在python中生成列表时出错
我正在尝试用python构建一个列表。该列表包含列表。单个内部列表由音频信号的各种特征组成，如标准偏差、平均频率等。但当我打印外部列表时，会得到一个空白列表。这是我的密码在python中生成列表时出错,python,list,numpy,nested-lists,Python,List,Numpy,Nested Lists,我正在尝试用python构建一个列表。该列表包含列表。单个内部列表由音频信号的各种特征组成，如标准偏差、平均频率等。但当我打印外部列表时，会得到一个空白列表。这是我的密码 from scipy.io.wavfile import read # to read wavfiles import matplotlib.pyplot as plotter from sklearn.tree import DecisionTreeClassifier as dtc import numpy as np
from scipy.io.wavfile import read # to read wavfiles
import matplotlib.pyplot as plotter
from sklearn.tree import DecisionTreeClassifier as dtc
import numpy as np
import os
import scipy
import math
np.set_printoptions(precision=4)
def __init__(self, criterion="gini", splitter="best", max_depth=None, min_samples_split=10, min_samples_leaf=1, min_weight_fraction_leaf=0, max_features=None, random_state=None, max_leaf_nodes=None, min_impurity_split=1e-7, class_weight=None, presort=False):
super(DecisionTreeClassifier, self).__init__(criterion=criterion, splitter=splitter, max_depth=max_depth, min_samples_split=min_samples_split, min_samples_leaf=min_samples_leaf, min_weight_fraction_leaf=min_weight_fraction_leaf, max_features=max_features, max_leaf_nodes=max_leaf_nodes, class_weight=class_weight, random_state=random_state, min_impurity_split=min_impurity_split, presort=presort)
fList = [] #feature list
mfList = [] #main feature list
labels = ["angry", "angry", "angry", "angry", "angry", "angry", "fear", "fear", "happy", "happy", "happy", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad", "sad"]
label = [1,2,3,4,5,6,7,8,9,10]
def stddev(lst,mf):
sum1 = 0
len1 = len(lst)-1
for i in range(len(lst)):
sum1 += pow((lst[i]-mf),2)
sd = np.sqrt(sum1/len1)
fList.append(sd)
def find_iqr(num,num_array=[],*args):
num_array.sort()
l=int((int(num)+1)/4)
m=int((int(num)+1)/2)
med=num_array[m]
u=int(3*(int(num)+1)/4)
fList.append(num_array[l]) #first quantile
fList.append(med) #median
fList.append(num_array[u]) #third quantile
fList.append(num_array[u]-num_array[l]) #inter quantile range
def build(path1):
dirlist=os.listdir(path1)
n=1
mf=0
for name in dirlist:
path=path1+name
print ("File ",n)
fs, x = read(path) #fs will have sampling rate and x will have sample #
#print ("The sampling rate: ",fs)
#print ("Size: ",x.size)
#print ("Duration: ",x.size/float(fs),"s")
'''
plotter.plot(x)
plotter.show() #x-axis is in samples
t = np.arange(x.size)/float(fs) #creating an array with values as time w.r.t samples
plotter.plot(t) #plot t w.r.t x
plotter.show()
y = x[100:600]
plotter.plot(y)
plotter.show() # showing close-up of samples
'''
j=0
med=0
for i in x:
j=j+1
mf=mf+i
mf=mf/j
fList.append(np.max(abs(x))) #amplitude
fList.append(mf) #mean frequency
find_iqr(j,x)
fList.append((3*med)-(2*mf)) #mode
stddev(x,mf)
#fftc = np.fft.rfft(x).tolist()
#mr = 20*scipy.log10(scipy.absolute(x)).tolist()
#fList.append(fftc) #1D dft
#fList.append(mr) #magnitude response
mfList.append(fList)
fList[:] = []
n=n+1
path1 = '/home/vishnu/Desktop/Trainingsamples/'
path2 = '/home/vishnu/Desktop/TestSamples/'
clf = dtc() # this class is used to make decision tree
build(path1)
print(mfList)
clf.fit(mfList,label)
mfList[:] = [] #clear mflist
tlist = build(path2)
res = clf.predict(tlist)
print(res)
('File ', 1)
SA1.py:50: RuntimeWarning: invalid value encountered in sqrt
sd = np.sqrt(sum1/len1)
('File ', 2)
('File ', 3)
('File ', 4)
('File ', 5)
('File ', 6)
('File ', 7)
('File ', 8)
('File ', 9)
('File ', 10)
[[], [], [], [], [], [], [], [], [], []]
Traceback (most recent call last):
File "SA1.py", line 111, in <module>
clf.fit(mfList,label)
File "/home/vishnu/.local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 739, in fit
X_idx_sorted=X_idx_sorted)
File "/home/vishnu/.local/lib/python2.7/site-packages/sklearn/tree/tree.py", line 122, in fit
X = check_array(X, dtype=DTYPE, accept_sparse="csc")
File "/home/vishnu/.local/lib/python2.7/site-packages/sklearn/utils/validation.py", line 424, in check_array
context))
ValueError: Found array with 0 feature(s) (shape=(10, 0)) while a minimum of 1 is required.
（'File'，1）
SA1.py:50:RuntimeWarning:在sqrt中遇到无效值
sd=np.sqrt（sum1/len1）
（“文件”，2）
（'File'，3）
（'File'，4）
（“文件”，5）
（“文件”，6）
（'File'，7）
（'File'，8）
（'File'，9）
（‘文件’，10）
[[], [], [], [], [], [], [], [], [], []]
回溯（最近一次呼叫最后一次）：
文件“SA1.py”，第111行，在
clf.fit（制造商列表、标签）
文件“/home/vishnu/.local/lib/python2.7/site-packages/sklearn/tree/tree.py”，第739行，适合
X_idx_排序=X_idx_排序）
文件“/home/vishnu/.local/lib/python2.7/site-packages/sklearn/tree/tree.py”，第122行，适合
X=检查数组（X，dtype=dtype，accept\u sparse=“csc”）
check_数组中的文件“/home/vishnu/.local/lib/python2.7/site packages/sklearn/utils/validation.py”，第424行
上下文）
ValueError:找到具有0个功能（形状=（10，0））的数组，但至少需要1个。
在这里可以看到，行
print（mfList）[]、[]、[]、[]、[]、[]、[]、[]、[]、[]、[]、[]、[]、[]、[]fList[：]=[]l = []
ml = []
def f(x):
for i in range(0, x):
l.append(i)
ml.append(l)
l[:] = []
f(10)
f(5)
print(ml)
ml>>> [[], []]
l[：]=[]l=[]ml>>> [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4]]
fList[：]=[]fListfListmfListfListfList[]mfListfList[:]=[]l = []
ml = []
def f(x):
for i in range(0, x):
l.append(i)
ml.append(l)
l[:] = []
f(10)
f(5)
print(ml)
ml>>> [[], []]
l[：]=[]l=[]ml>>> [[0, 1, 2, 3, 4, 5, 6, 7, 8, 9], [0, 1, 2, 3, 4]]
fList[：]=[]fListfListmfListfListfList[]mfListfList[:] = []
fList = []
你在103行有个错误
fList[:] = []
fList = []
请根据这些准则修改代码，嗯，我删除了我的答案，因为我不确定它是否正确。在调用循环之前，是否可以检查
dirlistfList[：]=[]dirlistfList[：]=[]