def test_resolution_dense(self):
#- dense with no offsets specified
data = np.random.uniform(size=(10, 10))
R = Resolution(data)
Rdense = R.todense()
self.assertTrue(np.all(Rdense == data))
#- with offsets
offsets = np.arange(-2, 4)
R = Resolution(data, offsets)
Rdense = R.todense()
for i in offsets:
self.assertTrue(np.all(Rdense.diagonal(i) == data.diagonal(i)), \
"diagonal {} doesn't match".format(i))
#- dense without offsets but larger than default_ndiag
ndiag = desispec.resolution.default_ndiag + 5
data = np.random.uniform(size=(ndiag, ndiag))
Rdense = Resolution(data).todense()
for i in range(ndiag):
if i <= desispec.resolution.default_ndiag // 2:
self.assertTrue(np.all(Rdense.diagonal(i) == data.diagonal(i)), \
"diagonal {} doesn't match".format(i))
self.assertTrue(np.all(Rdense.diagonal(-i) == data.diagonal(-i)), \
"diagonal {} doesn't match".format(-i))
else:
self.assertTrue(np.all(Rdense.diagonal(i) == 0.0), \
"diagonal {} not 0s".format(i))
self.assertTrue(np.all(Rdense.diagonal(-i) == 0.0), \
"diagonal {} not 0s".format(-i))
def test_resolution_dense(self):
#- dense with no offsets specified
data = np.random.uniform(size=(10,10))
R = Resolution(data)
Rdense = R.todense()
self.assertTrue(np.all(Rdense == data))
#- with offsets
offsets = np.arange(-2,4)
R = Resolution(data, offsets)
Rdense = R.todense()
for i in offsets:
self.assertTrue(np.all(Rdense.diagonal(i) == data.diagonal(i)), \
"diagonal {} doesn't match".format(i))
#- dense without offsets but larger than default_ndiag
ndiag = desispec.resolution.default_ndiag + 5
data = np.random.uniform(size=(ndiag, ndiag))
Rdense = Resolution(data).todense()
for i in range(ndiag):
if i <= desispec.resolution.default_ndiag//2:
self.assertTrue(np.all(Rdense.diagonal(i) == data.diagonal(i)), \
"diagonal {} doesn't match".format(i))
self.assertTrue(np.all(Rdense.diagonal(-i) == data.diagonal(-i)), \
"diagonal {} doesn't match".format(-i))
else:
self.assertTrue(np.all(Rdense.diagonal(i) == 0.0), \
"diagonal {} not 0s".format(i))
self.assertTrue(np.all(Rdense.diagonal(-i) == 0.0), \
"diagonal {} not 0s".format(-i))
def test_resolution_sparsedia(self):
data = np.random.uniform(size=(5, 10))
offsets = np.arange(-2, 3)
#- Original case: symetric and odd number of diagonals
Rdia = scipy.sparse.dia_matrix((data, offsets), shape=(10, 10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Non symetric but still odd number of diagonals
Rdia = scipy.sparse.dia_matrix((data, offsets + 1), shape=(10, 10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Even number of diagonals
Rdia = scipy.sparse.dia_matrix((data[1:, :], offsets[1:]),
shape=(10, 10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Unordered diagonals
data = np.random.uniform(size=(5, 10))
offsets = [0, 1, -1, 2, -2]
Rdia = scipy.sparse.dia_matrix((data, offsets), shape=(10, 10))
R1 = Resolution(Rdia)
R2 = Resolution(data, offsets)
self.assertTrue(np.all(R1.diagonal() == Rdia.diagonal()))
self.assertTrue(np.all(R2.diagonal() == Rdia.diagonal()))
self.assertTrue(np.all(R1.data == R2.data))
def test_resolution_sparsedia(self):
data = np.random.uniform(size=(5,10))
offsets = np.arange(-2,3)
#- Original case: symetric and odd number of diagonals
Rdia = scipy.sparse.dia_matrix((data, offsets), shape=(10,10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Non symetric but still odd number of diagonals
Rdia = scipy.sparse.dia_matrix((data, offsets+1), shape=(10,10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Even number of diagonals
Rdia = scipy.sparse.dia_matrix((data[1:,:], offsets[1:]), shape=(10,10))
R = Resolution(Rdia)
self.assertTrue(np.all(R.diagonal() == Rdia.diagonal()))
#- Unordered diagonals
data = np.random.uniform(size=(5,10))
offsets = [0,1,-1,2,-2]
Rdia = scipy.sparse.dia_matrix((data, offsets), shape=(10,10))
R1 = Resolution(Rdia)
R2 = Resolution(data, offsets)
self.assertTrue(np.all(R1.diagonal() == Rdia.diagonal()))
self.assertTrue(np.all(R2.diagonal() == Rdia.diagonal()))
self.assertTrue(np.all(R1.data == R2.data))