清單ndarray

Question

我試圖使用k均值聚類在SciPy的，正是一個在座：

http://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.vq.kmeans.html#scipy.cluster.vq.kmeans

我所試圖做的是要轉換列表的列表，如以下：

data without_x[ 
[0, 0, 0, 0, 0, 0, 0, 20.0, 1.0, 48.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1224.0, 125.5, 3156.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
[0, 0, 0, 0, 0, 0, 22.5, 56.0, 41.5, 85.5, 0, 0, 0, 0, 0, 0, 0, 0, 1495.0, 3496.5, 2715.0, 5566.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] 
] 

爲了與Kmeans方法一起使用它。當我嘗試將列表列表轉換爲ndarray時，我得到一個空數組，從而排除了整個分析。 ndarray的長度是可變的，它取決於收集的樣本數量。但我可以很容易地與 len（data_without_x）

以下是返回空列表的代碼片段。

import numpy as np 
import "other functions" 

data, data_without_x = data_preparation.generate_sampled_pdf() 
nodes_stats, k, list_of_list= result_som.get_number_k() 

data_array = np.array(data_without_x) 
whitened = whiten(data_array) 
centroids, distortion = kmeans(whitened, int(k), iter=100000) 

，這就是我得到的輸出只是一個簡單的日誌文件保存：

___________________________ 
this is the data array[[ 0. 0. 0. ..., 0. 0. 0.] 
[ 0. 0. 0. ..., 0. 0. 0.] 
[ 0. 0. 0. ..., 0. 0. 0.] 
..., 
[ 0. 0. 0. ..., 0. 0. 0.] 
[ 0. 0. 0. ..., 0. 0. 0.] 
[ 0. 0. 0. ..., 0. 0. 0.]] 
___________________________ 
This is the whitened array[[ nan nan nan ..., nan nan nan] 
[ nan nan nan ..., nan nan nan] 
[ nan nan nan ..., nan nan nan] 
..., 
[ nan nan nan ..., nan nan nan] 
[ nan nan nan ..., nan nan nan] 
[ nan nan nan ..., nan nan nan]] 
___________________________ 

沒有任何人有一個會發生什麼線索，當我嘗試列表列表轉換成numpy的.array？

感謝您的幫助

Answer 1

這正是如何將一個列表的列表轉換爲一個Python ndarray。你確定你的data_without_x填寫正確嗎？在我的機器：

data = [[1,2,3,4],[4,5,6,7,8]] 
data_arr = np.array(data) 

data_arr 
array([[1,2,3,4], 
     [5,6,7,8]]) 

這是行爲，我認爲你期待

看你輸入你有很多零的......記住，打印出不顯示所有的。你可能只是看到你輸入的所有「零」。檢查特定的非零元素，以確保

Answer 2

vq.whiten和vq.kmeans期望形狀(M, N)，其中每一行是一個觀察的陣列。所以，轉你的data_array：numpy的的

import numpy as np 
import scipy.cluster.vq as vq 
np.random.seed(2013)  

data_without_x = [ 
    [0, 0, 0, 0, 0, 0, 0, 20.0, 1.0, 48.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
     1224.0, 125.5, 3156.0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], 
    [0, 0, 0, 0, 0, 0, 22.5, 56.0, 41.5, 85.5, 0, 0, 0, 0, 0, 0, 0, 0, 1495.0, 
     3496.5, 2715.0, 5566.5, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] 
] 


data_array = np.array(data_without_x).T 
whitened = vq.whiten(data_array) 

centroids, distortion = vq.kmeans(whitened, 5) 
print(centroids) 

產生

[[ 1.22649791e+00 2.69573144e+00] 
[ 3.91943108e-03 5.57406434e-03] 
[ 5.73668382e+00 4.83161524e+00] 
[ 0.00000000e+00 1.29763133e+00]] 

Answer 3

使用asarray功能。 其簡單： Ref：https://docs.scipy.org/doc/numpy/reference/generated/numpy.asarray.html