Merge branch 'main' of https://github.com/SainsburyWellcomeCentre/aeo…

…n_mecha into dev

CITATION.cff

@@ -0,0 +1,8 @@
+cff-version: 1.0.0
+message: "If you use this software, please cite it as below."
+authors: 
+-  family-names: "Sainsbury Wellcome Centre Foraging Behaviour Working Group"
+title: "Aeon: An open-source platform to study the neural basis of ethological behaviours over naturalistic timescales"
+doi: 10.5281/zenodo.8413142
+date-released: 2023-10-05
+url: https://github.com/SainsburyWellcomeCentre/aeon_docs

README.md

@@ -73,4 +73,12 @@ Ensure you stay in the `~/ProjectAeon/aeon_mecha` directory for the rest of the
     - `docs/using_online_dashboard.md` : Instructions for connecting to Aeon's online dashboard
 - `env_config/` : Configuration files for the Aeon Python environment
 - `tests/` : Unit and integration tests
-    - `tests/data` : Data used by tests
+    - `tests/data` : Data used by tests
+
+## Citation Policy
+
+If you use this software, please cite it as below:
+
+Sainsbury Wellcome Centre Foraging Behaviour Working Group. (2023). Aeon: An open-source platform to study the neural basis of ethological behaviours over naturalistic timescales,  https://doi.org/10.5281/zenodo.8413142
+
+[![DOI](https://zenodo.org/badge/485512362.svg)](https://zenodo.org/badge/latestdoi/485512362)

aeon/__init__.py

@@ -1,4 +1,4 @@
-from importlib_metadata import PackageNotFoundError, version
+from importlib.metadata import PackageNotFoundError, version
 
 try:
     # Change here if project is renamed and does not equal the package name

aeon/schema/social.py

@@ -33,15 +33,9 @@ def read(
         """Reads data from the Harp-binarized tracking file."""
         # Get config file from `file`, then bodyparts from config file.
         model_dir = Path(file.stem.replace("_", "/")).parent
-<<<<<<< HEAD
         config_file_dir = ceph_proc_dir / model_dir
         if not config_file_dir.exists():
             raise FileNotFoundError(f"Cannot find model dir {config_file_dir}")
-=======
-        # `ceph_proc_dir` typically
-        config_file_dir = Path(ceph_proc_dir) / model_dir
-        assert config_file_dir.exists(), f"Cannot find model dir {config_file_dir}"
->>>>>>> b9a1e3f... Blackened and ruffed
         config_file = get_config_file(config_file_dir)
         parts = self.get_bodyparts(config_file)
 
@@ -52,7 +46,6 @@ def read(
         self.columns = columns
         data = super().read(file)
 
-<<<<<<< HEAD
         # Drop any repeat parts.
         unique_parts, unique_idxs = np.unique(parts, return_index=True)
         repeat_idxs = np.setdiff1d(np.arange(len(parts)), unique_idxs)
@@ -63,8 +56,6 @@ def read(
             data = data.iloc[:, keep_part_col_idxs]
             parts = unique_parts
 
-=======
->>>>>>> b9a1e3f... Blackened and ruffed
         # Set new columns, and reformat `data`.
         n_parts = len(parts)
         part_data_list = [pd.DataFrame()] * n_parts
@@ -102,21 +93,13 @@ def get_config_file(
     """Returns the config file from a model's config directory."""
     if config_file_names is None:
         config_file_names = ["confmap_config.json"]  # SLEAP (add for other trackers to this list)
-<<<<<<< HEAD
     config_file = None
-=======
-    config_file = Path()
->>>>>>> b9a1e3f... Blackened and ruffed
     for f in config_file_names:
         if (config_file_dir / f).exists():
             config_file = config_file_dir / f
             break
-<<<<<<< HEAD
     if config_file is None:
-         raise FileNotFoundError(f"Cannot find config file in {config_file_dir}")
-=======
-    assert config_file.is_file(), f"Cannot find config file in {config_file_dir}"
->>>>>>> b9a1e3f... Blackened and ruffed
+        raise FileNotFoundError(f"Cannot find config file in {config_file_dir}")
     return config_file
 
 

docs/env_setup/remote/miniconda_conda_remote_setup.md

@@ -14,5 +14,5 @@ conda env update -f env_config/env_dev.yml
     - `conda activate aeon`: activates the virtual environment; any commands now run within this terminal will take place within the virtual environment.
     - `conda deactivate aeon`: deactivates the virtual environment.
 4. (Optional) Add commands to the `.profile` file to add miniconda as an environment module and Bonsai and its dependencies to your system path on startup (this will be initialized each time you SSH into the HPC).    
-    - Copy the commands in the `.profile_example` file in this folder to your HPC home directory `.profile` file.
+    - Copy the commands in the `.profile_example` file in this folder to your HPC home directory `.profile` file (you will have to create this file if it doesn't already exist).
 5. For instructions on developing within the `aeon` environment, see [`developing_on_hpc.md`](./developing_on_hpc.md)

pyproject.toml

@@ -27,7 +27,6 @@ dependencies = [
   "dotmap",
   "fastparquet",
   "graphviz",
-  "importlib_metadata",
   "ipykernel",
   "jupyter",
   "jupyterlab",

tests/io/test_api.py

@@ -1,13 +1,9 @@
-<<<<<<< HEAD
 from pathlib import Path
 
-=======
->>>>>>> b9a1e3f... Blackened and ruffed
 import pandas as pd
 import pytest
 from pytest import mark
 
-<<<<<<< HEAD
 import aeon
 from aeon.schema.dataset import exp02
 
@@ -18,63 +14,34 @@
 @mark.api
 def test_load_start_only():
     data = aeon.load(nonmonotonic_path, exp02.Patch2.Encoder, start=pd.Timestamp("2022-06-06T13:00:49"))
-=======
-import aeon.io.api as aeon
-from aeon.schema.dataset import exp02
-
-
-@mark.api
-def test_load_start_only():
-    data = aeon.load(
-        "./tests/data/nonmonotonic", exp02.Patch2.Encoder, start=pd.Timestamp("2022-06-06T13:00:49")
-    )
->>>>>>> b9a1e3f... Blackened and ruffed
     assert len(data) > 0
 
 
 @mark.api
 def test_load_end_only():
     data = aeon.load(
-<<<<<<< HEAD
         nonmonotonic_path, exp02.Patch2.Encoder, end=pd.Timestamp("2022-06-06T13:00:49")
-=======
-        "./tests/data/nonmonotonic", exp02.Patch2.Encoder, end=pd.Timestamp("2022-06-06T13:00:49")
->>>>>>> b9a1e3f... Blackened and ruffed
     )
     assert len(data) > 0
 
 
 @mark.api
 def test_load_filter_nonchunked():
-<<<<<<< HEAD
     data = aeon.load(
         nonmonotonic_path, exp02.Metadata, start=pd.Timestamp("2022-06-06T09:00:00")
     )
-=======
-    data = aeon.load("./tests/data/nonmonotonic", exp02.Metadata, start=pd.Timestamp("2022-06-06T09:00:00"))
->>>>>>> b9a1e3f... Blackened and ruffed
     assert len(data) > 0
 
 
 @mark.api
 def test_load_monotonic():
-<<<<<<< HEAD
     data = aeon.load(monotonic_path, exp02.Patch2.Encoder)
     assert len(data) > 0 and data.index.is_monotonic_increasing
 
-=======
-    data = aeon.load("./tests/data/monotonic", exp02.Patch2.Encoder)
-    assert data.index.is_monotonic_increasing
->>>>>>> b9a1e3f... Blackened and ruffed
-
 
 @mark.api
 def test_load_nonmonotonic():
-<<<<<<< HEAD
     data = aeon.load(nonmonotonic_path, exp02.Patch2.Encoder)
-=======
-    data = aeon.load("./tests/data/nonmonotonic", exp02.Patch2.Encoder)
->>>>>>> b9a1e3f... Blackened and ruffed
     assert not data.index.is_monotonic_increasing