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#!/bin/bash

if [ "$#" = "0" ]; then
	echo "at least one argument is required"
	exit 1
fi

FILE=$1
GUARD="$2$(printf "%s" $FILE | tr '.' '_' | tr '[[:lower:]]' '[[:upper:]]')"

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#include <iostream>
#include <iomanip>


template<typename T>
union OptionInner {
    T full;
    char empty;
    
    OptionInner(): empty(0) {}

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import numpy as np

def gram_schmidt(X):
    '''
    Perform Gram-Schmidt orthogonalization on the rows of X.
    Return a new array Y with the same shape as Y of which
    the rows form an orthonormal basis.
    
    The input vectors must be linearly independent.
    The number of input vectors (rows) must not exceed the

H2CO3

Preamble

There is a longstanding issue/missing feature/bug with sockets on Docker on macOS; it may never work; you'll need to use a network connection between Docker containers and X11 on macOS for the foreseeable future.

I started from this gist and made some adjustments:

• the volume mappings aren't relevant/used, due to the socket issue above.
• this method only allows X11 connections from your Mac, not the entire local network, which would include everyone on the café/airport WiFi.
• updated to include using the host.docker.internal name for the the container host, instead.
• you have to restart XQuartz after the config change.

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#!/usr/bin/env python3

import numpy as np

def atk(board, x, y):
    h, w = board.shape
    rest = w - x
    atk = np.vstack([np.zeros((y, rest), dtype=int), np.ones(rest, dtype=int), np.zeros((h - 1 - y, rest), dtype=int)])
    atk |= np.eye(N=h, M=rest, k=-y, dtype=int)
    atk |= np.flip(np.eye(N=h, M=rest, k=y-h+1, dtype=int), axis=0)

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from math import floor
import numpy as np

def primes_upto(n):
    maxdiv = floor(n ** 0.5) + 1
    divs = np.arange(2, maxdiv)
    nums = np.arange(2, n + 1)
    rem = np.mod.outer(nums, divs)
    mask = np.less.outer(nums, divs ** 2)
    isprime = np.all(mask | rem, axis=1)

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import time
import numpy as np

def next_gen(world):
    idxs = np.array(np.meshgrid(*[[-1, 0, 1]]*2)).T.reshape(-1, 2)
    rots = [np.roll(world, idx, axis=(0, 1)) for idx in idxs]
    neigh = np.sum(rots, axis=0) # toroidal boundary conditions
    maybe = np.equal.outer([3, 4], neigh)
    masks = [np.ones(world.shape, dtype=bool), world]
    alive = masks & maybe

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#!/usr/bin/env python3

from functools import reduce
import numpy as np

def box(n):
    return np.repeat(
        np.repeat(
            np.arange(1, n**2+1).reshape(n, n),
            n, 1

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Here's my ER schema:

          owns                       is in
user   1 <----> N   real_estate   N <-----> 1   region

What I want:

• for each user,

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https://www.dropbox.com/s/fm1eduzdrblgvyu/Arpad_Goretity_Budapest_Rag.pdf?dl=0