This notebook was prepared by Donne Martin. Source and license info is on GitHub.

Challenge Notebook¶

Constraints¶

• Are items in each row sorted?
• Yes
• Are items in each column sorted?
• Yes
• Is the sorting in ascending or descending order?
• Ascending
• Is the matrix a rectangle? Not jagged?
• Yes
• Is the matrix square?
• Not necessarily
• Is the output a tuple (row, col)?
• Yes
• Is the item you are searching for always in the matrix?
• No
• Can we assume the inputs are valid?
• No
• Can we assume this fits memory?
• Yes

Test Cases¶

• None -> Exception
• General case
• Item found -> (row, col)

Algorithm¶

Refer to the Solution Notebook. If you are stuck and need a hint, the solution notebook's algorithm discussion might be a good place to start.

Code¶

In [ ]:
class SortedMatrix(object):

def find_val(self, matrix, val):
# TODO: Implement me
pass


Unit Test¶

The following unit test is expected to fail until you solve the challenge.

In [ ]:
# %load test_search_sorted_matrix.py
import unittest

class TestSortedMatrix(unittest.TestCase):

def test_find_val(self):
matrix = [[20, 40, 63, 80],
[30, 50, 80, 90],
[40, 60, 110, 110],
[50, 65, 105, 150]]
sorted_matrix = SortedMatrix()
self.assertRaises(TypeError, sorted_matrix.find_val, None, None)
self.assertEqual(sorted_matrix.find_val(matrix, 1000), None)
self.assertEqual(sorted_matrix.find_val(matrix, 60), (2, 1))
print('Success: test_find_val')

def main():
test = TestSortedMatrix()
test.test_find_val()

if __name__ == '__main__':
main()


Solution Notebook¶

Review the Solution Notebook for a discussion on algorithms and code solutions.