DIVIDE

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Divide two or more numeric arrays, matrices, dataframes, or constants element-wise. When a constant is divided into an array or matrix, each element in the array or matrix will be divided by the constant value. Params: a : OrderedPair|Scalar|Vector The input that will be divided by b. b : OrderedPair|Scalar|Vector The input that will divide a. Returns: out : OrderedPair|Scalar|Vector OrderedPair if a is an OrderedPair. x: the x-axis of input a. y: the result of the division of input a by input b. Scalar if a is a Scalar. c: the result of the division of input a by input b. Vector if a is a Vector. v: the result of the division of input a by input b.

Python Code

import numpy as np
from flojoy import flojoy, OrderedPair, Scalar, Vector
from blocks.MATH.ARITHMETIC.utils.arithmetic_utils import get_val
from functools import reduce


@flojoy
def DIVIDE(
    a: OrderedPair | Scalar | Vector, b: list[OrderedPair | Scalar | Vector]
) -> OrderedPair | Scalar | Vector:
    """Divide two or more numeric arrays, matrices, dataframes, or constants element-wise.

    When a constant is divided into an array or matrix, each element in the array or matrix will be divided by the constant value.

    Parameters
    ----------
    a : OrderedPair|Scalar|Vector
        The input that will be divided by b.
    b : OrderedPair|Scalar|Vector
        The input that will divide a.

    Returns
    -------
    OrderedPair|Scalar|Vector
        OrderedPair if a is an OrderedPair.
        x: the x-axis of input a.
        y: the result of the division of input a by input b.

        Scalar if a is a Scalar.
        c: the result of the division of input a by input b.

        Vector if a is a Vector.
        v: the result of the division of input a by input b.
    """

    initial = get_val(a)
    seq = map(lambda dc: get_val(dc), b)
    y = reduce(lambda u, v: np.divide(u, v), seq, initial)

    match a:
        case OrderedPair():
            return OrderedPair(x=a.x, y=y)
        case Vector():
            return Vector(v=y)
        case Scalar():
            return Scalar(c=y)

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Example App

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In this example we use DIVIDE to undo the effects of a SINE node.

We first generate two sine functions using LINSPACE and SINE nodes, and then use DIVIDE node to cancel them out which generates a flat scatter plot in SCATTER node.