| 71 | |
| 72 | |
| 73 | class Z_Normalizer(NormalizationMethod): |
| 74 | def __init__(self, mean, std, **kwargs): |
| 75 | super().__init__(**kwargs) |
| 76 | self.mean = mean |
| 77 | self.std = std |
| 78 | |
| 79 | def normalize(self, data, axis=None, *args, **kwargs): |
| 80 | return self(data) |
| 81 | |
| 82 | def inverse_normalize(self, normalized_data): |
| 83 | data = normalized_data * self.std + self.mean |
| 84 | return data |
| 85 | |
| 86 | def stored_values(self): |
| 87 | return {'mean': self.mean, 'std': self.std} |
| 88 | |
| 89 | def __call__(self, data): |
| 90 | return (data - self.mean) / self.std |
| 91 | |
| 92 | |
| 93 | class MinMax_Normalizer(NormalizationMethod): |
no outgoing calls
no test coverage detected