"Renvoie le script complet"
return self.__filestring
+# ==============================================================================
+class ImportFromFile(object):
+ """
+ Obtention de variables disrétisées en 1D, définies par une ou des variables
+ nommées, et sous la forme d'une série de points éventuellement indexés. La
+ lecture d'un fichier au format spécifié (ou intuité) permet de charger ces
+ fonctions depuis :
+ - des fichiers textes en colonnes de type TXT, CSV, TSV...
+ - des fichiers de données binaires NPY, NPZ...
+ La lecture du fichier complet ne se fait que si nécessaire, pour assurer la
+ performance tout en disposant de l'interprétation du contenu. Les fichiers
+ textes doivent présenter en première ligne (hors commentaire ou ligne vide)
+ les noms des variables de colonnes. Les commentaires commencent par un "#".
+ """
+ __slots__ = (
+ "_filename", "_varsline", "_format", "_delimiter", "_skiprows",
+ "__colnames", "__colindex", "__filestring", "__header")
+ def __enter__(self): return self
+ def __exit__(self, exc_type, exc_val, exc_tb): return False
+ #
+ def __init__(self, Filename=None, ColNames=None, ColIndex=None, Format="Guess"):
+ """
+ Verifie l'existence et les informations de définition du fichier. Les
+ noms de colonnes ou de variables sont ignorées si le format ne permet
+ pas de les indiquer.
+ Arguments :
+ - Filename : nom du fichier
+ - ColNames : noms de la ou des colonnes/variables à lire
+ - ColIndex : nom unique de la colonne/variable servant d'index
+ - Format : format du fichier et/ou des données inclues
+ """
+ if Filename is None:
+ raise ValueError("The name of the file, containing the variables to be read, has to be specified.")
+ if not os.path.isfile(Filename):
+ raise ValueError("The file, containing the variables to be read, doesn't seem to exist. Please check the file. The given file name is:\n \"%s\""%str(Filename))
+ self._filename = os.path.abspath(Filename)
+ #
+ self.__header, self._varsline, self._skiprows = self.__getentete(self._filename)
+ #
+ self._delimiter = None
+ self.__filestring = "".join(self.__header)
+ if Format.upper() == "GUESS":
+ if self._filename.split(".")[-1].lower() == "npy":
+ self._format = "NPY"
+ elif self._filename.split(".")[-1].lower() == "npz":
+ self._format = "NPZ"
+ elif self.__filestring.count(",") > 1 and self._filename.split(".")[-1].lower() == "csv":
+ self._format = "CSV"
+ self._delimiter = ","
+ elif self.__filestring.count(";") > 1 and self._filename.split(".")[-1].lower() == "csv":
+ self._format = "CSV"
+ self._delimiter = ";"
+ elif self.__filestring.count("\t") > 1 and self._filename.split(".")[-1].lower() == "tsv":
+ self._format = "TSV"
+ self._delimiter = "\t"
+ elif self.__filestring.count(" ") > 1 and self._filename.split(".")[-1].lower() == "txt":
+ self._format = "TXT"
+ else:
+ raise ValueError("Can not guess the file format, please specify the good one")
+ elif Format.upper() == "CSV" and self._delimiter is None:
+ if self.__filestring.count(",") > 1 and self._filename.split(".")[-1].lower() == "csv":
+ self._format = "CSV"
+ self._delimiter = ","
+ elif self.__filestring.count(";") > 1 and self._filename.split(".")[-1].lower() == "csv":
+ self._format = "CSV"
+ self._delimiter = ";"
+ elif Format.upper() == "TSV" and self._delimiter is None:
+ self._format = "TSV"
+ self._delimiter = "\t"
+ else:
+ self._format = str(Format).upper()
+ #
+ if ColNames is not None: self.__colnames = tuple(ColNames)
+ else: self.__colnames = None
+ #
+ if ColIndex is not None: self.__colindex = str(ColIndex)
+ else: self.__colindex = None
+
+ def __getentete(self, __filename, __nblines = 3):
+ "Lit l'entête du fichier pour trouver la définition des variables"
+ __header, __varsline, __skiprows = [], "", 1
+ if __filename.split(".")[-1].lower() in ("npy", "npz"):
+ pass
+ else:
+ with open(__filename,'r') as fid:
+ __line = fid.readline().strip()
+ while "#" in __line or len(__line) < 1:
+ __header.append(__line)
+ __skiprows += 1
+ __line = fid.readline().strip()
+ __varsline = __line # Première ligne non commentée non vide
+ for i in range(max(0,__nblines)):
+ __header.append(fid.readline())
+ return (__header, __varsline, __skiprows)
+
+ def __getindices(self, __colnames, __colindex, __delimiter=None ):
+ "Indices de colonnes correspondants à l'index et aux variables"
+ if __delimiter is None:
+ __varserie = self._varsline.strip('#').strip().split()
+ else:
+ __varserie = self._varsline.strip('#').strip().split(str(__delimiter))
+ #
+ if __colnames is not None:
+ __usecols = []
+ __colnames = tuple(__colnames)
+ for v in __colnames:
+ for i, n in enumerate(__varserie):
+ if v == n: __usecols.append(i)
+ __usecols = tuple(__usecols)
+ if len(__usecols) == 0: __usecols = None
+ else:
+ __usecols = None
+ #
+ if __colindex is not None:
+ __useindex = None
+ __colindex = str(__colindex)
+ for i, n in enumerate(__varserie):
+ if __colindex == n: __useindex = i
+ else:
+ __useindex = None
+ #
+ return (__usecols, __useindex)
+
+ def getvalue(self, ColNames=None, ColIndex=None ):
+ "Renvoie la ou les variables demandees par la liste de leurs noms"
+ # Uniquement si mise à jour
+ if ColNames is not None: self.__colnames = tuple(ColNames)
+ if ColIndex is not None: self.__colindex = str(ColIndex)
+ #
+ __index = None
+ if self._format == "NPY":
+ __columns = numpy.load(self._filename)
+ elif self._format == "NPZ":
+ __columns = None
+ with numpy.load(self._filename) as __allcolumns:
+ if self.__colnames is None:
+ self.__colnames = __allcolumns.files
+ for nom in self.__colnames:
+ if nom in __allcolumns.files:
+ if __columns is not None:
+ # Attention : toutes les variables doivent avoir la même taille
+ __columns = numpy.vstack((__columns, numpy.reshape(__allcolumns[nom], (1,-1))))
+ else:
+ # Première colonne
+ __columns = numpy.reshape(__allcolumns[nom], (1,-1))
+ if self.__colindex is not None and self.__colindex in __allcolumns.files:
+ __index = numpy.reshape(__allcolumns[self.__colindex], (1,-1))
+ elif self._format == "TXT":
+ __usecols, __useindex = self.__getindices(self.__colnames, self.__colindex)
+ __columns = numpy.loadtxt(self._filename, usecols = __usecols, skiprows=self._skiprows)
+ if __useindex is not None:
+ __index = numpy.loadtxt(self._filename, usecols = __useindex, skiprows=self._skiprows)
+ #
+ elif self._format == "CSV":
+ __usecols, __useindex = self.__getindices(self.__colnames, self.__colindex, self._delimiter)
+ __columns = numpy.loadtxt(self._filename, usecols = __usecols, delimiter = self._delimiter, skiprows=self._skiprows)
+ if __useindex is not None:
+ __index = numpy.loadtxt(self._filename, usecols = __useindex, delimiter = self._delimiter, skiprows=self._skiprows)
+ #
+ elif self._format == "TSV":
+ __usecols, __useindex = self.__getindices(self.__colnames, self.__colindex, self._delimiter)
+ __columns = numpy.loadtxt(self._filename, usecols = __usecols, delimiter = self._delimiter, skiprows=self._skiprows)
+ if __useindex is not None:
+ __index = numpy.loadtxt(self._filename, usecols = __useindex, delimiter = self._delimiter, skiprows=self._skiprows)
+ else:
+ raise ValueError("Unkown file format %s"%self._format)
+ #
+ return (self.__colnames, __columns, self.__colindex, __index)
+
+ def getstring(self):
+ "Renvoie le fichier complet"
+ with open(self._filename,'r') as fid:
+ return fid.read()
+
+# ==============================================================================
+class ImportScalarLinesFromFile(ImportFromFile):
+ """
+ Importation de fichier contenant des variables scalaires nommées. Le
+ fichier comporte soit 2, soit 4 colonnes, obligatoirement nommées "Name",
+ "Value", "Minimum", "Maximum" si les noms sont précisés. Sur chaque ligne
+ est indiqué le nom, la valeur, et éventuelement deux bornes min et max (ou
+ None si nécessaire pour une borne).
+
+ Seule la méthode "getvalue" est changée.
+ """
+ def __enter__(self): return self
+ def __exit__(self, exc_type, exc_val, exc_tb): return False
+ #
+ def __init__(self, Filename=None, ColNames=None, ColIndex=None, Format="Guess"):
+ ImportFromFile.__init__(self, Filename, ColNames, ColIndex, Format)
+ if self._format not in ["TXT", "CSV", "TSV"]:
+ raise ValueError("Unkown file format \"%s\""%self._format)
+ #
+ def getvalue(self, VarNames = None, HeaderNames=()):
+ "Renvoie la ou les variables demandees par la liste de leurs noms"
+ if VarNames is not None: __varnames = tuple(VarNames)
+ else: __varnames = None
+ #
+ if "Name" in self._varsline and "Value" in self._varsline and "Minimum" in self._varsline and "Maximum" in self._varsline:
+ __ftype = "NamValMinMax"
+ __dtypes = {'names' : ('Name', 'Value', 'Minimum', 'Maximum'),
+ 'formats': ('S128', 'g', 'g', 'g')}
+ __usecols = (0, 1, 2, 3)
+ def __replaceNoneN( s ):
+ if s.strip() == b'None': return numpy.NINF
+ else: return s
+ def __replaceNoneP( s ):
+ if s.strip() == b'None': return numpy.PINF
+ else: return s
+ __converters = {2: __replaceNoneN, 3: __replaceNoneP}
+ elif "Name" in self._varsline and "Value" in self._varsline and ("Minimum" not in self._varsline or "Maximum" not in self._varsline):
+ __ftype = "NamVal"
+ __dtypes = {'names' : ('Name', 'Value'),
+ 'formats': ('S128', 'g')}
+ __converters = None
+ __usecols = (0, 1)
+ elif len(HeaderNames)>0 and numpy.all([kw in self._varsline for kw in HeaderNames]):
+ __ftype = "NamLotOfVals"
+ __dtypes = {'names' : HeaderNames,
+ 'formats': tuple(['S128',]+['g']*(len(HeaderNames)-1))}
+ __usecols = tuple(range(len(HeaderNames)))
+ def __replaceNone( s ):
+ if s.strip() == b'None': return numpy.NAN
+ else: return s
+ __converters = dict()
+ for i in range(1,len(HeaderNames)):
+ __converters[i] = __replaceNone
+ else:
+ raise ValueError("Can not find names of columns for initial values. Wrong first line is:\n \"%s\""%__firstline)
+ #
+ if self._format == "TXT":
+ __content = numpy.loadtxt(self._filename, dtype = __dtypes, usecols = __usecols, skiprows = self._skiprows, converters = __converters)
+ elif self._format in ["CSV", "TSV"]:
+ __content = numpy.loadtxt(self._filename, dtype = __dtypes, usecols = __usecols, skiprows = self._skiprows, converters = __converters, delimiter = self._delimiter)
+ else:
+ raise ValueError("Unkown file format \"%s\""%self._format)
+ #
+ __names, __background, __bounds = [], [], []
+ for sub in __content:
+ if len(__usecols) == 4:
+ na, va, mi, ma = sub
+ if numpy.isneginf(mi): mi = None # Réattribue les variables None
+ elif numpy.isnan(mi): mi = None # Réattribue les variables None
+ if numpy.isposinf(ma): ma = None # Réattribue les variables None
+ elif numpy.isnan(ma): ma = None # Réattribue les variables None
+ elif len(__usecols) == 2 and __ftype == "NamVal":
+ na, va = sub
+ mi, ma = None, None
+ else:
+ nsub = list(sub)
+ na = sub[0]
+ for i, v in enumerate(nsub[1:]):
+ if numpy.isnan(v): nsub[i+1] = None
+ va = nsub[1:]
+ mi, ma = None, None
+ na = na.decode()
+ if (__varnames is None or na in __varnames) and (na not in __names):
+ # Ne stocke que la premiere occurence d'une variable
+ __names.append(na)
+ __background.append(va)
+ __bounds.append((mi,ma))
+ #
+ __names = tuple(__names)
+ __background = numpy.array(__background)
+ __bounds = tuple(__bounds)
+ #
+ return (__names, __background, __bounds)
+
# ==============================================================================
if __name__ == "__main__":
print('\n AUTODIAGNOSTIC \n')
