def test_Y_values(self):
X, Y = self.X, self.Y
Y[0, 0] = -1
with npt.assert_raises(ValueError):
CCA(Y, X, None, None)
Y[0] = 0
with npt.assert_raises(ValueError):
CCA(Y, X, None, None)
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path('example3_Y'))
X = np.loadtxt(get_data_path('example3_X'))
self.ordination = CCA(Y, X[:, :-1],
['Site0', 'Site1', 'Site2', 'Site3', 'Site4',
'Site5', 'Site6', 'Site7', 'Site8', 'Site9'],
['Species0', 'Species1', 'Species2', 'Species3',
'Species4', 'Species5', 'Species6', 'Species7',
'Species8'])
class TestCCAResults(object):
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path("example3_Y"))
X = np.loadtxt(get_data_path("example3_X"))
self.ordination = CCA(
Y,
X[:, :-1],
["Site0", "Site1", "Site2", "Site3", "Site4", "Site5", "Site6", "Site7", "Site8", "Site9"],
[
"Species0",
"Species1",
"Species2",
"Species3",
"Species4",
"Species5",
"Species6",
"Species7",
"Species8",
],
)
def test_scaling1_species(self):
scores = self.ordination.scores(1)
vegan_species = np.loadtxt(get_data_path("example3_species_scaling1_from_vegan"))
npt.assert_almost_equal(scores.species, vegan_species, decimal=6)
def test_scaling1_site(self):
scores = self.ordination.scores(1)
vegan_site = np.loadtxt(get_data_path("example3_site_scaling1_from_vegan"))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
def test_scaling2_species(self):
scores = self.ordination.scores(2)
vegan_species = np.loadtxt(get_data_path("example3_species_scaling2_from_vegan"))
npt.assert_almost_equal(scores.species, vegan_species, decimal=5)
def test_scaling2_site(self):
scores = self.ordination.scores(2)
vegan_site = np.loadtxt(get_data_path("example3_site_scaling2_from_vegan"))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
class TestCCAResults(object):
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path('example3_Y'))
X = np.loadtxt(get_data_path('example3_X'))
self.ordination = CCA(Y, X[:, :-1], [
'Site0', 'Site1', 'Site2', 'Site3', 'Site4', 'Site5', 'Site6',
'Site7', 'Site8', 'Site9'
], [
'Species0', 'Species1', 'Species2', 'Species3', 'Species4',
'Species5', 'Species6', 'Species7', 'Species8'
])
def test_scaling1_species(self):
scores = self.ordination.scores(1)
vegan_species = np.loadtxt(
get_data_path('example3_species_scaling1_from_vegan'))
npt.assert_almost_equal(scores.species, vegan_species, decimal=6)
def test_scaling1_site(self):
scores = self.ordination.scores(1)
vegan_site = np.loadtxt(
get_data_path('example3_site_scaling1_from_vegan'))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
def test_scaling2_species(self):
scores = self.ordination.scores(2)
vegan_species = np.loadtxt(
get_data_path('example3_species_scaling2_from_vegan'))
npt.assert_almost_equal(scores.species, vegan_species, decimal=5)
def test_scaling2_site(self):
scores = self.ordination.scores(2)
vegan_site = np.loadtxt(
get_data_path('example3_site_scaling2_from_vegan'))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
class TestCCAResults(object):
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path('example3_Y'))
X = np.loadtxt(get_data_path('example3_X'))
self.ordination = CCA(Y, X[:, :-1],
['Site0', 'Site1', 'Site2', 'Site3', 'Site4',
'Site5', 'Site6', 'Site7', 'Site8', 'Site9'],
['Species0', 'Species1', 'Species2', 'Species3',
'Species4', 'Species5', 'Species6', 'Species7',
'Species8'])
def test_scaling1_species(self):
scores = self.ordination.scores(1)
vegan_species = np.loadtxt(get_data_path(
'example3_species_scaling1_from_vegan'))
npt.assert_almost_equal(scores.species, vegan_species, decimal=6)
def test_scaling1_site(self):
scores = self.ordination.scores(1)
vegan_site = np.loadtxt(get_data_path(
'example3_site_scaling1_from_vegan'))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
def test_scaling2_species(self):
scores = self.ordination.scores(2)
vegan_species = np.loadtxt(get_data_path(
'example3_species_scaling2_from_vegan'))
npt.assert_almost_equal(scores.species, vegan_species, decimal=5)
def test_scaling2_site(self):
scores = self.ordination.scores(2)
vegan_site = np.loadtxt(get_data_path(
'example3_site_scaling2_from_vegan'))
npt.assert_almost_equal(scores.site, vegan_site, decimal=4)
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path('example3_Y'))
X = np.loadtxt(get_data_path('example3_X'))
self.ordination = CCA(Y, X[:, :-1],
['Site0', 'Site1', 'Site2', 'Site3', 'Site4',
'Site5', 'Site6', 'Site7', 'Site8', 'Site9'],
['Species0', 'Species1', 'Species2', 'Species3',
'Species4', 'Species5', 'Species6', 'Species7',
'Species8'])
def setup(self):
"""Data from table 11.3 in Legendre & Legendre 1998
(p. 590). Loaded results as computed with vegan 2.0-8 and
compared with table 11.5 if also there."""
Y = np.loadtxt(get_data_path("example3_Y"))
X = np.loadtxt(get_data_path("example3_X"))
self.ordination = CCA(
Y,
X[:, :-1],
["Site0", "Site1", "Site2", "Site3", "Site4", "Site5", "Site6", "Site7", "Site8", "Site9"],
[
"Species0",
"Species1",
"Species2",
"Species3",
"Species4",
"Species5",
"Species6",
"Species7",
"Species8",
],
)
def test_shape(self):
X, Y = self.X, self.Y
with npt.assert_raises(ValueError):
CCA(Y, X[:-1], None, None)
