Toolsets and Dashboards (toolset)
The toolset module provides complete analysis toolsets and dashboard generation capabilities.
Toolset subpackage: Dashboard generation utilities.
This subpackage provides high-level dashboard functions that combine multiple analysis tools into comprehensive visualizations.
- adctoolbox.toolset.generate_aout_dashboard(signal, fs=1.0, freq=None, output_path=None, resolution=12)[source]
Generate comprehensive analysis dashboard with 8 subplots in a 2x4 panel.
- Parameters:
signal (array_like) – Input signal (ADC output or analog signal)
fs (float, optional) – Sampling frequency (default: 1.0 for normalized frequency)
freq (float, optional) – Signal frequency in Hz (default: None, auto-estimate) Will be converted to normalized frequency where needed
output_path (str or Path, optional) – Path to save figure (default: None, don’t save)
resolution (int, optional) – ADC resolution in bits (default: 12)
- Returns:
fig (matplotlib.figure.Figure) – Figure object containing the dashboard
axes (ndarray) – Array of axes objects (2x4 grid, flattened)
- adctoolbox.toolset.generate_dout_dashboard(bits, freq=None, weights=None, output_path=None, show=False)[source]
Generate comprehensive digital analysis dashboard with 6 subplots in a 2x3 panel.
- Parameters:
bits (array_like) – Digital bits (N samples x B bits, MSB to LSB order)
freq (float, optional) – Normalized frequency (0-0.5). If None, auto-detect from calibration
weights (array_like, optional) – Nominal weights for bits (default: None, uses binary weights)
output_path (str or Path, optional) – Path to save figure (default: None, don’t save)
show (bool, optional) – Whether to display figure (default: False)
- Returns:
fig (matplotlib.figure.Figure) – Figure object containing the dashboard
axes (ndarray) – Array of axes objects (2x3 grid, flattened)