# ARGRELMIN

The ARGRELMIN node is based on a numpy or scipy function. The description of that function is as follows: Calculate the relative minima of 'data'. Params: data : ndarray Array in which to find the relative minima. axis : int Axis over which to select from 'data'. Default is 0. order : int How many points on each side to use for the comparison to consider "comparator(n, n+x)" to be True. mode : str How the edges of the vector are treated. Available options are 'wrap' (wrap around) or 'clip' (treat overflow as the same as the last (or first) element). Default 'clip'. See numpy.take. Returns: out : DataContainer type 'ordered pair', 'scalar', or 'matrix'
Python Code
from flojoy import OrderedPair, flojoy, Matrix, Scalar

import scipy.signal

@flojoy
def ARGRELMIN(
default: OrderedPair | Matrix,
axis: int = 0,
order: int = 1,
mode: str = "clip",
) -> OrderedPair | Matrix | Scalar:
"""The ARGRELMIN node is based on a numpy or scipy function.

The description of that function is as follows:

Calculate the relative minima of 'data'.

Parameters
----------
data : ndarray
Array in which to find the relative minima.
axis : int, optional
Axis over which to select from 'data'. Default is 0.
order : int, optional
How many points on each side to use for the comparison
to consider "comparator(n, n+x)" to be True.
mode : str, optional
How the edges of the vector are treated.
Available options are 'wrap' (wrap around) or 'clip' (treat overflow
as the same as the last (or first) element).
Default 'clip'. See numpy.take.

Returns
-------
DataContainer
type 'ordered pair', 'scalar', or 'matrix'
"""

result = OrderedPair(
x=default.x,
y=scipy.signal.argrelmin(
data=default.y,
axis=axis,
order=order,
mode=mode,
),
)

return result


Find this Flojoy Block on GitHub