Grokking Modern System Design Interview for Engineers & Managers
Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.
Python’s numpy.isfinite()
tests if an element is finite or not. It tests an array element-wise and returns a Boolean array as the output.
numpy.isfinite()
is declared as follows:
numpy.isfinite(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) = <ufunc 'isfinite'>
In the syntax above, x
is the non-optional parameter and the rest are optional parameters.
A universal function (ufunc) is a function that operates on ndarrays in an element-by-element fashion. The
isfinite()
method is a universal function.
The numpy.isfinite()
method takes the following compulsory parameter:
x
[array-like] - input array.The numpy.isfinite()
method takes the following optional parameters:
Parameter | Description |
out | represents the location into which the output of the method is stored. |
where | True value indicates that a universal function should be calculated at this position. |
casting | controls the type of datacasting that should occur. The same_kind option indicates that safe casting or casting within the same kind should take place. |
order | controls the memory layout order of the output function. The option K means reading the elements in the order they occur in memory. |
dtype | represents the desired data type of the array. |
subok |
numpy.isfinite()
returns Boolean values True
or False
depending on the following:
It returns False
if x
is positive infinity, negative infinity or NaN.
It returns True
in all other cases.
If x
is scalar, the return type is also scalar.
The example below shows the use of numpy.isfinite()
on the elements a
and b
:
import numpy as npa = 23b = np.nanprint (np.isfinite(a))print (np.isfinite(b))
The following example shows the use of numpy.isfinite()
on the array arr1
:
import numpy as nparr1 = np.array([2, np.inf, 0, 10000000000000])print (np.isfinite(arr1))
The following example shows the use of numpy.isfinite()
on the array arr2
:
import numpy as nparr2 = np.array([[1, 2, 3], [np.inf, np.nan, -np.inf]])print (np.isfinite(arr2))
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Grokking Modern System Design Interview for Engineers & Managers
Ace your System Design Interview and take your career to the next level. Learn to handle the design of applications like Netflix, Quora, Facebook, Uber, and many more in a 45-min interview. Learn the RESHADED framework for architecting web-scale applications by determining requirements, constraints, and assumptions before diving into a step-by-step design process.