jlconlin - 1 year ago 181

Python Question

I need to calculate the chi-squared fit to a set of arrays (

`observed`

`expected`

`expected`

`None`

I would like to use the

`scipy.stats.chisquare`

`None`

`TypeError: unsupported operand type(s) for -: 'float' and 'NoneType'`

I've tried to get around this by only including the data that is not

`None`

`import numpy.ma`

import scipy.stats

expected = [None, 2,3,4]

observed = [1,2.2,3.3,4.4]

expMasked = numpy.ma.masked_where(expected == None, expected)

obsMasked = numpy.ma.masked_where(expected == None, observed)

chi2 = scipy.stats.chisquare(obsMasked, f_exp=expMasked)

This just give me the same error.

`scipy.stats.chisquare`

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Answer Source

While it seems logical that `numpy.ma.masked_where(expected == None, expected)`

would in fact mask `expected`

where `None`

occurs, `numpy.ma`

does not recognize `None`

as comparable to `expected`

, so `None`

must be cast to an `np.array`

. Your code will work like this

```
import numpy as np
import scipy.stats
expected = [None, 2,3,4]
observed = [1,2.2,3.3,4.4]
expMasked = np.ma.masked_where(expected == np.array(None), expected)
obsMasked = np.ma.masked_where(observed == np.array(None), observed)
expMasked[expMasked.mask] = (VALUE YOU WANT MASKED VALUES TO BE REPLACED WITH)
obsMasked[obsMasked.mask] = (VALUE YOU WANT MASKED VALUES TO BE REPLACED WITH)
chi2 = scipy.stats.chisquare(np.array(obsMasked), f_exp=np.array(expMasked))
```

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