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()
