def readData(indict):
"""
Takes as input a dictionary with paths to data
as keys, and the name of the field to select as values.
Returns a record array with the field names as keys populated
by the data in the file located at the path provided
"""
print(indict)
data = None
paths = indict.keys()
feats = [f for f in flatten(indict.values())]
dt = np.dtype([(f, float) for f in feats])
print(dt)
for i, path in enumerate(paths):
#Check to see what type of reader we need
if ('delta' in indict[path]) and ('hlist' in str(path)):
d = readHaloRnn(path)
elif 'delta' in indict[path]:
if '*' in path:
files = glob(path)
for j,f in enumerate(files):
if j==0:
d = readPartRnn(f)
else:
gd = readPartRnn(f)
d = np.hstack((d,gd))
else:
d = readPartRnn(path)
elif 'hlist' in str(path):
d = readHL(path, fields = indict[path])
elif 'z' in indict[path]:
if i==0:
paths.append(path)
continue
d = np.zeros(len(d), dtype=np.dtype([('z',float)]))
d['z']+=path
else:
print("""This feature is not currently handled, if you would like to use
it, please add a new i/o fuction
""")
return None
if data==None:
data = np.ndarray(len(d),dtype=dt)
data_view = data.view(float).reshape(len(data), -1)
#Add data from this path to the rec array
#have to use views to change multiple columns of
#rec array
ii = np.ndarray(len(indict[path]), dtype=int)
for i in range(len(ii)):
ii[i] = np.where(np.array(dt.names)==indict[path][i])[0][0]
data_view[:,ii] = d[indict[path]].view(np.float).reshape(len(d),-1)
return data
def loadHalos(self):
self.halos = readHL(self.hlistpath, fields=self.fields)
