ericm

gsettings set org.gnome.desktop.peripherals.mouse speed 0
gsettings set org.gnome.desktop.peripherals.mouse accel-profile 'flat'

ericm

set tabstop=4
set shiftwidth=4
set expandtab
" vim-bootstrap 2021-03-29 19:11:41

"*****************************************************************************
"" Vim-Plug core
"*****************************************************************************
let vimplug_exists=expand('~/.vim/autoload/plug.vim')
if has('win32')&&!has('win64')

ericm

t = int(input())
abxy = []
for _ in range(t):
    abxy.append(tuple((int(x) for x in input().split())))

for ab in abxy:
    ded = (ab[2], ab[3])
    res = (ab[0], ab[1])
    x = (res[0]-ded[0], ded[0])
    y = (res[1]-ded[1], ded[1])

ericm

Base 10 Koorde allows a user 10 direct connections to other users.
Just like a graph in a social network, these direct connections will be drawn based on message connections.
However users will message >10 users so more is required.
We can replace direct connecitons based on a LRU policy.
Try to optimize and move peers closer together (by degree) if there's a lot of activity between them.
Due to the nature of the DHT being optimized for access to every node, use this to allow users to connect to new users

Possible way to initiate and maintain connections.
Generate a URL with data encoded in it that will give a user all 10 of its peers IP's. 
Peer will announce to all 10 instantly and try to initiate a connection with them.

ericm

Koorde in base 2

2^d = nodes
i = d-bit id
aware of = 2i%2^d && (2i+1%2^d)

Koorde

• Koord's De Bruijin graph has average lookup of O(logk(n)) where k is the base.
• the more we increase the base k, the lower the avg lookup time.

Koorde in base 10

ericm

class Solution:
    def solveSudoku(self, board: List[List[str]]) -> None:
        """
        Do not return anything, modify board in-place instead.
        """
        # Ui[j] i = ith, j = [box, column, row]
        gen = lambda: range(1, 10)
        missing = [(set(gen()),set(gen()),set(gen())) for _ in range(9)]
        
        # Populate missing

ericm

echo "READING CONFIG"
// Buy binds
bind "kp_end" "buy ak47; buy m4a1;"
bind "kp_downarrow" "buy mac10; buy mp9;"
bind "kp_pgdn" "buy ump45;"
bind "kp_leftarrow" " buy smokegrenade;"
bind "kp_5" " buy incgrenade; buy molotov;"
bind "kp_rightarrow" " buy flashbang;"
bind "kp_plus" " buy hegrenade;"
bind "kp_home" "buy deagle; buy revolver;"

ericm

Logistic Regression Classification aka using sigmoid

• Linear regression with h(x) >= .5 || < .5 requires feature scaling and ins't accurate.

• We require 0 <= h(x) <= 1 for binary classification.

Function

• Sigmoid function is logistic function
• h(x) = g(θ'x)
• g(x) = 1/(1+e^(-z))

ericm

from stackA import Stack

def infix():
    syms = Stack()
    pf = input("Type infix:")
    inp = pf.strip(" ")
    out = []
    for sym in inp:

        if sym in ["*", "/", "+", "-", "("]:

ericm

from stackA import Stack
from random import randint
from datetime import datetime

COLOURS = ["Red", "Green", "Blue"]

rand = lambda: randint(0, 2)

# Single stack
stacks = [Stack() for i in range(5)]