Update imports_utils.py

imports_utils.py

@@ -319,6 +319,64 @@ def getDataFromNotion(
 
 
 
+def getDataFromGrasshopper(
+        inputNameMatrix,
+        inputNameLanduse,
+        inputNameAttributeMapper,
+        inputNameLanduseMapper,        
+        inputNameAlpha = "alpha",
+        inputNameThreshold = "threshold"    
+        ):
+
+    if inputNameMatrix is not None:
+        matrix = inputs['input'][inputNameMatrix]
+        dfMatrix_gh = pd.DataFrame(matrix).T
+        dfMatrix_gh = dfMatrix_gh.apply(pd.to_numeric, errors='coerce')
+        dfMatrix_gh = dfMatrix_gh.replace([np.inf, -np.inf], 10000).fillna(0)
+        dfMatrix_gh = dfMatrix_gh.round(0).astype(int)
+    else:
+        matrix = None
+
+    if inputNameLanduse is not None:
+        landuses = inputs['input'][inputNameLanduse] 
+        dfLanduses_gh = pd.DataFrame(landuses).T
+        dfLanduses_gh = dfLanduses_gh.apply(pd.to_numeric, errors='coerce')
+        dfLanduses_gh = dfLanduses_gh.replace([np.inf, -np.inf], 0).fillna(0)  # cleaning function?
+        dfLanduses_gh = dfLanduses_gh.round(0).astype(int)
+    else:
+        landuses = None
+    
+    
+    if inputNameAttributeMapper is not None:
+        attributeMapperDict_gh = inputs['input'][inputNameAttributeMapper]
+    else:
+        attributeMapperDict_gh = None
+
+    if inputNameLanduseMapper is not None:  
+        landuseMapperDict_gh = inputs['input'][inputNameLanduseMapper]
+    else:
+        landuseMapperDict_gh = None
+
+
+    if inputNameAlpha is not None:
+        alpha = inputs['input'][inputNameAlpha]
+        if alpha is None:
+            alpha = alphaDefault
+    else:
+        alpha = alphaDefault
+        
+    if inputNameThreshold is not None:
+        threshold = inputs['input'][inputNameThreshold]
+        if threshold is None:
+            threshold = thresholdDefault
+    else:
+        threshold = thresholdDefault
+
+    
+    return dfMatrix_gh, dfLanduses_gh, attributeMapperDict_gh, landuseMapperDict_gh, alpha, threshold
+                           
+
+
 def splitDictByStrFragmentInColumnName(original_dict, substrings):
     result_dicts = {substring: {} for substring in substrings}
     for key, nested_dict in original_dict.items():