pyspc.io.prevision.read_Prevision14

pyspc.io.prevision.read_Prevision14(filename, codes=None, valid=False, hydro_version='hydro3', first_dt=None, last_dt=None, warning=True)[source]

Créer une instance Series à partir d’une base Prévision du SPC LCI, période 2014-2016

Paramètres:

filename (str) – Chemin de la base de données
codes (list) – Codes Hydro2/Hydro3 des stations
valid (bool) – Seulement les prévisions validées (True) ou toutes les prévisions produites (False) Défaut: False
hydro_version (str) – Version du référentiel: “hydro2” ou “hydro3”. Défaut: “hydro3”
first_dt (datetime) – Premier instant de prévision
last_dt (datetime) – Dernier instant de prévision
warning (bool) – Affiche les avertissement si True. Défaut: True

Renvoie:

series – Collection des prévisions

Type renvoyé:

pyspc.core.series.Series

Exemples

>>> from datetime import datetime as dt
>>> from pyspc.io.prevision import read_Prevision14
>>> filename = os.path.join('data/io/dbase', 'prevision_2014.mdb')
>>> first_dt = dt(2013, 5, 3, 12)
>>> last_dt = dt(2013, 5, 3, 23)
>>> codes = ['K1251810']

Cas des prévisions brutes - hydro2

>>> series = read_Prevision14(
...     filename=filename, codes=codes, first_dt=first_dt, last_dt=last_dt,
...     valid=False, hydro_version='hydro2')
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = Prevision14
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 27
*  ----------------------------------
*  SERIE #1
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2001, None
*  ----------------------------------
*  SERIE #2
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2001, None
*  ----------------------------------
*  SERIE #3
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2001, None
*  ----------------------------------
*  SERIE #4
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2002, None
*  ----------------------------------
*  SERIE #5
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2002, None
*  ----------------------------------
*  SERIE #6
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2002, None
*  ----------------------------------
*  SERIE #7
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2003, None
*  ----------------------------------
*  SERIE #8
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2003, None
*  ----------------------------------
*  SERIE #9
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2003, None
*  ----------------------------------
*  SERIE #10
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2004, None
*  ----------------------------------
*  SERIE #11
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2004, None
*  ----------------------------------
*  SERIE #12
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2004, None
*  ----------------------------------
*  SERIE #13
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2005, None
*  ----------------------------------
*  SERIE #14
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2005, None
*  ----------------------------------
*  SERIE #15
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2005, None
*  ----------------------------------
*  SERIE #16
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2006, None
*  ----------------------------------
*  SERIE #17
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2006, None
*  ----------------------------------
*  SERIE #18
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2006, None
*  ----------------------------------
*  SERIE #19
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2007, None
*  ----------------------------------
*  SERIE #20
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2007, None
*  ----------------------------------
*  SERIE #21
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2007, None
*  ----------------------------------
*  SERIE #22
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2008, None
*  ----------------------------------
*  SERIE #23
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2008, None
*  ----------------------------------
*  SERIE #24
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2008, None
*  ----------------------------------
*  SERIE #25
*      - CODE    = K1251810
*      - VARNAME = PH
*      - META    = 2013-05-03 23:00:00, LCI, 2009, None
*  ----------------------------------
*  SERIE #26
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI, 2009, None
*  ----------------------------------
*  SERIE #27
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI, 2009, None
*************************************

Cas des prévisions validées - hydro2

>>> series = read_Prevision14(
...     filename=filename, codes=codes, first_dt=first_dt, last_dt=last_dt,
...     valid=True, hydro_version='hydro2')
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = Prevision14
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 2
*  ----------------------------------
*  SERIE #1
*      - CODE    = K1251810
*      - VARNAME = QH
*      - META    = 2013-05-03 23:00:00, LCI-valid, 2006, None
*  ----------------------------------
*  SERIE #2
*      - CODE    = K1251810
*      - VARNAME = HH
*      - META    = 2013-05-03 23:00:00, LCI-valid, 2006, None
*************************************

Cas des prévisions brutes - hydro3

>>> filename = os.path.join('data/io/dbase', 'prevision_2014_hydro3.mdb')
>>> first_dt = dt(2016, 5, 31, 12)
>>> last_dt = dt(2016, 5, 31, 18)
>>> codes = ['K6373020']
>>> series = read_Prevision14(
...     filename=filename, codes=codes, first_dt=first_dt, last_dt=last_dt,
...     valid=False, hydro_version='hydro3')
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = Prevision14
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 8
*  ----------------------------------
*  SERIE #1
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI, 2001, Val
*  ----------------------------------
*  SERIE #2
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI, 2001, Val10
*  ----------------------------------
*  SERIE #3
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI, 2001, Val50
*  ----------------------------------
*  SERIE #4
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI, 2001, Val90
*  ----------------------------------
*  SERIE #5
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI, 2001, Val
*  ----------------------------------
*  SERIE #6
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI, 2001, Val10
*  ----------------------------------
*  SERIE #7
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI, 2001, Val50
*  ----------------------------------
*  SERIE #8
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI, 2001, Val90
*************************************

Cas des prévisions validées - hydro3

>>> series = read_Prevision14(
...     filename=filename, codes=codes, first_dt=first_dt, last_dt=last_dt,
...     valid=True, hydro_version='hydro3')
>>> series
*************************************
********** SERIES *******************
*************************************
*  NOM DE LA COLLECTION = Prevision14
*  TYPE DE COLLECTION   = fcst
*  NOMBRE DE SERIES     = 8
*  ----------------------------------
*  SERIE #1
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI-valid, 2001, Val
*  ----------------------------------
*  SERIE #2
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI-valid, 2001, Val10
*  ----------------------------------
*  SERIE #3
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI-valid, 2001, Val50
*  ----------------------------------
*  SERIE #4
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 13:00:00, LCI-valid, 2001, Val90
*  ----------------------------------
*  SERIE #5
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI-valid, 2001, Val
*  ----------------------------------
*  SERIE #6
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI-valid, 2001, Val10
*  ----------------------------------
*  SERIE #7
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI-valid, 2001, Val50
*  ----------------------------------
*  SERIE #8
*      - CODE    = K6373020
*      - VARNAME = QH
*      - META    = 2016-05-31 16:00:00, LCI-valid, 2001, Val90
*************************************