mdespriee

// This code is related to PR https://github.com/apache/spark/pull/17461
// I show how to use the setInitialModel() param of LDA to build a model incrementally, 
// and I compare the performance (perplexity) with a model built in one-shot


import scala.collection.mutable

import org.apache.spark.ml.{Pipeline, PipelineModel}
import org.apache.spark.ml.clustering.{LDA, LDAModel}

mariussoutier

  def time[T](block: => T): T = {
    val start = System.currentTimeMillis
    val res = block
    val totalTime = System.currentTimeMillis - start
    println("Elapsed time: %1d ms".format(totalTime))
    res
  }

Digital2Slave

import matplotlib.pyplot as plt
import numpy as np

def show_images(images, cols = 1, titles = None):
    """Display a list of images in a single figure with matplotlib.
    
    Parameters
    ---------
    images: List of np.arrays compatible with plt.imshow.
    

xgfs

xgfs_normal6 = [(64, 83, 211), (221, 179, 16), (181, 29, 20), (0, 190, 255), (251, 73, 176), (0, 178, 93), (202, 202, 202)]
xgfs_normal12 = [(235, 172, 35), (184, 0, 88), (0, 140, 249), (0, 110, 0), (0, 187, 173), (209, 99, 230), (178, 69, 2), (255, 146, 135), (89, 84, 214), (0, 198, 248), (135, 133, 0), (0, 167, 108), (189, 189, 189)]
xgfs_bright6 = [(239, 230, 69), (233, 53, 161), (0, 227, 255), (225, 86, 44), (83, 126, 255), (0, 203, 133), (238, 238, 238)]
xgfs_dark6 = [(0, 89, 0), (0, 0, 120), (73, 13, 0), (138, 3, 79), (0, 90, 138), (68, 53, 0), (88, 88, 88)]
xgfs_fancy6 = [(86, 100, 26), (192, 175, 251), (230, 161, 118), (0, 103, 138), (152, 68, 100), (94, 204, 171), (205, 205, 205)]
xgfs_tarnish6 = [(39, 77, 82), (199, 162, 166), (129, 139, 112), (96, 78, 60), (140, 159, 183), (121, 104, 128), (192, 192, 192)]

SeppPenner

Installing Python 3.7.4 on Raspbian

As of July 2018, Raspbian does not yet include the latest Python release, Python 3.7.4. This means we will have to build it ourselves, and here is how to do it.

1. Install the required build-tools (some might already be installed on your system).

shaypal5

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

def print_confusion_matrix(confusion_matrix, class_names, figsize = (10,7), fontsize=14):
    """Prints a confusion matrix, as returned by sklearn.metrics.confusion_matrix, as a heatmap.
    
    Note that due to returning the created figure object, when this funciton is called in a
    notebook the figure willl be printed twice. To prevent this, either append ; to your
    function call, or modify the function by commenting out the return expression.

lefticus

THIS DOCUMENT

IS OUT OF

DATE

See https://github.com/lefticus/cppbestpractices/blob/master/00-Table_of_Contents.md Instead!

C++ Coding Standards Part 0: Automated Code Analysis

Automated analysis is the main advantage to working with a modern statically typed compiled language like C++. Code analysis tools can inform us when we have implemented an operator overload with a non-canonical form, when we should have made a method const, or when the scope of a variable can be reduced.

dschep

Installing Python 3.6 on Raspbian

As of January 2018, Raspbian does not yet include the latest Python release, Python 3.6. This means we will have to build it ourselves, and here is how to do it. There is also an ansible role attached that automates it all for you.

1. Install the required build-tools (some might already be installed on your system).

vool

API domains

https://desktopapps.ryanair.com

https://api.ryanair.com

Airports

https://api.ryanair.com/aggregate/3/common?embedded=airports,countries,cities,regions,nearbyAirports,defaultAirport&market=en-gb

kachayev

from collections import defaultdict
from heapq import *

def dijkstra(edges, f, t):
    g = defaultdict(list)
    for l,r,c in edges:
        g[l].append((c,r))

    q, seen, mins = [(0,f,())], set(), {f: 0}
    while q: