Nicolás Guarín-Zapata nicoguaro

## helm_dir.ipynb

      
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                nicoguaro
                / helm_dir.ipynb
            
            
              Created
              March 12, 2025 03:28
            
              
                Solución de la ecuación de Helmholtz inhomogénea para el problema de Dirichlet.
              
          
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## sherlock.png

      
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                nicoguaro
                / sherlock.png
            
            
              Last active
              November 28, 2024 21:38
            
              
                Wordcloud of Sherlock Holmes
              
          
## cst_paper.mplstyle
# Stylesheet for matplotlib
#
# Author: Nicolas Guarin-Zapata
# Date: September, 2018

### Math Text
mathtext.fontset : cm

### Text
text.color : 757575

## dragon_curve.py
# -*- coding: utf-8 -*-
"""
Generate a dragon curve

@author: Nicolás Guarín-Zapata
@date: July 2024
"""
import os
import numpy as np
import matplotlib.pyplot as plt

## randomized_integration.py
import numpy as np
import matplotlib.pyplot as plt
from scipy.integrate import trapezoid, simpson, quad


repo = "https://raw.githubusercontent.com/nicoguaro/matplotlib_styles/master"
style = repo + "/styles/clean.mplstyle"
plt.style.use(style)
plt.rcParams["font.size"] = 20
plt.rcParams["lines.linewidth"] = 3

## flips_coins.py
# -*- 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

## environment.yml
name: ori-py
channels:
  - conda-forge
dependencies:
  - python
  - numpy
  - scipy
  - matplotlib
  - jupyterlab
  - pyvista

## hermite_quintic.ipynb

      
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                nicoguaro
                / hermite_quintic.ipynb
            
            
              Created
              May 17, 2024 22:49
            
              
                Hermite interpolation using quintic polynomials
              
          
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## poly_fit.py
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)

## SLR_wordcloud.py
# -*- 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()
	# Stylesheet for matplotlib
	#
	# Author: Nicolas Guarin-Zapata
	# Date: September, 2018

	### Math Text
	mathtext.fontset : cm

	### Text
	text.color : 757575
	# -- coding: utf-8 --
	"""
	Generate a dragon curve

	@author: Nicolás Guarín-Zapata
	@date: July 2024
	"""
	import os
	import numpy as np
	import matplotlib.pyplot as plt
	import numpy as np
	import matplotlib.pyplot as plt
	from scipy.integrate import trapezoid, simpson, quad


	repo = "https://raw.githubusercontent.com/nicoguaro/matplotlib_styles/master"
	style = repo + "/styles/clean.mplstyle"
	plt.style.use(style)
	plt.rcParams["font.size"] = 20
	plt.rcParams["lines.linewidth"] = 3
	# -- 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
	name: ori-py
	channels:
	- conda-forge
	dependencies:
	- python
	- numpy
	- scipy
	- matplotlib
	- jupyterlab
	- pyvista
	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)
	# -- 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()