Skip to content

Plotting

The toolkit provides two plotting systems: static plots (matplotlib, rendered as PNG) and live plots (pyqtgraph, real-time in the GUI). Both work with measurement data collected via the assignment syntax (label = instrument meas ...).

Static plots — plot

Render the measurement log (or a filtered subset) as a PNG image.

plot                                    # plot all measurements
plot linereg_*                          # only labels matching a glob pattern
plot linereg_* loadreg_*                # multiple patterns
plot --title "Line Regulation"          # custom title
plot load_* --save ../plots/load.png    # save to a specific path

The chart opens as an image tab in the GUI. If the matched measurements have different units (e.g. V and A), they are split into separate subplots automatically.

Options

Flag Description
--title "text" Set the plot title.
--save <path.png> Save the plot to a PNG file. Relative paths are resolved from the script directory.

Live plots — liveplot

Open a live-updating chart that refreshes as new measurements are recorded. This is the main way to visualize data during a sweep or ramp — you see each point appear in real time.

liveplot dmm_*                                          # one series
liveplot psu_v_* psu_i_*                                # two series on ONE chart
liveplot dmm_* --title "Sweep" --xlabel "Time (s)" --ylabel "Voltage (V)"

How it works

  1. Run the liveplot command before collecting data (typically at the top of your script).
  2. A new tab opens in the GUI immediately.
  3. As measurements are recorded, matching points appear on the chart automatically.
  4. The x-axis is time (seconds since the REPL session started).

Multiple series vs. multiple plots

  • Multiple patterns, one command = multiple series overlaid on one chart: 

    liveplot psu_v_* psu_i_*    # voltage and current on the same chart

  • Multiple liveplot commands = separate tabs: 

    liveplot psu_v_* --title "Voltage"    # tab 1
liveplot psu_i_* --title "Current"    # tab 2

Options

Flag Description
--title "text" Chart title (shown at the top).
--xlabel "text" X-axis label. Defaults to "Time (s)".
--ylabel "text" Y-axis label. Auto-detected from measurement units if not set.

Interacting with live plots

The live plot widget is fully interactive:

Action What it does
Scroll wheel Zoom in/out
Click + drag Pan around
Double-click Auto-fit view to all data

Crosshair and inspection

Action What it does
Hover Crosshair follows mouse, coordinate readout updates (bottom-right)
Click near a point Tooltip shows: label, value, unit, time, and series name

Toolbar buttons

Button Description
Pause / Resume Freeze the chart to examine data without it scrolling
Clear Wipe all displayed data. Only data recorded after the clear will appear
Fit Reset zoom to fit all data
Export Save the current view as a PNG image
Select Enter rectangle selection mode (see below)
Cross Toggle crosshair on/off
Grid Toggle grid lines on/off
Series buttons Click to show/hide individual series (only appears with multiple patterns)
Refresh Spinner controlling how often the chart updates (1–30 times per second)

Rectangle selection and Detail View

You can select a region of the live plot and open it in a standalone window for closer analysis.

Selecting data

  1. Click the Select button in the toolbar.
  2. Click the first corner of the region you want.
  3. Move the mouse — a white dashed rectangle previews the selection.
  4. Click the second corner — the rectangle locks in.
  5. A blue Open Selection button appears. Click it.

A new Detail Plot Window opens with only the data points inside your rectangle.

Detail Plot Window

The detail window is a standalone, editable plot for analysis and export:

Feature Description
Title / X / Y fields Type to change labels — the chart updates live
Grid Toggle grid lines
Cross Toggle crosshair
Fit Auto-range to all data
Export PNG Save as a 1920px-wide PNG image
Save CSV Export the selected data as a CSV file with columns: series, label, time, value
Click-to-inspect Same tooltip behavior as the live plot
Zoom / Pan Same scroll and drag behavior

SCPI examples with live plots

These bundled examples demonstrate live plotting. All work with --mock for testing without hardware.

live_voltage_sweep

Sweeps PSU through 51 voltage steps (0.5 V to 12 V via linspace) while a live plot tracks DMM readings.

examples load live_voltage_sweep
script run live_voltage_sweep

live_multi_plot

Opens two live-plot tabs (voltage and current) and ramps the PSU through 51 steps.

examples load live_multi_plot
script run live_multi_plot

live_combined_plot

Plots voltage and current as two series overlaid on a single chart. The key difference from live_multi_plot: one liveplot command with two patterns instead of two separate commands.

examples load live_combined_plot
script run live_combined_plot

live_freq_sweep

Sweeps AWG through 16 frequencies while a live plot tracks scope frequency measurements.

examples load live_freq_sweep
script run live_freq_sweep

Python API examples

Every example above also has a Python version. Import from the GUI menu under Examples > Python Scripts, or use the REPL:

python examples/python/live_voltage_sweep.py
python examples/python/live_multi_plot.py
python examples/python/live_combined_plot.py
python examples/python/live_freq_sweep.py

In Python scripts, start a live plot with:

repl.onecmd('liveplot dmm_* --title "My Plot" --xlabel "Time (s)" --ylabel "Voltage (V)"')

Record measurements with:

measured = dmm.measure_dc_voltage()
repl.ctx.measurements.record("dmm_5.0V", measured, "V", "dmm1")

Use linspace-style loops for many data points:

step = (V_END - V_START) / STEPS
voltages = [V_START + step * i for i in range(STEPS + 1)]

for target_v in voltages:
    psu.set_output_channel(ch, target_v, CURRENT_LIMIT)
    time.sleep(0.15)
    measured = dmm.measure_dc_voltage()
    repl.ctx.measurements.record(f"dmm_{target_v:.2f}V", measured, "V", "dmm1")

Stopping a running script

When any script or command is running, a red Running banner appears at the bottom of the console with a STOP button.

Clicking STOP:

  1. Kills the running thread immediately — does not wait for the current command to finish.
  2. Sets all instrument outputs to safe state (E-STOP) — voltages go to 0, outputs disable.
  3. Logs [STOPPED] Execution killed. All outputs set to safe state. to the console.

This is a kill switch. Use it when something goes wrong.

Tips

  • Run liveplot before the loop that collects data, so the tab is open and ready.
  • Use linspace (SCPI) or a Python list comprehension for many evenly-spaced points — 50+ points makes the live update clearly visible.
  • The Clear button only affects the display. The measurement store still has the data. Running a new script opens a new plot tab that starts fresh.
  • Use Select + Detail View to isolate an interesting region, then Save CSV for further analysis in Excel or Python.
  • Multiple live-plot tabs can be open simultaneously — each tracks its own patterns independently.