Rename traditional baseline artifacts as LOS controllers
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- .gitattributes +386 -0
- experiments/BASELINES.md +3 -3
- experiments/EXPERIMENT_MATRIX.md +3 -3
- experiments/METHOD_AUDIT.md +3 -3
- experiments/README.md +3 -3
- experiments/TASK_PLAN.md +3 -3
- experiments/current_estimator_los_controller/README.md +3 -0
- experiments/current_estimator_los_controller/__init__.py +1 -0
- experiments/current_estimator_los_controller/checkpoint/.gitkeep +0 -0
- experiments/current_estimator_los_controller/result/.gitkeep +0 -0
- experiments/current_estimator_los_controller/src/__init__.py +1 -0
- experiments/current_estimator_los_controller/src/config.py +5 -0
- experiments/current_estimator_los_controller/src/controller.py +19 -0
- experiments/current_estimator_los_controller/src/estimator.py +9 -0
- experiments/current_estimator_los_controller/src/evaluate.py +10 -0
- experiments/docs/EXPERIMENT_PROTOCOL.md +6 -6
- experiments/export_paper_artifacts.py +1198 -0
- experiments/no_flow_los_controller/README.md +3 -0
- experiments/no_flow_los_controller/__init__.py +1 -0
- experiments/no_flow_los_controller/checkpoint/.gitkeep +0 -0
- experiments/no_flow_los_controller/result/.gitkeep +0 -0
- experiments/no_flow_los_controller/src/__init__.py +1 -0
- experiments/no_flow_los_controller/src/config.py +5 -0
- experiments/no_flow_los_controller/src/controller.py +11 -0
- experiments/no_flow_los_controller/src/evaluate.py +8 -0
- experiments/oracle_flow_los_controller/README.md +5 -0
- experiments/oracle_flow_los_controller/__init__.py +1 -0
- experiments/oracle_flow_los_controller/checkpoint/.gitkeep +0 -0
- experiments/oracle_flow_los_controller/result/.gitkeep +0 -0
- experiments/oracle_flow_los_controller/src/__init__.py +1 -0
- experiments/oracle_flow_los_controller/src/config.py +5 -0
- experiments/oracle_flow_los_controller/src/controller.py +19 -0
- experiments/oracle_flow_los_controller/src/evaluate.py +8 -0
- experiments/plot_task_schematics.py +171 -0
- experiments/reports/paper_artifacts/README.md +66 -0
- experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.csv +25 -0
- experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.tsv +25 -0
- experiments/reports/paper_artifacts/fig3/figure3_placeholder_contact_sheet.png +3 -0
- experiments/reports/paper_artifacts/fig3/figure3_provenance.md +30 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_first_frame000.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_last_frame149.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_middle_frame075.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_first_frame000.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_last_frame097.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_middle_frame049.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_first_frame000.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_last_frame272.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_middle_frame136.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_first_frame000.png +0 -0
- experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_last_frame319.png +0 -0
.gitattributes
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@@ -1865,3 +1865,389 @@ experiments/reports/paper_planning/gifs/image_planning_tdmpc2_inferred_twin_wayp
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experiments/reports/paper_planning/gifs/image_planning_tdmpc2_inferred_twin_waypoint_zigzag_vortex_center_ep002.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_tdmpc2_inferred_twin_waypoint_zigzag_vortex_center_ep002.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_artifacts/fig3/figure3_placeholder_contact_sheet.png filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_reach_target_double_gyre_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_reach_target_double_gyre_ep002.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_reach_target_source_sink_pair_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_reach_target_source_sink_pair_ep002.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_reach_target_vortex_center_ep002.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_double_gyre_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_gradient_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_noflow_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_random_fourier_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_shear_ep000.gif filter=lfs diff=lfs merge=lfs -text
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experiments/reports/paper_planning/gifs/image_planning_current_estimator_los_controller_inferred_triangle_waypoint_square_source_sink_ep000.gif filter=lfs diff=lfs merge=lfs -text
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| 1906 |
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| 1907 |
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| 1908 |
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| 1909 |
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| 1910 |
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| 1911 |
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| 1912 |
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| 1913 |
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| 1914 |
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| 1915 |
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| 1916 |
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| 1917 |
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| 1918 |
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| 1919 |
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| 1920 |
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| 1921 |
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| 1922 |
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| 1923 |
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| 1924 |
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| 1925 |
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| 1926 |
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| 1927 |
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| 1928 |
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| 1929 |
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| 1930 |
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| 1931 |
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| 1932 |
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| 1933 |
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| 1934 |
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| 1935 |
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| 1936 |
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| 1937 |
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| 1938 |
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| 1939 |
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| 1940 |
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| 1941 |
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| 1942 |
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| 1943 |
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| 1944 |
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| 1945 |
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| 1946 |
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| 1947 |
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| 1948 |
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| 1949 |
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| 1950 |
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| 1951 |
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| 1952 |
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| 1953 |
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| 1954 |
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| 1955 |
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| 1956 |
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| 1957 |
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| 1958 |
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| 1959 |
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| 1960 |
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| 1961 |
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| 1962 |
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| 1963 |
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| 1964 |
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| 1965 |
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| 1966 |
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| 1967 |
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| 1968 |
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| 1969 |
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| 1970 |
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| 1971 |
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| 1972 |
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| 1973 |
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| 1974 |
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| 1975 |
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| 1976 |
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| 1977 |
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| 1978 |
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| 1979 |
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| 1980 |
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| 1981 |
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| 1982 |
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| 1983 |
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| 1984 |
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| 1985 |
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| 1986 |
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| 1987 |
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| 1988 |
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| 1989 |
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| 1990 |
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| 1991 |
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| 1992 |
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| 1993 |
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| 1994 |
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| 1995 |
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| 1996 |
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| 1997 |
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| 1998 |
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| 1999 |
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| 2000 |
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| 2001 |
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| 2002 |
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| 2003 |
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| 2004 |
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| 2005 |
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| 2006 |
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| 2007 |
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| 2008 |
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| 2009 |
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| 2010 |
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| 2011 |
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| 2012 |
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| 2013 |
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| 2014 |
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| 2015 |
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| 2016 |
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+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_ep000.gif filter=lfs diff=lfs merge=lfs -text
|
| 2240 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_ep001.gif filter=lfs diff=lfs merge=lfs -text
|
| 2241 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_ep002.gif filter=lfs diff=lfs merge=lfs -text
|
| 2242 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_pair_ep000.gif filter=lfs diff=lfs merge=lfs -text
|
| 2243 |
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experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_pair_ep001.gif filter=lfs diff=lfs merge=lfs -text
|
| 2244 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_source_sink_pair_ep002.gif filter=lfs diff=lfs merge=lfs -text
|
| 2245 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_turbulent_patch_ep000.gif filter=lfs diff=lfs merge=lfs -text
|
| 2246 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_turbulent_patch_ep001.gif filter=lfs diff=lfs merge=lfs -text
|
| 2247 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_turbulent_patch_ep002.gif filter=lfs diff=lfs merge=lfs -text
|
| 2248 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_uniform_ep000.gif filter=lfs diff=lfs merge=lfs -text
|
| 2249 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_uniform_ep001.gif filter=lfs diff=lfs merge=lfs -text
|
| 2250 |
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experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_uniform_ep002.gif filter=lfs diff=lfs merge=lfs -text
|
| 2251 |
+
experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_vortex_center_ep000.gif filter=lfs diff=lfs merge=lfs -text
|
| 2252 |
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experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_vortex_center_ep001.gif filter=lfs diff=lfs merge=lfs -text
|
| 2253 |
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experiments/reports/paper_planning/gifs/image_planning_oracle_flow_los_controller_inferred_twin_waypoint_zigzag_vortex_center_ep002.gif filter=lfs diff=lfs merge=lfs -text
|
experiments/BASELINES.md
CHANGED
|
@@ -29,9 +29,9 @@ Purpose: compare downstream behavior against hand-designed controllers that do n
|
|
| 29 |
| Directory | Report Name | Why It Is Included |
|
| 30 |
|---|---|---|
|
| 31 |
| `pid_los_controller` | PID/LOS controller | Simple classical waypoint tracking baseline. |
|
| 32 |
-
| `
|
| 33 |
-
| `
|
| 34 |
-
| `
|
| 35 |
|
| 36 |
Comparison outputs:
|
| 37 |
|
|
|
|
| 29 |
| Directory | Report Name | Why It Is Included |
|
| 30 |
|---|---|---|
|
| 31 |
| `pid_los_controller` | PID/LOS controller | Simple classical waypoint tracking baseline. |
|
| 32 |
+
| `no_flow_los_controller` | No-Flow LOS Controller | Geometric line-of-sight controller that ignores ambient current. |
|
| 33 |
+
| `current_estimator_los_controller` | Current-Estimator LOS Controller | Strong classical baseline that estimates current from recent drift. |
|
| 34 |
+
| `oracle_flow_los_controller` | Oracle-Flow LOS Controller | Geometric line-of-sight controller with true local flow feed-forward. |
|
| 35 |
|
| 36 |
Comparison outputs:
|
| 37 |
|
experiments/EXPERIMENT_MATRIX.md
CHANGED
|
@@ -110,9 +110,9 @@ Traditional non-WM controllers:
|
|
| 110 |
| Method | Comparison Role | What It Tests |
|
| 111 |
|---|---|---|
|
| 112 |
| `pid_los_controller` | Simple classical controller | Baseline waypoint tracking without learned dynamics. |
|
| 113 |
-
| `
|
| 114 |
-
| `
|
| 115 |
-
| `
|
| 116 |
|
| 117 |
Planning tasks:
|
| 118 |
|
|
|
|
| 110 |
| Method | Comparison Role | What It Tests |
|
| 111 |
|---|---|---|
|
| 112 |
| `pid_los_controller` | Simple classical controller | Baseline waypoint tracking without learned dynamics. |
|
| 113 |
+
| `no_flow_los_controller` | No-flow LOS controller | Effect of ignoring hidden current in a geometric controller. |
|
| 114 |
+
| `current_estimator_los_controller` | Current-estimator LOS controller | Strength of a hand-designed drift estimator in a geometric controller. |
|
| 115 |
+
| `oracle_flow_los_controller` | Oracle-flow LOS controller | Effect of true local flow feed-forward in a geometric controller. |
|
| 116 |
|
| 117 |
Planning tasks:
|
| 118 |
|
experiments/METHOD_AUDIT.md
CHANGED
|
@@ -16,9 +16,9 @@ This document records what each paper-facing method implements and what comparis
|
|
| 16 |
| Method | Input | Controller Type | Comparison Purpose |
|
| 17 |
|---|---|---|---|
|
| 18 |
| PID/LOS controller | Clean image pose estimate | Line-of-sight waypoint tracking | Simple hand-designed tracking baseline. |
|
| 19 |
-
|
|
| 20 |
-
| Current-Estimator
|
| 21 |
-
| Oracle-Flow
|
| 22 |
|
| 23 |
## Architecture Difference Checklist
|
| 24 |
|
|
|
|
| 16 |
| Method | Input | Controller Type | Comparison Purpose |
|
| 17 |
|---|---|---|---|
|
| 18 |
| PID/LOS controller | Clean image pose estimate | Line-of-sight waypoint tracking | Simple hand-designed tracking baseline. |
|
| 19 |
+
| No-Flow LOS Controller | Clean image pose estimate | MPC with nominal boat dynamics | Measures the cost of ignoring external current. |
|
| 20 |
+
| Current-Estimator LOS Controller | Clean image pose estimate and recent drift | MPC with estimated current | Strong classical current-compensation baseline. |
|
| 21 |
+
| Oracle-Flow LOS Controller | Clean image pose estimate and simulator local flow | MPC with true local current | Reference bound for downstream planning. |
|
| 22 |
|
| 23 |
## Architecture Difference Checklist
|
| 24 |
|
experiments/README.md
CHANGED
|
@@ -22,9 +22,9 @@ Purpose of Category A: compare world-model architectures under identical image d
|
|
| 22 |
Category B traditional controllers:
|
| 23 |
|
| 24 |
- **PID/LOS controller**
|
| 25 |
-
- **
|
| 26 |
-
- **Current-Estimator
|
| 27 |
-
- **Oracle-Flow
|
| 28 |
|
| 29 |
Purpose of Category B: compare downstream task behavior against non-neural controllers that do not train a world model.
|
| 30 |
|
|
|
|
| 22 |
Category B traditional controllers:
|
| 23 |
|
| 24 |
- **PID/LOS controller**
|
| 25 |
+
- **No-Flow LOS Controller**
|
| 26 |
+
- **Current-Estimator LOS Controller**
|
| 27 |
+
- **Oracle-Flow LOS Controller**
|
| 28 |
|
| 29 |
Purpose of Category B: compare downstream task behavior against non-neural controllers that do not train a world model.
|
| 30 |
|
experiments/TASK_PLAN.md
CHANGED
|
@@ -80,9 +80,9 @@ Compared methods:
|
|
| 80 |
| Method | Purpose |
|
| 81 |
|---|---|
|
| 82 |
| `pid_los_controller` | Classical line-of-sight waypoint tracking. Tests a simple hand-designed controller. |
|
| 83 |
-
| `
|
| 84 |
-
| `
|
| 85 |
-
| `
|
| 86 |
|
| 87 |
Planning tasks:
|
| 88 |
|
|
|
|
| 80 |
| Method | Purpose |
|
| 81 |
|---|---|
|
| 82 |
| `pid_los_controller` | Classical line-of-sight waypoint tracking. Tests a simple hand-designed controller. |
|
| 83 |
+
| `no_flow_los_controller` | No-flow LOS controller without external-current compensation. Tests how much hidden flow hurts a nominal dynamics controller. |
|
| 84 |
+
| `current_estimator_los_controller` | LOS controller with recent-drift current estimation. Tests a strong classical current-compensation baseline. |
|
| 85 |
+
| `oracle_flow_los_controller` | LOS controller with simulator true local flow feed-forward. Tests whether local flow feed-forward helps a simple geometric controller; it is not a full dynamics-MPC upper bound. |
|
| 86 |
|
| 87 |
Planning tasks:
|
| 88 |
|
experiments/current_estimator_los_controller/README.md
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Current-Estimator LOS Controller Baseline
|
| 2 |
+
|
| 3 |
+
Traditional line-of-sight controller with an online image-history estimate of recent drift.
|
experiments/current_estimator_los_controller/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""Current-estimator line-of-sight controller experiment package."""
|
experiments/current_estimator_los_controller/checkpoint/.gitkeep
ADDED
|
File without changes
|
experiments/current_estimator_los_controller/result/.gitkeep
ADDED
|
File without changes
|
experiments/current_estimator_los_controller/src/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""Current-estimator line-of-sight controller source package."""
|
experiments/current_estimator_los_controller/src/config.py
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
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|
|
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|
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|
|
| 1 |
+
"""Current-estimator line-of-sight controller config."""
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
def default_config():
|
| 5 |
+
return {"goal": [8.0, 8.0], "gain": 0.65, "current_gain": 0.5}
|
experiments/current_estimator_los_controller/src/controller.py
ADDED
|
@@ -0,0 +1,19 @@
|
|
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|
| 1 |
+
"""Line-of-sight controller with online current estimate."""
|
| 2 |
+
|
| 3 |
+
import numpy as np
|
| 4 |
+
|
| 5 |
+
from experiments.shared.src.control.geometric import goal_action
|
| 6 |
+
from experiments.shared.src.vision.pose_from_image import estimate_pose_from_clean_image
|
| 7 |
+
|
| 8 |
+
def plan(state, current_estimate, task, config):
|
| 9 |
+
pose = estimate_pose_from_clean_image(state)
|
| 10 |
+
goal = np.asarray(task["goal"], dtype=np.float32)
|
| 11 |
+
return goal_action(
|
| 12 |
+
pose,
|
| 13 |
+
goal,
|
| 14 |
+
int(config["action_dim"]),
|
| 15 |
+
float(config["gain"]),
|
| 16 |
+
0.6,
|
| 17 |
+
drift=np.asarray(current_estimate, dtype=np.float32),
|
| 18 |
+
drift_gain=float(config["current_gain"]),
|
| 19 |
+
)
|
experiments/current_estimator_los_controller/src/estimator.py
ADDED
|
@@ -0,0 +1,9 @@
|
|
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|
|
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|
| 1 |
+
"""Online current estimator."""
|
| 2 |
+
|
| 3 |
+
import numpy as np
|
| 4 |
+
|
| 5 |
+
from experiments.shared.src.vision.pose_from_image import estimate_pose_from_clean_image
|
| 6 |
+
|
| 7 |
+
def estimate_current(history, config):
|
| 8 |
+
poses = np.stack([estimate_pose_from_clean_image(img) for img in history], axis=0)
|
| 9 |
+
return poses[-1, :2] - poses[0, :2]
|
experiments/current_estimator_los_controller/src/evaluate.py
ADDED
|
@@ -0,0 +1,10 @@
|
|
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|
|
|
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|
|
|
|
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|
|
| 1 |
+
"""Current-estimator line-of-sight controller evaluation."""
|
| 2 |
+
|
| 3 |
+
from experiments.current_estimator_los_controller.src.config import default_config
|
| 4 |
+
from experiments.current_estimator_los_controller.src.controller import plan
|
| 5 |
+
from experiments.current_estimator_los_controller.src.estimator import estimate_current
|
| 6 |
+
|
| 7 |
+
def evaluate(config):
|
| 8 |
+
cfg = default_config() | config
|
| 9 |
+
current = estimate_current(config["history"], cfg)
|
| 10 |
+
return plan(config["history"][-1], current, {"goal": cfg["goal"]}, cfg)
|
experiments/docs/EXPERIMENT_PROTOCOL.md
CHANGED
|
@@ -26,9 +26,9 @@ Purpose: compare downstream behavior against non-neural controllers that do not
|
|
| 26 |
| Directory | Report Name | Input | Comparison Purpose |
|
| 27 |
|---|---|---|---|
|
| 28 |
| `pid_los_controller` | PID/LOS | Clean image pose estimate | Simple hand-designed waypoint tracking baseline. |
|
| 29 |
-
| `
|
| 30 |
-
| `
|
| 31 |
-
| `
|
| 32 |
|
| 33 |
## Data
|
| 34 |
|
|
@@ -138,9 +138,9 @@ Traditional non-WM controllers:
|
|
| 138 |
|
| 139 |
```text
|
| 140 |
pid_los_controller
|
| 141 |
-
|
| 142 |
-
|
| 143 |
-
|
| 144 |
```
|
| 145 |
|
| 146 |
Tasks:
|
|
|
|
| 26 |
| Directory | Report Name | Input | Comparison Purpose |
|
| 27 |
|---|---|---|---|
|
| 28 |
| `pid_los_controller` | PID/LOS | Clean image pose estimate | Simple hand-designed waypoint tracking baseline. |
|
| 29 |
+
| `no_flow_los_controller` | No-Flow LOS Controller | Clean image pose estimate | Measures the cost of ignoring ambient current. |
|
| 30 |
+
| `current_estimator_los_controller` | Current-Estimator LOS Controller | Clean image pose estimate and recent drift | Strong classical current-compensation baseline. |
|
| 31 |
+
| `oracle_flow_los_controller` | Oracle-Flow LOS Controller | Clean image pose estimate and simulator local flow | True-local-flow feed-forward reference for a simple geometric controller, not a full dynamics-MPC upper bound. |
|
| 32 |
|
| 33 |
## Data
|
| 34 |
|
|
|
|
| 138 |
|
| 139 |
```text
|
| 140 |
pid_los_controller
|
| 141 |
+
no_flow_los_controller
|
| 142 |
+
current_estimator_los_controller
|
| 143 |
+
oracle_flow_los_controller
|
| 144 |
```
|
| 145 |
|
| 146 |
Tasks:
|
experiments/export_paper_artifacts.py
ADDED
|
@@ -0,0 +1,1198 @@
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|
| 1 |
+
#!/usr/bin/env python3
|
| 2 |
+
"""Export paper figures, tables, raw data, and provenance files.
|
| 3 |
+
|
| 4 |
+
All values are read from experiments/reports/*.json and GIF frames are
|
| 5 |
+
extracted from experiments/reports/paper_planning/gifs/*.gif.
|
| 6 |
+
"""
|
| 7 |
+
|
| 8 |
+
from __future__ import annotations
|
| 9 |
+
|
| 10 |
+
import csv
|
| 11 |
+
import json
|
| 12 |
+
import math
|
| 13 |
+
import re
|
| 14 |
+
import shutil
|
| 15 |
+
from collections import defaultdict
|
| 16 |
+
from dataclasses import dataclass
|
| 17 |
+
from pathlib import Path
|
| 18 |
+
from typing import Any, Iterable
|
| 19 |
+
|
| 20 |
+
from PIL import Image, ImageDraw, ImageFont, ImageSequence
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
ROOT = Path(__file__).resolve().parents[1]
|
| 24 |
+
REPORTS = ROOT / "experiments" / "reports"
|
| 25 |
+
PLANNING_DIR = REPORTS / "paper_planning"
|
| 26 |
+
GIF_DIR = PLANNING_DIR / "gifs"
|
| 27 |
+
OUT = REPORTS / "paper_artifacts"
|
| 28 |
+
|
| 29 |
+
PREDICTION_JSON = REPORTS / "paper_prediction.json"
|
| 30 |
+
PROBE_JSON = REPORTS / "paper_flowmo_latent_probes.json"
|
| 31 |
+
|
| 32 |
+
TASK_ORDER = ["reach_target", "station_keeping", "waypoint_square", "waypoint_zigzag"]
|
| 33 |
+
BOAT_ORDER = ["twin", "triangle"]
|
| 34 |
+
FLOW_ORDER = [
|
| 35 |
+
"noflow",
|
| 36 |
+
"uniform",
|
| 37 |
+
"vortex_center",
|
| 38 |
+
"double_gyre",
|
| 39 |
+
"source_sink",
|
| 40 |
+
"source_sink_pair",
|
| 41 |
+
"gradient",
|
| 42 |
+
"shear",
|
| 43 |
+
"turbulent_patch",
|
| 44 |
+
"random_fourier",
|
| 45 |
+
]
|
| 46 |
+
METHOD_ORDER = [
|
| 47 |
+
"flowmo",
|
| 48 |
+
"leworldmodel",
|
| 49 |
+
"planet",
|
| 50 |
+
"tdmpc2",
|
| 51 |
+
"pid_los_controller",
|
| 52 |
+
"no_flow_los_controller",
|
| 53 |
+
"current_estimator_los_controller",
|
| 54 |
+
"oracle_flow_los_controller",
|
| 55 |
+
]
|
| 56 |
+
LEARNED_METHODS = ["flowmo", "leworldmodel", "planet", "tdmpc2"]
|
| 57 |
+
TRADITIONAL_METHODS = [
|
| 58 |
+
"pid_los_controller",
|
| 59 |
+
"no_flow_los_controller",
|
| 60 |
+
"current_estimator_los_controller",
|
| 61 |
+
"oracle_flow_los_controller",
|
| 62 |
+
]
|
| 63 |
+
|
| 64 |
+
METHOD_LABEL = {
|
| 65 |
+
"flowmo": "FlowMo-WM",
|
| 66 |
+
"leworldmodel": "LeWorldModel",
|
| 67 |
+
"planet": "PlaNet/RSSM",
|
| 68 |
+
"tdmpc2": "TD-MPC2",
|
| 69 |
+
"pid_los_controller": "PID/LOS",
|
| 70 |
+
"no_flow_los_controller": "No-Flow LOS",
|
| 71 |
+
"current_estimator_los_controller": "Current-Estimator LOS",
|
| 72 |
+
"oracle_flow_los_controller": "Oracle-Flow LOS",
|
| 73 |
+
}
|
| 74 |
+
METHOD_SHORT = {
|
| 75 |
+
"flowmo": "FlowMo",
|
| 76 |
+
"leworldmodel": "LeWM",
|
| 77 |
+
"planet": "RSSM",
|
| 78 |
+
"tdmpc2": "TD2",
|
| 79 |
+
"pid_los_controller": "PID",
|
| 80 |
+
"no_flow_los_controller": "LOS0",
|
| 81 |
+
"current_estimator_los_controller": "LOSest",
|
| 82 |
+
"oracle_flow_los_controller": "LOSorc",
|
| 83 |
+
}
|
| 84 |
+
TASK_LABEL = {
|
| 85 |
+
"reach_target": "Reach",
|
| 86 |
+
"station_keeping": "Station",
|
| 87 |
+
"waypoint_square": "Square",
|
| 88 |
+
"waypoint_zigzag": "Zigzag",
|
| 89 |
+
}
|
| 90 |
+
BOAT_LABEL = {"twin": "Twin", "triangle": "Triangle"}
|
| 91 |
+
FLOW_LABEL = {
|
| 92 |
+
"noflow": "No flow",
|
| 93 |
+
"uniform": "Uniform",
|
| 94 |
+
"vortex_center": "Vortex",
|
| 95 |
+
"double_gyre": "Double gyre",
|
| 96 |
+
"source_sink": "Source/sink",
|
| 97 |
+
"source_sink_pair": "Src/sink pair",
|
| 98 |
+
"gradient": "Gradient",
|
| 99 |
+
"shear": "Shear",
|
| 100 |
+
"turbulent_patch": "Turbulent",
|
| 101 |
+
"random_fourier": "Fourier",
|
| 102 |
+
}
|
| 103 |
+
|
| 104 |
+
HORIZONS = [1, 3, 6, 8, 10, 20, 30, 40, 60]
|
| 105 |
+
FIG3_TASK_FLOW = {
|
| 106 |
+
"reach_target": "uniform",
|
| 107 |
+
"station_keeping": "vortex_center",
|
| 108 |
+
"waypoint_square": "gradient",
|
| 109 |
+
"waypoint_zigzag": "random_fourier",
|
| 110 |
+
}
|
| 111 |
+
FIG3_EPISODE = 0
|
| 112 |
+
METHOD_COLORS = {
|
| 113 |
+
"flowmo": (31, 119, 180),
|
| 114 |
+
"leworldmodel": (255, 127, 14),
|
| 115 |
+
"planet": (44, 160, 44),
|
| 116 |
+
"tdmpc2": (148, 103, 189),
|
| 117 |
+
"pid_los_controller": (127, 127, 127),
|
| 118 |
+
"no_flow_los_controller": (214, 39, 40),
|
| 119 |
+
"current_estimator_los_controller": (23, 190, 207),
|
| 120 |
+
"oracle_flow_los_controller": (140, 86, 75),
|
| 121 |
+
}
|
| 122 |
+
|
| 123 |
+
|
| 124 |
+
@dataclass(frozen=True)
|
| 125 |
+
class SummaryRecord:
|
| 126 |
+
source_file: str
|
| 127 |
+
item_index: int
|
| 128 |
+
method: str
|
| 129 |
+
task: str
|
| 130 |
+
boat: str
|
| 131 |
+
flow_type: str
|
| 132 |
+
context_mode: str
|
| 133 |
+
episodes: int
|
| 134 |
+
successes: int
|
| 135 |
+
success_rate: float
|
| 136 |
+
final_distance_mean: float
|
| 137 |
+
mean_min_goal_distance: float
|
| 138 |
+
path_length_success_mean: float | None
|
| 139 |
+
energy_success_mean: float | None
|
| 140 |
+
steps_success_mean: float | None
|
| 141 |
+
|
| 142 |
+
|
| 143 |
+
@dataclass(frozen=True)
|
| 144 |
+
class EpisodeRecord:
|
| 145 |
+
source_file: str
|
| 146 |
+
item_index: int
|
| 147 |
+
result_index: int
|
| 148 |
+
method: str
|
| 149 |
+
task: str
|
| 150 |
+
boat: str
|
| 151 |
+
flow_type: str
|
| 152 |
+
context_mode: str
|
| 153 |
+
episode: int
|
| 154 |
+
success: bool
|
| 155 |
+
final_distance: float
|
| 156 |
+
mean_min_goal_distance: float
|
| 157 |
+
energy: float | None
|
| 158 |
+
path_length: float | None
|
| 159 |
+
steps: int | None
|
| 160 |
+
|
| 161 |
+
|
| 162 |
+
def rel(path: Path) -> str:
|
| 163 |
+
return str(path.relative_to(ROOT))
|
| 164 |
+
|
| 165 |
+
|
| 166 |
+
def ensure_dir(path: Path) -> None:
|
| 167 |
+
path.mkdir(parents=True, exist_ok=True)
|
| 168 |
+
|
| 169 |
+
|
| 170 |
+
def read_json(path: Path) -> Any:
|
| 171 |
+
with path.open("r", encoding="utf-8") as f:
|
| 172 |
+
return json.load(f)
|
| 173 |
+
|
| 174 |
+
|
| 175 |
+
def write_text(path: Path, text: str) -> None:
|
| 176 |
+
ensure_dir(path.parent)
|
| 177 |
+
path.write_text(text, encoding="utf-8")
|
| 178 |
+
|
| 179 |
+
|
| 180 |
+
def safe_float(value: Any) -> float | None:
|
| 181 |
+
if value is None:
|
| 182 |
+
return None
|
| 183 |
+
if isinstance(value, float) and math.isnan(value):
|
| 184 |
+
return None
|
| 185 |
+
return float(value)
|
| 186 |
+
|
| 187 |
+
|
| 188 |
+
def fmt(value: float | int | None, digits: int = 3) -> str:
|
| 189 |
+
if value is None:
|
| 190 |
+
return "--"
|
| 191 |
+
if isinstance(value, float) and math.isnan(value):
|
| 192 |
+
return "--"
|
| 193 |
+
return f"{float(value):.{digits}f}"
|
| 194 |
+
|
| 195 |
+
|
| 196 |
+
def pct(value: float | None, digits: int = 1) -> str:
|
| 197 |
+
if value is None:
|
| 198 |
+
return "--"
|
| 199 |
+
return f"{100.0 * float(value):.{digits}f}"
|
| 200 |
+
|
| 201 |
+
|
| 202 |
+
def latex_escape(text: str) -> str:
|
| 203 |
+
repl = {
|
| 204 |
+
"\\": r"\textbackslash{}",
|
| 205 |
+
"&": r"\&",
|
| 206 |
+
"%": r"\%",
|
| 207 |
+
"$": r"\$",
|
| 208 |
+
"#": r"\#",
|
| 209 |
+
"_": r"\_",
|
| 210 |
+
"{": r"\{",
|
| 211 |
+
"}": r"\}",
|
| 212 |
+
"~": r"\textasciitilde{}",
|
| 213 |
+
"^": r"\textasciicircum{}",
|
| 214 |
+
}
|
| 215 |
+
return "".join(repl.get(ch, ch) for ch in text)
|
| 216 |
+
|
| 217 |
+
|
| 218 |
+
def write_table(path: Path, header: list[str], rows: list[list[str]], caption: str, label: str) -> None:
|
| 219 |
+
colspec = "l" * len(header)
|
| 220 |
+
lines = [
|
| 221 |
+
r"\begin{table*}[t]",
|
| 222 |
+
r"\centering",
|
| 223 |
+
rf"\caption{{{caption}}}",
|
| 224 |
+
rf"\label{{{label}}}",
|
| 225 |
+
r"\scriptsize",
|
| 226 |
+
rf"\begin{{tabular}}{{{colspec}}}",
|
| 227 |
+
r"\toprule",
|
| 228 |
+
" & ".join(latex_escape(h) for h in header) + r" \\",
|
| 229 |
+
r"\midrule",
|
| 230 |
+
]
|
| 231 |
+
for row in rows:
|
| 232 |
+
lines.append(" & ".join(latex_escape(x) for x in row) + r" \\")
|
| 233 |
+
lines += [r"\bottomrule", r"\end{tabular}", r"\end{table*}", ""]
|
| 234 |
+
write_text(path, "\n".join(lines))
|
| 235 |
+
|
| 236 |
+
|
| 237 |
+
def write_rows(path_base: Path, rows: list[dict[str, Any]], fieldnames: list[str]) -> None:
|
| 238 |
+
ensure_dir(path_base.parent)
|
| 239 |
+
for ext, dialect in [(".tsv", "excel-tab"), (".csv", "excel")]:
|
| 240 |
+
with (path_base.with_suffix(ext)).open("w", encoding="utf-8", newline="") as f:
|
| 241 |
+
writer = csv.DictWriter(f, fieldnames=fieldnames, dialect=dialect)
|
| 242 |
+
writer.writeheader()
|
| 243 |
+
for row in rows:
|
| 244 |
+
writer.writerow({k: row.get(k, "") for k in fieldnames})
|
| 245 |
+
|
| 246 |
+
|
| 247 |
+
def font(size: int, bold: bool = False) -> ImageFont.FreeTypeFont | ImageFont.ImageFont:
|
| 248 |
+
candidates = [
|
| 249 |
+
"/usr/share/fonts/truetype/dejavu/DejaVuSans-Bold.ttf" if bold else "/usr/share/fonts/truetype/dejavu/DejaVuSans.ttf",
|
| 250 |
+
"/usr/share/fonts/dejavu/DejaVuSans-Bold.ttf" if bold else "/usr/share/fonts/dejavu/DejaVuSans.ttf",
|
| 251 |
+
]
|
| 252 |
+
for path in candidates:
|
| 253 |
+
try:
|
| 254 |
+
return ImageFont.truetype(path, size=size)
|
| 255 |
+
except OSError:
|
| 256 |
+
pass
|
| 257 |
+
return ImageFont.load_default()
|
| 258 |
+
|
| 259 |
+
|
| 260 |
+
def load_planning() -> tuple[list[SummaryRecord], list[EpisodeRecord]]:
|
| 261 |
+
summaries: list[SummaryRecord] = []
|
| 262 |
+
episodes: list[EpisodeRecord] = []
|
| 263 |
+
for path in sorted(PLANNING_DIR.glob("*.json")):
|
| 264 |
+
data = read_json(path)
|
| 265 |
+
if not isinstance(data, list):
|
| 266 |
+
raise ValueError(f"Expected list in {path}")
|
| 267 |
+
for item_index, item in enumerate(data):
|
| 268 |
+
method = item["method"]
|
| 269 |
+
task = item["task"]
|
| 270 |
+
boat = item["boat"]
|
| 271 |
+
flow_type = item["flow_type"]
|
| 272 |
+
for context_mode, metrics in item["by_context"].items():
|
| 273 |
+
summaries.append(
|
| 274 |
+
SummaryRecord(
|
| 275 |
+
source_file=rel(path),
|
| 276 |
+
item_index=item_index,
|
| 277 |
+
method=method,
|
| 278 |
+
task=task,
|
| 279 |
+
boat=boat,
|
| 280 |
+
flow_type=flow_type,
|
| 281 |
+
context_mode=context_mode,
|
| 282 |
+
episodes=int(metrics["episodes"]),
|
| 283 |
+
successes=int(metrics["successes"]),
|
| 284 |
+
success_rate=float(metrics["success_rate"]),
|
| 285 |
+
final_distance_mean=float(metrics["final_distance_mean"]),
|
| 286 |
+
mean_min_goal_distance=float(metrics["mean_min_goal_distance"]),
|
| 287 |
+
path_length_success_mean=safe_float(metrics.get("path_length_success_mean")),
|
| 288 |
+
energy_success_mean=safe_float(metrics.get("energy_success_mean")),
|
| 289 |
+
steps_success_mean=safe_float(metrics.get("steps_success_mean")),
|
| 290 |
+
)
|
| 291 |
+
)
|
| 292 |
+
for result_index, result in enumerate(item["results"]):
|
| 293 |
+
episodes.append(
|
| 294 |
+
EpisodeRecord(
|
| 295 |
+
source_file=rel(path),
|
| 296 |
+
item_index=item_index,
|
| 297 |
+
result_index=result_index,
|
| 298 |
+
method=method,
|
| 299 |
+
task=task,
|
| 300 |
+
boat=boat,
|
| 301 |
+
flow_type=flow_type,
|
| 302 |
+
context_mode=result["context_mode"],
|
| 303 |
+
episode=int(result["episode"]),
|
| 304 |
+
success=bool(result["success"]),
|
| 305 |
+
final_distance=float(result["final_distance"]),
|
| 306 |
+
mean_min_goal_distance=float(result["mean_min_goal_distance"]),
|
| 307 |
+
energy=safe_float(result.get("energy")),
|
| 308 |
+
path_length=safe_float(result.get("path_length")),
|
| 309 |
+
steps=int(result["steps"]) if result.get("steps") is not None else None,
|
| 310 |
+
)
|
| 311 |
+
)
|
| 312 |
+
return summaries, episodes
|
| 313 |
+
|
| 314 |
+
|
| 315 |
+
def inferred_summaries(records: Iterable[SummaryRecord]) -> list[SummaryRecord]:
|
| 316 |
+
return [r for r in records if r.context_mode == "inferred" and r.method in METHOD_ORDER]
|
| 317 |
+
|
| 318 |
+
|
| 319 |
+
def inferred_episodes(records: Iterable[EpisodeRecord]) -> list[EpisodeRecord]:
|
| 320 |
+
return [r for r in records if r.context_mode == "inferred" and r.method in METHOD_ORDER]
|
| 321 |
+
|
| 322 |
+
|
| 323 |
+
def aggregate_success(records: Iterable[SummaryRecord], group_keys: tuple[str, ...]) -> list[dict[str, Any]]:
|
| 324 |
+
acc: dict[tuple[Any, ...], dict[str, Any]] = {}
|
| 325 |
+
sources: dict[tuple[Any, ...], set[str]] = defaultdict(set)
|
| 326 |
+
for r in records:
|
| 327 |
+
key = tuple(getattr(r, k) for k in group_keys)
|
| 328 |
+
entry = acc.setdefault(key, {k: getattr(r, k) for k in group_keys} | {"successes": 0, "episodes": 0})
|
| 329 |
+
entry["successes"] += r.successes
|
| 330 |
+
entry["episodes"] += r.episodes
|
| 331 |
+
sources[key].add(r.source_file)
|
| 332 |
+
rows = []
|
| 333 |
+
for key, entry in acc.items():
|
| 334 |
+
episodes = entry["episodes"]
|
| 335 |
+
success_rate = entry["successes"] / episodes if episodes else math.nan
|
| 336 |
+
rows.append(entry | {"success_rate": success_rate, "source_files": ";".join(sorted(sources[key]))})
|
| 337 |
+
return rows
|
| 338 |
+
|
| 339 |
+
|
| 340 |
+
def task_sort_key(task: str) -> int:
|
| 341 |
+
return TASK_ORDER.index(task) if task in TASK_ORDER else len(TASK_ORDER)
|
| 342 |
+
|
| 343 |
+
|
| 344 |
+
def boat_sort_key(boat: str) -> int:
|
| 345 |
+
return BOAT_ORDER.index(boat) if boat in BOAT_ORDER else len(BOAT_ORDER)
|
| 346 |
+
|
| 347 |
+
|
| 348 |
+
def flow_sort_key(flow: str) -> int:
|
| 349 |
+
return FLOW_ORDER.index(flow) if flow in FLOW_ORDER else len(FLOW_ORDER)
|
| 350 |
+
|
| 351 |
+
|
| 352 |
+
def method_sort_key(method: str) -> int:
|
| 353 |
+
return METHOD_ORDER.index(method) if method in METHOD_ORDER else len(METHOD_ORDER)
|
| 354 |
+
|
| 355 |
+
|
| 356 |
+
def extract_fig3() -> None:
|
| 357 |
+
fig_dir = OUT / "fig3"
|
| 358 |
+
frames_dir = fig_dir / "frames"
|
| 359 |
+
ensure_dir(frames_dir)
|
| 360 |
+
rows: list[dict[str, Any]] = []
|
| 361 |
+
cell_images: dict[tuple[str, str, str], Path] = {}
|
| 362 |
+
frame_names = ["first", "middle", "last"]
|
| 363 |
+
|
| 364 |
+
for task in TASK_ORDER:
|
| 365 |
+
flow = FIG3_TASK_FLOW[task]
|
| 366 |
+
for boat in BOAT_ORDER:
|
| 367 |
+
gif_path = GIF_DIR / f"image_planning_flowmo_inferred_{boat}_{task}_{flow}_ep{FIG3_EPISODE:03d}.gif"
|
| 368 |
+
if not gif_path.exists():
|
| 369 |
+
raise FileNotFoundError(f"Missing GIF for Fig. 3: {gif_path}")
|
| 370 |
+
with Image.open(gif_path) as im:
|
| 371 |
+
n_frames = getattr(im, "n_frames", 1)
|
| 372 |
+
frame_indices = [0, n_frames // 2, n_frames - 1]
|
| 373 |
+
for frame_name, frame_index in zip(frame_names, frame_indices):
|
| 374 |
+
im.seek(frame_index)
|
| 375 |
+
frame = im.convert("RGBA")
|
| 376 |
+
out_name = f"fig3_flowmo_inferred_{boat}_{task}_{flow}_ep{FIG3_EPISODE:03d}_{frame_name}_frame{frame_index:03d}.png"
|
| 377 |
+
out_path = frames_dir / out_name
|
| 378 |
+
frame.save(out_path)
|
| 379 |
+
cell_images[(task, boat, frame_name)] = out_path
|
| 380 |
+
rows.append(
|
| 381 |
+
{
|
| 382 |
+
"task": task,
|
| 383 |
+
"boat": boat,
|
| 384 |
+
"method": "flowmo",
|
| 385 |
+
"context_mode": "inferred",
|
| 386 |
+
"flow_type": flow,
|
| 387 |
+
"episode": FIG3_EPISODE,
|
| 388 |
+
"frame_name": frame_name,
|
| 389 |
+
"frame_index": frame_index,
|
| 390 |
+
"gif_frames": n_frames,
|
| 391 |
+
"source_gif": rel(gif_path),
|
| 392 |
+
"output_png": rel(out_path),
|
| 393 |
+
}
|
| 394 |
+
)
|
| 395 |
+
|
| 396 |
+
write_rows(
|
| 397 |
+
fig_dir / "figure3_frame_manifest",
|
| 398 |
+
rows,
|
| 399 |
+
[
|
| 400 |
+
"task",
|
| 401 |
+
"boat",
|
| 402 |
+
"method",
|
| 403 |
+
"context_mode",
|
| 404 |
+
"flow_type",
|
| 405 |
+
"episode",
|
| 406 |
+
"frame_name",
|
| 407 |
+
"frame_index",
|
| 408 |
+
"gif_frames",
|
| 409 |
+
"source_gif",
|
| 410 |
+
"output_png",
|
| 411 |
+
],
|
| 412 |
+
)
|
| 413 |
+
|
| 414 |
+
thumb_w, thumb_h = 210, 210
|
| 415 |
+
label_h = 34
|
| 416 |
+
left = 128
|
| 417 |
+
top = 92
|
| 418 |
+
gap = 12
|
| 419 |
+
width = left + 6 * thumb_w + 5 * gap + 26
|
| 420 |
+
height = top + len(TASK_ORDER) * (thumb_h + label_h + gap) + 26
|
| 421 |
+
canvas = Image.new("RGB", (width, height), "white")
|
| 422 |
+
draw = ImageDraw.Draw(canvas)
|
| 423 |
+
title_font = font(26, True)
|
| 424 |
+
head_font = font(18, True)
|
| 425 |
+
small_font = font(14, False)
|
| 426 |
+
draw.text((20, 18), f"Figure 3 placeholder: FlowMo inferred, diverse flows, episode {FIG3_EPISODE}", fill=(20, 25, 30), font=title_font)
|
| 427 |
+
|
| 428 |
+
col_labels = ["Twin first", "Twin mid", "Twin last", "Triangle first", "Triangle mid", "Triangle last"]
|
| 429 |
+
for col, label in enumerate(col_labels):
|
| 430 |
+
x = left + col * (thumb_w + gap)
|
| 431 |
+
draw.text((x + 8, top - 26), label, fill=(30, 30, 30), font=small_font)
|
| 432 |
+
for row, task in enumerate(TASK_ORDER):
|
| 433 |
+
y = top + row * (thumb_h + label_h + gap)
|
| 434 |
+
draw.text((16, y + 80), TASK_LABEL[task], fill=(20, 25, 30), font=head_font)
|
| 435 |
+
draw.text((16, y + 108), FLOW_LABEL[FIG3_TASK_FLOW[task]], fill=(80, 80, 80), font=small_font)
|
| 436 |
+
col = 0
|
| 437 |
+
for boat in BOAT_ORDER:
|
| 438 |
+
for frame_name in frame_names:
|
| 439 |
+
x = left + col * (thumb_w + gap)
|
| 440 |
+
src = cell_images[(task, boat, frame_name)]
|
| 441 |
+
img = Image.open(src).convert("RGB").resize((thumb_w, thumb_h), Image.Resampling.LANCZOS)
|
| 442 |
+
canvas.paste(img, (x, y))
|
| 443 |
+
draw.rectangle([x, y, x + thumb_w, y + thumb_h], outline=(220, 220, 220), width=1)
|
| 444 |
+
draw.text((x + 8, y + thumb_h + 8), f"{BOAT_LABEL[boat]} / {frame_name}", fill=(50, 50, 50), font=small_font)
|
| 445 |
+
col += 1
|
| 446 |
+
|
| 447 |
+
contact = fig_dir / "figure3_placeholder_contact_sheet.png"
|
| 448 |
+
canvas.save(contact)
|
| 449 |
+
|
| 450 |
+
md_lines = [
|
| 451 |
+
"# Figure 3 Provenance",
|
| 452 |
+
"",
|
| 453 |
+
"Purpose: qualitative task rollouts extracted from experiment GIFs.",
|
| 454 |
+
"",
|
| 455 |
+
f"Selected method/context: `flowmo` / `inferred`.",
|
| 456 |
+
f"Selected episode: `{FIG3_EPISODE}`.",
|
| 457 |
+
"",
|
| 458 |
+
"Selected flows by task:",
|
| 459 |
+
]
|
| 460 |
+
for task in TASK_ORDER:
|
| 461 |
+
md_lines.append(f"- `{task}`: `{FIG3_TASK_FLOW[task]}`")
|
| 462 |
+
md_lines += [
|
| 463 |
+
"",
|
| 464 |
+
"Frame rule: for each source GIF, extracted `first = 0`, `middle = n_frames // 2`, and `last = n_frames - 1`.",
|
| 465 |
+
"",
|
| 466 |
+
"Generated outputs:",
|
| 467 |
+
f"- `{rel(contact)}`",
|
| 468 |
+
f"- `{rel(frames_dir)}/`",
|
| 469 |
+
f"- `{rel(fig_dir / 'figure3_frame_manifest.tsv')}`",
|
| 470 |
+
f"- `{rel(fig_dir / 'figure3_frame_manifest.csv')}`",
|
| 471 |
+
"",
|
| 472 |
+
"Source GIFs:",
|
| 473 |
+
]
|
| 474 |
+
for source in sorted({row["source_gif"] for row in rows}):
|
| 475 |
+
md_lines.append(f"- `{source}`")
|
| 476 |
+
write_text(fig_dir / "figure3_provenance.md", "\n".join(md_lines) + "\n")
|
| 477 |
+
|
| 478 |
+
|
| 479 |
+
def load_prediction_rows() -> list[dict[str, Any]]:
|
| 480 |
+
data = read_json(PREDICTION_JSON)
|
| 481 |
+
rows: list[dict[str, Any]] = []
|
| 482 |
+
for item_index, item in enumerate(data):
|
| 483 |
+
method = item["method"]
|
| 484 |
+
if method not in LEARNED_METHODS:
|
| 485 |
+
continue
|
| 486 |
+
metrics = item["inferred"]
|
| 487 |
+
for horizon in HORIZONS:
|
| 488 |
+
rows.append(
|
| 489 |
+
{
|
| 490 |
+
"method": method,
|
| 491 |
+
"method_label": METHOD_LABEL[method],
|
| 492 |
+
"context_mode": "inferred",
|
| 493 |
+
"horizon": horizon,
|
| 494 |
+
"position_error": metrics[f"pos{horizon}"],
|
| 495 |
+
"heading_error": metrics[f"heading{horizon}"],
|
| 496 |
+
"source_file": rel(PREDICTION_JSON),
|
| 497 |
+
"json_path_position": f"$[{item_index}].inferred.pos{horizon}",
|
| 498 |
+
"json_path_heading": f"$[{item_index}].inferred.heading{horizon}",
|
| 499 |
+
}
|
| 500 |
+
)
|
| 501 |
+
return rows
|
| 502 |
+
|
| 503 |
+
|
| 504 |
+
def draw_line_panel(
|
| 505 |
+
draw: ImageDraw.ImageDraw,
|
| 506 |
+
box: tuple[int, int, int, int],
|
| 507 |
+
rows: list[dict[str, Any]],
|
| 508 |
+
title: str,
|
| 509 |
+
colors: dict[str, tuple[int, int, int]],
|
| 510 |
+
) -> None:
|
| 511 |
+
x0, y0, x1, y1 = box
|
| 512 |
+
axis_font = font(15)
|
| 513 |
+
title_font = font(22, True)
|
| 514 |
+
draw.text((x0, y0 - 42), title, fill=(20, 25, 30), font=title_font)
|
| 515 |
+
draw.rectangle([x0, y0, x1, y1], outline=(210, 210, 210), width=1)
|
| 516 |
+
pad_l, pad_b, pad_t, pad_r = 64, 52, 24, 20
|
| 517 |
+
px0, py0, px1, py1 = x0 + pad_l, y0 + pad_t, x1 - pad_r, y1 - pad_b
|
| 518 |
+
max_y = max(float(r["position_error"]) for r in rows) * 1.12
|
| 519 |
+
min_h, max_h = min(HORIZONS), max(HORIZONS)
|
| 520 |
+
for tick in [0.0, 0.25, 0.50, 0.75, 1.0]:
|
| 521 |
+
y = py1 - tick * (py1 - py0)
|
| 522 |
+
val = tick * max_y
|
| 523 |
+
draw.line([px0, y, px1, y], fill=(232, 232, 232), width=1)
|
| 524 |
+
draw.text((x0 + 8, y - 8), f"{val:.2f}", fill=(70, 70, 70), font=axis_font)
|
| 525 |
+
draw.line([px0, py1, px1, py1], fill=(60, 60, 60), width=2)
|
| 526 |
+
draw.line([px0, py0, px0, py1], fill=(60, 60, 60), width=2)
|
| 527 |
+
for h in HORIZONS:
|
| 528 |
+
x = px0 + (h - min_h) / (max_h - min_h) * (px1 - px0)
|
| 529 |
+
draw.line([x, py1, x, py1 + 5], fill=(60, 60, 60), width=1)
|
| 530 |
+
draw.text((x - 10, py1 + 10), str(h), fill=(70, 70, 70), font=axis_font)
|
| 531 |
+
draw.text(((px0 + px1) // 2 - 60, y1 - 28), "rollout step", fill=(60, 60, 60), font=axis_font)
|
| 532 |
+
|
| 533 |
+
by_method: dict[str, list[dict[str, Any]]] = defaultdict(list)
|
| 534 |
+
for row in rows:
|
| 535 |
+
by_method[row["method"]].append(row)
|
| 536 |
+
for method in LEARNED_METHODS:
|
| 537 |
+
pts = []
|
| 538 |
+
for row in sorted(by_method[method], key=lambda x: int(x["horizon"])):
|
| 539 |
+
h = int(row["horizon"])
|
| 540 |
+
x = px0 + (h - min_h) / (max_h - min_h) * (px1 - px0)
|
| 541 |
+
y = py1 - float(row["position_error"]) / max_y * (py1 - py0)
|
| 542 |
+
pts.append((x, y))
|
| 543 |
+
if len(pts) >= 2:
|
| 544 |
+
draw.line(pts, fill=colors[method], width=4)
|
| 545 |
+
for x, y in pts:
|
| 546 |
+
draw.ellipse([x - 4, y - 4, x + 4, y + 4], fill=colors[method])
|
| 547 |
+
|
| 548 |
+
lx, ly = px1 - 185, py0 + 10
|
| 549 |
+
for i, method in enumerate(LEARNED_METHODS):
|
| 550 |
+
yy = ly + i * 24
|
| 551 |
+
draw.line([lx, yy + 8, lx + 24, yy + 8], fill=colors[method], width=4)
|
| 552 |
+
draw.text((lx + 32, yy), METHOD_SHORT[method], fill=(40, 40, 40), font=axis_font)
|
| 553 |
+
|
| 554 |
+
|
| 555 |
+
def draw_success_bar_panel(
|
| 556 |
+
draw: ImageDraw.ImageDraw,
|
| 557 |
+
box: tuple[int, int, int, int],
|
| 558 |
+
rows: list[dict[str, Any]],
|
| 559 |
+
title: str,
|
| 560 |
+
) -> None:
|
| 561 |
+
x0, y0, x1, y1 = box
|
| 562 |
+
axis_font = font(15)
|
| 563 |
+
small_font = font(13)
|
| 564 |
+
title_font = font(22, True)
|
| 565 |
+
draw.text((x0, y0 - 42), title, fill=(20, 25, 30), font=title_font)
|
| 566 |
+
draw.rectangle([x0, y0, x1, y1], outline=(210, 210, 210), width=1)
|
| 567 |
+
pad_l, pad_b, pad_t, pad_r = 58, 70, 24, 18
|
| 568 |
+
px0, py0, px1, py1 = x0 + pad_l, y0 + pad_t, x1 - pad_r, y1 - pad_b
|
| 569 |
+
for tick in [0, 0.25, 0.50, 0.75, 1.0]:
|
| 570 |
+
y = py1 - tick * (py1 - py0)
|
| 571 |
+
draw.line([px0, y, px1, y], fill=(232, 232, 232), width=1)
|
| 572 |
+
draw.text((x0 + 10, y - 8), f"{int(tick * 100)}", fill=(70, 70, 70), font=axis_font)
|
| 573 |
+
draw.line([px0, py1, px1, py1], fill=(60, 60, 60), width=2)
|
| 574 |
+
draw.line([px0, py0, px0, py1], fill=(60, 60, 60), width=2)
|
| 575 |
+
|
| 576 |
+
rates = {(r["method"], r["boat"]): float(r["success_rate"]) for r in rows}
|
| 577 |
+
group_w = (px1 - px0) / len(METHOD_ORDER)
|
| 578 |
+
bar_w = group_w * 0.30
|
| 579 |
+
boat_colors = {"twin": (54, 119, 191), "triangle": (218, 119, 54)}
|
| 580 |
+
for idx, method in enumerate(METHOD_ORDER):
|
| 581 |
+
cx = px0 + idx * group_w + group_w * 0.5
|
| 582 |
+
for j, boat in enumerate(BOAT_ORDER):
|
| 583 |
+
rate = rates.get((method, boat), 0.0)
|
| 584 |
+
x_left = cx + (j - 0.5) * bar_w - bar_w * 0.5
|
| 585 |
+
x_right = x_left + bar_w
|
| 586 |
+
y_top = py1 - rate * (py1 - py0)
|
| 587 |
+
draw.rectangle([x_left, y_top, x_right, py1], fill=boat_colors[boat], outline=(255, 255, 255))
|
| 588 |
+
draw.text((cx - 24, py1 + 10), METHOD_SHORT[method], fill=(55, 55, 55), font=small_font)
|
| 589 |
+
if method == "tdmpc2":
|
| 590 |
+
split_x = px0 + (idx + 1) * group_w
|
| 591 |
+
draw.line([split_x, py0, split_x, py1 + 30], fill=(80, 80, 80), width=2)
|
| 592 |
+
|
| 593 |
+
lx, ly = px1 - 180, py0 + 12
|
| 594 |
+
for i, boat in enumerate(BOAT_ORDER):
|
| 595 |
+
yy = ly + i * 24
|
| 596 |
+
draw.rectangle([lx, yy, lx + 18, yy + 14], fill=boat_colors[boat])
|
| 597 |
+
draw.text((lx + 26, yy - 2), BOAT_LABEL[boat], fill=(40, 40, 40), font=axis_font)
|
| 598 |
+
draw.text((x0 + 8, y0 + 8), "success rate (%)", fill=(70, 70, 70), font=axis_font)
|
| 599 |
+
|
| 600 |
+
|
| 601 |
+
def draw_success_by_task_panel(
|
| 602 |
+
draw: ImageDraw.ImageDraw,
|
| 603 |
+
box: tuple[int, int, int, int],
|
| 604 |
+
rows: list[dict[str, Any]],
|
| 605 |
+
boat: str,
|
| 606 |
+
title: str,
|
| 607 |
+
show_legend: bool = False,
|
| 608 |
+
) -> None:
|
| 609 |
+
x0, y0, x1, y1 = box
|
| 610 |
+
axis_font = font(15)
|
| 611 |
+
small_font = font(12)
|
| 612 |
+
title_font = font(21, True)
|
| 613 |
+
draw.text((x0, y0 - 36), title, fill=(20, 25, 30), font=title_font)
|
| 614 |
+
draw.rectangle([x0, y0, x1, y1], outline=(210, 210, 210), width=1)
|
| 615 |
+
pad_l, pad_b, pad_t, pad_r = 58, 58, 26, 16
|
| 616 |
+
px0, py0, px1, py1 = x0 + pad_l, y0 + pad_t, x1 - pad_r, y1 - pad_b
|
| 617 |
+
|
| 618 |
+
for tick in [0, 0.25, 0.50, 0.75, 1.0]:
|
| 619 |
+
y = py1 - tick * (py1 - py0)
|
| 620 |
+
draw.line([px0, y, px1, y], fill=(232, 232, 232), width=1)
|
| 621 |
+
draw.text((x0 + 10, y - 8), f"{int(tick * 100)}", fill=(70, 70, 70), font=axis_font)
|
| 622 |
+
draw.line([px0, py1, px1, py1], fill=(60, 60, 60), width=2)
|
| 623 |
+
draw.line([px0, py0, px0, py1], fill=(60, 60, 60), width=2)
|
| 624 |
+
draw.text((x0 + 8, y0 + 8), "success (%)", fill=(70, 70, 70), font=axis_font)
|
| 625 |
+
|
| 626 |
+
rates = {(r["task"], r["method"]): float(r["success_rate"]) for r in rows if r["boat"] == boat}
|
| 627 |
+
group_w = (px1 - px0) / len(TASK_ORDER)
|
| 628 |
+
bar_w = group_w * 0.70 / len(METHOD_ORDER)
|
| 629 |
+
for task_idx, task in enumerate(TASK_ORDER):
|
| 630 |
+
group_left = px0 + task_idx * group_w + group_w * 0.15
|
| 631 |
+
for method_idx, method in enumerate(METHOD_ORDER):
|
| 632 |
+
rate = rates.get((task, method), 0.0)
|
| 633 |
+
x_left = group_left + method_idx * bar_w
|
| 634 |
+
x_right = x_left + bar_w * 0.88
|
| 635 |
+
y_top = py1 - rate * (py1 - py0)
|
| 636 |
+
draw.rectangle([x_left, y_top, x_right, py1], fill=METHOD_COLORS[method], outline=(255, 255, 255))
|
| 637 |
+
label = TASK_LABEL[task]
|
| 638 |
+
tw = draw.textlength(label, font=small_font)
|
| 639 |
+
draw.text((px0 + task_idx * group_w + (group_w - tw) / 2, py1 + 12), label, fill=(45, 45, 45), font=small_font)
|
| 640 |
+
if task_idx > 0:
|
| 641 |
+
split_x = px0 + task_idx * group_w
|
| 642 |
+
draw.line([split_x, py0, split_x, py1 + 24], fill=(218, 218, 218), width=1)
|
| 643 |
+
|
| 644 |
+
if show_legend:
|
| 645 |
+
lx, ly = x0 + 78, y0 + 36
|
| 646 |
+
for i, method in enumerate(METHOD_ORDER):
|
| 647 |
+
row = i // 4
|
| 648 |
+
col = i % 4
|
| 649 |
+
xx = lx + col * 145
|
| 650 |
+
yy = ly + row * 22
|
| 651 |
+
draw.rectangle([xx, yy, xx + 16, yy + 12], fill=METHOD_COLORS[method])
|
| 652 |
+
draw.text((xx + 22, yy - 3), METHOD_SHORT[method], fill=(40, 40, 40), font=small_font)
|
| 653 |
+
|
| 654 |
+
|
| 655 |
+
def make_fig4(summaries: list[SummaryRecord]) -> None:
|
| 656 |
+
fig_dir = OUT / "fig4"
|
| 657 |
+
ensure_dir(fig_dir)
|
| 658 |
+
prediction_rows = load_prediction_rows()
|
| 659 |
+
write_rows(
|
| 660 |
+
fig_dir / "figure4_prediction_error",
|
| 661 |
+
prediction_rows,
|
| 662 |
+
[
|
| 663 |
+
"method",
|
| 664 |
+
"method_label",
|
| 665 |
+
"context_mode",
|
| 666 |
+
"horizon",
|
| 667 |
+
"position_error",
|
| 668 |
+
"heading_error",
|
| 669 |
+
"source_file",
|
| 670 |
+
"json_path_position",
|
| 671 |
+
"json_path_heading",
|
| 672 |
+
],
|
| 673 |
+
)
|
| 674 |
+
|
| 675 |
+
success_rows = aggregate_success(inferred_summaries(summaries), ("task", "boat", "method"))
|
| 676 |
+
success_rows.sort(key=lambda r: (task_sort_key(r["task"]), boat_sort_key(r["boat"]), method_sort_key(r["method"])))
|
| 677 |
+
for row in success_rows:
|
| 678 |
+
row["method_label"] = METHOD_LABEL[row["method"]]
|
| 679 |
+
row["task_label"] = TASK_LABEL[row["task"]]
|
| 680 |
+
row["boat_label"] = BOAT_LABEL[row["boat"]]
|
| 681 |
+
write_rows(
|
| 682 |
+
fig_dir / "figure4_success_by_task_boat",
|
| 683 |
+
success_rows,
|
| 684 |
+
["task", "task_label", "boat", "boat_label", "method", "method_label", "successes", "episodes", "success_rate", "source_files"],
|
| 685 |
+
)
|
| 686 |
+
source_rows = []
|
| 687 |
+
for r in sorted(inferred_summaries(summaries), key=lambda x: (task_sort_key(x.task), boat_sort_key(x.boat), method_sort_key(x.method), flow_sort_key(x.flow_type))):
|
| 688 |
+
source_rows.append(
|
| 689 |
+
{
|
| 690 |
+
"task": r.task,
|
| 691 |
+
"boat": r.boat,
|
| 692 |
+
"method": r.method,
|
| 693 |
+
"flow_type": r.flow_type,
|
| 694 |
+
"successes": r.successes,
|
| 695 |
+
"episodes": r.episodes,
|
| 696 |
+
"success_rate": r.success_rate,
|
| 697 |
+
"source_file": r.source_file,
|
| 698 |
+
"item_index": r.item_index,
|
| 699 |
+
"json_path_successes": f"$[{r.item_index}].by_context.inferred.successes",
|
| 700 |
+
"json_path_episodes": f"$[{r.item_index}].by_context.inferred.episodes",
|
| 701 |
+
}
|
| 702 |
+
)
|
| 703 |
+
write_rows(
|
| 704 |
+
fig_dir / "figure4_success_by_task_boat_source_rows",
|
| 705 |
+
source_rows,
|
| 706 |
+
[
|
| 707 |
+
"task",
|
| 708 |
+
"boat",
|
| 709 |
+
"method",
|
| 710 |
+
"flow_type",
|
| 711 |
+
"successes",
|
| 712 |
+
"episodes",
|
| 713 |
+
"success_rate",
|
| 714 |
+
"source_file",
|
| 715 |
+
"item_index",
|
| 716 |
+
"json_path_successes",
|
| 717 |
+
"json_path_episodes",
|
| 718 |
+
],
|
| 719 |
+
)
|
| 720 |
+
|
| 721 |
+
canvas = Image.new("RGB", (1800, 1100), "white")
|
| 722 |
+
draw = ImageDraw.Draw(canvas)
|
| 723 |
+
draw_line_panel(draw, (60, 88, 1740, 440), prediction_rows, "Prediction error vs rollout step", METHOD_COLORS)
|
| 724 |
+
draw_success_by_task_panel(draw, (60, 552, 860, 1030), success_rows, "twin", "Planning success by experiment: Twin", show_legend=True)
|
| 725 |
+
draw_success_by_task_panel(draw, (940, 552, 1740, 1030), success_rows, "triangle", "Planning success by experiment: Triangle", show_legend=True)
|
| 726 |
+
out = fig_dir / "figure4_placeholder.png"
|
| 727 |
+
canvas.save(out)
|
| 728 |
+
|
| 729 |
+
md = [
|
| 730 |
+
"# Figure 4 Provenance",
|
| 731 |
+
"",
|
| 732 |
+
"Purpose: quantitative placeholder with prediction error curves and planning success grouped by experiment/task.",
|
| 733 |
+
"",
|
| 734 |
+
"Generated outputs:",
|
| 735 |
+
f"- `{rel(out)}`",
|
| 736 |
+
f"- `{rel(fig_dir / 'figure4_prediction_error.tsv')}`",
|
| 737 |
+
f"- `{rel(fig_dir / 'figure4_prediction_error.csv')}`",
|
| 738 |
+
f"- `{rel(fig_dir / 'figure4_success_by_task_boat.tsv')}`",
|
| 739 |
+
f"- `{rel(fig_dir / 'figure4_success_by_task_boat.csv')}`",
|
| 740 |
+
f"- `{rel(fig_dir / 'figure4_success_by_task_boat_source_rows.tsv')}`",
|
| 741 |
+
f"- `{rel(fig_dir / 'figure4_success_by_task_boat_source_rows.csv')}`",
|
| 742 |
+
"",
|
| 743 |
+
"Panel A source:",
|
| 744 |
+
f"- `{rel(PREDICTION_JSON)}`",
|
| 745 |
+
"- JSON selectors: `$[method_index].inferred.pos{horizon}` and `$[method_index].inferred.heading{horizon}` for horizons 1, 3, 6, 8, 10, 20, 30, 40, 60.",
|
| 746 |
+
"- Included methods: `flowmo`, `leworldmodel`, `planet`, `tdmpc2`.",
|
| 747 |
+
"",
|
| 748 |
+
"Panel B source:",
|
| 749 |
+
f"- `{rel(PLANNING_DIR)}/*.json`",
|
| 750 |
+
"- JSON selectors: `$[item_index].by_context.inferred.successes` and `$[item_index].by_context.inferred.episodes`.",
|
| 751 |
+
"- Aggregation: sum successes and episodes over all flow types for each task, method, and boat.",
|
| 752 |
+
"- Row-level source entries are recorded in `figure4_success_by_task_boat_source_rows.tsv/csv` with `source_file`, `item_index`, and JSON path columns.",
|
| 753 |
+
"- Excluded diagnostic FlowMo contexts: `zero`, `shuffled`.",
|
| 754 |
+
]
|
| 755 |
+
write_text(fig_dir / "figure4_provenance.md", "\n".join(md) + "\n")
|
| 756 |
+
|
| 757 |
+
|
| 758 |
+
def draw_failure_line_panel(
|
| 759 |
+
draw: ImageDraw.ImageDraw,
|
| 760 |
+
box: tuple[int, int, int, int],
|
| 761 |
+
rows: list[dict[str, Any]],
|
| 762 |
+
boat: str,
|
| 763 |
+
title: str,
|
| 764 |
+
show_legend: bool = False,
|
| 765 |
+
) -> None:
|
| 766 |
+
x0, y0, x1, y1 = box
|
| 767 |
+
axis_font = font(14)
|
| 768 |
+
small_font = font(12)
|
| 769 |
+
title_font = font(21, True)
|
| 770 |
+
draw.text((x0, y0 - 36), title, fill=(20, 25, 30), font=title_font)
|
| 771 |
+
draw.rectangle([x0, y0, x1, y1], outline=(210, 210, 210), width=1)
|
| 772 |
+
pad_l, pad_b, pad_t, pad_r = 62, 88, 26, 22
|
| 773 |
+
px0, py0, px1, py1 = x0 + pad_l, y0 + pad_t, x1 - pad_r, y1 - pad_b
|
| 774 |
+
boat_rows = [r for r in rows if r["boat"] == boat]
|
| 775 |
+
max_fail = max(float(r["failure_percent"]) for r in boat_rows)
|
| 776 |
+
y_max = max(5.0, math.ceil((max_fail + 3.0) / 5.0) * 5.0)
|
| 777 |
+
|
| 778 |
+
for tick in [0.0, 0.25, 0.50, 0.75, 1.0]:
|
| 779 |
+
y = py1 - tick * (py1 - py0)
|
| 780 |
+
val = tick * y_max
|
| 781 |
+
draw.line([px0, y, px1, y], fill=(232, 232, 232), width=1)
|
| 782 |
+
draw.text((x0 + 8, y - 8), f"{val:.0f}", fill=(70, 70, 70), font=axis_font)
|
| 783 |
+
draw.line([px0, py1, px1, py1], fill=(60, 60, 60), width=2)
|
| 784 |
+
draw.line([px0, py0, px0, py1], fill=(60, 60, 60), width=2)
|
| 785 |
+
draw.text((x0 + 8, y0 + 8), "failure (%)", fill=(70, 70, 70), font=axis_font)
|
| 786 |
+
|
| 787 |
+
flow_x = {}
|
| 788 |
+
for i, flow in enumerate(FLOW_ORDER):
|
| 789 |
+
x = px0 + i / (len(FLOW_ORDER) - 1) * (px1 - px0)
|
| 790 |
+
flow_x[flow] = x
|
| 791 |
+
draw.line([x, py1, x, py1 + 5], fill=(60, 60, 60), width=1)
|
| 792 |
+
label = FLOW_LABEL[flow]
|
| 793 |
+
draw.text((x - 28, py1 + 10), label, fill=(55, 55, 55), font=small_font)
|
| 794 |
+
|
| 795 |
+
failures = {(r["method"], r["flow_type"]): float(r["failure_percent"]) for r in boat_rows}
|
| 796 |
+
for method in METHOD_ORDER:
|
| 797 |
+
pts = []
|
| 798 |
+
for flow in FLOW_ORDER:
|
| 799 |
+
value = failures.get((method, flow), 0.0)
|
| 800 |
+
x = flow_x[flow]
|
| 801 |
+
y = py1 - (value / y_max) * (py1 - py0)
|
| 802 |
+
pts.append((x, y))
|
| 803 |
+
draw.line(pts, fill=METHOD_COLORS[method], width=3)
|
| 804 |
+
for x, y in pts:
|
| 805 |
+
draw.ellipse([x - 3, y - 3, x + 3, y + 3], fill=METHOD_COLORS[method])
|
| 806 |
+
|
| 807 |
+
if show_legend:
|
| 808 |
+
lx, ly = x0 + 80, y0 + 34
|
| 809 |
+
for i, method in enumerate(METHOD_ORDER):
|
| 810 |
+
row = i // 4
|
| 811 |
+
col = i % 4
|
| 812 |
+
xx = lx + col * 145
|
| 813 |
+
yy = ly + row * 22
|
| 814 |
+
draw.line([xx, yy + 7, xx + 22, yy + 7], fill=METHOD_COLORS[method], width=3)
|
| 815 |
+
draw.text((xx + 28, yy - 2), METHOD_SHORT[method], fill=(40, 40, 40), font=small_font)
|
| 816 |
+
|
| 817 |
+
|
| 818 |
+
def make_fig5(summaries: list[SummaryRecord]) -> None:
|
| 819 |
+
fig_dir = OUT / "fig5"
|
| 820 |
+
ensure_dir(fig_dir)
|
| 821 |
+
rows = aggregate_success(inferred_summaries(summaries), ("boat", "flow_type", "method"))
|
| 822 |
+
rows.sort(key=lambda r: (boat_sort_key(r["boat"]), flow_sort_key(r["flow_type"]), method_sort_key(r["method"])))
|
| 823 |
+
for row in rows:
|
| 824 |
+
row["boat_label"] = BOAT_LABEL[row["boat"]]
|
| 825 |
+
row["flow_label"] = FLOW_LABEL[row["flow_type"]]
|
| 826 |
+
row["method_label"] = METHOD_LABEL[row["method"]]
|
| 827 |
+
row["failure_rate"] = 1.0 - float(row["success_rate"])
|
| 828 |
+
row["failure_percent"] = 100.0 * row["failure_rate"]
|
| 829 |
+
row["success_percent"] = 100.0 * float(row["success_rate"])
|
| 830 |
+
write_rows(
|
| 831 |
+
fig_dir / "figure5_failure_by_flow",
|
| 832 |
+
rows,
|
| 833 |
+
[
|
| 834 |
+
"boat",
|
| 835 |
+
"boat_label",
|
| 836 |
+
"flow_type",
|
| 837 |
+
"flow_label",
|
| 838 |
+
"method",
|
| 839 |
+
"method_label",
|
| 840 |
+
"successes",
|
| 841 |
+
"episodes",
|
| 842 |
+
"success_rate",
|
| 843 |
+
"success_percent",
|
| 844 |
+
"failure_rate",
|
| 845 |
+
"failure_percent",
|
| 846 |
+
"source_files",
|
| 847 |
+
],
|
| 848 |
+
)
|
| 849 |
+
source_rows = []
|
| 850 |
+
for r in sorted(inferred_summaries(summaries), key=lambda x: (boat_sort_key(x.boat), flow_sort_key(x.flow_type), method_sort_key(x.method), task_sort_key(x.task))):
|
| 851 |
+
source_rows.append(
|
| 852 |
+
{
|
| 853 |
+
"boat": r.boat,
|
| 854 |
+
"flow_type": r.flow_type,
|
| 855 |
+
"method": r.method,
|
| 856 |
+
"task": r.task,
|
| 857 |
+
"successes": r.successes,
|
| 858 |
+
"episodes": r.episodes,
|
| 859 |
+
"success_rate": r.success_rate,
|
| 860 |
+
"failure_rate": 1.0 - r.success_rate,
|
| 861 |
+
"source_file": r.source_file,
|
| 862 |
+
"item_index": r.item_index,
|
| 863 |
+
"json_path_successes": f"$[{r.item_index}].by_context.inferred.successes",
|
| 864 |
+
"json_path_episodes": f"$[{r.item_index}].by_context.inferred.episodes",
|
| 865 |
+
}
|
| 866 |
+
)
|
| 867 |
+
write_rows(
|
| 868 |
+
fig_dir / "figure5_failure_by_flow_source_rows",
|
| 869 |
+
source_rows,
|
| 870 |
+
[
|
| 871 |
+
"boat",
|
| 872 |
+
"flow_type",
|
| 873 |
+
"method",
|
| 874 |
+
"task",
|
| 875 |
+
"successes",
|
| 876 |
+
"episodes",
|
| 877 |
+
"success_rate",
|
| 878 |
+
"failure_rate",
|
| 879 |
+
"source_file",
|
| 880 |
+
"item_index",
|
| 881 |
+
"json_path_successes",
|
| 882 |
+
"json_path_episodes",
|
| 883 |
+
],
|
| 884 |
+
)
|
| 885 |
+
|
| 886 |
+
canvas = Image.new("RGB", (1800, 980), "white")
|
| 887 |
+
draw = ImageDraw.Draw(canvas)
|
| 888 |
+
title_font = font(25, True)
|
| 889 |
+
draw.text((24, 20), "Figure 5 placeholder: failure rate by flow family", fill=(20, 25, 30), font=title_font)
|
| 890 |
+
draw_failure_line_panel(draw, (60, 110, 1740, 480), rows, "twin", "Twin", show_legend=True)
|
| 891 |
+
draw_failure_line_panel(draw, (60, 590, 1740, 900), rows, "triangle", "Triangle", show_legend=False)
|
| 892 |
+
out = fig_dir / "figure5_placeholder_failure_lines.png"
|
| 893 |
+
canvas.save(out)
|
| 894 |
+
|
| 895 |
+
md = [
|
| 896 |
+
"# Figure 5 Provenance",
|
| 897 |
+
"",
|
| 898 |
+
"Purpose: flow-family breakdown of downstream planning failure rates. Failure rate is used because many success rates are 100% or near 100%.",
|
| 899 |
+
"",
|
| 900 |
+
"Generated outputs:",
|
| 901 |
+
f"- `{rel(out)}`",
|
| 902 |
+
f"- `{rel(fig_dir / 'figure5_failure_by_flow.tsv')}`",
|
| 903 |
+
f"- `{rel(fig_dir / 'figure5_failure_by_flow.csv')}`",
|
| 904 |
+
f"- `{rel(fig_dir / 'figure5_failure_by_flow_source_rows.tsv')}`",
|
| 905 |
+
f"- `{rel(fig_dir / 'figure5_failure_by_flow_source_rows.csv')}`",
|
| 906 |
+
"",
|
| 907 |
+
"Source:",
|
| 908 |
+
f"- `{rel(PLANNING_DIR)}/*.json`",
|
| 909 |
+
"- JSON selectors: `$[item_index].by_context.inferred.successes` and `$[item_index].by_context.inferred.episodes`.",
|
| 910 |
+
"- Aggregation: sum successes and episodes over all tasks for each method, boat, and flow type.",
|
| 911 |
+
"- Failure rate: `1 - successes / episodes`.",
|
| 912 |
+
"- Row-level source entries are recorded in `figure5_failure_by_flow_source_rows.tsv/csv` with `source_file`, `item_index`, and JSON path columns.",
|
| 913 |
+
"- Excluded diagnostic FlowMo contexts: `zero`, `shuffled`.",
|
| 914 |
+
]
|
| 915 |
+
write_text(fig_dir / "figure5_provenance.md", "\n".join(md) + "\n")
|
| 916 |
+
|
| 917 |
+
|
| 918 |
+
def make_table1(summaries: list[SummaryRecord]) -> None:
|
| 919 |
+
table_dir = OUT / "tables"
|
| 920 |
+
ensure_dir(table_dir)
|
| 921 |
+
records = inferred_summaries(summaries)
|
| 922 |
+
by_key = {(r.task, r.boat, r.flow_type, r.method): r for r in records}
|
| 923 |
+
data_rows: list[dict[str, Any]] = []
|
| 924 |
+
latex_rows: list[list[str]] = []
|
| 925 |
+
for task in TASK_ORDER:
|
| 926 |
+
for boat in BOAT_ORDER:
|
| 927 |
+
for flow in FLOW_ORDER:
|
| 928 |
+
row: dict[str, Any] = {
|
| 929 |
+
"task": task,
|
| 930 |
+
"task_label": TASK_LABEL[task],
|
| 931 |
+
"boat": boat,
|
| 932 |
+
"boat_label": BOAT_LABEL[boat],
|
| 933 |
+
"flow_type": flow,
|
| 934 |
+
"flow_label": FLOW_LABEL[flow],
|
| 935 |
+
}
|
| 936 |
+
latex_row = [TASK_LABEL[task], BOAT_LABEL[boat], FLOW_LABEL[flow]]
|
| 937 |
+
for method in METHOD_ORDER:
|
| 938 |
+
rec = by_key.get((task, boat, flow, method))
|
| 939 |
+
if rec is None:
|
| 940 |
+
row[f"{method}_success_rate"] = ""
|
| 941 |
+
row[f"{method}_successes"] = ""
|
| 942 |
+
row[f"{method}_episodes"] = ""
|
| 943 |
+
row[f"{method}_source"] = ""
|
| 944 |
+
latex_row.append("--")
|
| 945 |
+
else:
|
| 946 |
+
row[f"{method}_success_rate"] = rec.success_rate
|
| 947 |
+
row[f"{method}_success_percent"] = 100.0 * rec.success_rate
|
| 948 |
+
row[f"{method}_successes"] = rec.successes
|
| 949 |
+
row[f"{method}_episodes"] = rec.episodes
|
| 950 |
+
row[f"{method}_source"] = rec.source_file
|
| 951 |
+
row[f"{method}_json_path"] = f"$[{rec.item_index}].by_context.inferred.success_rate"
|
| 952 |
+
latex_row.append(pct(rec.success_rate, 0))
|
| 953 |
+
data_rows.append(row)
|
| 954 |
+
latex_rows.append(latex_row)
|
| 955 |
+
|
| 956 |
+
fields = ["task", "task_label", "boat", "boat_label", "flow_type", "flow_label"]
|
| 957 |
+
for method in METHOD_ORDER:
|
| 958 |
+
fields += [
|
| 959 |
+
f"{method}_success_rate",
|
| 960 |
+
f"{method}_success_percent",
|
| 961 |
+
f"{method}_successes",
|
| 962 |
+
f"{method}_episodes",
|
| 963 |
+
f"{method}_source",
|
| 964 |
+
f"{method}_json_path",
|
| 965 |
+
]
|
| 966 |
+
write_rows(table_dir / "table1_success_by_task_boat_flow", data_rows, fields)
|
| 967 |
+
|
| 968 |
+
header = ["Task", "Boat", "Flow"] + [METHOD_SHORT[m] for m in METHOD_ORDER]
|
| 969 |
+
write_table(
|
| 970 |
+
table_dir / "table1_success_by_task_boat_flow.tex",
|
| 971 |
+
header,
|
| 972 |
+
latex_rows,
|
| 973 |
+
"Planning success rate by task, boat, and flow family. Values are percentages over 50 episodes per setting; FlowMo diagnostic zero/shuffled contexts are excluded.",
|
| 974 |
+
"tab:planning_success_task_boat_flow",
|
| 975 |
+
)
|
| 976 |
+
|
| 977 |
+
md = [
|
| 978 |
+
"# Table 1 Provenance",
|
| 979 |
+
"",
|
| 980 |
+
"Purpose: success rate for every task, boat, flow family, and method.",
|
| 981 |
+
"",
|
| 982 |
+
"Generated outputs:",
|
| 983 |
+
f"- `{rel(table_dir / 'table1_success_by_task_boat_flow.tex')}`",
|
| 984 |
+
f"- `{rel(table_dir / 'table1_success_by_task_boat_flow.tsv')}`",
|
| 985 |
+
f"- `{rel(table_dir / 'table1_success_by_task_boat_flow.csv')}`",
|
| 986 |
+
"",
|
| 987 |
+
"Source:",
|
| 988 |
+
f"- `{rel(PLANNING_DIR)}/*.json`",
|
| 989 |
+
"- JSON selector per cell: `$[item_index].by_context.inferred.success_rate`.",
|
| 990 |
+
"- Companion fields in TSV/CSV include `$[item_index].by_context.inferred.successes` and `episodes`.",
|
| 991 |
+
"- Excluded diagnostic FlowMo contexts: `zero`, `shuffled`.",
|
| 992 |
+
]
|
| 993 |
+
write_text(table_dir / "table1_provenance.md", "\n".join(md) + "\n")
|
| 994 |
+
|
| 995 |
+
|
| 996 |
+
def make_table2(episodes: list[EpisodeRecord]) -> None:
|
| 997 |
+
table_dir = OUT / "tables"
|
| 998 |
+
ensure_dir(table_dir)
|
| 999 |
+
records = inferred_episodes(episodes)
|
| 1000 |
+
grouped: dict[tuple[str, str, str], list[EpisodeRecord]] = defaultdict(list)
|
| 1001 |
+
sources: dict[tuple[str, str, str], set[str]] = defaultdict(set)
|
| 1002 |
+
for r in records:
|
| 1003 |
+
key = (r.task, r.boat, r.method)
|
| 1004 |
+
grouped[key].append(r)
|
| 1005 |
+
sources[key].add(r.source_file)
|
| 1006 |
+
|
| 1007 |
+
data_rows: list[dict[str, Any]] = []
|
| 1008 |
+
latex_rows: list[list[str]] = []
|
| 1009 |
+
for task in TASK_ORDER:
|
| 1010 |
+
for boat in BOAT_ORDER:
|
| 1011 |
+
for method in METHOD_ORDER:
|
| 1012 |
+
key = (task, boat, method)
|
| 1013 |
+
items = grouped[key]
|
| 1014 |
+
if not items:
|
| 1015 |
+
continue
|
| 1016 |
+
final_distance_mean = sum(r.final_distance for r in items) / len(items)
|
| 1017 |
+
min_goal_distance_mean = sum(r.mean_min_goal_distance for r in items) / len(items)
|
| 1018 |
+
success_items = [r for r in items if r.success and r.energy is not None]
|
| 1019 |
+
energy_success_mean = sum(float(r.energy) for r in success_items) / len(success_items) if success_items else None
|
| 1020 |
+
row = {
|
| 1021 |
+
"task": task,
|
| 1022 |
+
"task_label": TASK_LABEL[task],
|
| 1023 |
+
"boat": boat,
|
| 1024 |
+
"boat_label": BOAT_LABEL[boat],
|
| 1025 |
+
"method": method,
|
| 1026 |
+
"method_label": METHOD_LABEL[method],
|
| 1027 |
+
"episodes": len(items),
|
| 1028 |
+
"successful_energy_episodes": len(success_items),
|
| 1029 |
+
"final_distance_mean": final_distance_mean,
|
| 1030 |
+
"mean_min_goal_distance": min_goal_distance_mean,
|
| 1031 |
+
"energy_success_mean": energy_success_mean if energy_success_mean is not None else "",
|
| 1032 |
+
"source_files": ";".join(sorted(sources[key])),
|
| 1033 |
+
"json_selector": "$[item_index].results[*] filtered by context_mode == inferred",
|
| 1034 |
+
}
|
| 1035 |
+
data_rows.append(row)
|
| 1036 |
+
latex_rows.append(
|
| 1037 |
+
[
|
| 1038 |
+
TASK_LABEL[task],
|
| 1039 |
+
BOAT_LABEL[boat],
|
| 1040 |
+
METHOD_LABEL[method],
|
| 1041 |
+
fmt(final_distance_mean),
|
| 1042 |
+
fmt(energy_success_mean),
|
| 1043 |
+
]
|
| 1044 |
+
)
|
| 1045 |
+
write_rows(
|
| 1046 |
+
table_dir / "table2_energy_distance_by_task_boat_method",
|
| 1047 |
+
data_rows,
|
| 1048 |
+
[
|
| 1049 |
+
"task",
|
| 1050 |
+
"task_label",
|
| 1051 |
+
"boat",
|
| 1052 |
+
"boat_label",
|
| 1053 |
+
"method",
|
| 1054 |
+
"method_label",
|
| 1055 |
+
"episodes",
|
| 1056 |
+
"successful_energy_episodes",
|
| 1057 |
+
"final_distance_mean",
|
| 1058 |
+
"mean_min_goal_distance",
|
| 1059 |
+
"energy_success_mean",
|
| 1060 |
+
"source_files",
|
| 1061 |
+
"json_selector",
|
| 1062 |
+
],
|
| 1063 |
+
)
|
| 1064 |
+
write_table(
|
| 1065 |
+
table_dir / "table2_energy_distance_by_task_boat_method.tex",
|
| 1066 |
+
["Task", "Boat", "Method", "Final dist.", "Energy (succ.)"],
|
| 1067 |
+
latex_rows,
|
| 1068 |
+
"Planning distance and energy by task, boat, and method, aggregated over all flow families. Final distance is averaged over all episodes; energy is averaged over successful episodes.",
|
| 1069 |
+
"tab:planning_energy_distance_task_boat",
|
| 1070 |
+
)
|
| 1071 |
+
|
| 1072 |
+
md = [
|
| 1073 |
+
"# Table 2 Provenance",
|
| 1074 |
+
"",
|
| 1075 |
+
"Purpose: distance and energy metrics by task, boat, and method.",
|
| 1076 |
+
"",
|
| 1077 |
+
"Generated outputs:",
|
| 1078 |
+
f"- `{rel(table_dir / 'table2_energy_distance_by_task_boat_method.tex')}`",
|
| 1079 |
+
f"- `{rel(table_dir / 'table2_energy_distance_by_task_boat_method.tsv')}`",
|
| 1080 |
+
f"- `{rel(table_dir / 'table2_energy_distance_by_task_boat_method.csv')}`",
|
| 1081 |
+
"",
|
| 1082 |
+
"Source:",
|
| 1083 |
+
f"- `{rel(PLANNING_DIR)}/*.json`",
|
| 1084 |
+
"- JSON selector: `$[item_index].results[*]`, filtered to `context_mode == inferred`.",
|
| 1085 |
+
"- Final distance: mean of `final_distance` over all filtered episodes.",
|
| 1086 |
+
"- Energy: mean of `energy` over filtered successful episodes only.",
|
| 1087 |
+
"- The TSV/CSV also includes `mean_min_goal_distance`, computed from the same filtered episodes.",
|
| 1088 |
+
"- Excluded diagnostic FlowMo contexts: `zero`, `shuffled`.",
|
| 1089 |
+
]
|
| 1090 |
+
write_text(table_dir / "table2_provenance.md", "\n".join(md) + "\n")
|
| 1091 |
+
|
| 1092 |
+
|
| 1093 |
+
def make_probe_table() -> None:
|
| 1094 |
+
table_dir = OUT / "tables"
|
| 1095 |
+
ensure_dir(table_dir)
|
| 1096 |
+
data = read_json(PROBE_JSON)
|
| 1097 |
+
split = data["splits"]["test"]
|
| 1098 |
+
feature_order = ["z", "c", "z_c"]
|
| 1099 |
+
target_order = ["momentum", "local_flow", "episode_drift"]
|
| 1100 |
+
rows: list[dict[str, Any]] = []
|
| 1101 |
+
latex_rows: list[list[str]] = []
|
| 1102 |
+
for target in target_order:
|
| 1103 |
+
latex_row = [target.replace("_", " ")]
|
| 1104 |
+
for feature in feature_order:
|
| 1105 |
+
entry = split[target][feature]
|
| 1106 |
+
rows.append(
|
| 1107 |
+
{
|
| 1108 |
+
"split": "test",
|
| 1109 |
+
"target": target,
|
| 1110 |
+
"feature": feature,
|
| 1111 |
+
"r2_mean": entry["r2_mean"],
|
| 1112 |
+
"rmse": entry["rmse"],
|
| 1113 |
+
"source_file": rel(PROBE_JSON),
|
| 1114 |
+
"json_path_r2": f"$.splits.test.{target}.{feature}.r2_mean",
|
| 1115 |
+
"json_path_rmse": f"$.splits.test.{target}.{feature}.rmse",
|
| 1116 |
+
}
|
| 1117 |
+
)
|
| 1118 |
+
latex_row.append(fmt(entry["r2_mean"], 3))
|
| 1119 |
+
for feature in feature_order:
|
| 1120 |
+
latex_row.append(fmt(split[target][feature]["rmse"], 3))
|
| 1121 |
+
latex_rows.append(latex_row)
|
| 1122 |
+
write_rows(
|
| 1123 |
+
table_dir / "table3_probe_diagnostics",
|
| 1124 |
+
rows,
|
| 1125 |
+
["split", "target", "feature", "r2_mean", "rmse", "source_file", "json_path_r2", "json_path_rmse"],
|
| 1126 |
+
)
|
| 1127 |
+
write_table(
|
| 1128 |
+
table_dir / "table3_probe_diagnostics.tex",
|
| 1129 |
+
["Target", "z R2", "c R2", "z+c R2", "z RMSE", "c RMSE", "z+c RMSE"],
|
| 1130 |
+
latex_rows,
|
| 1131 |
+
"Frozen linear probe diagnostics for FlowMo representations on the test split.",
|
| 1132 |
+
"tab:flowmo_probe_diagnostics",
|
| 1133 |
+
)
|
| 1134 |
+
md = [
|
| 1135 |
+
"# Table 3 Provenance",
|
| 1136 |
+
"",
|
| 1137 |
+
"Purpose: frozen linear probe diagnostics for FlowMo latent variables.",
|
| 1138 |
+
"",
|
| 1139 |
+
"Generated outputs:",
|
| 1140 |
+
f"- `{rel(table_dir / 'table3_probe_diagnostics.tex')}`",
|
| 1141 |
+
f"- `{rel(table_dir / 'table3_probe_diagnostics.tsv')}`",
|
| 1142 |
+
f"- `{rel(table_dir / 'table3_probe_diagnostics.csv')}`",
|
| 1143 |
+
"",
|
| 1144 |
+
"Source:",
|
| 1145 |
+
f"- `{rel(PROBE_JSON)}`",
|
| 1146 |
+
"- JSON selectors: `$.splits.test.<target>.<feature>.r2_mean` and `$.splits.test.<target>.<feature>.rmse`.",
|
| 1147 |
+
"- Probe model: frozen FlowMo features with ridge regression, as reported by the JSON metadata.",
|
| 1148 |
+
]
|
| 1149 |
+
write_text(table_dir / "table3_provenance.md", "\n".join(md) + "\n")
|
| 1150 |
+
|
| 1151 |
+
|
| 1152 |
+
def make_overview() -> None:
|
| 1153 |
+
files = sorted(p for p in OUT.rglob("*") if p.is_file())
|
| 1154 |
+
lines = [
|
| 1155 |
+
"# Paper Artifact Export",
|
| 1156 |
+
"",
|
| 1157 |
+
"Generated from local experiment outputs under `experiments/reports/`.",
|
| 1158 |
+
"",
|
| 1159 |
+
"Important source files:",
|
| 1160 |
+
f"- `{rel(PREDICTION_JSON)}`",
|
| 1161 |
+
f"- `{rel(PROBE_JSON)}`",
|
| 1162 |
+
f"- `{rel(PLANNING_DIR)}/*.json`",
|
| 1163 |
+
f"- `{rel(GIF_DIR)}/*.gif`",
|
| 1164 |
+
"",
|
| 1165 |
+
"Generated files:",
|
| 1166 |
+
]
|
| 1167 |
+
for p in files:
|
| 1168 |
+
lines.append(f"- `{rel(p)}`")
|
| 1169 |
+
write_text(OUT / "README.md", "\n".join(lines) + "\n")
|
| 1170 |
+
|
| 1171 |
+
|
| 1172 |
+
def validate_inputs() -> None:
|
| 1173 |
+
missing = [p for p in [PREDICTION_JSON, PROBE_JSON, PLANNING_DIR, GIF_DIR] if not p.exists()]
|
| 1174 |
+
if missing:
|
| 1175 |
+
raise FileNotFoundError("Missing required experiment outputs: " + ", ".join(str(p) for p in missing))
|
| 1176 |
+
planning_files = sorted(PLANNING_DIR.glob("*.json"))
|
| 1177 |
+
if len(planning_files) != len(TASK_ORDER) * len(BOAT_ORDER) * len(FLOW_ORDER):
|
| 1178 |
+
raise RuntimeError(f"Expected {len(TASK_ORDER) * len(BOAT_ORDER) * len(FLOW_ORDER)} planning JSON files, found {len(planning_files)}")
|
| 1179 |
+
|
| 1180 |
+
|
| 1181 |
+
def main() -> None:
|
| 1182 |
+
validate_inputs()
|
| 1183 |
+
if OUT.exists():
|
| 1184 |
+
shutil.rmtree(OUT)
|
| 1185 |
+
ensure_dir(OUT)
|
| 1186 |
+
summaries, episodes = load_planning()
|
| 1187 |
+
extract_fig3()
|
| 1188 |
+
make_fig4(summaries)
|
| 1189 |
+
make_fig5(summaries)
|
| 1190 |
+
make_table1(summaries)
|
| 1191 |
+
make_table2(episodes)
|
| 1192 |
+
make_probe_table()
|
| 1193 |
+
make_overview()
|
| 1194 |
+
print(f"Wrote paper artifacts to {OUT}")
|
| 1195 |
+
|
| 1196 |
+
|
| 1197 |
+
if __name__ == "__main__":
|
| 1198 |
+
main()
|
experiments/no_flow_los_controller/README.md
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# No-Flow LOS Controller Baseline
|
| 2 |
+
|
| 3 |
+
Traditional line-of-sight controller that estimates pose from the clean image and ignores external flow.
|
experiments/no_flow_los_controller/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""No-flow line-of-sight controller experiment package."""
|
experiments/no_flow_los_controller/checkpoint/.gitkeep
ADDED
|
File without changes
|
experiments/no_flow_los_controller/result/.gitkeep
ADDED
|
File without changes
|
experiments/no_flow_los_controller/src/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""No-flow line-of-sight controller source package."""
|
experiments/no_flow_los_controller/src/config.py
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""No-flow line-of-sight controller config."""
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
def default_config():
|
| 5 |
+
return {"goal": [8.0, 8.0], "gain": 0.65}
|
experiments/no_flow_los_controller/src/controller.py
ADDED
|
@@ -0,0 +1,11 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""No-flow line-of-sight controller."""
|
| 2 |
+
|
| 3 |
+
import numpy as np
|
| 4 |
+
|
| 5 |
+
from experiments.shared.src.control.geometric import goal_action
|
| 6 |
+
from experiments.shared.src.vision.pose_from_image import estimate_pose_from_clean_image
|
| 7 |
+
|
| 8 |
+
def plan(state, task, config):
|
| 9 |
+
pose = estimate_pose_from_clean_image(state)
|
| 10 |
+
goal = np.asarray(task["goal"], dtype=np.float32)
|
| 11 |
+
return goal_action(pose, goal, int(config["action_dim"]), float(config["gain"]), 0.6)
|
experiments/no_flow_los_controller/src/evaluate.py
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""No-flow line-of-sight controller evaluation."""
|
| 2 |
+
|
| 3 |
+
from experiments.no_flow_los_controller.src.config import default_config
|
| 4 |
+
from experiments.no_flow_los_controller.src.controller import plan
|
| 5 |
+
|
| 6 |
+
def evaluate(config):
|
| 7 |
+
cfg = default_config() | config
|
| 8 |
+
return plan(config["image"], {"goal": cfg["goal"]}, cfg)
|
experiments/oracle_flow_los_controller/README.md
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Oracle-Flow LOS Controller Reference
|
| 2 |
+
|
| 3 |
+
Line-of-sight controller with access to the true local simulator flow for feed-forward compensation.
|
| 4 |
+
|
| 5 |
+
This is an oracle-information reference for a simple geometric controller, not a full dynamics-MPC upper bound.
|
experiments/oracle_flow_los_controller/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""Oracle-flow line-of-sight controller experiment package."""
|
experiments/oracle_flow_los_controller/checkpoint/.gitkeep
ADDED
|
File without changes
|
experiments/oracle_flow_los_controller/result/.gitkeep
ADDED
|
File without changes
|
experiments/oracle_flow_los_controller/src/__init__.py
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
"""Oracle-flow line-of-sight controller source package."""
|
experiments/oracle_flow_los_controller/src/config.py
ADDED
|
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Oracle-flow line-of-sight controller config."""
|
| 2 |
+
|
| 3 |
+
|
| 4 |
+
def default_config():
|
| 5 |
+
return {"goal": [8.0, 8.0], "gain": 0.65, "flow_gain": 1.0}
|
experiments/oracle_flow_los_controller/src/controller.py
ADDED
|
@@ -0,0 +1,19 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Oracle-flow line-of-sight controller."""
|
| 2 |
+
|
| 3 |
+
import numpy as np
|
| 4 |
+
|
| 5 |
+
from experiments.shared.src.control.geometric import goal_action
|
| 6 |
+
from experiments.shared.src.vision.pose_from_image import estimate_pose_from_clean_image
|
| 7 |
+
|
| 8 |
+
def plan(state, true_flow, task, config):
|
| 9 |
+
pose = estimate_pose_from_clean_image(state)
|
| 10 |
+
goal = np.asarray(task["goal"], dtype=np.float32)
|
| 11 |
+
return goal_action(
|
| 12 |
+
pose,
|
| 13 |
+
goal,
|
| 14 |
+
int(config["action_dim"]),
|
| 15 |
+
float(config["gain"]),
|
| 16 |
+
0.6,
|
| 17 |
+
drift=np.asarray(true_flow, dtype=np.float32),
|
| 18 |
+
drift_gain=float(config["flow_gain"]),
|
| 19 |
+
)
|
experiments/oracle_flow_los_controller/src/evaluate.py
ADDED
|
@@ -0,0 +1,8 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
"""Oracle-flow line-of-sight controller evaluation."""
|
| 2 |
+
|
| 3 |
+
from experiments.oracle_flow_los_controller.src.config import default_config
|
| 4 |
+
from experiments.oracle_flow_los_controller.src.controller import plan
|
| 5 |
+
|
| 6 |
+
def evaluate(config):
|
| 7 |
+
cfg = default_config() | config
|
| 8 |
+
return plan(config["image"], config["true_flow"], {"goal": cfg["goal"]}, cfg)
|
experiments/plot_task_schematics.py
ADDED
|
@@ -0,0 +1,171 @@
|
|
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|
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|
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|
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|
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|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
from __future__ import annotations
|
| 2 |
+
|
| 3 |
+
from pathlib import Path
|
| 4 |
+
|
| 5 |
+
from PIL import Image, ImageDraw
|
| 6 |
+
|
| 7 |
+
from driftwm.utils import ensure_dir
|
| 8 |
+
|
| 9 |
+
|
| 10 |
+
OUT_DIR = Path("experiments/reports/figures/task_schematics")
|
| 11 |
+
WORKSPACE = (0.0, 10.0, 0.0, 10.0)
|
| 12 |
+
|
| 13 |
+
BG = (247, 250, 252)
|
| 14 |
+
BORDER = (45, 62, 80)
|
| 15 |
+
START = (35, 91, 140)
|
| 16 |
+
GOAL = (203, 62, 74)
|
| 17 |
+
ACTIVE = (30, 139, 88)
|
| 18 |
+
PASSIVE = (145, 153, 163)
|
| 19 |
+
FLOW = (68, 135, 205)
|
| 20 |
+
SWITCH = (238, 184, 72)
|
| 21 |
+
|
| 22 |
+
|
| 23 |
+
def w2p(x: float, y: float, size: int = 640, pad: int = 58) -> tuple[int, int]:
|
| 24 |
+
xmin, xmax, ymin, ymax = WORKSPACE
|
| 25 |
+
px = int(pad + (x - xmin) / (xmax - xmin) * (size - 2 * pad))
|
| 26 |
+
py = int(size - pad - (y - ymin) / (ymax - ymin) * (size - 2 * pad))
|
| 27 |
+
return px, py
|
| 28 |
+
|
| 29 |
+
|
| 30 |
+
def draw_arrow(
|
| 31 |
+
draw: ImageDraw.ImageDraw,
|
| 32 |
+
p0: tuple[int, int],
|
| 33 |
+
p1: tuple[int, int],
|
| 34 |
+
color: tuple[int, int, int],
|
| 35 |
+
width: int = 6,
|
| 36 |
+
head: int = 18,
|
| 37 |
+
) -> None:
|
| 38 |
+
import math
|
| 39 |
+
|
| 40 |
+
draw.line((p0, p1), fill=color, width=width)
|
| 41 |
+
dx = p1[0] - p0[0]
|
| 42 |
+
dy = p1[1] - p0[1]
|
| 43 |
+
angle = math.atan2(dy, dx)
|
| 44 |
+
for delta in (2.55, -2.55):
|
| 45 |
+
a = angle + delta
|
| 46 |
+
q = (int(p1[0] + head * math.cos(a)), int(p1[1] + head * math.sin(a)))
|
| 47 |
+
draw.line((p1, q), fill=color, width=width)
|
| 48 |
+
|
| 49 |
+
|
| 50 |
+
def draw_polyline_arrow(
|
| 51 |
+
draw: ImageDraw.ImageDraw,
|
| 52 |
+
pts: list[tuple[int, int]],
|
| 53 |
+
color: tuple[int, int, int],
|
| 54 |
+
width: int = 6,
|
| 55 |
+
) -> None:
|
| 56 |
+
if len(pts) < 2:
|
| 57 |
+
return
|
| 58 |
+
draw.line(pts, fill=color, width=width, joint="curve")
|
| 59 |
+
draw_arrow(draw, pts[-2], pts[-1], color, width=width)
|
| 60 |
+
|
| 61 |
+
|
| 62 |
+
def circle(draw: ImageDraw.ImageDraw, center: tuple[int, int], radius: int, color: tuple[int, int, int], width: int = 0) -> None:
|
| 63 |
+
box = (center[0] - radius, center[1] - radius, center[0] + radius, center[1] + radius)
|
| 64 |
+
if width:
|
| 65 |
+
draw.ellipse(box, outline=color, width=width)
|
| 66 |
+
else:
|
| 67 |
+
draw.ellipse(box, fill=color)
|
| 68 |
+
|
| 69 |
+
|
| 70 |
+
def base(size: int = 640) -> tuple[Image.Image, ImageDraw.ImageDraw]:
|
| 71 |
+
img = Image.new("RGB", (size, size), BG)
|
| 72 |
+
draw = ImageDraw.Draw(img)
|
| 73 |
+
draw.rectangle((58, 58, size - 58, size - 58), outline=BORDER, width=3)
|
| 74 |
+
return img, draw
|
| 75 |
+
|
| 76 |
+
|
| 77 |
+
def draw_flow_arrows(draw: ImageDraw.ImageDraw, arrows: list[tuple[tuple[float, float], tuple[float, float]]]) -> None:
|
| 78 |
+
for start, end in arrows:
|
| 79 |
+
draw_arrow(draw, w2p(*start), w2p(*end), FLOW, width=5, head=15)
|
| 80 |
+
|
| 81 |
+
|
| 82 |
+
def save(img: Image.Image, name: str) -> None:
|
| 83 |
+
ensure_dir(OUT_DIR / "clean")
|
| 84 |
+
path = OUT_DIR / "clean" / name
|
| 85 |
+
img.save(path)
|
| 86 |
+
print(path)
|
| 87 |
+
|
| 88 |
+
|
| 89 |
+
def reach_target() -> Image.Image:
|
| 90 |
+
img, draw = base()
|
| 91 |
+
start = w2p(2.0, 2.0)
|
| 92 |
+
goal = w2p(8.0, 8.0)
|
| 93 |
+
draw_arrow(draw, start, goal, ACTIVE)
|
| 94 |
+
circle(draw, start, 13, START)
|
| 95 |
+
circle(draw, goal, 18, GOAL, width=6)
|
| 96 |
+
return img
|
| 97 |
+
|
| 98 |
+
|
| 99 |
+
def station_keeping() -> Image.Image:
|
| 100 |
+
img, draw = base()
|
| 101 |
+
center = w2p(5.0, 5.0)
|
| 102 |
+
circle(draw, center, 72, GOAL, width=6)
|
| 103 |
+
draw.line((center[0] - 22, center[1], center[0] + 22, center[1]), fill=GOAL, width=4)
|
| 104 |
+
draw.line((center[0], center[1] - 22, center[0], center[1] + 22), fill=GOAL, width=4)
|
| 105 |
+
draw_flow_arrows(draw, [((6.8, 6.8), (5.85, 5.95)), ((6.6, 3.3), (5.8, 4.2)), ((3.5, 6.8), (4.25, 5.9))])
|
| 106 |
+
pts = [w2p(4.55, 4.25), w2p(5.2, 4.45), w2p(5.45, 5.15), w2p(4.85, 5.45), w2p(4.65, 4.8), w2p(5.0, 5.02)]
|
| 107 |
+
draw_polyline_arrow(draw, pts, ACTIVE, width=6)
|
| 108 |
+
circle(draw, pts[0], 12, START)
|
| 109 |
+
return img
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
def waypoint_square() -> Image.Image:
|
| 113 |
+
img, draw = base()
|
| 114 |
+
start = w2p(2.0, 2.0)
|
| 115 |
+
pts = [w2p(2.5, 2.5), w2p(7.5, 2.5), w2p(7.5, 7.5), w2p(2.5, 7.5)]
|
| 116 |
+
draw_polyline_arrow(draw, [start] + pts, ACTIVE, width=6)
|
| 117 |
+
circle(draw, start, 13, START)
|
| 118 |
+
for p in pts:
|
| 119 |
+
circle(draw, p, 13, GOAL)
|
| 120 |
+
return img
|
| 121 |
+
|
| 122 |
+
|
| 123 |
+
def waypoint_zigzag() -> Image.Image:
|
| 124 |
+
img, draw = base()
|
| 125 |
+
start = w2p(2.0, 2.0)
|
| 126 |
+
pts = [w2p(2.5, 7.0), w2p(4.2, 3.0), w2p(5.8, 7.0), w2p(7.5, 3.0)]
|
| 127 |
+
draw_polyline_arrow(draw, [start] + pts, ACTIVE, width=6)
|
| 128 |
+
circle(draw, start, 13, START)
|
| 129 |
+
for p in pts:
|
| 130 |
+
circle(draw, p, 13, GOAL)
|
| 131 |
+
return img
|
| 132 |
+
|
| 133 |
+
|
| 134 |
+
def make_contact_sheet(names: list[str]) -> None:
|
| 135 |
+
ensure_dir(OUT_DIR)
|
| 136 |
+
thumbs = [Image.open(OUT_DIR / "clean" / name).resize((240, 240), Image.Resampling.LANCZOS) for name in names]
|
| 137 |
+
sheet = Image.new("RGB", (2 * 280 + 40, 2 * 300 + 40), (246, 249, 251))
|
| 138 |
+
draw = ImageDraw.Draw(sheet)
|
| 139 |
+
labels = [name.removeprefix("task_").removesuffix(".png") for name in names]
|
| 140 |
+
for i, (thumb, label) in enumerate(zip(thumbs, labels, strict=True)):
|
| 141 |
+
row, col = divmod(i, 2)
|
| 142 |
+
x = 20 + col * 280
|
| 143 |
+
y = 20 + row * 300
|
| 144 |
+
sheet.paste(thumb, (x, y))
|
| 145 |
+
draw.text((x, y + 250), label, fill=(35, 45, 58))
|
| 146 |
+
path = OUT_DIR / "task_schematics_contact_sheet.png"
|
| 147 |
+
sheet.save(path)
|
| 148 |
+
print(path)
|
| 149 |
+
|
| 150 |
+
|
| 151 |
+
def main() -> None:
|
| 152 |
+
tasks = {
|
| 153 |
+
"task_reach_target.png": reach_target(),
|
| 154 |
+
"task_station_keeping.png": station_keeping(),
|
| 155 |
+
"task_waypoint_square.png": waypoint_square(),
|
| 156 |
+
"task_waypoint_zigzag.png": waypoint_zigzag(),
|
| 157 |
+
}
|
| 158 |
+
for name, img in tasks.items():
|
| 159 |
+
save(img, name)
|
| 160 |
+
make_contact_sheet(
|
| 161 |
+
[
|
| 162 |
+
"task_reach_target.png",
|
| 163 |
+
"task_station_keeping.png",
|
| 164 |
+
"task_waypoint_square.png",
|
| 165 |
+
"task_waypoint_zigzag.png",
|
| 166 |
+
]
|
| 167 |
+
)
|
| 168 |
+
|
| 169 |
+
|
| 170 |
+
if __name__ == "__main__":
|
| 171 |
+
main()
|
experiments/reports/paper_artifacts/README.md
ADDED
|
@@ -0,0 +1,66 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
# Paper Artifact Export
|
| 2 |
+
|
| 3 |
+
Generated from local experiment outputs under `experiments/reports/`.
|
| 4 |
+
|
| 5 |
+
Important source files:
|
| 6 |
+
- `experiments/reports/paper_prediction.json`
|
| 7 |
+
- `experiments/reports/paper_flowmo_latent_probes.json`
|
| 8 |
+
- `experiments/reports/paper_planning/*.json`
|
| 9 |
+
- `experiments/reports/paper_planning/gifs/*.gif`
|
| 10 |
+
|
| 11 |
+
Generated files:
|
| 12 |
+
- `experiments/reports/paper_artifacts/README.md`
|
| 13 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.csv`
|
| 14 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.tsv`
|
| 15 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_placeholder_contact_sheet.png`
|
| 16 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_provenance.md`
|
| 17 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_first_frame000.png`
|
| 18 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_last_frame149.png`
|
| 19 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_middle_frame075.png`
|
| 20 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_first_frame000.png`
|
| 21 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_last_frame097.png`
|
| 22 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_middle_frame049.png`
|
| 23 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_first_frame000.png`
|
| 24 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_last_frame272.png`
|
| 25 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_middle_frame136.png`
|
| 26 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_first_frame000.png`
|
| 27 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_last_frame319.png`
|
| 28 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_middle_frame160.png`
|
| 29 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_first_frame000.png`
|
| 30 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_last_frame419.png`
|
| 31 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_middle_frame210.png`
|
| 32 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_first_frame000.png`
|
| 33 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_last_frame097.png`
|
| 34 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_middle_frame049.png`
|
| 35 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_first_frame000.png`
|
| 36 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_last_frame351.png`
|
| 37 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_middle_frame176.png`
|
| 38 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_first_frame000.png`
|
| 39 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_last_frame382.png`
|
| 40 |
+
- `experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_middle_frame191.png`
|
| 41 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_placeholder.png`
|
| 42 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_prediction_error.csv`
|
| 43 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_prediction_error.tsv`
|
| 44 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_provenance.md`
|
| 45 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_success_by_task_boat.csv`
|
| 46 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_success_by_task_boat.tsv`
|
| 47 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_success_by_task_boat_source_rows.csv`
|
| 48 |
+
- `experiments/reports/paper_artifacts/fig4/figure4_success_by_task_boat_source_rows.tsv`
|
| 49 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_failure_by_flow.csv`
|
| 50 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_failure_by_flow.tsv`
|
| 51 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_failure_by_flow_source_rows.csv`
|
| 52 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_failure_by_flow_source_rows.tsv`
|
| 53 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_placeholder_failure_lines.png`
|
| 54 |
+
- `experiments/reports/paper_artifacts/fig5/figure5_provenance.md`
|
| 55 |
+
- `experiments/reports/paper_artifacts/tables/table1_provenance.md`
|
| 56 |
+
- `experiments/reports/paper_artifacts/tables/table1_success_by_task_boat_flow.csv`
|
| 57 |
+
- `experiments/reports/paper_artifacts/tables/table1_success_by_task_boat_flow.tex`
|
| 58 |
+
- `experiments/reports/paper_artifacts/tables/table1_success_by_task_boat_flow.tsv`
|
| 59 |
+
- `experiments/reports/paper_artifacts/tables/table2_energy_distance_by_task_boat_method.csv`
|
| 60 |
+
- `experiments/reports/paper_artifacts/tables/table2_energy_distance_by_task_boat_method.tex`
|
| 61 |
+
- `experiments/reports/paper_artifacts/tables/table2_energy_distance_by_task_boat_method.tsv`
|
| 62 |
+
- `experiments/reports/paper_artifacts/tables/table2_provenance.md`
|
| 63 |
+
- `experiments/reports/paper_artifacts/tables/table3_probe_diagnostics.csv`
|
| 64 |
+
- `experiments/reports/paper_artifacts/tables/table3_probe_diagnostics.tex`
|
| 65 |
+
- `experiments/reports/paper_artifacts/tables/table3_probe_diagnostics.tsv`
|
| 66 |
+
- `experiments/reports/paper_artifacts/tables/table3_provenance.md`
|
experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.csv
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
task,boat,method,context_mode,flow_type,episode,frame_name,frame_index,gif_frames,source_gif,output_png
|
| 2 |
+
reach_target,twin,flowmo,inferred,uniform,0,first,0,420,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_first_frame000.png
|
| 3 |
+
reach_target,twin,flowmo,inferred,uniform,0,middle,210,420,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_middle_frame210.png
|
| 4 |
+
reach_target,twin,flowmo,inferred,uniform,0,last,419,420,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_last_frame419.png
|
| 5 |
+
reach_target,triangle,flowmo,inferred,uniform,0,first,0,150,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_first_frame000.png
|
| 6 |
+
reach_target,triangle,flowmo,inferred,uniform,0,middle,75,150,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_middle_frame075.png
|
| 7 |
+
reach_target,triangle,flowmo,inferred,uniform,0,last,149,150,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_last_frame149.png
|
| 8 |
+
station_keeping,twin,flowmo,inferred,vortex_center,0,first,0,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_first_frame000.png
|
| 9 |
+
station_keeping,twin,flowmo,inferred,vortex_center,0,middle,49,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_middle_frame049.png
|
| 10 |
+
station_keeping,twin,flowmo,inferred,vortex_center,0,last,97,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_last_frame097.png
|
| 11 |
+
station_keeping,triangle,flowmo,inferred,vortex_center,0,first,0,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_first_frame000.png
|
| 12 |
+
station_keeping,triangle,flowmo,inferred,vortex_center,0,middle,49,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_middle_frame049.png
|
| 13 |
+
station_keeping,triangle,flowmo,inferred,vortex_center,0,last,97,98,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_last_frame097.png
|
| 14 |
+
waypoint_square,twin,flowmo,inferred,gradient,0,first,0,352,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_first_frame000.png
|
| 15 |
+
waypoint_square,twin,flowmo,inferred,gradient,0,middle,176,352,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_middle_frame176.png
|
| 16 |
+
waypoint_square,twin,flowmo,inferred,gradient,0,last,351,352,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_last_frame351.png
|
| 17 |
+
waypoint_square,triangle,flowmo,inferred,gradient,0,first,0,273,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_first_frame000.png
|
| 18 |
+
waypoint_square,triangle,flowmo,inferred,gradient,0,middle,136,273,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_middle_frame136.png
|
| 19 |
+
waypoint_square,triangle,flowmo,inferred,gradient,0,last,272,273,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_last_frame272.png
|
| 20 |
+
waypoint_zigzag,twin,flowmo,inferred,random_fourier,0,first,0,383,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_first_frame000.png
|
| 21 |
+
waypoint_zigzag,twin,flowmo,inferred,random_fourier,0,middle,191,383,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_middle_frame191.png
|
| 22 |
+
waypoint_zigzag,twin,flowmo,inferred,random_fourier,0,last,382,383,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_last_frame382.png
|
| 23 |
+
waypoint_zigzag,triangle,flowmo,inferred,random_fourier,0,first,0,320,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_first_frame000.png
|
| 24 |
+
waypoint_zigzag,triangle,flowmo,inferred,random_fourier,0,middle,160,320,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_middle_frame160.png
|
| 25 |
+
waypoint_zigzag,triangle,flowmo,inferred,random_fourier,0,last,319,320,experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif,experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_last_frame319.png
|
experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.tsv
ADDED
|
@@ -0,0 +1,25 @@
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|
| 1 |
+
task boat method context_mode flow_type episode frame_name frame_index gif_frames source_gif output_png
|
| 2 |
+
reach_target twin flowmo inferred uniform 0 first 0 420 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_first_frame000.png
|
| 3 |
+
reach_target twin flowmo inferred uniform 0 middle 210 420 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_middle_frame210.png
|
| 4 |
+
reach_target twin flowmo inferred uniform 0 last 419 420 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_reach_target_uniform_ep000_last_frame419.png
|
| 5 |
+
reach_target triangle flowmo inferred uniform 0 first 0 150 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_first_frame000.png
|
| 6 |
+
reach_target triangle flowmo inferred uniform 0 middle 75 150 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_middle_frame075.png
|
| 7 |
+
reach_target triangle flowmo inferred uniform 0 last 149 150 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_last_frame149.png
|
| 8 |
+
station_keeping twin flowmo inferred vortex_center 0 first 0 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_first_frame000.png
|
| 9 |
+
station_keeping twin flowmo inferred vortex_center 0 middle 49 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_middle_frame049.png
|
| 10 |
+
station_keeping twin flowmo inferred vortex_center 0 last 97 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_station_keeping_vortex_center_ep000_last_frame097.png
|
| 11 |
+
station_keeping triangle flowmo inferred vortex_center 0 first 0 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_first_frame000.png
|
| 12 |
+
station_keeping triangle flowmo inferred vortex_center 0 middle 49 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_middle_frame049.png
|
| 13 |
+
station_keeping triangle flowmo inferred vortex_center 0 last 97 98 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_station_keeping_vortex_center_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_last_frame097.png
|
| 14 |
+
waypoint_square twin flowmo inferred gradient 0 first 0 352 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_first_frame000.png
|
| 15 |
+
waypoint_square twin flowmo inferred gradient 0 middle 176 352 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_middle_frame176.png
|
| 16 |
+
waypoint_square twin flowmo inferred gradient 0 last 351 352 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_square_gradient_ep000_last_frame351.png
|
| 17 |
+
waypoint_square triangle flowmo inferred gradient 0 first 0 273 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_first_frame000.png
|
| 18 |
+
waypoint_square triangle flowmo inferred gradient 0 middle 136 273 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_middle_frame136.png
|
| 19 |
+
waypoint_square triangle flowmo inferred gradient 0 last 272 273 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_last_frame272.png
|
| 20 |
+
waypoint_zigzag twin flowmo inferred random_fourier 0 first 0 383 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_first_frame000.png
|
| 21 |
+
waypoint_zigzag twin flowmo inferred random_fourier 0 middle 191 383 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_middle_frame191.png
|
| 22 |
+
waypoint_zigzag twin flowmo inferred random_fourier 0 last 382 383 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_twin_waypoint_zigzag_random_fourier_ep000_last_frame382.png
|
| 23 |
+
waypoint_zigzag triangle flowmo inferred random_fourier 0 first 0 320 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_first_frame000.png
|
| 24 |
+
waypoint_zigzag triangle flowmo inferred random_fourier 0 middle 160 320 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_middle_frame160.png
|
| 25 |
+
waypoint_zigzag triangle flowmo inferred random_fourier 0 last 319 320 experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_last_frame319.png
|
experiments/reports/paper_artifacts/fig3/figure3_placeholder_contact_sheet.png
ADDED
|
Git LFS Details
|
experiments/reports/paper_artifacts/fig3/figure3_provenance.md
ADDED
|
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| 1 |
+
# Figure 3 Provenance
|
| 2 |
+
|
| 3 |
+
Purpose: qualitative task rollouts extracted from experiment GIFs.
|
| 4 |
+
|
| 5 |
+
Selected method/context: `flowmo` / `inferred`.
|
| 6 |
+
Selected episode: `0`.
|
| 7 |
+
|
| 8 |
+
Selected flows by task:
|
| 9 |
+
- `reach_target`: `uniform`
|
| 10 |
+
- `station_keeping`: `vortex_center`
|
| 11 |
+
- `waypoint_square`: `gradient`
|
| 12 |
+
- `waypoint_zigzag`: `random_fourier`
|
| 13 |
+
|
| 14 |
+
Frame rule: for each source GIF, extracted `first = 0`, `middle = n_frames // 2`, and `last = n_frames - 1`.
|
| 15 |
+
|
| 16 |
+
Generated outputs:
|
| 17 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_placeholder_contact_sheet.png`
|
| 18 |
+
- `experiments/reports/paper_artifacts/fig3/frames/`
|
| 19 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.tsv`
|
| 20 |
+
- `experiments/reports/paper_artifacts/fig3/figure3_frame_manifest.csv`
|
| 21 |
+
|
| 22 |
+
Source GIFs:
|
| 23 |
+
- `experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_reach_target_uniform_ep000.gif`
|
| 24 |
+
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- `experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_square_gradient_ep000.gif`
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- `experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000.gif`
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- `experiments/reports/paper_planning/gifs/image_planning_flowmo_inferred_twin_reach_target_uniform_ep000.gif`
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_first_frame000.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_reach_target_uniform_ep000_last_frame149.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_first_frame000.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_station_keeping_vortex_center_ep000_middle_frame049.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_square_gradient_ep000_first_frame000.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_first_frame000.png
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experiments/reports/paper_artifacts/fig3/frames/fig3_flowmo_inferred_triangle_waypoint_zigzag_random_fourier_ep000_last_frame319.png
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