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
4. Commit your changes: git add * && git commit -m "added my_new_testdata"
5. Open a Pull Request.

If you wish to perform preliminary tests against the dataset on a particular branch/commit, this can be done with the following procedure:

• To gather a single file:

import pooch

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

test_data_path = pooch.retrieve(
    url=f"{GITHUB_URL}/raw/{BRANCH_OR_COMMIT_HASH}/data/my_test_data.nc",
    known_hash="md5:1234567890abcdef",
)

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

ds = xr.open_dataset(test_data_path)

Loading data

If you wish to load data from this repository, this can be done with the following procedure:

• To gather a single file (using the streamflow_BCC-CSM1.1-m_rcp45.nc file as an example):

import pooch
import xarray as xr

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

test_data_path = pooch.retrieve(
    url=f"{GITHUB_URL}/raw/{BRANCH_OR_COMMIT_HASH}/data/cc_indicators/streamflow_BCC-CSM1.1-m_rcp45.nc",
    known_hash="md5:0ac83a4ee9dceecda68ac1ee542f50de",
)
ds = xr.open_dataset(test_data_path)

• To open multiple files stored within a zip archive (using the reference.zip file as an example):

import pooch
import xarray as xr

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

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

# Exactly how you open the files depends on the structure of the data. This will work for the reference.zip file:
ds = xr.open_mfdataset(files, combine="nested", concat_dim="platform")

• You can also simply extract the files to a directory:

from pathlib import Path
from zipfile import ZipFile

import pooch

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

test_data_path = pooch.retrieve(
    url=f"{GITHUB_URL}/raw/{BRANCH_OR_COMMIT_HASH}/data/cc_indicators/reference.zip",
    known_hash="md5:192544f3a081375a81d423e08038d32a",
)

directory_to_extract_to = Path(test_data_path).parent  # To extract to the same directory as the zip file
with ZipFile(test_data_path, 'r') as zip_ref:
    zip_ref.extractall(directory_to_extract_to)
    files = zip_ref.namelist()

Available datasets

Files

File	Size	Checksum
data/ravenpy/ERA5_Riviere_Rouge_global.nc	150.7 kiB	de985fa27ddceac690aeb34182a93f11
data/ravenpy/Debit_Riviere_Rouge.nc	343.5 kiB	5b0feedc34333244b1d9e9c251323478
data/optimal_interpolation/OI_data_corrected.zip	3.2 MiB	acdf90b78b53595eb97ff0e84fc07aa8
data/optimal_interpolation/OI_data.zip	2.9 MiB	1ab72270023366d0410eb6972d1e2656
data/cc_indicators/streamflow_BCC-CSM1.1-m_rcp45.nc	730.1 kiB	0ac83a4ee9dceecda68ac1ee542f50de
data/cc_indicators/reference.zip	23.7 kiB	192544f3a081375a81d423e08038d32a
data/cc_indicators/deltas.zip	1.6 MiB	ce6371e073e5324f9ade385c1c03e7eb
data/LSTM_data/single_watershed.nc	1.2 MiB	b1dfe4641321f63fb9198e9538fd679b
data/LSTM_data/multiple_watersheds.nc	3.2 MiB	31e1ae3ffcfd14d6a92faefd3d8bd57a
data/LSTM_data/LSTM_test_data_local.nc	118.0 kiB	2abfe4dd0287a43c1ab40372f4fc4de8
data/LSTM_data/LSTM_test_data.nc	325.1 kiB	e7f1ddba0cf3dc3c5c6aa28a0c504fa2