Source: satpy Version: 0.31.0-2 X-Debbugs-CC: debian-ci@lists.debian.org Severity: serious User: debian-ci@lists.debian.org Usertags: regression Dear maintainer(s),With a recent upload of satpy the autopkgtest of satpy fails in testing when that autopkgtest is run with the binary packages of satpy from unstable. It passes when run with only packages from testing. In tabular form:
pass fail satpy from testing 0.31.0-2 all others from testing from testingI copied some of the output at the bottom of this report. Did the set of tests get extended? It seems some tests are running out of memory space on 32 bit architectures.
Currently this regression is blocking the migration to testing [1]. Can you please investigate the situation and fix it?
More information about this bug and the reason for filing it can be found on https://wiki.debian.org/ContinuousIntegration/RegressionEmailInformation Paul [1] https://qa.debian.org/excuses.php?package=satpy https://ci.debian.net/data/autopkgtest/testing/armhf/s/satpy/16844833/log.gz==================================== ERRORS ==================================== _ ERROR at setup of TestModisL1b.test_scene_available_datasets[modis_l1b_nasa_mod021km_file-expected_names0-expected_data_res0-expected_geo_res0] _
request = <FixtureRequest for <Function test_scene_available_datasets[modis_l1b_nasa_mod021km_file-expected_names0-expected_data_res0-expected_geo_res0]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:316: in modis_l1b_nasa_mod021km_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_scene_available_datasets[modis_l1b_imapp_1000m_file-expected_names1-expected_data_res1-expected_geo_res1] _
request = <FixtureRequest for <Function test_scene_available_datasets[modis_l1b_imapp_1000m_file-expected_names1-expected_data_res1-expected_geo_res1]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:330: in modis_l1b_imapp_1000m_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_scene_available_datasets[modis_l1b_nasa_mod02hkm_file-expected_names2-expected_data_res2-expected_geo_res2] _
request = <FixtureRequest for <Function test_scene_available_datasets[modis_l1b_nasa_mod02hkm_file-expected_names2-expected_data_res2-expected_geo_res2]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:344: in modis_l1b_nasa_mod02hkm_file variable_infos.update(_get_visible_variable_info("EV_500_RefSB", 250, AVAILABLE_QKM_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 250, num_bands = 2, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 168. MiB for an array with shape (2, 8120, 5416) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_scene_available_datasets[modis_l1b_nasa_mod02qkm_file-expected_names3-expected_data_res3-expected_geo_res3] _
request = <FixtureRequest for <Function test_scene_available_datasets[modis_l1b_nasa_mod02qkm_file-expected_names3-expected_data_res3-expected_geo_res3]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:355: in modis_l1b_nasa_mod02qkm_file variable_infos.update(_get_visible_variable_info("EV_250_RefSB", 250, AVAILABLE_QKM_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 250, num_bands = 2, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 168. MiB for an array with shape (2, 8120, 5416) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_load_longitude_latitude[modis_l1b_nasa_mod021km_file-True-False-False-1000] _
request = <FixtureRequest for <Function test_load_longitude_latitude[modis_l1b_nasa_mod021km_file-True-False-False-1000]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:316: in modis_l1b_nasa_mod021km_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_load_longitude_latitude[modis_l1b_imapp_1000m_file-True-False-False-1000] _
request = <FixtureRequest for <Function test_load_longitude_latitude[modis_l1b_imapp_1000m_file-True-False-False-1000]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:330: in modis_l1b_imapp_1000m_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_load_longitude_latitude[modis_l1b_nasa_mod02hkm_file-False-True-True-250] _
request = <FixtureRequest for <Function test_load_longitude_latitude[modis_l1b_nasa_mod02hkm_file-False-True-True-250]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:344: in modis_l1b_nasa_mod02hkm_file variable_infos.update(_get_visible_variable_info("EV_500_RefSB", 250, AVAILABLE_QKM_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 250, num_bands = 2, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 168. MiB for an array with shape (2, 8120, 5416) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_load_longitude_latitude[modis_l1b_nasa_mod02qkm_file-False-True-True-250] _
request = <FixtureRequest for <Function test_load_longitude_latitude[modis_l1b_nasa_mod02qkm_file-False-True-True-250]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:355: in modis_l1b_nasa_mod02qkm_file variable_infos.update(_get_visible_variable_info("EV_250_RefSB", 250, AVAILABLE_QKM_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 250, num_bands = 2, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 168. MiB for an array with shape (2, 8120, 5416) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL1b.test_load_longitude_latitude[modis_l1b_nasa_1km_mod03_files-True-True-True-250] _
request = <FixtureRequest for <Function test_load_longitude_latitude[modis_l1b_nasa_1km_mod03_files-True-True-True-250]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:316: in modis_l1b_nasa_mod021km_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError __________ ERROR at setup of TestModisL1b.test_load_sat_zenith_angle ___________
request = <FixtureRequest for <Function test_load_sat_zenith_angle>> def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):item.callspec.params[param] = request.getfixturevalue(val.name)
elif param not in item.funcargs: item.funcargs[param] = request.getfixturevalue(param) > _fillfixtures()/usr/lib/python3/dist-packages/pytest_lazyfixture.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:316: in modis_l1b_nasa_mod021km_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _________________ ERROR at setup of TestModisL1b.test_load_vis _________________
request = <FixtureRequest for <Function test_load_vis>> def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):item.callspec.params[param] = request.getfixturevalue(val.name)
elif param not in item.funcargs: item.funcargs[param] = request.getfixturevalue(param) > _fillfixtures()/usr/lib/python3/dist-packages/pytest_lazyfixture.py:39: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:316: in modis_l1b_nasa_mod021km_file variable_infos.update(_get_visible_variable_info("EV_1KM_RefSB", 1000, AVAILABLE_1KM_VIS_PRODUCT_NAMES)) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:116: in _get_visible_variable_info
data = _generate_visible_data(resolution, len(bands))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
resolution = 1000, num_bands = 14, dtype = <class 'numpy.uint16'>def _generate_visible_data(resolution: int, num_bands: int, dtype=np.uint16) -> np.ndarray:
shape = _shape_for_resolution(resolution)
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 73.4 MiB for an array with shape (14, 2030, 1354) and data type uint16data = np.zeros((num_bands, shape[0], shape[1]), dtype=dtype)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:76: MemoryError _ ERROR at setup of TestModisL2.test_load_category_dataset[modis_l2_nasa_mod35_mod03_files-loadables0-1000-1000-True] _
request = <FixtureRequest for <Function test_load_category_dataset[modis_l2_nasa_mod35_mod03_files-loadables0-1000-1000-True]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:365: in modis_l1b_nasa_mod03_file variable_infos = _get_l1b_geo_variable_info(filename, 1000, include_angles=True) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:188: in _get_l1b_geo_variable_info
variables_info.update(_get_lonlat_variable_info(geo_resolution))/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:81: in _get_lonlat_variable_info
lon_5km, lat_5km = _generate_lonlat_data(resolution)/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:61: in _generate_lonlat_data
lat = np.repeat(np.linspace(35., 45., shape[0])[:, None], shape[1], 1) /usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:479: in repeat return _wrapfunc(a, 'repeat', repeats, axis=axis)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
obj = array([[35. ], [35.00492854], [35.00985707], ..., [44.99014293], [44.99507146], [45. ]]) method = 'repeat', args = (1354,), kwds = {'axis': 1} bound = <built-in method repeat of numpy.ndarray object at 0x10796548> def _wrapfunc(obj, method, *args, **kwds): bound = getattr(obj, method, None) if bound is None: return _wrapit(obj, method, *args, **kwds) try:
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 21.0 MiB for an array with shape (2030, 1354) and data type float64return bound(*args, **kwds)
/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:58: MemoryError_ ERROR at setup of TestModisL2.test_load_category_dataset[modis_l2_imapp_mask_byte1_geo_files-loadables1-None-1000-True] _
request = <FixtureRequest for <Function test_load_category_dataset[modis_l2_imapp_mask_byte1_geo_files-loadables1-None-1000-True]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:365: in modis_l1b_nasa_mod03_file variable_infos = _get_l1b_geo_variable_info(filename, 1000, include_angles=True) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:188: in _get_l1b_geo_variable_info
variables_info.update(_get_lonlat_variable_info(geo_resolution))/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:81: in _get_lonlat_variable_info
lon_5km, lat_5km = _generate_lonlat_data(resolution)/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:61: in _generate_lonlat_data
lat = np.repeat(np.linspace(35., 45., shape[0])[:, None], shape[1], 1) /usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:479: in repeat return _wrapfunc(a, 'repeat', repeats, axis=axis)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
obj = array([[35. ], [35.00492854], [35.00985707], ..., [44.99014293], [44.99507146], [45. ]]) method = 'repeat', args = (1354,), kwds = {'axis': 1} bound = <built-in method repeat of numpy.ndarray object at 0x10796548> def _wrapfunc(obj, method, *args, **kwds): bound = getattr(obj, method, None) if bound is None: return _wrapit(obj, method, *args, **kwds) try:
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 21.0 MiB for an array with shape (2030, 1354) and data type float64return bound(*args, **kwds)
/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:58: MemoryError_ ERROR at setup of TestModisL2.test_load_250m_cloud_mask_dataset[modis_l2_nasa_mod35_mod03_files-True] _
request = <FixtureRequest for <Function test_load_250m_cloud_mask_dataset[modis_l2_nasa_mod35_mod03_files-True]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:365: in modis_l1b_nasa_mod03_file variable_infos = _get_l1b_geo_variable_info(filename, 1000, include_angles=True) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:188: in _get_l1b_geo_variable_info
variables_info.update(_get_lonlat_variable_info(geo_resolution))/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:81: in _get_lonlat_variable_info
lon_5km, lat_5km = _generate_lonlat_data(resolution)/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:61: in _generate_lonlat_data
lat = np.repeat(np.linspace(35., 45., shape[0])[:, None], shape[1], 1) /usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:479: in repeat return _wrapfunc(a, 'repeat', repeats, axis=axis)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
obj = array([[35. ], [35.00492854], [35.00985707], ..., [44.99014293], [44.99507146], [45. ]]) method = 'repeat', args = (1354,), kwds = {'axis': 1} bound = <built-in method repeat of numpy.ndarray object at 0x10796548> def _wrapfunc(obj, method, *args, **kwds): bound = getattr(obj, method, None) if bound is None: return _wrapit(obj, method, *args, **kwds) try:
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 21.0 MiB for an array with shape (2030, 1354) and data type float64return bound(*args, **kwds)
/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:58: MemoryError_ ERROR at setup of TestModisL2.test_load_l2_dataset[modis_l2_imapp_snowmask_geo_files-loadables2-1000-True] _
request = <FixtureRequest for <Function test_load_l2_dataset[modis_l2_imapp_snowmask_geo_files-loadables2-1000-True]>>
def fill(request): item = request._pyfuncitem fixturenames = getattr(item, "fixturenames", None) if fixturenames is None: fixturenames = request.fixturenames if hasattr(item, 'callspec'):for param, val in sorted_by_dependency(item.callspec.params, fixturenames):
if val is not None and is_lazy_fixture(val):
item.callspec.params[param] = request.getfixturevalue(val.name)
/usr/lib/python3/dist-packages/pytest_lazyfixture.py:35: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:365: in modis_l1b_nasa_mod03_file variable_infos = _get_l1b_geo_variable_info(filename, 1000, include_angles=True) /usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:188: in _get_l1b_geo_variable_info
variables_info.update(_get_lonlat_variable_info(geo_resolution))/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:81: in _get_lonlat_variable_info
lon_5km, lat_5km = _generate_lonlat_data(resolution)/usr/lib/python3/dist-packages/satpy/tests/reader_tests/_modis_fixtures.py:61: in _generate_lonlat_data
lat = np.repeat(np.linspace(35., 45., shape[0])[:, None], shape[1], 1) /usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:479: in repeat return _wrapfunc(a, 'repeat', repeats, axis=axis)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
obj = array([[35. ], [35.00492854], [35.00985707], ..., [44.99014293], [44.99507146], [45. ]]) method = 'repeat', args = (1354,), kwds = {'axis': 1} bound = <built-in method repeat of numpy.ndarray object at 0x10796548> def _wrapfunc(obj, method, *args, **kwds): bound = getattr(obj, method, None) if bound is None: return _wrapit(obj, method, *args, **kwds) try:
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 21.0 MiB for an array with shape (2030, 1354) and data type float64return bound(*args, **kwds)
/usr/lib/python3/dist-packages/numpy/core/fromnumeric.py:58: MemoryError=================================== FAILURES =================================== _____________________________ TestScene.test_crop ______________________________
self = <satpy.tests.test_scene.TestScene object at 0xb4720760> def test_crop(self): """Test the crop method.""" from satpy import Scene from xarray import DataArray from pyresample.geometry import AreaDefinition scene1 = Scene()area_extent = (-5570248.477339745, -5561247.267842293, 5567248.074173927,
5570248.477339745) proj_dict = {'a': 6378169.0, 'b': 6356583.8, 'h': 35785831.0, 'lon_0': 0.0, 'proj': 'geos', 'units': 'm'} x_size = 3712 y_size = 3712 area_def = AreaDefinition( 'test', 'test', 'test', proj_dict, x_size, y_size, area_extent, ) area_def2 = AreaDefinition( 'test2', 'test2', 'test2', proj_dict, x_size // 2, y_size // 2, area_extent, ) scene1["1"] = DataArray(np.zeros((y_size, x_size)))scene1["2"] = DataArray(np.zeros((y_size, x_size)), dims=('y', 'x'))
scene1["3"] = DataArray(np.zeros((y_size, x_size)), dims=('y', 'x'),
attrs={'area': area_def})E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 105. MiB for an array with shape (3712, 3712) and data type float64
/usr/lib/python3/dist-packages/satpy/tests/test_scene.py:422: MemoryError_________________________ TestScene.test_crop_epsg_crs _________________________
self = <satpy.tests.test_scene.TestScene object at 0xf3acbac0> def test_crop_epsg_crs(self): """Test the crop method when source area uses an EPSG code.""" from satpy import Scene from xarray import DataArray from pyresample.geometry import AreaDefinition scene1 = Scene() area_extent = (699960.0, 5390220.0, 809760.0, 5500020.0) x_size = 3712 y_size = 3712 area_def = AreaDefinition( 'test', 'test', 'test', "EPSG:32630", x_size, y_size, area_extent, )
scene1["1"] = DataArray(np.zeros((y_size, x_size)), dims=('y', 'x'),
attrs={'area': area_def})E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 105. MiB for an array with shape (3712, 3712) and data type float64
/usr/lib/python3/dist-packages/satpy/tests/test_scene.py:484: MemoryError___________________________ TestScene.test_crop_rgb ____________________________
self = <satpy.tests.test_scene.TestScene object at 0xb4c6bc58> def test_crop_rgb(self): """Test the crop method on multi-dimensional data.""" from satpy import Scene from xarray import DataArray from pyresample.geometry import AreaDefinition scene1 = Scene()area_extent = (-5570248.477339745, -5561247.267842293, 5567248.074173927,
5570248.477339745) proj_dict = {'a': 6378169.0, 'b': 6356583.8, 'h': 35785831.0, 'lon_0': 0.0, 'proj': 'geos', 'units': 'm'} x_size = 3712 y_size = 3712 area_def = AreaDefinition( 'test', 'test', 'test', proj_dict, x_size, y_size, area_extent, ) area_def2 = AreaDefinition( 'test2', 'test2', 'test2', proj_dict, x_size // 2, y_size // 2, area_extent, )
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 315. MiB for an array with shape (3, 3712, 3712) and data type float64scene1["1"] = DataArray(np.zeros((3, y_size, x_size)), dims=('bands', 'y', 'x'), attrs={'area': area_def})
/usr/lib/python3/dist-packages/satpy/tests/test_scene.py:521: MemoryError_____________________ TestSceneAggregation.test_aggregate ______________________
self = <satpy.tests.test_scene.TestSceneAggregation testMethod=test_aggregate>
def test_aggregate(self): """Test the aggregate method.""" x_size = 3712 y_size = 3712 > scene1 = self._create_test_data(x_size, y_size)/usr/lib/python3/dist-packages/satpy/tests/test_scene.py:1810: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/test_scene.py:1836: in _create_test_data
scene1["2"] = DataArray(np.ones((y_size, x_size)), dims=('y', 'x'),_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
shape = (3712, 3712), dtype = None, order = 'C' @set_module('numpy') def ones(shape, dtype=None, order='C'): """ Return a new array of given shape and type, filled with ones. Parameters ---------- shape : int or sequence of ints Shape of the new array, e.g., ``(2, 3)`` or ``2``. dtype : data-type, optionalThe desired data-type for the array, e.g., `numpy.int8`. Default is
`numpy.float64`. order : {'C', 'F'}, optional, default: C Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory. Returns ------- out : ndarray Array of ones with the given shape, dtype, and order. See Also -------- ones_like : Return an array of ones with shape and type of input. empty : Return a new uninitialized array. zeros : Return a new array setting values to zero. full : Return a new array of given shape filled with value. Examples -------- >>> np.ones(5) array([1., 1., 1., 1., 1.]) >>> np.ones((5,), dtype=int) array([1, 1, 1, 1, 1]) >>> np.ones((2, 1)) array([[1.], [1.]]) >>> s = (2,2) >>> np.ones(s) array([[1., 1.], [1., 1.]]) """
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 105. MiB for an array with shape (3712, 3712) and data type float64a = empty(shape, dtype, order)
/usr/lib/python3/dist-packages/numpy/core/numeric.py:192: MemoryError______________ TestSceneAggregation.test_aggregate_with_boundary _______________
self = <satpy.tests.test_scene.TestSceneAggregation testMethod=test_aggregate_with_boundary>
def test_aggregate_with_boundary(self): """Test aggregation with boundary argument.""" x_size = 3711 y_size = 3711 > scene1 = self._create_test_data(x_size, y_size)/usr/lib/python3/dist-packages/satpy/tests/test_scene.py:1860: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/test_scene.py:1835: in _create_test_data scene1["1"] = DataArray(np.ones((y_size, x_size)), attrs={'_satpy_id_keys': default_id_keys_config}) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
shape = (3711, 3711), dtype = None, order = 'C' @set_module('numpy') def ones(shape, dtype=None, order='C'): """ Return a new array of given shape and type, filled with ones. Parameters ---------- shape : int or sequence of ints Shape of the new array, e.g., ``(2, 3)`` or ``2``. dtype : data-type, optionalThe desired data-type for the array, e.g., `numpy.int8`. Default is
`numpy.float64`. order : {'C', 'F'}, optional, default: C Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory. Returns ------- out : ndarray Array of ones with the given shape, dtype, and order. See Also -------- ones_like : Return an array of ones with shape and type of input. empty : Return a new uninitialized array. zeros : Return a new array setting values to zero. full : Return a new array of given shape filled with value. Examples -------- >>> np.ones(5) array([1., 1., 1., 1., 1.]) >>> np.ones((5,), dtype=int) array([1, 1, 1, 1, 1]) >>> np.ones((2, 1)) array([[1.], [1.]]) >>> s = (2,2) >>> np.ones(s) array([[1., 1.], [1., 1.]]) """
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 105. MiB for an array with shape (3711, 3711) and data type float64a = empty(shape, dtype, order)
/usr/lib/python3/dist-packages/numpy/core/numeric.py:192: MemoryError_____________________ TestMimicTPW2Reader.test_load_mimic ______________________
self = <satpy.tests.reader_tests.test_mimic_TPW2_nc.TestMimicTPW2Reader testMethod=test_load_mimic>
def test_load_mimic(self): """Load Mimic data.""" from satpy.readers import load_reader r = load_reader(self.reader_configs)with mock.patch('satpy.readers.mimic_TPW2_nc.netCDF4.Variable', xr.DataArray):
loadables = r.select_files_from_pathnames([ 'comp20190619.130000.nc', ]) r.create_filehandlers(loadables)
ds = r.load(['tpwGrid'])
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_mimic_TPW2_nc.py:126: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load
ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:701: in _load_dataset
res = xr.concat(slice_list, dim=dim) /usr/lib/python3/dist-packages/xarray/core/concat.py:242: in concat return f(/usr/lib/python3/dist-packages/xarray/core/concat.py:580: in _dataarray_concat
ds = _dataset_concat( /usr/lib/python3/dist-packages/xarray/core/concat.py:519: in _dataset_concatcombined = concat_vars(vars, dim, positions, combine_attrs=combine_attrs)
/usr/lib/python3/dist-packages/xarray/core/variable.py:2897: in concatreturn Variable.concat(variables, dim, positions, shortcut, combine_attrs)
/usr/lib/python3/dist-packages/xarray/core/variable.py:1854: in concat data = duck_array_ops.concatenate(arrays, axis=axis)/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:302: in concatenate
return _concatenate(as_shared_dtype(arrays), axis=axis) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:56: in f return wrapped(*args, **kwargs)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
args = ([array([[1.62000e+08, 1.62000e+08, 1.62000e+08, ..., 1.62018e+08, 1.62018e+08, 1.62018e+08], [1.61982e... [0.00000e+00, 1.00000e+00, 2.00000e+00, ..., 1.79970e+04, 1.79980e+04, 1.79990e+04]], dtype=float32)],) kwargs = {'axis': 0}relevant_args = [array([[1.62000e+08, 1.62000e+08, 1.62000e+08, ..., 1.62018e+08,
1.62018e+08, 1.62018e+08], [1.61982e+...], [0.00000e+00, 1.00000e+00, 2.00000e+00, ..., 1.79970e+04, 1.79980e+04, 1.79990e+04]], dtype=float32)]
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 618. MiB for an array with shape (9001, 18000) and data type float32???
<__array_function__ internals>:5: MemoryError_ TestModisL2.test_load_longitude_latitude[modis_l2_nasa_mod35_file-True-False-False-1000] _
self = <satpy.tests.reader_tests.test_modis_l2.TestModisL2 object at 0xe78c0328> input_files = ['/tmp/pytest-of-debci/pytest-0/modis_l20/MOD35_L2.A2021324.1132.061.2021324113236.hdf']
has_5km = True, has_500 = False, has_250 = False, default_res = 1000 @pytest.mark.parametrize( ('input_files', 'has_5km', 'has_500', 'has_250', 'default_res'), [ [lazy_fixture('modis_l2_nasa_mod35_file'), True, False, False, 1000], ] )def test_load_longitude_latitude(self, input_files, has_5km, has_500, has_250, default_res): """Test that longitude and latitude datasets are loaded correctly."""
from .test_modis_l1b import _load_and_check_geolocation scene = Scene(reader='modis_l2', filenames=input_files) shape_5km = _shape_for_resolution(5000) shape_500m = _shape_for_resolution(500) shape_250m = _shape_for_resolution(250) default_shape = _shape_for_resolution(default_res)with dask.config.set(scheduler=CustomScheduler(max_computes=1 + has_5km + has_500 + has_250)):
_load_and_check_geolocation(scene, "*", default_res, default_shape, True,
check_callback=_check_shared_metadata)/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_modis_l2.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_modis_l1b.py:56: in _load_and_check_geolocation
lon_vals, lat_vals = dask.compute(lon_arr, lat_arr) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/satpy/tests/utils.py:265: in __call__ return dask.get(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/local.py:563: in get_sync return get_async( /usr/lib/python3/dist-packages/dask/local.py:506: in get_async for key, res_info, failed in queue_get(queue).result(): /usr/lib/python3.9/concurrent/futures/_base.py:438: in result return self.__get_result() /usr/lib/python3.9/concurrent/futures/_base.py:390: in __get_result raise self._exception /usr/lib/python3/dist-packages/dask/local.py:548: in submit fut.set_result(fn(*args, **kwargs)) /usr/lib/python3/dist-packages/dask/local.py:237: in batch_execute_tasks return [execute_task(*a) for a in it] /usr/lib/python3/dist-packages/dask/local.py:237: in <listcomp> return [execute_task(*a) for a in it] /usr/lib/python3/dist-packages/dask/local.py:228: in execute_task result = pack_exception(e, dumps) /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/optimization.py:969: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) /usr/lib/python3/dist-packages/dask/core.py:151: in get result = _execute_task(task, cache) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in <genexpr> return func(*(_execute_task(a, cache) for a in args))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ arg = (<built-in function mul>, (<built-in function add>, '__dask_blockwise__2', '__dask_blockwise__3'), '__dask_blockwise__1') cache = {'__dask_blockwise__0': 5, '__dask_blockwise__1': 1.0, '__dask_blockwise__2': 0, '__dask_blockwise__3': array([[-2, -2.....,
[ 5, 5, 5, ..., 5, 5, 5], [ 6, 6, 6, ..., 6, 6, 6], [ 7, 7, 7, ..., 7, 7, 7]])} dsk = None def _execute_task(arg, cache, dsk=None): """Do the actual work of collecting data and executing a function Examples -------- >>> cache = {'x': 1, 'y': 2} Compute tasks against a cache>>> _execute_task((add, 'x', 1), cache) # Compute task in naive manner
2>>> _execute_task((add, (inc, 'x'), 1), cache) # Support nested computation
3 Also grab data from cache >>> _execute_task('x', cache) 1 Support nested lists >>> list(_execute_task(['x', 'y'], cache)) [1, 2]>>> list(map(list, _execute_task([['x', 'y'], ['y', 'x']], cache)))
[[1, 2], [2, 1]] >>> _execute_task('foo', cache) # Passes through on non-keys 'foo' """ if isinstance(arg, list): return [_execute_task(a, cache) for a in arg] elif istask(arg): func, args = arg[0], arg[1:]# Note: Don't assign the subtask results to a variable. numpy detects
# temporaries by their reference count and can execute certain # operations in-place.
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 21.0 MiB for an array with shape (2030, 1354) and data type float64return func(*(_execute_task(a, cache) for a in args))
/usr/lib/python3/dist-packages/dask/core.py:121: MemoryError_ TestModisL2.test_load_250m_cloud_mask_dataset[modis_l2_nasa_mod35_file-False] _
self = <satpy.tests.reader_tests.test_modis_l2.TestModisL2 object at 0xb4cc8a00> input_files = ['/tmp/pytest-of-debci/pytest-0/modis_l20/MOD35_L2.A2021324.1132.061.2021324113236.hdf']
exp_area = False @pytest.mark.parametrize( ('input_files', 'exp_area'), [ [lazy_fixture('modis_l2_nasa_mod35_file'), False], [lazy_fixture('modis_l2_nasa_mod35_mod03_files'), True], ] ) def test_load_250m_cloud_mask_dataset(self, input_files, exp_area): """Test loading 250m cloud mask.""" scene = Scene(reader='modis_l2', filenames=input_files) dataset_name = 'cloud_mask'
scene.load([dataset_name], resolution=250)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_modis_l2.py:134: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/scene.py:1213: in load
self._read_datasets_from_storage(**kwargs)/usr/lib/python3/dist-packages/satpy/scene.py:1233: in _read_datasets_from_storage
return self._read_dataset_nodes_from_storage(nodes, **kwargs)/usr/lib/python3/dist-packages/satpy/scene.py:1239: in _read_dataset_nodes_from_storage loaded_datasets = self._load_datasets_by_readers(reader_datasets, **kwargs) /usr/lib/python3/dist-packages/satpy/scene.py:1264: in _load_datasets_by_readers
new_datasets = reader_instance.load(ds_ids, **kwargs) /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:687: in _load_dataset
projectable = fh.get_dataset(dsid, ds_info) /usr/lib/python3/dist-packages/satpy/readers/modis_l2.py:139: in get_datasetdataset = self._extract_and_mask_category_dataset(dataset_id, dataset_info, dataset_name_in_file) /usr/lib/python3/dist-packages/satpy/readers/modis_l2.py:159: in _extract_and_mask_category_dataset
dataset = _extract_byte_mask(dataset,/usr/lib/python3/dist-packages/satpy/readers/modis_l2.py:204: in _extract_byte_mask
dataset_a = np.uint16(dataset_a) /usr/lib/python3/dist-packages/xarray/core/common.py:141: in __array__ return np.asarray(self.values, dtype=dtype) /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in <genexpr> return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/optimization.py:969: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) /usr/lib/python3/dist-packages/dask/core.py:151: in get result = _execute_task(task, cache) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/utils.py:35: in apply return func(*args, **kwargs)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
x = array([[[0, 0, 0, ..., 0, 0, 0], [0, 0, 0, ..., 0, 0, 0], [0, 0, 0, ..., 0, 0, 0], ..., ... ..., [0, 0, 0, ..., 0, 0, 0], [0, 0, 0, ..., 0, 0, 0], [0, 0, 0, ..., 0, 0, 0]]], dtype=int8) astype_dtype = dtype('uint8'), kwargs = {} def astype(x, astype_dtype=None, **kwargs):
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 15.7 MiB for an array with shape (6, 2030, 1354) and data type uint8return x.astype(astype_dtype, **kwargs)
/usr/lib/python3/dist-packages/dask/array/chunk.py:281: MemoryError------------------------------ Captured log call ------------------------------- WARNING satpy.readers.yaml_reader:yaml_reader.py:771 Required file type 'hdf_eos_geo' not found or loaded for 'latitude' WARNING satpy.readers.yaml_reader:yaml_reader.py:771 Required file type 'hdf_eos_geo' not found or loaded for 'longitude' ________________________ TestH5NWCSAF.test_get_dataset _________________________
self = <satpy.tests.reader_tests.test_nwcsaf_msg.TestH5NWCSAF testMethod=test_get_dataset>
def test_get_dataset(self): """Retrieve datasets from a NWCSAF msgv2013 hdf5 file.""" from satpy.readers.nwcsaf_msg2013_hdf5 import Hdf5NWCSAF from satpy.tests.utils import make_dataid filename_info = {} filetype_info = {} dsid = make_dataid(name="ct") test = Hdf5NWCSAF(self.filename_ct, filename_info, filetype_info) ds = test.get_dataset(dsid, {"file_key": "CT"}) self.assertEqual(ds.shape, (1856, 3712)) self.assertEqual(ds.dtype, np.uint8)
np.testing.assert_allclose(ds.data[1000:1010, 1000:1010].compute(), CTYPE_TEST_FRAME)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_nwcsaf_msg.py:521: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/dask/base.py:288: in compute
(result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in <genexpr> return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/optimization.py:969: in __call__ return core.get(self.dsk, self.outkey, dict(zip(self.inkeys, args))) /usr/lib/python3/dist-packages/dask/core.py:151: in get result = _execute_task(task, cache) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in <genexpr> return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:115: in _execute_task return [_execute_task(a, cache) for a in arg] /usr/lib/python3/dist-packages/dask/core.py:115: in <listcomp> return [_execute_task(a, cache) for a in arg] /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args)) /usr/lib/python3/dist-packages/dask/core.py:121: in <genexpr> return func(*(_execute_task(a, cache) for a in args))_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ arg = (<built-in function mul>, '__dask_blockwise__1', '__dask_blockwise__2') cache = {'__dask_blockwise__0': 0.0, '__dask_blockwise__1': array([[ 91, 125, 81, ..., 244, 74, 89],
[ 28, 226, 131,..., 132, 60, ..., 106, 126, 5],[100, 157, 165, ..., 169, 196, 199]], dtype=uint8), '__dask_blockwise__2': 1.0}
dsk = None def _execute_task(arg, cache, dsk=None): """Do the actual work of collecting data and executing a function Examples -------- >>> cache = {'x': 1, 'y': 2} Compute tasks against a cache>>> _execute_task((add, 'x', 1), cache) # Compute task in naive manner
2>>> _execute_task((add, (inc, 'x'), 1), cache) # Support nested computation
3 Also grab data from cache >>> _execute_task('x', cache) 1 Support nested lists >>> list(_execute_task(['x', 'y'], cache)) [1, 2]>>> list(map(list, _execute_task([['x', 'y'], ['y', 'x']], cache)))
[[1, 2], [2, 1]] >>> _execute_task('foo', cache) # Passes through on non-keys 'foo' """ if isinstance(arg, list): return [_execute_task(a, cache) for a in arg] elif istask(arg): func, args = arg[0], arg[1:]# Note: Don't assign the subtask results to a variable. numpy detects
# temporaries by their reference count and can execute certain # operations in-place.
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 52.6 MiB for an array with shape (1856, 3712) and data type float64return func(*(_execute_task(a, cache) for a in args))
/usr/lib/python3/dist-packages/dask/core.py:121: MemoryError__________________ TestSMOSL2WINDReader.test_load_wind_speed ___________________
self = <satpy.tests.reader_tests.test_smos_l2_wind.TestSMOSL2WINDReader testMethod=test_load_wind_speed>
def test_load_wind_speed(self): """Load wind_speed dataset.""" from satpy.readers import load_reader r = load_reader(self.reader_configs)with mock.patch('satpy.readers.smos_l2_wind.netCDF4.Variable', xr.DataArray):
loadables = r.select_files_from_pathnames([ 'SM_OPER_MIR_SCNFSW_20200420T021649_20200420T035013_110_001_7.nc', ]) r.create_filehandlers(loadables)
ds = r.load(['wind_speed'])
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_smos_l2_wind.py:116: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load
ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:687: in _load_dataset
projectable = fh.get_dataset(dsid, ds_info)/usr/lib/python3/dist-packages/satpy/readers/smos_l2_wind.py:140: in get_dataset
data = self._rename_coords(data)/usr/lib/python3/dist-packages/satpy/readers/smos_l2_wind.py:112: in _rename_coords
data = self._adjust_lon_coord(data)/usr/lib/python3/dist-packages/satpy/readers/smos_l2_wind.py:106: in _adjust_lon_coord
return data.where(data < 180., data - 360.) /usr/lib/python3/dist-packages/xarray/core/common.py:1286: in where return ops.where_method(self, cond, other) /usr/lib/python3/dist-packages/xarray/core/ops.py:176: in where_method return apply_ufunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:1174: in apply_ufunc
return apply_dataarray_vfunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:293: in apply_dataarray_vfunc
result_var = func(*data_vars)/usr/lib/python3/dist-packages/xarray/core/computation.py:742: in apply_variable_ufunc
result_data = func(*input_data)/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:290: in where_method
return where(cond, data, other) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:284: in where return _where(condition, *as_shared_dtype([x, y])) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:56: in f return wrapped(*args, **kwargs)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
args = (array([[ True, True, True, ..., True, True, True], [ True, True, True, ..., True, True, True], ...60.], [-360., -360., -360., ..., -360., -360., -360.], [-360., -360., -360., ..., -360., -360., -360.]])) kwargs = {} relevant_args = (array([[ True, True, True, ..., True, True, True], [ True, True, True, ..., True, True, True], ...60.], [-360., -360., -360., ..., -360., -360., -360.], [-360., -360., -360., ..., -360., -360., -360.]]))
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 7.92 MiB for an array with shape (721, 1440) and data type float64???
<__array_function__ internals>:5: MemoryError_____________________ TestTROPOMIL2Reader.test_load_bounds _____________________
self = <satpy.tests.reader_tests.test_tropomi_l2.TestTROPOMIL2Reader testMethod=test_load_bounds>
def test_load_bounds(self): """Load bounds dataset.""" from satpy.readers import load_reader r = load_reader(self.reader_configs)with mock.patch('satpy.readers.tropomi_l2.netCDF4.Variable', xr.DataArray):
loadables = r.select_files_from_pathnames([ 'S5P_OFFL_L2__NO2____20180709T170334_20180709T184504_03821_01_010002_20180715T184729.nc', ]) r.create_filehandlers(loadables) keys = ['latitude_bounds', 'longitude_bounds']
ds = r.load(keys)
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_tropomi_l2.py:173: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load
ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:687: in _load_dataset
projectable = fh.get_dataset(dsid, ds_info)/usr/lib/python3/dist-packages/satpy/readers/tropomi_l2.py:229: in get_dataset
data = data.where(good_mask, new_fill) /usr/lib/python3/dist-packages/xarray/core/common.py:1286: in where return ops.where_method(self, cond, other) /usr/lib/python3/dist-packages/xarray/core/ops.py:176: in where_method return apply_ufunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:1174: in apply_ufunc
return apply_dataarray_vfunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:293: in apply_dataarray_vfunc
result_var = func(*data_vars)/usr/lib/python3/dist-packages/xarray/core/computation.py:742: in apply_variable_ufunc
result_data = func(*input_data)/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:290: in where_method
return where(cond, data, other) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:284: in where return _where(condition, *as_shared_dtype([x, y]))/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:208: in as_shared_dtype
return [x.astype(out_type, copy=False) for x in arrays]_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.0 = <list_iterator object at 0xe94598>
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 44.6 MiB for an array with shape (3246, 450, 4) and data type float64return [x.astype(out_type, copy=False) for x in arrays]
/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:208: MemoryError ______________________ TestTROPOMIL2Reader.test_load_no2 _______________________
self = <satpy.tests.reader_tests.test_tropomi_l2.TestTROPOMIL2Reader testMethod=test_load_no2>
def test_load_no2(self): """Load NO2 dataset.""" from satpy.readers import load_reader r = load_reader(self.reader_configs)with mock.patch('satpy.readers.tropomi_l2.netCDF4.Variable', xr.DataArray):
loadables = r.select_files_from_pathnames([ 'S5P_OFFL_L2__NO2____20180709T170334_20180709T184504_03821_01_010002_20180715T184729.nc', ]) r.create_filehandlers(loadables)
ds = r.load(['nitrogen_dioxide_total_column'])
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_tropomi_l2.py:135: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load
ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:687: in _load_dataset
projectable = fh.get_dataset(dsid, ds_info)/usr/lib/python3/dist-packages/satpy/readers/tropomi_l2.py:229: in get_dataset
data = data.where(good_mask, new_fill) /usr/lib/python3/dist-packages/xarray/core/common.py:1286: in where return ops.where_method(self, cond, other) /usr/lib/python3/dist-packages/xarray/core/ops.py:176: in where_method return apply_ufunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:1174: in apply_ufunc
return apply_dataarray_vfunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:293: in apply_dataarray_vfunc
result_var = func(*data_vars)/usr/lib/python3/dist-packages/xarray/core/computation.py:742: in apply_variable_ufunc
result_data = func(*input_data)/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:290: in where_method
return where(cond, data, other) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:284: in where return _where(condition, *as_shared_dtype([x, y]))/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:208: in as_shared_dtype
return [x.astype(out_type, copy=False) for x in arrays]_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
.0 = <list_iterator object at 0xb46b2238>
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 11.1 MiB for an array with shape (3246, 450) and data type float64return [x.astype(out_type, copy=False) for x in arrays]
/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:208: MemoryError ______________________ TestTROPOMIL2Reader.test_load_so2 _______________________
self = <satpy.tests.reader_tests.test_tropomi_l2.TestTROPOMIL2Reader testMethod=test_load_so2>
def test_load_so2(self): """Load SO2 dataset.""" from satpy.readers import load_reader r = load_reader(self.reader_configs)with mock.patch('satpy.readers.tropomi_l2.netCDF4.Variable', xr.DataArray):
loadables = r.select_files_from_pathnames([ 'S5P_OFFL_L2__SO2____20181224T055107_20181224T073237_06198_01_010105_20181230T150634.nc', ]) r.create_filehandlers(loadables)
ds = r.load(['sulfurdioxide_total_vertical_column'])
/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_tropomi_l2.py:154: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:943: in load
ds = self._load_dataset_with_area(dsid, coords, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:839: in _load_dataset_with_area
ds = self._load_dataset_data(file_handlers, dsid, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:711: in _load_dataset_data
proj = self._load_dataset(dsid, ds_info, file_handlers, **kwargs)/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:687: in _load_dataset
projectable = fh.get_dataset(dsid, ds_info)/usr/lib/python3/dist-packages/satpy/readers/tropomi_l2.py:229: in get_dataset
data = data.where(good_mask, new_fill) /usr/lib/python3/dist-packages/xarray/core/common.py:1286: in where return ops.where_method(self, cond, other) /usr/lib/python3/dist-packages/xarray/core/ops.py:176: in where_method return apply_ufunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:1174: in apply_ufunc
return apply_dataarray_vfunc(/usr/lib/python3/dist-packages/xarray/core/computation.py:293: in apply_dataarray_vfunc
result_var = func(*data_vars)/usr/lib/python3/dist-packages/xarray/core/computation.py:742: in apply_variable_ufunc
result_data = func(*input_data)/usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:290: in where_method
return where(cond, data, other) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:284: in where return _where(condition, *as_shared_dtype([x, y])) /usr/lib/python3/dist-packages/xarray/core/duck_array_ops.py:56: in f return wrapped(*args, **kwargs)_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
args = (array([[ True, True, True, ..., True, True, True], [ True, True, True, ..., True, True, True], ...457e+04], [1.8458e+04, 1.8459e+04, 1.8460e+04, ..., 1.8905e+04, 1.8906e+04, 1.8907e+04]]), array(-999.)) kwargs = {} relevant_args = (array([[ True, True, True, ..., True, True, True], [ True, True, True, ..., True, True, True], ...457e+04], [1.8458e+04, 1.8459e+04, 1.8460e+04, ..., 1.8905e+04, 1.8906e+04, 1.8907e+04]]), array(-999.))
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 11.1 MiB for an array with shape (3246, 450) and data type float64???
<__array_function__ internals>:5: MemoryError_________________________ TestCompact.test_distributed _________________________
self = <satpy.tests.reader_tests.test_viirs_compact.TestCompact testMethod=test_distributed>
def setUp(self): """Create a fake file from scratch.""" fake_dnb = { "All_Data": { "ModeGran": {"value": 0}, "ModeScan": { "value": np.array( [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 249, ], dtype=np.uint8, ) }, "NumberOfScans": {"value": np.array([47])}, "VIIRS-DNB-GEO_All": { "AlignmentCoefficient": { "value": np.array( [ 2.11257413e-02, 2.11152732e-02, 2.11079046e-02, 2.10680142e-02, 1.80840008e-02, 1.80402063e-02, 1.79968309e-02, 1.79477539e-02, 2.20463774e-03, 2.17431062e-03, 2.14360282e-03, 2.11503846e-03, 2.08630669e-03, 2.05924874e-03, 2.03177333e-03, 2.00573727e-03, 1.98072987e-03, 1.95503305e-03, 1.93077011e-03, 1.90702057e-03, 1.88353716e-03, 1.86104013e-03, 1.83863181e-03, 1.81696517e-03, 1.79550308e-03, 1.77481642e-03, 1.75439729e-03, 1.73398503e-03, 1.71459839e-03, 1.69516564e-03, 1.67622324e-03, 1.65758410e-03, 1.63990213e-03, 1.62128301e-03, 1.60375470e-03, 1.58667017e-03, 1.61543000e-03, 1.59775047e-03, 1.50719041e-03, 1.48937735e-03, 1.47257745e-03, 1.50070526e-03, 1.48288533e-03, 9.29064234e-04, 9.12246935e-04, 8.95748264e-04, 8.71886965e-04, 8.55044520e-04, 8.38686305e-04, 8.18263041e-04, 8.01501446e-04, 7.85346841e-04, 1.15984806e-03, 1.14326552e-03, 1.12648588e-03, 1.11018715e-03, 1.09399087e-03, 1.19698711e-03, 1.18051842e-03, 1.16404379e-03, 1.14832399e-03, 9.92591376e-04, 9.75896895e-04, 9.59663419e-04, 9.43415158e-04, 9.27662419e-04, 8.92253709e-04, 8.75947590e-04, 8.60177504e-04, 8.44484195e-04, 8.35279003e-04, 8.19236680e-04, 8.03303672e-04, 7.87482015e-04, 7.60449213e-04, 7.44239136e-04, 7.28625571e-04, 7.12990935e-04, 6.89090986e-04, 6.73000410e-04, 6.57248020e-04, 6.41623745e-04, 6.20219158e-04, 6.04308851e-04, 5.88596100e-04, 5.73108089e-04, 3.65344196e-04, 3.49639275e-04, 3.34273063e-04, 4.81286290e-04, 4.65485587e-04, 4.49862011e-04, 4.34543617e-04, 4.19324206e-04, 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dtype=np.float32, ) }, "ExpansionCoefficient": { "value": np.array( [ 1.17600127e-03, 1.17271533e-03, 1.17000856e-03, 1.16674276e-03, 2.11251900e-03, 2.10516527e-03, 2.09726905e-03, 2.08941335e-03, 1.63907595e-02, 1.58577170e-02, 1.53679820e-02, 1.49007449e-02, 1.44708352e-02, 1.40612368e-02, 1.36818690e-02, 1.33193973e-02, 1.29744308e-02, 1.26568424e-02, 1.23488475e-02, 1.20567940e-02, 1.17803067e-02, 1.15150018e-02, 1.12629030e-02, 1.10203745e-02, 1.07905651e-02, 1.05690639e-02, 1.03563424e-02, 1.01526314e-02, 9.95650515e-03, 9.76785459e-03, 9.58597753e-03, 9.41115711e-03, 9.23914276e-03, 9.07964632e-03, 8.92116502e-03, 8.76654685e-03, 9.04925726e-03, 8.88936501e-03, 9.14804544e-03, 8.98920093e-03, 8.83030891e-03, 9.06952657e-03, 8.90891161e-03, 1.36343827e-02, 1.32706892e-02, 1.29242949e-02, 1.36271119e-02, 1.32572902e-02, 1.29025253e-02, 1.35165229e-02, 1.31412474e-02, 1.27808526e-02, 8.91761761e-03, 8.74674786e-03, 8.58181808e-03, 8.42147414e-03, 8.26664641e-03, 7.81304855e-03, 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], [b"off_USNO-PolarWander-UT1-ANC_Ser7_USNO_000f_20191025_201910250000Z_20191025000109Z_ee20191101120000Z_np" # noqa
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], [b"CmnGeo-SAA-AC_j01_20151008180000Z_20170807130000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"TLE-AUX_j01_20191024053224Z_20191024000000Z_ee00000000000000Z_-_nobc_ops_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-DNB-PARAM-LUT_j01_20180507121508Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-IMG-PARAM-LUT_j01_20180430182354Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-MOD-PARAM-LUT_j01_20180430182652Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-QA-LUT_j01_20180109121411Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
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"N_Creation_Time": np.array( [[b"062136.412867Z"]], dtype="|S15" ),"N_Day_Night_Flag": np.array([[b"Night"]], dtype="|S6"),
"N_Ending_Time_IET": np.array( [[1950675204849492]], dtype=np.uint64 ), "N_Granule_ID": np.array( [[b"J01002526558865"]], dtype="|S16" ),"N_Granule_Status": np.array([[b"N/A"]], dtype="|S4"), "N_Granule_Version": np.array([[b"A1"]], dtype="|S3"), "N_IDPS_Mode": np.array([[b"N/A"]], dtype="|S4"),
"N_Input_Prod": np.array( [ [b"SPACECRAFT-DIARY-RDR:J01002526558800:A1"], [b"SPACECRAFT-DIARY-RDR:J01002526559000:A1"], [b"VIIRS-SCIENCE-RDR:J01002526558865:A1"], ], dtype="|S40", ), "N_JPSS_Document_Ref": np.array( [ [ b"474-00448-02-06_JPSS-DD-Vol-II-Part-6_0200H.pdf" ], [ b"474-00448-02-06_JPSS-VIIRS-SDR-DD-Part-6_0200H_VIIRS-DNB-GEO-PP.xml" ], [ b"474-00448-03-06_JPSS-OAD-Vol-III-Part-6-VIIRS-RDR-SDR_-1.pdf" ], ], dtype="|S68", ),"N_LEOA_Flag": np.array([[b"On"]], dtype="|S3"),
"N_Nadir_Latitude_Max": np.array( [[45.3722]], dtype=np.float32 ), "N_Nadir_Latitude_Min": np.array( [[40.6172]], dtype=np.float32 ), "N_Nadir_Longitude_Max": np.array( [[-62.80047]], dtype=np.float32 ), "N_Nadir_Longitude_Min": np.array( [[-64.51342]], dtype=np.float32 ),"N_Number_Of_Scans": np.array([[47]], dtype=np.int32),
"N_Primary_Label": np.array( [[b"Non-Primary"]], dtype="|S12" ), "N_Quality_Summary_Names": np.array( [ [b"Automatic Quality Flag"], [b"Percent Missing Data"], [b"Percent Out of Bounds"], ], dtype="|S23", ), "N_Quality_Summary_Values": np.array( [[1], [61], [0]], dtype=np.int32 ), "N_Reference_ID": np.array( [[b"VIIRS-DNB-GEO:J01002526558865:A1"]], dtype="|S33" ), "N_Software_Version": np.array( [[b"CSPP_SDR_3_1_3"]], dtype="|S15" ), "N_Spacecraft_Maneuver": np.array( [[b"Normal Operations"]], dtype="|S18" ), "North_Bounding_Coordinate": np.array( [[46.8018]], dtype=np.float32 ), "South_Bounding_Coordinate": np.array( [[36.53401]], dtype=np.float32 ), "West_Bounding_Coordinate": np.array( [[-82.66234]], dtype=np.float32 ), } }, "attrs": {"Instrument_Short_Name": np.array([[b"VIIRS"]], dtype="|S6"), "N_Anc_Type_Tasked": np.array([[b"Official"]], dtype="|S9"),
"N_Collection_Short_Name": np.array( [[b"VIIRS-DNB-GEO"]], dtype="|S14" ),"N_Dataset_Type_Tag": np.array([[b"GEO"]], dtype="|S4"), "N_Processing_Domain": np.array([[b"ops"]], dtype="|S4"),
"Operational_Mode": np.array([[b"J01 Normal Operations, VIIRS Operational"]],
dtype="|S41", ), }, }, "VIIRS-DNB-SDR": { "VIIRS-DNB-SDR_Aggr": { "attrs": { "AggregateBeginningDate": np.array( [[b"20191025"]], dtype="|S9" ), "AggregateBeginningGranuleID": np.array( [[b"J01002526558865"]], dtype="|S16" ), "AggregateBeginningOrbitNumber": np.array( [[10015]], dtype=np.uint64 ), "AggregateBeginningTime": np.array( [[b"061125.120971Z"]], dtype="|S15" ), "AggregateEndingDate": np.array( [[b"20191025"]], dtype="|S9" ), "AggregateEndingGranuleID": np.array( [[b"J01002526558865"]], dtype="|S16" ), "AggregateEndingOrbitNumber": np.array( [[10015]], dtype=np.uint64 ), "AggregateEndingTime": np.array( [[b"061247.849492Z"]], dtype="|S15" ),"AggregateNumberGranules": np.array([[1]], dtype=np.uint64),
} }, "VIIRS-DNB-SDR_Gran_0": { "attrs": { "Ascending/Descending_Indicator": np.array( [[1]], dtype=np.uint8 ), "Band_ID": np.array([[b"N/A"]], dtype="|S4"),"Beginning_Date": np.array([[b"20191025"]], dtype="|S9"),
"Beginning_Time": np.array( [[b"061125.120971Z"]], dtype="|S15" ), "East_Bounding_Coordinate": np.array( [[-45.09281]], dtype=np.float32 ),"Ending_Date": np.array([[b"20191025"]], dtype="|S9"),
"Ending_Time": np.array( [[b"061247.849492Z"]], dtype="|S15" ), "G-Ring_Latitude": np.array( [ [41.84157], [44.31069], [46.78591], [45.41409], [41.07675], [38.81512], [36.53402], [40.55788], ], dtype=np.float32, ), "G-Ring_Longitude": np.array( [ [-82.65787], [-82.55148], [-82.47269], [-62.80042], [-45.09281], [-46.58528], [-47.95936], [-64.54196], ], dtype=np.float32, ), "N_Algorithm_Version": np.array( [[b"1.O.000.015"]], dtype="|S12" ), "N_Anc_Filename": np.array( [ [b"off_Planet-Eph-ANC_Static_JPL_000f_20151008_200001010000Z_20000101000000Z_ee00000000000000Z_np" # noqa
], [b"off_USNO-PolarWander-UT1-ANC_Ser7_USNO_000f_20191025_201910250000Z_20191025000109Z_ee20191101120000Z_np" # noqa
], ], dtype="|S104", ), "N_Aux_Filename": np.array( [ [b"CMNGEO-PARAM-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-DNB-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I1-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I2-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I3-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I4-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I5-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M1-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M10-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M11-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M12-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M13-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M14-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M15-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M16-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M2-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M3-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M4-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M5-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M6-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M7-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M8-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M9-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-RSBAUTOCAL-HISTORY-AUX_j01_20191024021527Z_20191024000000Z_ee00000000000000Z_-_nobc_ops_all-_ops" # noqa
], [b"VIIRS-RSBAUTOCAL-VOLT-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-EDD154640-109C-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-BB-TEMP-COEFFS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-CAL-AUTOMATE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Pred-SideA-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-COEFF-A-LUT_j01_20180109114311Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-COEFF-B-LUT_j01_20180109101739Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-004-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DELTA-C-LUT_j01_20180109000000Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DG-ANOMALY-DN-LIMITS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SideA-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-DN0-LUT_j01_20190930000000Z_20190928000000Z_ee00000000000000Z_PS-1-O-CCR-4262-026-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-FRAME-TO-ZONE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Op21-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-GAIN-RATIOS-LUT_j01_20190930000000Z_20190928000000Z_ee00000000000000Z_PS-1-O-CCR-4262-025-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-LGS-GAINS-LUT_j01_20180413122703Z_20180412000000Z_ee00000000000000Z_PS-1-O-CCR-3918-005-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-RVF-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Op21-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-STRAY-LIGHT-CORRECTION-LUT_j01_20190930160523Z_20191001000000Z_ee00000000000000Z_PS-1-O-CCR-4322-024-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-EBBT-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-EMISSIVE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-F-PREDICTED-LUT_j01_20180413123333Z_20180412000000Z_ee00000000000000Z_PS-1-O-CCR-3918-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GAIN-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-HAM-ER-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBC-ER-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBC-RR-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBS-TO-PIXELS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SameAsSNPP-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-QA-LUT_j01_20180109121411Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-RADIOMETRIC-PARAM-V3-LUT_j01_20161117000000Z_20180111000000Z_ee00000000000000Z_PS-1-O-CCR-17-3436-v003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-REFLECTIVE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SameAsSNPP-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-RELATIVE-SPECTRAL-RESPONSE-LUT_j01_20161031000000Z_20180111000000Z_ee00000000000000Z_PS-1-O-CCR-17-3436-v003-FusedM9-LE-PE_all-_all_all-_ops" # noqa
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], [b"VIIRS-SDR-SOLAR-IRAD-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Thuillier2002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-TELE-COEFFS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SideA-LE-PE_all-_all_all-_ops" # noqa
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"N_Creation_Time": np.array( [[b"062411.116253Z"]], dtype="|S15" ),"N_Day_Night_Flag": np.array([[b"Night"]], dtype="|S6"),
"N_Ending_Time_IET": np.array( [[1950675204849492]], dtype=np.uint64 ),"N_Graceful_Degradation": np.array([[b"No"]], dtype="|S3"),
"N_Granule_ID": np.array( [[b"J01002526558865"]], dtype="|S16" ),"N_Granule_Status": np.array([[b"N/A"]], dtype="|S4"), "N_Granule_Version": np.array([[b"A1"]], dtype="|S3"), "N_IDPS_Mode": np.array([[b"N/A"]], dtype="|S4"),
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"N_Nadir_Latitude_Max": np.array( [[45.3722]], dtype=np.float32 ), "N_Nadir_Latitude_Min": np.array( [[40.6172]], dtype=np.float32 ), "N_Nadir_Longitude_Max": np.array( [[-62.80047]], dtype=np.float32 ), "N_Nadir_Longitude_Min": np.array( [[-64.51342]], dtype=np.float32 ),"N_Number_Of_Scans": np.array([[47]], dtype=np.int32),
"N_Percent_Erroneous_Data": np.array( [[0.0]], dtype=np.float32 ), "N_Percent_Missing_Data": np.array( [[51.05127]], dtype=np.float32 ), "N_Percent_Not-Applicable_Data": np.array( [[0.0]], dtype=np.float32 ), "N_Primary_Label": np.array( [[b"Non-Primary"]], dtype="|S12" ), "N_Quality_Summary_Names": np.array( [ [b"Scan Quality Exclusion"], [b"Summary VIIRS SDR Quality"], ], dtype="|S26", ), "N_Quality_Summary_Values": np.array( [[24], [49]], dtype=np.int32 ),"N_RSB_Index": np.array([[17]], dtype=np.int32),
"N_Reference_ID": np.array( [[b"VIIRS-DNB-SDR:J01002526558865:A1"]], dtype="|S33" ),"N_Satellite/Local_Azimuth_Angle_Max": np.array(
[[179.9995]], dtype=np.float32 ),"N_Satellite/Local_Azimuth_Angle_Min": np.array(
[[-179.9976]], dtype=np.float32 ), "N_Satellite/Local_Zenith_Angle_Max": np.array( [[69.83973]], dtype=np.float32 ), "N_Satellite/Local_Zenith_Angle_Min": np.array( [[0.00898314]], dtype=np.float32 ), "N_Software_Version": np.array( [[b"CSPP_SDR_3_1_3"]], dtype="|S15" ), "N_Solar_Azimuth_Angle_Max": np.array( [[73.93496]], dtype=np.float32 ), "N_Solar_Azimuth_Angle_Min": np.array( [[23.83542]], dtype=np.float32 ), "N_Solar_Zenith_Angle_Max": np.array( [[147.5895]], dtype=np.float32 ), "N_Solar_Zenith_Angle_Min": np.array( [[126.3929]], dtype=np.float32 ), "N_Spacecraft_Maneuver": np.array( [[b"Normal Operations"]], dtype="|S18" ), "North_Bounding_Coordinate": np.array( [[46.8018]], dtype=np.float32 ), "South_Bounding_Coordinate": np.array( [[36.53402]], dtype=np.float32 ), "West_Bounding_Coordinate": np.array( [[-82.65787]], dtype=np.float32 ), } }, "attrs": {"Instrument_Short_Name": np.array([[b"VIIRS"]], dtype="|S6"),
"N_Collection_Short_Name": np.array( [[b"VIIRS-DNB-SDR"]], dtype="|S14" ),"N_Dataset_Type_Tag": np.array([[b"SDR"]], dtype="|S4"),
"N_Instrument_Flight_SW_Version": np.array( [[20], [65534]], dtype=np.int32 ),"N_Processing_Domain": np.array([[b"ops"]], dtype="|S4"),
"Operational_Mode": np.array([[b"J01 Normal Operations, VIIRS Operational"]],
dtype="|S41", ), }, }, }, "attrs": { "CVIIRS_Version": np.array([[b"2.0.1"]], dtype="|S5"),"Compact_VIIRS_SDR_Version": np.array([[b"3.1"]], dtype="|S3"),
"Distributor": np.array([[b"cspp"]], dtype="|S5"), "Mission_Name": np.array([[b"JPSS-1"]], dtype="|S7"), "N_Dataset_Source": np.array([[b"all-"]], dtype="|S5"), "N_GEO_Ref": np.array( [ [ b"GDNBO_j01_d20191025_t0611251_e0612478_b10015_c20191025062405837630_cspp_dev.h5" ] ], dtype="|S78", ),"N_HDF_Creation_Date": np.array([[b"20191025"]], dtype="|S8"), "N_HDF_Creation_Time": np.array([[b"062502.927000Z"]], dtype="|S14"),
"Platform_Short_Name": np.array([[b"J01"]], dtype="|S4"), "Satellite_Id_Filename": np.array([[b"j01"]], dtype="|S3"), }, }/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_viirs_compact.py:1485: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ mtrand.pyx:1169: in numpy.random.mtrand.RandomState.rand
??? mtrand.pyx:423: in numpy.random.mtrand.RandomState.random_sample ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 23.8 MiB for an array with shape (768, 4064) and data type float64???
_common.pyx:270: MemoryError_________________________ TestCompact.test_get_dataset _________________________
self = <satpy.tests.reader_tests.test_viirs_compact.TestCompact testMethod=test_get_dataset>
def setUp(self): """Create a fake file from scratch.""" fake_dnb = { "All_Data": { "ModeGran": {"value": 0}, "ModeScan": { "value": np.array( [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 254, 249, ], dtype=np.uint8, ) }, "NumberOfScans": {"value": np.array([47])}, "VIIRS-DNB-GEO_All": { "AlignmentCoefficient": { "value": np.array( [ 2.11257413e-02, 2.11152732e-02, 2.11079046e-02, 2.10680142e-02, 1.80840008e-02, 1.80402063e-02, 1.79968309e-02, 1.79477539e-02, 2.20463774e-03, 2.17431062e-03, 2.14360282e-03, 2.11503846e-03, 2.08630669e-03, 2.05924874e-03, 2.03177333e-03, 2.00573727e-03, 1.98072987e-03, 1.95503305e-03, 1.93077011e-03, 1.90702057e-03, 1.88353716e-03, 1.86104013e-03, 1.83863181e-03, 1.81696517e-03, 1.79550308e-03, 1.77481642e-03, 1.75439729e-03, 1.73398503e-03, 1.71459839e-03, 1.69516564e-03, 1.67622324e-03, 1.65758410e-03, 1.63990213e-03, 1.62128301e-03, 1.60375470e-03, 1.58667017e-03, 1.61543000e-03, 1.59775047e-03, 1.50719041e-03, 1.48937735e-03, 1.47257745e-03, 1.50070526e-03, 1.48288533e-03, 9.29064234e-04, 9.12246935e-04, 8.95748264e-04, 8.71886965e-04, 8.55044520e-04, 8.38686305e-04, 8.18263041e-04, 8.01501446e-04, 7.85346841e-04, 1.15984806e-03, 1.14326552e-03, 1.12648588e-03, 1.11018715e-03, 1.09399087e-03, 1.19698711e-03, 1.18051842e-03, 1.16404379e-03, 1.14832399e-03, 9.92591376e-04, 9.75896895e-04, 9.59663419e-04, 9.43415158e-04, 9.27662419e-04, 8.92253709e-04, 8.75947590e-04, 8.60177504e-04, 8.44484195e-04, 8.35279003e-04, 8.19236680e-04, 8.03303672e-04, 7.87482015e-04, 7.60449213e-04, 7.44239136e-04, 7.28625571e-04, 7.12990935e-04, 6.89090986e-04, 6.73000410e-04, 6.57248020e-04, 6.41623745e-04, 6.20219158e-04, 6.04308851e-04, 5.88596100e-04, 5.73108089e-04, 3.65344196e-04, 3.49639275e-04, 3.34273063e-04, 4.81286290e-04, 4.65485587e-04, 4.49862011e-04, 4.34543617e-04, 4.19324206e-04, 2.60536268e-04, 2.45052564e-04, 2.29740850e-04, 2.34466774e-04, 2.18822126e-04, 2.03370175e-04, 1.88058810e-04, 1.60192372e-04, 1.44485937e-04, 1.28920830e-04, 3.45615146e-04, 3.30171984e-04, 3.14682693e-04, 2.99300562e-04, 2.83925037e-04, 2.68518896e-04, 2.53254839e-04, 2.37950648e-04, 2.22716670e-04, 2.07562072e-04, 1.92296386e-04, 1.77147449e-04, 1.61994336e-04, 1.46895778e-04, 1.31844325e-04, 1.16730320e-04, 1.01757469e-04, 8.67861963e-05, 7.18669180e-05, 5.70719567e-05, 4.24701866e-05, 2.84846719e-05, 1.70599415e-05, -1.47213286e-05, -2.33691408e-05, -3.68025649e-05, -5.12388433e-05, -6.59972284e-05, -8.08926561e-05, -9.58433884e-05, -1.10882705e-04, -1.25976600e-04, -1.41044657e-04, -1.56166439e-04, -1.71307023e-04, -1.86516074e-04, -2.01731804e-04, -2.16980450e-04, -2.32271064e-04, -2.47527263e-04, -2.62940506e-04, -2.78283434e-04, -2.93711084e-04, -3.09180934e-04, -3.24661058e-04, -3.40237195e-04, -1.27807143e-04, -1.43646437e-04, -1.59638614e-04, -1.87593061e-04, -2.03169184e-04, -2.18941437e-04, -2.34920750e-04, -2.30605408e-04, -2.46262236e-04, -2.62226094e-04, -4.19838558e-04, -4.35510388e-04, -4.51152271e-04, -4.67120990e-04, -4.83241311e-04, -3.37647041e-04, -3.53568990e-04, -3.69836489e-04, -5.76354389e-04, -5.92070050e-04, -6.08178903e-04, -6.24440494e-04, -6.45648804e-04, -6.61431870e-04, -6.77491073e-04, -6.93967624e-04, -7.17683870e-04, -7.33471534e-04, -7.49999890e-04, -7.66390527e-04, -7.93468382e-04, -8.09502264e-04, -8.25728697e-04, -8.42282083e-04, -8.51265620e-04, -8.67322611e-04, -8.83649045e-04, -9.00280487e-04, -9.35055199e-04, -9.51097580e-04, -9.67527216e-04, -9.84144746e-04, -1.00128003e-03, -1.15522649e-03, -1.17168750e-03, -1.18826574e-03, -1.20496599e-03, -1.10272120e-03, -1.11865194e-03, -1.13539130e-03, -1.15241797e-03, -1.16964686e-03, -7.97322951e-04, -8.14269355e-04, -8.31696263e-04, -8.51555436e-04, -8.68656265e-04, -8.86220601e-04, -9.09406052e-04, -9.26509325e-04, -9.44124535e-04, -1.49479776e-03, 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dtype=np.float32, ) }, "ExpansionCoefficient": { "value": np.array( [ 1.17600127e-03, 1.17271533e-03, 1.17000856e-03, 1.16674276e-03, 2.11251900e-03, 2.10516527e-03, 2.09726905e-03, 2.08941335e-03, 1.63907595e-02, 1.58577170e-02, 1.53679820e-02, 1.49007449e-02, 1.44708352e-02, 1.40612368e-02, 1.36818690e-02, 1.33193973e-02, 1.29744308e-02, 1.26568424e-02, 1.23488475e-02, 1.20567940e-02, 1.17803067e-02, 1.15150018e-02, 1.12629030e-02, 1.10203745e-02, 1.07905651e-02, 1.05690639e-02, 1.03563424e-02, 1.01526314e-02, 9.95650515e-03, 9.76785459e-03, 9.58597753e-03, 9.41115711e-03, 9.23914276e-03, 9.07964632e-03, 8.92116502e-03, 8.76654685e-03, 9.04925726e-03, 8.88936501e-03, 9.14804544e-03, 8.98920093e-03, 8.83030891e-03, 9.06952657e-03, 8.90891161e-03, 1.36343827e-02, 1.32706892e-02, 1.29242949e-02, 1.36271119e-02, 1.32572902e-02, 1.29025253e-02, 1.35165229e-02, 1.31412474e-02, 1.27808526e-02, 8.91761761e-03, 8.74674786e-03, 8.58181808e-03, 8.42147414e-03, 8.26664641e-03, 7.81304855e-03, 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], [b"off_USNO-PolarWander-UT1-ANC_Ser7_USNO_000f_20191025_201910250000Z_20191025000109Z_ee20191101120000Z_np" # noqa
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], [b"CmnGeo-SAA-AC_j01_20151008180000Z_20170807130000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"TLE-AUX_j01_20191024053224Z_20191024000000Z_ee00000000000000Z_-_nobc_ops_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-DNB-PARAM-LUT_j01_20180507121508Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-IMG-PARAM-LUT_j01_20180430182354Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GEO-MOD-PARAM-LUT_j01_20180430182652Z_20180315000000Z_ee00000000000000Z_PS-1-O-CCR-3963-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-QA-LUT_j01_20180109121411Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
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"N_Creation_Time": np.array( [[b"062136.412867Z"]], dtype="|S15" ),"N_Day_Night_Flag": np.array([[b"Night"]], dtype="|S6"),
"N_Ending_Time_IET": np.array( [[1950675204849492]], dtype=np.uint64 ), "N_Granule_ID": np.array( [[b"J01002526558865"]], dtype="|S16" ),"N_Granule_Status": np.array([[b"N/A"]], dtype="|S4"), "N_Granule_Version": np.array([[b"A1"]], dtype="|S3"), "N_IDPS_Mode": np.array([[b"N/A"]], dtype="|S4"),
"N_Input_Prod": np.array( [ [b"SPACECRAFT-DIARY-RDR:J01002526558800:A1"], [b"SPACECRAFT-DIARY-RDR:J01002526559000:A1"], [b"VIIRS-SCIENCE-RDR:J01002526558865:A1"], ], dtype="|S40", ), "N_JPSS_Document_Ref": np.array( [ [ b"474-00448-02-06_JPSS-DD-Vol-II-Part-6_0200H.pdf" ], [ b"474-00448-02-06_JPSS-VIIRS-SDR-DD-Part-6_0200H_VIIRS-DNB-GEO-PP.xml" ], [ b"474-00448-03-06_JPSS-OAD-Vol-III-Part-6-VIIRS-RDR-SDR_-1.pdf" ], ], dtype="|S68", ),"N_LEOA_Flag": np.array([[b"On"]], dtype="|S3"),
"N_Nadir_Latitude_Max": np.array( [[45.3722]], dtype=np.float32 ), "N_Nadir_Latitude_Min": np.array( [[40.6172]], dtype=np.float32 ), "N_Nadir_Longitude_Max": np.array( [[-62.80047]], dtype=np.float32 ), "N_Nadir_Longitude_Min": np.array( [[-64.51342]], dtype=np.float32 ),"N_Number_Of_Scans": np.array([[47]], dtype=np.int32),
"N_Primary_Label": np.array( [[b"Non-Primary"]], dtype="|S12" ), "N_Quality_Summary_Names": np.array( [ [b"Automatic Quality Flag"], [b"Percent Missing Data"], [b"Percent Out of Bounds"], ], dtype="|S23", ), "N_Quality_Summary_Values": np.array( [[1], [61], [0]], dtype=np.int32 ), "N_Reference_ID": np.array( [[b"VIIRS-DNB-GEO:J01002526558865:A1"]], dtype="|S33" ), "N_Software_Version": np.array( [[b"CSPP_SDR_3_1_3"]], dtype="|S15" ), "N_Spacecraft_Maneuver": np.array( [[b"Normal Operations"]], dtype="|S18" ), "North_Bounding_Coordinate": np.array( [[46.8018]], dtype=np.float32 ), "South_Bounding_Coordinate": np.array( [[36.53401]], dtype=np.float32 ), "West_Bounding_Coordinate": np.array( [[-82.66234]], dtype=np.float32 ), } }, "attrs": {"Instrument_Short_Name": np.array([[b"VIIRS"]], dtype="|S6"), "N_Anc_Type_Tasked": np.array([[b"Official"]], dtype="|S9"),
"N_Collection_Short_Name": np.array( [[b"VIIRS-DNB-GEO"]], dtype="|S14" ),"N_Dataset_Type_Tag": np.array([[b"GEO"]], dtype="|S4"), "N_Processing_Domain": np.array([[b"ops"]], dtype="|S4"),
"Operational_Mode": np.array([[b"J01 Normal Operations, VIIRS Operational"]],
dtype="|S41", ), }, }, "VIIRS-DNB-SDR": { "VIIRS-DNB-SDR_Aggr": { "attrs": { "AggregateBeginningDate": np.array( [[b"20191025"]], dtype="|S9" ), "AggregateBeginningGranuleID": np.array( [[b"J01002526558865"]], dtype="|S16" ), "AggregateBeginningOrbitNumber": np.array( [[10015]], dtype=np.uint64 ), "AggregateBeginningTime": np.array( [[b"061125.120971Z"]], dtype="|S15" ), "AggregateEndingDate": np.array( [[b"20191025"]], dtype="|S9" ), "AggregateEndingGranuleID": np.array( [[b"J01002526558865"]], dtype="|S16" ), "AggregateEndingOrbitNumber": np.array( [[10015]], dtype=np.uint64 ), "AggregateEndingTime": np.array( [[b"061247.849492Z"]], dtype="|S15" ),"AggregateNumberGranules": np.array([[1]], dtype=np.uint64),
} }, "VIIRS-DNB-SDR_Gran_0": { "attrs": { "Ascending/Descending_Indicator": np.array( [[1]], dtype=np.uint8 ), "Band_ID": np.array([[b"N/A"]], dtype="|S4"),"Beginning_Date": np.array([[b"20191025"]], dtype="|S9"),
"Beginning_Time": np.array( [[b"061125.120971Z"]], dtype="|S15" ), "East_Bounding_Coordinate": np.array( [[-45.09281]], dtype=np.float32 ),"Ending_Date": np.array([[b"20191025"]], dtype="|S9"),
"Ending_Time": np.array( [[b"061247.849492Z"]], dtype="|S15" ), "G-Ring_Latitude": np.array( [ [41.84157], [44.31069], [46.78591], [45.41409], [41.07675], [38.81512], [36.53402], [40.55788], ], dtype=np.float32, ), "G-Ring_Longitude": np.array( [ [-82.65787], [-82.55148], [-82.47269], [-62.80042], [-45.09281], [-46.58528], [-47.95936], [-64.54196], ], dtype=np.float32, ), "N_Algorithm_Version": np.array( [[b"1.O.000.015"]], dtype="|S12" ), "N_Anc_Filename": np.array( [ [b"off_Planet-Eph-ANC_Static_JPL_000f_20151008_200001010000Z_20000101000000Z_ee00000000000000Z_np" # noqa
], [b"off_USNO-PolarWander-UT1-ANC_Ser7_USNO_000f_20191025_201910250000Z_20191025000109Z_ee20191101120000Z_np" # noqa
], ], dtype="|S104", ), "N_Aux_Filename": np.array( [ [b"CMNGEO-PARAM-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-DNB-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I1-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I2-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I3-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I4-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-I5-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M1-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M10-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M11-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M12-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M13-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M14-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M15-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M16-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M2-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M3-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M4-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M5-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M6-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M7-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M8-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-M9-SDR-DQTT_j01_20151008180000Z_20020101010000Z_ee00000000000000Z_PS-1-O-NPP-1-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-RSBAUTOCAL-HISTORY-AUX_j01_20191024021527Z_20191024000000Z_ee00000000000000Z_-_nobc_ops_all-_ops" # noqa
], [b"VIIRS-RSBAUTOCAL-VOLT-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-EDD154640-109C-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-BB-TEMP-COEFFS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-CAL-AUTOMATE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Pred-SideA-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-COEFF-A-LUT_j01_20180109114311Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-COEFF-B-LUT_j01_20180109101739Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-004-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DELTA-C-LUT_j01_20180109000000Z_20180409000000Z_ee00000000000000Z_PS-1-O-CCR-3742-003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DG-ANOMALY-DN-LIMITS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SideA-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-DN0-LUT_j01_20190930000000Z_20190928000000Z_ee00000000000000Z_PS-1-O-CCR-4262-026-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-FRAME-TO-ZONE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Op21-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-GAIN-RATIOS-LUT_j01_20190930000000Z_20190928000000Z_ee00000000000000Z_PS-1-O-CCR-4262-025-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-LGS-GAINS-LUT_j01_20180413122703Z_20180412000000Z_ee00000000000000Z_PS-1-O-CCR-3918-005-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-RVF-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Op21-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-DNB-STRAY-LIGHT-CORRECTION-LUT_j01_20190930160523Z_20191001000000Z_ee00000000000000Z_PS-1-O-CCR-4322-024-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-EBBT-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-EMISSIVE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-F-PREDICTED-LUT_j01_20180413123333Z_20180412000000Z_ee00000000000000Z_PS-1-O-CCR-3918-006-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-GAIN-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-HAM-ER-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBC-ER-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBC-RR-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-OBS-TO-PIXELS-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SameAsSNPP-LE-PE_all-_all_all-_ops" # noqa
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], [b"VIIRS-SDR-RADIOMETRIC-PARAM-V3-LUT_j01_20161117000000Z_20180111000000Z_ee00000000000000Z_PS-1-O-CCR-17-3436-v003-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-REFLECTIVE-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-SameAsSNPP-LE-PE_all-_all_all-_ops" # noqa
], [b"VIIRS-SDR-RELATIVE-SPECTRAL-RESPONSE-LUT_j01_20161031000000Z_20180111000000Z_ee00000000000000Z_PS-1-O-CCR-17-3436-v003-FusedM9-LE-PE_all-_all_all-_ops" # noqa
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], [b"VIIRS-SDR-SOLAR-IRAD-LUT_j01_20160331000000Z_20170807130000Z_ee00000000000000Z_PS-1-O-CCR-16-2859-v002-Thuillier2002-LE-PE_all-_all_all-_ops" # noqa
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"N_Input_Prod": np.array( [ [b"GEO-VIIRS-OBC-IP:J01002526558865:A1"], [b"SPACECRAFT-DIARY-RDR:J01002526558800:A1"], [b"SPACECRAFT-DIARY-RDR:J01002526559000:A1"], [b"VIIRS-DNB-GEO:J01002526558865:A1"], [b"VIIRS-IMG-RGEO-TC:J01002526558865:A1"], [b"VIIRS-MOD-RGEO-TC:J01002526558865:A1"], [b"VIIRS-SCIENCE-RDR:J01002526558012:A1"], [b"VIIRS-SCIENCE-RDR:J01002526558865:A1"], ], dtype="|S40", ), "N_JPSS_Document_Ref": np.array( [ [ b"474-00448-02-06_JPSS-DD-Vol-II-Part-6_0200H.pdf" ], [ b"474-00448-02-06_JPSS-VIIRS-SDR-DD-Part-6_0200H_VIIRS-DNB-SDR-PP.xml" ], [ b"474-00448-03-06_JPSS-OAD-Vol-III-Part-6-VIIRS-RDR-SDR_-1.pdf" ], ], dtype="|S68", ),"N_LEOA_Flag": np.array([[b"On"]], dtype="|S3"),
"N_Nadir_Latitude_Max": np.array( [[45.3722]], dtype=np.float32 ), "N_Nadir_Latitude_Min": np.array( [[40.6172]], dtype=np.float32 ), "N_Nadir_Longitude_Max": np.array( [[-62.80047]], dtype=np.float32 ), "N_Nadir_Longitude_Min": np.array( [[-64.51342]], dtype=np.float32 ),"N_Number_Of_Scans": np.array([[47]], dtype=np.int32),
"N_Percent_Erroneous_Data": np.array( [[0.0]], dtype=np.float32 ), "N_Percent_Missing_Data": np.array( [[51.05127]], dtype=np.float32 ), "N_Percent_Not-Applicable_Data": np.array( [[0.0]], dtype=np.float32 ), "N_Primary_Label": np.array( [[b"Non-Primary"]], dtype="|S12" ), "N_Quality_Summary_Names": np.array( [ [b"Scan Quality Exclusion"], [b"Summary VIIRS SDR Quality"], ], dtype="|S26", ), "N_Quality_Summary_Values": np.array( [[24], [49]], dtype=np.int32 ),"N_RSB_Index": np.array([[17]], dtype=np.int32),
"N_Reference_ID": np.array( [[b"VIIRS-DNB-SDR:J01002526558865:A1"]], dtype="|S33" ),"N_Satellite/Local_Azimuth_Angle_Max": np.array(
[[179.9995]], dtype=np.float32 ),"N_Satellite/Local_Azimuth_Angle_Min": np.array(
[[-179.9976]], dtype=np.float32 ), "N_Satellite/Local_Zenith_Angle_Max": np.array( [[69.83973]], dtype=np.float32 ), "N_Satellite/Local_Zenith_Angle_Min": np.array( [[0.00898314]], dtype=np.float32 ), "N_Software_Version": np.array( [[b"CSPP_SDR_3_1_3"]], dtype="|S15" ), "N_Solar_Azimuth_Angle_Max": np.array( [[73.93496]], dtype=np.float32 ), "N_Solar_Azimuth_Angle_Min": np.array( [[23.83542]], dtype=np.float32 ), "N_Solar_Zenith_Angle_Max": np.array( [[147.5895]], dtype=np.float32 ), "N_Solar_Zenith_Angle_Min": np.array( [[126.3929]], dtype=np.float32 ), "N_Spacecraft_Maneuver": np.array( [[b"Normal Operations"]], dtype="|S18" ), "North_Bounding_Coordinate": np.array( [[46.8018]], dtype=np.float32 ), "South_Bounding_Coordinate": np.array( [[36.53402]], dtype=np.float32 ), "West_Bounding_Coordinate": np.array( [[-82.65787]], dtype=np.float32 ), } }, "attrs": {"Instrument_Short_Name": np.array([[b"VIIRS"]], dtype="|S6"),
"N_Collection_Short_Name": np.array( [[b"VIIRS-DNB-SDR"]], dtype="|S14" ),"N_Dataset_Type_Tag": np.array([[b"SDR"]], dtype="|S4"),
"N_Instrument_Flight_SW_Version": np.array( [[20], [65534]], dtype=np.int32 ),"N_Processing_Domain": np.array([[b"ops"]], dtype="|S4"),
"Operational_Mode": np.array([[b"J01 Normal Operations, VIIRS Operational"]],
dtype="|S41", ), }, }, }, "attrs": { "CVIIRS_Version": np.array([[b"2.0.1"]], dtype="|S5"),"Compact_VIIRS_SDR_Version": np.array([[b"3.1"]], dtype="|S3"),
"Distributor": np.array([[b"cspp"]], dtype="|S5"), "Mission_Name": np.array([[b"JPSS-1"]], dtype="|S7"), "N_Dataset_Source": np.array([[b"all-"]], dtype="|S5"), "N_GEO_Ref": np.array( [ [ b"GDNBO_j01_d20191025_t0611251_e0612478_b10015_c20191025062405837630_cspp_dev.h5" ] ], dtype="|S78", ),"N_HDF_Creation_Date": np.array([[b"20191025"]], dtype="|S8"), "N_HDF_Creation_Time": np.array([[b"062502.927000Z"]], dtype="|S14"),
"Platform_Short_Name": np.array([[b"J01"]], dtype="|S4"), "Satellite_Id_Filename": np.array([[b"j01"]], dtype="|S3"), }, }/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_viirs_compact.py:1485: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ mtrand.pyx:1169: in numpy.random.mtrand.RandomState.rand
??? mtrand.pyx:423: in numpy.random.mtrand.RandomState.random_sample ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 23.8 MiB for an array with shape (768, 4064) and data type float64???
_common.pyx:270: MemoryError________________ TestAWIPSTiledWriter.test_basic_lettered_tiles ________________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xf3bf69e8>
def test_basic_lettered_tiles(self): """Test creating a lettered grid.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data(shape=(2000, 1000), chunks=500) area_def = self._get_test_area(shape=(2000, 1000),extents=(-1000000., -1500000., 1000000., 1500000.))
ds = self._get_test_lcc_data(data, area_def) # tile_count should be ignored since we specified lettered_grid
w.save_datasets([ds], sector_id='LCC', source_name="TESTS", tile_count=(3, 3), lettered_grid=True)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:261: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_34, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError------------------------------ Captured log call ------------------------------- WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname ________ TestAWIPSTiledWriter.test_basic_lettered_tiles_diff_projection ________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0x608eb0>
def test_basic_lettered_tiles_diff_projection(self):"""Test creating a lettered grid from data with differing projection.."""
import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True)crs = CRS("+proj=lcc +datum=WGS84 +ellps=WGS84 +lon_0=-95. +lat_0=45 +lat_1=45 +units=m +no_defs")
data = self._get_test_data(shape=(2000, 1000), chunks=500)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:276: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:144: in _get_test_data data = np.linspace(0., 1., shape[0] * shape[1], dtype=np.float32).reshape(shape)
<__array_function__ internals>:5: in linspace ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
start = 0.0, stop = 1.0, num = 2000000, endpoint = True, retstep = False dtype = <class 'numpy.float32'>, axis = 0 @array_function_dispatch(_linspace_dispatcher)def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
axis=0): """ Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. .. versionchanged:: 1.16.0 Non-scalar `start` and `stop` are now supported. Parameters ---------- start : array_like The starting value of the sequence. stop : array_likeThe end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step
size changes when `endpoint` is False. num : int, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpoint : bool, optionalIf True, `stop` is the last sample. Otherwise, it is not included.
Default is True. retstep : bool, optionalIf True, return (`samples`, `step`), where `step` is the spacing
between samples. dtype : dtype, optionalThe type of the output array. If `dtype` is not given, infer the data
type from the other input arguments. .. versionadded:: 1.9.0 axis : int, optionalThe axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
.. versionadded:: 1.16.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also --------arange : Similar to `linspace`, but uses a step size (instead of the
number of samples).geomspace : Similar to `linspace`, but with numbers spaced evenly on a log
scale (a geometric progression).logspace : Similar to `geomspace`, but with the end points specified as
logarithms. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() """ num = operator.index(num) if num < 0:raise ValueError("Number of samples, %s, must be non-negative." % num)
div = (num - 1) if endpoint else num # Convert float/complex array scalars to float, gh-3504# and make sure one can use variables that have an __array_interface__, gh-6634
start = asanyarray(start) * 1.0 stop = asanyarray(stop) * 1.0 dt = result_type(start, stop, float(num)) if dtype is None: dtype = dt delta = stop - start
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 15.3 MiB for an array with shape (2000000,) and data type float64y = _nx.arange(0, num, dtype=dt).reshape((-1,) + (1,) * ndim(delta))
/usr/lib/python3/dist-packages/numpy/core/function_base.py:128: MemoryError___________ TestAWIPSTiledWriter.test_lettered_tiles_update_existing ___________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0x4eeb98>
def test_lettered_tiles_update_existing(self): """Test updating lettered tiles with additional data.""" import shutil import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import dask first_base_dir = os.path.join(self.base_dir, 'first') w = AWIPSTiledWriter(base_dir=first_base_dir, compress=True) shape = (2000, 1000)
data = np.linspace(0., 1., shape[0] * shape[1], dtype=np.float32).reshape(shape)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:300: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ <__array_function__ internals>:5: in linspace
???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
start = 0.0, stop = 1.0, num = 2000000, endpoint = True, retstep = False dtype = <class 'numpy.float32'>, axis = 0 @array_function_dispatch(_linspace_dispatcher)def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
axis=0): """ Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. .. versionchanged:: 1.16.0 Non-scalar `start` and `stop` are now supported. Parameters ---------- start : array_like The starting value of the sequence. stop : array_likeThe end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step
size changes when `endpoint` is False. num : int, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpoint : bool, optionalIf True, `stop` is the last sample. Otherwise, it is not included.
Default is True. retstep : bool, optionalIf True, return (`samples`, `step`), where `step` is the spacing
between samples. dtype : dtype, optionalThe type of the output array. If `dtype` is not given, infer the data
type from the other input arguments. .. versionadded:: 1.9.0 axis : int, optionalThe axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
.. versionadded:: 1.16.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also --------arange : Similar to `linspace`, but uses a step size (instead of the
number of samples).geomspace : Similar to `linspace`, but with numbers spaced evenly on a log
scale (a geometric progression).logspace : Similar to `geomspace`, but with the end points specified as
logarithms. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() """ num = operator.index(num) if num < 0:raise ValueError("Number of samples, %s, must be non-negative." % num)
div = (num - 1) if endpoint else num # Convert float/complex array scalars to float, gh-3504# and make sure one can use variables that have an __array_interface__, gh-6634
start = asanyarray(start) * 1.0 stop = asanyarray(stop) * 1.0 dt = result_type(start, stop, float(num)) if dtype is None: dtype = dt delta = stop - start
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 15.3 MiB for an array with shape (2000000,) and data type float64y = _nx.arange(0, num, dtype=dt).reshape((-1,) + (1,) * ndim(delta))
/usr/lib/python3/dist-packages/numpy/core/function_base.py:128: MemoryError_____________ TestAWIPSTiledWriter.test_lettered_tiles_sector_ref ______________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xbbd58e68>
def test_lettered_tiles_sector_ref(self): """Test creating a lettered grid using the sector as reference.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True)
data = self._get_test_data(shape=(2000, 1000), chunks=500)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:366: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:144: in _get_test_data data = np.linspace(0., 1., shape[0] * shape[1], dtype=np.float32).reshape(shape)
<__array_function__ internals>:5: in linspace ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
start = 0.0, stop = 1.0, num = 2000000, endpoint = True, retstep = False dtype = <class 'numpy.float32'>, axis = 0 @array_function_dispatch(_linspace_dispatcher)def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
axis=0): """ Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. .. versionchanged:: 1.16.0 Non-scalar `start` and `stop` are now supported. Parameters ---------- start : array_like The starting value of the sequence. stop : array_likeThe end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step
size changes when `endpoint` is False. num : int, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpoint : bool, optionalIf True, `stop` is the last sample. Otherwise, it is not included.
Default is True. retstep : bool, optionalIf True, return (`samples`, `step`), where `step` is the spacing
between samples. dtype : dtype, optionalThe type of the output array. If `dtype` is not given, infer the data
type from the other input arguments. .. versionadded:: 1.9.0 axis : int, optionalThe axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
.. versionadded:: 1.16.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also --------arange : Similar to `linspace`, but uses a step size (instead of the
number of samples).geomspace : Similar to `linspace`, but with numbers spaced evenly on a log
scale (a geometric progression).logspace : Similar to `geomspace`, but with the end points specified as
logarithms. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() """ num = operator.index(num) if num < 0:raise ValueError("Number of samples, %s, must be non-negative." % num)
div = (num - 1) if endpoint else num # Convert float/complex array scalars to float, gh-3504# and make sure one can use variables that have an __array_interface__, gh-6634
start = asanyarray(start) * 1.0 stop = asanyarray(stop) * 1.0 dt = result_type(start, stop, float(num)) if dtype is None: dtype = dt delta = stop - start
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 15.3 MiB for an array with shape (2000000,) and data type float64y = _nx.arange(0, num, dtype=dt).reshape((-1,) + (1,) * ndim(delta))
/usr/lib/python3/dist-packages/numpy/core/function_base.py:128: MemoryError_______________ TestAWIPSTiledWriter.test_lettered_tiles_no_fit ________________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xe9d7760>
def test_lettered_tiles_no_fit(self):"""Test creating a lettered grid with no data overlapping the grid."""
from satpy.writers.awips_tiled import AWIPSTiledWriter w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True)
data = self._get_test_data(shape=(2000, 1000), chunks=500)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:386: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:144: in _get_test_data data = np.linspace(0., 1., shape[0] * shape[1], dtype=np.float32).reshape(shape)
<__array_function__ internals>:5: in linspace ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
start = 0.0, stop = 1.0, num = 2000000, endpoint = True, retstep = False dtype = <class 'numpy.float32'>, axis = 0 @array_function_dispatch(_linspace_dispatcher)def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
axis=0): """ Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. .. versionchanged:: 1.16.0 Non-scalar `start` and `stop` are now supported. Parameters ---------- start : array_like The starting value of the sequence. stop : array_likeThe end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step
size changes when `endpoint` is False. num : int, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpoint : bool, optionalIf True, `stop` is the last sample. Otherwise, it is not included.
Default is True. retstep : bool, optionalIf True, return (`samples`, `step`), where `step` is the spacing
between samples. dtype : dtype, optionalThe type of the output array. If `dtype` is not given, infer the data
type from the other input arguments. .. versionadded:: 1.9.0 axis : int, optionalThe axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
.. versionadded:: 1.16.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also --------arange : Similar to `linspace`, but uses a step size (instead of the
number of samples).geomspace : Similar to `linspace`, but with numbers spaced evenly on a log
scale (a geometric progression).logspace : Similar to `geomspace`, but with the end points specified as
logarithms. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() """ num = operator.index(num) if num < 0:raise ValueError("Number of samples, %s, must be non-negative." % num)
div = (num - 1) if endpoint else num # Convert float/complex array scalars to float, gh-3504# and make sure one can use variables that have an __array_interface__, gh-6634
start = asanyarray(start) * 1.0 stop = asanyarray(stop) * 1.0 dt = result_type(start, stop, float(num)) if dtype is None: dtype = dt delta = stop - start
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 15.3 MiB for an array with shape (2000000,) and data type float64y = _nx.arange(0, num, dtype=dt).reshape((-1,) + (1,) * ndim(delta))
/usr/lib/python3/dist-packages/numpy/core/function_base.py:128: MemoryError____________ TestAWIPSTiledWriter.test_lettered_tiles_no_valid_data ____________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xe9f7e38>
def test_lettered_tiles_no_valid_data(self): """Test creating a lettered grid with no valid data.""" from satpy.writers.awips_tiled import AWIPSTiledWriter w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = da.full((2000, 1000), np.nan, chunks=500, dtype=np.float32) area_def = self._get_test_area(shape=(2000, 1000),extents=(-1000000., -1500000., 1000000., 1500000.))
ds = self._get_test_lcc_data(data, area_def)
w.save_datasets([ds], sector_id='LCC', source_name="TESTS", tile_count=(3, 3), lettered_grid=True)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:403: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_34, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError------------------------------ Captured log call ------------------------------- WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname WARNING satpy.writers.awips_tiled:awips_tiled.py:935 environment ORGANIZATION not set for .production_location attribute, using hostname ____________ TestAWIPSTiledWriter.test_lettered_tiles_bad_filename _____________
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xc9fdd30>
def test_lettered_tiles_bad_filename(self): """Test creating a lettered grid with a bad filename.""" from satpy.writers.awips_tiled import AWIPSTiledWriterw = AWIPSTiledWriter(base_dir=self.base_dir, compress=True, filename="{Bad Key}.nc")
data = self._get_test_data(shape=(2000, 1000), chunks=500)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:412: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:144: in _get_test_data data = np.linspace(0., 1., shape[0] * shape[1], dtype=np.float32).reshape(shape)
<__array_function__ internals>:5: in linspace ???_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
start = 0.0, stop = 1.0, num = 2000000, endpoint = True, retstep = False dtype = <class 'numpy.float32'>, axis = 0 @array_function_dispatch(_linspace_dispatcher)def linspace(start, stop, num=50, endpoint=True, retstep=False, dtype=None,
axis=0): """ Return evenly spaced numbers over a specified interval. Returns `num` evenly spaced samples, calculated over the interval [`start`, `stop`]. The endpoint of the interval can optionally be excluded. .. versionchanged:: 1.16.0 Non-scalar `start` and `stop` are now supported. Parameters ---------- start : array_like The starting value of the sequence. stop : array_likeThe end value of the sequence, unless `endpoint` is set to False. In that case, the sequence consists of all but the last of ``num + 1`` evenly spaced samples, so that `stop` is excluded. Note that the step
size changes when `endpoint` is False. num : int, optionalNumber of samples to generate. Default is 50. Must be non-negative.
endpoint : bool, optionalIf True, `stop` is the last sample. Otherwise, it is not included.
Default is True. retstep : bool, optionalIf True, return (`samples`, `step`), where `step` is the spacing
between samples. dtype : dtype, optionalThe type of the output array. If `dtype` is not given, infer the data
type from the other input arguments. .. versionadded:: 1.9.0 axis : int, optionalThe axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.
.. versionadded:: 1.16.0 Returns ------- samples : ndarray There are `num` equally spaced samples in the closed interval ``[start, stop]`` or the half-open interval ``[start, stop)`` (depending on whether `endpoint` is True or False). step : float, optional Only returned if `retstep` is True Size of spacing between samples. See Also --------arange : Similar to `linspace`, but uses a step size (instead of the
number of samples).geomspace : Similar to `linspace`, but with numbers spaced evenly on a log
scale (a geometric progression).logspace : Similar to `geomspace`, but with the end points specified as
logarithms. Examples -------- >>> np.linspace(2.0, 3.0, num=5) array([2. , 2.25, 2.5 , 2.75, 3. ]) >>> np.linspace(2.0, 3.0, num=5, endpoint=False) array([2. , 2.2, 2.4, 2.6, 2.8]) >>> np.linspace(2.0, 3.0, num=5, retstep=True) (array([2. , 2.25, 2.5 , 2.75, 3. ]), 0.25) Graphical illustration: >>> import matplotlib.pyplot as plt >>> N = 8 >>> y = np.zeros(N) >>> x1 = np.linspace(0, 10, N, endpoint=True) >>> x2 = np.linspace(0, 10, N, endpoint=False) >>> plt.plot(x1, y, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.plot(x2, y + 0.5, 'o') [<matplotlib.lines.Line2D object at 0x...>] >>> plt.ylim([-0.5, 1]) (-0.5, 1) >>> plt.show() """ num = operator.index(num) if num < 0:raise ValueError("Number of samples, %s, must be non-negative." % num)
div = (num - 1) if endpoint else num # Convert float/complex array scalars to float, gh-3504# and make sure one can use variables that have an __array_interface__, gh-6634
start = asanyarray(start) * 1.0 stop = asanyarray(stop) * 1.0 dt = result_type(start, stop, float(num)) if dtype is None: dtype = dt delta = stop - starty = _nx.arange(0, num, dtype=dt).reshape((-1,) + (1,) * ndim(delta)) # In-place multiplication y *= delta/div is faster, but prevents the multiplicant # from overriding what class is produced, and thus prevents, e.g. use of Quantities, # see gh-7142. Hence, we multiply in place only for standard scalar types.
_mult_inplace = _nx.isscalar(delta) if div > 0: step = delta / div if _nx.any(step == 0): # Special handling for denormal numbers, gh-5437 y /= div if _mult_inplace: y *= delta else: y = y * delta else: if _mult_inplace: y *= step else: y = y * step else:# sequences with 0 items or 1 item with endpoint=True (i.e. div <= 0)
# have an undefined step step = NaN# Multiply with delta to allow possible override of output class.
y = y * delta y += start if endpoint and num > 1: y[-1] = stop if axis != 0: y = _nx.moveaxis(y, 0, axis) if retstep: return y.astype(dtype, copy=False), step else:
E numpy.core._exceptions._ArrayMemoryError: Unable to allocate 7.63 MiB for an array with shape (2000000,) and data type float32return y.astype(dtype, copy=False)
/usr/lib/python3/dist-packages/numpy/core/function_base.py:165: MemoryError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs0-C] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0x5eebb50>
sector = 'C', extra_kwargs = {} @pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_34, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs0-F] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xeb1640>
sector = 'F', extra_kwargs = {} @pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs1-C] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xfd406e8>
sector = 'C', extra_kwargs = {'environment_prefix': 'AA'} @pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs1-F] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xd59ac70>
sector = 'F', extra_kwargs = {'environment_prefix': 'AA'} @pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs2-C] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xabbac88>
sector = 'C'extra_kwargs = {'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'}
@pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____ TestAWIPSTiledWriter.test_multivar_numbered_tiles_glm[extra_kwargs2-F] ____
self = <satpy.tests.writer_tests.test_awips_tiled.TestAWIPSTiledWriter object at 0xc9d0328>
sector = 'F'extra_kwargs = {'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'}
@pytest.mark.parametrize( "sector", ['C', 'F'] ) @pytest.mark.parametrize( "extra_kwargs", [ {}, {'environment_prefix': 'AA'},{'environment_prefix': 'BB', 'filename': '{environment_prefix}_{name}_GLM_T{tile_number:04d}.nc'},
] ) def test_multivar_numbered_tiles_glm(self, sector, extra_kwargs): """Test creating a tiles with multiple variables.""" import xarray as xr from satpy.writers.awips_tiled import AWIPSTiledWriter import os os.environ['ORGANIZATION'] = '1' * 50 w = AWIPSTiledWriter(base_dir=self.base_dir, compress=True) data = self._get_test_data() area_def = self._get_test_area() ds1 = self._get_test_lcc_data(data, area_def) ds1.attrs.update( dict( name='total_energy', platform_name='GOES-17', sensor='SENSOR', units='1', scan_mode='M3', scene_abbr=sector, platform_shortname="G17" ) ) ds2 = ds1.copy() ds2.attrs.update({ 'name': 'flash_extent_density', }) ds3 = ds1.copy() ds3.attrs.update({ 'name': 'average_flash_area', }) dqf = ds1.copy() dqf = (dqf * 255).astype(np.uint8) dqf.attrs = ds1.attrs.copy() dqf.attrs.update({ 'name': 'DQF', '_FillValue': 1, })> w.save_datasets([ds1, ds2, ds3, dqf], sector_id='TEST', source_name="TESTS", tile_count=(3, 3), template='glm_l2_rad{}'.format(sector.lower()),
**extra_kwargs)/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_awips_tiled.py:499: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1615: in save_datasets
delayeds = self._delay_netcdf_creation(delayed_gen)/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1632: in _delay_netcdf_creation for dataset_to_save, output_filename, mode in dataset_iter(delayed_gen): /usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:1654: in dataset_iter
results = dask.compute(_delayed_gen)[0] /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError__________ TestMITIFFWriter.test_get_test_dataset_three_bands_prereq ___________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_get_test_dataset_three_bands_prereq>
def test_get_test_dataset_three_bands_prereq(self):"""Test basic writer operation with 3 bands with DataQuery prerequisites with missing name."""
import os from libtiff import TIFF from satpy.writers.mitiff import MITIFFWriter IMAGEDESCRIPTION = 270 dataset = self._get_test_dataset_three_bands_prereq() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:988: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-2_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError______________ TestMITIFFWriter.test_save_dataset_with_bad_value _______________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_save_dataset_with_bad_value>
def test_save_dataset_with_bad_value(self): """Test writer operation with bad values.""" import os import numpy as np from libtiff import TIFF from satpy.writers.mitiff import MITIFFWriter expected = np.array([[0, 4, 1, 37, 73], [110, 146, 183, 219, 255]]) dataset = self._get_test_dataset_with_bad_values() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:831: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-3_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError_____________ TestMITIFFWriter.test_save_dataset_with_calibration ______________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_save_dataset_with_calibration>
def test_save_dataset_with_calibration(self): """Test writer operation with calibration.""" import os import numpy as np from libtiff import TIFF from satpy.writers.mitiff import MITIFFWriter expected_ir = np.full((100, 200), 255) expected_vis = np.full((100, 200), 0)expected = np.stack([expected_vis, expected_vis, expected_ir, expected_ir, expected_ir, expected_vis]) expected_key_channel = ['Table_calibration: 1-VIS0.63, Reflectance(Albedo), [%], 8, [ 0.00 0.39 0.78 1.18 1.57 ' '1.96 2.35 2.75 3.14 3.53 3.92 4.31 4.71 5.10 5.49 5.88 6.27 6.67 7.06 7.45 7.84 8.24 ' '8.63 9.02 9.41 9.80 10.20 10.59 10.98 11.37 11.76 12.16 12.55 12.94 13.33 13.73 14.12 ' '14.51 14.90 15.29 15.69 16.08 16.47 16.86 17.25 17.65 18.04 18.43 18.82 19.22 19.61 ' '20.00 20.39 20.78 21.18 21.57 21.96 22.35 22.75 23.14 23.53 23.92 24.31 24.71 25.10 ' '25.49 25.88 26.27 26.67 27.06 27.45 27.84 28.24 28.63 29.02 29.41 29.80 30.20 30.59 ' '30.98 31.37 31.76 32.16 32.55 32.94 33.33 33.73 34.12 34.51 34.90 35.29 35.69 36.08 ' '36.47 36.86 37.25 37.65 38.04 38.43 38.82 39.22 39.61 40.00 40.39 40.78 41.18 41.57 ' '41.96 42.35 42.75 43.14 43.53 43.92 44.31 44.71 45.10 45.49 45.88 46.27 46.67 47.06 ' '47.45 47.84 48.24 48.63 49.02 49.41 49.80 50.20 50.59 50.98 51.37 51.76 52.16 52.55 ' '52.94 53.33 53.73 54.12 54.51 54.90 55.29 55.69 56.08 56.47 56.86 57.25 57.65 58.04 ' '58.43 58.82 59.22 59.61 60.00 60.39 60.78 61.18 61.57 61.96 62.35 62.75 63.14 63.53 ' '63.92 64.31 64.71 65.10 65.49 65.88 66.27 66.67 67.06 67.45 67.84 68.24 68.63 69.02 ' '69.41 69.80 70.20 70.59 70.98 71.37 71.76 72.16 72.55 72.94 73.33 73.73 74.12 74.51 ' '74.90 75.29 75.69 76.08 76.47 76.86 77.25 77.65 78.04 78.43 78.82 79.22 79.61 80.00 ' '80.39 80.78 81.18 81.57 81.96 82.35 82.75 83.14 83.53 83.92 84.31 84.71 85.10 85.49 ' '85.88 86.27 86.67 87.06 87.45 87.84 88.24 88.63 89.02 89.41 89.80 90.20 90.59 90.98 ' '91.37 91.76 92.16 92.55 92.94 93.33 93.73 94.12 94.51 94.90 95.29 95.69 96.08 96.47 ' '96.86 97.25 97.65 98.04 98.43 98.82 99.22 99.61 100.00 ]', 'Table_calibration: 2-VIS0.86, Reflectance(Albedo), [%], 8, [ 0.00 0.39 0.78 1.18 1.57 ' '1.96 2.35 2.75 3.14 3.53 3.92 4.31 4.71 5.10 5.49 5.88 6.27 6.67 7.06 7.45 7.84 8.24 ' '8.63 9.02 9.41 9.80 10.20 10.59 10.98 11.37 11.76 12.16 12.55 12.94 13.33 13.73 14.12 ' '14.51 14.90 15.29 15.69 16.08 16.47 16.86 17.25 17.65 18.04 18.43 18.82 19.22 19.61 ' '20.00 20.39 20.78 21.18 21.57 21.96 22.35 22.75 23.14 23.53 23.92 24.31 24.71 25.10 ' '25.49 25.88 26.27 26.67 27.06 27.45 27.84 28.24 28.63 29.02 29.41 29.80 30.20 30.59 ' '30.98 31.37 31.76 32.16 32.55 32.94 33.33 33.73 34.12 34.51 34.90 35.29 35.69 36.08 ' '36.47 36.86 37.25 37.65 38.04 38.43 38.82 39.22 39.61 40.00 40.39 40.78 41.18 41.57 ' '41.96 42.35 42.75 43.14 43.53 43.92 44.31 44.71 45.10 45.49 45.88 46.27 46.67 47.06 ' '47.45 47.84 48.24 48.63 49.02 49.41 49.80 50.20 50.59 50.98 51.37 51.76 52.16 52.55 ' '52.94 53.33 53.73 54.12 54.51 54.90 55.29 55.69 56.08 56.47 56.86 57.25 57.65 58.04 ' '58.43 58.82 59.22 59.61 60.00 60.39 60.78 61.18 61.57 61.96 62.35 62.75 63.14 63.53 ' '63.92 64.31 64.71 65.10 65.49 65.88 66.27 66.67 67.06 67.45 67.84 68.24 68.63 69.02 ' '69.41 69.80 70.20 70.59 70.98 71.37 71.76 72.16 72.55 72.94 73.33 73.73 74.12 74.51 ' '74.90 75.29 75.69 76.08 76.47 76.86 77.25 77.65 78.04 78.43 78.82 79.22 79.61 80.00 ' '80.39 80.78 81.18 81.57 81.96 82.35 82.75 83.14 83.53 83.92 84.31 84.71 85.10 85.49 ' '85.88 86.27 86.67 87.06 87.45 87.84 88.24 88.63 89.02 89.41 89.80 90.20 90.59 90.98 ' '91.37 91.76 92.16 92.55 92.94 93.33 93.73 94.12 94.51 94.90 95.29 95.69 96.08 96.47 ' '96.86 97.25 97.65 98.04 98.43 98.82 99.22 99.61 100.00 ]', u'Table_calibration: 3(3B)-IR3.7, BT, °[C], 8, [ 50.00 49.22 48.43 47.65 46.86 46.08 ' '45.29 44.51 43.73 42.94 42.16 41.37 40.59 39.80 39.02 38.24 37.45 36.67 35.88 35.10 ' '34.31 33.53 32.75 31.96 31.18 30.39 29.61 28.82 28.04 27.25 26.47 25.69 24.90 24.12 ' '23.33 22.55 21.76 20.98 20.20 19.41 18.63 17.84 17.06 16.27 15.49 14.71 13.92 13.14 ' '12.35 11.57 10.78 10.00 9.22 8.43 7.65 6.86 6.08 5.29 4.51 3.73 2.94 2.16 1.37 0.59 ' '-0.20 -0.98 -1.76 -2.55 -3.33 -4.12 -4.90 -5.69 -6.47 -7.25 -8.04 -8.82 -9.61 -10.39 ' '-11.18 -11.96 -12.75 -13.53 -14.31 -15.10 -15.88 -16.67 -17.45 -18.24 -19.02 -19.80 ' '-20.59 -21.37 -22.16 -22.94 -23.73 -24.51 -25.29 -26.08 -26.86 -27.65 -28.43 -29.22 ' '-30.00 -30.78 -31.57 -32.35 -33.14 -33.92 -34.71 -35.49 -36.27 -37.06 -37.84 -38.63 ' '-39.41 -40.20 -40.98 -41.76 -42.55 -43.33 -44.12 -44.90 -45.69 -46.47 -47.25 -48.04 ' '-48.82 -49.61 -50.39 -51.18 -51.96 -52.75 -53.53 -54.31 -55.10 -55.88 -56.67 -57.45 ' '-58.24 -59.02 -59.80 -60.59 -61.37 -62.16 -62.94 -63.73 -64.51 -65.29 -66.08 -66.86 ' '-67.65 -68.43 -69.22 -70.00 -70.78 -71.57 -72.35 -73.14 -73.92 -74.71 -75.49 -76.27 ' '-77.06 -77.84 -78.63 -79.41 -80.20 -80.98 -81.76 -82.55 -83.33 -84.12 -84.90 -85.69 ' '-86.47 -87.25 -88.04 -88.82 -89.61 -90.39 -91.18 -91.96 -92.75 -93.53 -94.31 -95.10 ' '-95.88 -96.67 -97.45 -98.24 -99.02 -99.80 -100.59 -101.37 -102.16 -102.94 -103.73 ' '-104.51 -105.29 -106.08 -106.86 -107.65 -108.43 -109.22 -110.00 -110.78 -111.57 ' '-112.35 -113.14 -113.92 -114.71 -115.49 -116.27 -117.06 -117.84 -118.63 -119.41 ' '-120.20 -120.98 -121.76 -122.55 -123.33 -124.12 -124.90 -125.69 -126.47 -127.25 ' '-128.04 -128.82 -129.61 -130.39 -131.18 -131.96 -132.75 -133.53 -134.31 -135.10 ' '-135.88 -136.67 -137.45 -138.24 -139.02 -139.80 -140.59 -141.37 -142.16 -142.94 ' '-143.73 -144.51 -145.29 -146.08 -146.86 -147.65 -148.43 -149.22 -150.00 ]', u'Table_calibration: 4-IR10.8, BT, °[C], 8, [ 50.00 49.22 48.43 47.65 46.86 46.08 '
'45.29 ''44.51 43.73 42.94 42.16 41.37 40.59 39.80 39.02 38.24 37.45 36.67 35.88 35.10 34.31 ' '33.53 32.75 31.96 31.18 30.39 29.61 28.82 28.04 27.25 26.47 25.69 24.90 24.12 23.33 ' '22.55 21.76 20.98 20.20 19.41 18.63 17.84 17.06 16.27 15.49 14.71 13.92 13.14 12.35 ' '11.57 10.78 10.00 9.22 8.43 7.65 6.86 6.08 5.29 4.51 3.73 2.94 2.16 1.37 0.59 -0.20 ' '-0.98 -1.76 -2.55 -3.33 -4.12 -4.90 -5.69 -6.47 -7.25 -8.04 -8.82 -9.61 -10.39 -11.18 ' '-11.96 -12.75 -13.53 -14.31 -15.10 -15.88 -16.67 -17.45 -18.24 -19.02 -19.80 -20.59 ' '-21.37 -22.16 -22.94 -23.73 -24.51 -25.29 -26.08 -26.86 -27.65 -28.43 -29.22 -30.00 ' '-30.78 -31.57 -32.35 -33.14 -33.92 -34.71 -35.49 -36.27 -37.06 -37.84 -38.63 -39.41 ' '-40.20 -40.98 -41.76 -42.55 -43.33 -44.12 -44.90 -45.69 -46.47 -47.25 -48.04 -48.82 ' '-49.61 -50.39 -51.18 -51.96 -52.75 -53.53 -54.31 -55.10 -55.88 -56.67 -57.45 -58.24 ' '-59.02 -59.80 -60.59 -61.37 -62.16 -62.94 -63.73 -64.51 -65.29 -66.08 -66.86 -67.65 ' '-68.43 -69.22 -70.00 -70.78 -71.57 -72.35 -73.14 -73.92 -74.71 -75.49 -76.27 -77.06 ' '-77.84 -78.63 -79.41 -80.20 -80.98 -81.76 -82.55 -83.33 -84.12 -84.90 -85.69 -86.47 ' '-87.25 -88.04 -88.82 -89.61 -90.39 -91.18 -91.96 -92.75 -93.53 -94.31 -95.10 -95.88 ' '-96.67 -97.45 -98.24 -99.02 -99.80 -100.59 -101.37 -102.16 -102.94 -103.73 -104.51 ' '-105.29 -106.08 -106.86 -107.65 -108.43 -109.22 -110.00 -110.78 -111.57 -112.35 ' '-113.14 -113.92 -114.71 -115.49 -116.27 -117.06 -117.84 -118.63 -119.41 -120.20 ' '-120.98 -121.76 -122.55 -123.33 -124.12 -124.90 -125.69 -126.47 -127.25 -128.04 ' '-128.82 -129.61 -130.39 -131.18 -131.96 -132.75 -133.53 -134.31 -135.10 -135.88 ' '-136.67 -137.45 -138.24 -139.02 -139.80 -140.59 -141.37 -142.16 -142.94 -143.73 ' '-144.51 -145.29 -146.08 -146.86 -147.65 -148.43 -149.22 -150.00 ]', u'Table_calibration: 5-IR11.5, BT, °[C], 8, [ 50.00 49.22 48.43 47.65 46.86 46.08 '
'45.29 ''44.51 43.73 42.94 42.16 41.37 40.59 39.80 39.02 38.24 37.45 36.67 35.88 35.10 34.31 ' '33.53 32.75 31.96 31.18 30.39 29.61 28.82 28.04 27.25 26.47 25.69 24.90 24.12 23.33 ' '22.55 21.76 20.98 20.20 19.41 18.63 17.84 17.06 16.27 15.49 14.71 13.92 13.14 12.35 ' '11.57 10.78 10.00 9.22 8.43 7.65 6.86 6.08 5.29 4.51 3.73 2.94 2.16 1.37 0.59 -0.20 ' '-0.98 -1.76 -2.55 -3.33 -4.12 -4.90 -5.69 -6.47 -7.25 -8.04 -8.82 -9.61 -10.39 -11.18 ' '-11.96 -12.75 -13.53 -14.31 -15.10 -15.88 -16.67 -17.45 -18.24 -19.02 -19.80 -20.59 ' '-21.37 -22.16 -22.94 -23.73 -24.51 -25.29 -26.08 -26.86 -27.65 -28.43 -29.22 -30.00 ' '-30.78 -31.57 -32.35 -33.14 -33.92 -34.71 -35.49 -36.27 -37.06 -37.84 -38.63 -39.41 ' '-40.20 -40.98 -41.76 -42.55 -43.33 -44.12 -44.90 -45.69 -46.47 -47.25 -48.04 -48.82 ' '-49.61 -50.39 -51.18 -51.96 -52.75 -53.53 -54.31 -55.10 -55.88 -56.67 -57.45 -58.24 ' '-59.02 -59.80 -60.59 -61.37 -62.16 -62.94 -63.73 -64.51 -65.29 -66.08 -66.86 -67.65 ' '-68.43 -69.22 -70.00 -70.78 -71.57 -72.35 -73.14 -73.92 -74.71 -75.49 -76.27 -77.06 ' '-77.84 -78.63 -79.41 -80.20 -80.98 -81.76 -82.55 -83.33 -84.12 -84.90 -85.69 -86.47 ' '-87.25 -88.04 -88.82 -89.61 -90.39 -91.18 -91.96 -92.75 -93.53 -94.31 -95.10 -95.88 ' '-96.67 -97.45 -98.24 -99.02 -99.80 -100.59 -101.37 -102.16 -102.94 -103.73 -104.51 ' '-105.29 -106.08 -106.86 -107.65 -108.43 -109.22 -110.00 -110.78 -111.57 -112.35 ' '-113.14 -113.92 -114.71 -115.49 -116.27 -117.06 -117.84 -118.63 -119.41 -120.20 ' '-120.98 -121.76 -122.55 -123.33 -124.12 -124.90 -125.69 -126.47 -127.25 -128.04 ' '-128.82 -129.61 -130.39 -131.18 -131.96 -132.75 -133.53 -134.31 -135.10 -135.88 ' '-136.67 -137.45 -138.24 -139.02 -139.80 -140.59 -141.37 -142.16 -142.94 -143.73 ' '-144.51 -145.29 -146.08 -146.86 -147.65 -148.43 -149.22 -150.00 ]', 'Table_calibration: 6(3A)-VIS1.6, Reflectance(Albedo), [%], 8, [ 0.00 0.39 0.78 1.18 ' '1.57 1.96 2.35 2.75 3.14 3.53 3.92 4.31 4.71 5.10 5.49 5.88 6.27 6.67 7.06 7.45 7.84 ' '8.24 8.63 9.02 9.41 9.80 10.20 10.59 10.98 11.37 11.76 12.16 12.55 12.94 13.33 13.73 ' '14.12 14.51 14.90 15.29 15.69 16.08 16.47 16.86 17.25 17.65 18.04 18.43 18.82 19.22 ' '19.61 20.00 20.39 20.78 21.18 21.57 21.96 22.35 22.75 23.14 23.53 23.92 24.31 24.71 ' '25.10 25.49 25.88 26.27 26.67 27.06 27.45 27.84 28.24 28.63 29.02 29.41 29.80 30.20 ' '30.59 30.98 31.37 31.76 32.16 32.55 32.94 33.33 33.73 34.12 34.51 34.90 35.29 35.69 ' '36.08 36.47 36.86 37.25 37.65 38.04 38.43 38.82 39.22 39.61 40.00 40.39 40.78 41.18 ' '41.57 41.96 42.35 42.75 43.14 43.53 43.92 44.31 44.71 45.10 45.49 45.88 46.27 46.67 ' '47.06 47.45 47.84 48.24 48.63 49.02 49.41 49.80 50.20 50.59 50.98 51.37 51.76 52.16 ' '52.55 52.94 53.33 53.73 54.12 54.51 54.90 55.29 55.69 56.08 56.47 56.86 57.25 57.65 ' '58.04 58.43 58.82 59.22 59.61 60.00 60.39 60.78 61.18 61.57 61.96 62.35 62.75 63.14 ' '63.53 63.92 64.31 64.71 65.10 65.49 65.88 66.27 66.67 67.06 67.45 67.84 68.24 68.63 ' '69.02 69.41 69.80 70.20 70.59 70.98 71.37 71.76 72.16 72.55 72.94 73.33 73.73 74.12 ' '74.51 74.90 75.29 75.69 76.08 76.47 76.86 77.25 77.65 78.04 78.43 78.82 79.22 79.61 ' '80.00 80.39 80.78 81.18 81.57 81.96 82.35 82.75 83.14 83.53 83.92 84.31 84.71 85.10 ' '85.49 85.88 86.27 86.67 87.06 87.45 87.84 88.24 88.63 89.02 89.41 89.80 90.20 90.59 ' '90.98 91.37 91.76 92.16 92.55 92.94 93.33 93.73 94.12 94.51 94.90 95.29 95.69 96.08 ' '96.47 96.86 97.25 97.65 98.04 98.43 98.82 99.22 99.61 100.00 ]']
dataset = self._get_test_dataset_calibration()w = MITIFFWriter(filename=dataset.attrs['metadata_requirements']['file_pattern'], base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:731: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError____________________ TestMITIFFWriter.test_save_one_dataset ____________________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_save_one_dataset>
def test_save_one_dataset(self): """Test basic writer operation with one dataset ie. no bands.""" import os from libtiff import TIFF from satpy.writers.mitiff import MITIFFWriter dataset = self._get_test_one_dataset() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:571: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-4_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError______________ TestMITIFFWriter.test_save_one_dataset_sesnor_set _______________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_save_one_dataset_sesnor_set>
def test_save_one_dataset_sesnor_set(self): """Test basic writer operation with one dataset ie. no bands.""" import os from libtiff import TIFF from satpy.writers.mitiff import MITIFFWriter dataset = self._get_test_one_dataset_sensor_set() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:586: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-5_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError------------------------------ Captured log call ------------------------------- WARNING satpy.writers.mitiff:mitiff.py:81 Sensor is set, will use the first value: {'avhrr'} ______________________ TestMITIFFWriter.test_simple_write ______________________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_simple_write>
def test_simple_write(self): """Test basic writer operation.""" from satpy.writers.mitiff import MITIFFWriter dataset = self._get_test_dataset() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:530: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-6_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError_________________ TestMITIFFWriter.test_simple_write_two_bands _________________
self = <satpy.tests.writer_tests.test_mitiff.TestMITIFFWriter testMethod=test_simple_write_two_bands>
def test_simple_write_two_bands(self):"""Test basic writer operation with 3 bands from 2 prerequisites."""
from satpy.writers.mitiff import MITIFFWriter dataset = self._get_test_dataset_three_bands_two_prereq() w = MITIFFWriter(base_dir=self.base_dir)
w.save_dataset(dataset)
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_mitiff.py:977: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/mitiff.py:113: in save_dataset
return delayed.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:517: in get_async raise_exception(exc, tb) /usr/lib/python3/dist-packages/dask/local.py:325: in reraise raise exc /usr/lib/python3/dist-packages/dask/local.py:223: in execute_task result = _execute_task(task, data) /usr/lib/python3/dist-packages/dask/core.py:121: in _execute_task return func(*(_execute_task(a, cache) for a in args))/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:104: in _delayed_create
self._save_datasets_as_mitiff(dataset, image_description,/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:728: in _save_datasets_as_mitiff
self._save_as_enhanced(tif, datasets, **kwargs)/usr/lib/python3/dist-packages/satpy/writers/mitiff.py:664: in _save_as_enhanced
data = chn.values.clip(0, 1) * 254. + 1 /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-7_0, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError_________________________ test_write_and_read_file_RGB _________________________
test_image_large_asia_RGB = <trollimage.xrimage.XRImage object at 0xb4697760> tmp_path = PosixPath('/tmp/pytest-of-debci/pytest-0/test_write_and_read_file_RGB0')
def test_write_and_read_file_RGB(test_image_large_asia_RGB, tmp_path): """Test writing and reading RGB.""" import rasterio from satpy.writers.ninjogeotiff import NinJoGeoTIFFWriter fn = os.fspath(tmp_path / "test.tif") ngtw = NinJoGeoTIFFWriter()
ngtw.save_dataset(
test_image_large_asia_RGB.data, filename=fn, fill_value=0, PhysicUnit="N/A", PhysicValue="N/A", SatelliteNameID=6400014, ChannelID=900015, DataType="GORN", DataSource="dowsing rod")/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_ninjogeotiff.py:467: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/satpy/writers/__init__.py:809: in save_dataset return self.save_image(img, filename=filename, compute=compute, fill_value=fill_value, **kwargs) /usr/lib/python3/dist-packages/satpy/writers/ninjogeotiff.py:178: in save_image
return super().save_image( /usr/lib/python3/dist-packages/satpy/writers/geotiff.py:228: in save_image return img.save(filename, fformat='tif', fill_value=fill_value, /usr/lib/python3/dist-packages/trollimage/xrimage.py:419: in save return self.rio_save(filename, fformat=fformat, /usr/lib/python3/dist-packages/trollimage/xrimage.py:590: in rio_save res = da.store(*to_store) /usr/lib/python3/dist-packages/dask/array/core.py:1043: in store compute_as_if_collection(Array, store_dsk, store_keys, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:315: in compute_as_if_collection return schedule(dsk2, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError_________________________ test_get_min_gray_value_RGB __________________________
ntg2 = <satpy.writers.ninjogeotiff.NinJoTagGenerator object at 0xb466e070> def test_get_min_gray_value_RGB(ntg2): """Test getting min gray value for RGB.Note that min/max gray value is mandatory in NinJo even for RGBs?
"""
assert ntg2.get_min_gray_value().compute().item() == 1 # fill value 0
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_ninjogeotiff.py:696: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/dataarray.py:955: in compute
return new.load(**kwargs) /usr/lib/python3/dist-packages/xarray/core/dataarray.py:929: in load ds = self._to_temp_dataset().load(**kwargs) /usr/lib/python3/dist-packages/xarray/core/dataset.py:865: in load evaluated_data = da.compute(*lazy_data.values(), **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError_________________________ test_get_max_gray_value_RGB __________________________
ntg2 = <satpy.writers.ninjogeotiff.NinJoTagGenerator object at 0xb466e070> def test_get_max_gray_value_RGB(ntg2): """Test max gray value for RGB."""
assert ntg2.get_max_gray_value() == 255
/usr/lib/python3/dist-packages/satpy/tests/writer_tests/test_ninjogeotiff.py:713: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ /usr/lib/python3/dist-packages/xarray/core/common.py:129: in __bool__
return bool(self.values) /usr/lib/python3/dist-packages/xarray/core/dataarray.py:651: in values return self.variable.values /usr/lib/python3/dist-packages/xarray/core/variable.py:517: in values return _as_array_or_item(self._data)/usr/lib/python3/dist-packages/xarray/core/variable.py:259: in _as_array_or_item
data = np.asarray(data) /usr/lib/python3/dist-packages/numpy/core/_asarray.py:83: in asarray return array(a, dtype, copy=False, order=order) /usr/lib/python3/dist-packages/dask/array/core.py:1491: in __array__ x = self.compute() /usr/lib/python3/dist-packages/dask/base.py:288: in compute (result,) = compute(self, traverse=False, **kwargs) /usr/lib/python3/dist-packages/dask/base.py:570: in compute results = schedule(dsk, keys, **kwargs) /usr/lib/python3/dist-packages/dask/threaded.py:79: in get results = get_async( /usr/lib/python3/dist-packages/dask/local.py:505: in get_async fire_tasks(chunksize) /usr/lib/python3/dist-packages/dask/local.py:500: in fire_tasks fut = submit(batch_execute_tasks, each_args) /usr/lib/python3.9/concurrent/futures/thread.py:176: in submit self._adjust_thread_count() /usr/lib/python3.9/concurrent/futures/thread.py:199: in _adjust_thread_count t.start()_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <Thread(ThreadPoolExecutor-0_35, initial)> def start(self): """Start the thread's activity.It must be called at most once per thread object. It arranges for the object's run() method to be invoked in a separate thread of control. This method will raise a RuntimeError if called more than once on the
same thread object. """ if not self._initialized: raise RuntimeError("thread.__init__() not called") if self._started.is_set(): raise RuntimeError("threads can only be started once") with _active_limbo_lock: _limbo[self] = self try:
_start_new_thread(self._bootstrap, ())
E RuntimeError: can't start new thread /usr/lib/python3.9/threading.py:892: RuntimeError=============================== warnings summary ===============================
../../../../usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_mviri_l1b_fiduceo_nc.py:535/usr/lib/python3/dist-packages/satpy/tests/reader_tests/test_mviri_l1b_fiduceo_nc.py:535: PytestUnknownMarkWarning: Unknown pytest.mark.file_handler_data - is this a typo? You can register custom marks to avoid this warning - for details, see https://docs.pytest.org/en/stable/mark.html
@pytest.mark.file_handler_data(mask_bad_quality=False) tests/test_composites.py: 13 warnings tests/test_config.py: 112 warnings tests/test_modifiers.py: 2 warnings tests/test_multiscene.py: 10 warnings tests/test_regressions.py: 6 warnings tests/test_resample.py: 14 warnings tests/test_scene.py: 15 warnings tests/test_writers.py: 4 warnings tests/test_yaml_reader.py: 3 warnings tests/compositor_tests/test_abi.py: 1 warning tests/compositor_tests/test_ahi.py: 1 warning tests/compositor_tests/test_glm.py: 1 warning tests/modifier_tests/test_crefl.py: 12 warnings tests/reader_tests/test_ahi_hsd.py: 2 warnings tests/reader_tests/test_ahi_l1b_gridded_bin.py: 1 warning tests/reader_tests/test_cmsaf_claas.py: 2 warnings tests/reader_tests/test_fci_l1c_nc.py: 16 warnings tests/reader_tests/test_generic_image.py: 3 warnings tests/reader_tests/test_geocat.py: 6 warnings tests/reader_tests/test_geos_area.py: 1 warning tests/reader_tests/test_gpm_imerg.py: 1 warning tests/reader_tests/test_hrit_base.py: 1 warning tests/reader_tests/test_mviri_l1b_fiduceo_nc.py: 12 warnings tests/reader_tests/test_nwcsaf_msg.py: 1 warning tests/reader_tests/test_nwcsaf_nc.py: 3 warnings tests/reader_tests/test_seviri_l1b_hrit.py: 3 warnings tests/reader_tests/test_seviri_l1b_native.py: 2 warnings tests/writer_tests/test_mitiff.py: 23 warnings/usr/lib/python3/dist-packages/pyproj/crs/crs.py:1256: UserWarning: You will likely lose important projection information when converting to a PROJ string from another format. See: https://proj.org/faq.html#what-is-the-best-format-for-describing-coordinate-reference-systems
return self._crs.to_proj4(version=version) tests/test_composites.py::TestMatchDataArrays::test_nondimensional_coords tests/test_composites.py::TestMatchDataArrays::test_nondimensional_coords tests/reader_tests/test_goes_imager_nc.py::GOESNCEUMFileHandlerRadianceTest::test_get_dataset_radiance tests/reader_tests/test_goes_imager_nc.py::GOESNCEUMFileHandlerRadianceTest::test_get_dataset_radiance tests/reader_tests/test_goes_imager_nc.py::GOESNCEUMFileHandlerRadianceTest::test_get_dataset_radiance tests/reader_tests/test_goes_imager_nc.py::GOESNCEUMFileHandlerRadianceTest::test_get_dataset_radiance tests/reader_tests/test_goes_imager_nc.py::GOESNCEUMFileHandlerReflectanceTest::test_get_dataset_reflectance/usr/lib/python3/dist-packages/xarray/core/dataarray.py:2343: PendingDeprecationWarning: dropping variables using `drop` will be deprecated; using drop_vars is encouraged.
ds = self._to_temp_dataset().drop(labels, dim, errors=errors) tests/test_data_download.py::TestDataDownload::test_find_registerable[readers0-writers0-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[readers0-None-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[readers0-writers2-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[None-writers0-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[None-None-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[None-writers2-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[readers2-writers0-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[readers2-None-None] tests/test_data_download.py::TestDataDownload::test_find_registerable[readers2-writers2-None]/usr/lib/python3/dist-packages/satpy/modifiers/_crefl.py:56: DeprecationWarning: 'dem_filename' for 'ReflectanceCorrector' is deprecated. Use 'url' instead.
warnings.warn("'dem_filename' for 'ReflectanceCorrector' is " tests/test_data_download.py::TestDataDownload::test_find_registerable[readers0-None-comp_sensors0]/usr/lib/python3/dist-packages/pyninjotiff/tifffile.py:154: UserWarning: failed to import the optional _tifffile C extension module.
Loading of some compressed images will be slow. Tifffile.c can be obtained at http://www.lfd.uci.edu/~gohlke/ warnings.warn( tests/test_dataset.py::test_combine_dicts_different[test_mda5]/usr/lib/python3/dist-packages/satpy/dataset/metadata.py:198: FutureWarning: elementwise comparison failed; returning scalar instead, but in the future will perform elementwise comparison
res = comp_func(a, b) tests/test_dataset.py::TestIDQueryInteractions::test_seviri_hrv_has_priority_over_vis008/usr/lib/python3/dist-packages/satpy/tests/test_dataset.py:662: UserWarning: Attribute access to DataIDs is deprecated, use key access instead.
assert res[0].name == "HRV" tests/test_dependency_tree.py::TestMultipleSensors::test_compositor_loaded_sensor_order/usr/lib/python3/dist-packages/satpy/tests/test_dependency_tree.py:223: UserWarning: Attribute access to DataIDs is deprecated, use key access instead.
self.assertEqual(comp_nodes[0].name.resolution, 500) tests/test_modifiers.py::TestPSPAtmosphericalCorrection::test_call tests/modifier_tests/test_crefl.py::TestReflectanceCorrectorModifier::test_reflectance_corrector_abi tests/modifier_tests/test_crefl.py::TestReflectanceCorrectorModifier::test_reflectance_corrector_abi/usr/lib/python3/dist-packages/dask/core.py:121: RuntimeWarning: invalid value encountered in remainder
return func(*(_execute_task(a, cache) for a in args)) tests/test_readers.py::TestReaderLoader::test_missing_requirements/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:495: UserWarning: No handler for reading requirement 'HRIT_EPI' for H-000-MSG4__-MSG4________-IR_108___-000006___-201809050900-__
warnings.warn(msg) tests/test_readers.py::TestReaderLoader::test_missing_requirements/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:495: UserWarning: No handler for reading requirement 'HRIT_PRO' for H-000-MSG4__-MSG4________-IR_108___-000006___-201809050900-__
warnings.warn(msg) tests/test_readers.py::TestReaderLoader::test_missing_requirements/usr/lib/python3/dist-packages/satpy/readers/yaml_reader.py:498: UserWarning: No matching requirement file of type HRIT_PRO for H-000-MSG4__-MSG4________-IR_108___-000006___-201809051000-__
warnings.warn(str(err) + ' for {}'.format(filename)) tests/test_resample.py::TestHLResample::test_type_preserve tests/test_resample.py::TestHLResample::test_type_preserve/usr/lib/python3/dist-packages/pyresample/geometry.py:567: DeprecationWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1
xyz = np.stack(transform(src, dst, lons, lats, alt), axis=1) tests/test_resample.py::TestKDTreeResampler::test_check_numpy_cache/usr/lib/python3/dist-packages/satpy/resample.py:551: UserWarning: Using Numpy files as resampling cache is deprecated.
warnings.warn("Using Numpy files as resampling cache is " tests/test_resample.py::TestBucketAvg::test_compute_and_not_use_skipna_handling tests/test_resample.py::TestBucketAvg::test_compute_and_not_use_skipna_handling tests/test_resample.py::TestBucketSum::test_compute_and_not_use_skipna_handling tests/test_resample.py::TestBucketSum::test_compute_and_not_use_skipna_handling/usr/lib/python3/dist-packages/satpy/resample.py:1072: DeprecationWarning: Argument mask_all_nan is deprecated.Please update Pyresample and use skipna for missing values handling.
warnings.warn('Argument mask_all_nan is deprecated.' tests/test_resample.py::TestBucketAvg::test_compute_and_use_skipna_handling tests/test_resample.py::TestBucketSum::test_compute_and_use_skipna_handling/usr/lib/python3/dist-packages/satpy/resample.py:1067: DeprecationWarning: Argument mask_all_nan is deprecated. Please use skipna for missing values handling. Continuing with default skipna=True, if not provided differently. warnings.warn('Argument mask_all_nan is deprecated. Please use skipna for missing values handling. '
tests/test_scene.py: 2 warnings tests/test_writers.py: 14 warnings tests/writer_tests/test_geotiff.py: 4 warnings/usr/lib/python3/dist-packages/rasterio/__init__.py:230: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix be returned.
s = writer(path, mode, driver=driver, tests/test_scene.py: 3 warnings tests/test_writers.py: 10 warnings tests/reader_tests/test_aapp_l1b.py: 3 warnings tests/writer_tests/test_geotiff.py: 2 warnings tests/writer_tests/test_simple_image.py: 2 warnings/usr/lib/python3/dist-packages/dask/core.py:121: RuntimeWarning: divide by zero encountered in true_divide
return func(*(_execute_task(a, cache) for a in args)) tests/test_scene.py: 3 warnings tests/test_writers.py: 10 warnings tests/writer_tests/test_geotiff.py: 2 warnings tests/writer_tests/test_simple_image.py: 2 warnings/usr/lib/python3/dist-packages/dask/core.py:121: RuntimeWarning: invalid value encountered in multiply
return func(*(_execute_task(a, cache) for a in args)) tests/enhancement_tests/test_enhancements.py::TestEnhancementStretch::test_crefl_scaling/usr/lib/python3/dist-packages/satpy/enhancements/__init__.py:114: DeprecationWarning: 'crefl_scaling' is deprecated, use 'piecewise_linear_stretch' instead. warnings.warn("'crefl_scaling' is deprecated, use 'piecewise_linear_stretch' instead.", DeprecationWarning)
tests/enhancement_tests/test_enhancements.py::TestColormapLoading::test_cmap_from_file_rgb_1 tests/enhancement_tests/test_enhancements.py::TestColormapLoading::test_cmap_list/usr/lib/python3/dist-packages/trollimage/colormap.py:207: UserWarning: Colormap 'colors' should be flotaing point numbers between 0 and 1. warnings.warn("Colormap 'colors' should be flotaing point numbers between 0 and 1.")
tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read tests/reader_tests/test_aapp_l1b.py::TestAAPPL1BAllChannelsPresent::test_read/usr/lib/python3/dist-packages/dask/core.py:121: RuntimeWarning: invalid value encountered in log
return func(*(_execute_task(a, cache) for a in args)) tests/reader_tests/test_abi_l2_nc.py::TestMCMIPReading::test_mcmip_get_dataset/usr/lib/python3/dist-packages/satpy/readers/abi_l2_nc.py:40: UserWarning: Attribute access to DataIDs is deprecated, use key access instead.
var += "_" + key.name tests/reader_tests/test_ahi_hsd.py::TestAHIHSDFileHandler::test_read_band tests/reader_tests/test_ahi_hsd.py::TestAHIHSDFileHandler::test_read_band tests/reader_tests/test_ahi_hsd.py::TestAHIHSDFileHandler::test_scene_loading tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius tests/reader_tests/test_utils.py::TestHelpers::test_get_earth_radius/usr/lib/python3/dist-packages/satpy/readers/utils.py:320: DeprecationWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1
x, y, z = pyproj.transform(latlong, geocent, lon, lat, 0.) tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDF::test_get_dataset tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDF::test_get_dataset_counts tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDF::test_get_dataset_vis tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDFIRCal::test_default_calibrate tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDFIRCal::test_gsics_radiance_corr tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDFIRCal::test_infile_calibrate tests/reader_tests/test_ami_l1b.py::TestAMIL1bNetCDFIRCal::test_user_radiance_corr/usr/lib/python3/dist-packages/satpy/readers/ami_l1b.py:165: DeprecationWarning: This function is deprecated. See: https://pyproj4.github.io/pyproj/stable/gotchas.html#upgrading-to-pyproj-2-from-pyproj-1
sc_position = pyproj.transform( tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTGetCalibratedReflectances::test_calibrated_reflectances_values tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTGetCalibratedBT::test_calibrated_bt_values tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTChannel3::test_channel_3a_masking tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTChannel3::test_channel_3b_masking tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTNavigation::test_latitudes_are_returned tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTNavigation::test_longitudes_are_returned/usr/lib/python3/dist-packages/satpy/readers/hrpt.py:80: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future
return (np.datetime64( tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTGetCalibratedReflectances::test_calibrated_reflectances_values tests/reader_tests/test_avhrr_l0_hrpt.py::TestHRPTChannel3::test_channel_3a_masking/usr/lib/python3/dist-packages/satpy/readers/hrpt.py:222: DeprecationWarning: parsing timezone aware datetimes is deprecated; this will raise an error in the future
- np.datetime64(str(self.year) + '-01-01T00:00:00Z')) tests/reader_tests/test_fci_l2_nc.py::TestFciL2NCReadingByteData::test_byte_extraction/usr/lib/python3/dist-packages/pyresample/geometry.py:1282: RuntimeWarning: invalid value encountered in double_scalars
self.pixel_offset_x = -self.area_extent[0] / self.pixel_size_x tests/reader_tests/test_fci_l2_nc.py::TestFciL2NCReadingByteData::test_byte_extraction/usr/lib/python3/dist-packages/pyresample/geometry.py:1283: RuntimeWarning: invalid value encountered in double_scalars
self.pixel_offset_y = self.area_extent[3] / self.pixel_size_y tests/reader_tests/test_generic_image.py: 7 warnings tests/reader_tests/test_smos_l2_wind.py: 2 warnings tests/writer_tests/test_mitiff.py: 5 warnings/usr/lib/python3/dist-packages/pyproj/crs/crs.py:131: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6
in_crs_string = _prepare_from_proj_string(in_crs_string) tests/reader_tests/test_generic_image.py::TestGenericImage::test_png_scene tests/reader_tests/test_generic_image.py::TestGenericImage::test_png_scene/usr/lib/python3/dist-packages/rasterio/__init__.py:220: NotGeoreferencedWarning: Dataset has no geotransform, gcps, or rpcs. The identity matrix be returned.
s = DatasetReader(path, driver=driver, sharing=sharing, **kwargs) tests/reader_tests/test_goes_imager_nc.py: 28 warnings/usr/lib/python3/dist-packages/satpy/readers/goes_imager_nc.py:738: DeprecationWarning: an integer is required (got type DataArray). Implicit conversion to integers using __int__ is deprecated, and may be removed in a future version of Python.
return datetime(year=dt.year, month=dt.month, day=dt.day, tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_angles tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_angles tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_angles tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_angles tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_meteo tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_meteo tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_meteo tests/reader_tests/test_olci_nc.py::TestOLCIReader::test_olci_meteo/usr/lib/python3/dist-packages/geotiepoints/interpolator.py:239: DeprecationWarning: elementwise comparison failed; this will raise an error in the future.
if np.all(self.hrow_indices == self.row_indices): tests/reader_tests/test_satpy_cf_nc.py: 8 warnings tests/writer_tests/test_cf.py: 19 warnings/usr/lib/python3/dist-packages/satpy/writers/cf_writer.py:754: FutureWarning: The default behaviour of the CF writer will soon change to not compress data by default. warnings.warn("The default behaviour of the CF writer will soon change to not compress data by default.",
tests/reader_tests/test_satpy_cf_nc.py: 18 warnings/usr/lib/python3/dist-packages/satpy/readers/satpy_cf_nc.py:240: DeprecationWarning: The truth value of an empty array is ambiguous. Returning False, but in future this will result in an error. Use `array.size > 0` to check that an array is not empty.
if 'modifiers' in ds_info and not ds_info['modifiers']: tests/reader_tests/test_satpy_cf_nc.py::TestCFReader::test_read_prefixed_channels_by_user_no_prefix tests/writer_tests/test_cf.py::TestCFWriter::test_save_dataset_a_digit_no_prefix_include_attr/usr/lib/python3/dist-packages/satpy/writers/cf_writer.py:566: UserWarning: Invalid NetCDF dataset name: 1 starts with a digit. warnings.warn('Invalid NetCDF dataset name: {} starts with a digit.'.format(name))
tests/reader_tests/test_seviri_base.py::TestOrbitPolynomialFinder::test_get_orbit_polynomial[orbit_polynomials1-time1-orbit_polynomial_exp1] tests/reader_tests/test_seviri_base.py::TestOrbitPolynomialFinder::test_get_orbit_polynomial_exceptions[orbit_polynomials1-time1]/usr/lib/python3/dist-packages/satpy/readers/seviri_base.py:770: UserWarning: No orbit polynomial valid for 2006-01-01T12:15:00.000000. Using closest match.
warnings.warn( tests/reader_tests/test_seviri_base.py::TestOrbitPolynomialFinder::test_get_orbit_polynomial_exceptions[orbit_polynomials0-time0]/usr/lib/python3/dist-packages/satpy/readers/seviri_base.py:770: UserWarning: No orbit polynomial valid for 2006-01-02T12:15:00.000000. Using closest match.
warnings.warn( tests/reader_tests/test_seviri_l1b_hrit.py::TestHRITMSGFileHandler::test_satpos_no_valid_orbit_polynomial tests/reader_tests/test_seviri_l1b_native.py::TestNativeMSGDataset::test_satpos_no_valid_orbit_polynomial/usr/lib/python3/dist-packages/satpy/readers/seviri_base.py:770: UserWarning: No orbit polynomial valid for 2006-01-01T12:15:09.304888. Using closest match.
warnings.warn( tests/reader_tests/test_seviri_l1b_nc.py::TestNCSEVIRIFileHandler::test_satpos_no_valid_orbit_polynomial/usr/lib/python3/dist-packages/satpy/readers/seviri_base.py:770: UserWarning: No orbit polynomial valid for 2020-01-01T00:00:00.000000. Using closest match.
warnings.warn( tests/reader_tests/test_slstr_l1b.py::TestSLSTRReader::test_instantiate/usr/lib/python3/dist-packages/satpy/readers/slstr_l1b.py:174: UserWarning: Warning: No radiance adjustment supplied for channel foo_nadir
warnings.warn("Warning: No radiance adjustment supplied " + tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_no_valid_data tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_no_valid_data/usr/lib/python3/dist-packages/dask/utils.py:35: RuntimeWarning: All-NaN slice encountered
return func(*args, **kwargs) tests/writer_tests/test_awips_tiled.py: 54 warnings/usr/lib/python3/dist-packages/satpy/writers/awips_tiled.py:940: UserWarning: Production location attribute is longer than 31 characters (AWIPS limit). Set it to a smaller value with the 'ORGANIZATION' environment variable. Defaults to hostname and is currently set to '11111111111111111111111111111111111111111111111111'.
warnings.warn("Production location attribute is longer than 31 " tests/writer_tests/test_cf.py::TestCFWriter::test_groups/usr/lib/python3/dist-packages/satpy/writers/cf_writer.py:361: UserWarning: Cannot pretty-format "acq_time" coordinates because they are not unique among the given datasets warnings.warn('Cannot pretty-format "{}" coordinates because they are not unique among the '
tests/writer_tests/test_cf.py::TestCFWriter::test_link_coords/usr/lib/python3/dist-packages/satpy/writers/cf_writer.py:305: UserWarning: Coordinate "not_exist" referenced by dataarray var4 does not exist, dropping reference. warnings.warn('Coordinate "{}" referenced by dataarray {} does not exist, dropping reference.'
tests/writer_tests/test_cf.py::TestCFWriter::test_save_with_compression/usr/lib/python3/dist-packages/satpy/writers/cf_writer.py:759: FutureWarning: The `compression` keyword will soon be deprecated. Please use the `encoding` of the DataArrays to tune compression from now on. warnings.warn("The `compression` keyword will soon be deprecated. Please use the `encoding` of the "
-- Docs: https://docs.pytest.org/en/stable/warnings.html=========================== short test summary info ============================ FAILED tests/test_scene.py::TestScene::test_crop - numpy.core._exceptions._Ar... FAILED tests/test_scene.py::TestScene::test_crop_epsg_crs - numpy.core._excep... FAILED tests/test_scene.py::TestScene::test_crop_rgb - numpy.core._exceptions... FAILED tests/test_scene.py::TestSceneAggregation::test_aggregate - numpy.core... FAILED tests/test_scene.py::TestSceneAggregation::test_aggregate_with_boundary FAILED tests/reader_tests/test_mimic_TPW2_nc.py::TestMimicTPW2Reader::test_load_mimic FAILED tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_longitude_latitude[modis_l2_nasa_mod35_file-True-False-False-1000] FAILED tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_250m_cloud_mask_dataset[modis_l2_nasa_mod35_file-False]
FAILED tests/reader_tests/test_nwcsaf_msg.py::TestH5NWCSAF::test_get_datasetFAILED tests/reader_tests/test_smos_l2_wind.py::TestSMOSL2WINDReader::test_load_wind_speed FAILED tests/reader_tests/test_tropomi_l2.py::TestTROPOMIL2Reader::test_load_bounds FAILED tests/reader_tests/test_tropomi_l2.py::TestTROPOMIL2Reader::test_load_no2 FAILED tests/reader_tests/test_tropomi_l2.py::TestTROPOMIL2Reader::test_load_so2 FAILED tests/reader_tests/test_viirs_compact.py::TestCompact::test_distributed FAILED tests/reader_tests/test_viirs_compact.py::TestCompact::test_get_dataset FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_basic_lettered_tiles FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_basic_lettered_tiles_diff_projection FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_update_existing FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_sector_ref FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_no_fit FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_no_valid_data FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_lettered_tiles_bad_filename FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs0-C] FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs0-F] FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs1-C] FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs1-F] FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs2-C] FAILED tests/writer_tests/test_awips_tiled.py::TestAWIPSTiledWriter::test_multivar_numbered_tiles_glm[extra_kwargs2-F] FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_get_test_dataset_three_bands_prereq FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_save_dataset_with_bad_value FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_save_dataset_with_calibration FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_save_one_dataset FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_save_one_dataset_sesnor_set FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_simple_write FAILED tests/writer_tests/test_mitiff.py::TestMITIFFWriter::test_simple_write_two_bands
FAILED tests/writer_tests/test_ninjogeotiff.py::test_write_and_read_file_RGB FAILED tests/writer_tests/test_ninjogeotiff.py::test_get_min_gray_value_RGB FAILED tests/writer_tests/test_ninjogeotiff.py::test_get_max_gray_value_RGBERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_scene_available_datasets[modis_l1b_nasa_mod021km_file-expected_names0-expected_data_res0-expected_geo_res0] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_scene_available_datasets[modis_l1b_imapp_1000m_file-expected_names1-expected_data_res1-expected_geo_res1] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_scene_available_datasets[modis_l1b_nasa_mod02hkm_file-expected_names2-expected_data_res2-expected_geo_res2] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_scene_available_datasets[modis_l1b_nasa_mod02qkm_file-expected_names3-expected_data_res3-expected_geo_res3] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_longitude_latitude[modis_l1b_nasa_mod021km_file-True-False-False-1000] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_longitude_latitude[modis_l1b_imapp_1000m_file-True-False-False-1000] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_longitude_latitude[modis_l1b_nasa_mod02hkm_file-False-True-True-250] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_longitude_latitude[modis_l1b_nasa_mod02qkm_file-False-True-True-250] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_longitude_latitude[modis_l1b_nasa_1km_mod03_files-True-True-True-250] ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_sat_zenith_angle ERROR tests/reader_tests/test_modis_l1b.py::TestModisL1b::test_load_vis - num... ERROR tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_category_dataset[modis_l2_nasa_mod35_mod03_files-loadables0-1000-1000-True] ERROR tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_category_dataset[modis_l2_imapp_mask_byte1_geo_files-loadables1-None-1000-True] ERROR tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_250m_cloud_mask_dataset[modis_l2_nasa_mod35_mod03_files-True] ERROR tests/reader_tests/test_modis_l2.py::TestModisL2::test_load_l2_dataset[modis_l2_imapp_snowmask_geo_files-loadables2-1000-True] = 38 failed, 1289 passed, 10 skipped, 5 deselected, 4 xfailed, 566 warnings, 15 errors in 226.63s (0:03:46) =
autopkgtest [11:33:26]: test python3
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