def test_axis_names(self): #self.Debug = True res = dict(list(zip(self.keys[:2], self.values))) plot_ordination(res, axis_names=['CCA1', 'CA1', 'CA2'], constrained_names='CCA') self.fig()
def test_biplot(self): res = dict(list(zip(self.keys, self.values))) plot_ordination(res, species_kw={'label': 'sp'}, biplot_kw={'label': ['b1', 'b2']}, samples_kw={'label': 'sa'}) self.fig()
def test_choices(self): res = dict(list(zip(self.keys, self.values))) plot_ordination(res, choices=[2, 3]) self.fig()
def test_species(self): res = dict(list(zip(self.keys[:3], self.values))) plot_ordination(res) self.fig()
def test_centroids(self): res = dict(list(zip(self.keys[:4], self.values))) plot_ordination(res) self.fig()
def test_axis_names(self): #self.Debug = True res = dict(zip(self.keys[:2], self.values)) plot_ordination(res, axis_names=['CCA1', 'CA1', 'CA2'], constrained_names='CCA') self.fig()
def test_basic(self): res = dict(list(zip(self.keys[:2], self.values))) plot_ordination(res) self.fig()
def test_choices(self): res = dict(zip(self.keys, self.values)) plot_ordination(res, choices=[2,3]) self.fig()
def test_biplot(self): res = dict(zip(self.keys, self.values)) plot_ordination(res, species_kw={'label': 'sp'}, biplot_kw={'label':['b1', 'b2']}, samples_kw={'label': 'sa'}) self.fig()
def test_centroids(self): res = dict(zip(self.keys[:4], self.values)) plot_ordination(res) self.fig()
def test_species(self): res = dict(zip(self.keys[:3], self.values)) plot_ordination(res) self.fig()
def test_basic(self): res = dict(zip(self.keys[:2], self.values)) plot_ordination(res) self.fig()