merge: resolve uv.lock conflict with main

Author: MarkusNeusinger

.github/workflows/ci-tests.yml

@@ -122,7 +122,7 @@ jobs:
 
     - name: Upload coverage to GitHub Artifacts
       if: steps.check.outputs.should_test == 'true' && always()
-      uses: actions/upload-artifact@v6
+      uses: actions/upload-artifact@v7
       with:
         name: coverage-report
         path: coverage.xml

app/package.json

@@ -38,13 +38,13 @@
     "@types/react": "^19.2.14",
     "@types/react-dom": "^19.1.7",
     "@types/react-syntax-highlighter": "^15.5.13",
-    "@typescript-eslint/eslint-plugin": "^8.56.0",
-    "@typescript-eslint/parser": "^8.56.0",
+    "@typescript-eslint/eslint-plugin": "^8.56.1",
+    "@typescript-eslint/parser": "^8.56.1",
     "@vitejs/plugin-react-swc": "^4.2.3",
     "@vitest/coverage-v8": "^4.0.18",
-    "eslint": "^10.0.0",
+    "eslint": "^10.0.2",
     "eslint-plugin-react-hooks": "^7.0.1",
-    "eslint-plugin-react-refresh": "^0.5.0",
+    "eslint-plugin-react-refresh": "^0.5.2",
     "jsdom": "^28.1.0",
     "typescript": "^5.9.2",
     "vite": "^7.3.1",

app/yarn.lock

@@ -0,0 +1,27 @@
+# acf-pacf: Autocorrelation and Partial Autocorrelation (ACF/PACF) Plot
+
+## Description
+
+Displays the autocorrelation function (ACF) and partial autocorrelation function (PACF) of a time series as vertical stem/bar plots arranged in two vertically stacked subplots. Each lag is represented by a vertical line from zero to the correlation value, with horizontal dashed lines indicating 95% confidence bounds. These plots are essential for identifying the order of AR and MA components in ARIMA modeling and for diagnosing residual independence.
+
+## Applications
+
+- Identifying appropriate ARIMA(p,d,q) model orders from the decay patterns in ACF and PACF before fitting a time series model
+- Diagnosing model residuals to verify that no significant autocorrelation remains after fitting a forecasting model
+- Detecting seasonal patterns in economic or climate data by observing periodic spikes at seasonal lags
+
+## Data
+
+- `value` (float) - Time series observations in chronological order
+- `timestamp` (datetime, optional) - Time index for the series; equally spaced intervals assumed
+- Size: 100-500 observations recommended for reliable correlation estimates
+- Example: Monthly airline passenger counts, daily stock returns, or hourly temperature readings
+
+## Notes
+
+- Display ACF in the top subplot and PACF in the bottom subplot, sharing the x-axis (lag number)
+- Use vertical stem lines (not filled bars) from the zero baseline to each correlation value
+- Show 95% confidence interval as horizontal dashed lines at approximately +/-1.96/sqrt(N)
+- Include lag 0 in ACF (always 1.0) but start PACF from lag 1
+- Label x-axis as "Lag" and y-axes as "ACF" and "PACF" respectively
+- Use 30-40 lags by default, adjusting based on data length

plots/acf-pacf/specification.md

@@ -0,0 +1,28 @@
+# Specification-level metadata for acf-pacf
+# Auto-synced to PostgreSQL on push to main
+
+spec_id: acf-pacf
+title: Autocorrelation and Partial Autocorrelation (ACF/PACF) Plot
+
+# Specification tracking
+created: "2026-03-07T20:31:52Z"
+updated: null
+issue: 4663
+suggested: MarkusNeusinger
+
+# Classification tags (applies to all library implementations)
+# See docs/reference/tagging-system.md for detailed guidelines
+tags:
+  plot_type:
+    - bar
+    - stem
+  data_type:
+    - timeseries
+    - numeric
+  domain:
+    - statistics
+    - finance
+  features:
+    - correlation
+    - multi
+    - annotated