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Update more parts of docs
Browse files- docs/examples.md +11 -11
docs/examples.md
CHANGED
@@ -23,8 +23,9 @@ find the expression `2 cos(x3) + x0^2 - 2`.
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```python
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X = 2 * np.random.randn(100, 5)
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y = 2 * np.cos(X[:, 3]) + X[:, 0] ** 2 - 2
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-
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-
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```
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## 2. Custom operator
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@@ -34,14 +35,13 @@ Here, we define a custom operator and use it to find an expression:
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```python
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X = 2 * np.random.randn(100, 5)
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y = 1 / X[:, 0]
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X,
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y,
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binary_operators=["plus", "mult"],
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unary_operators=["inv(x) = 1/x"],
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**kwargs
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)
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```
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## 3. Multiple outputs
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```python
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X = 2 * np.random.randn(100, 5)
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y = 1 / X[:, [0, 1, 2]]
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X,
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y,
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binary_operators=["plus", "mult"],
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unary_operators=["inv(x) = 1/x"],
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**kwargs
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)
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```
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## 4. Plotting an expression
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Here, let's use the same equations, but get a format we can actually
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use and test. We can add this option after a search via the `
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function:
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```python
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-
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```
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If you look at the lists of expressions before and after, you will
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see that the sympy format now has replaced `inv` with `1/`.
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```python
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X = 2 * np.random.randn(100, 5)
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y = 2 * np.cos(X[:, 3]) + X[:, 0] ** 2 - 2
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model = PySRRegressor(binary_operators=["+", "-", "*", "/"], **kwargs)
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model.fit(X, y)
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print(model)
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```
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## 2. Custom operator
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```python
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X = 2 * np.random.randn(100, 5)
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y = 1 / X[:, 0]
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model = PySRRegressor(
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binary_operators=["plus", "mult"],
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unary_operators=["inv(x) = 1/x"],
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**kwargs
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)
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model.fit(X, y)
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print(model)
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```
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## 3. Multiple outputs
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```python
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X = 2 * np.random.randn(100, 5)
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y = 1 / X[:, [0, 1, 2]]
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model = PySRRegressor(
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binary_operators=["plus", "mult"],
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unary_operators=["inv(x) = 1/x"],
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**kwargs
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)
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model.fit(X, y)
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```
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## 4. Plotting an expression
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Here, let's use the same equations, but get a format we can actually
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use and test. We can add this option after a search via the `set_params`
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function:
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```python
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model.set_params(extra_sympy_mappings={"inv": lambda x: 1/x})
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model.sympy()
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```
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If you look at the lists of expressions before and after, you will
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see that the sympy format now has replaced `inv` with `1/`.
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