def __init__(self,fName):
aPath=path.abspath(fName)
pSep=aPath.split(path.sep)
self.name=path.splitext(pSep[-1])[0]
self.time=float(pSep[-2])
self.function=pSep[-3]
self.cloudName=pSep[-4]
f=CleanCharactersFile(fName,charsToRemove="()")
r=BytesIO(b(f.content))
hLine=str(r.readline().strip()).replace("'","")
# missing in some libraries
if hLine.find("cellI tetFaceI")>0:
hLine=hLine.replace("cellI tetFaceI","cellI faceI stepFraction tetFaceI")
header=[str(n) for n in hLine.split()[1:]]
spec=[]
for name in header:
if name in ["currentProc","cellI","faceI","tetFaceI","tetPtI","origProc","origId","typeId"]:
spec.append((name,"i8"))
elif name in ["active"]:
spec.append((name,np.bool_))
else:
spec.append((str(name),"f8"))
self.data=np.recfromtxt(r,dtype=spec)
def toNumpy(self, regexp, dtypes):
import numpy as np
try:
return np.fromregex(StringIO(self.data), regexp, dtypes)
except TypeError:
from PyFoam.ThirdParty.six import BytesIO, b
return np.fromregex(BytesIO(b(self.data)), regexp, dtypes)
def toNumpy(self, regexp, dtypes):
"""Assume that the unparsed data contains line-wise data and transform it to a numpy-array.
@param regexp: regular expression where the groups correspond to the dtypes,
@param dtypes: list with dtypes"""
import numpy as np
try:
return np.fromregex(StringIO(self.data), regexp, dtypes)
except TypeError:
from PyFoam.ThirdParty.six import BytesIO, b
return np.fromregex(BytesIO(b(self.data)), regexp, dtypes)
def testSpreadsheetReadFileHandleTest(self):
sp = SpreadsheetData(txtName=BytesIO(filecontent))
self.assertEqual(len(sp.names()), 4)