# numpy.expm1() in Python

numpy.expm1(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
This mathematical function helps user to calculate exponential of all the elements subtracting 1 from all the input array elements.

Parameters :

```array    : [array_like]Input array or object whose elements, we need to test.
out      : [ndarray, optional]Output array with same dimensions as Input array,
placed with result.
**kwargs : allows you to pass keyword variable length of argument to a function.
It is used when we want to handle named argument in a function.
where    : [array_like, optional]True value means to calculate the universal
functions(ufunc) at that position, False value means to leave the
value in the output alone.
```

Return :

```An array with exponential(all elements of input array) - 1.
```

Code 1 : Working

 `# Python program explaining ` `# expm1() function ` ` `  `import` `numpy as np ` ` `  `in_array ``=` `[``1``, ``3``, ``5``] ` `print` `(``"Input array : \n"``, in_array) ` ` `  `exp_values ``=` `np.exp(in_array) ` `print` `(``"\nExponential value of array element : "` `       ``"\n"``, exp_values) ` ` `  `expm1_values ``=` `np.expm1(in_array) ` `print` `(``"\n(Exponential value of array element) - (1) "` `       ``": \n"``, expm1_values) `

Output :

```Input array :
[1, 3, 5]

Exponential value of array element :
[   2.71828183   20.08553692  148.4131591 ]

(Exponential value of array element) - (1) :
[   1.71828183   19.08553692  147.4131591 ]
```

Code 2 : Graphical representation

 `# Python program showing ` `# Graphical representation of  ` `# expm1() function ` ` `  `import` `numpy as np ` `import` `matplotlib.pyplot as plt ` ` `  `in_array ``=` `[``1``, ``1.2``, ``1.4``, ``1.6``, ``1.8``, ``2``] ` `out_array ``=` `np.expm1(in_array) ` ` `  `print``(``"out_array : "``, out_array) ` ` `  `y ``=` `[``1``, ``1.2``, ``1.4``, ``1.6``, ``1.8``, ``2``] ` `plt.plot(in_array, y, color ``=` `'blue'``, marker ``=` `"*"``) ` ` `  `# red for numpy.expm1() ` `plt.plot(out_array, y, color ``=` `'red'``, marker ``=` `"o"``) ` `plt.title(``"numpy.expm1()"``) ` `plt.xlabel(``"X"``) ` `plt.ylabel(``"Y"``) ` `plt.show()   `

Output :
out_array : [ 1.71828183 2.32011692 3.05519997 3.95303242 5.04964746 6.3890561 ] My Personal Notes arrow_drop_up Aspire to Inspire before I expire

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