Insets and panels

    To generate “stacked” panels, simply call panel more than once. To include panels when centering spanning axis labels and super titles, pass includepanels=True to . Panels do not interfere with the tight layout algorithm and .

    1. import proplot as plot
    2. import numpy as np
    3. state = np.random.RandomState(51423)
    4. data = (state.rand(20, 20) - 0.48).cumsum(axis=1).cumsum(axis=0)
    5. data = 10 * (data - data.min()) / (data.max() - data.min())
    7. # Stacked panels with outer colorbars
    8. for cbarloc, ploc in ('rb', 'br'):
    9.     fig, axs = plot.subplots(
    10.         axwidth=1.8, nrows=1, ncols=2,
    11.         share=0, panelpad=0.1, includepanels=True
    12.     )
    13.     axs.format(
    14.         xlabel='xlabel', ylabel='ylabel', title='Title',
    15.         suptitle='Using panels for summary statistics',
    16.     )
    18.     # Plot 2D dataset
    19.     axs.contourf(
    20.         data, cmap='glacial', extend='both',
    21.         colorbar=cbarloc, colorbar_kw={'label': 'colorbar'},
    22.     )
    24.     # Get summary statistics and settings
    25.     axis = int(ploc == 'r')  # dimension along which stats are taken
    26.     x1 = x2 = np.arange(20)
    28.     y2 = data.std(axis=axis)
    29.     if ploc == 'r':
    30.         titleloc = 'center'
    31.         x1, x2, y1, y2 = y1, y2, x1, x2
    33.     # Panels for plotting the mean. We make two panels at once and plot data
    34.     # on both panels at once by calling functions from SubplotsContainers.
    35.     # More realistically, you would plot data on each panel one-by-one.
    36.     space = 0
    37.     width = '4em'
    38.     kwargs = {'titleloc': titleloc, 'xreverse': False, 'yreverse': False}
    39.     paxs = axs.panel(ploc, space=space, width=width)
    40.     paxs.plot(x1, y1, color='gray7')
    41.     paxs.format(title='Mean', **kwargs)
    43.     # Panels for plotting the standard deviation
    44.     paxs = axs.panel(ploc, space=space, width=width)
    45.     paxs.plot(x2, y2, color='gray7', ls='--')
    46.     paxs.format(title='Stdev', **kwargs)

    1. import proplot as plot
    2. fig, axs = plot.subplots(axwidth=1.5, nrows=2, ncols=2, share=0)
    4. # Demonstrate that complex arrangements of panels does
    5. # not mess up subplot aspect ratios or tight layout spacing
    6. axs.format(
    7.     xlim=(0, 1), ylim=(0, 1),
    8.     xlabel='xlabel', ylabel='ylabel',
    9.     xticks=0.2, yticks=0.2,
    10.     title='Title', suptitle='Complex arrangement of panels',
    11.     collabels=['Column 1', 'Column 2'],
    12.     abc=True, abcloc='ul', titleloc='uc', abovetop=False,
    13. for ax, side in zip(axs, 'tlbr'):

    _images/insets_panels_3_0.svg

    Inset axes

    1. import proplot as plot
    2. import numpy as np
    4. # Generate sample data
    5. N = 20
    6. state = np.random.RandomState(51423)
    7. x, y = np.arange(10), np.arange(10)
    8. data = state.rand(10, 10)
    10. # Plot sample data
    11. fig, ax = plot.subplots(axwidth=3)
    12. m = ax.pcolormesh(data, cmap='Grays', levels=N)
    13. ax.colorbar(m, loc='b', label='label')
    14. ax.format(
    15.     xlabel='xlabel', ylabel='ylabel',
    16.     suptitle='"Zooming in" with an inset axes'
    17. )
    19. # Create inset axes representing a "zoom-in"
    20. iax = ax.inset(
    21.     [5, 5, 4, 4], transform='data', zoom=True,
    22.     zoom_kw={'color': 'red3', 'lw': 2, 'ls': '--'}
    23. )
    24. iax.format(
    25.     xlim=(2, 4), ylim=(2, 4), color='red7',
    26.     linewidth=1.5, ticklabelweight='bold'
    27. )