GH #2744: Fix installation on Python 3.12, 3.13

.github/workflows/github-actions-ci.yml

@@ -26,7 +26,7 @@ jobs:
     name: Lint
     runs-on: "ubuntu-latest"
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - name: flake8 linting
         run: |
           pip install flake8
@@ -43,28 +43,30 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        os: ["macos-latest", "windows-latest", "ubuntu-latest"]
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        os: ["ubuntu-latest"]
+        python-version: ["3.10", "3.13"]
+        include:
+          - os: "macos-latest"
+            python-version: "3.13"
+          - os: "windows-latest"
+            python-version: "3.13"
       fail-fast: false
-    defaults:
-      run:
-        shell: bash -l {0}
     steps:
-      - uses: actions/checkout@v2
-      - uses: conda-incubator/setup-miniconda@v2
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
         with:
-          auto-update-conda: true
           python-version: ${{ matrix.python-version }}
-          activate-environment: test-env
+          cache: pip
+          cache-dependency-path: |
+            requirements.txt
+            test_requirements.txt
       - name: Install
         run: |
-          conda activate test-env
-          pip install codecov
           pip install -r test_requirements.txt
           pip install .
       - name: Test
         run: |
-          py.test --cov=allensdk -n 4
+          python -m pytest -n 4 ${{ (matrix.os == 'ubuntu-latest' && matrix.python-version == '3.13') && '--cov=allensdk' || '' }}
 
   onprem:
     name: python ${{ matrix.image }} on-prem test
@@ -73,7 +75,7 @@ jobs:
       matrix:
         image: ["allensdk_local_py38:latest"]
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
       - name: run test in docker
         run: |
           docker run \

.github/workflows/nightly.yml

@@ -13,7 +13,7 @@ jobs:
         image: ["allensdk_local_py38:latest"]
         branch: ["master", "rc/**"]
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v4
         with:
           ref: ${{ matrix.branch }}
       - name: run test in docker

.github/workflows/notebook_runner.yml

@@ -1,23 +1,27 @@
 name: Notebooks
 on:
-  pull_request:
+  push:
     branches:
       - master
 jobs:
   run_notebooks:
     name: Notebook runner
     strategy:
       matrix:
-        os: ["ubuntu-latest"]
-        python-version: ["3.8"]
+        python-version: ["3.13"]
       fail-fast: false
-    runs-on: ${{ matrix.os }}
+    runs-on: ubuntu-latest-8x
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Set up Python
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
+          cache: pip
+          cache-dependency-path: |
+            requirements.txt
+            dev_requirements.txt
+            notebook_requirements.txt
       - name: Install
         run: |
           pip install -r requirements.txt

allensdk/brain_observatory/behavior/behavior_project_cache/project_apis/data_io/behavior_project_cloud_api.py

@@ -187,7 +187,7 @@ def _get_ophys_session_table(self):
         df = sanitize_data_columns(session_table_path, {"mouse_id": str})
         # Add UTC to match DateOfAcquisition object.
         df["date_of_acquisition"] = pd.to_datetime(
-            df["date_of_acquisition"], utc="True"
+            df["date_of_acquisition"], format="ISO8601", utc=True
         )
         df = enforce_df_int_typing(
             input_df=df, int_columns=VBO_INTEGER_COLUMNS, use_pandas_type=True
@@ -217,7 +217,7 @@ def _get_behavior_session_table(self):
         df = sanitize_data_columns(session_table_path, {"mouse_id": str})
         # Add UTC to match DateOfAcquisition object.
         df["date_of_acquisition"] = pd.to_datetime(
-            df["date_of_acquisition"], utc="True"
+            df["date_of_acquisition"], format="ISO8601", utc=True
         )
         df = enforce_df_int_typing(
             input_df=df, int_columns=VBO_INTEGER_COLUMNS, use_pandas_type=True
@@ -252,7 +252,7 @@ def _get_ophys_experiment_table(self):
         df = sanitize_data_columns(experiment_table_path, {"mouse_id": str})
         # Add UTC to match DateOfAcquisition object.
         df["date_of_acquisition"] = pd.to_datetime(
-            df["date_of_acquisition"], utc="True"
+            df["date_of_acquisition"], format="ISO8601", utc=True
         )
         df = enforce_df_int_typing(
             input_df=df, int_columns=VBO_INTEGER_COLUMNS, use_pandas_type=True

allensdk/brain_observatory/behavior/behavior_project_cache/project_apis/data_io/behavior_project_lims_api.py

@@ -511,7 +511,7 @@ def get_ophys_session_table(self) -> pd.DataFrame:
         )
         # Make date time explicitly UTC.
         table["date_of_acquisition"] = pd.to_datetime(
-            table["date_of_acquisition"], utc=True
+            table["date_of_acquisition"], format="ISO8601", utc=True
         )
 
         # Fill NaN values of imaging_plane_group_count with zero to match
@@ -554,7 +554,7 @@ def get_ophys_experiment_table(self) -> pd.DataFrame:
         """
         df = self._get_ophys_experiment_table()
         df["date_of_acquisition"] = pd.to_datetime(
-            df["date_of_acquisition"], utc=True
+            df["date_of_acquisition"], format="ISO8601", utc=True
         )
         # Set type to pandas.Int64 to enforce integer typing and not revert to
         # float.
@@ -581,7 +581,7 @@ def get_behavior_session_table(self) -> pd.DataFrame:
         summary_tbl = self._get_behavior_summary_table()
         # Add UTC time zone to match timezone from DateOfAcquisition object.
         summary_tbl["date_of_acquisition"] = pd.to_datetime(
-            summary_tbl["date_of_acquisition"], utc=True
+            summary_tbl["date_of_acquisition"], format="ISO8601", utc=True
         )
         # Query returns float typing of age_in_days. Convert to int to match
         # typing of the Age data_object.

allensdk/brain_observatory/behavior/behavior_project_cache/tables/metadata_table_schemas.py

@@ -78,7 +78,7 @@ class BehaviorSessionMetadataSchema(RaisingSchema):
     def convert_date_time(self, data, **kwargs):
         """Change date_of_acquisition to a date time type from string."""
         data["date_of_acquisition"] = pd.to_datetime(
-            data["date_of_acquisition"], utc=True
+            data["date_of_acquisition"], format="ISO8601", utc=True
         )
         return data
 

allensdk/brain_observatory/behavior/data_objects/cell_specimens/cell_specimens.py

@@ -857,13 +857,13 @@ def _validate_traces(
             if traces is None:
                 continue
             # validate traces contain expected roi ids
-            if not np.in1d(traces.value.index, cell_roi_ids).all():
+            if not np.isin(traces.value.index, cell_roi_ids).all():
                 raise RuntimeError(
                     f"{traces.name} contains ROI IDs that "
                     f"are not in "
                     f"cell_specimen_table.cell_roi_id"
                 )
-            if not np.in1d(cell_roi_ids, traces.value.index).all():
+            if not np.isin(cell_roi_ids, traces.value.index).all():
                 raise RuntimeError(
                     f"cell_specimen_table contains ROI IDs "
                     f"that are not in {traces.name}"

allensdk/brain_observatory/behavior/data_objects/metadata/behavior_metadata/behavior_metadata.py

@@ -149,7 +149,7 @@ def get_task_parameters(data: Dict) -> Dict:
     # displayed stimuli (no flashes).
 
     if stim_duration is None:
-        stim_duration = np.NaN
+        stim_duration = np.nan
     else:
         stim_duration = stim_duration[0]
 

allensdk/brain_observatory/behavior/data_objects/running_speed/running_acquisition.py

@@ -129,7 +129,7 @@ def from_nwb(
         cls,
         nwbfile: NWBFile
     ) -> "RunningAcquisition":
-        running_module = nwbfile.modules['running']
+        running_module = nwbfile.processing['running']
         dx_interface = running_module.get_data_interface('dx')
 
         dx = dx_interface.data

allensdk/brain_observatory/behavior/data_objects/running_speed/running_speed.py

@@ -188,7 +188,7 @@ def from_nwb(
         nwbfile: NWBFile,
         filtered=True
     ) -> "RunningSpeed":
-        running_module = nwbfile.modules['running']
+        running_module = nwbfile.processing['running']
         interface_name = 'speed' if filtered else 'speed_unfiltered'
         running_interface = running_module.get_data_interface(interface_name)
 

allensdk/brain_observatory/behavior/data_objects/stimuli/templates.py

@@ -208,7 +208,7 @@ def _add_image_index_to_nwb(
         image_index = IndexSeries(
             name=nwb_template.name,
             data=stimulus_index['image_index'].values,
-            unit='None',
+            unit='N/A',
             indexed_timeseries=nwb_template,
             timestamps=stimulus_index['start_time'].values)
         nwbfile.add_stimulus(image_index)

allensdk/brain_observatory/behavior/data_objects/task_parameters.py

@@ -223,7 +223,7 @@ def _parse_stimulus_key():
         # displayed stimuli (no flashes).
 
         if stim_duration is None:
-            stim_duration = np.NaN
+            stim_duration = np.nan
         else:
             stim_duration = stim_duration[0]
         return stim_duration

allensdk/brain_observatory/behavior/data_objects/trials/trial.py

@@ -415,7 +415,7 @@ def add_change_time(self, trial_dict: dict) -> Tuple[dict, float]:
         """
         change_frame = trial_dict['change_frame']
         if np.isnan(change_frame):
-            change_time = np.NaN
+            change_time = np.nan
         else:
             change_frame = int(change_frame)
             change_time = self._stimulus_timestamps.value[change_frame]

allensdk/brain_observatory/behavior/stimulus_processing.py

@@ -104,9 +104,9 @@ def get_images_dict(pkl) -> Dict:
             meta = dict(
                 image_category=cat.decode("utf-8"),
                 image_name=img_name.decode("utf-8"),
-                orientation=np.NaN,
-                phase=np.NaN,
-                spatial_frequency=np.NaN,
+                orientation=np.nan,
+                phase=np.nan,
+                spatial_frequency=np.nan,
                 image_index=ii,
             )
 
@@ -341,9 +341,9 @@ def get_stimulus_metadata(pkl) -> pd.DataFrame:
             "image_category": ["omitted"],
             "image_name": ["omitted"],
             "image_set": ["omitted"],
-            "orientation": np.NaN,
-            "phase": np.NaN,
-            "spatial_frequency": np.NaN,
+            "orientation": np.nan,
+            "phase": np.nan,
+            "spatial_frequency": np.nan,
             "image_index": len(stimulus_index_df),
         }
     )

allensdk/brain_observatory/behavior/swdb/behavior_project_cache.py

@@ -419,7 +419,7 @@ def get_stimulus_templates(self):
         # What we really want is a dict with image_name as key
         template_dict = {}
         image_index_names = self.get_image_index_names()
-        for image_index, image_name in image_index_names.iteritems():
+        for image_index, image_name in image_index_names.items():
             if image_name != 'omitted':
                 template_dict.update(
                     {image_name: stimulus_template_array[image_index, :, :]})

allensdk/brain_observatory/behavior/swdb/save_extended_stimulus_presentations_df.py

@@ -116,7 +116,7 @@ def get_extended_stimulus_presentations(session):
     )
     block_repetition_number = np.copy(block_inds)
 
-    for image_name, image_blocks in blocks_per_image.iteritems():
+    for image_name, image_blocks in blocks_per_image.items():
         if image_name != "omitted":
             for ind_block, block_number in enumerate(image_blocks):
                 # block_rep_number starts as a copy of block_inds, so we can

allensdk/brain_observatory/chisquare_categorical.py

@@ -71,7 +71,7 @@ def compute_chi_shuffle(
 def stim_table_to_categories(stim_table, columns, verbose=False):
     # get the categories for all sweeps with each unique combination of
     #   parameters in 'columns' being one category
-    # sweeps with non-finite values in ANY column (e.g. np.NaN) are labeled
+    # sweeps with non-finite values in ANY column (e.g. np.nan) are labeled
     #   as blank sweeps (category = -1)
     # TODO: Replace with EcephysSession.get_stimulus_conditions
 

allensdk/brain_observatory/demixer.py

@@ -103,6 +103,8 @@ def _demix_point(source_frame: np.ndarray, mask_traces: np.ndarray,
     overlap = flat_masks.dot(weighted_masks.T).toarray()
     try:
         demix_traces = linalg.solve(overlap, mask_weighted_trace)
+        if not np.all(np.isfinite(demix_traces)):
+            raise linalg.LinAlgError("non-finite result")
     except linalg.LinAlgError:
         logging.warning("Singular matrix, using least squares to solve.")
         x, _, _, _ = linalg.lstsq(overlap, mask_weighted_trace)

allensdk/brain_observatory/dff.py

@@ -325,7 +325,7 @@ def noise_std(x, noise_kernel_length=31, positive_peak_scale=1.5,
     """Robust estimate of the standard deviation of the trace noise."""
     _check_kernel(noise_kernel_length, len(x))
     if any(np.isnan(x)):
-        return np.NaN
+        return np.nan
     x = x - median_filter(x, noise_kernel_length, mode='constant')
     # first pass removing big pos peak outliers
     x = x[x < positive_peak_scale*np.abs(x.min())]

allensdk/brain_observatory/drifting_gratings.py

@@ -247,8 +247,8 @@ def get_peak(self):
                          np.abs(subset_stat[str(nc)].mean()))
 
             else:
-                peak.p_run_dg.iloc[nc] = np.NaN
-                peak.run_modulation_dg.iloc[nc] = np.NaN
+                peak.p_run_dg.iloc[nc] = np.nan
+                peak.run_modulation_dg.iloc[nc] = np.nan
 
             # reliability
             subset = self.sweep_response[
@@ -264,7 +264,7 @@ def get_peak(self):
             for i in range(len(subset)):
                 for j in range(len(subset)):
                     if i >= j:
-                        mask[i, j] = np.NaN
+                        mask[i, j] = np.nan
             corr_matrix *= mask
             peak.reliability_dg.iloc[nc] = np.nanmean(corr_matrix)
 

allensdk/brain_observatory/ecephys/align_timestamps/__main__.py

@@ -46,7 +46,7 @@ def align_timestamps(args):
             min_time = probe_split_times[idx]
 
             if idx == (len(probe_split_times) - 1):
-                max_time = np.Inf
+                max_time = np.inf
             else:
                 max_time = probe_split_times[idx + 1]
 

allensdk/brain_observatory/ecephys/align_timestamps/barcode_sync_dataset.py

@@ -63,10 +63,10 @@ def get_barcode_table(self, **barcode_kwargs):
 
         """
         warnings.warn(
-            np.VisibleDeprecationWarning(
-                """This function is deprecated as unecessary (and slated for
-                removal). Instead, simply use extract_barcodes."""
-            )
+            """This function is deprecated as unecessary (and slated for
+            removal). Instead, simply use extract_barcodes.""",
+            DeprecationWarning,
+            stacklevel=2,
         )
 
         barcode_times, barcodes = self.extract_barcodes(**barcode_kwargs)

allensdk/brain_observatory/ecephys/data_objects/trials.py

@@ -87,7 +87,7 @@ def add_change_time(self, trial_dict: dict) -> Tuple[dict, float]:
         """
         change_frame = trial_dict['change_frame']
         if np.isnan(change_frame):
-            change_time = np.NaN
+            change_time = np.nan
         else:
             no_delay = self._stimulus_timestamps.subtract_monitor_delay()
             change_frame = int(change_frame)

allensdk/brain_observatory/ecephys/ecephys_project_api/http_engine.py

@@ -118,15 +118,20 @@ def __init__(
 
         super(AsyncHttpEngine, self).__init__(scheme, host, **kwargs)
 
+        self._session = None
         if session:
-            self.session = session
+            self._session = session
             warnings.warn(
                 "Recieved preconstructed session, ignoring timeout parameter."
             )
-        else:
-            self.session = aiohttp.ClientSession(
+
+    @property
+    def session(self):
+        if self._session is None:
+            self._session = aiohttp.ClientSession(
                 timeout=aiohttp.client.ClientTimeout(self.timeout)
             )
+        return self._session
 
     async def _stream_coroutine(
         self, 
@@ -169,10 +174,10 @@ def stream(
         return functools.partial(self._stream_coroutine, route)
 
     def __del__(self):
-        if hasattr(self, "session"):
+        if getattr(self, "_session", None) is not None:
             nest_asyncio.apply()
             loop = asyncio.get_event_loop()
-            loop.run_until_complete(self.session.close())
+            loop.run_until_complete(self._session.close())
 
     @staticmethod
     def write_bytes(