feat: integrate cascade workflow

This commit is contained in:
ws50529
2026-05-27 08:38:40 +08:00
parent 63382f6cf5
commit b8ec600673
17 changed files with 572 additions and 500096 deletions
+47
View File
@@ -1,10 +1,15 @@
import asyncio
import json
import tempfile
import unittest
from pathlib import Path
from unittest.mock import patch
from fastapi import HTTPException
from fastapi.responses import JSONResponse
import dea.csv_processing as csv_processing
from dea.csv_processing import PRESET_FILE_ID
from dea_api import (
BodeCascadeParams,
BodeCompareParams,
@@ -18,6 +23,7 @@ from dea_api import (
design_filter,
filter_csv,
filter_csv_download,
preset_csv,
upload_csv,
write_mcu_command,
)
@@ -159,6 +165,47 @@ class DeaApiTest(unittest.TestCase):
raise AssertionError("Expected invalid MCU command validation to fail")
def test_preset_csv_endpoint_returns_local_ignored_file_metadata(self):
with tempfile.TemporaryDirectory() as tmp:
preset_path = Path(tmp) / "preset_signals.csv"
preset_path.write_text("time,value\n0,1\n1,2\n", encoding="utf-8")
with patch.object(csv_processing, "PRESET_CSV_PATH", str(preset_path)):
body = preset_csv()
self.assertTrue(body["available"])
self.assertEqual(body["file_id"], PRESET_FILE_ID)
self.assertEqual(body["columns"], ["time", "value"])
self.assertEqual(body["default_col_idx"], 1)
self.assertEqual(body["rows"], 2)
def test_filter_can_use_preset_file_id_and_skip_blank_signal_cells(self):
with tempfile.TemporaryDirectory() as tmp:
preset_path = Path(tmp) / "preset_signals.csv"
preset_path.write_text("time,value\n0,1\n1,\n2,3\n", encoding="utf-8")
with patch.object(csv_processing, "PRESET_CSV_PATH", str(preset_path)):
body = asyncio.run(
filter_csv(
file_id=PRESET_FILE_ID,
b="1",
a="1",
col_idx=1,
b_int=None,
a_int=None,
shift_in=14,
shift_out=14,
shift_b=14,
shift_a=14,
use_round=False,
)
)
self.assertEqual(body["total_points"], 2)
self.assertEqual(body["index"], [0, 2])
self.assertEqual(body["original"], [1.0, 3.0])
def test_filter_downsamples_plot_response_for_large_csv(self):
rows = ["value"] + [str(i) for i in range(6001)]
upload = InMemoryUpload(("\n".join(rows) + "\n").encode("utf-8"), "input.csv")