Merge branch 'develop' into jprince127-patch-1

.flake8

@@ -0,0 +1,2 @@
+[flake8]
+exclude = .venv

.github/workflows/build.yml

@@ -30,15 +30,11 @@ jobs:
         if: ${{ startsWith(matrix.os, 'windows') }}
         uses: FedericoCarboni/setup-ffmpeg@v3
         id: setup-ffmpeg
-      - name: Install Forest
-        run: pip install -e .
-      - name: Install dev dependencies
-        run: pip install -r requirements.txt
+      - name: Install Forest and optional development dependencies
+        run: pip install -e ".[dev]"
       - name: Run code style checking
         run: flake8
       - name: Run static type checking
         run: mypy -p forest
-      - name: Run legacy tests
-        run: python -m unittest tests/imports.py
-      - name: Run pytest suite
+      - name: Run the test suite
         run: pytest

.gitignore

@@ -1,13 +1,15 @@
 __pycache__/
+dist/
+forest_analysis.egg-info/
+
+.vagrant/
 .venv/
+venv/
 .DS_Store
 
 # IntelliJ, VsCode project files
-.idea
-.vscode
-
-# for installing Forest in editable mode when developing
-/forest.egg-info/
+.idea/
+.vscode/
 
 #We don't want to add data to github
 /tutorials/data/

README.md

@@ -1,13 +1,14 @@
 [![build](https://github.com/onnela-lab/forest/actions/workflows/build.yml/badge.svg)](https://github.com/onnela-lab/forest/actions/workflows/build.yml)
 [![Documentation Status](https://readthedocs.org/projects/forest-docs/badge/)](https://forest.beiwe.org/en/latest/)
 
-<img width="264" height="99" src="forest-logo-color.png" alt="Forest logo">
+<!--- using a URL to display logo on PyPI --->
+<img width="264" height="99" src="https://raw.githubusercontent.com/onnela-lab/forest/main/forest-logo-color.png" alt="Forest logo">
 
 The Onnela Lab at the Harvard T.H. Chan School of Public Health has developed the Forest library to analyze smartphone-based high-throughput digital phenotyping data. The main intellectual challenge in smartphone-based digital phenotyping has moved from data collection to data analysis. Our research focuses on the development of mathematical and statistical methods for analyzing intensive high-dimensional data. We are actively developing the Forest library for analyzing smartphone-based high-throughput digital phenotyping data collected with the [Beiwe](https://github.com/onnela-lab/beiwe-backend) platform. Forest will implement our methods for analyzing Beiwe data as a Python package and is released under the BSD-3 open-source license. The Forest library will continue to grow over the coming years as we develop new analytical methods.
 
 Forest can be run locally but is also integrated into the Beiwe back-end on AWS, consistent with the preferred big-data computing paradigm of moving computation to the data. Integrated with Beiwe, Forest can be used to generate on-demand analytics, most importantly daily or hourly summary statistics of collected data, which are stored in a relational database on AWS. The system also implements an API for Tableau, which supports the creation of customizable workbooks and dashboards to view data summaries and troubleshoot any issues with data collection. Tableau is commercial software but is available under free viewer licenses and may be free to academic users for the first year (see Tableau for more information).
 
-For more detailed info on specific subpackages, see our [Documentation](https://forest.beiwe.org). Please note that Forest uses Python 3.11.
+For more detailed info on specific subpackages, see our [Documentation](https://forest.beiwe.org).
 
 # Description
 
@@ -30,13 +31,13 @@ Output: typically summary files
 
 # Usage
 
-To install, clone this repository to a local directory and then:
+Please note that Forest uses Python 3.11. To install, clone this repository to a local directory and then:
 
 ```console
 pip install path/to/forest
 ```
 
-Alternatively, [install directly from github](https://pip.pypa.io/en/stable/reference/pip_install/#git) with `pip`. As the repo is public, it won't prompt you to login. If you've used forest in the past, it might be prudent to do a '''pip uninstall forest''' first.
+Alternatively, [install directly from GitHub](https://pip.pypa.io/en/stable/cli/pip_install/#examples) with `pip`. As the repo is public, it won't prompt you to login. If you've used forest in the past, it might be prudent to do a `pip uninstall forest` first.
 
 ```console
 pip install git+https://github.com/onnela-lab/forest
@@ -46,7 +47,7 @@ To immediately test out forest, adapt the filepaths in the code below and run:
 
 ```python
 # Currently, all imports from `forest` must be explicit.  For the below example you need to import the following
-# In future, it would be great to have all functions import automatically
+# In the future, it would be great to have all functions import automatically
 import datetime
 
 from forest.bonsai.simulate_log_data import sim_log_data

docs/source/development.md

@@ -4,10 +4,9 @@ Information for contributors
 
 ## Quick start
 * Change current directory to the top level of your local Forest repository
-* Install Forest in editable mode: `pip install -e .`
-* Install development tools: `pip install -r requirements.txt`
+* Install Forest in editable mode along with development tools: `pip install -e ".[dev]"`
 * Run code style checks: `flake8`
-* Run type hint checks: `mypy -p forest`
+* Run type hint checks: `mypy`
 * Run test suite: `pytest`
 
 ### Documentation
@@ -44,6 +43,23 @@ Open `docs/_build/html/index.html` in a web browser to check the results
 * Use the [logging module](https://docs.python.org/3/library/logging.html) instead of `print()`
 * [Formatting log messages](http://reinout.vanrees.org/weblog/2015/06/05/logging-formatting.html): `logger.info("%s went %s wrong", 42, 'very')`
 * Continue writing code and comments all the way until the end of the line then indent appropriately
+* [Packaging Python Projects](https://packaging.python.org/en/latest/tutorials/packaging-projects)
+
+### Packaging and distribution
+
+#### Python Package Index
+* Use [TestPyPI](https://test.pypi.org/) for testing that your package can be uploaded, downloaded, and installed correctly
+* [Register an account](https://test.pypi.org/account/register/)
+* [Create an API token](https://test.pypi.org/manage/account/#api-tokens) (setting the "Scope" to "Entire account")
+* [Add API token](https://packaging.python.org/en/latest/specifications/pypirc/#using-a-pypi-token) to your `$HOME/.pypirc` file
+* Generate distribution archives: `python -m build`
+* Check the results: `twine check dist/*`
+* Upload distribution archives:
+  * TestPyPI: `twine upload --repository testpypi dist/*`
+  * PyPI: `twine upload dist/*`
+* Install from TestPyPI to verify:
+  * TestPyPI: `pip install --index-url https://test.pypi.org/simple/ --no-deps forest-analysis`
+  * PyPI: `pip install forest-analysis`
 
 ## GitHub
 

mypy.ini

@@ -1,4 +1,6 @@
 [mypy]
+mypy_path = src
+packages = forest
 python_version = 3.11
 
 [mypy-holidays]

pyproject.toml

@@ -0,0 +1,71 @@
+[build-system]
+requires = ["setuptools>=64", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "forest-analysis"
+version = "1.0.dev3"
+description = "Forest is a library for analyzing smartphone-based high-throughput digital phenotyping data"
+authors = [
+    { name = "Onnela Lab", email = "[email protected]" }
+]
+maintainers = [
+    { name = "Onnela Lab", email = "[email protected]" }
+]
+readme = "README.md"
+license = { text = "BSD-3-Clause" }
+requires-python = ">=3.11"
+dependencies = [
+    "holidays",
+    "librosa",
+    "numpy",
+    "openrouteservice",
+    "pandas",
+    "pyproj",
+    "python-dateutil",
+    "pytz",
+    "ratelimit",
+    "requests",
+    "scipy",
+    "shapely",
+    "ssqueezepy",
+    "timezonefinder",
+]
+keywords = ["digital phenotyping", "smartphone", "statistics", "accelerometer", "GPS"]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Environment :: Console",
+    "Intended Audience :: Science/Research",
+    "License :: OSI Approved :: BSD License",
+    "Natural Language :: English",
+    "Operating System :: MacOS :: MacOS X",
+    "Operating System :: Microsoft :: Windows",
+    "Operating System :: POSIX :: Linux",
+    "Programming Language :: Python :: 3.11",
+    "Topic :: Scientific/Engineering",
+    "Topic :: Scientific/Engineering :: Information Analysis",
+]
+
+[project.urls]
+Documentation = "https://forest.beiwe.org"
+Homepage = "https://github.com/onnela-lab/forest"
+Issues = "https://github.com/onnela-lab/forest/issues"
+Source = "https://github.com/onnela-lab/forest"
+
+[project.optional-dependencies]
+dev = [
+    "build",
+    "flake8",
+    "flake8-pytest-style",
+    "mypy",
+    "pytest",
+    "pytest-mock",
+    "twine",
+    "types-python-dateutil",
+    "types-pytz",
+    "types-requests",
+    "types-setuptools",
+]
+
+[tool.setuptools.package-data]
+"forest.poplar.raw" = ["noncode/*.csv", "noncode/*.json"]

pytest.ini

@@ -1,4 +1,6 @@
 [pytest]
+addopts = --import-mode=importlib
+testpaths = tests
 filterwarnings =
     error
     # Ignore specific DeprecationWarnings from librosa.core.intervals

forest/bonsai/tests/test_simulate_gps_data.py → tests/bonsai/test_simulate_gps_data.py

@@ -282,7 +282,7 @@ def test_get_path_close_locations(coords1, coords3):
             == 2)
 
 
-@pytest.fixture()
+@pytest.fixture
 def random_path(directions1, coords1, coords2):
     lat1, lon1 = coords1
     lat2, lon2 = coords2
@@ -507,7 +507,7 @@ def test_person_office_days(sample_coordinates, sample_locations,
     assert len(random_person.office_days) <= 5
 
 
-@pytest.fixture()
+@pytest.fixture
 def sample_person(sample_coordinates, sample_locations, sample_attributes):
     user_attrs = sample_attributes["User 5"]
     attributes = Attributes(**user_attrs)
@@ -804,7 +804,7 @@ def test_gen_all_traj_dist_travelled(sample_person, mocker):
     assert np.all(total_d_list >= 0)
 
 
-@pytest.fixture()
+@pytest.fixture
 def generated_trajectory(sample_person, mocker):
     mocker.patch(
         "forest.bonsai.simulate_gps_data.get_path", side_effect=mock_get_path
@@ -869,7 +869,7 @@ def test_load_attributes_switches(sample_attributes):
     assert switches[5]["travelling_status-20"] == 1
 
 
-@pytest.fixture()
+@pytest.fixture
 def sample_addresses():
     return np.array(
         [

forest/jasmine/tests/test_traj2stats.py → tests/jasmine/test_traj2stats.py

@@ -12,12 +12,12 @@
 )
 
 
-@pytest.fixture()
+@pytest.fixture
 def coords1():
     return 51.457183, -2.597960
 
 
-@pytest.fixture()
+@pytest.fixture
 def coords2():
     return 51.457267, -2.598045
 
@@ -54,7 +54,7 @@ def test_transform_point_to_circle_radius(coords1):
     assert 4 <= distance <= 5
 
 
-@pytest.fixture()
+@pytest.fixture
 def sample_trajectory():
     """16 minutes of a random trajectory"""
     return np.array(
@@ -153,7 +153,7 @@ def sample_trajectory():
     )
 
 
-@pytest.fixture()
+@pytest.fixture
 def sample_nearby_locations():
     ids = {
         "post_box": [560374554],
@@ -480,7 +480,7 @@ def test_gps_summaries_pcr(
     assert summary["physical_circadian_rhythm_stratified"].iloc[1] == 0
 
 
-@pytest.fixture()
+@pytest.fixture
 def mobmat1():
     """mobility matrix 1"""
     return np.array(
@@ -494,7 +494,7 @@ def mobmat1():
     )
 
 
-@pytest.fixture()
+@pytest.fixture
 def mobmat2():
     """mobility matrix 2"""
     return np.array(
@@ -508,7 +508,7 @@ def mobmat2():
     )
 
 
-@pytest.fixture()
+@pytest.fixture
 def mobmat3():
     """mobility matrix 3"""
     return np.array(