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# Licensed under a 3-clause BSD style license - see LICENSE.rst
# This module contains tests of a class equivalent to pre-1.0 NDData.
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from ...tests.helper import pytest
from ..nddata import NDData
from ..compat import NDDataArray
from ..nduncertainty import StdDevUncertainty
from ... import units as u
NDDATA_ATTRIBUTES = ['mask', 'flags', 'uncertainty', 'unit', 'shape', 'size',
'dtype', 'ndim', 'wcs', 'convert_unit_to']
def test_nddataarray_has_attributes_of_old_nddata():
ndd = NDDataArray([1, 2, 3])
for attr in NDDATA_ATTRIBUTES:
assert hasattr(ndd, attr)
def test_nddata_simple():
nd = NDDataArray(np.zeros((10, 10)))
assert nd.shape == (10, 10)
assert nd.size == 100
assert nd.dtype == np.dtype(float)
def test_nddata_parameters():
# Test for issue 4620
nd = NDDataArray(data=np.zeros((10, 10)))
assert nd.shape == (10, 10)
assert nd.size == 100
assert nd.dtype == np.dtype(float)
# Change order; `data` has to be given explicitly here
nd = NDDataArray(meta={}, data=np.zeros((10, 10)))
assert nd.shape == (10, 10)
assert nd.size == 100
assert nd.dtype == np.dtype(float)
# Pass uncertainty as second implicit argument
data = np.zeros((10, 10))
uncertainty = StdDevUncertainty(0.1 + np.zeros_like(data))
nd = NDDataArray(data, uncertainty)
assert nd.shape == (10, 10)
assert nd.size == 100
assert nd.dtype == np.dtype(float)
assert nd.uncertainty == uncertainty
def test_nddata_conversion():
nd = NDDataArray(np.array([[1, 2, 3], [4, 5, 6]]))
assert nd.size == 6
assert nd.dtype == np.dtype(int)
@pytest.mark.parametrize('flags_in', [
np.array([True, False]),
np.array([1, 0]),
[True, False],
[1, 0],
np.array(['a', 'b']),
['a', 'b']])
def test_nddata_flags_init_without_np_array(flags_in):
ndd = NDDataArray([1, 1], flags=flags_in)
assert (ndd.flags == flags_in).all()
@pytest.mark.parametrize(('shape'), [(10,), (5, 5), (3, 10, 10)])
def test_nddata_flags_invalid_shape(shape):
with pytest.raises(ValueError) as exc:
NDDataArray(np.zeros((10, 10)), flags=np.ones(shape))
assert exc.value.args[0] == 'dimensions of flags do not match data'
def test_convert_unit_to():
# convert_unit_to should return a copy of its input
d = NDDataArray(np.ones((5, 5)))
d.unit = 'km'
d.uncertainty = StdDevUncertainty(0.1 + np.zeros_like(d))
# workaround because zeros_like does not support dtype arg until v1.6
# and NDData accepts only bool ndarray as mask
tmp = np.zeros_like(d.data)
d.mask = np.array(tmp, dtype=np.bool)
d1 = d.convert_unit_to('m')
assert np.all(d1.data == np.array(1000.0))
assert np.all(d1.uncertainty.array == 1000.0 * d.uncertainty.array)
assert d1.unit == u.m
# changing the output mask should not change the original
d1.mask[0, 0] = True
assert d.mask[0, 0] != d1.mask[0, 0]
d.flags = np.zeros_like(d.data)
d1 = d.convert_unit_to('m')
# check that subclasses can require wcs and/or unit to be present and use
# _arithmetic and convert_unit_to
class SubNDData(NDDataArray):
"""
Subclass for test initialization of subclasses in NDData._arithmetic and
NDData.convert_unit_to
"""
def __init__(self, *arg, **kwd):
super(SubNDData, self).__init__(*arg, **kwd)
if self.unit is None:
raise ValueError("Unit for subclass must be specified")
if self.wcs is None:
raise ValueError("WCS for subclass must be specified")
def test_init_of_subclass_in_convert_unit_to():
data = np.ones([10, 10])
arr1 = SubNDData(data, unit='m', wcs=5)
result = arr1.convert_unit_to('km')
np.testing.assert_array_equal(arr1.data, 1000 * result.data)
# Test for issue #4129:
def test_nddataarray_from_nddataarray():
ndd1 = NDDataArray([1., 4., 9.],
uncertainty=StdDevUncertainty([1., 2., 3.]),
flags=[0, 1, 0])
ndd2 = NDDataArray(ndd1)
# Test that the 2 instances point to the same objects and aren't just
# equal; this is explicitly documented for the main data array and we
# probably want to catch any future change in behaviour for the other
# attributes too and ensure they are intentional.
assert ndd2.data is ndd1.data
assert ndd2.uncertainty is ndd1.uncertainty
assert ndd2.flags is ndd1.flags
assert ndd2.meta == ndd1.meta
# Test for issue #4137:
def test_nddataarray_from_nddata():
ndd1 = NDData([1., 4., 9.],
uncertainty=StdDevUncertainty([1., 2., 3.]))
ndd2 = NDDataArray(ndd1)
assert ndd2.data is ndd1.data
assert ndd2.uncertainty is ndd1.uncertainty
assert ndd2.meta == ndd1.meta
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