pyspc.model.otamin16.rt_data.RT_Data
- class pyspc.model.otamin16.rt_data.RT_Data(filename=None, datatype=None)[source]
Bases :
objectClasse permettant la manipulation du prv OTAMIN v2016.
- filename
Nom du fichier prv de OTAMIN v2016
- Type:
str
- datatype
Type du fichier de données
- Type:
str
- __init__(filename=None, datatype=None)[source]
Initialiser l’instance de la classe RT_Data (prv) de Otamin v2016.
- Paramètres:
filename (str) – Nom du fichier prv de OTAMIN v2016
datatype (str) – Type du fichier de données
Methods
__init__([filename, datatype])Initialiser l'instance de la classe RT_Data (prv) de Otamin v2016.
Liste des types de format prv Otamin.
read()Lire un fichier prv Otamin.
write([data])Ecrire un fichier prv OTAMIN.
- classmethod get_types()[source]
Liste des types de format prv Otamin.
- Renvoie:
list – Types de format prv Otamin
.. seealso:: – pyspc.verification.Otamin.convention.EXPORT_DTYPES
- read()[source]
Lire un fichier prv Otamin.
- Renvoie:
data – Dataframe des données
- Type renvoyé:
pnd.DataFrame
Exemples
>>> from pyspc.verification.otamin16 import RT_Data >>> f = 'data/model/otamin16/GRP_B_20200911_1515_2.prv' >>> d = RT_Data(filename=f, datatype='fcst') >>> df = d.read() >>> df Stations A6701210 Grandeurs Q IdSeries 57gGRPd000_2001 57gGRPd000_2002 57gGRPd000_2003 # Modeles 57gGRPd000 57gGRPd000 57gGRPd000 # Scenarios 2001 2002 2003 # DtDerObs 03-02-2020 12:00 03-02-2020 12:00 03-02-2020 12:00 2020-02-03 13:00:00 41.689 41.614 41.784 2020-02-03 14:00:00 43.426 43.161 43.760 2020-02-03 15:00:00 44.285 43.699 45.025 2020-02-03 16:00:00 44.395 43.438 45.649 2020-02-03 17:00:00 44.109 42.775 45.949 2020-02-03 18:00:00 43.340 41.659 45.793 2020-02-03 19:00:00 42.448 40.459 45.491 2020-02-03 20:00:00 41.470 39.230 45.023 2020-02-03 21:00:00 40.312 37.941 44.198 2020-02-03 22:00:00 39.044 36.614 43.123 2020-02-03 23:00:00 37.754 35.292 41.936 2020-02-04 00:00:00 36.612 34.060 40.888 2020-02-04 01:00:00 36.184 33.290 40.909 2020-02-04 02:00:00 36.708 33.133 42.427 2020-02-04 03:00:00 38.304 33.660 45.723 2020-02-04 04:00:00 40.523 34.575 50.083 2020-02-04 05:00:00 43.099 35.706 55.065 2020-02-04 06:00:00 45.781 36.908 60.224 2020-02-04 07:00:00 48.223 37.971 64.957 2020-02-04 08:00:00 50.064 38.681 68.613 2020-02-04 09:00:00 50.648 38.654 70.013 2020-02-04 10:00:00 50.161 38.023 69.503 2020-02-04 11:00:00 48.963 37.008 67.750 2020-02-04 12:00:00 47.745 36.014 66.030
>>> f = 'data/model/otamin16/GRP_B_20200911_1515_DA_2.prv' >>> d = Data(filename=f, datatype='fcst') >>> df = d.read() >>> df Stations A6701210 ... Grandeurs RR ... TA IdSeries 57gGRPd000_2001 ... 57gGRPd000_2003 # Modeles 57gGRPd000 ... 57gGRPd000 # Scenarios 2001 ... 2003 # DtDerObs 03-02-2020 12:00 ... 03-02-2020 12:00 2020-02-03 13:00:00 1.1 ... NaN 2020-02-03 14:00:00 1.1 ... NaN 2020-02-03 15:00:00 1.1 ... NaN 2020-02-03 16:00:00 0.2 ... NaN 2020-02-03 17:00:00 0.2 ... NaN 2020-02-03 18:00:00 0.2 ... NaN 2020-02-03 19:00:00 0.3 ... NaN 2020-02-03 20:00:00 0.3 ... NaN 2020-02-03 21:00:00 0.3 ... NaN 2020-02-03 22:00:00 0.4 ... NaN 2020-02-03 23:00:00 0.4 ... NaN 2020-02-04 00:00:00 0.4 ... NaN 2020-02-04 01:00:00 3.6 ... NaN 2020-02-04 02:00:00 3.6 ... NaN 2020-02-04 03:00:00 3.6 ... NaN 2020-02-04 04:00:00 0.8 ... NaN 2020-02-04 05:00:00 0.8 ... NaN 2020-02-04 06:00:00 0.8 ... NaN 2020-02-04 07:00:00 0.4 ... NaN 2020-02-04 08:00:00 0.4 ... NaN 2020-02-04 09:00:00 0.4 ... NaN 2020-02-04 10:00:00 0.7 ... NaN 2020-02-04 11:00:00 0.7 ... NaN 2020-02-04 12:00:00 0.7 ... NaN
>>> f = 'data/model/otamin16/GRP_B_20200203_1200_2.prv' >>> d = Data(filename=f, datatype='trend') >>> df = d.read() >>> df Stations A6701210 Grandeurs Q IdSeries 57gGRPd000_2001_-1 ... 57gGRPd000_2001_90 # Modeles 57gGRPd000 ... 57gGRPp000 # Scenarios 2001 ... 2001 # DtDerObs 03-02-2020 12:00 ... 03-02-2020 12 # Probas -1 ... 90 2020-02-03 13:00:00 41.689 ... 42.977 2020-02-03 14:00:00 43.426 ... 46.273 2020-02-03 15:00:00 44.285 ... 48.725 2020-02-03 16:00:00 44.395 ... 50.069 2020-02-03 17:00:00 44.109 ... 50.962 2020-02-03 18:00:00 43.340 ... 51.269 2020-02-03 19:00:00 42.448 ... 51.050 2020-02-03 20:00:00 41.470 ... 50.691 2020-02-03 21:00:00 40.312 ... 50.070 2020-02-03 22:00:00 39.044 ... 49.208 2020-02-03 23:00:00 37.754 ... 48.272 2020-02-04 00:00:00 36.612 ... 47.480 2020-02-04 01:00:00 36.184 ... 47.263 2020-02-04 02:00:00 36.708 ... 48.290 2020-02-04 03:00:00 38.304 ... 50.748 2020-02-04 04:00:00 40.523 ... 54.066 2020-02-04 05:00:00 43.099 ... 57.906 2020-02-04 06:00:00 45.781 ... 61.938 2020-02-04 07:00:00 48.223 ... 65.412 2020-02-04 08:00:00 50.064 ... 68.085 2020-02-04 09:00:00 50.648 ... 69.058 2020-02-04 10:00:00 50.161 ... 68.571 2020-02-04 11:00:00 48.963 ... 67.106 2020-02-04 12:00:00 47.745 ... 65.605