Python/matrix/pascal_triangle.py
Caeden Perelli-Harris f512b4d105
refactor: Move pascals triange to maths/ ()
* refactor: Move pascals triange to maths/

* Update xgboost_classifier.py

* statsmodels is now compatible with Python 3.11

* statsmodels is now compatible with Python 3.11

* cython>=0.29.28

* cython>=0.29.28  # For statsmodels on Python 3.11

Co-authored-by: Christian Clauss <cclauss@me.com>
2022-11-01 20:25:39 +01:00

190 lines
6.0 KiB
Python

"""
This implementation demonstrates how to generate the elements of a Pascal's triangle.
The element havingva row index of r and column index of c can be derivedvas follows:
triangle[r][c] = triangle[r-1][c-1]+triangle[r-1][c]
A Pascal's triangle is a triangular array containing binomial coefficients.
https://en.wikipedia.org/wiki/Pascal%27s_triangle
"""
def print_pascal_triangle(num_rows: int) -> None:
"""
Print Pascal's triangle for different number of rows
>>> print_pascal_triangle(5)
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
"""
triangle = generate_pascal_triangle(num_rows)
for row_idx in range(num_rows):
# Print left spaces
for _ in range(num_rows - row_idx - 1):
print(end=" ")
# Print row values
for col_idx in range(row_idx + 1):
if col_idx != row_idx:
print(triangle[row_idx][col_idx], end=" ")
else:
print(triangle[row_idx][col_idx], end="")
print()
def generate_pascal_triangle(num_rows: int) -> list[list[int]]:
"""
Create Pascal's triangle for different number of rows
>>> generate_pascal_triangle(0)
[]
>>> generate_pascal_triangle(1)
[[1]]
>>> generate_pascal_triangle(2)
[[1], [1, 1]]
>>> generate_pascal_triangle(3)
[[1], [1, 1], [1, 2, 1]]
>>> generate_pascal_triangle(4)
[[1], [1, 1], [1, 2, 1], [1, 3, 3, 1]]
>>> generate_pascal_triangle(5)
[[1], [1, 1], [1, 2, 1], [1, 3, 3, 1], [1, 4, 6, 4, 1]]
>>> generate_pascal_triangle(-5)
Traceback (most recent call last):
...
ValueError: The input value of 'num_rows' should be greater than or equal to 0
>>> generate_pascal_triangle(7.89)
Traceback (most recent call last):
...
TypeError: The input value of 'num_rows' should be 'int'
"""
if not isinstance(num_rows, int):
raise TypeError("The input value of 'num_rows' should be 'int'")
if num_rows == 0:
return []
elif num_rows < 0:
raise ValueError(
"The input value of 'num_rows' should be greater than or equal to 0"
)
triangle: list[list[int]] = []
for current_row_idx in range(num_rows):
current_row = populate_current_row(triangle, current_row_idx)
triangle.append(current_row)
return triangle
def populate_current_row(triangle: list[list[int]], current_row_idx: int) -> list[int]:
"""
>>> triangle = [[1]]
>>> populate_current_row(triangle, 1)
[1, 1]
"""
current_row = [-1] * (current_row_idx + 1)
# first and last elements of current row are equal to 1
current_row[0], current_row[-1] = 1, 1
for current_col_idx in range(1, current_row_idx):
calculate_current_element(
triangle, current_row, current_row_idx, current_col_idx
)
return current_row
def calculate_current_element(
triangle: list[list[int]],
current_row: list[int],
current_row_idx: int,
current_col_idx: int,
) -> None:
"""
>>> triangle = [[1], [1, 1]]
>>> current_row = [1, -1, 1]
>>> calculate_current_element(triangle, current_row, 2, 1)
>>> current_row
[1, 2, 1]
"""
above_to_left_elt = triangle[current_row_idx - 1][current_col_idx - 1]
above_to_right_elt = triangle[current_row_idx - 1][current_col_idx]
current_row[current_col_idx] = above_to_left_elt + above_to_right_elt
def generate_pascal_triangle_optimized(num_rows: int) -> list[list[int]]:
"""
This function returns a matrix representing the corresponding pascal's triangle
according to the given input of number of rows of Pascal's triangle to be generated.
It reduces the operations done to generate a row by half
by eliminating redundant calculations.
:param num_rows: Integer specifying the number of rows in the Pascal's triangle
:return: 2-D List (matrix) representing the Pascal's triangle
Return the Pascal's triangle of given rows
>>> generate_pascal_triangle_optimized(3)
[[1], [1, 1], [1, 2, 1]]
>>> generate_pascal_triangle_optimized(1)
[[1]]
>>> generate_pascal_triangle_optimized(0)
[]
>>> generate_pascal_triangle_optimized(-5)
Traceback (most recent call last):
...
ValueError: The input value of 'num_rows' should be greater than or equal to 0
>>> generate_pascal_triangle_optimized(7.89)
Traceback (most recent call last):
...
TypeError: The input value of 'num_rows' should be 'int'
"""
if not isinstance(num_rows, int):
raise TypeError("The input value of 'num_rows' should be 'int'")
if num_rows == 0:
return []
elif num_rows < 0:
raise ValueError(
"The input value of 'num_rows' should be greater than or equal to 0"
)
result: list[list[int]] = [[1]]
for row_index in range(1, num_rows):
temp_row = [0] + result[-1] + [0]
row_length = row_index + 1
# Calculate the number of distinct elements in a row
distinct_elements = sum(divmod(row_length, 2))
row_first_half = [
temp_row[i - 1] + temp_row[i] for i in range(1, distinct_elements + 1)
]
row_second_half = row_first_half[: (row_index + 1) // 2]
row_second_half.reverse()
row = row_first_half + row_second_half
result.append(row)
return result
def benchmark() -> None:
"""
Benchmark multiple functions, with three different length int values.
"""
from collections.abc import Callable
from timeit import timeit
def benchmark_a_function(func: Callable, value: int) -> None:
call = f"{func.__name__}({value})"
timing = timeit(f"__main__.{call}", setup="import __main__")
# print(f"{call:38} = {func(value)} -- {timing:.4f} seconds")
print(f"{call:38} -- {timing:.4f} seconds")
for value in range(15): # (1, 7, 14):
for func in (generate_pascal_triangle, generate_pascal_triangle_optimized):
benchmark_a_function(func, value)
print()
if __name__ == "__main__":
import doctest
doctest.testmod()
benchmark()