mbeltagy

#!/bin/false

# This file will be sourced in init.sh

# https://raw.githubusercontent.com/ai-dock/comfyui/main/config/provisioning/animated.sh
printf "\n##############################################\n#                                            #\n#          Provisioning container            #\n#                                            #\n#         This will take some time           #\n#                                            #\n# Your container will be ready on completion #\n#                                            #\n##############################################\n\n"


## Set paths
## main paths

mbeltagy

julia> let_in_pos = Dict{Int,Char}(); 
julia> let_not_in_pos = Dict{Char,Vector{Int}}();
julia> let_not_in_word = Set{Char}();
julia> word_set = copy(words);
julia> word=rand(word_set)
"excel"
 
julia> update_constraints_by_response!(word, "00020", let_in_pos, let_not_in_pos, let_not_in_word)
julia> word_set_reduction!(word_set, let_in_pos, let_not_in_pos, let_not_in_word)
698-element Vector{String}:

mbeltagy

lines = readlines("input20.txt")
algo = lines[1]|> x->[c=='.' ? false : true for c in x]
imag = lines[3:end] .|> (x->[c=='.' ? false : true for c in x]) |> x->hcat(x...)

# pad the image by zeroes to simulate the infnitued 
function pad(imag,pad)
    oldsize = size(imag)
    newsize =  oldsize .+ 2*pad
    new_imag = zeros(eltype(imag), newsize...)
    new_imag[pad+1:oldsize[1]+pad,pad+1:oldsize[2]+pad] .= imag

mbeltagy

input_dir = "images_need_fix/"
output_dir = "images_fixed/"
input_files = readdir(input_dir)

filter!(x->endswith(x,"png"),input_files)

for f in input_files
    input_base_name = splitext(f)[1]
    output_file_name = input_base_name*".jpg"
    from = joinpath(input_dir,f)

mbeltagy

"Pascal triangle"
function pascal(n)
   (n<=0) && error("Pascal trinalge can not have zero or negative rows")
   r=Vector{Int}(undef,n)
   pr=Vector{Int}(undef,n)
   pr[1]=r[1]=1
   println(@view pr[1])
   for i=2:n
      r[1]=r[i]=1
      for j=2:i-1

mbeltagy

round_up(x,m::Integer)=ceil(Int,x/m).*m
round_down(x,m::Integer)=floor(Int,x/m).*m

mbeltagy

using Interpolations, Plots
# Demonstrating interpolations 

x=0:0.5:2π
y=sin.(x);
itp=LinearInterpolation(x,y);
y2=[itp(x) for x in 0:0.1:2];
x2=0:0.1:6;
y2=[itp(x) for x in x2];
itpC=CubicSplineInterpolation(x,y);

mbeltagy

using CSV
data=CSV.read("Jan19.csv")
# The occursin is used to get the line where the transfer happened...hence summing all transfers
audi_ind=findall(x->ismissing(x) ? false : occursin(r"audi"i,x), data[:,1])
data[audi_ind,1:3][:Cash] |> x-> prod.(split.(x,',')) |> x-> Meta.parse.(x) |> sum

mbeltagy

#=
I was getting the following errors when running 
Pkg.update("TensorFlow") 
On my ubunutu 14.04

INFO: Building TensorFlow.jl for CPU use only. To enable the GPU, set the TF_USE_GPU environment variable to 1 and rebuild TensorFlow.jl
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
  0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
curl: (60) server certificate verification failed. CAfile: /etc/ssl/certs/ca-certificates.crt CRLfile: none

mbeltagy

# Reading a fusion table from Julia
using Requests, DataFrames

request_url = "https://www.googleapis.com/fusiontables/v2/query"
query = "SELECT * FROM 1KlX4PFF81wlx_TJ4zGudN_NoV_gq_GwrxuVau_M"

resp=get(request_url,query=Dict("sql"=>query, "key"=>"somekey","alt"=>"csv"))

myTable=readtable(IOBuffer(resp.data));