Examples

Note

All code below targets yaml2plot 2.0.0. The modern workflow is:

1. data = y2p.load_spice_raw("my.raw") – obtain an xarray.Dataset with signals and metadata

2. spec = y2p.PlotSpec.from_yaml(""" ... """) – build a PlotSpec (YAML string or file)

3. fig = y2p.plot(data, spec) – create the Plotly figure

This page contains practical examples for common use cases with yaml2plot.

Basic Waveform Plot

Plot input and output voltages from an amplifier simulation:

import yaml2plot as y2p

# Load simulation data
data = y2p.load_spice_raw("amplifier.raw")

# Simple voltage plot using YAML configuration
spec = y2p.PlotSpec.from_yaml("""
title: "Amplifier Response"
x:
 signal: "time"
 label: "Time (s)"
y:
  - label: "Voltage (V)"
    signals:
      Input: "v(in)"
      Output: "v(out)"
""")

fig = y2p.plot(data, spec)

Multi-Y-Axis Plot

Create multiple strips with shared x-axis and rangeslider:

data = y2p.load_spice_raw("complete_analysis.raw")

spec = y2p.PlotSpec.from_yaml("""
title: "Complete Circuit Analysis"
x:
 signal: "time"
 label: "Time (s)"
y:
  - label: "Voltage (V)"
    signals:
      Input: "v(in)"
      Output: "v(out)"
  - label: "Current (A)"
    signals:
      M1: "i(m1)"
      M2: "i(m2)"
  - label: "Supply Voltage (V)"
    signals:
      VDD: "v(vdd)"
      VSS: "v(vss)"
 show_rangeslider: true
""")

fig = y2p.plot(data, spec)

AC Analysis with Complex Signal Processing

AC analysis results contain complex numbers for voltage and current signals, enabling proper magnitude and phase analysis for transfer functions and Bode plots:

import yaml2plot as y2p
import numpy as np

# Load AC analysis data (contains complex numbers)
data = y2p.load_spice_raw("ac_analysis.raw")

tf = data["v(out)"]/data["v(in)"]
data["tf_db"] = 20*np.log10(np.abs(tf))
data["tf_phase"] = np.angle(tf)/np.pi*180

spec = y2p.PlotSpec.from_yaml("""
title: "Transfer Function Bode Plot"
x:
 signal: "frequency"
 label: "Frequency (Hz)"
 scale: "log"
y:
  - label: "Magnitude (dB)"
    signals:
      H(jω): "tf_db"
  - label: "Phase (degrees)"
    signals:
      φ(jω): "tf_phase"
height: 800
show_rangeslider: true
""")

fig = y2p.plot(data, spec)

Comparison Plots

Compare results from different simulation runs:

import xarray as xr
# Load multiple simulations
data1 = y2p.load_spice_raw("before_optimization.raw")
data2 = y2p.load_spice_raw("after_optimization.raw")

# Create comparison signals
data = xr.Dataset()
data["v_out_before"] = data1["v(out)"]
data["v_out_after"] = data2["v(out)"]

spec = y2p.PlotSpec.from_yaml("""
title: "Optimization Comparison"
x:
 signal: "time"
 label: "Time (s)"
y:
  - label: "Voltage (V)"
    signals:
      Before: "v_out_before"
      After: "v_out_after"
""")

fig = y2p.plot(data, spec)