matiskay

javascript:( function() {
    console.group( 'Performance Information for all entries of ' + window.location.href );
    console.log( '\n-> Duration is displayed in ms\n ' )
    
    var entries = window.performance.getEntries();
    
    entries = entries.sort( function( a, b ) {
        return b.duration - a.duration;
    } );
    

matiskay

import numpy as np
import pylab as pl
import pandas as pd

from sklearn import svm
from sklearn import linear_model
from sklearn import tree

from sklearn.metrics import confusion_matrix

matiskay

# Mathieu Blondel, September 2010
# License: BSD 3 clause

import numpy as np
from numpy import linalg
import cvxopt
import cvxopt.solvers

def linear_kernel(x1, x2):
    return np.dot(x1, x2)

matiskay

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)

matiskay

The difference between XYZ and TMS tiles and how to convert between them

Lots of tile-based maps use either the XYZ or TMS scheme. These are the maps that have tiles ending in /0/0/0.png or something. Sometimes if it's a script, it'll look like &z=0&y=0&x=0 instead. Anyway, these are usually maps in Spherical Mercator.

Good examples are OpenStreetMap, Google Maps, MapBox, MapQuest, etc. Lots of maps.

Most of those are in XYZ. The best documentation for that is slippy map tilenames on the OSM Wiki, and Klokan's Tiles a la Google.

matiskay

When there are so many other projections to chose from, why is it that today the Mercator projection is still such a widely recognized image used to represent the globe? The answer may be simply convention or habit. The inertia of habit is a powerful force.

^Alberto Rios

The main reason Mercator's projection became so popular was because of its navigational usefulness; in his map, straight lines represent lines of constant compass bearing. However, in manipulating the map to ensure this feature, the sizes of countries become hugely distorted. In particular, the southern hemisphere appears much smaller than it is in reality.

^The Guardian

Map projections have become a popular new-journalism meme. With a quick article, you can recap centuries of cartographic history and open peoples eyes to a variety of unusual ways to shape the world. The

matiskay

Plotting Node Density

1. download the source data

    wget http://fred.dev.openstreetmap.org/density/tiles.13
    wget http://fred.dev.openstreetmap.org/density/tiles.16
   

2. convert to simple, gnuplot-readable text format

sed 's/([0-9]) z=([0-9]) x=([0-9]) y=([0-9])/\3 \4 \1/' < tiles.13 > tiles.13.txt

matiskay

#!/usr/bin/env python
###############################################################################
# $Id$
#
# Project:  GDAL2Tiles, Google Summer of Code 2007 & 2008
#           Global Map Tiles Classes
# Purpose:	Convert a raster into TMS tiles, create KML SuperOverlay EPSG:4326,
#			generate a simple HTML viewers based on Google Maps and OpenLayers
# Author:	Klokan Petr Pridal, klokan at klokan dot cz
# Web:		http://www.klokan.cz/projects/gdal2tiles/

matiskay

Latency numbers every programmer should know

L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns                     on recent CPU
L2 cache reference ........................... 7 ns                     14x L1 cache
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns                     20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy ............. 3,000 ns  =   3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns  =  20 µs
SSD random read ........................ 150,000 ns  = 150 µs

Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs 4X memory

matiskay

from dictalchemy import make_class_dictable
from flask import Flask, request, jsonify, json
from flask_sqlalchemy import SQLAlchemy
from jsonpatch import JsonPatch, JsonPatchException

app = Flask(__name__)
app.debug = True
db = SQLAlchemy(app)
make_class_dictable(db.Model)