pearcemc

class MultiClassDS:
    """
    Generates a dataset of n points from c classes in ratio r
    """
    def __init__(self, classes, length=1000, ratio=None):
        #set params
        self.classes, self.length, self.ratio = classes, length, ratio

        #no ratio supplied? set it to even split
        if not ratio: self._normalise_ratio()

pearcemc

def vis3d(ds):
    """Visualise a 3d MultiClassDS"""
    fig = plt.figure()                            #start pyplot
    fig.suptitle('3d vis')                        #add a title
    cols = ['g', 'b', 'r', 'y']                   #colour options
    ax = fig.add_subplot(111, projection="3d")    #initialise 3d
    ax.set_xlabel('X')                            #set axis labels
    ax.set_ylabel('Y')
    ax.set_zlabel('Z')
    for i, clas in enumerate(ds.get_vectors()):   #loop through the vectorised classes 

pearcemc

from django.conf import settings     #for RECAPTCHA_PRIVATE key

def verify_recaptcha(request):
    import urllib, urllib2, re
    values = {
    "privatekey": settings.RECAPTCHA_PRIVATE,
    "remoteip": request.META['REMOTE_ADDR'],
    "challenge": request.POST['recaptcha_challenge_field'],
    "response": request.POST['recaptcha_response_field'],
    }

pearcemc

"""
Quick and dirty experimental implementation of k-nearest neighbours technique
"""

from scipy import randn
import scipy.stats as stats
import random

from kdata import *