Exp

Description

The Exp class computes the exponential (e^x) of each element in a data sequence. This function is commonly used in exponential growth models and in scenarios requiring data scaling or transformations.

Parameters: Exp takes no parameters.

NaN handling: NaN values are not modified.

Usage Example and Plot

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

data = np.random.normal(size=30) / 5
exp_data = Exp()(data)

fig = make_subplots(
    rows=2, cols=1,
    shared_xaxes=True,
    row_heights=[1/2, 1/2],
    vertical_spacing=0.1
)

fig.add_trace(go.Scatter(y=data, mode='lines+markers', name='Original Data'), row=1, col=1)
fig.add_trace(go.Scatter(y=exp_data, mode='lines+markers', name='Exponential (e^x)', line=dict(color='red')), row=2, col=1)

fig.update_layout(
    title="Exponential Transformation (Exp)",
    xaxis_title="Index",
    yaxis_title="Original Data",
    yaxis2_title="Exponential",
    margin=dict(l=20, r=20, t=80, b=20),
    legend=dict(orientation="h", yanchor="bottom", y=1.02, xanchor="right", x=1)
)

fig.show()