本文整理汇总了TypeScript中@angular/facade.ListWrapper.slice方法的典型用法代码示例。如果您正苦于以下问题：TypeScript ListWrapper.slice方法的具体用法？TypeScript ListWrapper.slice怎么用？TypeScript ListWrapper.slice使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类@angular/facade.ListWrapper的用法示例。
在下文中一共展示了ListWrapper.slice方法的4个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的TypeScript代码示例。
示例1: it
it('should return the last sampleSize runs when it has at least the given size', () => {
createValidator(2);
var sample = [mv(0, 0, {'a': 1}), mv(1, 1, {'b': 2}), mv(2, 2, {'c': 3})];
expect(validator.validate(ListWrapper.slice(sample, 0, 2)))
.toEqual(ListWrapper.slice(sample, 0, 2));
expect(validator.validate(sample)).toEqual(ListWrapper.slice(sample, 1, 3));
});示例2: it
it('should return the last sampleSize runs when the regression slope is >0', () => {
createValidator({size: 2, metric: 'script'});
var sample = [mv(0, 0, {'script': 1}), mv(1, 1, {'script': 2}), mv(2, 2, {'script': 3})];
expect(validator.validate(ListWrapper.slice(sample, 0, 2)))
.toEqual(ListWrapper.slice(sample, 0, 2));
expect(validator.validate(sample)).toEqual(ListWrapper.slice(sample, 1, 3));
});示例3: validate
validate(completeSample: MeasureValues[]): MeasureValues[] {
if (completeSample.length >= this._sampleSize) {
return ListWrapper.slice(completeSample, completeSample.length - this._sampleSize,
completeSample.length);
} else {
return null;
}
}示例4: validate
validate(completeSample: MeasureValues[]): MeasureValues[] {
if (completeSample.length >= this._sampleSize) {
var latestSample = ListWrapper.slice(completeSample, completeSample.length - this._sampleSize,
completeSample.length);
var xValues = [];
var yValues = [];
for (var i = 0; i < latestSample.length; i++) {
// For now, we only use the array index as x value.
// TODO(tbosch): think about whether we should use time here instead
xValues.push(i);
yValues.push(latestSample[i].values[this._metric]);
}
var regressionSlope = Statistic.calculateRegressionSlope(
xValues, Statistic.calculateMean(xValues), yValues, Statistic.calculateMean(yValues));
return regressionSlope >= 0 ? latestSample : null;
} else {
return null;
}
}