Plotting

Module: equser.plotting Dependencies: [analysis] extra (matplotlib)

Static matplotlib plots for PMon and CPOW data. Install with:

pip install equser[analysis]

PowerMonitorPlotter

Plot power monitor (PMon) time-series data.

from equser.plotting import PowerMonitorPlotter

plotter = PowerMonitorPlotter()

# Plot from a file
plotter.plot_file('pmon_data.parquet')

# Plot from a PyArrow Table
from equser.data import load_pmon
table = load_pmon('pmon_data.parquet')
plotter.plot(table)

Methods

Output

Generates a multi-panel figure with:

• Frequency vs. time
• Phase RMS voltages vs. time
• Phase RMS currents vs. time
• Phase active power vs. time

Color scheme follows standard power systems convention (black/red/blue for phases A/B/C).

WaveformPlotter

Plot CPOW waveform captures.

from equser.plotting import WaveformPlotter

plotter = WaveformPlotter()

# Plot from a file
plotter.plot_file('cpow_data.parquet')

Methods

Output

Generates voltage and current waveform plots with proper scaling. The neutral current is automatically adjusted by the CT sensitivity ratio (NEUTRAL_CT_RATIO = 30).

Color schemes

Both plotters support named color schemes:

Saving plots

All plotters return matplotlib figure objects. Save in any format:

fig = plotter.plot_file('data.parquet')
fig.savefig('output.png', dpi=150, bbox_inches='tight')
fig.savefig('output.svg')
fig.savefig('output.pdf')