Add scientific package: Numpy

Author: DevOpsThinh

.idea/FromCodingToDeepLearning.iml

@@ -0,0 +1,77 @@
+# Author: Nguyen Truong Thinh
+# Contact me: nguyentruongthinhvn2020@gmail.com || +84393280504
+#
+# Package & libraries for scientific computing section
+from matplotlib import pyplot as plt
+
+import numpy as np
+
+# Mathematical functions
+print(np.log(32))
+print(np.exp(3))
+print(np.sin(2))
+print(np.cos(2))
+
+# Numpy arrays: Single dimensional
+my_arr = np.array([0, 1, 3, 4, 5])
+print(my_arr)
+
+my_arr = np.array(range(0, 10))
+print(my_arr)
+
+my_arr = np.linspace(1.1, 4.8, num=6)
+print(my_arr)
+print("\nmy array type is: ", type(my_arr))
+print("\nThe first element is: ", my_arr[0])
+
+my_arr[0] = 1.0
+print("\nThe first element is now: ", my_arr[0])
+
+my_arr[0:4] = 99
+print('\nThe my array is now:', my_arr)
+print('\nThe max of my array is: ', my_arr.max())
+print('\nThe min of my array is: ', my_arr.min())
+print('The mean of my array is: ', my_arr.mean())
+# Numpy arrays: Multi-dimensional
+_2d_matrix = np.array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9]])
+print(_2d_matrix)
+print('\nThe matrix dimensions are: ', _2d_matrix.shape)
+print('\nElement in first row, third column is: ', _2d_matrix[0, 2])
+print('\nElement in second row, fifth column is: ', _2d_matrix[1, 4])
+
+rs_2d_matrix = _2d_matrix.reshape(5, 2)
+print('\nReshaped matrix is: \n', rs_2d_matrix)
+trans_2d_matrix = _2d_matrix.transpose()
+print('\nTransposed matrix is: \n', trans_2d_matrix)
+into_lines = _2d_matrix.ravel()
+print('\nUnraveled matrix is: \n', into_lines)
+
+array_zeros = np.zeros((3, 5))
+print('\n', array_zeros)
+array_ones = np.ones((8, 9))
+print('\n', array_ones)
+array_pi = np.full((3, 7), 3.14159)
+print('\n', array_pi)
+
+_3d_matrix = np.ones((3, 5, 3))
+print('\n 3D matrix: \n', _3d_matrix)
+
+array_ones[2:6, 2:] = 8.95
+print('My large matrix of ones is now: \n', array_ones)
+
+arr_1 = np.array([[0, 1, 2], [3, 4, 5], [6, 7, 8]])
+arr_2 = np.array([[3, 6, 9], [12, 9, 15], [6, 36, 63]])
+print('Array 1:\n', arr_1)
+print('Array 2: \n', arr_2)
+array_3 = arr_2 + np.sin(arr_1) - arr_1 / arr_2
+print('\nArray 3:\n', array_3)
+
+other_array = np.array([1, 2, 3, 4, 5])
+for i in other_array:
+    print(i**3 + i)
+
+x = np.array(range(0, 9))
+y = np.sqrt(x)
+plt.plot(x, y)
+print('\nMy an other array y has values: ', y)
+

.idea/misc.xml

@@ -56,14 +56,14 @@
     print('Is There A specialized Key?: ', 'specialized' in info_dict_dev)
     # Logic & Loops
     for i in range(0, 10):
-        boolIsGreaterThanSix = (i >= 3)
+        boolIsGreaterThanThree = (i >= 3)
         if i == 5:
             print('Ignores at 5, continues at i = 6')
             continue
         if i == 9:
             print('Over flow at i = 9')
             break
-        print(f'{i} - Spam: {boolIsGreaterThanSix}')
+        print(f'{i} - Spam: {boolIsGreaterThanThree}')
 
     for i in range(0, 30):
         my_step_by_steps = (i % 3)
@@ -72,6 +72,13 @@
 
     cube_nums = [i ** 3 for i in range(10)]
     print(cube_nums)
+
+    a_number = 20
+    while a_number > 10:
+        a_number -= 3
+        if a_number < 10:
+            break
+        print("value: ", a_number)
     # Custom functions
     friends_stock_list = [info_dict_dev, info_dict_tester, info_dict_po, info_dict_boss]
     data = get_data_from_list(friends_stock_list)