edwinb-ai

using Random
using StaticArrays
using LinearAlgebra
using DelimitedFiles
using ThreadPools
using Printf
using CellListMap.PeriodicSystems
import CellListMap.PeriodicSystems: copy_output, reset_output!, reducer

struct Parameters

edwinb-ai

import numpy as np
from scipy.fft import fft


def clenshaw_curtis(f, a, b, n):
    # Obtain Chebyshev points
    x = np.cos(np.pi * np.arange(n + 1) / n)
    # Rescale the points to the interval
    scaled_x = ((a + b) + ((b - a) * x)) * 0.5
    # Evalute the integrand

edwinb-ai

function blockjonsson(a::AbstractArray)
    d = log2(length(a))
    x = copy(a)
    if (d - floor(d)) != 0
        @info "Warning: Data size = $(floor(2^d)), is not a power of 2."
        @info "Truncating data to $(2^floor(d))."
        x = x[1:(2^round(Int, floor(d)))]
    end
    d = round(Int, floor(d))
    n = 2^d

edwinb-ai

function four1!(data, nn, isign)
    n = Int(2 * nn)
    j = 1

    for i = 1:2:n
        if j > i
            tempr = data[j]
            tempi = data[j + 1]
            data[j] = data[i]
            data[j + 1] = data[i + 1]

edwinb-ai

BootStrap: library
From: ubuntu:20.04

%post
export PATH=/julia-1.5.3/bin:$PATH

apt-get -y update

# install some basic tools
apt-get -y install curl tar gzip git

edwinb-ai

BootStrap: library
From: ubuntu:16.04

%post
export PATH=/julia-1.5.3/bin:$PATH
export LD_LIBRARY_PATH=/julia-1.5.3/lib:/julia-1.5.3/lib/julia:$LD_LIBRARY_PATH
export LC_ALL=C

apt-get -y update

edwinb-ai

import tensorflow as tf
import tensorflow.keras as K
import numpy as np


# Load the MNIST data and show the shape, should be (60000, 28, 28)
mnist = K.datasets.mnist
(x_train, y_train), (x_test, y_test) = mnist.load_data()
print(x_train.shape)

edwinb-ai

import os
import sys

def some_seed():
    seed = int.from_bytes(os.urandom(7), sys.byteorder)

    return seed

edwinb-ai

# Configuration for Alacritty, the GPU enhanced terminal emulator.

# Any items in the `env` entry below will be added as
# environment variables. Some entries may override variables
# set by alacritty itself.
#env:
  # TERM variable
  #
  # This value is used to set the `$TERM` environment variable for
  # each instance of Alacritty. If it is not present, alacritty will

edwinb-ai

import hashlib, binascii, os

def hash_password(password):
    """Hash a password for storing."""
    salt = hashlib.sha256(os.urandom(60)).hexdigest().encode("ascii")
    pwdhash = hashlib.pbkdf2_hmac("sha512", password.encode("utf-8"), 
                                salt, 100000)
    pwdhash = binascii.hexlify(pwdhash)
    return (salt + pwdhash).decode("ascii")