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)