nicoguaro

# -*- coding: utf-8 -*-
"""
Flip a fair coin 100 times—it gives a sequence of heads (H)
and tails (T). For each HH in the sequence of flips, Alice
gets a point; for each HT, Bob does, so e.g. for the
sequence THHHT Alice gets 2 points and Bob gets 1 point.
Who is most likely to win?


https://x.com/littmath/status/1769044719034647001

nicoguaro

name: ori-py
channels:
  - conda-forge
dependencies:
  - python
  - numpy
  - scipy
  - matplotlib
  - jupyterlab
  - pyvista

nicoguaro

nicoguaro

import numpy as np
from numpy.polynomial import Polynomial


rng = np.random.default_rng()
x = np.arange(10)
y = np.arange(10) + 0.01*rng.standard_normal(10)

p_fitted = np.polynomial.Polynomial.fit(x, y, deg=1)

nicoguaro

# -*- coding: utf-8 -*-
import matplotlib.pyplot as plt
from wordcloud import WordCloud, STOPWORDS


#%%
f = open('output_file.txt', 'r', encoding="utf8")
text = f.read()
f.close()

nicoguaro

nicoguaro

import numpy as np
import matplotlib.pyplot as plt
from skimage import measure


y, x, z = np.mgrid[-2:2:100j, -2:2:100j, -2:2:100j]
f = (x**2 + 9/4*y**2 + z**2 - 1)**3 - x**2 * z**3 - 9/80*y**2*z**3
verts, faces, _, _ = measure.marching_cubes(f, 0, spacing=(0.1, 0.1, 0.1))

fig = plt.figure()

nicoguaro

# -*- coding: utf-8 -*-
"""
Eigenvalues for matrices with random entries with values of 1 or -1

@author: Nicolás Guarín-Zapata
@date: November 2022
"""

import numpy as np
import matplotlib.pyplot as plt

nicoguaro

nicoguaro