# sciPy stats.signaltonoise() function | Python

scipy.stats.signaltonoise(arr, axis=0, ddof=0) function computes the signal-to-noise ratio of the input data.

Its formula :

Parameters :
arr : [array_like]Input array or object having the elements to calculate the signal-to-noise ratio
axis : Axis along which the mean is to be computed. By default axis = 0.
ddof : Degree of freedom correction for Standard Deviation.

Results : mean to standard deviation ratio i.e. signal-to-noise ratio.

Code #1: Working

 `# stats.signaltonoise() method  ` `import` `numpy as np ` `from` `scipy ``import` `stats ` `  `  `  `  `arr1 ``=` `[[``20``, ``2``, ``7``, ``1``, ``34``], ` `        ``[``50``, ``12``, ``12``, ``34``, ``4``]] ` ` `  `arr2 ``=` `[``50``, ``12``, ``12``, ``34``, ``4``] ` ` `  `print` `(``"\narr1 : "``, arr1) ` `print` `(``"\narr2 : "``, arr2) ` ` `  `print` `(``"\nsignaltonoise ratio for arr1 : "``,  ` `       ``stats.signaltonoise(arr1, axis ``=` `0``, ddof ``=` `0``)) ` ` `  `print` `(``"\nsignaltonoise ratio for arr1 : "``,  ` `       ``stats.signaltonoise(arr1, axis ``=` `1``, ddof ``=` `0``)) ` ` `  `print` `(``"\nsignaltonoise ratio for arr1 : "``,  ` `       ``stats.signaltonoise(arr2, axis ``=` `0``, ddof ``=` `0``))  `

Output :

arr1 : [[20, 2, 7, 1, 34], [50, 12, 12, 34, 4]]

arr2 : [50, 12, 12, 34, 4]

signaltonoise ratio for arr1 : [2.33333333 1.4 3.8 1.06060606 1.26666667]

signaltonoise ratio for arr1 : [1.01779811 1.31482934]

signaltonoise ratio for arr2 : 1.3148293369202024

Code #2 : How to implement

 `def` `signaltonoise(a, axis, ddof): ` `    ``a ``=` `np.asanyarray(a) ` `    ``m ``=` `a.mean(axis) ` `    ``sd ``=` `a.std(axis ``=` `axis, ddof ``=` `ddof) ` `    ``return` `np.where(sd ``=``=` `0``, ``0``, m ``/` `sd) ` ` `  `print` `(``"\nsignaltonoise ratio for arr1 : "``,  ` `       ``signaltonoise(arr1, axis ``=` `0``, ddof ``=` `0``)) ` ` `  `print` `(``"\nsignaltonoise ratio for arr1 : "``,  ` `       ``signaltonoise(arr1, axis ``=` `1``, ddof ``=` `0``)) ` ` `  `print` `(``"\nsignaltonoise ratio for arr2 : "``,  ` `       ``signaltonoise(arr2, axis ``=` `0``, ddof ``=` `0``)) `

Output :

signaltonoise ratio for arr1 : [2.33333333 1.4 3.8 1.06060606 1.26666667]

signaltonoise ratio for arr1 : [1.01779811 1.31482934]

signaltonoise ratio for arr2 : 1.3148293369202024

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