'numpy.ndarray' object has no attribute 'iteritems'

Question

I want to get a histogram of the raw digits data in 784 dimensions. Here is my code:

import sys,os
from math import *
import random
from numpy import *
import matplotlib.pyplot as plt
import datasets

waitForEnter=False
def exampleDistance(x1, x2):
    dist = 0.
    for i,v1 in x1.iteritems():
        v2 = 0.
        if x2.has_key(i): v2 = x2[i]
        dist += (v1 - v2) * (v1 - v2)
    for i,v2 in x2.iteritems():
        if not x1.has_key(i):
            dist += v2 * v2
    return sqrt(dist)

def computeDistances(data):
    #N = len(data)
    #D = len(data[0])
    N, D = data.shape
    dist = []
    for n in range(N):
        for m in range(n):
            dist.append( exampleDistance(data[n],data[m])  / sqrt(D))
    return dist
Dims = [784]
#Cols = ['#FF0000', '#880000', '#000000', '#000088', '#0000FF']
Cols = ['#FF0000']
Bins = arange(0, 1, 0.02)


plt.xlabel('distance / sqrt(dimensionality)')
plt.ylabel('# of pairs of points at that distance')
#plt.title('dimensionality versus uniform point distances')
plt.title('dimensionality versus digits data point distances')

for i,d in enumerate(Dims):
    distances = computeDistances(datasets.DigitData.X)
    print "D=%d, average distance=%g" % (d, mean(distances) * sqrt(d))
    plt.hist(distances,
             Bins,
             histtype='step',
             color=Cols[i])
    if waitForEnter:
        plt.legend(['%d dims' % d for d in Dims])
        plt.show(False)
        x = raw_input('Press enter to continue...')


plt.legend(['%d dims' % d for d in Dims])
plt.savefig('fig.pdf')
plt.show()

But there is something wrong:

Traceback (most recent call last):
  File "HW3.py", line 56, in <module>
    distances = computeDistances(datasets.DigitData.X)
  File "HW3.py", line 39, in computeDistances
    dist.append( exampleDistance(data[n],data[m])  / sqrt(D))
  File "HW3.py", line 23, in exampleDistance
    for i,v1 in x1.iteritems():
AttributeError: 'numpy.ndarray' object has no attribute 'iteritems'

Besides, here is the digit datasets:

class DigitData:
    Xall,Yall = loadDigitData('data/1vs2.all')
    N,D = Xall.shape
    N0 = int(float(N) * 0.5)
    X = Xall[0:N0,:]
    Y = Yall[0:N0]
    Xte = Xall[N0:,:]
    Yte = Yall[N0:]

Then how can I fix it? As a python beginner, I'm very confused of plotting.

Community · Accepted Answer · 2017-05-23 12:34:07Z

0

I would recommend reading this earlier post and if you still did not find your answer comment on this. I hope that will help.

edited May 23, 2017 at 12:34

CommunityBot

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answered Feb 19, 2017 at 0:33

i.n.n.m

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3 Comments

JennyShen Over a year ago

Thanks for answering. I know iteritems() is used for dictionary not array.However, the function def exampleDistance(x1, x2): is given by Prof. She let us to use this function to calculate distance. I think I have to minimize the changing in exampleDistance(x1, x2), but I don't know how to do it?

i.n.n.m Over a year ago

can you try changing iteritems with items in your function, change it to for i,v1 in x1.items() ?

i.n.n.m Over a year ago

Assuming you have a dictionary with keys,, try for i, v1 in enumerate(x1.iteritems(),1): . This should do the trick. Here 1 is setting the index to start from 1.

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