matrix.py

   1 import urlparse
   2 import json
   3
   4 import scipy
   5 import scipy.linalg
   6 from scipy import *
   7
   8 def null(A, eps=1e-15):
   9     u, s, vh = scipy.linalg.svd(A)
  10     null_mask = (s <= eps)
  11     null_space = scipy.compress(null_mask, vh, axis=0)
  12     return scipy.transpose(null_space)
  13
  14 def eigenvalues(A, eps=1e-15):
  15     u, s, vh = scipy.linalg.svd(A)
  16     return s
  17
  18 def application(environ, start_response):
  19     if environ['REQUEST_METHOD'] == 'POST':
  20         post_data = environ['wsgi.input'].read()
  21
  22         post_data = urlparse.parse_qsl(post_data, True, True)
  23
  24         data_string = str(post_data[0][1])
  25         data_rows = data_string.splitlines()
  26         for index, row in enumerate(data_rows):
  27             data_rows[index] = row.split()
  28
  29         given_matrix = data_rows
  30         null_space = null(given_matrix)
  31         try:
  32             null_space = null_space / null_space.max()
  33         except:
  34             pass
  35
  36 #        la, v = scipy.linalg.eig(given_matrix)
  37 #       output += "eigenvalues:<br>"
  38 #        for l in la:
  39 #            output += str(l)
  40         determinant = scipy.linalg.det(given_matrix)
  41
  42     output = json.dumps({
  43         'nullspace' : str(null_space),
  44         'eigenvalues' : str(eigenvalues(given_matrix)),
  45         'determinant' : str(determinant)
  46         })
  47
  48     output_len = sum(len(line) for line in output)
  49     start_response('200 OK', [('Content-type', 'application/json'),
  50                               ('Content-Length', str(output_len))])
  51     return output