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# Dmitrydmishin

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Created Apr 22, 2020
Numerically checking surprising identities regarding the sums involving Fibonacci numbers
View check_invfib_sum.py
 #%metadata% #url: https://twitter.com/diegorattaggi/status/1252654580720119810/photo/1 from sympy import * mfib = Matrix([[0,1],[1,1]]) fib0 = Matrix([0,1]) luc0 = Matrix([2,1]) eye = Matrix([[1,0],[0,1]]) def fibo(n):
Created Nov 18, 2019
Detect optimal step for minimal order Schreiber test signal
View schreiber.py
 import numpy as np import scipy as sp import scipy.linalg from math import floor, pi #Detect optimal step for minimal order Schreiber test signal #Set to False to disable printing _verbose = True
Last active Nov 22, 2018
Numerically calculate fractional iterate of x^2-2
View approx_fractional_iterate.py
 def approxfi(x, n): #Apply x -> F(x) mapping until x is sufficiently large k = 0 while (x < 1e14) and (k<100): x = x**2-2 k += 1 #Calculate approximate fractional iterate for large argument x = x**(2**n) #Apply reverse mapping x -> F[-1](x) for _ in range(k):
Created Apr 29, 2016
Unwrap imgage pixels into a 1-dimensional array along the Hilbert's curve, then convert it to sound using SOX
View hilbert_image2audio.py
 #!/usr/bin/env python from __future__ import print_function, division import os.path from numpy import array, hstack, vstack, clip from PIL import Image import numpy as np import subprocess # need the subprocess module from tempfile import mkdtemp import shutil
Created Dec 24, 2015
View audio2hilbert.py
 #!/usr/bin/env python #This is Python3 executable import os.path from numpy import array, hstack, vstack, clip from PIL import Image import numpy as np import subprocess import re #SOX_EXEC = r"C:\Program Files\sox-14-4-2\sox.exe"
Created Oct 31, 2015
Experiments with S(x) = sin(x) + sin(2x)/2 + sin(4x)/4 + ...
View sumsin_mpmath.py
 """Experiments with the 'sumsin' function: maximization and plotting S(x) = sin(x) + sin(2x)/2 + sin(4x)/4 + ... it appears that S(x) reaches maximum at xmax = 0.8905302010175791857059461558*7027* whereas 36pi/127=0.8905302010175791857059461558*9025* Plots of the function:
Created Oct 23, 2014
Generate Fourier transform of the coprime integers map
View coprime_fft.py
 #Requires: numpy, PIL from fractions import gcd from numpy import array, meshgrid, frompyfunc, clip, histogram from numpy.fft import fft2 import numpy as np from PIL import Image def value_diapason(x, percent=0.95, nbins=100): """Use histogram to determine area, covering 95% of values""" counts, bins = histogram(x.ravel(),nbins)
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