Layout

Layout#

The first step is to create a layout and test manifest for your project, so that you can relate measurements and analyses back to your source layout.

You can generate the layout with any layout tool. In this notebook you can use gdsfactory.

Generate layout#

You can use generate_layout.py to create a GDS layout file with different rings.

from generate_layout import top

c = top()
c.write_gds("test_chip.gds")
c.plot()
../../../_images/4522b4569f1fa25315611578f4def9d8ba974a3a67e52b4914261dec07dbe6f1.png

Generate device table#

A design manifest is a table of devices and settings. A device contains the cell id, (x, y) locations and settings.

It can also optionally contain analysis and analysis_parameters that will trigger automated analysis when uploading new data associated to the device.

Here you can read them from the GDS and write a design manifest, which we can use to associate measurement data with the devices on the GDS. However, you can use any method you prefer to generate your test manifest.

import kfactory as kf
import csv

c = kf.kcl["top"]
rings = c.kcl["rings"]
csvpath = "design_manifest.csv"

analysis = "[fsr]"
analysis_parameters = '[{"height": -0.01, "distance": 20}]'

with open(csvpath, "w") as f:
    writer = csv.writer(f)
    writer.writerow(
        [
            "cell",
            "x",
            "y",
            "radius_um",
            "gap_um",
            "analysis",
            "analysis_parameters",
        ]
    )

    iterator = rings.kdb_cell.begin_instances_rec()
    iterator.targets = "Ring*"
    while not iterator.at_end():
        _c = c.kcl[iterator.inst_cell().cell_index()]
        name = _c.name
        if "RingDouble" in name:
            _disp = (iterator.trans() * iterator.inst_trans()).disp
            params = name.split("-")
            writer.writerow(
                [
                    name,
                    _disp.x,
                    _disp.y,
                    int(params[1]),
                    float(params[2]),
                    analysis,
                    analysis_parameters,
                ]
            )
        iterator.next()

You can take a look a the contents of the device manifest you created.

import pandas as pd

df = pd.read_csv(csvpath)
df
cell x y radius_um gap_um analysis analysis_parameters
0 RingDouble-20-0.25- 331580 121311 20 0.25 [fsr] [{"height": -0.01, "distance": 20}]
1 RingDouble-20-0.2- 331580 285371 20 0.20 [fsr] [{"height": -0.01, "distance": 20}]
2 RingDouble-20-0.15- 331580 449331 20 0.15 [fsr] [{"height": -0.01, "distance": 20}]
3 RingDouble-10-0.2- 331480 613191 10 0.20 [fsr] [{"height": -0.01, "distance": 20}]
4 RingDouble-10-0.15- 331480 757151 10 0.15 [fsr] [{"height": -0.01, "distance": 20}]
5 RingDouble-10-0.1- 331480 901011 10 0.10 [fsr] [{"height": -0.01, "distance": 20}]
6 RingDouble-5-0.2- 331480 1044771 5 0.20 [fsr] [{"height": -0.01, "distance": 20}]
7 RingDouble-5-0.15- 331480 1178731 5 0.15 [fsr] [{"height": -0.01, "distance": 20}]
8 RingDouble-5-0.1- 331480 1312591 5 0.10 [fsr] [{"height": -0.01, "distance": 20}]
Contents