k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and send them to the cluster def parzen_async(): # clear the previous results delete_group('parzen', Sphinx 1.3.1. index modules | Django Q 0.5.3 documentation » Index A | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A args (Schedule attribute) (Task attribute) async()

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and send them to the cluster def parzen_async(): # clear the previous results delete_group('parzen', Sphinx 1.3.1. index modules | Django Q 0.4.6 documentation » Index A | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A args (Schedule attribute) (Task attribute) async()

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and send them to the cluster def parzen_async(): # clear the previous results delete_group('parzen', 1.3.1. index modules | Django Q 0.6.4 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) args (Schedule attribute)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.1. index modules | Django Q 0.7.8 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) args (Schedule attribute)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.1. index modules | Django Q 0.7.10 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.1. index modules | Django Q 0.7.11 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.4. index modules | Django Q 0.7.14 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.1. index modules | Django Q 0.7.12 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.5. index modules | Django Q 0.7.18 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)

k_n = 0 for row in x_samples: x_i = (point_x - row[:, numpy.newaxis]) / h for row in x_i: if numpy.abs(row) > (1 / 2): break else: k_n += += 1 return h, (k_n / len(x_samples)) / (h ** point_x.shape[1]) # create 100 calculations and return the collated result def parzen_async(): # clear the previous results delete_group('parzen' 1.3.4. index modules | Django Q 0.7.15 documentation » Index A | B | C | D | E | F | G | H | I | K | L | M | N | O | P | Q | R | S | T | U | W | Y A acknowledge() (Broker method) append() (Chain method)