366 lines
9.6 KiB
Swift
366 lines
9.6 KiB
Swift
// Copyright © 2014-2019 the Surge contributors
|
|
//
|
|
// 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.
|
|
|
|
import XCTest
|
|
|
|
@testable import Surge
|
|
|
|
// swiftlint:disable nesting
|
|
|
|
class StatisticsTests: XCTestCase {
|
|
// MARK: - Sum
|
|
|
|
func test_sum_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.sum(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + $1 }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_sum_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.sum(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + $1 }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Sum of Absolute Values
|
|
|
|
func test_asum_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.asum(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + abs($1) }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_asum_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.asum(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + abs($1) }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Sum of Absolute Values
|
|
|
|
func test_sumsq_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.sumsq(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_sumsq_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.sumsq(lhs)
|
|
|
|
let expected: Scalar = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Maximum
|
|
|
|
func test_max_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.max(lhs)
|
|
|
|
let expected: Scalar = lhs.max()!
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_max_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.max(lhs)
|
|
|
|
let expected: Scalar = lhs.max()!
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Minimum
|
|
|
|
func test_min_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.min(lhs)
|
|
|
|
let expected: Scalar = lhs.min()!
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_min_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.min(lhs)
|
|
|
|
let expected: Scalar = lhs.min()!
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Mean
|
|
|
|
func test_mean_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.mean(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + $1 }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_mean_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.mean(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + $1 }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Mean of Magnitudes
|
|
|
|
func test_meamg_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.meamg(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + abs($1) }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_meamg_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.meamg(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + abs($1) }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Mean of Squares
|
|
|
|
func test_measq_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.measq(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_measq_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.measq(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
return sum / Scalar(lhs.count)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Root Mean of Squares
|
|
|
|
func test_rmsq_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.rmsq(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
let mean = sum / Scalar(lhs.count)
|
|
return sqrt(mean)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_rmsq_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.rmsq(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let sum = lhs.reduce(0) { $0 + ($1 * $1) }
|
|
let mean = sum / Scalar(lhs.count)
|
|
return sqrt(mean)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-8)
|
|
}
|
|
|
|
// MARK: - Variance
|
|
|
|
func test_variance_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.variance(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let mean = lhs.reduce(0) { $0 + $1 } / Scalar(lhs.count)
|
|
let diff = lhs.map { $0 - mean }
|
|
let diffSq = diff.map { $0 * $0 }
|
|
let sumDiffSq = diffSq.reduce(0.0) { $0 + $1 }
|
|
return sumDiffSq / Scalar(lhs.count - 1)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
func test_variance_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.variance(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let mean = lhs.reduce(0) { $0 + $1 } / Scalar(lhs.count)
|
|
let diff = lhs.map { $0 - mean }
|
|
let diffSq = diff.map { $0 * $0 }
|
|
let sumDiffSq = diffSq.reduce(0.0) { $0 + $1 }
|
|
return sumDiffSq / Scalar(lhs.count - 1)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-4)
|
|
}
|
|
|
|
// MARK: - Standard Deviation
|
|
|
|
func test_std_array_float() {
|
|
typealias Scalar = Float
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.std(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let mean = lhs.reduce(0) { $0 + $1 } / Scalar(lhs.count)
|
|
let diff = lhs.map { $0 - mean }
|
|
let diffSq = diff.map { $0 * $0 }
|
|
let sumDiffSq = diffSq.reduce(0.0) { $0 + $1 }
|
|
let variance = sumDiffSq / Scalar(lhs.count - 1)
|
|
return sqrt(variance)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-3)
|
|
}
|
|
|
|
func test_std_array_double() {
|
|
typealias Scalar = Double
|
|
|
|
let lhs: [Scalar] = .monotonicNormalized()
|
|
|
|
let actual: Scalar = Surge.std(lhs)
|
|
|
|
let expected: Scalar = {
|
|
let mean = lhs.reduce(0) { $0 + $1 } / Scalar(lhs.count)
|
|
let diff = lhs.map { $0 - mean }
|
|
let diffSq = diff.map { $0 * $0 }
|
|
let sumDiffSq = diffSq.reduce(0.0) { $0 + $1 }
|
|
let variance = sumDiffSq / Scalar(lhs.count - 1)
|
|
return sqrt(variance)
|
|
}()
|
|
|
|
XCTAssertEqual(actual, expected, accuracy: 1e-3)
|
|
}
|
|
}
|