'numpy.float64'オブジェクトは反復可能ではありません - 平均クラスタリング

Question

python newbie here。このコードを実行しようとしていますが、オブジェクトが反復可能でないというエラーメッセージが表示されます。私が間違っていることについていくつかアドバイスをいただければ幸いです。ありがとう。ここで

import matplotlib.pyplot as plt 
import numpy as np 
import pandas as pd 

temp = pd.read_csv("file.csv", encoding='latin-1') 
xy = temp.ix[:,2:6] 
X = xy.values 

---

X 
array([[    nan,    nan], 
    [    nan,    nan], 
    [ 3.92144000e+00,    nan], 
    [ 4.42382000e+00,    nan], 
    [ 4.18931000e+00, 5.61562775e+02], 
    [    nan,    nan], 
    [ 4.33025000e+00, 6.73123391e+02], 
    [ 6.43775000e+00,    nan], 
    [ 3.12299000e+00, 2.21886627e+03], 
    [    nan,    nan], 
    [    nan,    nan]]) 

---

from itertools import cycle 
colors = cycle('bgrcmykbgrcmykbgrcmykbgrcmyk') 

class Mean_Shift: 
    def __init__(self, radius=4): 
     self.radius = radius 

    def fit(self, data): 
     centroids = {} 

     for i in range(len(data)): 
      centroids[i] = data[i] 

     while True: 
      new_centroids = [] 
      for i in centroids: 
       in_bandwidth = [] 
       centroid = centroids[i] 
       for featureset in data: 
        if np.linalg.norm(featureset-centroid) < self.radius: 
         in_bandwidth.append(featureset) 

       new_centroid = np.average(in_bandwidth, axis=0) 
       new_centroids.append(tuple(new_centroid)) 

      uniques = sorted(list(set(new_centroids))) 

      prev_centroids = dict(centroids) 

      centroids = {} 
      for i in range(len(uniques)): 
       centroids[i] = np.array(uniques[i]) 

      optimized = True 

      for i in centroids: 
       if not np.array_equal(centroids[i], prev_centroids[i]): 
        optimized = False 

       if not optimized: 
        break 

      if optimized: 
       break 

     self.centroids = centroids 

    def predict(self,data): 
     pass 


clf = Mean_Shift() 
clf.fit(X) 

centroids = clf.centroids 

plt.scatter(X[:,0],X[:,1],s=50) 

for c in centroids: 
plt.scatter(centroids[c][0], centroids[c][1], color = 'k', marker='*', s=150) 

plt.show() 

私が取得エラーコードです：

/Users/carla/anaconda/lib/python3.5/site-packages/numpy/core/_methods.py:59: RuntimeWarning: Mean of empty slice. 
    warnings.warn("Mean of empty slice.", RuntimeWarning) 
--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-11-e13932b6e72d> in <module>() 
50 
51 clf = Mean_Shift() 
---> 52 clf.fit(X) 
53 
54 centroids = clf.centroids 

<ipython-input-11-e13932b6e72d> in fit(self, data) 
22 
23     new_centroid = np.average(in_bandwidth, axis=0) 
---> 24     new_centroids.append(tuple(new_centroid)) 
25 
26    uniques = sorted(list(set(new_centroids))) 

TypeError: 'numpy.float64' object is not iterable 

Answer 1

new_centroid = np.average(in_bandwidth, axis=0) 

はnew_centroidにスカラを代入され、あなたがTRYIありますエラーを投げているtuple(scalar)に転送してください。

tuple(2.) 

--------------------------------------------------------------------------- 
TypeError         Traceback (most recent call last) 
<ipython-input-51-4406f9e676cf> in <module>() 
----> 1 tuple(2.) 

TypeError: 'float' object is not iterable