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# 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 $
"""
__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
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.failUnless(isinstance(xmsub, MaskedArray))
assert_equal(xmsub._data, xsub)
self.failUnless(isinstance(xmsub._data, SubArray))
def test_maskedarray_subclassing(self):
"Tests subclassing MaskedArray"
(x, mx) = self.data
self.failUnless(isinstance(mx._data, np.matrix))
def test_masked_unary_operations(self):
"Tests masked_unary_operation"
(x, mx) = self.data
self.failUnless(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.failUnless(isinstance(add(mx,mx), mmatrix))
self.failUnless(isinstance(add(mx,x), mmatrix))
# Result should work
assert_equal(add(mx,x), mx+x)
self.failUnless(isinstance(add(mx,mx)._data, np.matrix))
self.failUnless(isinstance(add.outer(mx,mx), mmatrix))
self.failUnless(isinstance(hypot(mx,mx), mmatrix))
self.failUnless(isinstance(hypot(mx,x), mmatrix))
def test_masked_binary_operations(self):
"Tests domained_masked_binary_operation"
(x, mx) = self.data
xmx = masked_array(mx.data.__array__(), mask=mx.mask)
self.failUnless(isinstance(divide(mx,mx), mmatrix))
self.failUnless(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.failUnless(isinstance(z,MaskedArray))
self.failUnless(not isinstance(z, MSubArray))
self.failUnless(isinstance(z._data, SubArray))
assert_equal(z._data.info, {})
#
z = (ym+1)
self.failUnless(isinstance(z, MaskedArray))
self.failUnless(isinstance(z, MSubArray))
self.failUnless(isinstance(z._data, SubArray))
self.failUnless(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.failUnless(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.failUnless(not isinstance(mxsub, MSubArray))
self.failUnless(isinstance(mxsub, MaskedArray))
assert_equal(mxsub._mask, m)
#
mxsub = asarray(xsub)
self.failUnless(not isinstance(mxsub, MSubArray))
self.failUnless(isinstance(mxsub, MaskedArray))
assert_equal(mxsub._mask, m)
#
mxsub = masked_array(xsub, subok=True)
self.failUnless(isinstance(mxsub, MSubArray))
assert_equal(mxsub.info, xsub.info)
assert_equal(mxsub._mask, xsub._mask)
#
mxsub = asanyarray(xsub)
self.failUnless(isinstance(mxsub, MSubArray))
assert_equal(mxsub.info, xsub.info)
assert_equal(mxsub._mask, m)
################################################################################
if __name__ == '__main__':
run_module_suite()
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