#!/usr/bin/python3
# -*- coding: utf-8 -*-
########################################################################
#
# This file is part of python module <pyspc>.
# Copyright (C) 2013-2021 R. Marty
# (renaud.marty@developpement-durable.gouv.fr)
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program (see COPYING.txt).
# If not, see <http://www.gnu.org/licenses/>.
#
########################################################################
"""
Modélisations hydrologiques - GRP version 2018 - Temps-réel interne
"""
import os.path
import pandas as pnd
from pyspc.convention.grp20 import RT_INTERN_DTYPES
[docs]
class GRPRT_Intern():
"""
Structure de données GRPRT Intern (Variables internes de GRP *Temps Réel*)
Fichiers
- PQE_1A.DAT
- PQE_1A_D.DAT
Attributes
----------
filename : str
Nom du fichier Archve de GRP *Temps-Réel*
realtime : bool
Temps-réel (True) ou Temps différé (False)
"""
[docs]
def __init__(self, filename=None):
"""
Initialisation de l'instance de la classe GRPRT_Intern
Parameters
----------
filename : str
Nom du fichier Interne de GRP *Temps-Réel*
"""
self.filename = filename
self.realtime = self.split_basename(filename=self.filename)
def __str__(self):
"""
Afficher les méta-données de l'instance GRPRT_Intern
"""
text = """
*************************************
*********** GRP 2018 - RT Intern ****
*************************************
* NOM FICHIER = {filename}
* TEMPS-REEL = {realtime}
*************************************
"""
return text.format(**vars(self))
[docs]
def read(self):
"""
Lire le fichier de variables internes Temps-Réel / Temps-Différé
Returns
-------
pandas.DataFrame
Tableau des variables internes de GRP Temps-Réel
Examples
--------
>>> from pyspc.model.grp20 import GRPRT_Intern
Cas avec des données au pas de temps horaire (mm: mm par heure)
>>> f = 'data/model/grp20/rt/intern/PQE_1A_D.DAT'
>>> reader = GRPRT_Intern(filename=f)
>>> df = reader.read()
>>> df
Qsim(mm) Qobs(mm) ETP(mm) P(mm) T(C) R(mm) S(mm)
DATE (TU)
2007-01-18 12:00:00 0.3649 0.3278 0.0338 0.16 NaN 25.7607 247.0715
2007-01-18 13:00:00 0.3604 0.3221 0.0338 0.12 NaN 25.6028 247.0227
2007-01-18 14:00:00 0.3556 0.3164 0.0319 0.20 NaN 25.4343 246.9898
2007-01-18 15:00:00 0.3762 0.3147 0.0281 3.04 NaN 26.1560 247.5004
2007-01-18 16:00:00 0.4350 0.3170 0.0224 3.36 NaN 28.1103 248.0608
2007-01-18 17:00:00 0.5277 0.3363 0.0148 4.16 NaN 30.9372 248.7550
2007-01-18 18:00:00 0.6924 0.4108 0.0054 8.48 NaN 35.3932 250.1835
2007-01-18 19:00:00 0.8931 0.5981 0.0000 3.72 NaN 40.1447 250.7462
2007-01-18 20:00:00 1.1170 0.9132 0.0000 7.60 NaN 44.8370 251.9237
2007-01-18 21:00:00 1.3698 1.1836 0.0000 6.32 NaN 49.5851 252.8453
2007-01-18 22:00:00 1.7101 1.4474 0.0000 9.44 NaN 55.3158 254.1844
2007-01-18 23:00:00 2.0794 1.7065 0.0000 6.64 NaN 60.9018 255.0535
2007-01-19 00:00:00 2.4511 1.9306 0.0000 7.88 NaN 66.0258 256.0480
2007-01-19 01:00:00 2.8393 2.1194 0.0000 8.44 NaN 70.9637 257.0599
2007-01-19 02:00:00 3.1850 2.2889 0.0000 5.32 NaN 75.0719 257.6386
2007-01-19 03:00:00 3.4561 2.3727 0.0000 6.64 NaN 78.1338 258.3505
2007-01-19 04:00:00 3.6906 2.5446 0.0000 5.96 NaN 80.6836 258.9535
2007-01-19 05:00:00 3.9359 2.7203 0.0000 6.72 NaN 83.2603 259.6137
2007-01-19 06:00:00 4.2034 2.7348 0.0000 7.24 NaN 85.9773 260.2969
2007-01-19 07:00:00 4.5018 2.8931 0.0057 7.44 NaN 88.9021 260.9651
2007-01-19 08:00:00 4.7756 3.4033 0.0158 6.60 NaN 91.4986 261.5183
2007-01-19 09:00:00 4.9946 3.9310 0.0239 6.48 NaN 93.5192 262.0343
2007-01-19 10:00:00 5.1346 4.1923 0.0300 5.36 NaN 94.7865 262.4276
2007-01-19 11:00:00 5.1242 4.2232 0.0340 2.96 NaN 94.6928 262.5975
2007-01-19 12:00:00 4.9236 4.0355 0.0360 1.32 NaN 92.8691 262.6214
2007-01-19 13:00:00 4.6138 3.5419 0.0360 1.08 NaN 89.9744 262.6241
2007-01-19 14:00:00 4.2787 3.1272 0.0340 0.48 NaN 86.7255 262.5745
2007-01-19 15:00:00 3.9910 2.9025 0.0300 1.60 NaN 83.8279 262.6235
2007-01-19 16:00:00 3.7529 2.7505 0.0239 1.00 NaN 81.3466 262.6202
2007-01-19 17:00:00 3.5319 2.6294 0.0158 0.72 NaN 78.9680 262.5932
2007-01-19 18:00:00 3.3168 2.4929 0.0057 0.80 NaN 76.5767 262.5743
Cas avec des données au pas de temps journalier (mm: mm par jour)
>>> f = 'data/model/grp20/rt/intern/PQE_1A_D_journalier.DAT'
>>> reader = GRPRT_Intern(filename=f)
>>> df = reader.read()
>>> df
Qsim(mm) Qobs(mm) ETP(mm) P(mm) T(C) R(mm) S(mm)
DATE (TU)
2007-01-17 5.1060 NaN 0.2546 0.40 NaN 22.4859 244.9885
2007-01-18 5.3363 6.0837 0.2727 7.84 NaN 22.9351 244.9837
2007-01-19 23.3179 13.6173 0.2909 70.08 NaN 42.8322 254.6694
2007-01-20 61.3244 68.1413 0.2818 82.96 NaN 60.9440 261.5377
2007-01-21 49.2584 33.2340 0.2091 10.48 NaN 56.5619 260.4014
2007-01-22 24.8283 22.5610 0.2000 9.00 NaN 43.8974 259.2471
2007-01-23 15.1648 14.3262 0.2000 2.04 NaN 36.0085 257.4833
2007-01-24 9.7221 10.6448 0.1818 1.12 NaN 29.8515 255.6995
"""
with open(self.filename, 'r', encoding='iso-8859-15') as f:
f.readline()
f.readline()
x = f.readline().split(';')[0]
df = pnd.read_csv(
self.filename,
encoding='latin_1',
sep=';',
header=0,
skiprows=[0, 1, 3, 4],
index_col=False,
dtype={x: str},
na_values=[-99.9, '-99.9000', -9.9900, '-9.9900'],
)
df.set_index(x, inplace=True)
df.index.name = 'DATE (TU)'
# Nettoyer la colonne superflue
df.drop(columns=df.columns[-1], inplace=True)
# Nettoyer les intitulés des colonnes
df.columns = [c.strip() for c in df.columns]
df.index.name = df.index.name.strip()
lendt = list({len(i) for i in df.index})[0]
if lendt == 12:
fmt = '%Y%m%d%H%M'
elif lendt == 10:
fmt = '%Y%m%d%H'
elif lendt == 8:
fmt = '%Y%m%d'
else:
raise NotImplementedError
df.index = pnd.to_datetime(df.index, format=fmt)
return df
[docs]
def write(self, data=None):
"""
Ecrire le fichier Interne de GRP Temps-Réel / Temps-Différé
"""
raise NotImplementedError
[docs]
@staticmethod
def split_basename(filename=None):
"""
Extraire les informations depuis le nom du fichier
de données GRP Intern (GRP *Temps-Réel*)
Parameters
----------
filename : str
Fichier de données GRP Archive (GRP *Temps-Réel*)
Returns
-------
realtime : bool
Temps-réel (True) ou Temps différé (False)
Examples
--------
>>> from pyspc.model.grp20 import GRPRT_Intern
>>> f = 'data/model/grp20/rt/intern/PQE_1A.DAT'
>>> realtime = GRPRT_Intern.split_basename(filename=f)
>>> realtime
True
>>> f = 'data/model/grp20/rt/intern/PQE_1A_D.DAT'
>>> realtime = GRPRT_Intern.split_basename(filename=f)
>>> realtime
False
"""
if filename is None:
return None
x = os.path.splitext(os.path.basename(filename))[0].split('_')
return len(x) != 3 or x[-1] != 'D'
[docs]
def check_datatype(self, datatype):
"""
Contrôler la cohérence entre le type et le nom du fichier
Parameters
----------
datatype : str
Type de fichier
Raises
------
ValueError
Si incohérence entre le type et le nom du fichier
"""
test_file = self.split_basename(filename=self.filename)
test_dtype = RT_INTERN_DTYPES[datatype]
if (test_file and not test_dtype) or (not test_file and test_dtype):
raise ValueError("Incohérence entre le type et le nom du fichier")
[docs]
@staticmethod
def get_types():
"""
Type de fichier de variable interne GRP Temps-réel
- intern : variable interne temps-réel
- intern_diff : variable interne temps différé
"""
return sorted(RT_INTERN_DTYPES.keys())