The numpy.ceil() is a mathematical function that returns the ceil of the elements of array. The ceil of the scalar x is the smallest integer i, such that i >= x
Syntax : numpy.ceil(x[, out]) = ufunc ‘ceil’)
Parameters :
a : [array_like] Input arrayReturn : The ceil of each element with float data-type.
Code #1 : Working
# Python program explaining# ceil() functionimport numpy as np in_array = [.5, 1.5, 2.5, 3.5, 4.5, 10.1]print ("Input array : \n", in_array) ceiloff_values = np.ceil(in_array)print ("\nRounded values : \n", ceiloff_values) in_array = [.53, 1.54, .71]print ("\nInput array : \n", in_array) ceiloff_values = np.ceil(in_array)print ("\nRounded values : \n", ceiloff_values) in_array = [.5538, 1.33354, .71445]print ("\nInput array : \n", in_array) ceiloff_values = np.ceil(in_array)print ("\nRounded values : \n", ceiloff_values) |
Output :
Input array : [0.5, 1.5, 2.5, 3.5, 4.5, 10.1] Rounded values : [ 1. 2. 3. 4. 5. 11.] Input array : [0.53, 1.54, 0.71] Rounded values : [ 1. 2. 1.] Input array : [0.5538, 1.33354, 0.71445] Rounded values : [ 1. 2. 1.]
Code #2 : Working
# Python program explaining# ceil() functionimport numpy as np in_array = [1.67, 4.5, 7, 9, 12]print ("Input array : \n", in_array) ceiloff_values = np.ceil(in_array)print ("\nRounded values : \n", ceiloff_values) in_array = [133.000, 344.54, 437.56, 44.9, 1.2]print ("\nInput array : \n", in_array) ceiloff_values = np.ceil(in_array)print ("\nRounded values upto 2: \n", ceiloff_values) |
Output :
Input array : [1.67, 4.5, 7, 9, 12] Rounded values : [ 2. 5. 7. 9. 12.] Input array : [133.0, 344.54, 437.56, 44.9, 1.2] Rounded values upto 2: [ 133. 345. 438. 45. 2.]
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.ceil.html#numpy.ceil
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