Here's a function I wrote to calculate hourly averages:
It seems a bit slow, however... any thoughts on how to improve it?
def calc_hravg(X):
"""Calculates hourly average from input data"""
X_hr = []
minX = X[:,0].min()
hr = dt.datetime(*minX.timetuple()[0:4])
while hr <= dt.datetime(*X[-1,0].timetuple()[0:4]):
nhr = hr + dt.timedelta(hours=1)
ind = np.where( (X[:,0] > hr) & (X[:,0] < nhr) )
vals = X[ind,1][0].T
try:
#hr_avg = np.sum(vals) / len(vals)
hr_avg = np.average(vals)
except:
hr_avg = np.nan
X_hr.append([hr,hr_avg])
hr = hr + dt.timedelta(hours=1)
return np.array(X_hr)
--
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