生成具有重复率的 numpy 数组

Question

这是我的问题：我必须生成一些合成数据（如 7/8 列），相互关联（使用皮尔逊系数）。我可以很容易地做到这一点，但接下来我必须在每列中插入一定比例的重复项（是的，皮尔逊系数会更低），每列都不同。问题是我不想亲自插入重复的内容，因为在我的情况下它就像作弊。有人知道如何生成已经重复的相关数据吗？我已经搜索过，但通常问题是关于删除或避免重复..语言：python3 要生成相关数据，我使用了这个简单的代码：生成相关数据

Answer 1

尝试这样的事情：

indices = np.random.randint(0, array.shape[0], size = int(np.ceil(percentage * array.shape[0])))

for index in indices:

  array.append(array[index])

在这里，我假设您的数据存储在array一个 ndarray 中，其中每行包含您的 7/8 列数据。上面的代码应该创建一个随机索引数组，您选择其条目（行）并再次附加到数组中。

Answer 2

我找到了解决办法。我发布了代码，它可能对某人有帮助。

#this are the data, generated randomically with a given shape

rnd = np.random.random(size=(10**7, 8))

#that array represent a column of the covariance matrix (i want correlated data, so i randomically choose a number between 0.8 and 0.95)

#I added other 7 columns, with varing range of values (all upper than 0.7)

attr1 = np.random.uniform(0.8, .95, size = (8,1))

#attr2,3,4,5,6,7 like attr1

#corr_mat is the matrix, union of columns

corr_mat = np.column_stack((attr1,attr2,attr3,attr4,attr5, attr6,attr7,attr8))

from statsmodels.stats.correlation_tools import cov_nearest

#using that function i found the nearest covariance matrix to my matrix,

#to be sure that it's positive definite

a = cov_nearest(corr_mat)

from scipy.linalg import cholesky

upper_chol = cholesky(a)

# Finally, compute the inner product of upper_chol and rnd

ans = rnd @ upper_chol

#ans now has randomically correlated data (high correlation, but is customizable)

#next i create a pandas Dataframe with ans values

df = pd.DataFrame(ans, columns=['att1', 'att2', 'att3', 'att4', 

                            'att5', 'att6', 'att7', 'att8'])

#last step is to truncate float values of ans in a variable way, so i got 

#duplicates in varying percentage

a = df.values

for i in range(8):

     trunc = np.random.randint(5,12)

     print(trunc)

     a.T[i] = a.T[i].round(decimals=trunc)

#float values of ans have 16 decimals, so i randomically choose an int

# between 5 and 12 and i use it to truncate each value

最后，这些是我每列的重复百分比：

duplicate rate attribute: att1 = 5.159390000000002

duplicate rate attribute: att2 = 11.852260000000001

duplicate rate attribute: att3 = 12.036079999999998

duplicate rate attribute: att4 = 35.10611

duplicate rate attribute: att5 = 4.6471599999999995

duplicate rate attribute: att6 = 35.46553

duplicate rate attribute: att7 = 0.49115000000000464

duplicate rate attribute: att8 = 37.33252