Div

Description

Div computes the elementwise quotient of two aligned input streams, x / y. It takes two inputs and returns one output; a NaN in either input yields NaN at that step.

Parameters: Div takes no parameters.

Examples

Usage example

import numpy as np
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from screamer import Div

np.random.seed(0)
a = np.cumsum(np.random.normal(size=200))
b = 2 + np.abs(np.cumsum(np.random.normal(size=200)))   # kept positive to avoid divide-by-zero
out = Div()(a, b)                       # elementwise a / b

fig = make_subplots(rows=2, cols=1, shared_xaxes=True,
                    row_heights=[0.55, 0.45], vertical_spacing=0.08)
fig.add_trace(go.Scatter(y=a, mode="lines", name="a"), row=1, col=1)
fig.add_trace(go.Scatter(y=b, mode="lines", name="b"), row=1, col=1)
fig.add_trace(go.Scatter(y=out, mode="lines", name="a / b",
                         line=dict(color="red")), row=2, col=1)
fig.update_layout(title="Elementwise quotient of two signals (Div)",
                  margin=dict(l=20, r=20, t=60, b=20),
                  legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1))
fig.update_yaxes(title_text="inputs", row=1, col=1)
fig.update_yaxes(title_text="a / b", row=2, col=1)
fig.show()

NaN handling

Policy: ignore. A NaN in any input at index t causes the function to skip that step: output at t is NaN and internal state is unchanged. Subsequent finite samples are processed as if step t had not occurred.