Python Scipy：scipy.stats.spearmanr返回nans [英] Python Scipy: scipy.stats.spearmanr returning nans

问题描述

编辑：我认为基本可以解决。

Basically solved I think.

我正在使用scipy.stats中的spearmanr来查找多个不同样本中变量之间的相关性。我大约有2500个变量和36个样本（或观察值）

I am using spearmanr from scipy.stats to find the correlations between variables across a number of different samples. I have around 2500 variables and 36 samples (or 'observations')

如果我使用全部36个样本计算相关性，则spearmanr可以正常工作。如果仅使用前18个样本，它也可以正常工作。但是，如果使用后18个样本，则会出错并返回nans。

If I calculate the correlations using all 36 samples, spearmanr works fine. If I use only the first 18 samples it also works fine. However if I use the latter 18 samples I get an error and nans are returned.

这是错误：

/Home/s1215235/.local/lib/python2.7/site-packages/numpy/lib/function_base.py:1945: RuntimeWarning: invalid value encountered in true_divide
return c / sqrt(multiply.outer(d, d))
/Home/s1215235/.local/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1718: RuntimeWarning: invalid value encountered in greater
cond1 = (scale > 0) & (x > self.a) & (x < self.b)
/Home/s1215235/.local/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1718: RuntimeWarning: invalid value encountered in less
cond1 = (scale > 0) & (x > self.a) & (x < self.b)
/Home/s1215235/.local/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1719: RuntimeWarning: invalid value encountered in less_equal
cond2 = cond0 & (x <= self.a)

这是代码：

populationdata = np.vstack(thing).astype(np.float)
rho, pval = stats.spearmanr(populationdata[:,sampleindexes], axis = 1)

（populationdata是一个充满浮点的numpy数组； [:, sampleindexes]允许

(populationdata is a numpy array full of floats; [:,sampleindexes] allows only a few of the columns to be used.

这就是rho返回的形式：

And this is what rho is returned as:

[[ 1.                 nan         nan ...,  1.         -0.05882353
  -0.08574929]
 [        nan         nan         nan ...,         nan         nan
          nan]
 [        nan         nan         nan ...,         nan         nan
          nan]
 ..., 
 [ 1.                 nan         nan ...,  1.         -0.05882353
  -0.08574929]
 [-0.05882353         nan         nan ..., -0.05882353  1.          0.68599434]
 [-0.08574929         nan         nan ..., -0.08574929  0.68599434  1.        ]]

推荐答案

在评论中指出，因此很多$ 0。 因此， populationdata [：，sampleindexes] 可能具有全为0的行。这将导致 spearmanr 生成 nan 。例如，

In a comment it was noted that "There are a lot of 0s though." So populationdata[:,sampleindexes] probably has rows that are all 0. That will cause spearmanr to generate nan. For example,

In [3]: spearmanr([[0, 0, 0], [1, 2, 3]], axis=1)
/Users/warren/anaconda/lib/python2.7/site-packages/numpy/lib/function_base.py:1957: RuntimeWarning: invalid value encountered in true_divide
  return c / sqrt(multiply.outer(d, d))
/Users/warren/anaconda/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1728: RuntimeWarning: invalid value encountered in greater
  cond1 = (scale > 0) & (x > self.a) & (x < self.b)
/Users/warren/anaconda/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1728: RuntimeWarning: invalid value encountered in less
  cond1 = (scale > 0) & (x > self.a) & (x < self.b)
/Users/warren/anaconda/lib/python2.7/site-packages/scipy/stats/_distn_infrastructure.py:1729: RuntimeWarning: invalid value encountered in less_equal
  cond2 = cond0 & (x <= self.a)
Out[3]: (nan, nan)

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