JesseCrocker

#!/usr/bin/env python3

import argparse
import os
from pmtiles.reader import MmapSource, Reader, all_tiles
from pmtiles.writer import Writer
from pmtiles.tile import Compression
from pmtiles.tile import zxy_to_tileid
from tqdm import tqdm
def merge_pmtiles(input_dir: str, output_file: str) -> None:

raydouglass

#!/usr/bin/env bash

set -euxo pipefail

if [ "$EUID" -ne 0 ]; then
  echo "Please run as root"
  exit 1
fi

if ! command nvcc --version >/dev/null 2>&1; then

wriglz

/* 
Data sources for National Park boundaries:
- England: https://environment.data.gov.uk/DefraDataDownload/?mapService=NE/NationalParksEngland&Mode=spatial
- Scotland: https://spatialdata.gov.scot/geonetwork/srv/eng/catalog.search#/home
- Wales: https://datamap.gov.wales/layers/inspire-nrw:NRW_NATIONAL_PARK
*/ 

WITH
  park_info AS(
    -- Select required information about each National Park from a merged dataset

wriglz

-- Snap the points to their closest lines, found in the subquery below
SELECT
  point_id,
  line_id,
  ST_LINE_INTERPOLATE_POINT(line_geom,
  ST_Line_Locate_Point(line_geom, point_geom)) AS snapped_points --Create the snapped points
FROM 

--Subquery to find the closest line to each point (within a pre-defined raidus)
(

leighajarett

zacharyDez

create table hex_r8 as (
  with envelope as (
        select st_envelope(wkb_geometry) geom from quartiers_sociologiques 
    ), h3_id as (
        select h3_polyfill(geom, 8) id from envelope
    )
    select id, st_setsrid(h3_h3index_to_geoboundary(id), 4326) geom from h3_id
  );

janbenetka

SELECT jslibs.h3.ST_GEOGPOINTFROMH3("u2ce02j")
SELECT jslibs.h3.ST_H3_BOUNDARY(jslibs.h3.ST_H3(ST_GEOGPOINT(13.377534960188237, 49.747300576525554), 11))
SELECT jslibs.h3.h3GetResolution("u2ce02j");


# lat/lon to hexagon
SELECT jslibs.h3.ST_H3(ST_GEOGPOINT(statistics.coordinate.longitude, statistics.coordinate.latitude), 10) AS dwell_hex_id,


WITH polygon AS (

270ajay

from ortools.sat.python import cp_model

''' course: https://www.coursera.org/learn/solving-algorithms-discrete-optimization#about 
About how cp works and intro to solver strategies'''



def patchingThe9HeavensProblem(): #sudoku problem
    model = cp_model.CpModel()

dougallj

# IDA (disassembler) and Hex-Rays (decompiler) plugin for Apple AMX
#
# WIP research. (This was edited to add more info after someone posted it to
# Hacker News. Click "Revisions" to see full changes.)
#
# Copyright (c) 2020 dougallj


# Based on Python port of VMX intrinsics plugin:
# Copyright (c) 2019 w4kfu - Synacktiv

Mizux

#!/usr/bin/env python3
"""Capacited Vehicles Routing Problem (CVRP).

Here we simulate a vehicle already loaded with 4 orders and on its way to deliver them
When a new order (node 5 -> 6) arrives.
"""
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp

def print_solution(manager, routing, solution):