xhydro-testdata

Testing data to support the xHydro and xDatasets projects.

Contributing

In order to add a new dataset to the xHydro/xDatasets testing data, please ensure you perform the following:

1. Create a new branch: git checkout -b my_new_testdata_branch
2. Place your dataset within an appropriate subdirectory (or create a new one: mkdir data).
3. Run the md5 checksum generation script: python report_check_sums.py. This will update the data/registry.txt file with the new dataset and its checksum.
4. Commit your changes: git add * && git commit -m "added my_new_testdata"
5. Open a Pull Request.
6. Once the Pull Request has been merged, create a new release and tag it with the current date (e.g. v2026-02-04).
7. In xHydro itself, change the default_testdata_version variable to the new release tag (e.g. v2026-02-04) in xhydro/testing/helpers.py.
8. Overwrite the entries in xhydro/testing/registry.txt file with the new entries from this repository's data/registry.txt file.

Loading data with xHydro

• To gather a single file:

from xhydro.testing.helpers import deveraux

test_data_path = deveraux(branch="main").fetch(  # or "my_development_branch"
    "my_subfolder/my_test_data.nc"
)

# If your testing data is `xarray`-readable, you can then use the following:
import xarray as xr

ds = xr.open_dataset(test_data_path)

• To download and unzip multiple files stored within a zip archive:

from xhydro.testing.helpers import deveraux
import pooch

files = deveraux().fetch(
    "my_subfolder/my_test_data.zip",
    processor=pooch.Unzip(),
)

# Each file within the zip archive will be downloaded to a temporary directory, and the `files` variable will contain a list of the paths to each of these files. Exactly how you open the files depends on the structure of the data.

Loading data without using xHydro

The above procedure is the recommended way to load data from this repository, but if you wish to load data without using xHydro, you can do so with the following procedure:

• To gather a single file:

import pooch

GITHUB_URL = "https://github.com/hydrologie/xhydro-testdata"
BRANCH_OR_COMMIT_HASH = "main"  # or "my_development_branch"

test_data_path = pooch.retrieve(
    url=f"{GITHUB_URL}/raw/{BRANCH_OR_COMMIT_HASH}/data/my_subfolder/my_test_data.nc",
    known_hash="sha256:1234567890abcdef",
)

• To download and unzip multiple files stored within a zip archive:

import pooch

GITHUB_URL = "https://github.com/hydrologie/xhydro-testdata"
BRANCH_OR_COMMIT_HASH = "main"  # or "my_development_branch"

files = pooch.retrieve(
    url=f"{GITHUB_URL}/raw/{BRANCH_OR_COMMIT_HASH}/data/my_subfolder/my_test_data.zip",
    known_hash="md5:192544f3a081375a81d423e08038d32a",
    processor=pooch.Unzip(),
)

# Each file within the zip archive will be downloaded to a temporary directory, and the `files` variable will contain a list of the paths to each of these files. Exactly how you open the files depends on the structure of the data.

Available datasets

Files

File	Size	Checksum
use_case/deltas.zip	57.9 kiB	sha256:70eb2da69550c1b839749cb5552bcd7b44196ff4d8ab7951c2e5254638a7b598
ravenpy/hru_subset.zip	193.9 kiB	sha256:969b4a0d0c1f0c24dbb5baca98676f2573178cd58ef4162aa6b9fce51ceecf06
ravenpy/ERA5_Riviere_Rouge_global.nc	150.7 kiB	sha256:341ac746130a0d3e3189d3a41dc8528d6bd22869a519b68e134959407ad200a3
ravenpy/Debit_Riviere_Rouge.nc	343.5 kiB	sha256:d0a27de5eb3cb466e60669d894296bcbc4e9f590edc1ae2490685babd10b2d22
precip_oi/stations_flags_clean_subset.nc	70.0 kiB	sha256:03513b859e6c99ab02728f49b0e3e7382375e7311c68e33c8d59d6f734eb08d1
precip_oi/ERA5_land_3_variables_raw_subset.nc	3.8 MiB	sha256:09ee75f73bb4e88bddb6c9184245766ebe8cc6b13b58ef58a4754e523138ff1f
pmp/CMIP.CCCma.CanESM5.historical.r1i1p1f1.fx.gn.zarr.zip	12.7 kiB	sha256:dc7c92fc098ca5adf43e76b25e3f79b70815ed961e945952983bb68b3c380cf1
pmp/CMIP.CCCma.CanESM5.historical.r1i1p1f1.day.gn.zarr.zip	758.5 kiB	sha256:d5775b2f09381f2f3a7cc06af76f62fb216b60252aab3a602280a513554d59ad
optimal_interpolation/OI_data_corrected.zip	3.2 MiB	sha256:48ee08325bd35c6bce5c0e52e3ee25df27c830720929060f607fb0417c476941
optimal_interpolation/OI_data.zip	2.9 MiB	sha256:9cd881a19fc82bda560e636d3f6a2c40718b82f5bce1e31aedce6d1b2e41d7d8
hydro_modelling/ERA5_testdata.nc	100.9 kiB	sha256:7051f696f30d9772511cfbae81a0be0bd2898f25d123227f5f5fa4869138fa4e
extreme_value_analysis/sea-levels_fremantle.zarr.zip	5.6 kiB	sha256:af6abf274bf8809eca7fa0d33540979203fa4d9833e13c8e6adf3f4d15966a40
extreme_value_analysis/rainfall_excedance.zarr.zip	7.5 kiB	sha256:ce29ea4b4b427bac0c11c0bb1ead4bb961aee2ba88ac0abffc859a155986f232
extreme_value_analysis/genpareto.zip	136.0 kiB	sha256:f6b67160dd1373ad6a9ce511788184a0bbed23e0c297315d1686ecbb88e16e0a
extreme_value_analysis/genextreme.zip	228.0 kiB	sha256:8d036acca8b9a4608930c97d6cebfbf24205a20c7e43c47dcbdc14221a643b0c
extreme_value_analysis/NOAA_GFDL_ESM4.zip	88.7 kiB	sha256:483a5ffd398aa60db2d2c6d41857cd02c201a7f9efcacef2610a2521f72a22b6
cc_indicators/streamflow_BCC-CSM1.1-m_rcp45.nc	730.1 kiB	sha256:8699f40153abdea098d580f73b1f8ad64875823f0d8479fdc4f8a40b4adcaf5e
cc_indicators/reference.zip	23.7 kiB	sha256:80e21de39a78da49f809ddf35bd2d21271828450ea2da71eac08aab13c7b846e
cc_indicators/deltas.zip	1.6 MiB	sha256:d6bff404c7e1514d819db9e46c69a3756a0a5f847586fc2fa4e573de3ee1d355
LSTM_data/single_watershed.nc	1.2 MiB	sha256:bea90106d540a7b8b6aca4013ae6c2a9f202a37620f9f265fe3d7c70bf9ff7c8
LSTM_data/multiple_watersheds.nc	3.2 MiB	sha256:acc5a9821fefbd85cda5283cdfdc00c9290662b5ff6f83ac5637ae84f730c427
LSTM_data/LSTM_test_data_local.nc	118.0 kiB	sha256:4e4a70efd9405b481556c73f700dd87d0bf2169366a89b14cd8d8f771f093da8
LSTM_data/LSTM_test_data.nc	325.1 kiB	sha256:fcac6067708cbdc7e4df6d05471e89ce562bfe8720f0324f113d17fa9d1fe87b