McUtils.Plots
A plotting framework that builds off of matplotlib, but potentially could use a different backend.
The design is intended to mirror the Graphics framework in Mathematica and where possible option
names have been chosen to be the same.
Difficulties with matplotlib prevent a perfect mirror but the design is consistent.
There are a few primary divisions:
Graphics/Graphics3D/GraphicsGridprovide basic access tomatplotlib.figureandmatplotlib.axesthey also hold aGraphicsPropertyManager/GraphicsPropertyManager3Dthat manages all properties (image_size,axes_label,ticks_style, etc.). The full lists can be found on the relevant reference pages and are bound aspropertieson theGraphics/Graphics3Dinstances.Plot/Plot3Dand everything in thePlotssubpackage provide concrete instances of common plots with nice names/consistent with Mathematica for discoverability but primarily fall back ontomatplotlibbuilt-in methods and then allow for restyling/data reuse, etc.Primitivesprovide direct access to the shapes that are actually plotted on screen (i.e.matplotlib.Patchobjects) in a convenient way to add on to existing plotsStylingprovides access to theme management/construction
Image/animation support and other back end support for 3D graphics (VTK) are provided at the experimental level.
Members
Examples
- Plot
- Plot3D
- GraphicsGrid
- PlotStyling
- PlotGridStyling
- Scatter
- ListContourPlot
- ListTriPlot3D
- ListTriDensityPlot
- ListTriContourPlot
- Animation
- X3D
- ColorPalettes
- ColorMaps
- PropertySetting
- PlotDelayed
- Plot3DDelayed
Before we can run our examples we should get a bit of setup out of the way. Since these examples were harvested from the unit tests not all pieces will be necessary for all situations.
All tests are wrapped in a test class
class PlotsTests(TestCase):
def tearDownClass(cls):
import matplotlib.pyplot as plt
def result_file(self, fname):
if not os.path.isdir(os.path.join(TestManager.test_dir, "test_results")):
os.mkdir(os.path.join(TestManager.test_dir, "test_results"))
return os.path.join(TestManager.test_dir, "test_results", fname)
Plot
def test_Plot(self):
grid = np.linspace(0, 2*np.pi, 100)
plot = Plot(grid, np.sin(grid))
plot.show()
# plot.savefig(self.result_file("test_Plot.png"))
plot.close()
Plot3D
def test_Plot3D(self):
import matplotlib.cm as colormaps
f = lambda pt: np.sin(pt[0]) + np.cos(pt[1])
plot = Plot3D(f, np.arange(0, 2 * np.pi, .1), np.arange(0, 2 * np.pi, .1),
plot_style={
"cmap": colormaps.get_cmap('viridis')
},
axes_labels=['dogs', 'cats',
Styled('rats', color='red')
],
plot_label='my super cool 3D plot',
plot_range=[(-5, 5)] * 3,
plot_legend='i lik turtle',
colorbar=True
)
plot.savefig(self.result_file("test_Plot3D.png"))
plot.close()
GraphicsGrid
def test_GraphicsGrid(self):
main = GraphicsGrid(ncols=3, nrows=1)
grid = np.linspace(0, 2 * np.pi, 100)
grid_2D = np.meshgrid(grid, grid)
main[0, 0] = ContourPlot(grid_2D[1], grid_2D[0], np.sin(grid_2D[0]), figure=main[0, 0])
main[0, 1] = ContourPlot(grid_2D[1], grid_2D[0], np.sin(grid_2D[0]) * np.cos(grid_2D[1]), figure=main[0, 1])
main[0, 2] = ContourPlot(grid_2D[1], grid_2D[0], np.cos(grid_2D[1]), figure=main[0, 2])
# main.show()
main.savefig(self.result_file("test_GraphicsGrid.png"))
main.close()
PlotStyling
def test_PlotStyling(self):
grid = np.linspace(0, 2 * np.pi, 100)
# file = '~/Desktop/y.png'
plot = Plot(grid, np.sin(grid),
aspect_ratio=1.3,
theme='dark_background',
ticks_style={'color':'red', 'labelcolor':'red'},
plot_label='bleh',
padding=((30, 0), (20, 20))
)
# plot.savefig(file)
# plot = Image.from_file(file)
plot.show()
# plot.savefig(self.result_file("test_PlotStyling.png"))
plot.close()
PlotGridStyling
def test_PlotGridStyling(self):
main = GraphicsGrid(ncols=3, nrows=1, theme='Solarize_Light2', figure_label='my beuatufil triptych',
padding=((50, 10), (50, 65)),
spacings=[50, 0])
grid = np.linspace(0, 2 * np.pi, 100)
grid_2D = np.meshgrid(grid, grid)
x = grid_2D[1]; y = grid_2D[0]
main[0, 0] = ContourPlot(x, y, np.sin(y), plot_label='$sin(x)$',
axes_labels=[None, "cats (cc)"],
figure=main[0, 0]
)
main[0, 1] = ContourPlot(x, y, np.sin(x) * np.cos(y),
plot_label='$sin(x)cos(y)$',
axes_labels=[Styled("dogs (arb.)", {'color': 'red'}), None],
figure=main[0, 1])
main[0, 2] = ContourPlot(x, y, np.cos(y), plot_label='$cos(y)$', figure=main[0, 2])
main.colorbar = {"graphics": main[0, 1].graphics}
main.show()
# main.savefig(self.result_file("test_PlotGridStyling.png"))
main.close()
Scatter
def test_Scatter(self):
pts = np.random.rand(50, 2)
plot = ScatterPlot(*pts.T,
aspect_ratio=2,
image_size=250
)
plot.show()
# plot.savefig(self.result_file("test_Scatter.pdf"), format='pdf')
plot.close()
ListContourPlot
def test_ListContourPlot(self):
pts = np.pi*np.random.rand(150, 2)
sins = np.sin(pts[:, 0])
coses = np.cos(pts[:, 1])
ptss = np.concatenate((pts, np.reshape(sins*coses, sins.shape + (1,))), axis=1)
plot = ListContourPlot(ptss)
plot.savefig(self.result_file("test_ListContourPlot.png"))
plot.close()
ListTriPlot3D
def test_ListTriPlot3D(self):
pts = np.pi*np.random.rand(150, 2)
sins = np.sin(pts[:, 0])
coses = np.cos(pts[:, 1])
ptss = np.concatenate((pts, np.reshape(sins*coses, sins.shape + (1,))), axis=1)
plot = ListTriPlot3D(ptss)
plot.savefig(self.result_file("test_ListTriPlot3D.png"))
plot.close()
ListTriDensityPlot
def test_ListTriDensityPlot(self):
pts = np.pi*np.random.rand(150, 2)
sins = np.sin(pts[:, 0])
coses = np.cos(pts[:, 1])
ptss = np.concatenate((pts, np.reshape(sins*coses, sins.shape + (1,))), axis=1)
plot = ListTriDensityPlot(ptss)
plot.savefig(self.result_file("test_ListTriDensityPlot.png"))
plot.close()
ListTriContourPlot
def test_ListTriContourPlot(self):
pts = np.pi*np.random.rand(150, 2)
sins = np.sin(pts[:, 0])
coses = np.cos(pts[:, 1])
ptss = np.concatenate((pts, np.reshape(sins*coses, sins.shape + (1,))), axis=1)
plot = ListTriContourPlot(ptss)
plot.add_colorbar()
plot.savefig(self.result_file("test_ListTriContourPlot.png"))
plot.close()
Animation
def test_Animation(self):
"Currently broken"
def get_data(*args):
pts = np.pi*np.random.normal(scale = .25, size=(10550, 2))
sins = np.sin(pts[:, 0])
coses = np.cos(pts[:, 1])
ptss = np.concatenate((pts, np.reshape(sins*coses, sins.shape + (1,))), axis=1)
return (ptss, )
plot = ListTriContourPlot(*get_data(),
animate = get_data,
plot_range = [
[-np.pi, np.pi],
[-np.pi, np.pi]
]
)
plot.show()
plot.savefig(self.result_file("test_ListTriContourPlot.gif"))
plot.close()
X3D
def test_X3D(self):
plot = Graphics3D(backend="x3d", image_size=[1500, 500], background='white')
Sphere(color='red').plot(plot)
plot.show()
ColorPalettes
def test_ColorPalettes(self):
rgb_code = [200, 10, 25]
huh = ColorPalette.color_convert(rgb_code, 'rgb', 'xyz')
og = ColorPalette.color_convert(huh, 'xyz', 'rgb')
print(huh, og)
huh = ColorPalette.color_convert(rgb_code, 'rgb', 'hsl')
og = ColorPalette.color_convert(huh, 'hsl', 'rgb')
print(huh, og, ColorPalette.rgb_code(og))
huh = ColorPalette.color_convert(rgb_code, 'rgb', 'hsv')
og = ColorPalette.color_convert(huh, 'hsv', 'rgb')
print(huh, og, ColorPalette.rgb_code(og))
huh = ColorPalette.color_convert(rgb_code, 'rgb', 'lab')
og = ColorPalette.color_convert(huh, 'lab', 'rgb')
print(huh, og, ColorPalette.rgb_code(og))
print(ColorPalette("pastel").blend(.2))
# return
grid = np.linspace(0, 2 * np.pi, 200)
# base_fig = None
# for i in range(6):
# base_fig = Plot(
# grid,
# i + np.sin((i + 1) * grid),
# figure=base_fig,
# style_list={'color': ColorPalette("pastel")}
# )
palette_base = [
"#3a2652", "#dcca00", "#a15547",
"#009b5d", "#14013d",
"#8d0001", "#494947"
]
lighter_palette = [
ColorPalette.color_lighten(c, .2, shift=True)
for c in palette_base
]
lighter_palette_hsl = [
ColorPalette.color_lighten(c, .2, modification_space='hsl', shift=True)
for c in palette_base
]
for n,p in {
'starters':'starters',
'base':palette_base,
'lighter':lighter_palette,
'lighter_hsl':lighter_palette_hsl,
}.items():
base_fig = None
print(ColorPalette(p).get_colorblindness_test_url())
for i in range(6):
base_fig = Plot(
grid,
i + np.sin((i + 1) * grid),
figure=base_fig,
style_list={'color': ColorPalette(p)},
plot_label=n
)
ColorMaps
def test_ColorMaps(self):
print(
ColorPalette('pastel').blend([
0, .2, .5, 1.1
])
)
print(
ColorPalette('pastel')([0, .2, .5, 1.1])
)
grid_x = np.linspace(0, 2*np.pi, 100)
grid_y = np.linspace(0, 2*np.pi, 100)
mg = np.meshgrid(grid_x, grid_y)
grid_z = np.sum(np.meshgrid(np.sin(grid_x), np.cos(grid_y)), axis=0)
ContourPlot(
*mg,
grid_z,
cmap=ColorPalette('starters').as_colormap(
levels=np.linspace(0, 1, 20)**2,
cmap_type='interpolated'
),
levels=50,
colorbar=True
).show()
PropertySetting
def test_PropertySetting(self):
StickPlot(
np.linspace(0, 2*np.pi, 35),
np.sin(np.linspace(0, 2*np.pi, 35)),
color='red',
label='spec_1',
plot_legend=True
).show()
PlotDelayed
def test_PlotDelayed(self):
p = Plot(background = 'black')
for i, c in enumerate(('red', 'white', 'blue')):
p.plot(np.sin, [-2 + 4/3*i, -2 + 4/3*(i+1)], color = c)
# p.show()
p.savefig(self.result_file("test_PlotDelayed.gif"))
p.close()
Plot3DDelayed
def test_Plot3DDelayed(self):
p = Plot3D(background = 'black')
for i, c in enumerate(('red', 'white', 'blue')):
p.plot(
lambda g: (
np.sin(g.T[0]) + np.cos(g.T[1])
),
[-2 + 4/3*i, -2 + 4/3*(i+1)],
[-2 + 4/3*i, -2 + 4/3*(i+1)],
color = c)
# p.show()
p.savefig(self.result_file("test_Plot3DDelayed.gif"))
p.close()