ValueError:使用序列设置数组元素-Python 实用宝典

ValueError:使用序列设置数组元素

此Python代码: import numpy as p def firstfunction(): UnFilteredDuringExSummaryOfMeansArray = [] MeanOutputHeader=['TestID','ConditionName','FilterType','RRMean','HRMean', 'dZdtMaxVoltageMean','BZMean','ZXMean','LVETMean','Z0Mean', 'StrokeVolumeMean','CardiacOutputMean','VelocityIndexMean'] dataMatrix = BeatByBeatMatrixOfMatrices[column] roughTrimmedMatrix = p.array(dataMatrix[1:,1:17]) trimmedMatrix = p.array(roughTrimmedMatrix,dtype=p.float64) #ERROR THROWN HERE myMeans = p.mean(trimmedMatrix,axis=0,dtype=p.float64) conditionMeansArray = [TestID,testCondition,'UnfilteredBefore',myMeans[3], myMeans[4], myMeans[6], myMeans[9], myMeans[10], myMeans[11], myMeans[12], myMeans[13], myMeans[14], myMeans[15]] UnFilteredDuringExSummaryOfMeansArray.append(conditionMeansArray) secondfunction(UnFilteredDuringExSummaryOfMeansArray) return def secondfunction(UnFilteredDuringExSummaryOfMeansArray): RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3] return firstfunction() …

问题:ValueError:使用序列设置数组元素

Python代码:

import numpy as p

def firstfunction():
    UnFilteredDuringExSummaryOfMeansArray = []
    MeanOutputHeader=['TestID','ConditionName','FilterType','RRMean','HRMean',
                      'dZdtMaxVoltageMean','BZMean','ZXMean','LVETMean','Z0Mean',
                      'StrokeVolumeMean','CardiacOutputMean','VelocityIndexMean']
    dataMatrix = BeatByBeatMatrixOfMatrices[column]
    roughTrimmedMatrix = p.array(dataMatrix[1:,1:17])


    trimmedMatrix = p.array(roughTrimmedMatrix,dtype=p.float64)  #ERROR THROWN HERE


    myMeans = p.mean(trimmedMatrix,axis=0,dtype=p.float64)
    conditionMeansArray = [TestID,testCondition,'UnfilteredBefore',myMeans[3], myMeans[4], 
                           myMeans[6], myMeans[9], myMeans[10], myMeans[11], myMeans[12],
                           myMeans[13], myMeans[14], myMeans[15]]
    UnFilteredDuringExSummaryOfMeansArray.append(conditionMeansArray)
    secondfunction(UnFilteredDuringExSummaryOfMeansArray)
    return

def secondfunction(UnFilteredDuringExSummaryOfMeansArray):
    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]
    return

firstfunction()

引发此错误消息:

File "mypath\mypythonscript.py", line 3484, in secondfunction
RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]
ValueError: setting an array element with a sequence.

谁能告诉我该怎么做才能解决上面破碎的代码中的问题,以便停止抛出错误消息?


编辑: 我做了一个打印命令来获取矩阵的内容,这就是它打印出来的内容:

UnFilteredDuringExSummaryOfMeansArray为:

[['TestID', 'ConditionName', 'FilterType', 'RRMean', 'HRMean', 'dZdtMaxVoltageMean', 'BZMean', 'ZXMean', 'LVETMean', 'Z0Mean', 'StrokeVolumeMean', 'CardiacOutputMean', 'VelocityIndexMean'],
[u'HF101710', 'PreEx10SecondsBEFORE', 'UnfilteredBefore', 0.90670000000000006, 66.257731979420001, 1.8305673000000002, 0.11750000000000001, 0.15120546389880002, 0.26870546389879996, 27.628261216480002, 86.944190346160013, 5.767261352345999, 0.066259118585869997],
[u'HF101710', '25W10SecondsBEFORE', 'UnfilteredBefore', 0.68478571428571422, 87.727887206978565, 2.2965444125714285, 0.099642857142857144, 0.14952476549885715, 0.24916762264164286, 27.010483303721429, 103.5237336525, 9.0682762747642869, 0.085022572648242867],
[u'HF101710', '50W10SecondsBEFORE', 'UnfilteredBefore', 0.54188235294117659, 110.74841107829413, 2.6719262705882354, 0.077705882352917643, 0.15051306356552943, 0.2282189459185294, 26.768787504858825, 111.22827075238826, 12.329456404418824, 0.099814258468417641],
[u'HF101710', '75W10SecondsBEFORE', 'UnfilteredBefore', 0.4561904761904762, 131.52996981880955, 3.1818159523809522, 0.074714285714290493, 0.13459344175047619, 0.20930772746485715, 26.391156337028569, 123.27387909873812, 16.214243779323812, 0.1205685359981619]]

对我来说,这看起来像是5行乘13列的矩阵,但是当通过脚本运行不同的数据时,行数是可变的。使用我要添加的相同数据。

编辑2:但是,脚本抛出错误。因此,我认为您的想法不能解释此处正在发生的问题。谢谢你 还有其他想法吗?


编辑3:

仅供参考,如果我替换此有问题的代码行:

    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]

与此相反:

    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray)[1:,3]

然后,脚本的该部分可以正常工作而不会引发错误,但是此代码行更进一步:

p.ylim(.5*RRDuringArray.min(),1.5*RRDuringArray.max())

引发此错误:

File "mypath\mypythonscript.py", line 3631, in CreateSummaryGraphics
  p.ylim(.5*RRDuringArray.min(),1.5*RRDuringArray.max())
TypeError: cannot perform reduce with flexible type

因此,您可以看到我需要指定数据类型以便能够在matplotlib中使用ylim,但是指定数据类型会引发引发此帖子的错误消息。

This Python code:

import numpy as p

def firstfunction():
    UnFilteredDuringExSummaryOfMeansArray = []
    MeanOutputHeader=['TestID','ConditionName','FilterType','RRMean','HRMean',
                      'dZdtMaxVoltageMean','BZMean','ZXMean','LVETMean','Z0Mean',
                      'StrokeVolumeMean','CardiacOutputMean','VelocityIndexMean']
    dataMatrix = BeatByBeatMatrixOfMatrices[column]
    roughTrimmedMatrix = p.array(dataMatrix[1:,1:17])


    trimmedMatrix = p.array(roughTrimmedMatrix,dtype=p.float64)  #ERROR THROWN HERE


    myMeans = p.mean(trimmedMatrix,axis=0,dtype=p.float64)
    conditionMeansArray = [TestID,testCondition,'UnfilteredBefore',myMeans[3], myMeans[4], 
                           myMeans[6], myMeans[9], myMeans[10], myMeans[11], myMeans[12],
                           myMeans[13], myMeans[14], myMeans[15]]
    UnFilteredDuringExSummaryOfMeansArray.append(conditionMeansArray)
    secondfunction(UnFilteredDuringExSummaryOfMeansArray)
    return

def secondfunction(UnFilteredDuringExSummaryOfMeansArray):
    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]
    return

firstfunction()

Throws this error message:

File "mypath\mypythonscript.py", line 3484, in secondfunction
RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]
ValueError: setting an array element with a sequence.

Can anyone show me what to do to fix the problem in the broken code above so that it stops throwing an error message?


EDIT: I did a print command to get the contents of the matrix, and this is what it printed out:

UnFilteredDuringExSummaryOfMeansArray is:

[['TestID', 'ConditionName', 'FilterType', 'RRMean', 'HRMean', 'dZdtMaxVoltageMean', 'BZMean', 'ZXMean', 'LVETMean', 'Z0Mean', 'StrokeVolumeMean', 'CardiacOutputMean', 'VelocityIndexMean'],
[u'HF101710', 'PreEx10SecondsBEFORE', 'UnfilteredBefore', 0.90670000000000006, 66.257731979420001, 1.8305673000000002, 0.11750000000000001, 0.15120546389880002, 0.26870546389879996, 27.628261216480002, 86.944190346160013, 5.767261352345999, 0.066259118585869997],
[u'HF101710', '25W10SecondsBEFORE', 'UnfilteredBefore', 0.68478571428571422, 87.727887206978565, 2.2965444125714285, 0.099642857142857144, 0.14952476549885715, 0.24916762264164286, 27.010483303721429, 103.5237336525, 9.0682762747642869, 0.085022572648242867],
[u'HF101710', '50W10SecondsBEFORE', 'UnfilteredBefore', 0.54188235294117659, 110.74841107829413, 2.6719262705882354, 0.077705882352917643, 0.15051306356552943, 0.2282189459185294, 26.768787504858825, 111.22827075238826, 12.329456404418824, 0.099814258468417641],
[u'HF101710', '75W10SecondsBEFORE', 'UnfilteredBefore', 0.4561904761904762, 131.52996981880955, 3.1818159523809522, 0.074714285714290493, 0.13459344175047619, 0.20930772746485715, 26.391156337028569, 123.27387909873812, 16.214243779323812, 0.1205685359981619]]

Looks like a 5 row by 13 column matrix to me, though the number of rows is variable when different data are run through the script. With this same data that I am adding in this.

EDIT 2: However, the script is throwing an error. So I do not think that your idea explains the problem that is happening here. Thank you, though. Any other ideas?


EDIT 3:

FYI, if I replace this problem line of code:

    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray,dtype=p.float64)[1:,3]

with this instead:

    RRDuringArray = p.array(UnFilteredDuringExSummaryOfMeansArray)[1:,3]

Then that section of the script works fine without throwing an error, but then this line of code further down the line:

p.ylim(.5*RRDuringArray.min(),1.5*RRDuringArray.max())

Throws this error:

File "mypath\mypythonscript.py", line 3631, in CreateSummaryGraphics
  p.ylim(.5*RRDuringArray.min(),1.5*RRDuringArray.max())
TypeError: cannot perform reduce with flexible type

So you can see that I need to specify the data type in order to be able to use ylim in matplotlib, but yet specifying the data type is throwing the error message that initiated this post.


回答 0

从您展示给我们的代码中,我们唯一可以看出的是您正在尝试从形状不像多维数组的列表中创建数组。例如

numpy.array([[1,2], [2, 3, 4]])

要么

numpy.array([[1,2], [2, [3, 4]]])

将产生此错误消息,因为输入列表的形状不是可以转换为多维数组的(通用)“框”。因此可能UnFilteredDuringExSummaryOfMeansArray包含不同长度的序列。

编辑:此错误消息的另一个可能原因是尝试将字符串用作类型数组中的元素float

numpy.array([1.2, "abc"], dtype=float)

那就是您根据编辑尝试的内容。如果您确实想拥有一个同时包含字符串和浮点数的NumPy数组,则可以使用dtype object,它使该数组可以容纳任意Python对象:

numpy.array([1.2, "abc"], dtype=object)

不知道您的代码将完成什么,我无法判断这是否是您想要的。

From the code you showed us, the only thing we can tell is that you are trying to create an array from a list that isn't shaped like a multi-dimensional array. For example

numpy.array([[1,2], [2, 3, 4]])

or

numpy.array([[1,2], [2, [3, 4]]])

will yield this error message, because the shape of the input list isn't a (generalised) "box" that can be turned into a multidimensional array. So probably UnFilteredDuringExSummaryOfMeansArray contains sequences of different lengths.

Edit: Another possible cause for this error message is trying to use a string as an element in an array of type float:

numpy.array([1.2, "abc"], dtype=float)

That is what you are trying according to your edit. If you really want to have a NumPy array containing both strings and floats, you could use the dtype object, which enables the array to hold arbitrary Python objects:

numpy.array([1.2, "abc"], dtype=object)

Without knowing what your code shall accomplish, I can't judge if this is what you want.


回答 1

Python ValueError:

ValueError: setting an array element with a sequence.

就是说的意思,您正在尝试将一系列数字填充到单个数字槽中。它可以在各种情况下抛出。

1.当您将python元组或列表传递为numpy数组元素时:

import numpy

numpy.array([1,2,3])               #good

numpy.array([1, (2,3)])            #Fail, can't convert a tuple into a numpy 
                                   #array element


numpy.mean([5,(6+7)])              #good

numpy.mean([5,tuple(range(2))])    #Fail, can't convert a tuple into a numpy 
                                   #array element


def foo():
    return 3
numpy.array([2, foo()])            #good


def foo():
    return [3,4]
numpy.array([2, foo()])            #Fail, can't convert a list into a numpy 
                                   #array element

2.通过尝试将长度大于1的numpy数组塞入numpy数组元素:

x = np.array([1,2,3])
x[0] = np.array([4])         #good



x = np.array([1,2,3])
x[0] = np.array([4,5])       #Fail, can't convert the numpy array to fit 
                             #into a numpy array element

正在创建一个numpy数组,并且numpy不知道如何将多值元组或数组填充到单个元素插槽中。它期望您给它提供的任何结果都可以求出单个数字,如果没有,Numpy会回答说它不知道如何设置带有序列的数组元素。

The Python ValueError:

ValueError: setting an array element with a sequence.

Means exactly what it says, you're trying to cram a sequence of numbers into a single number slot. It can be thrown under various circumstances.

1. When you pass a python tuple or list to be interpreted as a numpy array element:

import numpy

numpy.array([1,2,3])               #good

numpy.array([1, (2,3)])            #Fail, can't convert a tuple into a numpy 
                                   #array element


numpy.mean([5,(6+7)])              #good

numpy.mean([5,tuple(range(2))])    #Fail, can't convert a tuple into a numpy 
                                   #array element


def foo():
    return 3
numpy.array([2, foo()])            #good


def foo():
    return [3,4]
numpy.array([2, foo()])            #Fail, can't convert a list into a numpy 
                                   #array element

2. By trying to cram a numpy array length > 1 into a numpy array element:

x = np.array([1,2,3])
x[0] = np.array([4])         #good



x = np.array([1,2,3])
x[0] = np.array([4,5])       #Fail, can't convert the numpy array to fit 
                             #into a numpy array element

A numpy array is being created, and numpy doesn't know how to cram multivalued tuples or arrays into single element slots. It expects whatever you give it to evaluate to a single number, if it doesn't, Numpy responds that it doesn't know how to set an array element with a sequence.


回答 2

就我而言,我在Tensorflow中遇到此错误,原因是我试图输入具有不同长度或序列的数组:

例如:

import tensorflow as tf

input_x = tf.placeholder(tf.int32,[None,None])



word_embedding = tf.get_variable('embeddin',shape=[len(vocab_),110],dtype=tf.float32,initializer=tf.random_uniform_initializer(-0.01,0.01))

embedding_look=tf.nn.embedding_lookup(word_embedding,input_x)

with tf.Session() as tt:
    tt.run(tf.global_variables_initializer())

    a,b=tt.run([word_embedding,embedding_look],feed_dict={input_x:example_array})
    print(b)

如果我的数组是:

example_array = [[1,2,3],[1,2]]

然后我会得到错误:

ValueError: setting an array element with a sequence.

但是如果我做填充,那么:

example_array = [[1,2,3],[1,2,0]]

现在可以了。

In my case , I got this Error in Tensorflow , Reason was i was trying to feed a array with different length or sequences :

example :

import tensorflow as tf

input_x = tf.placeholder(tf.int32,[None,None])



word_embedding = tf.get_variable('embeddin',shape=[len(vocab_),110],dtype=tf.float32,initializer=tf.random_uniform_initializer(-0.01,0.01))

embedding_look=tf.nn.embedding_lookup(word_embedding,input_x)

with tf.Session() as tt:
    tt.run(tf.global_variables_initializer())

    a,b=tt.run([word_embedding,embedding_look],feed_dict={input_x:example_array})
    print(b)

And if my array is :

example_array = [[1,2,3],[1,2]]

Then i will get error :

ValueError: setting an array element with a sequence.

but if i do padding then :

example_array = [[1,2,3],[1,2,0]]

Now it's working.


回答 3

对于那些在Numpy中遇到类似问题的人,一个非常简单的解决方案是:

定义dtype=object限定的阵列用于向它分配值时。例如:

out = np.empty_like(lil_img, dtype=object)

for those who are having trouble with similar problems in Numpy, a very simple solution would be:

defining dtype=object when defining an array for assigning values to it. for instance:

out = np.empty_like(lil_img, dtype=object)

回答 4

就我而言,问题是另一个。我正在尝试将int列表转换为array。问题在于,一个列表的长度与其他列表不同。如果要证明这一点,则必须执行以下操作:

print([i for i,x in enumerate(list) if len(x) != 560])

在我的情况下,长度参考为560。

In my case, the problem was another. I was trying convert lists of lists of int to array. The problem was that there was one list with a different length than others. If you want to prove it, you must do:

print([i for i,x in enumerate(list) if len(x) != 560])

In my case, the length reference was 560.


回答 5

就我而言,问题在于数据帧X []的散点图:

ax.scatter(X[:,0],X[:,1],c=colors,    
       cmap=CMAP, edgecolor='k', s=40)  #c=y[:,0],

#ValueError: setting an array element with a sequence.
#Fix with .toarray():
colors = 'br'
y = label_binarize(y, classes=['Irrelevant','Relevant'])
ax.scatter(X[:,0].toarray(),X[:,1].toarray(),c=colors,   
       cmap=CMAP, edgecolor='k', s=40)

In my case, the problem was with a scatterplot of a dataframe X[]:

ax.scatter(X[:,0],X[:,1],c=colors,    
       cmap=CMAP, edgecolor='k', s=40)  #c=y[:,0],

#ValueError: setting an array element with a sequence.
#Fix with .toarray():
colors = 'br'
y = label_binarize(y, classes=['Irrelevant','Relevant'])
ax.scatter(X[:,0].toarray(),X[:,1].toarray(),c=colors,   
       cmap=CMAP, edgecolor='k', s=40)

回答 6

当形状不规则或元素具有不同的数据类型时,dtype传递给np.array 的参数只能为object

import numpy as np

# arr1 = np.array([[10, 20.], [30], [40]], dtype=np.float32)  # error
arr2 = np.array([[10, 20.], [30], [40]])  # OK, and the dtype is object
arr3 = np.array([[10, 20.], 'hello'])     # OK, and the dtype is also object

``

When the shape is not regular or the elements have different data types, the dtype argument passed to np.array only can be object.

import numpy as np

# arr1 = np.array([[10, 20.], [30], [40]], dtype=np.float32)  # error
arr2 = np.array([[10, 20.], [30], [40]])  # OK, and the dtype is object
arr3 = np.array([[10, 20.], 'hello'])     # OK, and the dtype is also object

``


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