visit water buckets 2 #79
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The waypoint.py file was previously added in a commit, because it was rebased from another branch that used waypoint.py before it was removed from the repo.
| from .common.modules.position_global import PositionGlobal | ||
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| # Earth radius in meters | ||
| EARTH_RADIUS = 6378137 |
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Good job breaking this out to a constant
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| def waypoint_distance(point_1: PositionGlobal, point_2: PositionGlobal) -> "tuple[bool, float]": | ||
| """Return the great-circle distance of two points Earth, using Haversine's |
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TIL that we don't have an accepted format for docstrings 💀. Nothing to change here but just a quirk we didn't care to catch in prev PRs.
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| lat1, lon1, lat2, lon2 = map( | ||
| math.radians, | ||
| [ |
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prefer tuple over lists for uses cases like this
| and (True, distance) otherwise, where distance is the great-circle | ||
| distance between point_1 and point_2. | ||
| """ | ||
| # this function only calculates distance for waypoints with the same |
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Add this blurb in the docstring
| ], | ||
| ) | ||
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| dlat = lat2 - lat1 |
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don't use contractions in variables names
| """ | ||
| # this function only calculates distance for waypoints with the same | ||
| # altitude | ||
| if point_1.altitude != point_2.altitude: |
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Can you test how badly it affects accuracy if we ignore altitude difference/take the average, since we add the radius of the Earth I can see the error being insignificant
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Move tests to the same file and split with classes
| def find_optimal_path( | ||
| origin: PositionGlobal, buckets: "list[PositionGlobal]", buckets_at_once: int = 2 | ||
| ) -> "tuple[bool, list[PositionGlobal]]": | ||
| """Find an optimal itinerary of waypoints, given that we must |
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Add a reference to the algo you're using
| if not success: | ||
| return False, None | ||
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| for permutation in itertools.permutations(sorted_buckets): |
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If we're doing permutations why are we sorting the buckets
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oh LOL coming from C++ I thought the list must be sorted to iterate over all possible permutations.
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| success, path = find_optimal_path(origin, buckets, 2) | ||
| assert success | ||
| assert path == [ |
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I trust this is the optimal path but it's hard to verify that at a glance. Add a test where the critical path is obvious (3 waypoints, 2 close by one much further; you don't need to base them off real locations)
Find the optimal itinerary, given an origin waypoint (the source of water) and a list of bucket waypoints. We can only visit a fixed number of buckets before we must return to the origin waypoint to fetch more water each time.
Finishes task https://app.asana.com/0/0/1209038151009011/f