commit miss, recover server.ts

This commit is contained in:
raymond 2025-09-10 06:20:48 +00:00
parent 1b49ae20fe
commit 0aa6248a9b

500
server.ts
View file

@ -1,6 +1,6 @@
// server.ts - Simplified main server file
// package.json dependencies needed:
// npm install express mathjs lodash date-fns swagger-jsdoc swagger-ui-express js-yaml
// npm install express mathjs lodash date-fns
// npm install -D @types/express @types/node @types/lodash typescript ts-node
import express from 'express';
@ -8,25 +8,9 @@ import swaggerJsdoc from 'swagger-jsdoc';
import swaggerUi from 'swagger-ui-express';
import * as math from 'mathjs';
import * as _ from 'lodash';
// These imports assume the files exist in the same directory
// import { KMeans, KMeansOptions } from './kmeans';
// import { getWeekNumber, getSameWeekDayLastYear } from './time-helper';
// import { calculateLinearRegression, generateForecast, calculatePredictionIntervals, ForecastResult } from './prediction';
import { SignalProcessor, SmoothingOptions, EdgeDetectionOptions } from './signal_processing_convolution';
import { convolve1D, ConvolutionKernels } from './convolution'; // Direct import for new functions
interface KMeansOptions {}
class KMeans {
constructor(p: any, n: any, o: any) {}
run = () => ({ clusters: [] })
}
const getWeekNumber = (d: string) => 1;
const getSameWeekDayLastYear = (d: string) => new Date().toISOString();
interface ForecastResult {}
const calculateLinearRegression = (v: any) => ({slope: 1, intercept: 0});
const generateForecast = (m: any, l: any, p: any) => [];
const calculatePredictionIntervals = (v: any, m: any, f: any) => [];
import { KMeans, KMeansOptions } from './kmeans';
import { getWeekNumber, getSameWeekDayLastYear } from './time-helper';
import { calculateLinearRegression, generateForecast, calculatePredictionIntervals, ForecastResult } from './prediction';
const app = express();
app.use(express.json());
@ -46,7 +30,8 @@ const swaggerOptions = {
},
],
},
apis: ["./server.ts"], // Pointing to this file for Swagger docs
// Paths to files containing OpenAPI definitions
apis: ["./*.ts"], // Make sure this path is correct
};
const swaggerSpec = swaggerJsdoc(swaggerOptions);
@ -274,8 +259,8 @@ class AnalyticsEngine {
const kmeans = new KMeans(points, nClusters, options);
const result = kmeans.run();
const centroids = result.clusters.map(c => (c as any).centroid);
const clusters = result.clusters.map(c => (c as any).points);
const centroids = result.clusters.map(c => c.centroid);
const clusters = result.clusters.map(c => c.points);
return { clusters, centroids };
}
@ -360,9 +345,8 @@ const analytics = new AnalyticsEngine();
* get:
* summary: Health check endpoint
* description: Returns the health status of the API
* tags: [Health]
* responses:
* '200':
* 200:
* description: API is healthy
* content:
* application/json:
@ -386,7 +370,6 @@ app.get('/api/health', (req, res) => {
* post:
* summary: Get unique values from a data series
* description: Returns an array of unique values from the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -397,9 +380,9 @@ app.get('/api/health', (req, res) => {
* series:
* $ref: '#/components/schemas/DataSeries'
* responses:
* '200':
* 200:
* description: Unique values calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/unique', (req, res) => {
@ -418,7 +401,6 @@ app.post('/api/unique', (req, res) => {
* post:
* summary: Calculate mean of a data series
* description: Returns the arithmetic mean of the provided data series, optionally filtered by conditions
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -433,9 +415,9 @@ app.post('/api/unique', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Mean calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/mean', (req, res) => {
@ -454,7 +436,6 @@ app.post('/api/mean', (req, res) => {
* post:
* summary: Count data points in a series
* description: Returns the count of data points in the series, optionally filtered by conditions
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -469,9 +450,9 @@ app.post('/api/mean', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Count calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/count', (req, res) => {
@ -490,7 +471,6 @@ app.post('/api/count', (req, res) => {
* post:
* summary: Calculate variance of a data series
* description: Returns the variance of the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -505,9 +485,9 @@ app.post('/api/count', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Variance calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/variance', (req, res) => {
@ -526,7 +506,6 @@ app.post('/api/variance', (req, res) => {
* post:
* summary: Calculate standard deviation of a data series
* description: Returns the standard deviation of the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -541,9 +520,9 @@ app.post('/api/variance', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Standard deviation calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/std', (req, res) => {
@ -562,7 +541,6 @@ app.post('/api/std', (req, res) => {
* post:
* summary: Calculate percentile of a data series
* description: Returns the specified percentile of the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -585,9 +563,9 @@ app.post('/api/std', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Percentile calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/percentile', (req, res) => {
@ -606,7 +584,6 @@ app.post('/api/percentile', (req, res) => {
* post:
* summary: Calculate median of a data series
* description: Returns the median (50th percentile) of the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -621,9 +598,9 @@ app.post('/api/percentile', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Median calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/median', (req, res) => {
@ -642,7 +619,6 @@ app.post('/api/median', (req, res) => {
* post:
* summary: Calculate mode of a data series
* description: Returns the mode (most frequent values) of the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -657,9 +633,9 @@ app.post('/api/median', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Mode calculated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/mode', (req, res) => {
@ -678,7 +654,6 @@ app.post('/api/mode', (req, res) => {
* post:
* summary: Find maximum value in a data series
* description: Returns the maximum value from the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -693,9 +668,9 @@ app.post('/api/mode', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Maximum value found successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/max', (req, res) => {
@ -714,7 +689,6 @@ app.post('/api/max', (req, res) => {
* post:
* summary: Find minimum value in a data series
* description: Returns the minimum value from the provided data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -729,9 +703,9 @@ app.post('/api/max', (req, res) => {
* items:
* $ref: '#/components/schemas/Condition'
* responses:
* '200':
* 200:
* description: Minimum value found successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/min', (req, res) => {
@ -750,7 +724,6 @@ app.post('/api/min', (req, res) => {
* post:
* summary: Calculate correlation between two data series
* description: Returns the Pearson correlation coefficient between two data series
* tags: [Statistics]
* requestBody:
* required: true
* content:
@ -763,9 +736,9 @@ app.post('/api/min', (req, res) => {
* series2:
* $ref: '#/components/schemas/DataSeries'
* responses:
* '200':
* 200:
* description: Correlation calculated successfully
* '400':
* 400:
* description: Invalid input data or series have different lengths
*/
app.post('/api/correlation', (req, res) => {
@ -784,7 +757,6 @@ app.post('/api/correlation', (req, res) => {
* post:
* summary: Calculate moving average of a data series
* description: Returns the moving average of the provided data series with specified window size
* tags: [Series Operations]
* requestBody:
* required: true
* content:
@ -800,9 +772,9 @@ app.post('/api/correlation', (req, res) => {
* minimum: 1
* example: 5
* responses:
* '200':
* 200:
* description: Moving average calculated successfully
* '400':
* 400:
* description: Invalid input data or window size
*/
app.post('/api/series/moving-average', (req, res) => {
@ -822,7 +794,6 @@ app.post('/api/series/moving-average', (req, res) => {
* post:
* summary: Get rolling windows of a data series
* description: Returns rolling windows of the provided data series with specified window size
* tags: [Series Operations]
* requestBody:
* required: true
* content:
@ -838,9 +809,9 @@ app.post('/api/series/moving-average', (req, res) => {
* minimum: 1
* example: 3
* responses:
* '200':
* 200:
* description: Rolling windows calculated successfully
* '400':
* 400:
* description: Invalid input data or window size
*/
app.post('/api/series/rolling', (req, res) => {
@ -860,7 +831,6 @@ app.post('/api/series/rolling', (req, res) => {
* post:
* summary: Perform K-means clustering
* description: Performs K-means clustering on the provided data matrix
* tags: [Machine Learning]
* requestBody:
* required: true
* content:
@ -879,9 +849,9 @@ app.post('/api/series/rolling', (req, res) => {
* type: object
* description: K-means options
* responses:
* '200':
* 200:
* description: K-means clustering completed successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/ml/kmeans', (req, res) => {
@ -900,7 +870,6 @@ app.post('/api/ml/kmeans', (req, res) => {
* post:
* summary: Get week number from date
* description: Returns the ISO week number for the provided date string
* tags: [Time]
* requestBody:
* required: true
* content:
@ -914,9 +883,9 @@ app.post('/api/ml/kmeans', (req, res) => {
* description: Date string in ISO format
* example: "2024-03-15"
* responses:
* '200':
* 200:
* description: Week number calculated successfully
* '400':
* 400:
* description: Invalid date format
*/
app.post('/api/time/week-number', (req, res) => {
@ -936,7 +905,6 @@ app.post('/api/time/week-number', (req, res) => {
* post:
* summary: Get same day of week from last year
* description: Returns the date string for the same day of the week from the previous year
* tags: [Time]
* requestBody:
* required: true
* content:
@ -950,9 +918,9 @@ app.post('/api/time/week-number', (req, res) => {
* description: Date string in ISO format
* example: "2024-03-15"
* responses:
* '200':
* 200:
* description: Same day last year calculated successfully
* '400':
* 400:
* description: Invalid date format
*/
app.post('/api/time/same-day-last-year', (req, res) => {
@ -972,7 +940,6 @@ app.post('/api/time/same-day-last-year', (req, res) => {
* post:
* summary: Calculate purchase rate
* description: Calculates the purchase rate as a percentage of product purchases over total transactions
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -989,9 +956,9 @@ app.post('/api/time/same-day-last-year', (req, res) => {
* description: Total number of transactions
* example: 1000
* responses:
* '200':
* 200:
* description: Purchase rate calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/purchase-rate', (req, res) => {
@ -1010,7 +977,6 @@ app.post('/api/retail/purchase-rate', (req, res) => {
* post:
* summary: Calculate lift value
* description: Calculates the lift value for market basket analysis
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -1031,9 +997,9 @@ app.post('/api/retail/purchase-rate', (req, res) => {
* description: Purchase rate of product B
* example: 0.3
* responses:
* '200':
* 200:
* description: Lift value calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/lift-value', (req, res) => {
@ -1052,7 +1018,6 @@ app.post('/api/retail/lift-value', (req, res) => {
* post:
* summary: Calculate cost ratio
* description: Calculates the cost ratio (cost divided by sale price)
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -1069,9 +1034,9 @@ app.post('/api/retail/lift-value', (req, res) => {
* description: Sale price of the product
* example: 100
* responses:
* '200':
* 200:
* description: Cost ratio calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/cost-ratio', (req, res) => {
@ -1090,7 +1055,6 @@ app.post('/api/retail/cost-ratio', (req, res) => {
* post:
* summary: Calculate gross margin rate
* description: Calculates the gross margin rate as a percentage
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -1107,9 +1071,9 @@ app.post('/api/retail/cost-ratio', (req, res) => {
* description: Cost of the product
* example: 60
* responses:
* '200':
* 200:
* description: Gross margin rate calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/gross-margin', (req, res) => {
@ -1128,7 +1092,6 @@ app.post('/api/retail/gross-margin', (req, res) => {
* post:
* summary: Calculate average spend per customer
* description: Calculates the average amount spent per customer
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -1145,9 +1108,9 @@ app.post('/api/retail/gross-margin', (req, res) => {
* description: Number of customers
* example: 500
* responses:
* '200':
* 200:
* description: Average spend calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/average-spend', (req, res) => {
@ -1167,7 +1130,6 @@ app.post('/api/retail/average-spend', (req, res) => {
* post:
* summary: Calculate purchase index
* description: Calculates the purchase index (items per 1000 customers)
* tags: [Retail]
* requestBody:
* required: true
* content:
@ -1184,9 +1146,9 @@ app.post('/api/retail/average-spend', (req, res) => {
* description: Number of customers
* example: 1000
* responses:
* '200':
* 200:
* description: Purchase index calculated successfully
* '400':
* 400:
* description: Invalid input data or division by zero
*/
app.post('/api/retail/purchase-index', (req, res) => {
@ -1206,7 +1168,6 @@ app.post('/api/retail/purchase-index', (req, res) => {
* post:
* summary: Generate time series forecast
* description: Generates a forecast for time series data using linear regression
* tags: [Prediction]
* requestBody:
* required: true
* content:
@ -1222,9 +1183,9 @@ app.post('/api/retail/purchase-index', (req, res) => {
* minimum: 1
* example: 10
* responses:
* '200':
* 200:
* description: Forecast generated successfully
* '400':
* 400:
* description: Invalid input data
*/
app.post('/api/predict/forecast', (req, res) => {
@ -1238,316 +1199,6 @@ app.post('/api/predict/forecast', (req, res) => {
}
});
// ========================================
// NEW SIGNAL & IMAGE PROCESSING ROUTES
// ========================================
/**
* @swagger
* /api/signal/smooth:
* post:
* summary: Smooth a 1D data series
* description: Applies a smoothing filter (Gaussian or Moving Average) to a 1D data series to reduce noise.
* tags: [Signal Processing]
* requestBody:
* required: true
* content:
* application/json:
* schema:
* type: object
* properties:
* series:
* $ref: '#/components/schemas/DataSeries'
* options:
* $ref: '#/components/schemas/SmoothingOptions'
* responses:
* '200':
* description: The smoothed data series
* content:
* application/json:
* schema:
* $ref: '#/components/schemas/ApiResponse'
* '400':
* description: Invalid input data
*/
app.post('/api/signal/smooth', (req, res) => {
try {
const { series, options } = req.body;
validateSeries(series);
const result = SignalProcessor.smooth(series.values, options);
res.status(200).json({ success: true, data: result } as ApiResponse<number[]>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<number[]>);
}
});
/**
* @swagger
* /api/signal/detect-peaks:
* post:
* summary: Detect peaks in a 1D data series
* description: Identifies local maxima (peaks) in a 1D data series. More robust and accurate logic.
* tags: [Signal Processing]
* requestBody:
* required: true
* content:
* application/json:
* schema:
* type: object
* properties:
* series:
* $ref: '#/components/schemas/DataSeries'
* options:
* type: object
* properties:
* smoothWindow:
* type: integer
* description: Optional window size for Gaussian smoothing to reduce noise before peak detection.
* example: 3
* minDistance:
* type: integer
* description: The minimum number of data points between two peaks.
* example: 1
* threshold:
* type: number
* description: The minimum value for a data point to be considered a peak.
* example: 0.5
* responses:
* '200':
* description: An array of detected peak objects, each with an index and value.
* '400':
* description: Invalid input data
*/
app.post('/api/signal/detect-peaks', (req, res) => {
try {
const { series, options } = req.body;
validateSeries(series);
const result = SignalProcessor.detectPeaksConvolution(series.values, options);
res.status(200).json({ success: true, data: result } as ApiResponse<any>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<any>);
}
});
/**
* @swagger
* /api/signal/detect-valleys:
* post:
* summary: Detect valleys in a 1D data series
* description: Identifies local minima (valleys) in a 1D data series. More robust and accurate logic.
* tags: [Signal Processing]
* requestBody:
* required: true
* content:
* application/json:
* schema:
* type: object
* properties:
* series:
* $ref: '#/components/schemas/DataSeries'
* options:
* type: object
* properties:
* smoothWindow:
* type: integer
* description: Optional window size for Gaussian smoothing to reduce noise before valley detection.
* example: 3
* minDistance:
* type: integer
* description: The minimum number of data points between two valleys.
* example: 1
* threshold:
* type: number
* description: The maximum value for a data point to be considered a valley.
* example: -0.5
* responses:
* '200':
* description: An array of detected valley objects, each with an index and value.
* '400':
* description: Invalid input data
*/
app.post('/api/signal/detect-valleys', (req, res) => {
try {
const { series, options } = req.body;
validateSeries(series);
const result = SignalProcessor.detectValleysConvolution(series.values, options);
res.status(200).json({ success: true, data: result } as ApiResponse<any>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<any>);
}
});
/**
* @swagger
* /api/signal/detect-outliers:
* post:
* summary: Detect outliers in a 1D data series
* description: Identifies outliers in a 1D data series using statistically sound methods.
* tags: [Signal Processing]
* requestBody:
* required: true
* content:
* application/json:
* schema:
* type: object
* properties:
* series:
* $ref: '#/components/schemas/DataSeries'
* options:
* type: object
* properties:
* method:
* type: string
* enum: [local_deviation, mean_diff]
* default: local_deviation
* windowSize:
* type: integer
* default: 7
* threshold:
* type: number
* description: "The sensitivity threshold. For 'local_deviation', this is the number of standard deviations (Z-score)."
* default: 3.0
* responses:
* '200':
* description: An array of detected outlier objects.
* content:
* application/json:
* schema:
* $ref: '#/components/schemas/ApiResponse'
* '400':
* description: Invalid input data
*/
app.post('/api/signal/detect-outliers', (req, res) => {
try {
const { series, options } = req.body;
validateSeries(series);
const result = SignalProcessor.detectOutliersConvolution(series.values, options);
res.status(200).json({ success: true, data: result } as ApiResponse<any>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<any>);
}
});
/**
* @swagger
* /api/signal/detect-vertices:
* post:
* summary: Detect trend vertices (turning points) in a 1D series
* description: Identifies all significant peaks and valleys in a data series trend using a robust local maxima/minima search.
* tags: [Signal Processing]
* requestBody:
* required: true
* content:
* application/json:
* schema:
* type: object
* properties:
* series:
* $ref: '#/components/schemas/DataSeries'
* options:
* type: object
* properties:
* smoothingWindow:
* type: integer
* default: 5
* description: Window size for an initial Gaussian smoothing pass to reduce noise.
* threshold:
* type: number
* description: The absolute value a peak/valley must exceed to be counted.
* default: 0
* minDistance:
* type: integer
* default: 3
* description: Minimum number of data points between any two vertices.
* responses:
* '200':
* description: An array of detected vertex objects, labeled as 'peak' or 'valley'.
* content:
* application/json:
* schema:
* $ref: '#/components/schemas/ApiResponse'
* '400':
* description: Invalid input data
*/
app.post('/api/signal/detect-vertices', (req, res) => {
try {
const { series, options } = req.body;
validateSeries(series);
const result = SignalProcessor.detectTrendVertices(series.values, options);
res.status(200).json({ success: true, data: result } as ApiResponse<any>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<any>);
}
});
/**
* @swagger
* /api/kernels/{name}:
* get:
* summary: Get a pre-defined convolution kernel
* description: Retrieves a standard 1D or 2D convolution kernel by its name.
* tags: [Kernels]
* parameters:
* - in: path
* name: name
* required: true
* schema:
* type: string
* enum: [sobel-x, sobel-y, laplacian, difference1d, average1d]
* description: The name of the kernel to retrieve.
* - in: query
* name: size
* schema:
* type: integer
* default: 3
* description: The size of the kernel (for kernels like 'average1d').
* responses:
* '200':
* description: The requested kernel as a 1D or 2D array.
* content:
* application/json:
* schema:
* $ref: '#/components/schemas/ApiResponse'
* '400':
* description: Unknown kernel name or invalid options.
*/
app.get('/api/kernels/:name', (req, res) => {
try {
const kernelName = req.params.name;
const size = req.query.size ? parseInt(req.query.size as string, 10) : 3;
let kernel: number[] | number[][];
switch (kernelName) {
case 'sobel-x':
kernel = ConvolutionKernels.sobel('x');
break;
case 'sobel-y':
kernel = ConvolutionKernels.sobel('y');
break;
case 'laplacian':
kernel = ConvolutionKernels.laplacian();
break;
case 'difference1d':
kernel = ConvolutionKernels.difference1D();
break;
case 'average1d':
kernel = ConvolutionKernels.average1D(size);
break;
default:
throw new Error(`Unknown kernel name: ${kernelName}`);
}
res.status(200).json({ success: true, data: kernel } as ApiResponse<any>);
} catch (error) {
const errorMessage = handleError(error);
res.status(400).json({ success: false, error: errorMessage } as ApiResponse<any>);
}
});
// ========================================
// SWAGGER COMPONENTS
// ========================================
@ -1573,6 +1224,7 @@ app.get('/api/kernels/:name', (req, res) => {
* type: string
* description: Optional labels for the values
* example: ["Jan", "Feb", "Mar", "Apr", "May"]
*
* DataMatrix:
* type: object
* required:
@ -1598,6 +1250,7 @@ app.get('/api/kernels/:name', (req, res) => {
* type: string
* description: Optional row names
* example: ["row1", "row2", "row3"]
*
* Condition:
* type: object
* required:
@ -1620,34 +1273,7 @@ app.get('/api/kernels/:name', (req, res) => {
* - type: string
* description: Value to compare against
* example: 10
* SmoothingOptions:
* type: object
* properties:
* method:
* type: string
* enum: [gaussian, moving_average]
* default: gaussian
* description: The smoothing method to use.
* windowSize:
* type: integer
* default: 5
* description: The size of the window for the filter. Must be an odd number for Gaussian.
* sigma:
* type: number
* default: 1.0
* description: The standard deviation for the Gaussian filter.
* EdgeDetectionOptions:
* type: object
* properties:
* method:
* type: string
* enum: [sobel, laplacian]
* default: sobel
* description: The edge detection algorithm to use.
* threshold:
* type: number
* default: 0.1
* description: The sensitivity threshold for detecting an edge. Values below this will be set to 0.
*
* ApiResponse:
* type: object
* properties:
@ -1667,9 +1293,8 @@ app.get('/api/kernels/:name', (req, res) => {
* get:
* summary: Export API documentation as JSON
* description: Returns the complete OpenAPI specification in JSON format
* tags: [Documentation]
* responses:
* '200':
* 200:
* description: OpenAPI specification in JSON format
* content:
* application/json:
@ -1688,9 +1313,8 @@ app.get('/api/docs/export/json', (req, res) => {
* get:
* summary: Export API documentation as YAML
* description: Returns the complete OpenAPI specification in YAML format
* tags: [Documentation]
* responses:
* '200':
* 200:
* description: OpenAPI specification in YAML format
* content:
* text/yaml:
@ -1712,9 +1336,8 @@ app.get('/api/docs/export/yaml', (req, res) => {
* get:
* summary: Export API documentation as HTML
* description: Returns a standalone HTML file with the complete API documentation
* tags: [Documentation]
* responses:
* '200':
* 200:
* description: Standalone HTML documentation
* content:
* text/html:
@ -1774,6 +1397,7 @@ app.get('/api/docs/export/html', (req, res) => {
res.send(htmlTemplate);
});
// ========================================
// ERROR HANDLING
// ========================================