import numpy as np #import library to current file
vector = [0, 1, 3] #define normal vector
nvector = numpy.array(vector) #cast normal vector into numpy vector
matrix = [[0,1,2,3], [4,5,6,7], [8,9,10,11], [12,13,14,15]]
nmatrix = np.array(matrix)
#################################################################
# create zero or one matrix
np.ones((2,3), float)
np.ones((2,3), int)
np.zeros((2,3), float)
np.zeros((2,3), int)
marr = narr.copy() #==> create new copy of array
################################################################
nmatrix.astype("f") #change elements type to float
np.diag(nmatrix) #Matrix diameter
vector1.T #Transpose vector
np.repeat(vector,2) #Repeat vector element 2 times ==> (1,2) ==> (1, 1 , 2, 2)
pos = np.arange(0,15,1) **2 #generate matrix elements from value 0 to 15 with 1 as step finally power on 2
################################################################
################################################################
pos = array([ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144,169, 196])
[False, False, False], [False, False, False]])
narr[(narr > 0) & (narr < 3)] = 10 #==> it is call by reference, now narr is:array([[10, 10, 3], [ 0, 0, 0], [ 0, 0, 0]])
array([[0, 9, 6], [6, 5, 6], [8, 1, 3], [0, 8, 3]])tarr[1::1, 1:2] #==> [[5],
[1], [8]]
####################################def quicksort (arr, i = 0): if i == 0: #cast array to numpy array in first function call arr = numpy.array(arr) if len(arr) == i: #continue recursive call till last element return arr m = min( arr[i:] ) #find min from floating incremental position mi = numpy.argmin( arr[i:] ) + i #find min position & add i to achive real position in original array arr[mi:mi+1] = arr[i:i+1] arr[i:i+1] = m return quicksort (arr, i+1)
#----------------------
#Sample Call:
import numpy arr = [6,5,4,8,6,5,4,7,9,9,-1,100] quicksort(arr)
#----------------------
#Result:
array([ -1, 4, 4, 5, 5, 6, 6, 7, 8, 9, 9, 100])###########################################