Emily's Completed Methods for Arrays #34
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CheezItMan
reviewed
Sep 22, 2020
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| # Time complexity: O(n) because I'm performing a linear search until the loop reaches nil in the array. | ||
| # Space complexity: O(1), because I'm only looking for 1 value, it doesn't matter what size the array is. | ||
| def length(array) |
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| # Time complexity: O(1) because retrieving an element is constant, regardless of the size. | ||
| # Space complexity: O(1) because size of the array doesn't matter? Still retrieving one element at a time. | ||
| def print_array(array) |
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👍 , however the time complexity is O(n) because you print out n elements and it increases as the size of the array increases proportionately.
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| # Time complexity: O(n) for an unsorted array, because of its linear search to find that value. | ||
| # Space complexity: O(1), because I'm only looking for 1 value. | ||
| def search(array, length, value_to_find) |
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| # Time complexity: O(n) because it involves a linear search for an unsorted array. O(1), if it's sorted because the search will end if it's the first element (largest_value = array[0]). | ||
| # Space complexity: O(1), because I'm only looking for 1 value. | ||
| def find_largest(array, length) |
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| # Time complexity: O(n) because it involves a linear search for an unsorted array. O(1), if it's sorted because the search will end if it's the first element (smallest_val = array[0]). | ||
| # Space complexity: O(1), because I'm only looking for 1 value. | ||
| def find_smallest(array, length) |
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| # Time complexity: O(1), because I'm retrieving one element at a time? | ||
| # Space complexity: O(1) | ||
| def reverse(array, length) |
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👍 , however the time complexity is O(n) because you loop n/2 times.
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| # Time complexity: O(log n), to narrow down my search by n/2 after an iteration, and then n/4 if there's another iteration that's needed to find the value. | ||
| # Space complexity: O(1), because I'm only looking for 1 value. | ||
| def binary_search(array, length, value_to_find) |
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*need to review Big-O!