3 different conda yaml and installation scripts

Author: yeshaokai

amadeusgpt/analysis_objects/event.py

@@ -540,8 +540,7 @@ def fuse_subgraph_by_kvs(
         For example, if there are two conditions to be met in the masks we look for locations that have overlap as 2
         """
         # retrieve all events that satisfy the conditions (k=v)
-        events = graph.traverse_by_kvs(merge_kvs)
-
+        events = graph.traverse_by_kvs(merge_kvs)        
         if not allow_more_than_2_overlap:
             assert (
                 Event.check_max_in_sum(events) <= number_of_overlap_for_fusion

amadeusgpt/app_utils.py

@@ -112,7 +112,7 @@ def __init__(self, amadeus_answer=None, json_entry=None):
             amadeus_answer = amadeus_answer.to_dict()
         self.data.update(amadeus_answer)
 
-    def render(self):
+    def render(self, debug = False):
         """
         We use the getter for better encapsulation
         overall structure of what to be rendered
@@ -180,9 +180,10 @@ def render(self):
                         st.markdown(f"Error: {qa_message['error_message']}\n ")
                         # Remind users we are fixing the error by self debuging
                         st.markdown(f"Let me try to fix the error by self-debugging\n ")
-                        for i in range(1):
-                            sandbox.llms["self_debug"].speak(sandbox)
+                        if not debug:
+                            sandbox.llms["self_debug"].speak(sandbox)                        
                             qa_message = sandbox.code_execution(qa_message)
+                            self.render(debug = True)
                     # do not need to execute the block one more time
                     if not self.rendered:
                         self.rendered = True

amadeusgpt/managers/animal_manager.py

@@ -212,6 +212,16 @@ def get_keypoints(self) -> ndarray:
         """
         Get the keypoints of animals. The shape is of shape  n_frames, n_individuals, n_kpts, n_dims
         """
+        use_superanimal = False
+        if use_superanimal:
+            import deeplabcut
+            from deeplabcut.modelzoo.video_inference import video_inference_superanimal
+            superanimal_name = 'superanimal_topviewmouse_hrnetw32'
+            video_inference_superanimal(videos = [self.config['video_info']['video_file_path']],
+                            superanimal_name = superanimal_name,
+                            video_adapt = False,
+                            dest_folder = 'temp_pose')
+
         ret = np.stack([animal.get_keypoints() for animal in self.animals], axis=1)
         return ret
 

amadeusgpt/managers/event_manager.py

@@ -440,10 +440,12 @@ def get_composite_events(
                         graphs.append(animal_animal_subgraph)
             # we then fuse events from different task programs that involve animal-object interactions
             for object_name in self.object_manager.get_object_names():
-
+                # if we strictly require the object needs to match, then EPM head dipping example won't work.
+                # so we cannot require objects to match. This causes some ambiguity.
                 animal_object_subgraph = EventGraph.fuse_subgraph_by_kvs(
                     graph,
-                    {"sender_animal_name": animal_name, "object_names": object_name},
+                    {"sender_animal_name": animal_name,},
+                      #"object_names": object_name},
                     number_of_overlap_for_fusion=2,
                 )
                 graphs.append(animal_object_subgraph)

amadeusgpt/programs/sandbox.py

@@ -389,15 +389,14 @@ def render_qa_message(self, qa_message):
         n_animals = behavior_analysis.animal_manager.get_n_individuals()
         bodypart_names = behavior_analysis.animal_manager.get_keypoint_names()
         visual_manager = behavior_analysis.visual_manager
-        plots = []
-
+        plots = []       
         if isinstance(function_rets, tuple):
             # could be plotting tuple
             if isinstance(function_rets[0], plt.Figure):
                 # this is for "return fig, ax"
                 plots.append(function_rets)
 
-            else:
+            else:               
                 for e in function_rets:
                     if isinstance(e, list) and len(e) > 0 and isinstance(e[0], BaseEvent):
                         # here we need to understand what we do with the events
@@ -521,8 +520,8 @@ def render_temp_message(query, sandbox):
         print("after code execution")
         print(len(qa_message["function_rets"]))
         events = qa_message["function_rets"]
-        for event in events:
-            print (event)
+       
+    sandbox.render_qa_message(qa_message)
 
     if qa_message["function_rets"] is not None:
         st.markdown(qa_message["function_rets"])
@@ -543,72 +542,80 @@ def render_temp_message(query, sandbox):
     # testing qa message
     from amadeusgpt.analysis_objects.object import ROIObject
     from amadeusgpt.main import create_amadeus
-
-    config = Config("amadeusgpt/configs/mabe_template.yaml")
+    import pickle
+    config = Config("amadeusgpt/configs/EPM_template.yaml")
 
     amadeus = create_amadeus(config)
     sandbox = amadeus.sandbox
-
-    def get_chases_events(config: Config):
-        '''
-        Parameters:
-        ----------
-        config: Config
-        '''
-        # create_analysis returns an instance of AnimalBehaviorAnalysis
-        analysis = create_analysis(config)
-
-        # Get events where the closest distance between animals is less than 40 pixels
-        closest_distance_events = analysis.get_animals_animals_events(
-            cross_animal_query_list=['closest_distance<40'],
-            bodypart_names=None,
-            otheranimal_bodypart_names=None,
-            min_window=1,
-            max_window=100000
-        )
-
-        # Get events where the angle between animals is less than 30 degrees
-        angle_events = analysis.get_animals_animals_events(
-            cross_animal_query_list=['relative_angle<30'],
-            bodypart_names=None,
-            otheranimal_bodypart_names=None,
-            min_window=1,
-            max_window=100000
-        )
-
-        print ('angle_events')
-        for event in angle_events:
-            print (event)
-        return angle_events
-
-        # Get events where the animal's speed is greater than 0.2
-        speed_events = analysis.get_animals_state_events(
-            query='speed>0.2',
-            bodypart_names=None,
-            min_window=1,
-            max_window=100000
-        )
-
-        # Combine the closest distance and angle events using logical AND
-        distance_angle_events = analysis.get_composite_events(
-            events_A=closest_distance_events,
-            events_B=angle_events,
-            composition_type='logical_and',
-            max_interval_between_sequential_events=0,
-            min_window=1,
-            max_window=100000
-        )
-
-        # Combine the result with the speed events using logical AND
-        chases_events = analysis.get_composite_events(
-            events_A=distance_angle_events,
-            events_B=speed_events,
-            composition_type='logical_and',
-            max_interval_between_sequential_events=0,
-            min_window=1,
-            max_window=100000
-        )
-
-        return chases_events
-
-    get_chases_events(config)
+    analysis = sandbox.exec_namespace["behavior_analysis"]
+    with open("temp_roi_objects.pickle", "rb") as f:
+        roi_objects = pickle.load(f)
+
+    for name, roi_object in roi_objects.items():
+        analysis.object_manager.add_roi_object(ROIObject(name, roi_object["Path"]))
+
+    render_temp_message("random query", sandbox)
+
+    # def get_head_dips_events(config: Config):
+    #     """
+    #     Identify and count the number of head_dips events.
+
+    #     Parameters:
+    #     ----------
+    #     config: Config
+
+    #     Returns:
+    #     -------
+    #     head_dips_events: List[BaseEvent]
+    #         List of events where head_dips behavior occurs.
+    #     num_bouts: int
+    #         Number of bouts for head_dips behavior.
+    #     """
+    #     # Create an instance of AnimalBehaviorAnalysis
+    #     analysis = create_analysis(config)
+
+    #     # Get events where mouse_center and neck are inside ROI0
+    #     mouse_center_neck_in_ROI0_events = analysis.get_animals_object_events(
+    #         object_name='ROI0',
+    #         query='overlap == True',
+    #         bodypart_names=['mouse_center', 'neck'],
+    #         min_window=1,
+    #         max_window=100000,
+    #         negate=False
+    #     )
+    #     # print ("mouse center neck in ROI0")
+    #     # print (len(mouse_center_neck_in_ROI0_events))
+    #     # for event in mouse_center_neck_in_ROI0_events:
+    #     #     print (event)
+
+    #     # Get events where head_midpoint is outside ROI1
+    #     head_midpoint_outside_ROI1_events = analysis.get_animals_object_events(
+    #         object_name='ROI1',
+    #         query='overlap == True',
+    #         bodypart_names=['head_midpoint'],
+    #         min_window=1,
+    #         max_window=100000,
+    #         negate=True
+    #     )
+    #     # print ('mouse head not in ROI1')
+    #     # print (len(head_midpoint_outside_ROI1_events))
+    #     # for event in head_midpoint_outside_ROI1_events:
+    #     #     print (event)
+
+    #     # Combine the events to define head_dips behavior
+    #     head_dips_events = analysis.get_composite_events(
+    #         events_A=mouse_center_neck_in_ROI0_events,
+    #         events_B=head_midpoint_outside_ROI1_events,
+    #         composition_type='logical_and',
+    #         max_interval_between_sequential_events=0,
+    #         min_window=1,
+    #         max_window=100000
+    #     )
+    #     print ('head dips events', len(head_dips_events))
+
+    #     # Count the number of bouts for head_dips behavior
+    #     num_bouts = len(head_dips_events)
+
+    #     return head_dips_events, num_bouts
+
+    # get_head_dips_events(config)

conda/amadesuGPT-cpu.yml

@@ -0,0 +1,10 @@
+# This environment can be used to install amadeusGPT
+name: amadeusgpt-cpu
+channels:
+    - defaults
+dependencies:
+    - python<3.10
+    - pytables==3.8.0
+    - hdf5
+    - pip
+    - jupyter

conda/amadesuGPT-gpu.yml

@@ -0,0 +1,10 @@
+# This environment can be used to install amadeusGPT
+name: amadeusgpt-gpu
+channels:
+    - defaults
+dependencies:
+    - python==3.10
+    - pytables==3.8.0
+    - hdf5
+    - pip
+    - jupyter

conda/amadesuGPT.yml conda/amadesuGPT-minimal.ymlconda/amadesuGPT.yml renamed to conda/amadesuGPT-minimal.yml

@@ -1,6 +1,5 @@
 # This environment can be used to install amadeusGPT
-
-name: amadeusgpt
+name: amadeusgpt-minimal
 channels:
     - defaults
 dependencies:

install_cpu.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+source /Users/shaokaiye/miniforge3/bin/activate
+conda env create -f conda/amadesuGPT-cpu.yml
+conda activate amadeusgpt-cpu
+conda install pytorch cpuonly -c pytorch
+
+pip install -e .[streamlit]

install_cpu_minimal.sh

@@ -0,0 +1,6 @@
+#!/bin/bash
+source /Users/shaokaiye/miniforge3/bin/activate
+conda env create -f conda/amadesuGPT-minimal.yml
+conda activate amadeusgpt-minimal
+
+pip install -e .[streamlit]