(self, value, clip=None)
| 2932 | *bound_init_signature.parameters.values()]) |
| 2933 | |
| 2934 | def __call__(self, value, clip=None): |
| 2935 | value, is_scalar = self.process_value(value) |
| 2936 | if self.vmin is None or self.vmax is None: |
| 2937 | self.autoscale_None(value) |
| 2938 | if self.vmin > self.vmax: |
| 2939 | raise ValueError("vmin must be less or equal to vmax") |
| 2940 | if self.vmin == self.vmax: |
| 2941 | return np.full_like(value, 0) |
| 2942 | if clip is None: |
| 2943 | clip = self.clip |
| 2944 | if clip: |
| 2945 | value = np.clip(value, self.vmin, self.vmax) |
| 2946 | t_value = self._trf.transform(value).reshape(np.shape(value)) |
| 2947 | t_vmin, t_vmax = self._trf.transform([self.vmin, self.vmax]) |
| 2948 | if not np.isfinite([t_vmin, t_vmax]).all(): |
| 2949 | raise ValueError("Invalid vmin or vmax") |
| 2950 | t_value -= t_vmin |
| 2951 | t_value /= (t_vmax - t_vmin) |
| 2952 | t_value = np.ma.masked_invalid(t_value, copy=False) |
| 2953 | return t_value[0] if is_scalar else t_value |
| 2954 | |
| 2955 | def inverse(self, value): |
| 2956 | if not self.scaled(): |
nothing calls this directly
no test coverage detected