Map the normalized values (i.e., index in the colormap) back to data values. Parameters ---------- values : array-like The input data, as an iterable or a structured numpy array. - If iterable, must be of length `n_components`. Each element
(self, values)
| 3511 | return result |
| 3512 | |
| 3513 | def inverse(self, values): |
| 3514 | """ |
| 3515 | Map the normalized values (i.e., index in the colormap) back to data values. |
| 3516 | |
| 3517 | Parameters |
| 3518 | ---------- |
| 3519 | values : array-like |
| 3520 | The input data, as an iterable or a structured numpy array. |
| 3521 | |
| 3522 | - If iterable, must be of length `n_components`. Each element can be a |
| 3523 | scalar or array-like and is mapped through the corresponding norm. |
| 3524 | - If structured array, must have `n_components` fields. Each field |
| 3525 | is mapped through the corresponding norm. |
| 3526 | |
| 3527 | """ |
| 3528 | values = self._iterable_components_in_data(values, self.n_components) |
| 3529 | result = tuple(n.inverse(v) for n, v in zip(self.norms, values)) |
| 3530 | return result |
| 3531 | |
| 3532 | def autoscale(self, A): |
| 3533 | """ |