Re: Climate Data - KX Learning Hub

rocuinneagain

Member

September 29, 2023 at 12:00 am

Yes it could be used.

To test you could look at PyKX for an easy Python interface.

A 2 minute example of passing in a Dataset to q in shown below.

PyKX allows Registering Custom Conversions so you could create a function to pass the Dataset in exactly the form you wish to q instead of passing it all as a dictionary in my example.

import pykx as kx 
import xarray as xr 
import numpy as np 
import pandas as pd

ds = xr.Dataset(     
      {"foo": (("x", "y"), np.random.rand(5, 5))},     
      coords={         "x": [10, 20, 30, 40, 50],         
                       "y": pd.date_range("2000-01-01", periods=5),         
                       "z": ("x", list("abcde")),     }, )

kx.q['ds'] = kx.toq(ds.to_dict())

kx.q('ds')

pykx.Dictionary(pykx.q(' 
coords   | `x`y`z!+`dims`attrs`data!((,`x;,`y;,`x);(()!();()!();()!());(10 20.. attrs    | ()!() dims     | `x`y!5 5 data_vars| (,`foo)!+`dims`attrs`data!(,`x`y;,()!();,(0.7412575 0.2054306 0.10.. '))

kx.q('flip ds[`coords;;`data]')

pykx.Table(pykx.q(' 
x  y                             z 
---------------------------------- 
10 2000.01.01D00:00:00.000000000 a 
20 2000.01.02D00:00:00.000000000 b 
30 2000.01.03D00:00:00.000000000 c 
40 2000.01.04D00:00:00.000000000 d 
50 2000.01.05D00:00:00.000000000 e '))

kx.q('ds[`data_vars;`foo;`data]')

pykx.List(pykx.q(' 0.7412575 0.2054306   0.1009393 0.8792678 0.04105999 0.1811459 0.01659637  0.2406029 0.4900055 0.551788   0.6303767 0.0702013   0.6831359 0.5961667 0.3722388  0.9255059 0.9202499   0.5055902 0.9767793 0.7440498  0.7331576 0.003197568 0.4939932 0.5433492 0.01175784 '))

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rocuinneagain