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  • jacklovell · 2 ✖

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  • Using where() in datasets with dataarrays with different dimensions results in huge RAM consumption · 2 ✖

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  • NONE · 2 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
273529203 https://github.com/pydata/xarray/issues/1217#issuecomment-273529203 https://api.github.com/repos/pydata/xarray/issues/1217 MDEyOklzc3VlQ29tbWVudDI3MzUyOTIwMw== jacklovell 4849151 2017-01-18T16:43:03Z 2017-01-19T05:15:52Z NONE

The problem isn't as bad with a smaller example (though the runtime is doubled). I've attached a minimum working example, which seems to suggest that maybe there was a problem with xarray creating a MultiIndex and duplicating all the data? (I've left in input() to allow checking memory usage before the program exists, but there isn't much difference in this example). xrmin.py.txt

Edit by @shoyer: added code from attachment inline: ```python

!/usr/bin/env python3

import time import sys import numpy as np import xarray as xr

ds = xr.Dataset() ds['data1'] = xr.DataArray(np.arange(1000), coords={'t1': np.linspace(0, 1, 1000)}) ds['data1b'] = xr.DataArray(np.arange(1000, 2000), coords={'t1': np.linspace(0, 1, 1000)}) ds['data2'] = xr.DataArray(np.arange(2000, 5000), coords={'t2': np.linspace(0, 1, 3000)}) ds['data2b'] = xr.DataArray(np.arange(6000, 9000), coords={'t2': np.linspace(0, 1, 3000)}) if sys.argv[1] == "nodrop": now = time.time() print(ds.where(ds.data1 < 50, drop=True)) print("Took {} seconds".format(time.time() - now)) elif sys.argv[1] == "drop": ds1 = ds.drop('t2') now = time.time() print(ds1.where(ds1.data1 < 50, drop=True)) print("Took {} seconds".format(time.time() - now)) input("Press return to exit") ```

 
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   Using where() in datasets with dataarrays with different dimensions results in huge RAM consumption 201617371
273523770 https://github.com/pydata/xarray/issues/1217#issuecomment-273523770 https://api.github.com/repos/pydata/xarray/issues/1217 MDEyOklzc3VlQ29tbWVudDI3MzUyMzc3MA== jacklovell 4849151 2017-01-18T16:25:19Z 2017-01-18T16:25:19Z NONE

data1 and data2 represent two stages of data acquisition within one "shot" of our experiment. I'd like to be able to group each shot's data into a single dataset.

I want to extract from the dataset only the values for which my where() condition is true, and I'll only be using DataArrays which share the same dimension as the one in the condition. For example, if I do: ds_low = ds.where(ds.data1 < 0.1, drop=True) I'll only use stuff in ds_low with the same dimension as ds.data1. So in my case extracting the data with the shared dimension using ds.drop(<unused dim>) is appropriate.

It would be nice to have xarray throw a warning or error to prevent me chomping up all the RAM in my system if I do try to do this sort of thing though. Or it could simply mask off with NaN everything in the DataArrays which have a different dimension.

Give me a second to provide a minimal working example.

 
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   Using where() in datasets with dataarrays with different dimensions results in huge RAM consumption 201617371

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