Backend 1.5.0

docs/examples.md

@@ -644,7 +644,67 @@ You can then view the logs with:
 tensorboard --logdir logs/
 ```
 
-## 13. Additional features
+## 13. Using differential operators
+
+As part of the `TemplateExpressionSpec` described above,
+you can also use differential operators within the template.
+The operator for this is `D` which takes an expression as the first argument,
+and the argument _index_ we are differentiating as the second argument.
+This lets you compute integrals via evolution.
+
+For example, let's say we wish to find the integral of $\frac{1}{x^2 \sqrt{x^2 - 1}}$
+in the range $x > 1$.
+We can compute the derivative of a function $f(x)$, and compare that
+to numerical samples of $\frac{1}{x^2\sqrt{x^2-1}}$. Then, by extension,
+$f(x)$ represents the indefinite integral of it with some constant offset!
+
+```python
+import numpy as np
+from pysr import PySRRegressor, TemplateExpressionSpec
+
+x = np.random.uniform(1, 10, (1000,))  # Integrand sampling points
+y = 1 / (x**2 * np.sqrt(x**2 - 1))     # Evaluation of the integrand
+
+expression_spec = TemplateExpressionSpec(
+    ["f"],
+    """
+    function diff_f_x((; f), (x,))
+        df = D(f, 1)  # Symbolic derivative of f with respect to its first arg
+        return df(x)
+    end
+    """
+)
+
+model = PySRRegressor(
+    binary_operators=["+", "-", "*", "/"],
+    unary_operators=["sqrt"],
+    expression_spec=expression_spec,
+    maxsize=20,
+)
+model.fit(x[:, np.newaxis], y)
+```
+
+If everything works, you should find something that simplifies to $\frac{\sqrt{x^2 - 1}}{x}$.
+
+Here, we write out a full function in Julia.
+But we can also do an anonymous function, like `((; f), (x,)) -> D(f, 1)(x)`. We can also avoid the fancy unpacking syntax and write:
+`(nt, xs) -> D(nt.f, 1)(xs[1])` which is completely equivalent. Note that in Julia,
+the following two syntaxes are equivalent:
+
+```julia
+nt = (; f=1, g=2)  # Create a "named tuple"
+(; f, g) = nt
+```
+
+and
+
+```julia
+f = nt.f
+g = nt.g
+```
+
+
+## 14. Additional features
 
 For the many other features available in PySR, please
 read the [Options section](options.md).

docs/operators.md

@@ -7,56 +7,32 @@ takes one or two scalars as input, and returns on scalar as output,
 is likely to be a valid operator[^1].
 A selection of these and other valid operators are stated below.
 
-**Binary**
-
-- `+`
-- `-`
-- `*`
-- `/`
-- `^`
-- `max`
-- `min`
-- `mod`
-- `cond`
-    - Equal to `(x, y) -> x > 0 ? y : 0`
-- `greater`
-    - Equal to `(x, y) -> x > y ? 1 : 0`
-- `logical_or`
-    - Equal to `(x, y) -> (x > 0 || y > 0) ? 1 : 0`
-- `logical_and`
-    - Equal to `(x, y) -> (x > 0 && y > 0) ? 1 : 0`
-
-**Unary**
-
-- `neg`
-- `square`
-- `cube`
-- `exp`
-- `abs`
-- `log`
-- `log10`
-- `log2`
-- `log1p`
-- `sqrt`
-- `sin`
-- `cos`
-- `tan`
-- `sinh`
-- `cosh`
-- `tanh`
-- `atan`
-- `asinh`
-- `acosh`
-- `atanh_clip`
-    - Equal to `atanh(mod(x + 1, 2) - 1)`
-- `erf`
-- `erfc`
-- `gamma`
-- `relu`
-- `round`
-- `floor`
-- `ceil`
-- `sign`
+Also, note that it's a good idea to not use too many operators, since
+it can exponentially increase the search space.
+
+**Binary Operators**
+
+| Arithmetic    | Comparison | Logic    |
+|--------------|------------|----------|
+| `+`          | `max`      | `logical_or`[^2] |
+| `-`          | `min`      | `logical_and`[^3]|
+| `*`          | `greater`[^4] |                 |
+| `/`          | `cond`[^5]   |                 |
+| `^`          | `mod`      |                 |
+
+**Unary Operators**
+
+| Basic      | Exp/Log    | Trig      | Hyperbolic | Special   | Rounding   |
+|------------|------------|-----------|------------|-----------|------------|
+| `neg`      | `exp`      | `sin`     | `sinh`     | `erf`     | `round`    |
+| `square`   | `log`      | `cos`     | `cosh`     | `erfc`    | `floor`    |
+| `cube`     | `log10`    | `tan`     | `tanh`     | `gamma`   | `ceil`     |
+| `cbrt`     | `log2`     | `asin`    | `asinh`    | `relu`    |            |
+| `sqrt`     | `log1p`    | `acos`    | `acosh`    | `sinc`    |            |
+| `abs`      |            | `atan`    | `atanh`    |           |            |
+| `sign`     |            |           |            |           |            |
+| `inv`      |            |           |            |           |            |
+
 
 ## Custom
 
@@ -96,3 +72,7 @@ any invalid values over the training dataset.
 <!-- (Will say "However, you may need to define a `extra_sympy_mapping`":) -->
 
 [^1]: However, you will need to define a sympy equivalent in `extra_sympy_mapping` if you want to use a function not in the above list.
+[^2]: `logical_or` is equivalent to `(x, y) -> (x > 0 || y > 0) ? 1 : 0`
+[^3]: `logical_and` is equivalent to `(x, y) -> (x > 0 && y > 0) ? 1 : 0`
+[^4]: `greater` is equivalent to `(x, y) -> x > y ? 1 : 0`
+[^5]: `cond` is equivalent to `(x, y) -> x > 0 ? y : 0`

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pysr"
-version = "1.2.0"
+version = "1.3.0"
 authors = [
     {name = "Miles Cranmer", email = "[email protected]"},
 ]

pysr/juliapkg.json

@@ -3,7 +3,7 @@
     "packages": {
         "SymbolicRegression": {
             "uuid": "8254be44-1295-4e6a-a16d-46603ac705cb",
-            "version": "=1.4.0"
+            "version": "=1.5.0"
         },
         "Serialization": {
             "uuid": "9e88b42a-f829-5b0c-bbe9-9e923198166b",