| 845 | return params |
| 846 | |
| 847 | def to_h5(self, output_name): |
| 848 | data = np.full( |
| 849 | ( |
| 850 | len(self.metadata["imnames"]), |
| 851 | self.max_n_individuals, |
| 852 | self.n_multibodyparts, |
| 853 | 4, |
| 854 | ), |
| 855 | fill_value=np.nan, |
| 856 | ) |
| 857 | for ind, assemblies in self.assemblies.items(): |
| 858 | for n, assembly in enumerate(assemblies): |
| 859 | data[ind, n] = assembly.data |
| 860 | index = pd.MultiIndex.from_product( |
| 861 | [ |
| 862 | ["scorer"], |
| 863 | map(str, range(self.max_n_individuals)), |
| 864 | map(str, range(self.n_multibodyparts)), |
| 865 | ["x", "y", "likelihood"], |
| 866 | ], |
| 867 | names=["scorer", "individuals", "bodyparts", "coords"], |
| 868 | ) |
| 869 | temp = data[..., :3].reshape((data.shape[0], -1)) |
| 870 | df = pd.DataFrame(temp, columns=index) |
| 871 | df.to_hdf(output_name, key="ass") |
| 872 | |
| 873 | def to_pickle(self, output_name): |
| 874 | data = dict() |