support for optional edge rescaling

This commit is contained in:
Florian Förster 2025-06-20 09:10:37 +02:00
parent 6cdab45e61
commit 76c5ce3d9f
4 changed files with 19 additions and 5 deletions

View File

@ -1,8 +1,8 @@
# d-opt -- lang_main: config file
[paths]
inputs = './lang-data/in/'
results = './lang-data/out/'
inputs = './lang-main/data/tests/in/'
results = './lang-main/data/tests/out/'
models = './lang-models'
graph_export_filename = 'EXPORT-TokenGraph'
@ -35,6 +35,7 @@ threshold_amount_characters = 5
threshold_similarity = 0.92
[graph_postprocessing]
enable_edge_rescaling = false
max_edge_number = -1
[time_analysis.uniqueness]

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@ -1,11 +1,11 @@
[project]
name = "tom-plugin"
version = "0.1.2dev1"
version = "0.1.2"
description = "Wrapper for TOM plugins with different helper CLIs, primarily integration testing"
authors = [
{name = "d-opt GmbH, resp. Florian Förster", email = "f.foerster@d-opt.com"},
]
dependencies = ["lang-main[spacy-md,spacy-trf]>=0.1.1"]
dependencies = ["lang-main[spacy-md,spacy-trf]>=0.1.2.dev3"]
requires-python = ">=3.11"
readme = "README.md"
license = {text = "MIT"}
@ -73,6 +73,7 @@ directory = "reports/coverage"
[tool.pdm]
distribution = true
@ -94,10 +95,13 @@ dev = [
"bump-my-version>=0.29.0",
"jupyterlab>=4.3.4",
"ipywidgets>=8.1.5",
"pytest>=8.4.1",
"coverage>=7.9.1",
"pytest-cov>=6.2.1",
]
[tool.bumpversion]
current_version = "0.1.2dev1"
current_version = "0.1.2"
parse = """(?x)
(?P<major>0|[1-9]\\d*)\\.
(?P<minor>0|[1-9]\\d*)\\.

View File

@ -12,6 +12,7 @@ from lang_main.analysis.graphs import (
)
from lang_main.constants import (
CYTO_BASE_NETWORK_NAME,
ENABLE_EDGE_RESCALING,
INPUT_PATH_FOLDER,
SAVE_PATH_FOLDER,
SKIP_GRAPH_POSTPROCESSING,
@ -51,6 +52,7 @@ pipe_graph_postprocessing = build_tk_graph_post_pipe()
pipe_graph_rescaling = build_tk_graph_rescaling_pipe(
save_result=True,
exit_point=EntryPoints.TK_GRAPH_ANALYSIS_RESCALED,
enable_rescaling=ENABLE_EDGE_RESCALING,
)
pipe_timeline = build_timeline_pipe()

7
tests/test_pipeline.py Normal file
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@ -0,0 +1,7 @@
from tom_plugin import pipeline
def test_pipeline():
test_id = 'test1'
filename = 'Dummy_Dataset_N_1000.csv'
pipeline.run_on_csv_data(id=test_id, filename=filename)