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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,50 +1,62 @@ | ||
| <?php | ||
|
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||
| namespace Designbycode\FuzzySearch; | ||
|
|
||
| class LevenshteinDistance { | ||
| /** | ||
| * Calculate the Levenshtein distance between two strings. | ||
| * | ||
| * The Levenshtein distance is a measure of the minimum number of single-character edits | ||
| * (insertions, deletions or substitutions) required to change one word into the other. | ||
| * | ||
| * @param string $str1 The first string. | ||
| * @param string $str2 The second string. | ||
| * @return int The Levenshtein distance between the two strings. | ||
| */ | ||
| public static function calculate(string $str1, string $str2): int | ||
| { | ||
| // Create a 2D array to store the distances between substrings of $str1 and $str2 | ||
| $distanceMatrix = array(); | ||
|
|
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| // Initialize the first row and column of the matrix | ||
| $str1Length = strlen($str1); | ||
| $str2Length = strlen($str2); | ||
| for ($i = 0; $i <= $str1Length; $i++) { | ||
| $distanceMatrix[$i][0] = $i; // Distance from empty string to $str1 substrings | ||
| } | ||
| for ($j = 0; $j <= $str2Length; $j++) { | ||
| $distanceMatrix[0][$j] = $j; // Distance from empty string to $str2 substrings | ||
| } | ||
| namespace Designbycode\FuzzySearch; | ||
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| // Iterate through the characters of $str1 and $str2 | ||
| for ($i = 1; $i <= $str1Length; $i++) { | ||
| for ($j = 1; $j <= $str2Length; $j++) { | ||
| // Calculate the cost of substitution (0 if characters match, 1 if they don't) | ||
| $substitutionCost = ($str1[$i - 1] == $str2[$j - 1]) ? 0 : 1; | ||
| use TypeError; | ||
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| // Calculate the minimum distance between the current substrings | ||
| $insertionDistance = $distanceMatrix[$i - 1][$j] + 1; // Insert a character into $str1 | ||
| $deletionDistance = $distanceMatrix[$i][$j - 1] + 1; // Delete a character from $str1 | ||
| $substitutionDistance = $distanceMatrix[$i - 1][$j - 1] + $substitutionCost; // Substitute a character in $str1 | ||
| class LevenshteinDistance | ||
| { | ||
| /** | ||
| * Calculate the Levenshtein distance between two strings. | ||
| * | ||
| * The Levenshtein distance is a measure of the minimum number of single-character edits | ||
| * (insertions, deletions or substitutions) required to change one word into the other. | ||
| * | ||
| * @param string $str1 The first string. | ||
| * @param string $str2 The second string. | ||
| * @return int The Levenshtein distance between the two strings. | ||
| */ | ||
| public static function calculate(mixed $str1, mixed $str2): int | ||
| { | ||
|
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| // Choose the minimum distance | ||
| $distanceMatrix[$i][$j] = min($insertionDistance, $deletionDistance, $substitutionDistance); | ||
| } | ||
| } | ||
| if (!is_string($str1)) { | ||
| throw new TypeError('Argument 1 passed to LevenshteinDistance::calculate() must be of the type string'); | ||
| } | ||
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| if (!is_string($str2)) { | ||
| throw new TypeError('Argument 2 passed to LevenshteinDistance::calculate() must be of the type string'); | ||
| } | ||
|
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| // Create a 2D array to store the distances between substrings of $str1 and $str2 | ||
| $distanceMatrix = []; | ||
|
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| // Return the Levenshtein distance between the entire strings | ||
| return $distanceMatrix[$str1Length][$str2Length]; | ||
| // Initialize the first row and column of the matrix | ||
| $str1Length = strlen($str1); | ||
| $str2Length = strlen($str2); | ||
| for ($i = 0; $i <= $str1Length; $i++) { | ||
| $distanceMatrix[$i][0] = $i; // Distance from empty string to $str1 substrings | ||
| } | ||
| for ($j = 0; $j <= $str2Length; $j++) { | ||
| $distanceMatrix[0][$j] = $j; // Distance from empty string to $str2 substrings | ||
| } | ||
|
|
||
| // Iterate through the characters of $str1 and $str2 | ||
| for ($i = 1; $i <= $str1Length; $i++) { | ||
| for ($j = 1; $j <= $str2Length; $j++) { | ||
| // Calculate the cost of substitution (0 if characters match, 1 if they don't) | ||
| $substitutionCost = ($str1[$i - 1] == $str2[$j - 1]) ? 0 : 1; | ||
|
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| // Calculate the minimum distance between the current substrings | ||
| $insertionDistance = $distanceMatrix[$i - 1][$j] + 1; // Insert a character into $str1 | ||
| $deletionDistance = $distanceMatrix[$i][$j - 1] + 1; // Delete a character from $str1 | ||
| $substitutionDistance = $distanceMatrix[$i - 1][$j - 1] + $substitutionCost; // Substitute a character in $str1 | ||
|
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| // Choose the minimum distance | ||
| $distanceMatrix[$i][$j] = min($insertionDistance, $deletionDistance, $substitutionDistance); | ||
| } | ||
| } | ||
|
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| // Return the Levenshtein distance between the entire strings | ||
| return $distanceMatrix[$str1Length][$str2Length]; | ||
| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,31 +1,31 @@ | ||
| <?php | ||
|
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| use Designbycode\FuzzySearch\FuzzySearch; | ||
| use Designbycode\FuzzySearch\FuzzySearch; | ||
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| test('search returns similar matches', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('aple'); | ||
| expect($results)->toEqual(['apple']); | ||
| }); | ||
| test('search returns similar matches', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('aple'); | ||
| expect($results)->toEqual(['apple']); | ||
| }); | ||
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| test('search returns no results for non-existent query', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('xyz'); | ||
| expect($results)->toEqual([]); | ||
| }); | ||
| test('search returns no results for non-existent query', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('xyz'); | ||
| expect($results)->toEqual([]); | ||
| }); | ||
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| test('search returns exact match', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('apple'); | ||
| expect($results)->toEqual(['apple']); | ||
| }); | ||
| test('search returns exact match', function () { | ||
| $index = ['apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('apple'); | ||
| expect($results)->toEqual(['apple']); | ||
| }); | ||
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| test('search is case-insensitive', function () { | ||
| $index = ['Apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('aPpLe'); | ||
| expect($results)->toEqual(['Apple']); | ||
| }); | ||
| test('search is case-insensitive', function () { | ||
| $index = ['Apple', 'banana', 'orange', 'grape', 'pear']; | ||
| $fuzzySearch = new FuzzySearch($index); | ||
| $results = $fuzzySearch->search('aPpLe'); | ||
| expect($results)->toEqual(['Apple']); | ||
| }); |
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