def test_dynamic_lisa_vectors():
_, _, rose = _data_generation()
fig1, _ = dynamic_lisa_vectors(rose)
plt.close(fig1)
fig2, _ = dynamic_lisa_vectors(rose, arrows=False)
plt.close(fig2)
fig3, _ = dynamic_lisa_vectors(rose, c='r')
plt.close(fig3)
def test_dynamic_lisa_vectors():
_, _, rose = _data_generation()
fig1, _ = dynamic_lisa_vectors(rose)
plt.close(fig1)
fig2, _ = dynamic_lisa_vectors(rose, arrows=False)
plt.close(fig2)
fig3, _ = dynamic_lisa_vectors(rose, c='r')
plt.close(fig3)
fig4, axs = plt.subplots(1, 3)
dynamic_lisa_vectors(rose, ax=axs[0], color='r')
plt.close(fig4)
def plot_vectors(self, arrows=True):
"""
Plot vectors of positional transition of LISA values
within quadrant in scatterplot in a polar plot.
Parameters
----------
ax : Matplotlib Axes instance, optional
If given, the figure will be created inside this axis.
Default =None.
arrows : boolean, optional
If True show arrowheads of vectors. Default =True
**kwargs : keyword arguments, optional
Keywords used for creating and designing the plot.
Note: 'c' and 'color' cannot be passed when attribute is not None
Returns
-------
fig : Matplotlib Figure instance
Moran scatterplot figure
ax : matplotlib Axes instance
Axes in which the figure is plotted
"""
from splot.giddy import dynamic_lisa_vectors
fig, ax = dynamic_lisa_vectors(self, arrows=arrows)
return fig, ax
def test_dynamic_lisa_vectors():
from splot.giddy import dynamic_lisa_vectors
_, _, rose = _data_generation()
fig1, _ = dynamic_lisa_vectors(rose)
plt.close(fig1)
fig2, _ = dynamic_lisa_vectors(rose, arrows=False)
plt.close(fig2)
fig3, _ = dynamic_lisa_vectors(rose, c="r")
plt.close(fig3)
fig4, axs = plt.subplots(1, 3)
dynamic_lisa_vectors(rose, ax=axs[0], color="r")
plt.close(fig4)