Traktor/myenv/Lib/site-packages/scipy/datasets/tests/test_data.py
2024-05-23 01:57:24 +02:00

124 lines
4.0 KiB
Python

from scipy.datasets._registry import registry
from scipy.datasets._fetchers import data_fetcher
from scipy.datasets._utils import _clear_cache
from scipy.datasets import ascent, face, electrocardiogram, download_all
from numpy.testing import assert_equal, assert_almost_equal
import os
import pytest
try:
import pooch
except ImportError:
raise ImportError("Missing optional dependency 'pooch' required "
"for scipy.datasets module. Please use pip or "
"conda to install 'pooch'.")
data_dir = data_fetcher.path # type: ignore
def _has_hash(path, expected_hash):
"""Check if the provided path has the expected hash."""
if not os.path.exists(path):
return False
return pooch.file_hash(path) == expected_hash
class TestDatasets:
@pytest.fixture(scope='module', autouse=True)
def test_download_all(self):
# This fixture requires INTERNET CONNECTION
# test_setup phase
download_all()
yield
def test_existence_all(self):
assert len(os.listdir(data_dir)) >= len(registry)
def test_ascent(self):
assert_equal(ascent().shape, (512, 512))
# hash check
assert _has_hash(os.path.join(data_dir, "ascent.dat"),
registry["ascent.dat"])
def test_face(self):
assert_equal(face().shape, (768, 1024, 3))
# hash check
assert _has_hash(os.path.join(data_dir, "face.dat"),
registry["face.dat"])
def test_electrocardiogram(self):
# Test shape, dtype and stats of signal
ecg = electrocardiogram()
assert_equal(ecg.dtype, float)
assert_equal(ecg.shape, (108000,))
assert_almost_equal(ecg.mean(), -0.16510875)
assert_almost_equal(ecg.std(), 0.5992473991177294)
# hash check
assert _has_hash(os.path.join(data_dir, "ecg.dat"),
registry["ecg.dat"])
def test_clear_cache(tmp_path):
# Note: `tmp_path` is a pytest fixture, it handles cleanup
dummy_basepath = tmp_path / "dummy_cache_dir"
dummy_basepath.mkdir()
# Create three dummy dataset files for dummy dataset methods
dummy_method_map = {}
for i in range(4):
dummy_method_map[f"data{i}"] = [f"data{i}.dat"]
data_filepath = dummy_basepath / f"data{i}.dat"
data_filepath.write_text("")
# clear files associated to single dataset method data0
# also test callable argument instead of list of callables
def data0():
pass
_clear_cache(datasets=data0, cache_dir=dummy_basepath,
method_map=dummy_method_map)
assert not os.path.exists(dummy_basepath/"data0.dat")
# clear files associated to multiple dataset methods "data3" and "data4"
def data1():
pass
def data2():
pass
_clear_cache(datasets=[data1, data2], cache_dir=dummy_basepath,
method_map=dummy_method_map)
assert not os.path.exists(dummy_basepath/"data1.dat")
assert not os.path.exists(dummy_basepath/"data2.dat")
# clear multiple dataset files "data3_0.dat" and "data3_1.dat"
# associated with dataset method "data3"
def data4():
pass
# create files
(dummy_basepath / "data4_0.dat").write_text("")
(dummy_basepath / "data4_1.dat").write_text("")
dummy_method_map["data4"] = ["data4_0.dat", "data4_1.dat"]
_clear_cache(datasets=[data4], cache_dir=dummy_basepath,
method_map=dummy_method_map)
assert not os.path.exists(dummy_basepath/"data4_0.dat")
assert not os.path.exists(dummy_basepath/"data4_1.dat")
# wrong dataset method should raise ValueError since it
# doesn't exist in the dummy_method_map
def data5():
pass
with pytest.raises(ValueError):
_clear_cache(datasets=[data5], cache_dir=dummy_basepath,
method_map=dummy_method_map)
# remove all dataset cache
_clear_cache(datasets=None, cache_dir=dummy_basepath)
assert not os.path.exists(dummy_basepath)