@nova-ui/dashboards
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Nova Dashboards is a framework designed to provide feature developers with a common solution for presenting data coming from various sources within a single view, as well as a set of predefined widget visualizations that are 100% configuration-driven and
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JavaScript
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// © 2022 SolarWinds Worldwide, LLC. All rights reserved.
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to
// deal in the Software without restriction, including without limitation the
// rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
// sell copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
Object.defineProperty(exports, "__esModule", { value: true });
exports.transformNormalize = void 0;
const tslib_1 = require("tslib");
const cloneDeep_1 = tslib_1.__importDefault(require("lodash/cloneDeep"));
function transformNormalize(data, hasPercentile) {
const transformed = (0, cloneDeep_1.default)(data);
const dataValues = {
x: [],
y: [],
};
transformed.forEach((d) => {
dataValues.x.push(d.x.valueOf());
dataValues.y.push(d.y);
});
const normalizedData = normalize(dataValues.y);
normalizedData.forEach((value, index) => {
transformed[index].y = value * 100.0;
});
function normalize(values) {
// find max and min
const max = Math.max(...values);
const min = Math.min(...values);
// if max = min --> return every value = 0
// else --> return normalized data values
return max === min
? values.map((value) => 0)
: values.map((value) => (value - min) / (max - min));
}
return transformed;
}
exports.transformNormalize = transformNormalize;
//# sourceMappingURL=transformer-normalize.js.map