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  1. import numpy as np
  2.  
  3. def run():
  4.     # create a column vector
  5.     col_vec = np.array([[1], [2]])
  6.     print "column vector"
  7.     print col_vec
  8.  
  9.     # create a row vector
  10.     row_vec = np.array([[1, 2]])
  11.     print "row vector"
  12.     print row_vec
  13.  
  14.     # create a matrix
  15.     mat = np.array([[1, 2], [3, 4]])
  16.     print "matrix"
  17.     print mat
  18.  
  19.     # inspect dimensions
  20.     print "row vector dimensions", row_vec.ndim
  21.     shape = row_vec.shape
  22.     print "row vector rows", shape[0], "columns", shape[1]
  23.  
  24.     print "matrix dimensions", mat.ndim
  25.     shape = mat.shape
  26.     print "matrix rows", shape[0], "columns", shape[1]
  27.  
  28.     # transpose
  29.     vec_t = row_vec.transpose() # or row_vec.T
  30.     print "transposed vector"
  31.     print vec_t
  32.  
  33.     mat_t = mat.transpose() # or mat.T
  34.     print "transposed matrix"
  35.     print mat_t
  36.  
  37.     a = np.array([[2], [-4], [1]])
  38.     b = np.array([[2], [1], [-2]])
  39.  
  40.     # addition 
  41.     print "a + b"
  42.     print a + b
  43.  
  44.     # subtraction
  45.     print "a - b"
  46.     print a - b
  47.  
  48.     # scalar multiplication
  49.     print "1.2 * a"
  50.     print 1.2 * a
  51.  
  52.     # element wise multiplication
  53.     print "a * b"
  54.     print a * b    
  55.  
  56.     # vector scalar product
  57.     print "a . b"
  58.     print np.dot(a.transpose(), b)
  59.  
  60.     # vector cross product
  61.     print "a x b"
  62.     print np.cross(a, b, axis=0) # or np.cross(a.T, b.T).T
  63.  
  64.     identity = np.array([[1, 0], [0, 1]])
  65.  
  66.     # matrix vector product
  67.     print "identity . col_vec"
  68.     print np.dot(identity, col_vec)
  69.  
  70.     # matrix product
  71.     print "identity . mat"
  72.     print np.dot(identity, mat)
  73.  
  74.  
  75.  
Success #stdin #stdout 0.1s 23944KB
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https://ideone.com/xFLQDm
Linear algebra calculations in NumPy
language:
Python (cpython 2.7.16)
created:
10 years ago
visibility:
secret

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