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import { NamedStatistics } from '../../../types';
import Calculator from './Calculator';
const { PointsManager } = utilities;
export default class BasicStatsCalculator extends Calculator {
private static max = [-Infinity];
private static min = [Infinity];
private static sum = [0];
private static count = 0;
// private static sumSquares = [0];
// Values for Welford's algorithm
private static runMean = [0];
private static m2 = [0];
// Collect the points to be returned
private static pointsInShape = PointsManager.create3(1024);
public static statsInit(options: { noPointsCollection: boolean }) {
if (options.noPointsCollection) {
BasicStatsCalculator.pointsInShape = null;
}
}
/**
* This callback is used when we verify if the point is in the annotation drawn
* so we can get every point in the shape to calculate the statistics
*/
static statsCallback = ({ value: newValue, pointLPS = null }): void => {
Iif (
Array.isArray(newValue) &&
newValue.length > 1 &&
this.max.length === 1
) {
this.max.push(this.max[0], this.max[0]);
this.min.push(this.min[0], this.min[0]);
this.sum.push(this.sum[0], this.sum[0]);
this.runMean.push(0, 0);
// this.sumSquares.push(this.sumSquares[0], this.sumSquares[0]);
this.m2.push(this.m2[0], this.m2[0]);
}
this.pointsInShape?.push(pointLPS);
const newArray = Array.isArray(newValue) ? newValue : [newValue];
this.count += 1;
this.max.map((it, idx) => {
const value = newArray[idx];
const delta = value - this.runMean[idx];
this.sum[idx] += value;
this.runMean[idx] += delta / this.count;
const delta2 = value - this.runMean[idx];
this.m2[idx] += delta * delta2;
// this.sumSquares[idx] += value * value;
this.min[idx] = Math.min(this.min[idx], value);
this.max[idx] = Math.max(it, value);
});
};
/**
* Basic function that calculates statistics for a given array of points.
* @returns An object that contains :
* max : The maximum value of the array
* mean : mean of the array
* stdDev : standard deviation of the array
* array : An array of hte above values, in order.
*/
static getStatistics = (options?: { unit: string }): NamedStatistics => {
const mean = this.sum.map((sum) => sum / this.count);
const stdDev = this.m2.map((squaredDiffSum) =>
Math.sqrt(squaredDiffSum / this.count)
);
// const stdDevWithSumSquare = this.sumSquares.map((it, idx) =>
// Math.sqrt(this.sumSquares[idx] / this.count - mean[idx] ** 2)
// );
const unit = options?.unit || null;
const named: NamedStatistics = {
max: {
name: 'max',
label: 'Max Pixel',
value: singleArrayAsNumber(this.max),
unit,
},
min: {
name: 'min',
label: 'Min Pixel',
value: singleArrayAsNumber(this.min),
unit,
},
mean: {
name: 'mean',
label: 'Mean Pixel',
value: singleArrayAsNumber(mean),
unit,
},
stdDev: {
name: 'stdDev',
label: 'Standard Deviation',
value: singleArrayAsNumber(stdDev),
unit,
},
// stdDevWithSumSquare: {
// name: 'stdDevWithSumSquare',
// value: singleArrayAsNumber(stdDevWithSumSquare),
// unit,
// },
count: {
name: 'count',
label: 'Pixel Count',
value: this.count,
unit: null,
},
pointsInShape: this.pointsInShape,
array: [],
};
named.array.push(
named.max,
named.mean,
named.stdDev,
// Use the stdDev twice to preserve old ordering - this is updated to be
// correct value with Welford's algorithm now.
named.stdDev,
named.count
);
this.max = [-Infinity];
this.min = [Infinity];
this.sum = [0];
// this.sumSquares = [0];
this.m2 = [0];
this.runMean = [0];
this.count = 0;
this.pointsInShape = PointsManager.create3(1024);
return named;
};
}
function singleArrayAsNumber(val: number[]) {
return val.length === 1 ? val[0] : val;
}
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