def compute_errors(known):
for i, p in known.iterrows():
lat_err = p.modern_lat - p.pred_lat
lon_err = p.modern_lon - p.pred_lon
sq_err = lat_err**2 + lon_err**2
modern_coords = (p.modern_lat, p.modern_lon)
pred_coords = (p.pred_lat, p.pred_lon)
dist_err = vincenty(modern_coords, pred_coords).miles
known.loc[i, 'lat_err'] = lat_err
known.loc[i, 'lon_err'] = lon_err
known.loc[i, 'sq_err'] = sq_err
known.loc[i, 'dist_err'] = dist_err
def main(filename, model):
places = common.read_places()
known, unknown = common.split_places(places)
validate_each(known, model)
compute_errors(known)
known.to_csv(filename, encoding='cp1252')
if __name__ == '__main__':
modelname = sys.argv[1]
model = common.construct_model(modelname)
filename = os.path.join(common.PTOL_HOME, 'Data',
'validate_%s.csv' % modelname)
main(filename, model)
def _construct_and_fill_model(self):
super()._construct_and_fill_model()
self.device_ids = sly.env.remap_gpu_devices([self._config[GPU_DEVICE]])
self.model = construct_model(sly.TaskPaths.MODEL_DIR)
sly.logger.info('Weights are loaded.')
title = ' '.join(os.path.basename(filename)[0:-4].split('_'))
common.write_kml_file(filename, None, known, unknown)
common.write_csv_file(filename[0:-4] + '.csv', known, unknown)
common.write_map_file(filename[0:-4] + '.pdf', known, unknown, 30, 24, 300, 'ptol_name', title)
common.write_map_file(filename[0:-4] + '.png', known, unknown, 30, 24, 300, 'ptol_name', title)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Predict unknown Ptolemy places.')
parser.add_argument('--model', help='prediction model to use')
parser.add_argument('--sgdb', help='read from sgdb with given prefix')
parser.add_argument('--xlsx', help='xlsx to read from instead of sgdb')
parser.add_argument('--output', help='output filename')
args = parser.parse_args()
model = common.construct_model(args.model)
if args.sgdb:
places = common.read_places(args.sgdb)
elif args.xlsx:
places = common.read_places_xlsx(args.xlsx)
else:
sys.stderr.write('must specify one of --sgdb or --xlsx')
exit(1)
if args.output:
output = args.output
else:
output = os.path.join(common.PTOL_HOME, 'Data', '%s.kml' % args.model)
main(output, model, places)
common.write_map_file(filename[0:-4] + '.pdf', known, unknown, 30, 24, 300,
'ptol_name', title)
common.write_map_file(filename[0:-4] + '.png', known, unknown, 30, 24, 300,
'ptol_name', title)
if __name__ == '__main__':
parser = argparse.ArgumentParser(
description='Predict unknown Ptolemy places.')
parser.add_argument('--model', help='prediction model to use')
parser.add_argument('--sgdb', help='read from sgdb with given prefix')
parser.add_argument('--xlsx', help='xlsx to read from instead of sgdb')
parser.add_argument('--output', help='output filename')
args = parser.parse_args()
model = common.construct_model(args.model)
if args.sgdb:
places = common.read_places(args.sgdb)
elif args.xlsx:
places = common.read_places_xlsx(args.xlsx)
else:
sys.stderr.write('must specify one of --sgdb or --xlsx')
exit(1)
if args.output:
output = args.output
else:
output = os.path.join(common.PTOL_HOME, 'Data', '%s.kml' % args.model)
main(output, model, places)
known.loc[known.iloc[test,:].index, 'pred_lon'] = testy[0][1]
def compute_errors(known):
for i, p in known.iterrows():
lat_err = p.modern_lat - p.pred_lat
lon_err = p.modern_lon - p.pred_lon
sq_err = lat_err ** 2 + lon_err ** 2
modern_coords = (p.modern_lat, p.modern_lon)
pred_coords = (p.pred_lat, p.pred_lon)
dist_err = vincenty(modern_coords, pred_coords).miles
known.loc[i, 'lat_err'] = lat_err
known.loc[i, 'lon_err'] = lon_err
known.loc[i, 'sq_err'] = sq_err
known.loc[i, 'dist_err'] = dist_err
def main(filename, model):
places = common.read_places()
known, unknown = common.split_places(places)
validate_each(known, model)
compute_errors(known)
known.to_csv(filename, encoding='cp1252')
if __name__ == '__main__':
modelname = sys.argv[1]
model = common.construct_model(modelname)
filename = os.path.join(common.PTOL_HOME, 'Data', 'validate_%s.csv' % modelname)
main(filename, model)