Merge pull request #283 from lnccbrown/280-pin-numpy-version

Bumped PyMC version and limited numpy version

.github/workflows/build_and_publish.yml

@@ -12,7 +12,7 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v3
@@ -67,7 +67,7 @@ jobs:
       - name: Setup Python
         uses: actions/setup-python@v3
         with:
-          python-version: 3.9
+          python-version: 3.11
 
       - name: Install poetry
         uses: snok/install-poetry@v1
@@ -82,7 +82,7 @@ jobs:
         id: cache
         with:
           path: .venv
-          key: venv-${{ runner.os }}-3.9-${{ hashFiles('**/pyproject.toml') }}
+          key: venv-${{ runner.os }}-3.11-${{ hashFiles('**/pyproject.toml') }}
 
       - name: Install dependencies
         if: steps.cache.outputs.cache-hit != 'true'

.github/workflows/build_docs.yml

@@ -18,7 +18,7 @@ jobs:
       - name: Setup Python
         uses: actions/setup-python@v3
         with:
-          python-version: "3.9"
+          python-version: "3.11"
 
       - name: Install poetry
         uses: snok/install-poetry@v1
@@ -33,7 +33,7 @@ jobs:
         id: cache
         with:
           path: .venv
-          key: venv-${{ runner.os }}-3.9-${{ hashFiles('**/pyproject.toml') }}
+          key: venv-${{ runner.os }}-3.11-${{ hashFiles('**/pyproject.toml') }}
 
       - name: Install dependencies
         if: steps.cache.outputs.cache-hit != 'true'

.github/workflows/run_tests.yml

@@ -11,7 +11,7 @@ jobs:
     strategy:
       fail-fast: true
       matrix:
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11"]
 
     steps:
       - uses: actions/checkout@v3

README.md

@@ -47,7 +47,12 @@ You will need optional dependencies to use JAX-based samplers and graph the mode
 Please refer to our [installation guide](https://lnccbrown.github.io/HSSM/getting_started/installation/)
 for more detailed instructions.
 
-**Note**: Possible solutions to any issues with installations with hssm can be located [here](https://github.com/lnccbrown/HSSM/discussions). We recommend leveraging an environment manager with Python 3.9~3.11 to prevent any problems with dependencies during the installation process. Please note that hssm is tested for python 3.9, 3.10, 3.11. Use other python versions with caution.
+**Note**: Possible solutions to any issues with installations with hssm can be located
+    [here](https://github.com/lnccbrown/HSSM/discussions). We recommend leveraging an
+    environment manager with Python 3.10~3.11 to prevent any problems with dependencies
+    during the installation process. Please note that hssm is tested for python 3.10,
+    3.11. As of HSSM v0.1.6, support for Python 3.9 is dropped. Use other python
+    versions with caution.
 
 ## Example
 

docs/index.md

@@ -48,9 +48,11 @@ For more detailed guidance, please check out our [installation guide](getting_st
 
     Possible solutions to any issues with installations with hssm can be located
     [here](https://github.com/lnccbrown/HSSM/discussions). We recommend leveraging an
-    environment manager with Python 3.9~3.11 to prevent any problems with dependencies
-    during the installation process. Please note that hssm is tested for python 3.9, 3.10,
-    3.11. Use other python versions with caution.
+    environment manager with Python 3.10~3.11 to prevent any problems with dependencies
+    during the installation process. Please note that hssm is tested for python 3.10,
+    3.11. As of HSSM v0.1.6, support for Python 3.9 is dropped. Use other python
+    versions with caution.
+
 
 ### Setting global float type
 

pyproject.toml

@@ -15,11 +15,11 @@ repository = "https://github.com/lnccbrown/HSSM"
 keywords = ["HSSM", "sequential sampling models", "bayesian", "bayes", "mcmc"]
 
 [tool.poetry.dependencies]
-python = ">=3.9,<3.12"
-pymc = ">=5.6.0,<5.7.0"
+python = ">=3.10,<3.12"
+pymc = ">=5.9.0"
 scipy = "1.10.1"
 arviz = "^0.14.0"
-numpy = "^1.23.4"
+numpy = ">=1.23.4,<1.26"
 onnx = "^1.12.0"
 jax = "^0.4.0"
 jaxlib = "^0.4.0"

src/hssm/config.py

@@ -1,6 +1,6 @@
 """Config and ModelConfig classes that process configs."""
 
-
+# This is necessary to enable forward looking
 from __future__ import annotations
 
 from copy import deepcopy

src/hssm/distribution_utils/dist.py

@@ -5,8 +5,6 @@
 generation ops.
 """
 
-from __future__ import annotations
-
 import logging
 from os import PathLike
 from typing import Any, Callable, Iterable, Type

src/hssm/distribution_utils/onnx/onnx.py

@@ -4,8 +4,6 @@
 from onnx model files and wrapping jax log-likelihood functions in pytensor Ops.
 """
 
-from __future__ import annotations
-
 from os import PathLike
 from typing import Callable
 

src/hssm/hssm.py

@@ -6,19 +6,25 @@
 This file defines the entry class HSSM.
 """
 
-from __future__ import annotations
-
 import logging
 from copy import deepcopy
 from inspect import isclass
+from os import PathLike
 from pathlib import Path
-from typing import TYPE_CHECKING, Any, Callable, Literal
+from typing import Any, Callable, Literal
 
+import arviz as az
 import bambi as bmb
+import numpy as np
+import pandas as pd
 import pymc as pm
 import pytensor
 from bambi.model_components import DistributionalComponent
 
+from hssm.defaults import (
+    LoglikKind,
+    SupportedModels,
+)
 from hssm.distribution_utils import (
     make_blackbox_op,
     make_distribution,
@@ -39,18 +45,6 @@
 
 from .config import Config, ModelConfig
 
-if TYPE_CHECKING:
-    from os import PathLike
-
-    import arviz as az
-    import numpy as np
-    import pandas as pd
-
-    from hssm.defaults import (
-        LoglikKind,
-        SupportedModels,
-    )
-
 _logger = logging.getLogger("hssm")
 
 

src/hssm/likelihoods/analytical.py

@@ -5,8 +5,6 @@
 https://gist.github.com/sammosummo/c1be633a74937efaca5215da776f194b.
 """
 
-from __future__ import annotations
-
 from typing import Type
 
 import numpy as np

src/hssm/likelihoods/blackbox.py

@@ -1,7 +1,5 @@
 """Black box likelihoods written in Cython for "ddm" and "ddm_sdv" models."""
 
-from __future__ import annotations
-
 import numpy as np
 from hddm_wfpt import wfpt
 

src/hssm/param.py

@@ -1,7 +1,5 @@
 """The Param utility class."""
 
-from __future__ import annotations
-
 import logging
 from typing import Any, Union, cast
 

src/hssm/prior.py

@@ -9,8 +9,6 @@
 3. The ability to shorten the output of bmb.Prior.
 """
 
-from __future__ import annotations
-
 from typing import Callable
 
 import bambi as bmb

src/hssm/simulator.py

@@ -1,17 +1,11 @@
 """Simulates data with basic ssm_simulators."""
 
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
 import numpy as np
 import pandas as pd
+from numpy.typing import ArrayLike
 from ssms.basic_simulators.simulator import simulator
 from ssms.config import model_config
 
-if TYPE_CHECKING:
-    from numpy.typing import ArrayLike
-
 
 def simulate_data(
     model: str,

src/hssm/utils.py

@@ -9,8 +9,6 @@
 _parse_bambi().
 """
 
-from __future__ import annotations
-
 import logging
 from copy import deepcopy
 from typing import Any, Iterable, Literal, NewType

tests/test_onnx.py

@@ -22,7 +22,9 @@ def fixture_path():
 def onnx_session(fixture_path):
     model_path = str(fixture_path / "angle.onnx")
 
-    return onnxruntime.InferenceSession(model_path, None)
+    return onnxruntime.InferenceSession(
+        model_path, None, providers=["CPUExecutionProvider"]
+    )
 
 
 def test_interpret_onnx(onnx_session, fixture_path):