小编use*_*704的帖子

代码:

import numpy
from matplotlib.mlab import PCA
file_name = "store1_pca_matrix.txt"
ori_data = numpy.loadtxt(file_name,dtype='float', comments='#', delimiter=None,                 converters=None, skiprows=0, usecols=None, unpack=False, ndmin=0)
result = PCA(ori_data)

这是我的代码.虽然我的输入矩阵没有nan和inf,但我确实得到了下面所述的错误.

raise LinAlgError("SVD did not converge") LinAlgError: SVD did not converge

有什么问题？

这是我为Kosaraju算法做的代码的第一部分.

###### reading the data #####
with open('data.txt') as req_file:
        ori_data = []
        for line in req_file:
            line = line.split()
            if line:
                line = [int(i) for i in line]
                ori_data.append(line)

###### forming the Grev ####
revscc_dic = {}
for temp in ori_data:
    if temp[1] not in revscc_dic:
        revscc_dic[temp[1]] = [temp[0]]
    else:
        revscc_dic[temp[1]].append(temp[0])

print revscc_dic        

######## finding the G#####
scc_dic = {}
for temp in ori_data:
    if temp[0] not in scc_dic:
        scc_dic[temp[0]] = [temp[1]]
    else:
        scc_dic[temp[0]].append(temp[1])

print scc_dic        

##### iterative dfs …

这是我的karger min cut算法的代码.据我所知,我实现的算法是正确的.但我没有得到正确答案.如果有人可以检查出了什么问题,我将不胜感激.

import random
from random import randint

#loading data from the text file#
with open('data.txt') as req_file:
    mincut_data = []
    for line in req_file:
        line = line.split()
        if line:
            line = [int(i) for i in line]
            mincut_data.append(line)

#extracting edges from the data #            
edgelist = []
nodelist = []
for every_list in mincut_data:
    nodelist.append(every_list[0])
    temp_list = []
    for temp in range(1,len(every_list)):
        temp_list = [every_list[0], every_list[temp]]
        flag = 0
        for ad in edgelist:
            if set(ad) == set(temp_list):
                flag = …

这是合并排序的代码..代码工作得很好,并对数字进行排序.但是,如果我们要更大的数据必须进行排序,那么就会出现问题.要排序的数据包含不重复的数字.但是在排序之后,有一些数字会重复多次.我不明白为什么会这样......当我给出100000个数字的数据集时会发生这种情况.当要对较小的数据进行排序时,代码非常有效.

def mergeSort(alist):
    if len(alist)>1:
        mid = len(alist)/2
        lefthalf = alist[:mid]
        righthalf = alist[mid:]

        mergeSort(lefthalf)
        mergeSort(righthalf)

        i=0
        j=0
        k=0
        while i<len(lefthalf) and j<len(righthalf):
            if lefthalf[i]<righthalf[j]:
                alist[k]=lefthalf[i]
                i=i+1
            else:
                alist[k]=righthalf[j]
                j=j+1
            k=k+1

        while i<len(lefthalf):
            alist[k]=lefthalf[i]
            i=i+1
            k=k+1

        while j<len(righthalf):
            alist[k]=righthalf[j]
            j=j+1
            k=k+1


print("select the file: ")
file_name =  tkFileDialog.askopenfile(mode='r', title='Select word list file')
inv_data = np.loadtxt(file_name,dtype='float', comments='#', delimiter=None, converters=None, skiprows=0, usecols=None,
                unpack=False, ndmin=0)
mergeSort(inv_data)
print("sorted list :", inv_data)

数据集位于以下链接 http://spark-public.s3.amazonaws.com/algo1/programming_prob/IntegerArray.txt

我想使用 ARIMAResults 类进行 ARIMA 建模。任何人都可以引用普通 ARIMA 类和 ARIMAResults 类之间的区别吗？另外，有人可以通过举个例子来帮助我做 ARIMAResults 吗？我有一组数据，必须拟合 ARIMA 模型并预测值。