Log

Description

The Log class computes the natural logarithm (ln) of each element in a data sequence. This function is useful for logarithmic scaling, often employed to stabilize variance or compress large data ranges.

Parameters: Log takes no parameters.

NaN handling: NaN values and negative values (since they’re undefined for logarithms) are not modified and remain as NaN.

Usage Example and Plot

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

data = np.abs(np.random.normal(size=30)) + 1
log_data = Log()(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=log_data, mode='lines+markers', name='Natural Log (ln)', line=dict(color='red')), row=2, col=1)

fig.update_layout(
    title="Natural Logarithm Transformation (Log)",
    xaxis_title="Index",
    yaxis_title="Original Data",
    yaxis2_title="Natural Log",
    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()