"John [H2O]" <washa...@gmail.com> wrote
The data is just x,y data where x = datetime objects from the datetime
module. y are just floats. It is bundled in a numpy array.
So the only import statements are:
import datetime as dt
import numpy as np
I pass the array X, where X is a numpy array of shape [n,2] where n is
the
number of points in the data.
I assume there is a good reason to use a numpy array instead of
a regular list? ie You need a numpy array elsewhere in the code?
I've never used numpy bt there is a possibility that array access
is slower than list access, but I have no idea. It just adds an extra
level of complexity thats all.
As for your comment regarding the invariant... would it be:
while hr q:
I think he meant
while hr <= q
as per your original code
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) )
I have no idea what this is doing but do you really mean a bitwise
and here? You are effectively bitwise anding two boolean values
which seems odd to put it mildly...
vals = X[ind,1][0].T
try:
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)
HTH,
--
Alan Gauld
Author of the Learn to Program web site
http://www.alan-g.me.uk/
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