matrix.py

   1 import cgi
   2 from scipy import compress, transpose
   3 from scipy.linalg import svd, det
   4 import json
   5
   6 def calculate_nullspace(A, eps=1e-15):
   7     u, s, vh = svd(A)
   8     null_mask = (s <= eps)
   9     null_space = compress(null_mask, vh, axis=0)
  10     return transpose(null_space)
  11
  12 def calculate_eigenvalues(A, eps=1e-15):
  13     u, s, vh = svd(A)
  14     return s
  15
  16 def application(environ, start_response):
  17     parameters = cgi.parse_qs(environ.get('QUERY_STRING', ''))
  18
  19     query_string = str(parameters['matrix'][0])
  20     matrix = query_string.splitlines()
  21     for index, row in enumerate(matrix):
  22         matrix[index] = row.split()
  23
  24     while len(matrix) < len(matrix[0]):
  25         matrix.append([0]*len(matrix[0]))
  26
  27     nullspace = calculate_nullspace(matrix)
  28     if nullspace.max() != 0:
  29         nullspace = nullspace / nullspace.max()
  30
  31     eigenvalues = calculate_eigenvalues(matrix)
  32     determinant = det(matrix)
  33
  34     output = json.dumps({
  35         'nullspace' : str(nullspace),
  36         'eigenvalues' : str(eigenvalues),
  37         'determinant' : str(determinant)
  38         })
  39
  40     output_len = sum(len(line) for line in output)
  41     start_response('200 OK', [('Content-type', 'application/json'),
  42                               ('Content-Length', str(output_len))])
  43     return output