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friedman

FriedmanDriftDataset

Friedman Drift Dataset.

Source code in spotpython/data/friedman.py 
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class FriedmanDriftDataset:
    """Friedman Drift Dataset."""

    def __init__(self, n_samples=100, change_point1=50, change_point2=75, seed=None, constant=False) -> None:
        """Constructor for the Friedman Drift Dataset.

        Args:
            n_samples (int): The number of samples to generate.
            change_point1 (int): The index of the first change point.
            change_point2 (int): The index of the second change point.
            seed (int): The seed for the random number generator.
            constant (bool): If True, only the first feature is set to 1 and all others are set to 0.

        Returns:
            None (None): None

        Examples:
            >>> from spotpython.data.friedman import FriedmanDriftDataset
                data_generator = FriedmanDriftDataset(n_samples=100,
                    seed=42, change_point1=50, change_point2=75, constant=False)
                data = [data for data in data_generator]
                indices = [i for _, _, i in data]
                values = {f"x{i}": [] for i in range(5)}
                values["y"] = []
                for x, y, _ in data:
                    for i in range(5):
                        values[f"x{i}"].append(x[i])
                    values["y"].append(y)
                plt.figure(figsize=(10, 6))
                for label, series in values.items():
                    plt.plot(indices, series, label=label)
                plt.xlabel('Index')
                plt.ylabel('Value')
                plt.title('')
                plt.axvline(x=50, color='k', linestyle='--', label='Drift Point 1')
                plt.axvline(x=75, color='r', linestyle='--', label='Drift Point 2')
                plt.legend()
                plt.grid(True)
                plt.show()
        """
        self.n_samples = n_samples
        self._change_point1 = change_point1
        self._change_point2 = change_point2
        self.seed = seed
        self.index = 0
        self.rng = random.Random(self.seed)
        self.constant = constant

    def __iter__(self):
        return self

    def __next__(self):
        if self.index >= self.n_samples:  # Specifying end of generation
            raise StopIteration
        if self.constant:
            # x[0] is set to 1, all others to 0
            x = {0: 1}
            x.update({i: 0 for i in range(1, 10)})  # All x[i] are 0 for i > 0
        else:
            x = {i: self.rng.uniform(a=0, b=1) for i in range(10)}
        y = self._global_recurring_abrupt_gen(x, self.index) + self.rng.gauss(mu=0, sigma=1)
        result = (x, y, self.index)
        self.index += 1
        return result

    def _global_recurring_abrupt_gen(self, x, index):
        if index < self._change_point1 or index >= self._change_point2:
            return 10 * math.sin(math.pi * x[0] * x[1]) + 20 * (x[2] - 0.5) ** 2 + 10 * x[3] + 5 * x[4]
        else:
            return 10 * math.sin(math.pi * x[3] * x[5]) + 20 * (x[1] - 0.5) ** 2 + 10 * x[0] + 5 * x[2]

    def __len__(self) -> int:
        """
        Returns the length of the dataset.

        Returns:
            int: The length of the dataset.


        """
        return self.n_samples

__init__(n_samples=100, change_point1=50, change_point2=75, seed=None, constant=False)

Constructor for the Friedman Drift Dataset.

Parameters:

Name Type Description Default
n_samples int

The number of samples to generate.

 100
change_point1 int

The index of the first change point.

 50
change_point2 int

The index of the second change point.

 75
seed int

The seed for the random number generator.

 None
constant bool

If True, only the first feature is set to 1 and all others are set to 0.

 False

Returns:

Name Type Description
None None

None

Examples:

>>> from spotpython.data.friedman import FriedmanDriftDataset
    data_generator = FriedmanDriftDataset(n_samples=100,
        seed=42, change_point1=50, change_point2=75, constant=False)
    data = [data for data in data_generator]
    indices = [i for _, _, i in data]
    values = {f"x{i}": [] for i in range(5)}
    values["y"] = []
    for x, y, _ in data:
        for i in range(5):
            values[f"x{i}"].append(x[i])
        values["y"].append(y)
    plt.figure(figsize=(10, 6))
    for label, series in values.items():
        plt.plot(indices, series, label=label)
    plt.xlabel('Index')
    plt.ylabel('Value')
    plt.title('')
    plt.axvline(x=50, color='k', linestyle='--', label='Drift Point 1')
    plt.axvline(x=75, color='r', linestyle='--', label='Drift Point 2')
    plt.legend()
    plt.grid(True)
    plt.show()
Source code in spotpython/data/friedman.py 
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def __init__(self, n_samples=100, change_point1=50, change_point2=75, seed=None, constant=False) -> None:
    """Constructor for the Friedman Drift Dataset.

    Args:
        n_samples (int): The number of samples to generate.
        change_point1 (int): The index of the first change point.
        change_point2 (int): The index of the second change point.
        seed (int): The seed for the random number generator.
        constant (bool): If True, only the first feature is set to 1 and all others are set to 0.

    Returns:
        None (None): None

    Examples:
        >>> from spotpython.data.friedman import FriedmanDriftDataset
            data_generator = FriedmanDriftDataset(n_samples=100,
                seed=42, change_point1=50, change_point2=75, constant=False)
            data = [data for data in data_generator]
            indices = [i for _, _, i in data]
            values = {f"x{i}": [] for i in range(5)}
            values["y"] = []
            for x, y, _ in data:
                for i in range(5):
                    values[f"x{i}"].append(x[i])
                values["y"].append(y)
            plt.figure(figsize=(10, 6))
            for label, series in values.items():
                plt.plot(indices, series, label=label)
            plt.xlabel('Index')
            plt.ylabel('Value')
            plt.title('')
            plt.axvline(x=50, color='k', linestyle='--', label='Drift Point 1')
            plt.axvline(x=75, color='r', linestyle='--', label='Drift Point 2')
            plt.legend()
            plt.grid(True)
            plt.show()
    """
    self.n_samples = n_samples
    self._change_point1 = change_point1
    self._change_point2 = change_point2
    self.seed = seed
    self.index = 0
    self.rng = random.Random(self.seed)
    self.constant = constant

__len__()

Returns the length of the dataset.

Returns:

Name Type Description
int int

The length of the dataset.
Source code in spotpython/data/friedman.py 
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def __len__(self) -> int:
    """
    Returns the length of the dataset.

    Returns:
        int: The length of the dataset.


    """
    return self.n_samples