|
@@ -22,13 +22,12 @@ def main():
|
|
|
|
|
|
p_expe_id = args.expeId
|
|
|
|
|
|
-
|
|
|
# connect to Mongo db and collect data
|
|
|
client = MongoClient(cfg.default_host)
|
|
|
db = client.sin3d
|
|
|
|
|
|
query = {
|
|
|
- 'data.msg.experimentName': "CalibrationMeasurement",
|
|
|
+ 'data.msg.experimentName': "CalibrationMeasurement",
|
|
|
'data.msgId': "EXPERIMENT_VALIDATED"
|
|
|
}
|
|
|
|
|
@@ -52,11 +51,18 @@ def main():
|
|
|
|
|
|
experiment_user_thresholds = []
|
|
|
experiment_error_thresholds = []
|
|
|
- for id, val in enumerate(user_data['msg']['extracts']):
|
|
|
+ for val in user_data['msg']['extracts']:
|
|
|
+ threshold_id = int(val['index'])
|
|
|
experiment_user_thresholds.append(val['quality'])
|
|
|
- experiment_error_thresholds.append((int(val['quality'] - threshold_img[id])))
|
|
|
+ error = (val['quality'] - threshold_img[threshold_id])
|
|
|
+ error_squared = error * error
|
|
|
+ experiment_error_thresholds.append(error_squared)
|
|
|
|
|
|
- print(user_id, experiment_user_thresholds, experiment_error_thresholds, np.mean(experiment_error_thresholds))
|
|
|
+ print('----------------------------------------------')
|
|
|
+ print('User', user_id)
|
|
|
+ print(experiment_user_thresholds)
|
|
|
+ print(list(map(lambda x: str('%.2f' % x), experiment_error_thresholds)))
|
|
|
+ print(np.mean(experiment_error_thresholds))
|
|
|
|
|
|
if __name__== "__main__":
|
|
|
- main()
|
|
|
+ main()
|