",
+    "description": "Runs a training campaign. \nRequires that a model has been set up (to train from scratch) or loaded (to continue training).",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_PlotContours/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "PlotContours",
     "category": "ARA",
     "subcategory": "5 Plotter",
-    "description": "Plots the distribution contours for each pair of variables from the data in the dataset.",
+    "description": "Plots the distribution contours for each pair of variables from the data in the dataset. \nLaunches an interactive plot in a browser. \nRequires a dataset to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_PlotContoursRequest/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "PlotContReq",
     "category": "ARA",
     "subcategory": "5 Plotter",
-    "description": "Plots the predicted values of the requested designs against the distribution contours for each pair of the corresponding variables.",
+    "description": "Plots the predicted values of the requested designs against the distribution contours for each pair of the corresponding variables. \nLaunches an interactive plot in a browser. \nRequires that a request has been made and designs have been generated.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_PlotCorrelations/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "PlotCorrelations",
     "category": "ARA",
     "subcategory": "5 Plotter",
-    "description": "Plots correlation matrix for the given variables from the data in the dataset.",
+    "description": "Plots correlation matrix for the given variables from the data in the dataset. \nLaunches an interactive plot in a browser. \nRequires a dataset to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,

src/aixd_ara/components/ara_PlotDistributions/metadata.json

@@ -3,7 +3,7 @@
     "nickname": "PlotDistribution",
     "category": "ARA",
     "subcategory": "5 Plotter",
-    "description": "Plots the distribution of the given variables from the data in the dataset.",
+    "description": "Plots the distribution of the given variables from the data in the dataset. \nLaunches an interactive plot in a browser. \nRequires a dataset to be loaded.",
     "exposure": 2,
     "ghpython": {
         "isAdvancedMode": false,