bradtraversy

Webpack & Tailwind CSS Setup

Create your package.json

npm init -y

Create your src folder

Create a folder called src and add an empty index.js file. The code that webpack compiles goes in here including any Javascript modules and the main Tailwind file.

karussell

Android Java

• https://github.com/maplibre/maplibre-navigation-android (mapbox fork from GraphHopper)
• https://github.com/luish88/Turn-by-Turn-Navigation-Module-for-Android (uses GraphHopper with offline routing)
• https://github.com/maksumon/myRoute

JavaScript

• https://github.com/flyandi/react-native-maps-navigation-example -> https://github.com/flyandi/react-native-maps-navigation (2019) (android and ios only, no web)
• https://github.com/ffwdme/ffwdme.js (2017)

alexlib

Python version of the MATLAB code in this Stack Overflow post: http://stackoverflow.com/a/18648210/97160

The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.

Implemented in Python + NumPy + SciPy + matplotlib.

kitloong

!!! This guide was created with Macbook Pro M1. Path may vary for different or even same machine.

Install Homebrew

/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"

Install PHP

qpwo

"""
A minimal implementation of Monte Carlo tree search (MCTS) in Python 3
Luke Harold Miles, July 2019, Public Domain Dedication
See also https://en.wikipedia.org/wiki/Monte_Carlo_tree_search
https://gist.github.com/qpwo/c538c6f73727e254fdc7fab81024f6e1
"""
from abc import ABC, abstractmethod
from collections import defaultdict
import math

lantiga

Indexed convolutions

A convolution operator over a 1D tensor (BxCxL), where a list of neighbors for each element is provided through a indices tensor (LxK), where K is the size of the convolution kernel. Each row of indices specifies the indices of the K neighbors of the corresponding element in the input. A -1 is handled like for zero padding.

Note that the neighbors specified in indices are not relative, but rather absolute. They have to be specified for each of the elements of the output.

A use case is for convolutions over non-square lattices, such as images on hexagonal lattices coming from Cherenkov telescopes (http://www.isdc.unige.ch/%7Elyard/FirstLight/FirstLight_slowHD.mov).

Example:

fasiha

from numpy import linalg as la
import numpy as np


def nearestPD(A):
    """Find the nearest positive-definite matrix to input

    A Python/Numpy port of John D'Errico's `nearestSPD` MATLAB code [1], which
    credits [2].

NKUCodingCat

# This script may use ~8 MiB Memory, it is fast and safe

def find_IP(dns_ser, domain, timeout = 2):
    import dns.resolver, sys
    try:
        T = dns.resolver.Resolver(); T.nameservers = [dns_ser, ]; T.timeout = T.lifetime = timeout
        answers = T.query(domain, raise_on_no_answer=False)
        return [rdata for rdata in answers]
    except Exception as e:
        if e.__class__.__base__ == dns.exception.DNSException:

nim65s

from numpy import arccos, array, dot, pi
from numpy.linalg import det, norm

def distance(A, B, P):
    """ segment line AB, point P, where each one is an array([x, y]) """
    if all(A == P) or all(B == P):
        return 0
    if arccos(dot((P - A) / norm(P - A), (B - A) / norm(B - A))) > pi / 2:
        return norm(P - A)
    if arccos(dot((P - B) / norm(P - B), (A - B) / norm(A - B))) > pi / 2:

liabru

var testObject = {
    pi: Math.PI,
    e: Math.E,
    one: 1,
    x: 1.5,
    str: "1.2345"
};
 
var places = 2,
    json = JSON.stringify(testObject, function(key, value) {