pyspc.io.lamedo.read_BdImage

pyspc.io.lamedo.read_BdImage(filename=None, ratio_image=1, ratio_stats=1, warning=True)[source]

Créer une instance Series à partir de données BdImage.

Paramètres:
  • filename (str) – Nom du fichier d’observations de Météo-France

  • ratio_image (float) – Ratio minimal requis pour les images

  • ratio_stats (float) – Ratio minimal requis pour les statistiques

  • warning (bool) – Imprimer les erreurs ?

Renvoie:

series – Collection de séries de données

Type renvoyé:

pyspc.core.series.Series

Exemples

>>> from pyspc.io.lamedo import read_BdImage

Cas d’observations statistiques sur une zone

>>> f = 'data'/data/lamedo/getObsStatsByZones_antilope-j1-rr_000100.xml'
>>> series = read_BdImage(filename=f)
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = obs
*  NOMBRE DE SERIES     = 14
*  ----------------------------------
*  SERIE #1
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,cvar
*  ----------------------------------
*  SERIE #2
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,etyp
*  ----------------------------------
*  SERIE #3
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,max
*  ----------------------------------
*  SERIE #4
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,med
*  ----------------------------------
*  SERIE #5
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,min
*  ----------------------------------
*  SERIE #6
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,moy
*  ----------------------------------
*  SERIE #7
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q10
*  ----------------------------------
*  SERIE #8
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q20
*  ----------------------------------
*  SERIE #9
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q30
*  ----------------------------------
*  SERIE #10
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q40
*  ----------------------------------
*  SERIE #11
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q60
*  ----------------------------------
*  SERIE #12
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q70
*  ----------------------------------
*  SERIE #13
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q80
*  ----------------------------------
*  SERIE #14
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q90
*************************************

Cas d’observations statistiques sur une zone avec application de ratios

>>> f = 'data'/data/lamedo/getObsStatsByZones_antilope-j1-rr_000100.xml'
>>> series = read_BdImage(filename=f, ratio_image=0.8, ratio_stats=0.8)
Avertissement : le ratio 'image' est inférieur au seuil de tolérance
(0.80 > 12/24=0.5) pour l'image detype=antilope, soustype=j1
et date=2021-05-09 06:00:00
Avertissement : le ratio 'stats' est inférieur au seuil de tolérance
(0.80 > 10/19=0.5263157894736842) pour la statistique deloc=LO8060
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = obs
*  NOMBRE DE SERIES     = 14
*  ----------------------------------
*  SERIE #1
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,cvar
*  ----------------------------------
*  SERIE #2
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,etyp
*  ----------------------------------
*  SERIE #3
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,max
*  ----------------------------------
*  SERIE #4
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,med
*  ----------------------------------
*  SERIE #5
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,min
*  ----------------------------------
*  SERIE #6
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,moy
*  ----------------------------------
*  SERIE #7
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q10
*  ----------------------------------
*  SERIE #8
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q20
*  ----------------------------------
*  SERIE #9
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q30
*  ----------------------------------
*  SERIE #10
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q40
*  ----------------------------------
*  SERIE #11
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q60
*  ----------------------------------
*  SERIE #12
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q70
*  ----------------------------------
*  SERIE #13
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q80
*  ----------------------------------
*  SERIE #14
*      - CODE    = LO8060
*      - VARNAME = PH
*      - META    = antilope,j1,rr,q90
*************************************

Cas d’observations “pixel” sur une bbox

>>> f = 'data'/data/lamedo/getObsValuesByBBox_antilope-j1-rr_010000.xml'
>>> series = read_BdImage(filename=f)
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = obs
*  NOMBRE DE SERIES     = 4
*  ----------------------------------
*  SERIE #1
*      - CODE    = 793500.0,6412500.0
*      - VARNAME = PJ
*      - META    = antilope,j1,rr,val
*  ----------------------------------
*  SERIE #2
*      - CODE    = 793500.0,6413500.0
*      - VARNAME = PJ
*      - META    = antilope,j1,rr,val
*  ----------------------------------
*  SERIE #3
*      - CODE    = 794500.0,6412500.0
*      - VARNAME = PJ
*      - META    = antilope,j1,rr,val
*  ----------------------------------
*  SERIE #4
*      - CODE    = 794500.0,6413500.0
*      - VARNAME = PJ
*      - META    = antilope,j1,rr,val
*************************************

Cas d’observations “pixel” sur une bbox - Température

>>> f = 'data'/data/lamedo/getObsValuesByBBox_sim-t-t.xml'
>>> series = read_BdImage(filename=f)
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = obs
*  NOMBRE DE SERIES     = 6
*  ----------------------------------
*  SERIE #1
*      - CODE    = 779000.0,6404000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*  ----------------------------------
*  SERIE #2
*      - CODE    = 779000.0,6412000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*  ----------------------------------
*  SERIE #3
*      - CODE    = 779000.0,6420000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*  ----------------------------------
*  SERIE #4
*      - CODE    = 787000.0,6404000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*  ----------------------------------
*  SERIE #5
*      - CODE    = 787000.0,6412000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*  ----------------------------------
*  SERIE #6
*      - CODE    = 787000.0,6420000.0
*      - VARNAME = TI
*      - META    = sim,t,t,val
*************************************

Cas de prévisions statistiques sur une zone

>>> f = 'data'/data/lamedo/getPrevByNetworkStatsByZones_pprod-rr-total.xml'
>>> series = read_BdImage(filename=f)
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 1
*  ----------------------------------
*  SERIE #1
*      - CODE    = LO850
*      - VARNAME = PH
*      - META    = 2025-09-21 00:00:00+00:00, pprod, rr,total, moy
*************************************

Cas de prévisions “pixel” sur une bbox

>>> f = 'data'/data/lamedo/getPrevByNetworkValuesByBBox_pprod-rr-total.xml'
>>> series = read_BdImage(filename=f)
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = BdImage
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 4
*  ----------------------------------
*  SERIE #1
*      - CODE    = 793500.0,6412500.0
*      - VARNAME = PH
*      - META    = 2025-09-21 00:00:00+00:00, pprod, rr,total, val
*  ----------------------------------
*  SERIE #2
*      - CODE    = 793500.0,6413500.0
*      - VARNAME = PH
*      - META    = 2025-09-21 00:00:00+00:00, pprod, rr,total, val
*  ----------------------------------
*  SERIE #3
*      - CODE    = 794500.0,6412500.0
*      - VARNAME = PH
*      - META    = 2025-09-21 00:00:00+00:00, pprod, rr,total, val
*  ----------------------------------
*  SERIE #4
*      - CODE    = 794500.0,6413500.0
*      - VARNAME = PH
*      - META    = 2025-09-21 00:00:00+00:00, pprod, rr,total, val
*************************************