Updated symbolic example to modern pysr+sympy

examples/symbolic_regression.ipynb

@@ -74,14 +74,7 @@
     "import optax  # https://github.com/deepmind/optax\n",
     "import pysr  # https://github.com/MilesCranmer/PySR\n",
     "import sympy\n",
-    "import sympy2jax  # https://github.com/google/sympy2jax\n",
-    "\n",
-    "\n",
-    "# Note that PySR, which we use for symbolic regression, uses Julia as a backend.\n",
-    "# You'll need to install a recent version of Julia if you don't have one.\n",
-    "# (And can get funny errors if you have a too-old version of Julia already.)\n",
-    "# You may also need to restart Python after running `pysr.install()` the first time.\n",
-    "pysr.install(quiet=True)"
+    "import sympy2jax  # https://github.com/google/sympy2jax"
    ]
   },
   {
@@ -112,7 +105,7 @@
     "def quantise(expr, quantise_to):\n",
     "    if isinstance(expr, sympy.Float):\n",
     "        return expr.func(round(float(expr) / quantise_to) * quantise_to)\n",
-    "    elif isinstance(expr, sympy.Symbol):\n",
+    "    elif isinstance(expr, (sympy.Symbol, sympy.Integer)):\n",
     "        return expr\n",
     "    else:\n",
     "        return expr.func(*[quantise(arg, quantise_to) for arg in expr.args])"
@@ -174,7 +167,7 @@
     "    with tempfile.TemporaryDirectory() as tempdir:\n",
     "        symbolic_regressor = pysr.PySRRegressor(\n",
     "            niterations=symbolic_migration_steps,\n",
-    "            ncyclesperiteration=symbolic_mutation_steps,\n",
+    "            ncycles_per_iteration=symbolic_mutation_steps,\n",
     "            populations=symbolic_num_populations,\n",
     "            population_size=symbolic_population_size,\n",
     "            optimizer_iterations=symbolic_descent_steps,\n",