Visualizing Layouts

Once a LayoutView is created, you can visualize and inspect it using the IPKISS Layout visualizer via the .visualize() method, as shown below:

import si_fab.all as pdk
import ipkiss3.all as i3

mmi = pdk.MMI1x2Optimized1550()
mmi_layout = mmi.Layout()

mmi_layout.visualize()

Within the IPKISS Layout visualizer, you can explore your layout and perform a range of actions, such as

toggling labels, the grid, and port labels
snapping the layout to the grid
hiding or showing layers

The .visualize() method accepts several parameters (see visualize) that were previously used to customize the layout display in the earlier matplotlib-based visualizer. These parameters have no effect in the newer IPKISS Layout visualizer, since layout display customization is now handled directly through the GUI.

Using the matplotlib visualizer

To use a different visualizer, such as the earlier visualizer based on matplotlib, you can do so by either:

setting the engine argument in the .visualize() call
setting the IPKISS_VISUALIZER_ENGINE environment variable

In this case, all parameters of .visualize() can be used to customize the layout appearance.

The example below shows how to visualize a layout using matplotlib, with annotations enabled:

import si_fab.all as pdk
import ipkiss3.all as i3

mmi = pdk.MMI1x2Optimized1550()
mmi_layout = mmi.Layout()

mmi_layout.visualize(engine="matplotlib", annotate=True)

visualize

class ipkiss3.all.LayoutView

Parameters:

view_name: String that contains only alphanumeric characters from the ASCII set or contains _$. ASCII set is extended on PY3.: The name of the view

visualize(canvas_size=None, box=None, show=True, display_styles=<ipkiss3.technology.TechValue object>, default_display_style=None, annotate=False, labels=True, figure=None, legacy=False, grid=True, engine=None)

Visualize a layout.

NOTE: None of these parameters interact with the new IPKISS Layout Visualizer.

One can decide to use another visualizer, by following one of two methods.

setting the engine argument in the visualize call
setting the env variable IPKISS_VISUALIZER_ENGINE

Both can receive three values: ‘ipkiss-layout’, ‘matplotlib’, ‘legacy’

Parameters:

canvas_size: list: Size of the canvas: [width, height]
box: list: (deprecated) Box size, [north, east, south, west]
show: boolean: Show the image, default is True.
display_styles: DisplayStyleSet: The display style set, default is TECH.DISPLAY.DEFAULT_DISPLAY_STYLE_SET.
default_display_style: DisplayStyle: The default display style in case a layer is not associated with one, the default is DisplayStyle(alpha=0.4).
annotate: boolean: Whether to annotate the ports, default is False.
labels: boolean: Whether to show the labels, default is True.
figure: Figure: Reuse an existing matplotlib Figure. By default, a new Figure will be created.
legacy: boolean: (deprecated, use engine instead) Use the legacy version of visualize
grid: boolean: Show the gridlines, default is True.
engine: EngineType | None: Decide which engine the visualizer uses. See the NOTE in this docstring.

Returns:

None, if applicable a matplotlib Figure.