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2024/03/26 - Updating Demo python files
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‎advanced/PythonDemo_03_Numpy_module.py

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# This file provides demo for numpy module
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import numpy as np
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import random
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def initialisation_demo():
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# To create empty array
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arr = np.zeros(5, 'i')
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print("Empty arr: ", arr, " dtype:", arr.dtype, " dimension: ", arr.ndim)
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str_arr = np.zeros(5, "O")
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print("Empty string arr: ", str_arr, " dtype:", str_arr.dtype, " dimension: ", str_arr.ndim)
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arr = np.ones(5, 'i')
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print("Array with ones : ", arr, " dtype:", arr.dtype, " dimension: ", arr.ndim)
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str_arr = np.full(5, "Test", object)
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print("String arr with default values: ", str_arr, " dtype:", str_arr.dtype, " dimension: ", str_arr.ndim)
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zero_like_arr = np.zeros_like(arr)
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print("zero_like_arr: ", zero_like_arr, " dtype:",
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zero_like_arr.dtype, " dimension: ", zero_like_arr.ndim)
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one_like_arr = np.ones_like(str_arr, dtype='f', shape=2)
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print("one_like_arr: ", one_like_arr, " dtype:", one_like_arr.dtype,
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" dimension: ", one_like_arr.ndim)
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full_like_arr = np.full_like(one_like_arr, fill_value="Hi", dtype=object, shape=[1, 2])
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print("full_like_arr: ", full_like_arr, " dtype:", full_like_arr.dtype,
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" dimension: ", full_like_arr.ndim)
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def one_dimensional_array():
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num_list = random.sample(range(0, 100), 7)
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arr = np.array(num_list, 'i')
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print("Accessing elements using indexing of one dimensional array")
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for i in range(arr.size):
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print(f"arr[{i}]: {arr[i]}", end="\t")
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print("")
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print("Updating value at 2nd position to 39")
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arr[1] = 39
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print("Post updating value at 2nd position: ", arr)
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print("Updating values at more than one position using slicing "
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" i.e. position 6 and 7 ")
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arr[5:7] = 29
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print("Post updating value at 6th and 7th position: ", arr)
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print("Array from 2nd element till 7th element "
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"with skip = 2 "
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"using slicing: ", arr[1:6:2])
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print("To access array using negative indexing ", arr[-3:])
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print("To reverse array ", arr[::-1])
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def two_dimensional_arr():
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# empty array with zero values
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arr = np.zeros((2, 2), dtype='i')
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print("2-D array with zero values ", arr)
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# initialising array with values
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arr = np.array([[1, 2], [3, 4], [5, 6], [7, 8], [9, -1]], dtype='i')
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print("2-D array with initial values ", arr, " dimension: ", arr.ndim,
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" Data type: ", arr.dtype, " size of array: ", arr.size,
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"shape: ", arr.shape)
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# accessing elements using index
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print("element at 1st row and 2nd column: ", arr[1, 1])
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# updating value at particular position
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print("update value at 1st row and 2nd column to 9")
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arr[1, 1] = 9
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print("Array post updating element at 1st row and 2nd column")
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print(arr)
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# updating value at multiple position
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print("update value at 2nd row: 7")
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arr[2:3] = 7
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print("Array post updating element at 3rd row")
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print(arr)
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new_arr = arr[1:4:2]
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# get 2-D array from existing one
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print("Getting new 2-D array from existing one using"
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"slicing", new_arr, " shape: ", new_arr.shape)
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new_arr = arr[1:4:2, 0:1]
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# get 2-D array from existing one with one column
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print("Getting new 2-D array with one column "
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"from existing one using"
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"slicing", new_arr, " shape: ", new_arr.shape)
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# reverse 2-D array
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print("Reverse 2-D array ", arr[::-1])
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def copy_and_view_demo():
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arr = np.array([1, 2, 3, 4], dtype=int)
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print("Original arr : ", arr, " base: ", arr.base)
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arr1 = arr.copy()
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print("Copied arr : ", arr1, " base: ", arr1.base)
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arr2 = arr.view()
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print("Viewed arr : ", arr2, " base: ", arr2.base)
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print("updating element at 1st index "
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"in copied array with value 5 and"
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"view with value 7")
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arr1[1] = 5
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arr2[2] = 7
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print("post update")
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print(f"original array: {arr}")
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print(f"Copied array: {arr1}")
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print(f"view: {arr2}")
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def shapeDemo():
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arr = np.full((3, 2), 1, dtype='i')
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for i in arr:
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for j in i:
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print(j, end="\t")
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print("")
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def reShapeDemo():
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num_list = random.sample(range(1, 100), 7)
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arr = np.array(num_list, dtype='i')
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print(f"Input array before resize: {arr} with shape: {arr.shape} and base: {arr.base}")
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try:
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reshaped_arr = np.reshape(arr, newshape=(2, 4))
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except ValueError as v:
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print("Error received : ", v)
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print("Need to resize now input array !!!")
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arr = np.resize(arr, 8)
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print(f"Input array post resize: {arr} with shape: {arr.shape} and base: {arr.base}")
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reshaped_arr = np.reshape(arr, newshape=(2, 4))
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print(f"Reshaped array with new shape: {reshaped_arr.shape} and base: {reshaped_arr.base}")
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for i in reshaped_arr:
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for j in i:
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print(j, end="\t")
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print("")
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finally:
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print("-"*50)
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def reShapeDemo2():
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arr = np.array([[1, 2, 3], [4, 5, 6]], dtype='i')
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print(f"Input array before reshape: {arr} with shape: {arr.shape} and base: {arr.base}")
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arr1 = arr.flatten()
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arr2 = arr.ravel()
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print("Flatten existing array: ", arr1, " with base: ", arr1.base)
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print("ravel existing array: ", arr2, " with base: ", arr2.base)
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def itrDemo():
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arr = np.array([[1, 2, 3], [4, 5, 6]], dtype='i')
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for x in np.nditer(arr[::, :2], flags=['buffered'], op_dtypes='S'):
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print(x)
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def joinDemo():
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arr1 = np.array([1, 2, 3, 4, 5], dtype='i')
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arr2 = np.array([7, 8, 9, 10, 11], dtype='i')
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# using concatenate
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print(np.concatenate((arr1, arr2)))
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# using stack
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print(np.stack((arr1, arr2), axis=1))
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# using hstack
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print(np.hstack((arr1, arr2)))
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# using vstack
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print(np.vstack((arr1, arr2)))
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def main():
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print("Version of numpy", np.__version__)
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reShapeDemo()
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if __name__ == "__main__":
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main()

‎advanced/PythonDemo_04_Random_module.py

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from numpy import random
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import numpy as np
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def generateRandomNumbers():
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print("Random int: ", random.randint(0, 10))
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print("Random float between 0 and 1: ", random.rand())
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print("Random float between 10 and 20: ", random.uniform(10, 20))
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print("-" * 25)
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def generateRandomArrays():
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print("One Dimensional array")
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print("Random int array: ", random.randint(low=5, high=12, size=5))
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print("Random float array: ", random.rand(3))
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print("Random float array of 5 elements between 10 and 20: ", random.uniform(10, 20, 5))
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print("-" * 25)
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def generateRandomArrays2():
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print("Two Dimensional array")
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print("Random int array: ", random.randint(low=5, high=12, size=(2, 3)))
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print("Random float array: ", random.rand(3, 2))
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print("Random float array of 5 elements between 10 and 20: ", random.uniform(10, 20, (2, 2)))
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print("-" * 25)
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def generateRandomArraysWithChoice():
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print("generateRandomArraysWithChoice")
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print("Random int array with choice : ", random.choice([10, 20, 30, 40, 11], 3))
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print("Random int array with choice and probability: ", random.choice([10, 20, 30], 6, p=[0.25, 0.45, 0.30]))
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print("Random float array with choice : ", random.choice([10.5, 12.0, 11.25, 31.5], 3))
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print("-" * 25)
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def shuffle_and_permutation_demo():
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arr = np.array([1, 2, 3, 4, 5])
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print("Array before shuffling: ", arr)
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random.shuffle(arr)
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print("Array post shuffling: ", arr)
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arr = np.array([6, 7, 8, 9])
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print("Input Array before permutation: ", arr)
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permutation_arr = random.permutation(arr)
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print("Input Array post permutation: ", arr)
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print("Permutation Array post permutation: ", permutation_arr)
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print("-" * 25)
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def main():
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print("Version of numpy", np.__version__)
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generateRandomNumbers()
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generateRandomArrays()
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generateRandomArrays2()
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generateRandomArraysWithChoice()
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shuffle_and_permutation_demo()
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if __name__ == "__main__":
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main()

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