Now we will run a sheet resistance analysis using the device analyses we triggered in the device analysis notebook. Make sure all the analyses we triggered are finished (i.e. make sure the last cell in that notebook has finished running)!
As before, make sure you have the following environment variables set or added to a .env file:
GDSFACTORY_HUB_API_URL="https://{org}.gdsfactoryhub.com"
GDSFACTORY_HUB_QUERY_URL="https://query.{org}.gdsfactoryhub.com"
GDSFACTORY_HUB_KEY="<your-gdsfactoryplus-api-key>"
project_id = f"resistance-{getpass.getuser()}"
client = gfh.create_client_from_env(project_id=project_id)
api = client.api()
query = client.query()
utils = client.utils()
{'output': {'sheet_resistance': 97.34212154102445},
'summary_plot': <Figure size 640x480 with 1 Axes>,
'die_pkey': 'ee8b77d0-6488-413a-a0d9-80dc6cae6cf0'}

Just like before we can run the analysis function remotely to see if it runs there too. It might even be faster than the local run, because the server is closer to the database.
We can upload this analysis function:
with gfh.suppress_api_error():
result = api.upload_function(
function_id="die_iv_sheet_resistance",
target_model="die",
file=gfh.get_module_path(iv_sheet_resistance),
test_target_model_pk=die_pkey,
test_kwargs={
"width_key": "width_um",
"length_key": "length_um",
},
)
Duplicate function
Let's start all the analyses:
die_pks = [d["pk"] for d in query.dies().execute().data]
results = []
for die_pk in (pb := tqdm(die_pks)):
pb.set_postfix(die_pk=die_pk)
result = api.start_analysis(
analysis_id=f"die_iv_sheet_resistance_{die_pk}",
function_id="die_iv_sheet_resistance",
target_model="die",
target_model_pk=die_pk,
kwargs={
"width_key": "width_um",
"length_key": "length_um",
},
)
results.append(result)
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Let's have a look at the last analysis:
analysis_pks = [r["pk"] for r in results]
utils.analyses().wait_for_completion(pks=analysis_pks)
analyses = query.analyses().in_("pk", analysis_pks).execute().data
succesful_analyses = [a for a in analyses if a["status"] == "COMPLETED"]
analysis = succesful_analyses[-1]
img = api.download_plot(analysis["summary_plot"]["path"])
img.resize((530, 400))
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