drmalex07

import json
import geojson
from shapely.geometry import shape

o = {
   "coordinates": [[[23.314208, 37.768469], [24.039306, 37.768469], [24.039306, 38.214372], [23.314208, 38.214372], [23.314208, 37.768469]]], 
   "type": "Polygon"
}

s = json.dumps(o)

bbengfort

import networkx as nx
import graph_tool as gt



def get_prop_type(value, key=None):
    """
    Performs typing and value conversion for the graph_tool PropertyMap class.
    If a key is provided, it also ensures the key is in a format that can be

ximeg

#!/usr/bin/env python
# Implementation of algorithm from http://stackoverflow.com/a/22640362/6029703
import numpy as np
import pylab

def thresholding_algo(y, lag, threshold, influence):
    signals = np.zeros(len(y))
    filteredY = np.array(y)
    avgFilter = [0]*len(y)
    stdFilter = [0]*len(y)

jenningsanderson

What are the Daylight OpenStreetMap Parquet Files?

Listed on the registry of Open Data on AWS, the Daylight OpenStreetMap Parquet files contain the latest Daylight Map Distribution of OpenStreetMap in an analysis-ready format. This dataset is optimized for cloud-based queries with Amazon Athena, meaning anyone can access the entire dataset with SQL queries in the browser, without the need to download or access the files directly.

The Daylight Map Distribution of OpenStreetMap is always openly available for download in the standard OSM PBF format (find it at daylightmap.org). The parquet files, however, were first made available alongside Daylight release v1.9. They contain fully resolved geometries and additional metadata including areas, lengths, and quadkeys, not present in the PBF.

In total, the OSM features files contain nearly 1B features including 178M+ nodes, 816M+ ways, and 5M+ relations. These are all _renderable f

sgillies

from math import sqrt

from matplotlib import pyplot
from shapely.geometry import *

GM = (sqrt(5)-1.0)/2.0
W = 8.0
H = W*GM
SIZE = (W, H)
COLORS = ['#6699cc', '#ffcc33']

drewda

# code from http://danieljlewis.org/files/2010/06/Jenks.pdf
# described at http://danieljlewis.org/2010/06/07/jenks-natural-breaks-algorithm-in-python/

def getJenksBreaks( dataList, numClass ):
  dataList.sort()
  mat1 = []
  for i in range(0,len(dataList)+1):
    temp = []
    for j in range(0,numClass+1):
      temp.append(0)

invisiblefunnel

zachallaun

import zulip
import os
import json

client = zulip.Client(config_file='.config', verbose=True)

class TodoManager(object):
    def __init__(self, client):
        self.client = client
        self.todo_file = ".todos"