Update to phpunit 8 and bump min php to 7.2 (#367)
* Update to phpunit 8 * Require at least PHP 7.2
This commit is contained in:
Marcin Michalski
Arkadiusz Kondas
parent
cefb4fc7a7
commit
db82afa263
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@ -1,4 +1,5 @@
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/vendor/
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.php_cs.cache
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/build
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/tests/Performance/Data/*.csv
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.php_cs.cache
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.phpunit.result.cache
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@ -4,14 +4,10 @@ matrix:
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fast_finish: true
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include:
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- os: linux
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php: '7.1'
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env: DISABLE_XDEBUG="true" STATIC_ANALYSIS="true"
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- os: linux
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php: '7.2'
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env: PHPUNIT_FLAGS="--coverage-clover build/logs/clover.xml"
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env: PHPUNIT_FLAGS="--coverage-clover build/logs/clover.xml" DISABLE_XDEBUG="true" STATIC_ANALYSIS="true"
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- os: linux
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php: '7.3'
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@ -1,6 +1,6 @@
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# PHP-ML - Machine Learning library for PHP
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[](https://php.net/)
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[](https://php.net/)
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[](https://packagist.org/packages/php-ai/php-ml)
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[](https://travis-ci.org/php-ai/php-ml)
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[](http://php-ml.readthedocs.org/)
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@ -15,7 +15,7 @@
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Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
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PHP-ML requires PHP >= 7.1.
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PHP-ML requires PHP >= 7.2.
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Simple example of classification:
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```php
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@ -20,14 +20,14 @@
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}
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],
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"require": {
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"php": "^7.1"
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"php": "^7.2"
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},
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"require-dev": {
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"phpbench/phpbench": "^0.14.0",
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"phpstan/phpstan-phpunit": "^0.11",
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"phpstan/phpstan-shim": "^0.11",
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"phpstan/phpstan-strict-rules": "^0.11",
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"phpunit/phpunit": "^7.0.0",
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"phpunit/phpunit": "^8.0",
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"symplify/coding-standard": "^5.1",
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"symplify/easy-coding-standard": "^5.1"
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},
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@ -4,7 +4,7 @@
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"Read more about it at https://getcomposer.org/doc/01-basic-usage.md#installing-dependencies",
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"This file is @generated automatically"
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],
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"content-hash": "dee9be6daf48915171d2778b17d941fa",
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"content-hash": "b329ea9fc7b690ad2d498e85a445d214",
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"packages": [],
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"packages-dev": [
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{
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@ -1881,40 +1881,40 @@
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},
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{
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"name": "phpunit/php-code-coverage",
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"version": "6.1.4",
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"version": "7.0.3",
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"source": {
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"type": "git",
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"url": "https://github.com/sebastianbergmann/php-code-coverage.git",
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"reference": "807e6013b00af69b6c5d9ceb4282d0393dbb9d8d"
|
||||
"reference": "0317a769a81845c390e19684d9ba25d7f6aa4707"
|
||||
},
|
||||
"dist": {
|
||||
"type": "zip",
|
||||
"url": "https://api.github.com/repos/sebastianbergmann/php-code-coverage/zipball/807e6013b00af69b6c5d9ceb4282d0393dbb9d8d",
|
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"reference": "807e6013b00af69b6c5d9ceb4282d0393dbb9d8d",
|
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"url": "https://api.github.com/repos/sebastianbergmann/php-code-coverage/zipball/0317a769a81845c390e19684d9ba25d7f6aa4707",
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"reference": "0317a769a81845c390e19684d9ba25d7f6aa4707",
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"shasum": ""
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},
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"require": {
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"ext-dom": "*",
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"ext-xmlwriter": "*",
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"php": "^7.1",
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"phpunit/php-file-iterator": "^2.0",
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"php": "^7.2",
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"phpunit/php-file-iterator": "^2.0.2",
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"phpunit/php-text-template": "^1.2.1",
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"phpunit/php-token-stream": "^3.0",
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"phpunit/php-token-stream": "^3.0.1",
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"sebastian/code-unit-reverse-lookup": "^1.0.1",
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"sebastian/environment": "^3.1 || ^4.0",
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"sebastian/environment": "^4.1",
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"sebastian/version": "^2.0.1",
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"theseer/tokenizer": "^1.1"
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},
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"require-dev": {
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"phpunit/phpunit": "^7.0"
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"phpunit/phpunit": "^8.0"
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},
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"suggest": {
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"ext-xdebug": "^2.6.0"
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"ext-xdebug": "^2.6.1"
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},
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"type": "library",
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"extra": {
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"branch-alias": {
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"dev-master": "6.1-dev"
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"dev-master": "7.0-dev"
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}
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},
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"autoload": {
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@ -1940,7 +1940,7 @@
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"testing",
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"xunit"
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],
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"time": "2018-10-31T16:06:48+00:00"
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"time": "2019-02-26T07:38:26+00:00"
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},
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{
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"name": "phpunit/php-file-iterator",
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@ -2133,16 +2133,16 @@
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},
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{
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"name": "phpunit/phpunit",
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"version": "7.5.7",
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"version": "8.0.5",
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"source": {
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"type": "git",
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"url": "https://github.com/sebastianbergmann/phpunit.git",
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"reference": "eb343b86753d26de07ecba7868fa983104361948"
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"reference": "19cbed2120839772c4a00e8b28456b0c77d1a7b4"
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},
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"dist": {
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"type": "zip",
|
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"url": "https://api.github.com/repos/sebastianbergmann/phpunit/zipball/eb343b86753d26de07ecba7868fa983104361948",
|
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"reference": "eb343b86753d26de07ecba7868fa983104361948",
|
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"url": "https://api.github.com/repos/sebastianbergmann/phpunit/zipball/19cbed2120839772c4a00e8b28456b0c77d1a7b4",
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"reference": "19cbed2120839772c4a00e8b28456b0c77d1a7b4",
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"shasum": ""
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},
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"require": {
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@ -2152,27 +2152,25 @@
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"ext-libxml": "*",
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"ext-mbstring": "*",
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"ext-xml": "*",
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"ext-xmlwriter": "*",
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"myclabs/deep-copy": "^1.7",
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"phar-io/manifest": "^1.0.2",
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"phar-io/version": "^2.0",
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"php": "^7.1",
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"php": "^7.2",
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"phpspec/prophecy": "^1.7",
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"phpunit/php-code-coverage": "^6.0.7",
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"phpunit/php-code-coverage": "^7.0",
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"phpunit/php-file-iterator": "^2.0.1",
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"phpunit/php-text-template": "^1.2.1",
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"phpunit/php-timer": "^2.1",
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"sebastian/comparator": "^3.0",
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"sebastian/diff": "^3.0",
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"sebastian/environment": "^4.0",
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"sebastian/environment": "^4.1",
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"sebastian/exporter": "^3.1",
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"sebastian/global-state": "^2.0",
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"sebastian/global-state": "^3.0",
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"sebastian/object-enumerator": "^3.0.3",
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"sebastian/resource-operations": "^2.0",
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"sebastian/version": "^2.0.1"
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},
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"conflict": {
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"phpunit/phpunit-mock-objects": "*"
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},
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"require-dev": {
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"ext-pdo": "*"
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},
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@ -2187,7 +2185,7 @@
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"type": "library",
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"extra": {
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"branch-alias": {
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"dev-master": "7.5-dev"
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"dev-master": "8.0-dev"
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}
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},
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"autoload": {
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@ -2213,7 +2211,7 @@
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"testing",
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"xunit"
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],
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"time": "2019-03-16T07:31:17+00:00"
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"time": "2019-03-16T07:33:46+00:00"
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},
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{
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"name": "psr/cache",
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@ -2692,23 +2690,26 @@
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},
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{
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"name": "sebastian/global-state",
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"version": "2.0.0",
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"version": "3.0.0",
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"source": {
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"type": "git",
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"url": "https://github.com/sebastianbergmann/global-state.git",
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"reference": "e8ba02eed7bbbb9e59e43dedd3dddeff4a56b0c4"
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"reference": "edf8a461cf1d4005f19fb0b6b8b95a9f7fa0adc4"
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||||
},
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"dist": {
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"type": "zip",
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||||
"url": "https://api.github.com/repos/sebastianbergmann/global-state/zipball/e8ba02eed7bbbb9e59e43dedd3dddeff4a56b0c4",
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||||
"reference": "e8ba02eed7bbbb9e59e43dedd3dddeff4a56b0c4",
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"url": "https://api.github.com/repos/sebastianbergmann/global-state/zipball/edf8a461cf1d4005f19fb0b6b8b95a9f7fa0adc4",
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"reference": "edf8a461cf1d4005f19fb0b6b8b95a9f7fa0adc4",
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"shasum": ""
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},
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"require": {
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"php": "^7.0"
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"php": "^7.2",
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"sebastian/object-reflector": "^1.1.1",
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"sebastian/recursion-context": "^3.0"
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},
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"require-dev": {
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"phpunit/phpunit": "^6.0"
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"ext-dom": "*",
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"phpunit/phpunit": "^8.0"
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},
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"suggest": {
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"ext-uopz": "*"
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@ -2716,7 +2717,7 @@
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"type": "library",
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"extra": {
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"branch-alias": {
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"dev-master": "2.0-dev"
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"dev-master": "3.0-dev"
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}
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},
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"autoload": {
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@ -2739,7 +2740,7 @@
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"keywords": [
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"global state"
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],
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"time": "2017-04-27T15:39:26+00:00"
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"time": "2019-02-01T05:30:01+00:00"
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},
|
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{
|
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"name": "sebastian/object-enumerator",
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@ -4749,7 +4750,7 @@
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"prefer-stable": false,
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"prefer-lowest": false,
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"platform": {
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"php": "^7.1"
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"php": "^7.2"
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},
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"platform-dev": []
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}
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@ -1,6 +1,6 @@
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# PHP-ML - Machine Learning library for PHP
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[](https://php.net/)
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[](https://php.net/)
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[](https://packagist.org/packages/php-ai/php-ml)
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[](https://travis-ci.org/php-ai/php-ml)
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[](http://php-ml.readthedocs.org/)
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@ -15,7 +15,7 @@
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Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
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PHP-ML requires PHP >= 7.1.
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PHP-ML requires PHP >= 7.2.
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Simple example of classification:
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```php
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@ -171,12 +171,12 @@ class LogisticRegressionTest extends TestCase
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$zero = $method->invoke($predictor, [0.1, 0.1], 0);
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$one = $method->invoke($predictor, [0.1, 0.1], 1);
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self::assertEquals(1, $zero + $one, '', 1e-6);
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self::assertEqualsWithDelta(1, $zero + $one, 1e-6);
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self::assertTrue($zero > $one);
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$zero = $method->invoke($predictor, [0.9, 0.9], 0);
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$one = $method->invoke($predictor, [0.9, 0.9], 1);
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self::assertEquals(1, $zero + $one, '', 1e-6);
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self::assertEqualsWithDelta(1, $zero + $one, 1e-6);
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self::assertTrue($zero < $one);
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}
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@ -213,9 +213,9 @@ class LogisticRegressionTest extends TestCase
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$two = $method->invoke($predictor, [3.0, 9.5], 2);
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$not_two = $method->invoke($predictor, [3.0, 9.5], 'not_2');
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self::assertEquals(1, $zero + $not_zero, '', 1e-6);
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self::assertEquals(1, $one + $not_one, '', 1e-6);
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self::assertEquals(1, $two + $not_two, '', 1e-6);
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self::assertEqualsWithDelta(1, $zero + $not_zero, 1e-6);
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self::assertEqualsWithDelta(1, $one + $not_one, 1e-6);
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self::assertEqualsWithDelta(1, $two + $not_two, 1e-6);
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self::assertTrue($zero < $two);
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self::assertTrue($one < $two);
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}
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@ -33,14 +33,14 @@ class KernelPCATest extends TestCase
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[-0.13128352866095], [-0.20865959471756], [-0.17531601535848], [0.4240660966961],
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[0.36351946685163], [-0.14334173054136], [0.22454914091011], [0.15035027480881], ];
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$kpca = new KernelPCA(KernelPCA::KERNEL_RBF, null, 1, 15);
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$kpca = new KernelPCA(KernelPCA::KERNEL_RBF, null, 1, 15.);
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$reducedData = $kpca->fit($data);
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// Due to the fact that the sign of values can be flipped
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// during the calculation of eigenValues, we have to compare
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// absolute value of the values
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array_map(function ($val1, $val2) use ($epsilon): void {
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self::assertEquals(abs($val1), abs($val2), '', $epsilon);
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self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
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}, $transformed, $reducedData);
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// Fitted KernelPCA object can also transform an arbitrary sample of the
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@ -48,7 +48,7 @@ class KernelPCATest extends TestCase
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$newData = [1.25, 2.25];
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$newTransformed = [0.18956227539216];
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$newTransformed2 = $kpca->transform($newData);
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self::assertEquals(abs($newTransformed[0]), abs($newTransformed2[0]), '', $epsilon);
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self::assertEqualsWithDelta(abs($newTransformed[0]), abs($newTransformed2[0]), $epsilon);
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}
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public function testKernelPCAThrowWhenKernelInvalid(): void
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@ -51,7 +51,7 @@ class LDATest extends TestCase
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// absolute value of the values
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$row1 = array_map('abs', $row1);
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$row2 = array_map('abs', $row2);
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self::assertEquals($row1, $row2, '', $epsilon);
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self::assertEqualsWithDelta($row1, $row2, $epsilon);
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};
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array_map($check, $control, $transformed2);
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@ -42,7 +42,7 @@ class PCATest extends TestCase
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// during the calculation of eigenValues, we have to compare
|
||||
// absolute value of the values
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||||
array_map(function ($val1, $val2) use ($epsilon): void {
|
||||
self::assertEquals(abs($val1), abs($val2), '', $epsilon);
|
||||
self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
|
||||
}, $transformed, $reducedData);
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||||
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||||
// Test fitted PCA object to transform an arbitrary sample of the
|
||||
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@ -52,7 +52,7 @@ class PCATest extends TestCase
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$newRow2 = $pca->transform($row);
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||||
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||||
array_map(function ($val1, $val2) use ($epsilon): void {
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self::assertEquals(abs($val1), abs($val2), '', $epsilon);
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||||
self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
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||||
}, $newRow, $newRow2);
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||||
}
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||||
}
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||||
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@ -54,6 +54,6 @@ class TfIdfTransformerTest extends TestCase
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$transformer = new TfIdfTransformer($samples);
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$transformer->transform($samples);
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self::assertEquals($tfIdfSamples, $samples, '', 0.001);
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||||
self::assertEqualsWithDelta($tfIdfSamples, $samples, 0.001);
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}
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||||
}
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@ -15,10 +15,9 @@ final class ANOVAFValueTest extends TestCase
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$dataset = new IrisDataset();
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||||
$function = new ANOVAFValue();
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||||
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||||
self::assertEquals(
|
||||
self::assertEqualsWithDelta(
|
||||
[119.2645, 47.3644, 1179.0343, 959.3244],
|
||||
$function->score($dataset->getSamples(), $dataset->getTargets()),
|
||||
'',
|
||||
0.0001
|
||||
);
|
||||
}
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||||
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|
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|||
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@ -15,7 +15,7 @@ final class UnivariateLinearRegressionTest extends TestCase
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$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
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||||
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||||
$function = new UnivariateLinearRegression();
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self::assertEquals([6.97286, 6.48558], $function->score($samples, $targets), '', 0.0001);
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||||
self::assertEqualsWithDelta([6.97286, 6.48558], $function->score($samples, $targets), 0.0001);
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||||
}
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||||
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||||
public function testRegressionScoreWithoutCenter(): void
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||||
|
|
@ -24,6 +24,6 @@ final class UnivariateLinearRegressionTest extends TestCase
|
|||
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
|
||||
|
||||
$function = new UnivariateLinearRegression(false);
|
||||
self::assertEquals([1.74450, 18.08347], $function->score($samples, $targets), '', 0.0001);
|
||||
self::assertEqualsWithDelta([1.74450, 18.08347], $function->score($samples, $targets), 0.0001);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -33,7 +33,7 @@ class ConjugateGradientTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
|
||||
}
|
||||
|
||||
public function testRunOptimizationWithCustomInitialTheta(): void
|
||||
|
|
@ -61,7 +61,7 @@ class ConjugateGradientTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1.087708, 2.212034], $theta, '', 0.000001);
|
||||
self::assertEqualsWithDelta([-1.087708, 2.212034], $theta, 0.000001);
|
||||
}
|
||||
|
||||
public function testRunOptimization2Dim(): void
|
||||
|
|
@ -89,7 +89,7 @@ class ConjugateGradientTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2, -3], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
|
||||
}
|
||||
|
||||
public function testThrowExceptionOnInvalidTheta(): void
|
||||
|
|
|
|||
|
|
@ -32,7 +32,7 @@ class GDTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
|
||||
}
|
||||
|
||||
public function testRunOptimization2Dim(): void
|
||||
|
|
@ -60,6 +60,6 @@ class GDTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2, -3], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -32,7 +32,7 @@ class StochasticGDTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
|
||||
}
|
||||
|
||||
public function testRunOptimization2Dim(): void
|
||||
|
|
@ -60,6 +60,6 @@ class StochasticGDTest extends TestCase
|
|||
|
||||
$theta = $optimizer->runOptimization($samples, $targets, $callback);
|
||||
|
||||
self::assertEquals([-1, 2, -3], $theta, '', 0.1);
|
||||
self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -47,7 +47,7 @@ class MinkowskiTest extends TestCase
|
|||
$expectedDistance = 2.080;
|
||||
$actualDistance = $this->distanceMetric->distance($a, $b);
|
||||
|
||||
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001);
|
||||
self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
|
||||
}
|
||||
|
||||
public function testCalculateDistanceForThreeDimensions(): void
|
||||
|
|
@ -58,7 +58,7 @@ class MinkowskiTest extends TestCase
|
|||
$expectedDistance = 5.819;
|
||||
$actualDistance = $this->distanceMetric->distance($a, $b);
|
||||
|
||||
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001);
|
||||
self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
|
||||
}
|
||||
|
||||
public function testCalculateDistanceForThreeDimensionsWithDifferentLambda(): void
|
||||
|
|
@ -71,6 +71,6 @@ class MinkowskiTest extends TestCase
|
|||
$expectedDistance = 5.300;
|
||||
$actualDistance = $distanceMetric->distance($a, $b);
|
||||
|
||||
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001);
|
||||
self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -15,13 +15,13 @@ class RBFTest extends TestCase
|
|||
$rbf = new RBF($gamma = 0.001);
|
||||
|
||||
self::assertEquals(1, $rbf->compute([1, 2], [1, 2]));
|
||||
self::assertEquals(0.97336, $rbf->compute([1, 2, 3], [4, 5, 6]), '', $delta = 0.0001);
|
||||
self::assertEquals(0.00011, $rbf->compute([4, 5], [1, 100]), '', $delta = 0.0001);
|
||||
self::assertEqualsWithDelta(0.97336, $rbf->compute([1, 2, 3], [4, 5, 6]), $delta = 0.0001);
|
||||
self::assertEqualsWithDelta(0.00011, $rbf->compute([4, 5], [1, 100]), $delta = 0.0001);
|
||||
|
||||
$rbf = new RBF($gamma = 0.2);
|
||||
|
||||
self::assertEquals(1, $rbf->compute([1, 2], [1, 2]));
|
||||
self::assertEquals(0.00451, $rbf->compute([1, 2, 3], [4, 5, 6]), '', $delta = 0.0001);
|
||||
self::assertEqualsWithDelta(0.00451, $rbf->compute([1, 2, 3], [4, 5, 6]), $delta = 0.0001);
|
||||
self::assertEquals(0, $rbf->compute([4, 5], [1, 100]));
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -21,11 +21,11 @@ class EigenvalueDecompositionTest extends TestCase
|
|||
|
||||
$decomp = new EigenvalueDecomposition($matrix);
|
||||
|
||||
self::assertEquals([0.0490833989, 1.28402771], $decomp->getRealEigenvalues(), '', 0.001);
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([0.0490833989, 1.28402771], $decomp->getRealEigenvalues(), 0.001);
|
||||
self::assertEqualsWithDelta([
|
||||
[-0.735178656, 0.677873399],
|
||||
[-0.677873399, -0.735178656],
|
||||
], $decomp->getEigenvectors(), '', 0.001);
|
||||
], $decomp->getEigenvectors(), 0.001);
|
||||
}
|
||||
|
||||
public function testMatrixWithAllZeroRow(): void
|
||||
|
|
@ -39,12 +39,12 @@ class EigenvalueDecompositionTest extends TestCase
|
|||
|
||||
$decomp = new EigenvalueDecomposition($matrix);
|
||||
|
||||
self::assertEquals([0.0, 6.0, 10.0], $decomp->getRealEigenvalues(), '', 0.0001);
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([0.0, 6.0, 10.0], $decomp->getRealEigenvalues(), 0.0001);
|
||||
self::assertEqualsWithDelta([
|
||||
[0, 0, 1],
|
||||
[0, 1, 0],
|
||||
[1, 0, 0],
|
||||
], $decomp->getEigenvectors(), '', 0.0001);
|
||||
], $decomp->getEigenvectors(), 0.0001);
|
||||
}
|
||||
|
||||
public function testMatrixThatCauseErrorWithStrictComparision(): void
|
||||
|
|
@ -58,12 +58,12 @@ class EigenvalueDecompositionTest extends TestCase
|
|||
|
||||
$decomp = new EigenvalueDecomposition($matrix);
|
||||
|
||||
self::assertEquals([-5.2620873481, 1.0, 10.2620873481], $decomp->getRealEigenvalues(), '', 0.000001);
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([-5.2620873481, 1.0, 10.2620873481], $decomp->getRealEigenvalues(), 0.000001);
|
||||
self::assertEqualsWithDelta([
|
||||
[-0.3042688, -0.709960552, 0.63511928],
|
||||
[-0.9191450, 0.393919298, 0.0],
|
||||
[0.25018574, 0.5837667, 0.7724140],
|
||||
], $decomp->getEigenvectors(), '', 0.0001);
|
||||
], $decomp->getEigenvectors(), 0.0001);
|
||||
}
|
||||
|
||||
public function testRandomSymmetricMatrixEigenPairs(): void
|
||||
|
|
@ -98,7 +98,7 @@ class EigenvalueDecompositionTest extends TestCase
|
|||
$leftSide = $m1->multiply($m2)->toArray();
|
||||
$rightSide = $m2->multiplyByScalar($lambda)->toArray();
|
||||
|
||||
self::assertEquals($leftSide, $rightSide, '', $epsilon);
|
||||
self::assertEqualsWithDelta($leftSide, $rightSide, $epsilon);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -60,7 +60,7 @@ class MatrixTest extends TestCase
|
|||
[1 / 4, 4, 1, 0, 2, 3 / 7],
|
||||
[1, 8, 7, 5, 4, 4 / 5],
|
||||
]);
|
||||
self::assertEquals(1116.5035, $matrix->getDeterminant(), '', $delta = 0.0001);
|
||||
self::assertEqualsWithDelta(1116.5035, $matrix->getDeterminant(), $delta = 0.0001);
|
||||
}
|
||||
|
||||
public function testMatrixTranspose(): void
|
||||
|
|
@ -157,7 +157,7 @@ class MatrixTest extends TestCase
|
|||
[-1 / 2, 1 / 2, -1 / 2],
|
||||
];
|
||||
|
||||
self::assertEquals($inverseMatrix, $matrix->inverse()->toArray(), '', $delta = 0.0001);
|
||||
self::assertEqualsWithDelta($inverseMatrix, $matrix->inverse()->toArray(), $delta = 0.0001);
|
||||
}
|
||||
|
||||
public function testCrossOutMatrix(): void
|
||||
|
|
@ -256,7 +256,7 @@ class MatrixTest extends TestCase
|
|||
*/
|
||||
public function testFrobeniusNorm(array $matrix, float $norm): void
|
||||
{
|
||||
self::assertEquals($norm, (new Matrix($matrix))->frobeniusNorm(), '', 0.0001);
|
||||
self::assertEqualsWithDelta($norm, (new Matrix($matrix))->frobeniusNorm(), 0.0001);
|
||||
}
|
||||
|
||||
public function dataProviderForFrobeniusNorm(): array
|
||||
|
|
|
|||
|
|
@ -19,7 +19,7 @@ final class ANOVATest extends TestCase
|
|||
|
||||
$f = [1.47058824, 4.0, 3.0];
|
||||
|
||||
self::assertEquals($f, ANOVA::oneWayF($samples), '', 0.00000001);
|
||||
self::assertEqualsWithDelta($f, ANOVA::oneWayF($samples), 0.00000001);
|
||||
}
|
||||
|
||||
public function testOneWayFWithDifferingSizes(): void
|
||||
|
|
@ -29,7 +29,7 @@ final class ANOVATest extends TestCase
|
|||
[[1, 3, 3], [1, 3, 4]],
|
||||
];
|
||||
|
||||
self::assertEquals([0.6, 2.4, 1.24615385], ANOVA::oneWayF($samples), '', 0.00000001);
|
||||
self::assertEqualsWithDelta([0.6, 2.4, 1.24615385], ANOVA::oneWayF($samples), 0.00000001);
|
||||
}
|
||||
|
||||
public function testThrowExceptionOnTooSmallSamples(): void
|
||||
|
|
|
|||
|
|
@ -16,18 +16,18 @@ class CorrelationTest extends TestCase
|
|||
$delta = 0.001;
|
||||
$x = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260];
|
||||
$y = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
|
||||
self::assertEquals(-0.641, Correlation::pearson($x, $y), '', $delta);
|
||||
self::assertEqualsWithDelta(-0.641, Correlation::pearson($x, $y), $delta);
|
||||
|
||||
//http://www.statisticshowto.com/how-to-compute-pearsons-correlation-coefficients/
|
||||
$delta = 0.001;
|
||||
$x = [43, 21, 25, 42, 57, 59];
|
||||
$y = [99, 65, 79, 75, 87, 82];
|
||||
self::assertEquals(0.549, Correlation::pearson($x, $y), '', $delta);
|
||||
self::assertEqualsWithDelta(0.549, Correlation::pearson($x, $y), $delta);
|
||||
|
||||
$delta = 0.001;
|
||||
$x = [60, 61, 62, 63, 65];
|
||||
$y = [3.1, 3.6, 3.8, 4, 4.1];
|
||||
self::assertEquals(0.911, Correlation::pearson($x, $y), '', $delta);
|
||||
self::assertEqualsWithDelta(0.911, Correlation::pearson($x, $y), $delta);
|
||||
}
|
||||
|
||||
public function testThrowExceptionOnInvalidArgumentsForPearsonCorrelation(): void
|
||||
|
|
|
|||
|
|
@ -38,18 +38,18 @@ class CovarianceTest extends TestCase
|
|||
|
||||
// Calculate only one covariance value: Cov(x, y)
|
||||
$cov1 = Covariance::fromDataset($matrix, 0, 0);
|
||||
self::assertEquals($cov1, $knownCovariance[0][0], '', $epsilon);
|
||||
self::assertEqualsWithDelta($cov1, $knownCovariance[0][0], $epsilon);
|
||||
$cov1 = Covariance::fromXYArrays($x, $x);
|
||||
self::assertEquals($cov1, $knownCovariance[0][0], '', $epsilon);
|
||||
self::assertEqualsWithDelta($cov1, $knownCovariance[0][0], $epsilon);
|
||||
|
||||
$cov2 = Covariance::fromDataset($matrix, 0, 1);
|
||||
self::assertEquals($cov2, $knownCovariance[0][1], '', $epsilon);
|
||||
self::assertEqualsWithDelta($cov2, $knownCovariance[0][1], $epsilon);
|
||||
$cov2 = Covariance::fromXYArrays($x, $y);
|
||||
self::assertEquals($cov2, $knownCovariance[0][1], '', $epsilon);
|
||||
self::assertEqualsWithDelta($cov2, $knownCovariance[0][1], $epsilon);
|
||||
|
||||
// Second: calculation cov matrix with automatic means for each column
|
||||
$covariance = Covariance::covarianceMatrix($matrix);
|
||||
self::assertEquals($knownCovariance, $covariance, '', $epsilon);
|
||||
self::assertEqualsWithDelta($knownCovariance, $covariance, $epsilon);
|
||||
|
||||
// Thirdly, CovMatrix: Means are precalculated and given to the method
|
||||
$x = array_column($matrix, 0);
|
||||
|
|
@ -58,7 +58,7 @@ class CovarianceTest extends TestCase
|
|||
$meanY = Mean::arithmetic($y);
|
||||
|
||||
$covariance = Covariance::covarianceMatrix($matrix, [$meanX, $meanY]);
|
||||
self::assertEquals($knownCovariance, $covariance, '', $epsilon);
|
||||
self::assertEqualsWithDelta($knownCovariance, $covariance, $epsilon);
|
||||
}
|
||||
|
||||
public function testThrowExceptionOnEmptyX(): void
|
||||
|
|
|
|||
|
|
@ -20,9 +20,9 @@ class GaussianTest extends TestCase
|
|||
$x = [0, 0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0];
|
||||
$pdf = [0.3989, 0.3969, 0.3520, 0.2419, 0.1295, 0.0539, 0.0175, 0.0044];
|
||||
foreach ($x as $i => $v) {
|
||||
self::assertEquals($pdf[$i], $g->pdf($v), '', $delta);
|
||||
self::assertEqualsWithDelta($pdf[$i], $g->pdf($v), $delta);
|
||||
|
||||
self::assertEquals($pdf[$i], Gaussian::distributionPdf($mean, $std, $v), '', $delta);
|
||||
self::assertEqualsWithDelta($pdf[$i], Gaussian::distributionPdf($mean, $std, $v), $delta);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -19,9 +19,9 @@ class MeanTest extends TestCase
|
|||
public function testArithmeticMean(): void
|
||||
{
|
||||
$delta = 0.01;
|
||||
self::assertEquals(3.5, Mean::arithmetic([2, 5]), '', $delta);
|
||||
self::assertEquals(41.16, Mean::arithmetic([43, 21, 25, 42, 57, 59]), '', $delta);
|
||||
self::assertEquals(1.7, Mean::arithmetic([0.5, 0.5, 1.5, 2.5, 3.5]), '', $delta);
|
||||
self::assertEqualsWithDelta(3.5, Mean::arithmetic([2, 5]), $delta);
|
||||
self::assertEqualsWithDelta(41.16, Mean::arithmetic([43, 21, 25, 42, 57, 59]), $delta);
|
||||
self::assertEqualsWithDelta(1.7, Mean::arithmetic([0.5, 0.5, 1.5, 2.5, 3.5]), $delta);
|
||||
}
|
||||
|
||||
public function testMedianThrowExceptionOnEmptyArray(): void
|
||||
|
|
|
|||
|
|
@ -15,15 +15,15 @@ class StandardDeviationTest extends TestCase
|
|||
//https://pl.wikipedia.org/wiki/Odchylenie_standardowe
|
||||
$delta = 0.001;
|
||||
$population = [5, 6, 8, 9];
|
||||
self::assertEquals(1.825, StandardDeviation::population($population), '', $delta);
|
||||
self::assertEqualsWithDelta(1.825, StandardDeviation::population($population), $delta);
|
||||
|
||||
//http://www.stat.wmich.edu/s216/book/node126.html
|
||||
$delta = 0.5;
|
||||
$population = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
|
||||
self::assertEquals(4079, StandardDeviation::population($population), '', $delta);
|
||||
self::assertEqualsWithDelta(4079, StandardDeviation::population($population), $delta);
|
||||
|
||||
$population = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260];
|
||||
self::assertEquals(50989, StandardDeviation::population($population), '', $delta);
|
||||
self::assertEqualsWithDelta(50989, StandardDeviation::population($population), $delta);
|
||||
}
|
||||
|
||||
public function testThrowExceptionOnEmptyArrayIfNotSample(): void
|
||||
|
|
@ -43,7 +43,7 @@ class StandardDeviationTest extends TestCase
|
|||
*/
|
||||
public function testSumOfSquares(array $numbers, float $sum): void
|
||||
{
|
||||
self::assertEquals($sum, StandardDeviation::sumOfSquares($numbers), '', 0.0001);
|
||||
self::assertEqualsWithDelta($sum, StandardDeviation::sumOfSquares($numbers), 0.0001);
|
||||
}
|
||||
|
||||
public function dataProviderForSumOfSquaresDeviations(): array
|
||||
|
|
|
|||
|
|
@ -14,7 +14,7 @@ final class VarianceTest extends TestCase
|
|||
*/
|
||||
public function testVarianceFromInt(array $numbers, float $variance): void
|
||||
{
|
||||
self::assertEquals($variance, Variance::population($numbers), '', 0.001);
|
||||
self::assertEqualsWithDelta($variance, Variance::population($numbers), 0.001);
|
||||
}
|
||||
|
||||
public function dataProviderForPopulationVariance(): array
|
||||
|
|
|
|||
|
|
@ -51,6 +51,6 @@ class AccuracyTest extends TestCase
|
|||
|
||||
$expected = PHP_VERSION_ID >= 70100 ? 1 : 0.959;
|
||||
|
||||
self::assertEquals($expected, $accuracy, '', 0.01);
|
||||
self::assertEqualsWithDelta($expected, $accuracy, 0.01);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -45,11 +45,11 @@ class ClassificationReportTest extends TestCase
|
|||
'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45
|
||||
];
|
||||
|
||||
self::assertEquals($precision, $report->getPrecision(), '', 0.01);
|
||||
self::assertEquals($recall, $report->getRecall(), '', 0.01);
|
||||
self::assertEquals($f1score, $report->getF1score(), '', 0.01);
|
||||
self::assertEquals($support, $report->getSupport(), '', 0.01);
|
||||
self::assertEquals($average, $report->getAverage(), '', 0.01);
|
||||
self::assertEqualsWithDelta($precision, $report->getPrecision(), 0.01);
|
||||
self::assertEqualsWithDelta($recall, $report->getRecall(), 0.01);
|
||||
self::assertEqualsWithDelta($f1score, $report->getF1score(), 0.01);
|
||||
self::assertEqualsWithDelta($support, $report->getSupport(), 0.01);
|
||||
self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testClassificationReportGenerateWithNumericLabels(): void
|
||||
|
|
@ -85,11 +85,11 @@ class ClassificationReportTest extends TestCase
|
|||
'f1score' => 0.49,
|
||||
];
|
||||
|
||||
self::assertEquals($precision, $report->getPrecision(), '', 0.01);
|
||||
self::assertEquals($recall, $report->getRecall(), '', 0.01);
|
||||
self::assertEquals($f1score, $report->getF1score(), '', 0.01);
|
||||
self::assertEquals($support, $report->getSupport(), '', 0.01);
|
||||
self::assertEquals($average, $report->getAverage(), '', 0.01);
|
||||
self::assertEqualsWithDelta($precision, $report->getPrecision(), 0.01);
|
||||
self::assertEqualsWithDelta($recall, $report->getRecall(), 0.01);
|
||||
self::assertEqualsWithDelta($f1score, $report->getF1score(), 0.01);
|
||||
self::assertEqualsWithDelta($support, $report->getSupport(), 0.01);
|
||||
self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testClassificationReportAverageOutOfRange(): void
|
||||
|
|
@ -114,7 +114,7 @@ class ClassificationReportTest extends TestCase
|
|||
'f1score' => 0.6, // Harmonic mean of precision and recall
|
||||
];
|
||||
|
||||
self::assertEquals($average, $report->getAverage(), '', 0.01);
|
||||
self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testClassificationReportMacroAverage(): void
|
||||
|
|
@ -130,7 +130,7 @@ class ClassificationReportTest extends TestCase
|
|||
'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45
|
||||
];
|
||||
|
||||
self::assertEquals($average, $report->getAverage(), '', 0.01);
|
||||
self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testClassificationReportWeightedAverage(): void
|
||||
|
|
@ -146,7 +146,7 @@ class ClassificationReportTest extends TestCase
|
|||
'f1score' => 0.61, // (2/3 * 1 + 0 * 1 + 4/5 * 3) / 5 = 46/75
|
||||
];
|
||||
|
||||
self::assertEquals($average, $report->getAverage(), '', 0.01);
|
||||
self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testPreventDivideByZeroWhenTruePositiveAndFalsePositiveSumEqualsZero(): void
|
||||
|
|
@ -156,10 +156,10 @@ class ClassificationReportTest extends TestCase
|
|||
|
||||
$report = new ClassificationReport($labels, $predicted);
|
||||
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([
|
||||
1 => 0.0,
|
||||
2 => 0.5,
|
||||
], $report->getPrecision(), '', 0.01);
|
||||
], $report->getPrecision(), 0.01);
|
||||
}
|
||||
|
||||
public function testPreventDivideByZeroWhenTruePositiveAndFalseNegativeSumEqualsZero(): void
|
||||
|
|
@ -169,11 +169,11 @@ class ClassificationReportTest extends TestCase
|
|||
|
||||
$report = new ClassificationReport($labels, $predicted);
|
||||
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([
|
||||
1 => 0.0,
|
||||
2 => 1,
|
||||
3 => 0,
|
||||
], $report->getPrecision(), '', 0.01);
|
||||
], $report->getPrecision(), 0.01);
|
||||
}
|
||||
|
||||
public function testPreventDividedByZeroWhenPredictedLabelsAllNotMatch(): void
|
||||
|
|
@ -183,11 +183,11 @@ class ClassificationReportTest extends TestCase
|
|||
|
||||
$report = new ClassificationReport($labels, $predicted);
|
||||
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([
|
||||
'precision' => 0,
|
||||
'recall' => 0,
|
||||
'f1score' => 0,
|
||||
], $report->getAverage(), '', 0.01);
|
||||
], $report->getAverage(), 0.01);
|
||||
}
|
||||
|
||||
public function testPreventDividedByZeroWhenLabelsAreEmpty(): void
|
||||
|
|
@ -197,10 +197,10 @@ class ClassificationReportTest extends TestCase
|
|||
|
||||
$report = new ClassificationReport($labels, $predicted);
|
||||
|
||||
self::assertEquals([
|
||||
self::assertEqualsWithDelta([
|
||||
'precision' => 0,
|
||||
'recall' => 0,
|
||||
'f1score' => 0,
|
||||
], $report->getAverage(), '', 0.01);
|
||||
], $report->getAverage(), 0.01);
|
||||
}
|
||||
}
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ class GaussianTest extends TestCase
|
|||
{
|
||||
$gaussian = new Gaussian();
|
||||
|
||||
self::assertEquals($expected, $gaussian->compute($value), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $gaussian->compute($value), 0.001);
|
||||
}
|
||||
|
||||
public function gaussianProvider(): array
|
||||
|
|
@ -41,7 +41,7 @@ class GaussianTest extends TestCase
|
|||
{
|
||||
$gaussian = new Gaussian();
|
||||
$activatedValue = $gaussian->compute($value);
|
||||
self::assertEquals($expected, $gaussian->differentiate($value, $activatedValue), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $gaussian->differentiate($value, $activatedValue), 0.001);
|
||||
}
|
||||
|
||||
public function gaussianDerivativeProvider(): array
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ class HyperboliTangentTest extends TestCase
|
|||
{
|
||||
$tanh = new HyperbolicTangent($beta);
|
||||
|
||||
self::assertEquals($expected, $tanh->compute($value), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $tanh->compute($value), 0.001);
|
||||
}
|
||||
|
||||
public function tanhProvider(): array
|
||||
|
|
@ -42,7 +42,7 @@ class HyperboliTangentTest extends TestCase
|
|||
{
|
||||
$tanh = new HyperbolicTangent($beta);
|
||||
$activatedValue = $tanh->compute($value);
|
||||
self::assertEquals($expected, $tanh->differentiate($value, $activatedValue), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $tanh->differentiate($value, $activatedValue), 0.001);
|
||||
}
|
||||
|
||||
public function tanhDerivativeProvider(): array
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ class PReLUTest extends TestCase
|
|||
{
|
||||
$prelu = new PReLU($beta);
|
||||
|
||||
self::assertEquals($expected, $prelu->compute($value), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $prelu->compute($value), 0.001);
|
||||
}
|
||||
|
||||
public function preluProvider(): array
|
||||
|
|
|
|||
|
|
@ -18,7 +18,7 @@ class SigmoidTest extends TestCase
|
|||
{
|
||||
$sigmoid = new Sigmoid($beta);
|
||||
|
||||
self::assertEquals($expected, $sigmoid->compute($value), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $sigmoid->compute($value), 0.001);
|
||||
}
|
||||
|
||||
public function sigmoidProvider(): array
|
||||
|
|
@ -42,7 +42,7 @@ class SigmoidTest extends TestCase
|
|||
{
|
||||
$sigmoid = new Sigmoid($beta);
|
||||
$activatedValue = $sigmoid->compute($value);
|
||||
self::assertEquals($expected, $sigmoid->differentiate($value, $activatedValue), '', 0.001);
|
||||
self::assertEqualsWithDelta($expected, $sigmoid->differentiate($value, $activatedValue), 0.001);
|
||||
}
|
||||
|
||||
public function sigmoidDerivativeProvider(): array
|
||||
|
|
|
|||
|
|
@ -8,8 +8,8 @@ use Phpml\NeuralNetwork\ActivationFunction;
|
|||
use Phpml\NeuralNetwork\Layer;
|
||||
use Phpml\NeuralNetwork\Network\LayeredNetwork;
|
||||
use Phpml\NeuralNetwork\Node\Input;
|
||||
use PHPUnit\Framework\MockObject\MockObject;
|
||||
use PHPUnit\Framework\TestCase;
|
||||
use PHPUnit_Framework_MockObject_MockObject;
|
||||
|
||||
class LayeredNetworkTest extends TestCase
|
||||
{
|
||||
|
|
@ -56,7 +56,7 @@ class LayeredNetworkTest extends TestCase
|
|||
}
|
||||
|
||||
/**
|
||||
* @return LayeredNetwork|PHPUnit_Framework_MockObject_MockObject
|
||||
* @return LayeredNetwork|MockObject
|
||||
*/
|
||||
private function getLayeredNetworkMock()
|
||||
{
|
||||
|
|
@ -64,7 +64,7 @@ class LayeredNetworkTest extends TestCase
|
|||
}
|
||||
|
||||
/**
|
||||
* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject
|
||||
* @return ActivationFunction|MockObject
|
||||
*/
|
||||
private function getActivationFunctionMock()
|
||||
{
|
||||
|
|
|
|||
|
|
@ -9,8 +9,8 @@ use Phpml\NeuralNetwork\ActivationFunction;
|
|||
use Phpml\NeuralNetwork\Layer;
|
||||
use Phpml\NeuralNetwork\Network\MultilayerPerceptron;
|
||||
use Phpml\NeuralNetwork\Node\Neuron;
|
||||
use PHPUnit\Framework\MockObject\MockObject;
|
||||
use PHPUnit\Framework\TestCase;
|
||||
use PHPUnit_Framework_MockObject_MockObject;
|
||||
|
||||
class MultilayerPerceptronTest extends TestCase
|
||||
{
|
||||
|
|
@ -106,7 +106,7 @@ class MultilayerPerceptronTest extends TestCase
|
|||
}
|
||||
|
||||
/**
|
||||
* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject
|
||||
* @return ActivationFunction|MockObject
|
||||
*/
|
||||
private function getActivationFunctionMock()
|
||||
{
|
||||
|
|
|
|||
|
|
@ -6,8 +6,8 @@ namespace Phpml\Tests\NeuralNetwork\Node\Neuron;
|
|||
|
||||
use Phpml\NeuralNetwork\Node\Neuron;
|
||||
use Phpml\NeuralNetwork\Node\Neuron\Synapse;
|
||||
use PHPUnit\Framework\MockObject\MockObject;
|
||||
use PHPUnit\Framework\TestCase;
|
||||
use PHPUnit_Framework_MockObject_MockObject;
|
||||
|
||||
class SynapseTest extends TestCase
|
||||
{
|
||||
|
|
@ -43,7 +43,7 @@ class SynapseTest extends TestCase
|
|||
/**
|
||||
* @param int|float $output
|
||||
*
|
||||
* @return Neuron|PHPUnit_Framework_MockObject_MockObject
|
||||
* @return Neuron|MockObject
|
||||
*/
|
||||
private function getNodeMock($output = 1)
|
||||
{
|
||||
|
|
|
|||
|
|
@ -7,8 +7,8 @@ namespace Phpml\Tests\NeuralNetwork\Node;
|
|||
use Phpml\NeuralNetwork\ActivationFunction\BinaryStep;
|
||||
use Phpml\NeuralNetwork\Node\Neuron;
|
||||
use Phpml\NeuralNetwork\Node\Neuron\Synapse;
|
||||
use PHPUnit\Framework\MockObject\MockObject;
|
||||
use PHPUnit\Framework\TestCase;
|
||||
use PHPUnit_Framework_MockObject_MockObject;
|
||||
|
||||
class NeuronTest extends TestCase
|
||||
{
|
||||
|
|
@ -22,7 +22,7 @@ class NeuronTest extends TestCase
|
|||
|
||||
public function testNeuronActivationFunction(): void
|
||||
{
|
||||
/** @var BinaryStep|PHPUnit_Framework_MockObject_MockObject $activationFunction */
|
||||
/** @var BinaryStep|MockObject $activationFunction */
|
||||
$activationFunction = $this->getMockBuilder(BinaryStep::class)->getMock();
|
||||
$activationFunction->method('compute')->with(0)->willReturn($output = 0.69);
|
||||
|
||||
|
|
@ -37,7 +37,7 @@ class NeuronTest extends TestCase
|
|||
$neuron->addSynapse($synapse = $this->getSynapseMock());
|
||||
|
||||
self::assertEquals([$synapse], $neuron->getSynapses());
|
||||
self::assertEquals(0.88, $neuron->getOutput(), '', 0.01);
|
||||
self::assertEqualsWithDelta(0.88, $neuron->getOutput(), 0.01);
|
||||
}
|
||||
|
||||
public function testNeuronRefresh(): void
|
||||
|
|
@ -46,15 +46,15 @@ class NeuronTest extends TestCase
|
|||
$neuron->getOutput();
|
||||
$neuron->addSynapse($this->getSynapseMock());
|
||||
|
||||
self::assertEquals(0.5, $neuron->getOutput(), '', 0.01);
|
||||
self::assertEqualsWithDelta(0.5, $neuron->getOutput(), 0.01);
|
||||
|
||||
$neuron->reset();
|
||||
|
||||
self::assertEquals(0.88, $neuron->getOutput(), '', 0.01);
|
||||
self::assertEqualsWithDelta(0.88, $neuron->getOutput(), 0.01);
|
||||
}
|
||||
|
||||
/**
|
||||
* @return Synapse|PHPUnit_Framework_MockObject_MockObject
|
||||
* @return Synapse|MockObject
|
||||
*/
|
||||
private function getSynapseMock(int $output = 2)
|
||||
{
|
||||
|
|
|
|||
|
|
@ -115,7 +115,7 @@ class PipelineTest extends TestCase
|
|||
$pipeline = new Pipeline([$selector = new SelectKBest(2)], new SVC());
|
||||
$pipeline->train($samples, $targets);
|
||||
|
||||
self::assertEquals([1.47058823, 4.0, 3.0], $selector->scores(), '', 0.00000001);
|
||||
self::assertEqualsWithDelta([1.47058823, 4.0, 3.0], $selector->scores(), 0.00000001);
|
||||
self::assertEquals(['b'], $pipeline->predict([[1, 3, 5]]));
|
||||
}
|
||||
|
||||
|
|
|
|||
|
|
@ -32,7 +32,7 @@ class ImputerTest extends TestCase
|
|||
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $data);
|
||||
$imputer->transform($data);
|
||||
|
||||
self::assertEquals($imputeData, $data, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testComplementsMissingValuesWithMeanStrategyOnRowAxis(): void
|
||||
|
|
@ -54,7 +54,7 @@ class ImputerTest extends TestCase
|
|||
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_ROW, $data);
|
||||
$imputer->transform($data);
|
||||
|
||||
self::assertEquals($imputeData, $data, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testComplementsMissingValuesWithMediaStrategyOnColumnAxis(): void
|
||||
|
|
@ -76,7 +76,7 @@ class ImputerTest extends TestCase
|
|||
$imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_COLUMN, $data);
|
||||
$imputer->transform($data);
|
||||
|
||||
self::assertEquals($imputeData, $data, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testComplementsMissingValuesWithMediaStrategyOnRowAxis(): void
|
||||
|
|
@ -98,7 +98,7 @@ class ImputerTest extends TestCase
|
|||
$imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_ROW, $data);
|
||||
$imputer->transform($data);
|
||||
|
||||
self::assertEquals($imputeData, $data, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testComplementsMissingValuesWithMostFrequentStrategyOnColumnAxis(): void
|
||||
|
|
@ -172,7 +172,7 @@ class ImputerTest extends TestCase
|
|||
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $trainData);
|
||||
$imputer->transform($data);
|
||||
|
||||
self::assertEquals($imputeData, $data, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testThrowExceptionWhenTryingToTransformWithoutTrainSamples(): void
|
||||
|
|
|
|||
|
|
@ -33,7 +33,7 @@ class NormalizerTest extends TestCase
|
|||
$normalizer = new Normalizer();
|
||||
$normalizer->transform($samples);
|
||||
|
||||
self::assertEquals($normalized, $samples, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testNormalizeSamplesWithL1Norm(): void
|
||||
|
|
@ -53,7 +53,7 @@ class NormalizerTest extends TestCase
|
|||
$normalizer = new Normalizer(Normalizer::NORM_L1);
|
||||
$normalizer->transform($samples);
|
||||
|
||||
self::assertEquals($normalized, $samples, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testFitNotChangeNormalizerBehavior(): void
|
||||
|
|
@ -73,11 +73,11 @@ class NormalizerTest extends TestCase
|
|||
$normalizer = new Normalizer();
|
||||
$normalizer->transform($samples);
|
||||
|
||||
self::assertEquals($normalized, $samples, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
|
||||
|
||||
$normalizer->fit($samples);
|
||||
|
||||
self::assertEquals($normalized, $samples, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testL1NormWithZeroSumCondition(): void
|
||||
|
|
@ -97,7 +97,7 @@ class NormalizerTest extends TestCase
|
|||
$normalizer = new Normalizer(Normalizer::NORM_L1);
|
||||
$normalizer->transform($samples);
|
||||
|
||||
self::assertEquals($normalized, $samples, '', $delta = 0.01);
|
||||
self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
|
||||
}
|
||||
|
||||
public function testStandardNorm(): void
|
||||
|
|
|
|||
|
|
@ -21,7 +21,7 @@ class LeastSquaresTest extends TestCase
|
|||
$regression = new LeastSquares();
|
||||
$regression->train($samples, $targets);
|
||||
|
||||
self::assertEquals(4.06, $regression->predict([64]), '', $delta);
|
||||
self::assertEqualsWithDelta(4.06, $regression->predict([64]), $delta);
|
||||
|
||||
//http://www.stat.wmich.edu/s216/book/node127.html
|
||||
$samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]];
|
||||
|
|
@ -30,11 +30,11 @@ class LeastSquaresTest extends TestCase
|
|||
$regression = new LeastSquares();
|
||||
$regression->train($samples, $targets);
|
||||
|
||||
self::assertEquals(7659.35, $regression->predict([9300]), '', $delta);
|
||||
self::assertEquals(5213.81, $regression->predict([57000]), '', $delta);
|
||||
self::assertEquals(4188.13, $regression->predict([77006]), '', $delta);
|
||||
self::assertEquals(7659.35, $regression->predict([9300]), '', $delta);
|
||||
self::assertEquals(278.66, $regression->predict([153260]), '', $delta);
|
||||
self::assertEqualsWithDelta(7659.35, $regression->predict([9300]), $delta);
|
||||
self::assertEqualsWithDelta(5213.81, $regression->predict([57000]), $delta);
|
||||
self::assertEqualsWithDelta(4188.13, $regression->predict([77006]), $delta);
|
||||
self::assertEqualsWithDelta(7659.35, $regression->predict([9300]), $delta);
|
||||
self::assertEqualsWithDelta(278.66, $regression->predict([153260]), $delta);
|
||||
}
|
||||
|
||||
public function testPredictSingleFeatureSamplesWithMatrixTargets(): void
|
||||
|
|
@ -48,7 +48,7 @@ class LeastSquaresTest extends TestCase
|
|||
$regression = new LeastSquares();
|
||||
$regression->train($samples, $targets);
|
||||
|
||||
self::assertEquals(4.06, $regression->predict([64]), '', $delta);
|
||||
self::assertEqualsWithDelta(4.06, $regression->predict([64]), $delta);
|
||||
}
|
||||
|
||||
public function testPredictMultiFeaturesSamples(): void
|
||||
|
|
@ -62,10 +62,10 @@ class LeastSquaresTest extends TestCase
|
|||
$regression = new LeastSquares();
|
||||
$regression->train($samples, $targets);
|
||||
|
||||
self::assertEquals(-800614.957, $regression->getIntercept(), '', $delta);
|
||||
self::assertEquals([-0.0327, 404.14], $regression->getCoefficients(), '', $delta);
|
||||
self::assertEquals(4094.82, $regression->predict([60000, 1996]), '', $delta);
|
||||
self::assertEquals(5711.40, $regression->predict([60000, 2000]), '', $delta);
|
||||
self::assertEqualsWithDelta(-800614.957, $regression->getIntercept(), $delta);
|
||||
self::assertEqualsWithDelta([-0.0327, 404.14], $regression->getCoefficients(), $delta);
|
||||
self::assertEqualsWithDelta(4094.82, $regression->predict([60000, 1996]), $delta);
|
||||
self::assertEqualsWithDelta(5711.40, $regression->predict([60000, 2000]), $delta);
|
||||
}
|
||||
|
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public function testSaveAndRestore(): void
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||||
|
|
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|||
|
|
@ -21,7 +21,7 @@ class SVRTest extends TestCase
|
|||
$regression = new SVR(Kernel::LINEAR);
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$regression->train($samples, $targets);
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||||
|
||||
self::assertEquals(4.03, $regression->predict([64]), '', $delta);
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||||
self::assertEqualsWithDelta(4.03, $regression->predict([64]), $delta);
|
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}
|
||||
|
||||
public function testPredictMultiFeaturesSamples(): void
|
||||
|
|
@ -34,7 +34,7 @@ class SVRTest extends TestCase
|
|||
$regression = new SVR(Kernel::LINEAR);
|
||||
$regression->train($samples, $targets);
|
||||
|
||||
self::assertEquals([4109.82, 4112.28], $regression->predict([[60000, 1996], [60000, 2000]]), '', $delta);
|
||||
self::assertEqualsWithDelta([4109.82, 4112.28], $regression->predict([[60000, 1996], [60000, 2000]]), $delta);
|
||||
}
|
||||
|
||||
public function testSaveAndRestore(): void
|
||||
|
|
|
|||
|
|
@ -59,8 +59,8 @@ SV
|
|||
);
|
||||
$svm->train($samples, $labels);
|
||||
|
||||
self::assertContains(PHP_EOL.'probA ', $svm->getModel());
|
||||
self::assertContains(PHP_EOL.'probB ', $svm->getModel());
|
||||
self::assertStringContainsString(PHP_EOL.'probA ', $svm->getModel());
|
||||
self::assertStringContainsString(PHP_EOL.'probB ', $svm->getModel());
|
||||
}
|
||||
|
||||
public function testPredictSampleWithLinearKernel(): void
|
||||
|
|
|
|||
Loading…
Reference in New Issue