geobuckets/dist/src/classifiers/standardDeviation.js

Lightweight Javascript (TypeScript, really) library for classification. Dependency free, tested, and type safe.

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import { calcMean, calcStandardDeviation, validateDataArray, validateNumberClasses } from "../utils";
export var standardDeviationBuckets = function (data, numberClasses, matchDataBounds) {
    if (matchDataBounds === void 0) { matchDataBounds = true; }
    return __awaiter(void 0, void 0, void 0, function () {
        var bucketMin, bucketMax, standardDeviation, mean, buckets, meanBound, idx_1, idx_2, infBound, supBound, idx_3, idx;
        return __generator(this, function (_a) {
            switch (_a.label) {
                case 0:
                    validateDataArray(data.length);
                    validateNumberClasses(numberClasses, data.length);
                    bucketMin = Math.min.apply(Math, data);
                    bucketMax = Math.max.apply(Math, data);
                    return [4 /*yield*/, calcStandardDeviation(data)];
                case 1:
                    standardDeviation = _a.sent();
                    return [4 /*yield*/, calcMean(data)];
                case 2:
                    mean = _a.sent();
                    buckets = [];
                    switch (numberClasses % 2) {
                        case 0:
                            meanBound = numberClasses / 2;
                            buckets[meanBound] = mean;
                            for (idx_1 = meanBound - 1; idx_1 > 0; idx_1--) {
                                buckets[idx_1] = buckets[idx_1 + 1] - standardDeviation;
                            }
                            for (idx_2 = meanBound + 1; idx_2 < numberClasses; idx_2++) {
                                buckets[idx_2] = buckets[idx_2 - 1] + standardDeviation;
                            }
                            break;
                        case 1:
                            infBound = Math.floor(numberClasses / 2);
                            supBound = infBound + 1;
                            buckets[infBound] = mean - (standardDeviation / 2);
                            buckets[supBound] = mean + (standardDeviation / 2);
                            for (idx_3 = infBound - 1; idx_3 > 0; idx_3--) {
                                buckets[idx_3] = buckets[idx_3 + 1] - standardDeviation;
                            }
                            for (idx = supBound + 1; idx < numberClasses; idx++) {
                                buckets[idx] = buckets[idx - 1] + standardDeviation;
                            }
                            break;
                    }
                    buckets[0] = matchDataBounds ? buckets[1] - standardDeviation : bucketMin;
                    buckets[numberClasses] = matchDataBounds ? buckets[numberClasses - 1] + standardDeviation : bucketMax;
                    return [2 /*return*/, buckets];
            }
        });
    });
};