Hacktoberfest 2026: le issue che i maintainer hanno segnato per ottobre, aperte e adatte ai principianti. Sfoglia le issue Hacktoberfest

entities don't handle being set to np.inf

Aperta
  • Qualcosa non va?
#133 7 commenti 0 reazioni 0 assegnatari Vedi su GitHub

Nessuno ha ancora preso questa issue.

Valutazione

Difficoltà
3/5
Tempo stimato
1-2 giorni
Idoneità per principianti
42/100
Tipo di issue
Bug
Chiarezza
Abbastanza chiara
Stato di attività
Ferma
Stack tecnologico
numpy, python
Ambito
backend

Direzione di ricerca

Parti dalle chiamate Python cmd_interface.set mostrate nel control script e segui come il service gestisce i valori delle entità. Riproduci il caso con np.inf, quindi verifica che il service segnali un errore o vada intenzionalmente in crash invece di rimanere bloccato; nell’issue non è indicato alcun file sorgente o test specifico.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

My data taking scripts ran into an edge case where it tried to set an entity to np.inf. The script just hung. I didn't even see an error in the service logs. I think the dripline should catch this case and try to intentionally crash or throw an error.

To go into more detail, here is the relevant portion of my control script.

                popt_reflection, pcov_reflection = data_lorentzian_fit(s11_pow, freq, 'reflection')
                perr_reflection = np.sqrt(np.diag(pcov_reflection))

                print('Reflection lorentzian fitted parameters')
                print(popt_reflection)
                self.cmd_interface.set('f_reflection', popt_reflection[0])
                self.cmd_interface.set('sig_f_reflection', perr_reflection[0])
                self.cmd_interface.set('Q_reflection', popt_reflection[1])
                self.cmd_interface.set('sig_Q_reflection', perr_reflection[1])
                self.cmd_interface.set('dy_reflection', popt_reflection[2])
                self.cmd_interface.set('sig_dy_reflection', perr_reflection[2])
                self.cmd_interface.set('C_reflection', popt_reflection[3])
                self.cmd_interface.set('sig_C_reflection', perr_reflection[3])

My script couldn't perform the fit on the VNA trace.

 Setting na_measurement_status to start_measurement
Logging list of endpoints
Switching to transmission path
Switching to reflection path
Switching to transmission path
VNA reflection measurement
Setting na_measurement_status to start_measurement
Logging list of endpoints
Switching to transmission path
Transmission lorentzian fitted parameters
[1.61968618e+10 1.59075036e+04 2.62957230e-01 3.45835612e-03]
Switching to reflection path
/usr/local/lib/python3.7/site-packages/scipy/optimize/minpack.py:829: OptimizeWarning: Covariance of the parameters could not be estimated
  category=OptimizeWarning)
Reflection lorentzian fitted parameters
[1.61903696e+10 4.84379319e+00 2.84176343e+02 2.84231409e+02]

I think when I get an OptimizeWarning error, the values of my pcov are np.inf, so it tried to set sig_f_reflection to np.inf and just hung without making any sort of progress.

➜  ~ kubectl logs -f double-precision-logger-dripline-python-deployment-6b7fbf8d4b7h --tail 20 
{'timestamp': '2021-03-22T16:32:18.386845Z', 'sensor_name': 'Q_transmission', 'value_cal': 15907.503649437182, 'value_raw': 15907.503649437182}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:18.399052Z', 'sensor_name': 'sig_Q_transmission', 'value_cal': 570.3355496234211, 'value_raw': 570.3355496234211}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:18.411096Z', 'sensor_name': 'dy_transmission', 'value_cal': 0.26295723019139855, 'value_raw': 0.26295723019139855}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:18.423272Z', 'sensor_name': 'sig_dy_transmission', 'value_cal': 0.010107652156098478, 'value_raw': 0.010107652156098478}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:18.436062Z', 'sensor_name': 'C_transmission', 'value_cal': 0.003458356118361542, 'value_raw': 0.003458356118361542}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:18.449049Z', 'sensor_name': 'sig_C_transmission', 'value_cal': 0.00015618094767875254, 'value_raw': 0.00015618094767875254}
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:26[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:26.161902Z', 'sensor_name': 'f_reflection', 'value_cal': 16190369623.81609, 'value_raw': 16190369623.81609}
2021-03-22T16:32:26[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:18[INFO    ] dripline.implementations.postgres_sensor_logger(49) -> finished processing data
2021-03-22T16:32:26[INFO    ] dripline.implementations.postgres_sensor_logger(46) -> insert data are:
{'timestamp': '2021-03-22T16:32:26.161902Z', 'sensor_name': 'f_reflection', 'value_cal': 16190369623.81609, 'value_raw': 16190369623.81609}
Lingua principale
Python
Stelle
3
Fork
6
Nessuna PR unita negli ultimi 30g

Preparare l'ambiente

  • Include un Dockerfile o un file Docker Compose
  • Ha un modello di pull request
  • Nessuna guida per i contributori

Come iniziare

  1. Leggi tutta la issue e poi la guida ai contributi del progetto.
  2. Commenta sulla issue per dire che te ne occupi tu — evita che due persone facciano lo stesso lavoro.
  3. Fai un fork del repository e lavora su un branch.
  4. Apri una pull request che faccia riferimento al numero della issue.

Altre issue di driplineorg/dripline-python

Tutte le issue di driplineorg/dripline-python

Issue simili

Altre issue su Python

Ricevi le nuove issue nella tua casella

Un breve riepilogo di issue GitHub adatte ai principianti.