omaraflak

import numpy as np
import pyglet

def draw_points(points, format="v2f"):
    pyglet.graphics.draw(
        len(points),
        pyglet.gl.GL_POINTS,
        (format, tuple([x for p in points for x in p]))
    )

omaraflak

import numpy as np
from scipy import signal
from matplotlib import animation, pyplot as plt

def animate(i):
    global board
    neighbors = signal.correlate2d(board, kernel, mode="same")
    board = ((board == 1) & ((neighbors == 2) | (neighbors == 3))) | ((board == 0) & (neighbors == 3))
    image.set_data(board)
    return image

omaraflak

all:
	g++ main.cpp -o main -std=c++11 `sdl2-config --cflags --libs`
	./main

omaraflak

const client = require('socket.io-client')('http://localhost:5000')
const siof = require('./socket.io-file')

client.on('connect', () => {
    console.log('connected to server')
    client.once('ready', () => {
        const metadata = { filename: 'file2.pdf' } // filename on the receiving end
        siof(client).emit('file', 'filepath/to/file.pdf', metadata, (sent, total) => {
            const percentage = (100 * sent / total).toFixed(2)
            console.log(`${percentage}%`)

omaraflak

import numpy as np
import matplotlib.pyplot as plt

N = 100         # in how much sub pieces we should break a 1sec interval
T = 15          # total duration of the simulation
dt = 1 / N      # dt
g = 9.81        # acceleration of gravity
L = 1           # pendulum rope length
k = 0.8         # air resistance coefficient
m = 1           # mass of the pendulum

omaraflak

import numpy as np
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D

I = 300     # samples per class
N = 3       # features
J = 2       # clusters

mean_true = np.random.randint(-20, 20, (J, N))
variance_true = np.array([np.identity(N) * np.random.randint(1, 20, N) for j in range(J)])

omaraflak

import numpy as np
import matplotlib.pyplot as plt

def normalize(vector):
    return vector / np.linalg.norm(vector)

def reflected(vector, axis):
    return vector - 2 * np.dot(vector, axis) * axis

def sphere_intersect(center, radius, ray_origin, ray_direction):

omaraflak

# global variable along with width, height, etc.
max_depth = 3

# everything that follows is inside the double for loop
color = np.zeros((3))
reflection = 1

for k in range(max_depth):
    nearest_object, min_distance = # ...
    # ...

omaraflak

def reflected(vector, axis):
    return vector - 2 * np.dot(vector, axis) * axis

omaraflak

# ...
if is_shadowed:
    break

# RGB
illumination = np.zeros((3))

# ambiant
illumination += nearest_object['ambient'] * light['ambient']