update for model collections properly support mm units

.vscode/launch.json

@@ -0,0 +1,17 @@
+{
+  // Use IntelliSense to learn about possible attributes.
+  // Hover to view descriptions of existing attributes.
+  // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+  "version": "0.2.0",
+  "configurations": [
+    {
+      "name": "Python: Current File",
+      "type": "python",
+      "request": "launch",
+      "program": "${file}",
+      "console": "integratedTerminal",
+      "justMyCode": true,
+      "envFile": "${workspaceFolder}/.env"
+    }
+  ]
+}

bg_specklepy/Operations/columnOffsetEvaluation.py

@@ -3,6 +3,7 @@ import math
 from specklepy.objects.base import Base
 from specklepy.objects.other import RenderMaterial
 from bg_specklepy.Geometry.sphere import Sphere
+from specklepy.api.resources.commit import Commit as SpeckleCommit
 from bg_specklepy.SpeckleServer.commit import Commit
 from bg_specklepy.SpeckleServer.client import Client
 
@@ -11,6 +12,7 @@ class ColumnOffsetEvaluation():
     def __init__(self,
                  client_obj: Client,
                  stream_id: str,
+                 commit_object: SpeckleCommit,
                  commit_data: Base,
                  echo_level : int = 0,
                  tolerance : float = 0.01,
@@ -38,7 +40,7 @@ class ColumnOffsetEvaluation():
         self.column_elements = None
         self.data_frame = None
         self.offset_columns_dataframe = None
-        self.commit_object = None
+        self.commit_object = commit_object
         self._units = 'm'
         self._units_scaling = 1
 
@@ -62,23 +64,26 @@ class ColumnOffsetEvaluation():
         '''
 
         # HACKY - muss einen besseren Weg geben?
-        if not "Revit" in self.commit_data[dir(self.commit_data)[0]][0].speckle_type:
+        # if not "Revit" in self.commit_object.
+        if "Revit" not in self.commit_object.sourceApplication:
             raise NotImplementedError("Column offset evaluation currently restricted to Revit models only.")
 
         if self.echo_level == 1:
             print("[UPDATE]\t:\tRevit model detected ...")
 
-        if self.commit_data.speckle_type != "Objects.Organization.Model":
+        if self.commit_data.speckle_type not in ["Objects.Organization.Model", "Speckle.Core.Models.Collection"]:
             raise AttributeError("Commit data not of correct speckle type. A Revit Model needs to be used as basis input.")
 
+        column_collection = [collection for collection in self.commit_data.elements if collection.applicationId == "Structural Columns"][0]
+        self.column_elements = column_collection.elements
         # More languages to be added. But, Revit export should be standard english
-        for column_parameter in ["@Structural Columns", "@Tragwerksstützen"]:
-            try:
-                self.column_elements = self.commit_data[column_parameter]
-                self.column_parameter = column_parameter
-                break
-            except KeyError:
-                continue
+        # for column_parameter in ["@Structural Columns", "@Tragwerksstützen"]:
+        #     try:
+        #         self.column_elements = self.commit_data[column_parameter]
+        #         self.column_parameter = column_parameter
+        #         break
+        #     except KeyError:
+        #         continue
 
         if self.column_elements[0].units != 'm':
             if self.column_elements[0].units == 'mm':
@@ -237,7 +242,7 @@ class ColumnOffsetEvaluation():
         for index, row in self.offset_columns_dataframe.iterrows():
 
             obj = Base()
-
+            obj.units = self._units
             obj["@column_above"], obj["@column_below"], obj["@offset"] = {}, {}, {}
 
             radius = 0.35 * self._units_scaling

bg_specklepy/analysis_column_eccentricity.py

@@ -56,6 +56,7 @@ def main(speckle_project_data: str, function_inputs: str, speckle_token: str):
     evaluation = ColumnOffsetEvaluation(
                                         client_obj=client_obj, 
                                         stream_id=stream_id,
+                                        commit_object = commit,
                                         commit_data = commit_data,
                                         tolerance = inputs.tolerance,
                                         echo_level = inputs.echo_level,

tests/test_operations_column_offset_evaluation.py

@@ -1,25 +1,26 @@
-# Definierte Modell aus dem Beispiel https://speckle.xyz/streams/ff47530e95
-# 3 Stützenversätze
-from bg_specklepy.SpeckleServer.client import Client
-from bg_specklepy.SpeckleServer.stream import Stream
-from bg_specklepy.SpeckleServer.branch import Branch
-from bg_specklepy.SpeckleServer.commit import Commit
-from bg_specklepy.Operations.columnOffsetEvaluation import ColumnOffsetEvaluation
+import os
+from bg_specklepy.analysis_column_eccentricity import (
+    FunctionInputs,
+    SpeckleProjectData,
+    main,
+)
+
 
 def test_operations_column_offset_evaluation():
+    speckle_project_data = SpeckleProjectData(
+        projectId="9a9689bf01",
+        modelId="231110ac11-institute-var-2-ifc.ifc",
+        versionId="c13d21b3cf",
+        speckleServerUrl="http://latest.speckle.systems",
+    )
+    function_inputs = FunctionInputs(tolerance=0.02, echoLevel=1, scaleSpheres=False)
+    speckle_token = os.getenv("SPECKLE_TOKEN")
+    main(
+        speckle_project_data.json(by_alias=True),
+        function_inputs.json(by_alias=True),
+        speckle_token,
+    )
 
-    speckle_server = "insert"
-    speckle_token = "insert"
 
-    client_obj = Client(speckle_server, speckle_token)
-    stream_obj = Stream(client_obj, 0)
-    branch_obj = Branch(client_obj, stream_obj, 6)
-    commit_data = Commit.get_data(branch_obj, 0)
-
-    evaluation = ColumnOffsetEvaluation(commit_data = commit_data,
-                                        tolerance = 0.02,
-                                        echo_level = 0,
-                                        scale_spheres = False)
-    evaluation.run()
-
-    assert len(evaluation.commit_data["@Analysis_ColumnEccentricity"]) == 3
+if __name__ == ("__main__"):
+    test_operations_column_offset_evaluation()