Update docs

docs/start.md

@@ -44,8 +44,10 @@ model = PySRRegressor(
         "cos",
         "exp",
         "sin",
+        "inv(x)=1/x",  # Custom operator (julia syntax)
     ],
     model_selection="best",
+    loss="loss(x, y) = (x - y)^2",  # Custom loss function (julia syntax)
 )
 ```
 This will set up the model for 5 iterations of the search code, which contains hundreds of thousands of mutations and equation evaluations.
@@ -69,13 +71,13 @@ print(model)
 to print the learned equations:
 ```python
 PySRRegressor.equations = [
-   pick      score                                           Equation           MSE  Complexity
-0         0.000000                                          3.5082064  2.710828e+01           1
-1         0.964260                                          (x0 * x0)  3.940544e+00           3
-2         0.030096                          (-0.47978288 + (x0 * x0))  3.710349e+00           5
-3         0.840770                              ((x0 * x0) + cos(x3))  1.600564e+00           6
-4         0.928380                ((x0 * x0) + (2.5313091 * cos(x3)))  2.499724e-01           8
-5  >>>>  13.956461  ((-0.49999997 + (x0 * x0)) + (2.5382001 * cos(...  1.885665e-13          10
+           pick      score                                           equation          loss  complexity
+        0         0.000000                                          3.0282464  2.816982e+01           1
+        1         1.008026                                          (x0 * x0)  3.751666e+00           3
+        2         0.015337                          (-0.33649465 + (x0 * x0))  3.638336e+00           5
+        3         0.888050                              ((x0 * x0) + cos(x3))  1.497019e+00           6
+        4         0.898539                ((x0 * x0) + (2.4816332 * cos(x3)))  2.481797e-01           8
+        5  >>>>  10.604434  ((-0.49998775 + (x0 * x0)) + (2.5382009 * cos(...  1.527115e-10          10
 ]
 ```
 This arrow in the `pick` column indicates which equation is currently selected by your
@@ -88,7 +90,7 @@ SymPy format (`sympy_format`), and even JAX and PyTorch format
 (both of which are differentiable).
 
 There are several other useful features such as denoising (e.g., `denoising=True`),
-feature selection (e.g., `select_k_features=3`).
+feature selection (e.g., `select_k_features=3`), and many others.
 For a summary of features and options, see [this docs page](https://pysr.readthedocs.io/en/latest/docs/options/).
 You can see the full API at [this page](https://pysr.readthedocs.io/en/latest/docs/api-documentation/).
 

example.py

@@ -13,8 +13,11 @@ model = PySRRegressor(
         "cos",
         "exp",
         "sin",
+        "inv(x)=1/x",  # Custom operator (julia syntax)
     ],
     model_selection="best",
+    loss="loss(x, y) = (x - y)^2",  # Custom loss function (julia syntax)
+    multithreading=False,
 )
 
 model.fit(X, y)