NumPy: Create a three-dimension array, fill the array elements with values using unsigned integer (0 to 255)
NumPy: Random Exercise-17 with Solution
Write a NumPy program to create a three-dimension array with shape (300,400,5) and set to a variable. Fill the array elements with values using unsigned integer (0 to 255).
Sample Solution:
Python Code:
# Importing NumPy library and aliasing it as np
import numpy as np
# Setting the random seed to 32 for reproducibility
np.random.seed(32)
# Generating a 3D NumPy array 'nums' with dimensions 300x400x5
# Filling it with random integers in the range [0, 256) and data type uint8
nums = np.random.randint(low=0, high=256, size=(300, 400, 5), dtype=np.uint8)
# Printing the generated array 'nums'
print(nums)
Sample Output:
[[[215 42 224 219 43] [166 69 15 133 255] [105 95 54 37 201] ... [240 22 66 232 132] [ 13 85 53 220 170] [249 62 221 146 69]] [[ 73 79 148 132 164] [ 3 93 98 138 200] [174 34 31 208 130] ... [ 15 252 41 64 39] [188 216 223 124 27] [ 85 112 240 116 231]] [[227 50 243 20 171] [ 12 66 108 102 63] [107 54 0 0 173] ... [215 46 57 99 151] [243 199 31 28 179] [143 7 30 175 190]] ... [[214 64 64 212 62] [140 44 217 17 164] [226 146 247 53 199] ... [189 68 49 117 63] [ 14 17 109 82 92] [155 221 135 184 231]] [[132 194 160 136 102] [132 244 230 117 181] [146 245 21 164 29] ... [125 240 243 190 240] [137 41 157 117 155] [ 20 92 72 182 41]] [[120 45 198 218 190] [ 42 150 190 103 106] [164 71 220 114 59] ... [143 20 219 154 85] [219 190 170 227 246] [ 39 14 127 230 158]]]
Explanation:
In the above exercise –
np.random.seed(32): This line sets the random seed to 32, which ensures that the same sequence of random numbers is generated each time the code is run.
nums = np.random.randint(low=0, high=256, size=(300, 400, 5), dtype=np.uint8): This line generates a 3D array of random integers. The parameters are as follows:
- low=0: The lower bound (inclusive) for the random integers.
- high=256: The upper bound (exclusive) for the random integers.
- size=(300, 400, 5): The shape of the output array.
- dtype=np.uint8: The data type of the output array, which is an unsigned 8-bit integer. This means the integers can have values between 0 and 255 (inclusive).
print(nums): Finally print() function prints the generated 3D array of random unsigned 8-bit integers.
Python-Numpy Code Editor:
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