Merge tag 'v0.18.4' into cleanup

.github/workflows/CI.yml

@@ -32,12 +32,12 @@ jobs:
     strategy:
       matrix:
         julia-version: ['1']
-        python-version: ['3.11']
+        python-version: ['3.12']
         os: [ubuntu-latest]
         test-id: [main]
         include:
           - julia-version: '1.6'
-            python-version: '3.7'
+            python-version: '3.8'
             os: ubuntu-latest
             test-id: include
           - julia-version: '1'
@@ -99,11 +99,11 @@ jobs:
     strategy:
       matrix:
         os: ['ubuntu-latest']
-        python-version: ['3.11']
+        python-version: ['3.12']
         julia-version: ['1']
         include:
           - os: ubuntu-latest
-            python-version: '3.7'
+            python-version: '3.8'
             julia-version: '1.6'
     steps:
       - uses: actions/checkout@v4
@@ -122,7 +122,7 @@ jobs:
         shell: bash -l {0}
     strategy:
       matrix:
-        python-version: ['3.11']
+        python-version: ['3.12']
         os: ['ubuntu-latest']
 
     steps:
@@ -181,8 +181,8 @@ jobs:
     strategy:
       matrix:
         python-version:
-          - '3.11'
-          - '3.7'
+          - '3.12'
+          - '3.8'
         os: ['ubuntu-latest']
 
     steps:
@@ -199,10 +199,10 @@ jobs:
             pip install mypy
       - name: "Install additional dependencies"
         run: python -m pip install jax jaxlib torch
-        if: ${{ matrix.python-version != '3.7' }}
+        if: ${{ matrix.python-version != '3.8' }}
       - name: "Run mypy"
         run: python -m mypy --install-types --non-interactive pysr
-        if: ${{ matrix.python-version != '3.7' }}
+        if: ${{ matrix.python-version != '3.8' }}
       - name: "Run compatible mypy"
         run: python -m mypy --ignore-missing-imports pysr
-        if: ${{ matrix.python-version == '3.7' }}
+        if: ${{ matrix.python-version == '3.8' }}

.github/workflows/CI_Windows.yml

@@ -30,7 +30,7 @@ jobs:
     strategy:
       matrix:
         julia-version: ['1']
-        python-version: ['3.11']
+        python-version: ['3.12']
         os: [windows-latest]
 
     steps:

.github/workflows/CI_docker_large_nightly.yml

@@ -19,7 +19,7 @@ jobs:
       fail-fast: false
       matrix:
         julia-version: ['1.6', '1']
-        python-version: ['3.7', '3.11']
+        python-version: ['3.8', '3.12']
         os: [ubuntu-latest]
         arch: ['linux/amd64', 'linux/arm64']
 

.github/workflows/CI_large_nightly.yml

@@ -23,8 +23,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        julia-version: ['1.6', '1.8', '1.9']
-        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11']
+        julia-version: ['1.6', '1.8', '1.10']
+        python-version: ['3.8', '3.10', '3.12']
         os: [ubuntu-latest, macos-latest, windows-latest]
 
     steps:

.github/workflows/CI_mac.yml

@@ -30,7 +30,7 @@ jobs:
     strategy:
       matrix:
         julia-version: ['1']
-        python-version: ['3.11']
+        python-version: ['3.12']
         os: [macos-latest]
 
     steps:

.github/workflows/docker_deploy.yml

@@ -18,8 +18,8 @@ jobs:
       matrix:
         os: [ubuntu-latest]
         arch: [linux/amd64]
-        python-version: [3.11.6]
-        julia-version: [1.9.4]
+        python-version: [3.12.3]
+        julia-version: [1.10.3]
     steps:
       - name: Checkout
         uses: actions/checkout@v4

docs/examples.md

@@ -428,7 +428,7 @@ the evaluation, as we simply evaluated each argument and divided the result) int
 `((2.3554819 + -0.3554746) - (x1 * (x0 * x0)))` and
 `(-1.0000019 - (x2 * x2))`, meaning that our discovered equation is
 equal to:
-$\frac{x_0^2 x_1 - 2.0000073}{x_2^2 - 1.0000019}$, which
+$\frac{x_0^2 x_1 - 2.0000073}{x_2^2 + 1.0000019}$, which
 is nearly the same as the true equation!
 
 ## 10. Dimensional constraints
@@ -520,6 +520,8 @@ a constant `"2.6353e-22[m s⁻²]"`.
 
 Note that this expression has a large dynamic range so may be difficult to find. Consider searching with a larger `niterations` if needed.
 
+Note that you can also search for exclusively dimensionless constants by settings
+`dimensionless_constants_only` to `true`.
 
 ## 11. Additional features
 

environment.yml

@@ -2,7 +2,7 @@ name: test
 channels:
   - conda-forge
 dependencies:
-  - python>=3.7
+  - python>=3.8
   - sympy>=1.0.0,<2.0.0
   - pandas>=0.21.0,<3.0.0
   - numpy>=1.13.0,<2.0.0

pyproject.toml

@@ -4,14 +4,14 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pysr"
-version = "0.18.3"
+version = "0.18.4"
 authors = [
     {name = "Miles Cranmer", email = "[email protected]"},
 ]
 description = "Simple and efficient symbolic regression"
 readme = {file = "README.md", content-type = "text/markdown"}
 license = {file = "LICENSE"}
-requires-python = ">=3.7"
+requires-python = ">=3.8"
 classifiers = [
     "Programming Language :: Python :: 3",
     "Operating System :: OS Independent",
@@ -34,5 +34,6 @@ profile = "black"
 dev-dependencies = [
     "pre-commit>=3.7.0",
     "ipython>=8.23.0",
+    "ipykernel>=6.29.4",
     "mypy>=1.10.0",
 ]

pysr/julia_import.py

@@ -36,6 +36,11 @@ else:
         os.environ[k] = os.environ.get(k, default)
 
 
+autoload_extensions = os.environ.get("PYSR_AUTOLOAD_EXTENSIONS")
+if autoload_extensions is not None:
+    # Deprecated; so just pass to juliacall
+    os.environ["PYTHON_JULIACALL_AUTOLOAD_IPYTHON_EXTENSION"] = autoload_extensions
+
 from juliacall import Main as jl  # type: ignore
 
 jl: Any = jl  # type: ignore
@@ -43,28 +48,6 @@ jl: Any = jl  # type: ignore
 
 jl_version = (jl.VERSION.major, jl.VERSION.minor, jl.VERSION.patch)
 
-# Next, automatically load the juliacall extension if we're in a Jupyter notebook
-autoload_extensions = os.environ.get("PYSR_AUTOLOAD_EXTENSIONS", "yes")
-if autoload_extensions in {"yes", ""} and jl_version >= (1, 9, 0):
-    try:
-        get_ipython = sys.modules["IPython"].get_ipython
-
-        if "IPKernelApp" not in get_ipython().config:
-            raise ImportError("console")
-
-        print(
-            "Detected Jupyter notebook. Loading juliacall extension. Set `PYSR_AUTOLOAD_EXTENSIONS=no` to disable."
-        )
-
-        # TODO: Turn this off if juliacall does this automatically
-        get_ipython().run_line_magic("load_ext", "juliacall")
-    except Exception:
-        pass
-elif autoload_extensions not in {"no", "yes", ""}:
-    warnings.warn(
-        "PYSR_AUTOLOAD_EXTENSIONS environment variable is set to something other than 'yes' or 'no' or ''."
-    )
-
 jl.seval("using SymbolicRegression")
 SymbolicRegression = jl.SymbolicRegression
 

pysr/juliapkg.json

@@ -3,7 +3,7 @@
     "packages": {
         "SymbolicRegression": {
             "uuid": "8254be44-1295-4e6a-a16d-46603ac705cb",
-            "version": "=0.24.3"
+            "version": "=0.24.4"
         },
         "Serialization": {
             "uuid": "9e88b42a-f829-5b0c-bbe9-9e923198166b",

pysr/param_groupings.yml

@@ -14,6 +14,7 @@
     - loss_function
     - model_selection
     - dimensional_constraint_penalty
+    - dimensionless_constants_only
   - Working with Complexities:
     - parsimony
     - constraints

pysr/sr.py

@@ -337,6 +337,9 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
     dimensional_constraint_penalty : float
         Additive penalty for if dimensional analysis of an expression fails.
         By default, this is `1000.0`.
+    dimensionless_constants_only : bool
+        Whether to only search for dimensionless constants, if using units.
+        Default is `False`.
     use_frequency : bool
         Whether to measure the frequency of complexities, and use that
         instead of parsimony to explore equation space. Will naturally
@@ -707,6 +710,7 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         complexity_of_variables: Union[int, float] = 1,
         parsimony: float = 0.0032,
         dimensional_constraint_penalty: Optional[float] = None,
+        dimensionless_constants_only: bool = False,
         use_frequency: bool = True,
         use_frequency_in_tournament: bool = True,
         adaptive_parsimony_scaling: float = 20.0,
@@ -802,6 +806,7 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         self.complexity_of_variables = complexity_of_variables
         self.parsimony = parsimony
         self.dimensional_constraint_penalty = dimensional_constraint_penalty
+        self.dimensionless_constants_only = dimensionless_constants_only
         self.use_frequency = use_frequency
         self.use_frequency_in_tournament = use_frequency_in_tournament
         self.adaptive_parsimony_scaling = adaptive_parsimony_scaling
@@ -1693,6 +1698,7 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
             # These have the same name:
             parsimony=self.parsimony,
             dimensional_constraint_penalty=self.dimensional_constraint_penalty,
+            dimensionless_constants_only=self.dimensionless_constants_only,
             alpha=self.alpha,
             maxdepth=maxdepth,
             fast_cycle=self.fast_cycle,

pysr/test/test_startup.py

@@ -118,10 +118,6 @@ class TestStartup(unittest.TestCase):
                 code="import juliacall; import pysr",
                 msg="juliacall module already imported.",
             ),
-            dict(
-                code='import os; os.environ["PYSR_AUTOLOAD_EXTENSIONS"] = "foo"; import pysr',
-                msg="PYSR_AUTOLOAD_EXTENSIONS environment variable is set",
-            ),
         ]
         for warning_test in warning_tests:
             result = subprocess.run(

requirements.txt

@@ -2,7 +2,7 @@ sympy>=1.0.0,<2.0.0
 pandas>=0.21.0,<3.0.0
 numpy>=1.13.0,<2.0.0
 scikit_learn>=1.0.0,<2.0.0
-juliacall==0.9.19
+juliacall==0.9.20
 click>=7.0.0,<9.0.0
 setuptools>=50.0.0
 typing_extensions>=4.0.0,<5.0.0; python_version < "3.8"