Build array conversion into DictMixin (OpenwaterHealth#119)

This is just a convenience so when we add new numpy array fields to
dataclasses we don't have to manually build the numpy array conversion
into the `from_dict` of the class

Author: ebrahimebrahim

src/openlifu/db/session.py

@@ -138,13 +138,13 @@ def from_dict(d:Dict):
         if 'volume' in d:
             raise ValueError("Sessions no longer recognize a volume attribute -- it is now volume_id.")
         if 'array_transform' in d:
-            d['array_transform'] = ArrayTransform(np.array(d['array_transform']['matrix']), d['array_transform']['units'])
+            d['array_transform'] = ArrayTransform.from_dict(d['array_transform'])
         if 'transducer_tracking_results' in d:
             d['transducer_tracking_results'] = [
                 TransducerTrackingResult(
                     t['photoscan_id'],
-                    ArrayTransform(np.array(t['transducer_to_photoscan_transform']['matrix']),t['transducer_to_photoscan_transform']['units']),
-                    ArrayTransform(np.array(t['photoscan_to_volume_transform']['matrix']), t['photoscan_to_volume_transform']['units']),
+                    ArrayTransform.from_dict(t['transducer_to_photoscan_transform']),
+                    ArrayTransform.from_dict(t['photoscan_to_volume_transform']),
                     t['transducer_to_photoscan_tracking_approved'],
                     t['photoscan_to_volume_tracking_approved']
                     )
@@ -161,7 +161,7 @@ def from_dict(d:Dict):
             for target_id,(approval,transforms) in d['virtual_fit_results'].items():
                 d['virtual_fit_results'][target_id] = (
                     approval,
-                    [ArrayTransform(np.array(t_dict["matrix"]), t_dict["units"]) for t_dict in transforms],
+                    [ArrayTransform.from_dict(t_dict) for t_dict in transforms],
                 )
         if isinstance(d['markers'], list):
             if len(d['markers'])>0 and isinstance(d['markers'][0], dict):

src/openlifu/geo.py

@@ -8,6 +8,7 @@
 import numpy as np
 import vtk
 
+from openlifu.util.dict_conversion import DictMixin
 from openlifu.util.units import getunitconversion
 
 
@@ -140,7 +141,7 @@ def to_json(self, compact:bool) -> str:
 
 
 @dataclass
-class ArrayTransform:
+class ArrayTransform(DictMixin):
     """An affine transform with a unit string, often intended to represent how a transducer array is positionsed in space."""
 
     matrix: np.ndarray

src/openlifu/util/dict_conversion.py

@@ -1,13 +1,15 @@
 from __future__ import annotations
 
-from dataclasses import asdict, dataclass
-from typing import Any, Dict, Type, TypeVar
+from dataclasses import asdict, dataclass, fields
+from typing import Any, Dict, Type, TypeVar, get_origin
+
+import numpy as np
 
 T = TypeVar('T', bound='DictMixin')
 
 @dataclass
 class DictMixin:
-    """Mixin for basic conversion to and from dict."""
+    """Mixin for basic conversion of a dataclass to and from dict."""
     def to_dict(self) -> Dict[str,Any]:
         """
         Convert the object to a dictionary
@@ -27,4 +29,12 @@ def from_dict(cls : Type[T], parameter_dict:Dict[str,Any]) -> T:
         """
         if "class" in parameter_dict:
             parameter_dict.pop("class")
-        return cls(**parameter_dict)
+        new_object = cls(**parameter_dict)
+
+        # Convert anything that should be a numpy array to numpy
+        for field in fields(cls):
+            # Note that sometimes "field.type" is a string rather than a type due to the "from annotations import __future__" stuff
+            if get_origin(field.type) is np.ndarray or field.type is np.ndarray or "np.ndarray" in field.type:
+                setattr(new_object, field.name, np.array(getattr(new_object,field.name)))
+
+        return new_object