Python datetime4[ns] to MATLAB

Question

Emily Browning 2022-10-31

1
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此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/1840188-python-datetime4-ns-to-matlab

回答： Suvansh Arora 2022-11-3

I'm trying to import data from an xarray in python with time data stored as (datetime64[ns]) into matlab by saving it as a netcdf. When importing it into matlab with ncread it is output as a int64:

0

609999895

1250000000

1859999895

2500000000

3119999885

3769999980

4380000114

5039999961

5650000095

6299999952

6910000085

I'm having trouble figuring out how to convert this to something understandable.

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KSSV 2022-10-31

You need to look into functions like datestr, datetime.

Emily Browning 2022-10-31

t = datetime(X,'ConvertFrom',dateType) This seam close but I can't find a dateType that fits.

In python the first value looks like 2022-08-23T22:03:51.200000047

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Answer 1

Suvansh Arora 2022-11-3

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在 MATLAB Online 中打开

One of the possible workarounds is to pre-process the date and time in python and convert it to Year, Month, Day, Hours, Minute and seconds.

Please follow below Python code snippet:

import numpy as np 
import pandas as pd 
# First datetime entry: 
var = np.datetime64('2022-08-23T22:03:51.200000047') 
# Helper function that converts above date-time to Hours, Months, Days, Seconds, years, etc: 
def dt2cal(dt): 
""" 
Convert array of datetime64 to a calendar array of year, month, day, hour, 
minute, seconds, microsecond with these quantites indexed on the last axis. 
Parameters 
---------- 
dt : datetime64 array (...) 
    numpy.ndarray of datetimes of arbitrary shape 
Returns 
------- 
cal : uint32 array (..., 7) 
    calendar array with last axis representing year, month, day, hour, 
minute, second, microsecond 
""" 
# allocate output  
out = np.empty(dt.shape + (7,), dtype="u4") 
# decompose calendar floors 
Y, M, D, h, m, s = [dt.astype(f"M8[{x}]") for x in "YMDhms"] 
    out[..., 0] = Y + 1970 # Gregorian Year 
        out[..., 1] = (M - Y) + 1 # month 
        out[..., 2] = (D - M) + 1 # dat 
        out[..., 3] = (dt - D).astype("m8[h]") # hour 
        out[..., 4] = (dt - h).astype("m8[m]") # minute 
        out[..., 5] = (dt - m).astype("m8[s]") # second 
        out[..., 6] = (dt - s).astype("m8[us]") # microsecond 
        return out 

Now we can Import this data to MATLAB and use datetime function to convert back to the required format, please follow below mentioned MATLAB code snippet for that:

% The arrays mentioned below, we will import from python 
Y = [2014;2013;2012]; 
M = 01; 
D = [31;30;31]; 
H = [1;2;3]; 
M = [12; 10; 1]; 
S = [1;1;1]; 
% Using datetime function to convert back, please refer documentation for details 
t = datetime(Y,M,D,H,M,S) 