annotate DEPENDENCIES/mingw32/Python27/Lib/site-packages/numpy/ma/tests/test_subclassing.py @ 133:4acb5d8d80b6 tip

Don't fail environmental check if README.md exists (but .txt and no-suffix don't)

# pylint: disable-msg=W0611, W0612, W0511,R0201
"""Tests suite for MaskedArray & subclassing.

:author: Pierre Gerard-Marchant
:contact: pierregm_at_uga_dot_edu
:version: $Id: test_subclassing.py 3473 2007-10-29 15:18:13Z jarrod.millman $

"""
from __future__ import division, absolute_import, print_function

__author__ = "Pierre GF Gerard-Marchant ($Author: jarrod.millman $)"
__version__ = '1.0'
__revision__ = "$Revision: 3473 $"
__date__ = '$Date: 2007-10-29 17:18:13 +0200 (Mon, 29 Oct 2007) $'

import numpy as np
from numpy.testing import *
from numpy.ma.testutils import *
from numpy.ma.core import *


class SubArray(np.ndarray):
    # Defines a generic np.ndarray subclass, that stores some metadata
    # in the  dictionary `info`.
    def __new__(cls,arr,info={}):
        x = np.asanyarray(arr).view(cls)
        x.info = info
        return x

    def __array_finalize__(self, obj):
        self.info = getattr(obj, 'info', {})
        return

    def __add__(self, other):
        result = np.ndarray.__add__(self, other)
        result.info.update({'added':result.info.pop('added', 0)+1})
        return result

subarray = SubArray


class MSubArray(SubArray, MaskedArray):

    def __new__(cls, data, info={}, mask=nomask):
        subarr = SubArray(data, info)
        _data = MaskedArray.__new__(cls, data=subarr, mask=mask)
        _data.info = subarr.info
        return _data

    def __array_finalize__(self, obj):
        MaskedArray.__array_finalize__(self, obj)
        SubArray.__array_finalize__(self, obj)
        return

    def _get_series(self):
        _view = self.view(MaskedArray)
        _view._sharedmask = False
        return _view
    _series = property(fget=_get_series)

msubarray = MSubArray


class MMatrix(MaskedArray, np.matrix,):

    def __new__(cls, data, mask=nomask):
        mat = np.matrix(data)
        _data = MaskedArray.__new__(cls, data=mat, mask=mask)
        return _data

    def __array_finalize__(self, obj):
        np.matrix.__array_finalize__(self, obj)
        MaskedArray.__array_finalize__(self, obj)
        return

    def _get_series(self):
        _view = self.view(MaskedArray)
        _view._sharedmask = False
        return _view
    _series = property(fget=_get_series)

mmatrix = MMatrix


# also a subclass that overrides __str__, __repr__ and __setitem__, disallowing
# setting to non-class values (and thus np.ma.core.masked_print_option)
class ComplicatedSubArray(SubArray):
    def __str__(self):
        return 'myprefix {0} mypostfix'.format(
            super(ComplicatedSubArray, self).__str__())

    def __repr__(self):
        # Return a repr that does not start with 'name('
        return '<{0} {1}>'.format(self.__class__.__name__, self)

    def __setitem__(self, item, value):
        # this ensures direct assignment to masked_print_option will fail
        if not isinstance(value, ComplicatedSubArray):
            raise ValueError("Can only set to MySubArray values")
        super(ComplicatedSubArray, self).__setitem__(item, value)


class TestSubclassing(TestCase):
    # Test suite for masked subclasses of ndarray.

    def setUp(self):
        x = np.arange(5)
        mx = mmatrix(x, mask=[0, 1, 0, 0, 0])
        self.data = (x, mx)

    def test_data_subclassing(self):
        # Tests whether the subclass is kept.
        x = np.arange(5)
        m = [0, 0, 1, 0, 0]
        xsub = SubArray(x)
        xmsub = masked_array(xsub, mask=m)
        self.assertTrue(isinstance(xmsub, MaskedArray))
        assert_equal(xmsub._data, xsub)
        self.assertTrue(isinstance(xmsub._data, SubArray))

    def test_maskedarray_subclassing(self):
        # Tests subclassing MaskedArray
        (x, mx) = self.data
        self.assertTrue(isinstance(mx._data, np.matrix))

    def test_masked_unary_operations(self):
        # Tests masked_unary_operation
        (x, mx) = self.data
        with np.errstate(divide='ignore'):
            self.assertTrue(isinstance(log(mx), mmatrix))
            assert_equal(log(x), np.log(x))

    def test_masked_binary_operations(self):
        # Tests masked_binary_operation
        (x, mx) = self.data
        # Result should be a mmatrix
        self.assertTrue(isinstance(add(mx, mx), mmatrix))
        self.assertTrue(isinstance(add(mx, x), mmatrix))
        # Result should work
        assert_equal(add(mx, x), mx+x)
        self.assertTrue(isinstance(add(mx, mx)._data, np.matrix))
        self.assertTrue(isinstance(add.outer(mx, mx), mmatrix))
        self.assertTrue(isinstance(hypot(mx, mx), mmatrix))
        self.assertTrue(isinstance(hypot(mx, x), mmatrix))

    def test_masked_binary_operations2(self):
        # Tests domained_masked_binary_operation
        (x, mx) = self.data
        xmx = masked_array(mx.data.__array__(), mask=mx.mask)
        self.assertTrue(isinstance(divide(mx, mx), mmatrix))
        self.assertTrue(isinstance(divide(mx, x), mmatrix))
        assert_equal(divide(mx, mx), divide(xmx, xmx))

    def test_attributepropagation(self):
        x = array(arange(5), mask=[0]+[1]*4)
        my = masked_array(subarray(x))
        ym = msubarray(x)
        #
        z = (my+1)
        self.assertTrue(isinstance(z, MaskedArray))
        self.assertTrue(not isinstance(z, MSubArray))
        self.assertTrue(isinstance(z._data, SubArray))
        assert_equal(z._data.info, {})
        #
        z = (ym+1)
        self.assertTrue(isinstance(z, MaskedArray))
        self.assertTrue(isinstance(z, MSubArray))
        self.assertTrue(isinstance(z._data, SubArray))
        self.assertTrue(z._data.info['added'] > 0)
        #
        ym._set_mask([1, 0, 0, 0, 1])
        assert_equal(ym._mask, [1, 0, 0, 0, 1])
        ym._series._set_mask([0, 0, 0, 0, 1])
        assert_equal(ym._mask, [0, 0, 0, 0, 1])
        #
        xsub = subarray(x, info={'name':'x'})
        mxsub = masked_array(xsub)
        self.assertTrue(hasattr(mxsub, 'info'))
        assert_equal(mxsub.info, xsub.info)

    def test_subclasspreservation(self):
        # Checks that masked_array(...,subok=True) preserves the class.
        x = np.arange(5)
        m = [0, 0, 1, 0, 0]
        xinfo = [(i, j) for (i, j) in zip(x, m)]
        xsub = MSubArray(x, mask=m, info={'xsub':xinfo})
        #
        mxsub = masked_array(xsub, subok=False)
        self.assertTrue(not isinstance(mxsub, MSubArray))
        self.assertTrue(isinstance(mxsub, MaskedArray))
        assert_equal(mxsub._mask, m)
        #
        mxsub = asarray(xsub)
        self.assertTrue(not isinstance(mxsub, MSubArray))
        self.assertTrue(isinstance(mxsub, MaskedArray))
        assert_equal(mxsub._mask, m)
        #
        mxsub = masked_array(xsub, subok=True)
        self.assertTrue(isinstance(mxsub, MSubArray))
        assert_equal(mxsub.info, xsub.info)
        assert_equal(mxsub._mask, xsub._mask)
        #
        mxsub = asanyarray(xsub)
        self.assertTrue(isinstance(mxsub, MSubArray))
        assert_equal(mxsub.info, xsub.info)
        assert_equal(mxsub._mask, m)

    def test_subclass_repr(self):
        """test that repr uses the name of the subclass
        and 'array' for np.ndarray"""
        x = np.arange(5)
        mx = masked_array(x, mask=[True, False, True, False, False])
        self.assertTrue(repr(mx).startswith('masked_array'))
        xsub = SubArray(x)
        mxsub = masked_array(xsub, mask=[True, False, True, False, False])
        self.assertTrue(repr(mxsub).startswith(
            'masked_{0}(data = [-- 1 -- 3 4]'.format(SubArray.__name__)))

    def test_subclass_str(self):
        """test str with subclass that has overridden str, setitem"""
        # first without override
        x = np.arange(5)
        xsub = SubArray(x)
        mxsub = masked_array(xsub, mask=[True, False, True, False, False])
        self.assertTrue(str(mxsub) == '[-- 1 -- 3 4]')

        xcsub = ComplicatedSubArray(x)
        assert_raises(ValueError, xcsub.__setitem__, 0,
                      np.ma.core.masked_print_option)
        mxcsub = masked_array(xcsub, mask=[True, False, True, False, False])
        self.assertTrue(str(mxcsub) == 'myprefix [-- 1 -- 3 4] mypostfix')


###############################################################################
if __name__ == '__main__':
    run_module_suite()