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Wrap lines that go beyond GitHub Editor (#1925)

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* Wrap lines that go beyond GiHub Editor

* flake8 --count --select=E501 --max-line-length=127

* updating DIRECTORY.md

* Update strassen_matrix_multiplication.py

* fixup! Format Python code with psf/black push

* Update decision_tree.py

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>
This commit is contained in:
Christian Clauss
2020-05-01 23:36:35 +02:00
committed by GitHub
parent bcaa88b26c
commit 6acd7fb5ce
19 changed files with 161 additions and 82 deletions
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12
maths/pi_monte_carlo_estimation.py
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@@ -23,9 +23,11 @@ class Point:
def estimate_pi(number_of_simulations: int) -> float:
"""
Generates an estimate of the mathematical constant PI (see https://en.wikipedia.org/wiki/Monte_Carlo_method#Overview).
Generates an estimate of the mathematical constant PI.
See https://en.wikipedia.org/wiki/Monte_Carlo_method#Overview
The estimate is generated by Monte Carlo simulations. Let U be uniformly drawn from the unit square [0, 1) x [0, 1). The probability that U lies in the unit circle is:
The estimate is generated by Monte Carlo simulations. Let U be uniformly drawn from
the unit square [0, 1) x [0, 1). The probability that U lies in the unit circle is:
P[U in unit circle] = 1/4 PI
@@ -33,10 +35,12 @@ def estimate_pi(number_of_simulations: int) -> float:
PI = 4 * P[U in unit circle]
We can get an estimate of the probability P[U in unit circle] (see https://en.wikipedia.org/wiki/Empirical_probability) by:
We can get an estimate of the probability P[U in unit circle].
See https://en.wikipedia.org/wiki/Empirical_probability by:
1. Draw a point uniformly from the unit square.
2. Repeat the first step n times and count the number of points in the unit circle, which is called m.
2. Repeat the first step n times and count the number of points in the unit
circle, which is called m.
3. An estimate of P[U in unit circle] is m/n
"""
if number_of_simulations < 1:

5
maths/zellers_congruence.py
View File

@@ -147,7 +147,10 @@ if __name__ == "__main__":
doctest.testmod()
parser = argparse.ArgumentParser(
description="Find out what day of the week nearly any date is or was. Enter date as a string in the mm-dd-yyyy or mm/dd/yyyy format"
description=(
"Find out what day of the week nearly any date is or was. Enter "
"date as a string in the mm-dd-yyyy or mm/dd/yyyy format"
)
)
parser.add_argument(
"date_input", type=str, help="Date as a string (mm-dd-yyyy or mm/dd/yyyy)"