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Cache and load starmap #25

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129 changes: 66 additions & 63 deletions promis/gui/main.py
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Original file line number Diff line number Diff line change
Expand Up @@ -275,7 +275,7 @@ def load_map_data(req: RunRequest):
with open(path, 'rb'):
uam = PolarMap.load(path)
has_cache = True
print("found cache map data in loadmapdata")
print(f"Found cached map data in file with id uam_{hash_val}")
except FileNotFoundError:
dir_path = os.path.join(program_storage_path, "cache")
os.makedirs(dir_path, exist_ok=True)
Expand Down Expand Up @@ -314,88 +314,91 @@ def calculate_star_map(req: RunRequest, hash_val: int):

star_map_hash_val = create_hash_starmap(req, dynamic_layer, hash_val)

# load the cache info
#try:
# with open(f"./cache/starmap_{star_map_hash_val}.pickle", 'rb') as f:
# print("found cache star map in starmap")
#except FileNotFoundError:
# create polar map
path = path_of_cache_or_config(f"starmap_{star_map_hash_val}.pickle")

# apply uncertainty to all osm fetched map feature
loc_type_table = _get_location_type_table()
loc_to_uncertainty = dict()
for entry in loc_type_table:
if entry.std_dev != 0:
loc_to_uncertainty[entry.location_type] = (entry.std_dev**2) * eye(2)
try:
# try to load the cached StaRMap info
with open(path, 'rb') as f:
print(f"Found cached StaR Map in file with id starmap_{star_map_hash_val}")
star_map = StaRMap.load(path)

except FileNotFoundError:
# create polar map
# apply uncertainty to all osm fetched map feature
loc_type_table = _get_location_type_table()
loc_to_uncertainty = dict()
for entry in loc_type_table:
if entry.std_dev != 0:
loc_to_uncertainty[entry.location_type] = (entry.std_dev**2) * eye(2)

carte_map = polar_map.to_cartesian()
carte_map.apply_covariance(loc_to_uncertainty)
carte_map = polar_map.to_cartesian()
carte_map.apply_covariance(loc_to_uncertainty)

polar_map = carte_map.to_polar()
polar_map = carte_map.to_polar()

# create all markers, lines and polygons to uam
for marker in markers:
if marker.location_type == "":
continue
# create all markers, lines and polygons to uam
for marker in markers:
if marker.location_type == "":
continue

polar_marker = PolarLocation(marker.latlng[1],
marker.latlng[0],
location_type=marker.location_type)
if marker.std_dev != 0:
cartesian_marker = polar_marker.to_cartesian(origin)
cartesian_marker.covariance = (marker.std_dev**2) * eye(2)
polar_marker = cartesian_marker.to_polar(origin)
polar_marker = PolarLocation(marker.latlng[1],
marker.latlng[0],
location_type=marker.location_type)
if marker.std_dev != 0:
cartesian_marker = polar_marker.to_cartesian(origin)
cartesian_marker.covariance = (marker.std_dev**2) * eye(2)
polar_marker = cartesian_marker.to_polar(origin)

polar_map.features.append(polar_marker)
polar_map.features.append(polar_marker)

for polyline in polylines:
if polyline.location_type == "":
continue
locations = []
for location in polyline.latlngs:
locations.append(PolarLocation(location[1], location[0]))
for polyline in polylines:
if polyline.location_type == "":
continue
locations = []
for location in polyline.latlngs:
locations.append(PolarLocation(location[1], location[0]))

polyline_feature = PolarPolyLine(locations, location_type=polyline.location_type)
polyline_feature = PolarPolyLine(locations, location_type=polyline.location_type)

if polyline.std_dev != 0:
cartesian_polyline = polyline_feature.to_cartesian(origin)
cartesian_polyline.covariance = (polyline.std_dev**2) * eye(2)
polyline_feature = cartesian_polyline.to_polar(origin)
if polyline.std_dev != 0:
cartesian_polyline = polyline_feature.to_cartesian(origin)
cartesian_polyline.covariance = (polyline.std_dev**2) * eye(2)
polyline_feature = cartesian_polyline.to_polar(origin)

polar_map.features.append(polyline_feature)
polar_map.features.append(polyline_feature)

for polygon in polygons:
if polygon.location_type == "":
continue
locations = []
for location in polygon.latlngs:
locations.append(PolarLocation(location[1], location[0]))
for polygon in polygons:
if polygon.location_type == "":
continue
locations = []
for location in polygon.latlngs:
locations.append(PolarLocation(location[1], location[0]))

polygon_feature = PolarPolygon(locations, location_type=polygon.location_type)
polygon_feature = PolarPolygon(locations, location_type=polygon.location_type)

if polygon.std_dev != 0:
cartesian_polygon = polygon_feature.to_cartesian(origin)
cartesian_polygon.covariance = (polygon.std_dev**2) * eye(2)
polygon_feature = cartesian_polygon.to_polar(origin)
if polygon.std_dev != 0:
cartesian_polygon = polygon_feature.to_cartesian(origin)
cartesian_polygon.covariance = (polygon.std_dev**2) * eye(2)
polygon_feature = cartesian_polygon.to_polar(origin)

polar_map.features.append(polygon_feature)
polar_map.features.append(polygon_feature)


uam = polar_map.to_cartesian()
uam = polar_map.to_cartesian()

# Setting up the probabilistic spatial relations from the UAM
star_map = StaRMap(uam)
# Setting up the probabilistic spatial relations from the UAM
star_map = StaRMap(uam)

# Initializing the StaR Map on a raster of points evenly spaced out across the mission area,
# sampling 25 random variants of the UAM for estimating the spatial relation parameters
support_resolutions = req.support_resolutions
evaluation_points = CartesianRasterBand(origin, support_resolutions, width, height)
# Initializing the StaR Map on a raster of points evenly spaced out across the mission area,
# sampling 25 random variants of the UAM for estimating the spatial relation parameters
support_resolutions = req.support_resolutions
evaluation_points = CartesianRasterBand(origin, support_resolutions, width, height)

star_map.initialize(evaluation_points, sample_size, logic)
star_map.initialize(evaluation_points, sample_size, logic)

# origin, width, height, num_iteration, num_improvement
# origin, width, height, num_iteration, num_improvement

#star_map.save(f"./cache/starmap_{star_map_hash_val}.pickle")
star_map.save(path)

app.star_map = star_map

Expand All @@ -407,7 +410,7 @@ def inference(req: RunRequest, hash_val: int):
#try:
# with open(f"./cache/starmap_{hashVal}.pickle", 'rb') as f:
# star_map = StaRMap.load(f"./cache/starmap_{hashVal}.pickle")
# print("found cache star map in inference")
# print(f"Found cached StaR Map in file with id starmap_{star_map_hash_val} in inference step")
#except FileNotFoundError:
# raise HTTPException(status_code=404, detail="No star map found on this request.")

Expand Down