未验证 提交 a9846523 编写于 作者: R Rohan R Bharadwaj 提交者: GitHub

[mypy] Fix type annotations for maths directory (#5782)

* [mypy] Fix annotations in `maths/series/p_series.py`

* Update p_series.py

* Update p_series.py

* Remove from excluded in mypy.ini

* Type annotation for series

* Annotate maths/proth_number.py (properly)

* Remove from excluded in mypy.ini

* Annotate average_mode.py

* Update average_mode.py

* Update average_mode.py

* Update average_mode.py

* Update average_mode.py

* Remove from excluded in mypy.ini

* Fix annotations in gamma_recursive.py

* Remove from excluded in mypy.ini

* Annotations for geometric_series.py

* Update geometric_series.py

* Update mypy.ini

* Update average_mode.py

* Update average_mode.py

* Update average_mode.py

* Update mypy.ini

* Update mypy.ini

* Update mypy.ini

* Update average_mode.py

* Update proth_number.py

* Update average_mode.py

* Update gamma_recursive.py

* Update proth_number.py

* Update mypy.ini

* Update geometric_series.py

* Update average_mode.py

* Update proth_number.py

* Update geometric_series.py

* Update geometric_series.py

* Update geometric_series.py

* Update p_series.py

* Update geometric_series.py

* Update p_series.py

* Update p_series.py

* Update geometric_series.py

* Update p_series.py

* Update p_series.py

* Remove data_structures/stacks/next_greater_element.py|
Co-authored-by: NChristian Clauss <cclauss@me.com>
上级 db5aa1d1
def mode(input_list: list) -> list: # Defining function "mode."
from typing import Any
def mode(input_list: list) -> list[Any]:
"""This function returns the mode(Mode as in the measures of
central tendency) of the input data.
The input list may contain any Datastructure or any Datatype.
>>> input_list = [2, 3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 2, 2, 2]
>>> mode(input_list)
>>> mode([2, 3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 2, 2, 2])
[2]
>>> input_list = [3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 4, 2, 2, 2]
>>> mode(input_list)
>>> mode([3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 4, 2, 2, 2])
[2]
>>> input_list = [3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 4, 4, 2, 2, 4, 2]
>>> mode(input_list)
>>> mode([3, 4, 5, 3, 4, 2, 5, 2, 2, 4, 4, 4, 2, 2, 4, 2])
[2, 4]
>>> input_list = ["x", "y", "y", "z"]
>>> mode(input_list)
>>> mode(["x", "y", "y", "z"])
['y']
>>> input_list = ["x", "x" , "y", "y", "z"]
>>> mode(input_list)
>>> mode(["x", "x" , "y", "y", "z"])
['x', 'y']
"""
result = list() # Empty list to store the counts of elements in input_list
for x in input_list:
result.append(input_list.count(x))
if not result:
if not input_list:
return []
y = max(result) # Gets the maximum value in the result list.
result = [input_list.count(value) for value in input_list]
y = max(result) # Gets the maximum count in the input list.
# Gets values of modes
result = {input_list[i] for i, value in enumerate(result) if value == y}
return sorted(result)
return sorted({input_list[i] for i, value in enumerate(result) if value == y})
if __name__ == "__main__":
......
......@@ -2,7 +2,6 @@
Gamma function is a very useful tool in math and physics.
It helps calculating complex integral in a convenient way.
for more info: https://en.wikipedia.org/wiki/Gamma_function
Python's Standard Library math.gamma() function overflows around gamma(171.624).
"""
from math import pi, sqrt
......@@ -71,7 +70,7 @@ if __name__ == "__main__":
from doctest import testmod
testmod()
num = 1
num = 1.0
while num:
num = float(input("Gamma of: "))
print(f"gamma({num}) = {gamma(num)}")
......
"""
Calculate the nth Proth number
Source:
https://handwiki.org/wiki/Proth_number
"""
......@@ -12,22 +11,17 @@ def proth(number: int) -> int:
"""
:param number: nth number to calculate in the sequence
:return: the nth number in Proth number
Note: indexing starts at 1 i.e. proth(1) gives the first Proth number of 3
>>> proth(6)
25
>>> proth(0)
Traceback (most recent call last):
...
ValueError: Input value of [number=0] must be > 0
>>> proth(-1)
Traceback (most recent call last):
...
ValueError: Input value of [number=-1] must be > 0
>>> proth(6.0)
Traceback (most recent call last):
...
......@@ -44,14 +38,12 @@ def proth(number: int) -> int:
elif number == 2:
return 5
else:
block_index = number // 3
"""
+1 for binary starting at 0 i.e. 2^0, 2^1, etc.
+1 to start the sequence at the 3rd Proth number
Hence, we have a +2 in the below statement
"""
block_index = math.log(block_index, 2) + 2
block_index = int(block_index)
block_index = int(math.log(number // 3, 2)) + 2
proth_list = [3, 5]
proth_index = 2
......@@ -66,6 +58,10 @@ def proth(number: int) -> int:
if __name__ == "__main__":
import doctest
doctest.testmod()
for number in range(11):
value = 0
try:
......
"""
This is a pure Python implementation of the Geometric Series algorithm
https://en.wikipedia.org/wiki/Geometric_series
Run the doctests with the following command:
python3 -m doctest -v geometric_series.py
or
......@@ -11,8 +10,17 @@ python3 geometric_series.py
"""
def geometric_series(nth_term: int, start_term_a: int, common_ratio_r: int) -> list:
"""Pure Python implementation of Geometric Series algorithm
from __future__ import annotations
def geometric_series(
nth_term: float | int,
start_term_a: float | int,
common_ratio_r: float | int,
) -> list[float | int]:
"""
Pure Python implementation of Geometric Series algorithm
:param nth_term: The last term (nth term of Geometric Series)
:param start_term_a : The first term of Geometric Series
:param common_ratio_r : The common ratio between all the terms
......@@ -20,15 +28,15 @@ def geometric_series(nth_term: int, start_term_a: int, common_ratio_r: int) -> l
ration with first term with increase in power till last term (nth term)
Examples:
>>> geometric_series(4, 2, 2)
[2, '4.0', '8.0', '16.0']
[2, 4.0, 8.0, 16.0]
>>> geometric_series(4.0, 2.0, 2.0)
[2.0, '4.0', '8.0', '16.0']
[2.0, 4.0, 8.0, 16.0]
>>> geometric_series(4.1, 2.1, 2.1)
[2.1, '4.41', '9.261000000000001', '19.448100000000004']
[2.1, 4.41, 9.261000000000001, 19.448100000000004]
>>> geometric_series(4, 2, -2)
[2, '-4.0', '8.0', '-16.0']
[2, -4.0, 8.0, -16.0]
>>> geometric_series(4, -2, 2)
[-2, '-4.0', '-8.0', '-16.0']
[-2, -4.0, -8.0, -16.0]
>>> geometric_series(-4, 2, 2)
[]
>>> geometric_series(0, 100, 500)
......@@ -38,9 +46,9 @@ def geometric_series(nth_term: int, start_term_a: int, common_ratio_r: int) -> l
>>> geometric_series(0, 0, 0)
[]
"""
if "" in (nth_term, start_term_a, common_ratio_r):
return ""
series = []
if not all((nth_term, start_term_a, common_ratio_r)):
return []
series: list[float | int] = []
power = 1
multiple = common_ratio_r
for _ in range(int(nth_term)):
......@@ -48,16 +56,20 @@ def geometric_series(nth_term: int, start_term_a: int, common_ratio_r: int) -> l
series.append(start_term_a)
else:
power += 1
series.append(str(float(start_term_a) * float(multiple)))
series.append(float(start_term_a * multiple))
multiple = pow(float(common_ratio_r), power)
return series
if __name__ == "__main__":
nth_term = input("Enter the last number (n term) of the Geometric Series")
start_term_a = input("Enter the starting term (a) of the Geometric Series")
common_ratio_r = input(
"Enter the common ratio between two terms (r) of the Geometric Series"
import doctest
doctest.testmod()
nth_term = float(input("Enter the last number (n term) of the Geometric Series"))
start_term_a = float(input("Enter the starting term (a) of the Geometric Series"))
common_ratio_r = float(
input("Enter the common ratio between two terms (r) of the Geometric Series")
)
print("Formula of Geometric Series => a + ar + ar^2 ... +ar^n")
print(geometric_series(nth_term, start_term_a, common_ratio_r))
"""
This is a pure Python implementation of the P-Series algorithm
https://en.wikipedia.org/wiki/Harmonic_series_(mathematics)#P-series
For doctests run following command:
python -m doctest -v p_series.py
or
python3 -m doctest -v p_series.py
For manual testing run:
python3 p_series.py
"""
def p_series(nth_term: int, power: int) -> list:
"""Pure Python implementation of P-Series algorithm
from __future__ import annotations
:return: The P-Series starting from 1 to last (nth) term
def p_series(nth_term: int | float | str, power: int | float | str) -> list[str]:
"""
Pure Python implementation of P-Series algorithm
:return: The P-Series starting from 1 to last (nth) term
Examples:
>>> p_series(5, 2)
[1, '1/4', '1/9', '1/16', '1/25']
['1', '1 / 4', '1 / 9', '1 / 16', '1 / 25']
>>> p_series(-5, 2)
[]
>>> p_series(5, -2)
[1, '1/0.25', '1/0.1111111111111111', '1/0.0625', '1/0.04']
['1', '1 / 0.25', '1 / 0.1111111111111111', '1 / 0.0625', '1 / 0.04']
>>> p_series("", 1000)
''
['']
>>> p_series(0, 0)
[]
>>> p_series(1, 1)
[1]
['1']
"""
if nth_term == "":
return nth_term
return [""]
nth_term = int(nth_term)
power = int(power)
series = []
series: list[str] = []
for temp in range(int(nth_term)):
series.append(f"1/{pow(temp + 1, int(power))}" if series else 1)
series.append(f"1 / {pow(temp + 1, int(power))}" if series else "1")
return series
if __name__ == "__main__":
nth_term = input("Enter the last number (nth term) of the P-Series")
power = input("Enter the power for P-Series")
import doctest
doctest.testmod()
nth_term = int(input("Enter the last number (nth term) of the P-Series"))
power = int(input("Enter the power for P-Series"))
print("Formula of P-Series => 1+1/2^p+1/3^p ..... 1/n^p")
print(p_series(nth_term, power))
......@@ -2,5 +2,4 @@
ignore_missing_imports = True
install_types = True
non_interactive = True
exclude = (data_structures/stacks/next_greater_element.py|graphs/boruvka.py|graphs/breadth_first_search.py|graphs/breadth_first_search_2.py|graphs/check_cycle.py|graphs/finding_bridges.py|graphs/greedy_min_vertex_cover.py|graphs/random_graph_generator.py|maths/average_mode.py|maths/gamma_recursive.py|maths/proth_number.py|maths/series/geometric_series.py|maths/series/p_series.py|matrix_operation.py|other/least_recently_used.py|other/lfu_cache.py|other/lru_cache.py|searches/simulated_annealing.py|searches/ternary_search.py)
exclude = (graphs/boruvka.py|graphs/breadth_first_search.py|graphs/breadth_first_search_2.py|graphs/check_cycle.py|graphs/finding_bridges.py|graphs/greedy_min_vertex_cover.py|graphs/random_graph_generator.py|matrix_operation.py|other/least_recently_used.py|other/lfu_cache.py|other/lru_cache.py|searches/simulated_annealing.py|searches/ternary_search.py)
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