def test__uses_figure_or_subplot_configs_correctly(self):
figure = aplt.Figure(figsize=(8, 8))
cmap = aplt.Cmap(cmap="warm")
mat_plot_2d = aplt.MatPlot2D(figure=figure, cmap=cmap)
plotter = abstract_plotters.AbstractPlotter(mat_plot_2d=mat_plot_2d)
assert plotter.mat_plot_2d.figure.config_dict["figsize"] == (8, 8)
assert plotter.mat_plot_2d.figure.config_dict["aspect"] == "square"
assert plotter.mat_plot_2d.cmap.config_dict["cmap"] == "warm"
assert plotter.mat_plot_2d.cmap.config_dict["norm"] == "linear"
figure = aplt.Figure()
figure.is_for_subplot = True
cmap = aplt.Cmap()
cmap.is_for_subplot = True
mat_plot_2d = aplt.MatPlot2D(figure=figure, cmap=cmap)
plotter = abstract_plotters.AbstractPlotter(mat_plot_2d=mat_plot_2d)
assert plotter.mat_plot_2d.figure.config_dict["figsize"] == None
assert plotter.mat_plot_2d.figure.config_dict["aspect"] == "square"
assert plotter.mat_plot_2d.cmap.config_dict["cmap"] == "jet"
assert plotter.mat_plot_2d.cmap.config_dict["norm"] == "linear"
def test__plot__works_for_reasonable_range_of_values(self):
figure = aplt.Figure()
figure.open()
plt.imshow(np.ones((2, 2)))
cb = aplt.Colorbar(fraction=1.0, pad=2.0)
cb.set()
figure.close()
figure.open()
plt.imshow(np.ones((2, 2)))
cb = aplt.Colorbar(
fraction=0.1,
pad=0.5,
manual_tick_values=[0.25, 0.5, 0.75],
manual_tick_labels=[1.0, 2.0, 3.0],
)
cb.set()
figure.close()
figure.open()
plt.imshow(np.ones((2, 2)))
cb = aplt.Colorbar(fraction=0.1, pad=0.5)
cb.set_with_color_values(cmap=aplt.Cmap().config_dict["cmap"],
color_values=[1.0, 2.0, 3.0])
figure.close()
def test__open_and_close_subplot_figures(self):
figure = aplt.Figure(figsize=(20, 20))
plotter = abstract_plotters.AbstractPlotter(mat_plot_2d=aplt.MatPlot2D(
figure=figure))
plotter.mat_plot_2d.figure.open()
assert plt.fignum_exists(num=1) is True
plotter.mat_plot_2d.figure.close()
assert plt.fignum_exists(num=1) is False
plotter = abstract_plotters.AbstractPlotter(mat_plot_2d=aplt.MatPlot2D(
figure=figure))
assert plt.fignum_exists(num=1) is False
plotter.open_subplot_figure(number_subplots=4)
assert plt.fignum_exists(num=1) is True
plotter.mat_plot_2d.figure.close()
assert plt.fignum_exists(num=1) is False
def test__aspect_from_shape_native(self):
figure = aplt.Figure(aspect="auto")
aspect = figure.aspect_from_shape_native(shape_native=(2, 2))
assert aspect == "auto"
figure = aplt.Figure(aspect="square")
aspect = figure.aspect_from_shape_native(shape_native=(2, 2))
assert aspect == 1.0
aspect = figure.aspect_from_shape_native(shape_native=(4, 2))
assert aspect == 0.5
def test__open_and_close__open_and_close_figures_correct(self):
figure = aplt.Figure()
figure.open()
assert plt.fignum_exists(num=1) is True
figure.close()
assert plt.fignum_exists(num=1) is False
def test__overlay_array__works_for_reasonable_values(self):
arr = aa.Array2D.manual_native(array=[[1.0, 2.0], [3.0, 4.0]],
pixel_scales=0.5,
origin=(2.0, 2.0))
figure = aplt.Figure(aspect="auto")
array_overlay = aplt.ArrayOverlay(alpha=0.5)
array_overlay.overlay_array(array=arr, figure=figure)
def test__loads_values_from_config_if_not_manually_input(self):
figure = aplt.Figure()
assert figure.config_dict["figsize"] == (7, 7)
assert figure.config_dict["aspect"] == "square"
figure = aplt.Figure(aspect="auto")
assert figure.config_dict["figsize"] == (7, 7)
assert figure.config_dict["aspect"] == "auto"
figure = aplt.Figure()
figure.is_for_subplot = True
assert figure.config_dict["figsize"] == None
assert figure.config_dict["aspect"] == "square"
figure = aplt.Figure(figsize=(6, 6))
figure.is_for_subplot = True
assert figure.config_dict["figsize"] == (6, 6)
assert figure.config_dict["aspect"] == "square"
def test__subplot_figsize_for_number_of_subplots(self):
plotter = aplt.SubPlotter()
figsize = plotter.get_subplot_figsize(number_subplots=1)
assert figsize == (18, 8)
figsize = plotter.get_subplot_figsize(number_subplots=4)
assert figsize == (13, 10)
plotter = aplt.SubPlotter(figure=aplt.Figure(figsize=(20, 20)))
figsize = plotter.get_subplot_figsize(number_subplots=4)
assert figsize == (20, 20)
def test__set_legend_works_for_plot(self):
figure = aplt.Figure(aspect="auto")
figure.open()
line = aplt.YXPlot(linewidth=2, linestyle="-", c="k")
line.plot_y_vs_x(y=[1.0, 2.0, 3.0],
x=[1.0, 2.0, 3.0],
plot_axis_type="linear",
label="hi")
legend = aplt.Legend(fontsize=1)
legend.set()
figure.close()
def test__subplot_figsize_for_number_of_subplots(self):
plotter = abstract_plotters.AbstractPlotter()
figsize = plotter.get_subplot_figsize(number_subplots=1)
assert figsize == (18, 8)
figsize = plotter.get_subplot_figsize(number_subplots=4)
assert figsize == (13, 10)
figure = aplt.Figure(figsize=(20, 20))
plotter = abstract_plotters.AbstractPlotter(mat_plot_2d=aplt.MatPlot2D(
figure=figure))
figsize = plotter.get_subplot_figsize(number_subplots=4)
assert figsize == (20, 20)
def test__figure__from_config_or_via_manual_input(self):
plotter = aplt.Plotter()
assert plotter.figure.figsize == (7, 7)
assert plotter.figure.aspect == "auto"
plotter = aplt.Plotter(figure=aplt.Figure(aspect="auto"))
assert plotter.figure.figsize == (7, 7)
assert plotter.figure.aspect == "auto"
sub_plotter = aplt.SubPlotter()
assert sub_plotter.figure.figsize == None
assert sub_plotter.figure.aspect == "square"
sub_plotter = aplt.SubPlotter(figure=aplt.Figure.sub(figsize=(6, 6)))
assert sub_plotter.figure.figsize == (6, 6)
assert sub_plotter.figure.aspect == "square"
image_path=dataset_path + "image.fits",
noise_map_path=dataset_path + "noise_map.fits",
psf_path=dataset_path + "psf.fits",
pixel_scales=0.1,
)
# We can plot an image as follows:
aplt.imaging.image(imaging=imaging)
# Does the figure display correctly on your computer screen?
#
# If not, you can customize a number of matplotlib setup options using a Plotter object in PyAutoArray.
plotter = aplt.Plotter(
figure=aplt.Figure(figsize=(7, 7)),
ticks=aplt.Ticks(ysize=8, xsize=8),
labels=aplt.Labels(ysize=6, xsize=6, titlesize=12),
)
aplt.imaging.image(imaging=imaging, plotter=plotter)
# Many matplotlib setup options can be customized, but for now we're only concerned with making sure figures display
# cleanly in your Jupter Notebooks. However, for future reference, a description of all options can be found in the file
# 'autolens_workspace/plot/mat_objs.py'.
# Ideally, we wouldn't need to specify a new plotter every time we plot an image, especially as you'll be changing
# the same option to the same value over and over again (e.g. the figsize). Fortunately, the default values used by
# PyAutoLens can be fully customized.
# Checkout the the file 'autolens_workspace/config/visualize/figures.ini'.