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sluo1250Copilot
sluo1250
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Copilot
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Add support for Python 3.13 (#894)
- Bump requires-python from >=3.9 to >=3.12 (arviz requires >=3.12) - Update classifiers to 3.12/3.13 - Bump dependency minimums for 3.13 wheel availability - Replace np.in1d with np.isin (removed in NumPy 2.x) - Fix deprecated pandas freq aliases (M -> ME) - Fix chained assignment for pandas Copy-on-Write - Fix invalid escape sequence in docstring - Update CI actions to v4/v5 and test matrix to [3.12, 3.13] - Update tox envlist to py312, py313 Closes #891 Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
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‎.github/workflows/pypi-deploy.yaml‎

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@@ -8,9 +8,9 @@ jobs:
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deploy:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v4
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- name: Set up Python
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uses: actions/setup-python@v2
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uses: actions/setup-python@v5
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with:
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python-version: "3.x"
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- name: Install dependencies

‎.github/workflows/test.yaml‎

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@@ -6,7 +6,7 @@ jobs:
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lint:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- uses: actions/checkout@v4
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- uses: psf/black@stable
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with:
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options: "--check --verbose --color"
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# You can use PyPy versions in python-version.
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# For example, pypy2 and pypy3
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matrix:
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python-version: [3.9]
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python-version: ["3.12", "3.13"]
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steps:
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- uses: actions/checkout@v2
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- uses: actions/checkout@v4
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v2
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python-version }}
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# You can test your matrix by printing the current Python version

‎orbit/diagnostics/metrics.py‎

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@@ -60,7 +60,7 @@ def rmsse(test_actual, test_prediction, train_actual):
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compared to a naive lag-1 predictor.
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.. math::
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\sqrt{\frac{1}{h}\frac{\sum^{n+h}_{t=n+1}(Y_t-\hat{Y}_t)^2}{\frac{1}{n-1}\sum^{n}_{t=2}{(Y_t-Y_{t-1})^2}
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\\sqrt{\\frac{1}{h}\\frac{\\sum^{n+h}_{t=n+1}(Y_t-\\hat{Y}_t)^2}{\\frac{1}{n-1}\\sum^{n}_{t=2}{(Y_t-Y_{t-1})^2}
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Notes
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-----

‎orbit/template/ktr.py‎

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@@ -760,7 +760,7 @@ def _generate_insample_tp(self, training_meta, date_array):
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"""Used in _generate_seas"""
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train_date_array = training_meta[TrainingMetaKeys.DATE_ARRAY.value]
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num_of_observations = training_meta[TrainingMetaKeys.NUM_OF_OBS.value]
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idx = np.nonzero(np.in1d(train_date_array, date_array))[0]
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idx = np.nonzero(np.isin(train_date_array, date_array))[0]
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tp = (idx + 1) / num_of_observations
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return tp
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‎pyproject.toml‎

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@@ -1,6 +1,6 @@
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[tool.black]
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line-length = 88
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target-version = ['py39', 'py310', 'py311']
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target-version = ['py312', 'py313']
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include = '\.pyi?$'
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extend-exclude = '''
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# A regex preceded with ^/ will apply only to files and directories
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version = "1.1.5.0"
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description = "Orbit is a package for Bayesian time series modeling and inference."
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readme = "README.md"
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requires-python = ">=3.9"
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requires-python = ">=3.12"
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dependencies = [
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"arviz",
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"cmdstanpy>=1.2.1",
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"importlib_resources",
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"matplotlib>=3.3.2",
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"numpy>=1.18",
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"pandas>=1.0.3",
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"matplotlib>=3.9.2",
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"numpy>=2.1.0",
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"pandas>=2.2.3",
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"pyro-ppl>=1.4.0",
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"scipy>=1.4.1",
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"seaborn>=0.10.0",
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"statsmodels>=0.11.1",
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"torch>=1.11.0",
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"scipy>=1.14.1",
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"seaborn>=0.13.2",
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"statsmodels>=0.14.3",
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"torch>=2.5.0",
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"tqdm>=4.36.1",
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]
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license = {text = "Apache License 2.0"}
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classifiers = [
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"Programming Language :: Python",
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"Programming Language :: Python :: 3.9",
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"Programming Language :: Python :: 3.10",
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"Programming Language :: Python :: 3.11",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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]
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[project.optional-dependencies]
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dev = [

‎requirements.txt‎

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@@ -2,13 +2,13 @@ arviz
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cmdstanpy>=1.2.1
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importlib_resources
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ipywidgets
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matplotlib>=3.3.2
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numpy>=1.26.4
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pandas>=2.3.0
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matplotlib>=3.9.2
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numpy>=2.1.0
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pandas>=2.2.3
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pyro-ppl>=1.4.0
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scipy>=1.4.1
10-
seaborn>=0.10.0
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scipy>=1.14.1
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seaborn>=0.13.2
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setuptools>=42
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statsmodels>=0.14.4
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statsmodels>=0.14.3
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torch
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tqdm>=4.36.1

‎tests/orbit/models/test_dlt.py‎

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@@ -156,7 +156,7 @@ def test_invalid_regressor(make_weekly_data, regressor_signs, invalid_input):
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train_df, test_df, coef = make_weekly_data
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regressor_col = train_df.columns.tolist()[2:]
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# make invalid values
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train_df[regressor_col[0]][36] = invalid_input
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train_df.loc[train_df.index[36], regressor_col[0]] = invalid_input
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expected_flag = False
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try:
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dlt = DLT(
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186186
train_df, test_df, coef = make_weekly_data
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regressor_col = train_df.columns.tolist()[2:]
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# make invalid values
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test_df[regressor_col[0]][3] = invalid_input
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test_df.loc[test_df.index[3], regressor_col[0]] = invalid_input
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expected_flag = False
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try:
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dlt = DLT(

‎tests/orbit/models/test_ktr.py‎

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@@ -131,7 +131,7 @@ def test_ktr_regression(make_daily_data, regressor_col):
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@pytest.mark.parametrize(
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"regression_knot_dates",
134-
[pd.date_range(start="2016-03-01", end="2019-01-01", freq="3M")],
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[pd.date_range(start="2016-03-01", end="2019-01-01", freq="3ME")],
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)
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@pytest.mark.parametrize(
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"make_daily_data", [{"seasonality": "dual", "with_coef": True}], indirect=True

‎tests/orbit/models/test_ktrlite.py‎

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@@ -107,8 +107,8 @@ def test_ktrlite_level_segments(make_daily_data, level_segments):
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@pytest.mark.parametrize(
108108
"level_knot_dates",
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[
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pd.date_range(start="2016-03-01", end="2019-01-01", freq="3M"),
111-
pd.date_range(start="2016-03-01", end="2019-01-01", freq="6M"),
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pd.date_range(start="2016-03-01", end="2019-01-01", freq="3ME"),
111+
pd.date_range(start="2016-03-01", end="2019-01-01", freq="6ME"),
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],
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)
114114
@pytest.mark.parametrize(

‎tox.ini‎

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@@ -1,5 +1,5 @@
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[tox]
2-
envlist = py38
2+
envlist = py312, py313
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[testenv]
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deps = pytest

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