matiskay

#!/bin/bash

# config
IMGS=(
"
     +             o     +       +      o      \n\
 +        o     o       +                 +    \n\
+      o     +              o          +       \n\
 o          +                        0         \n\
     o  +           +        +           +     \n\

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

library('testthat');

test_that('The Standard Desviation of n numbers', {
  x <- c(1, 2, 3, 4, 5, 6, 7, 8);
  sd <- sd(x);
  
  expect_that(sd, equals(2.449490))
});

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 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

import requests
import json

pizza_list = 'http://pizzahut.com.pe/Content/static/jsons/pizza-list.json'
#size_list = 'http://pizzahut.com.pe/Content/static/jsons/size-list.json'

r = requests.get(pizza_list)

pizzas = json.loads(r.text)

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

Fecha Local	Hora Local	Latitud	Longitud	Profundidad	Magnitud	"Intensidad - Localidades"
05/10/2014	06:05:29	-11.95	-77.59	36 Km	4.0 ML	 II Ancón, Lima
02/10/2014	16:33:57	-12.04	-77.13	60 Km	4.0 ML	 II-III Lima
01/10/2014	18:47:54	-13.69	-76.47	41 Km	4.6 ML	 III Pisco; II-III Tambo de Mora, Chincha Alta;II San Vicente, Lunahuana, Ica
30/09/2014	06:39:22	-13.84	-71.83	8 Km	3.6 ML	 II Misca
27/09/2014	21:35:27	-13.81	-71.89	6 Km	5.1 ML	 VII Misca;VI Cusibamba, Toroy, Moyoc; V Colcha,Rondocán;IV Paccaritambo, Ccochirihuay;III-IV Yaurisque, Huanoquite;III Cusco, Omacha; II-III Ccapi;II Urubamba, Calca, Anta, Yanaoca, Huancarani
25/09/2014	22:54:12	-16.79	-70.60	8 Km	3.8 ML	 II Calacoa
25/09/2014	06:19:10	-12.49	-77.31	24 Km	3.9 ML	 II Callao, Lima
19/09/2014	21:44:36	-15.65	-74.03	66 Km	4.5 ML	 II-III Chala; II Atico, Yauca, Caraveli
17/09/2014	23:19:58	-6.15	-76.35	123 Km	4.9 ML	 II Lamas, Moyobamba

matiskay

ops@osm-db:~/learning$ mb-util tiles/planet planet.mbtiles
INFO:mbutil.util:Importing disk to MBTiles
DEBUG:mbutil.util:tiles/planet --> planet.mbtiles
INFO:mbutil.util:metadata from metadata.json restored
DEBUG:mbutil.util: Read tile from Zoom (z): 0	Col (x): 0	Row (y): 0
DEBUG:mbutil.util: Read tile from Zoom (z): 2	Col (x): 1	Row (y): 2
DEBUG:mbutil.util: Read tile from Zoom (z): 1	Col (x): 0	Row (y): 1
DEBUG:mbutil.util: Read tile from Zoom (z): 8	Col (x): 75	Row (y): 159
DEBUG:mbutil.util: Read tile from Zoom (z): 5	Col (x): 9	Row (y): 19
DEBUG:mbutil.util: Read tile from Zoom (z): 6	Col (x): 18	Row (y): 39

matiskay

Latam in OpenStreetMaps

Rendering all the points in Latam

Rendering all the lines in Latam