NDarray of DateTime about numpy.net HOT 3 OPEN

I don't know. Can you post an equivalent snippet in Python?

from numpy.net.

@henon Well there's multiple ways. I think this is the most idiomatic:

import numpy as np

datetimes = np.array(
    [
        '2000-01-15', 
        '2000-06-15', 
        '2001-01-15',
        '2001-06-15'
    ], 
    dtype='datetime64'
)

print(datetimes.dtype)
print(np.diff(datetimes))

You can also do this:

import numpy as np
from datetime import datetime

datetimes = [
    np.datetime64('2000-01-15'),
    np.datetime64('2000-06-15'),
    np.datetime64('2001-01-15'),
    np.datetime64('2001-06-15')
]

datetimes = np.array(datetimes)

print(np.diff(datetimes).dtype)
print(np.diff(datetimes))

But if I had to emulate the C# as closely as I could, I guess I was attempting something like this:

import numpy as np
from datetime import datetime

datetimes = [
    datetime(2000, 1, 15),
    datetime(2000, 6, 15),
    datetime(2001, 1, 15),
    datetime(2001, 6, 15)
]

datetimes = np.array(datetimes)

print(np.diff(datetimes).dtype)
print(np.diff(datetimes))

So it looks like there's an np.datetime64 type wrapped around datetime from the standard library. Maybe I shouldn't have been trying to access System.DateTime? Perhaps there is already an np.datetime64 equivalent in Numpy.NET?

from numpy.net.

If you know how the date times are represented in memory in numpy (i.e. milliseconds since 1970 or whatever, I really don't know) then you can always use this workaround as described in #115 by creating a byte[] that contains the data which represent the datetimes you want. Of course that is a quite inconvenient workaround.

I'll look into it how I can support date time arrays, maybe I'll have to use the same workaround internally anyway.

from numpy.net.