Split CI into separate windows action

.github/workflows/CI.yml

@@ -25,7 +25,7 @@ jobs:
       matrix:
         julia-version: ['1.5.0', '1.6.1']
         python-version: ['3.6', '3.8']
-        os: [ubuntu-latest, windows-latest]
+        os: [ubuntu-latest]
     
     steps:
       - uses: actions/checkout@v1.0.0
@@ -65,11 +65,9 @@ jobs:
         run: coverage run --source=pysr --omit='*/feynman_problems.py' -m unittest test.test
         shell: bash
       - name: "Install JAX"
-        if: matrix.os != 'windows-latest'
         run: pip install jax jaxlib # (optional import)
         shell: bash
       - name: "Run JAX tests"
-        if: matrix.os != 'windows-latest'
         run: coverage run --append --source=pysr --omit='*/feynman_problems.py' -m unittest test.test_jax
         shell: bash
       - name: "Install Torch"

.github/workflows/CI_Windows.yml

@@ -0,0 +1,72 @@
+on:
+  push:
+    branches:
+      - '*'
+    paths:
+      - 'test/**'
+      - 'pysr/**'
+      - '.github/workflows/**'
+      - 'setup.py'
+      - 'Project.toml'
+  pull_request:
+    branches:
+      - '*'
+    paths:
+      - 'test/**'
+      - 'pysr/**'
+      - '.github/workflows/**'
+      - 'setup.py'
+      - 'Project.toml'
+
+jobs:
+  test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        julia-version: ['1.5.0', '1.6.1']
+        python-version: ['3.6', '3.8']
+        os: [windows-latest]
+    
+    steps:
+      - uses: actions/checkout@v1.0.0
+      - name: "Set up Julia"
+        uses: julia-actions/setup-julia@v1.6.0
+        with:
+          version: ${{ matrix.julia-version }}
+      - name: "Change package server"
+        shell: bash
+        env:
+            JULIA_PKG_SERVER: ""
+        run: |
+            julia -e 'using Pkg; Pkg.Registry.add("General")'
+      - name: "Cache dependencies"
+        uses: actions/cache@v1 # Thanks FromFile.jl
+        env:
+          cache-name: cache-artifacts
+        with:
+          path: ~/.julia/artifacts
+          key: ${{ runner.os }}-build-${{ env.cache-name }}-${{ hashFiles('**/Project.toml') }}
+          restore-keys: |
+            ${{ runner.os }}-build-${{ env.cache-name }}-
+            ${{ runner.os }}-build-
+            ${{ runner.os }}-
+      - name: "Set up Python"
+        uses: actions/setup-python@v1
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: "Install PySR"
+        run: |
+            python -m pip install --upgrade pip
+            pip install -r requirements.txt
+            python setup.py install
+      - name: "Install Coverage tool"
+        run: pip install coverage coveralls
+      - name: "Run tests"
+        run: python -m unittest test.test
+        shell: bash
+      - name: "Install Torch"
+        run: pip install torch # (optional import)
+        shell: bash
+      - name: "Run Torch tests"
+        run: python -m unittest test.test_torch
+        shell: bash

pysr/sr.py

@@ -293,7 +293,7 @@ def pysr(X, y, weights=None,
         warnings.warn("Note: you are running with more than 10,000 datapoints. You should consider turning on batching (https://pysr.readthedocs.io/en/latest/docs/options/#batching). You should also reconsider if you need that many datapoints. Unless you have a large amount of noise (in which case you should smooth your dataset first), generally < 10,000 datapoints is enough to find a functional form with symbolic regression. More datapoints will lower the search speed.")
 
     if maxsize > 40:
-        warnings.warn("Note: Using a large maxsize for the equation search will be slow and use significant memory. You should consider turning `useFrequency` to False, and perhaps use `warmupMaxsizeBy`.")
+        warnings.warn("Note: Using a large maxsize for the equation search will be exponentially slower and use significant memory. You should consider turning `useFrequency` to False, and perhaps use `warmupMaxsizeBy`.")
 
     X, variable_names, selection = _handle_feature_selection(
             X, select_k_features,