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67 | 67 | 'gamma': [1e-2, 1e-1, 1, 10, 100, 1000], |
68 | 68 | 'scale': 'small'}, |
69 | 69 | {'num_iterations': (1, 100), # gets expensive with more iterations |
70 | | - 'gamma': (1e-4, 1e7)}) |
| 70 | + 'gamma': (1e-4, 1e7)}), |
71 | 71 | smooth_acceleration: ({'gamma': [1e-2, 1e-1, 1, 10, 100, 1000], |
72 | 72 | 'window_size': [3, 10, 30, 50, 90, 130]}, |
73 | 73 | {'gamma': (1e-4, 1e7), |
74 | | - 'window_size': (1, 1000)}) |
75 | | - # jerk_sliding: |
76 | | - # constant_velocity: |
77 | | - # constant_acceleration: |
78 | | - # constant_jerk: |
| 74 | + 'window_size': (1, 1000)}), |
| 75 | + constant_velocity: ({'forwardbackward': [True, False], |
| 76 | + 'q': [1e-8, 1e-4, 1e-1, 1e1, 1e4, 1e8], |
| 77 | + 'r': [1e-8, 1e-4, 1e-1, 1e1, 1e4, 1e8]}, |
| 78 | + {'q': (1e-10, 1e10), |
| 79 | + 'r': (1e-10, 1e10)}) |
79 | 80 | } |
80 | 81 | for method in [meandiff, gaussiandiff, friedrichsdiff]: |
81 | 82 | method_params_and_bounds[method] = method_params_and_bounds[mediandiff] |
82 | 83 | for method in [acceleration, jerk]: |
83 | 84 | method_params_and_bounds[method] = method_params_and_bounds[velocity] |
84 | 85 | method_params_and_bounds[jerk_sliding] = method_params_and_bounds[smooth_acceleration] |
| 86 | +for method in [constant_acceleration, constant_jerk]: |
| 87 | + method_params_and_bounds[method] = method_params_and_bounds[constant_velocity] |
85 | 88 |
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86 | 89 |
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87 | 90 | # This function to be at the top level for multiprocessing |
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