class TestRDAResults(object): # STATUS: L&L only shows results with scaling 1, and they agree # with vegan's (module multiplying by a constant). I can also # compute scaling 2, agreeing with vegan, but there are no written # results in L&L. def setup(self): """Data from table 11.3 in Legendre & Legendre 1998.""" Y = np.loadtxt(get_data_path("example2_Y")) X = np.loadtxt(get_data_path("example2_X")) self.ordination = RDA( Y, X, ["Site0", "Site1", "Site2", "Site3", "Site4", "Site5", "Site6", "Site7", "Site8", "Site9"], ["Species0", "Species1", "Species2", "Species3", "Species4", "Species5"], ) def test_scaling1(self): scores = self.ordination.scores(1) # Load data as computed with vegan 2.0-8 vegan_species = np.loadtxt(get_data_path("example2_species_scaling1_from_vegan")) npt.assert_almost_equal(scores.species, vegan_species, decimal=6) vegan_site = np.loadtxt(get_data_path("example2_site_scaling1_from_vegan")) npt.assert_almost_equal(scores.site, vegan_site, decimal=6) def test_scaling2(self): scores = self.ordination.scores(2) # Load data as computed with vegan 2.0-8 vegan_species = np.loadtxt(get_data_path("example2_species_scaling2_from_vegan")) npt.assert_almost_equal(scores.species, vegan_species, decimal=6) vegan_site = np.loadtxt(get_data_path("example2_site_scaling2_from_vegan")) npt.assert_almost_equal(scores.site, vegan_site, decimal=6)
def setup(self): """Data from table 11.3 in Legendre & Legendre 1998.""" Y = np.loadtxt(get_data_path('example2_Y')) X = np.loadtxt(get_data_path('example2_X')) self.ordination = RDA(Y, X, ['Site0', 'Site1', 'Site2', 'Site3', 'Site4', 'Site5', 'Site6', 'Site7', 'Site8', 'Site9'], ['Species0', 'Species1', 'Species2', 'Species3', 'Species4', 'Species5'])
def setup(self): """Data from table 11.3 in Legendre & Legendre 1998.""" Y = np.loadtxt(get_data_path("example2_Y")) X = np.loadtxt(get_data_path("example2_X")) self.ordination = RDA( Y, X, ["Site0", "Site1", "Site2", "Site3", "Site4", "Site5", "Site6", "Site7", "Site8", "Site9"], ["Species0", "Species1", "Species2", "Species3", "Species4", "Species5"], )
class TestRDAResults(object): # STATUS: L&L only shows results with scaling 1, and they agree # with vegan's (module multiplying by a constant). I can also # compute scaling 2, agreeing with vegan, but there are no written # results in L&L. def setup(self): """Data from table 11.3 in Legendre & Legendre 1998.""" Y = np.loadtxt(get_data_path('example2_Y')) X = np.loadtxt(get_data_path('example2_X')) self.ordination = RDA(Y, X, [ 'Site0', 'Site1', 'Site2', 'Site3', 'Site4', 'Site5', 'Site6', 'Site7', 'Site8', 'Site9' ], [ 'Species0', 'Species1', 'Species2', 'Species3', 'Species4', 'Species5' ]) def test_scaling1(self): scores = self.ordination.scores(1) # Load data as computed with vegan 2.0-8 vegan_species = np.loadtxt( get_data_path('example2_species_scaling1_from_vegan')) npt.assert_almost_equal(scores.species, vegan_species, decimal=6) vegan_site = np.loadtxt( get_data_path('example2_site_scaling1_from_vegan')) npt.assert_almost_equal(scores.site, vegan_site, decimal=6) def test_scaling2(self): scores = self.ordination.scores(2) # Load data as computed with vegan 2.0-8 vegan_species = np.loadtxt( get_data_path('example2_species_scaling2_from_vegan')) npt.assert_almost_equal(scores.species, vegan_species, decimal=6) vegan_site = np.loadtxt( get_data_path('example2_site_scaling2_from_vegan')) npt.assert_almost_equal(scores.site, vegan_site, decimal=6)