What is numpy.clip()?
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As programmers, we have to be familiar with arrays and lists as best as we can. Knowing basic methods to manipulate arrays/lists according to our needs is one of the fundamentals of Computer Programming.
In this article, we will look at a clip()`, which helps us to create a subarray containing elements according to our parameters.
The clip() function is used to clip (limit) the values of an array between two numbers. The out-of-range values are swapped out for those by the minimum values that are specified in the argument.
Syntax
The syntax for clip() function is:
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Parameters
The clip() function takes in these parameters:
- arr: This mandatory parameter represents the array that is to be clipped.
- arr_min: This mandatory parameter represents the starting limit for clipping the input array.
- arr_max: The maximum values that are to be clipped from the array.
- out: This represents the location where the resultant array is stored.
Return Type
When we use the clip() function in Python, a resultant array is generated, which follows the constraints added while defining the function clip().
Output
As we can see, the resultant array contains only elements between our minimum and maximum values (between 2 and 7).
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Examples
To further solidify our knowledge of the clip() function, we will look into some code examples:
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Using np.arrange() function to generate an array
The arrange() function in NumPy is used to generate an array from 0 to the number specified as its parameter.
Output
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Applying numpy.clip() on user-defined arrays
In this example, we will create our array, and use the clip() function on it.
Output
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The Lower Limit of NumPy Clip is an Array
As we have used an integer to specify the upper and the lower limit, we will use an array as the lower limit.
Output
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The Upper Limit of numpy.clip() is an Array
As we have used an integer to specify the upper and the lower limit, we will use an array as the upper limit.
Output
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Lower and Upper Limit of numpy.clip() are Arrays
In this example, we will use independent arrays as our upper and lower limits.
Output
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The Shape of the Input Array and the Shape of the Upper and Lower Limit are Different
If the shape of the input array is different than the shape of the upper or lower limit of the clip() function, we will get a value error
Output
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NumPy Clip for 2D Arrays
You may use Numpy Clip on an N-dimensional array as well. Clipping can assist you in getting rid of junk data, especially for 2D arrays that are useful for storing picture pixel values.
Output
Conclusion
- In this article, we learned about the clip(); a function that allows us to limit the elements of an array.
- To understand the working of the clip() function, we demonstrated various scenarios in which we use the clip() function to limit arrays.
- One of the scenarios is when we want to clip out a certain section of a two-dimensional array. With the help of the clip() function, we are easily able to achieve that.