直出SCI的Python绘图库

import proplot as pplt
import numpy as np

# Sample data
cycle = pplt.Cycle('davos', right=0.8)
state = np.random.RandomState(51423)
N, M = 400, 20
xmax = 20
x = np.linspace(0, 100, N)
y = 100 * (state.rand(N, M) - 0.42).cumsum(axis=0)

# Plot the data
fig = pplt.figure(refwidth=2.2, share=False)
axs = fig.subplots([[0, 1, 1, 0], [2, 2, 3, 3]], wratios=(2, 1, 1, 2))
axs[0].axvspan(
    0, xmax, zorder=3, edgecolor='red', facecolor=pplt.set_alpha('red', 0.2),
)
for i, ax in enumerate(axs):
    inbounds = i == 1
    title = f'Restricted xlim inbounds={inbounds}'
    title += ' (default)' if inbounds else ''
    ax.format(
        xmax=(None if i == 0 else xmax),
        title=('Default xlim' if i == 0 else title),
    )
    ax.plot(x, y, cycle=cycle, inbounds=inbounds)
fig.format(
    xlabel='xlabel',
    ylabel='ylabel',
    suptitle='Default ylim restricted to in-bounds data'
)

import proplot as pplt
import numpy as np

# Sample data
cmap = 'turku_r'
state = np.random.RandomState(51423)
N = 80
x = y = np.arange(N + 1)
data = 10 + (state.normal(0, 3, size=(N, N))).cumsum(axis=0).cumsum(axis=1)
xlim = ylim = (0, 25)

# Plot the data
fig, axs = pplt.subplots(
    [[0, 1, 1, 0], [2, 2, 3, 3]], wratios=(1.3, 1, 1, 1.3), span=False, refwidth=2.2,
)
axs[0].fill_between(
    xlim, *ylim, zorder=3, edgecolor='red', facecolor=pplt.set_alpha('red', 0.2),
)
for i, ax in enumerate(axs):
    inbounds = i == 1
    title = f'Restricted lims inbounds={inbounds}'
    title += ' (default)' if inbounds else ''
    ax.format(
        xlim=(None if i == 0 else xlim),
        ylim=(None if i == 0 else ylim),
        title=('Default axis limits' if i == 0 else title),
    )
    ax.pcolor(x, y, data, cmap=cmap, inbounds=inbounds)
fig.format(
    xlabel='xlabel',
    ylabel='ylabel',
    suptitle='Default vmin/vmax restricted to in-bounds data'
)

import proplot as pplt
import numpy as np

# Fake data with unusual longitude seam location and without coverage over poles
offset = -40
lon = pplt.arange(offset, 360 + offset - 1, 60)
lat = pplt.arange(-60, 60 + 1, 30)
state = np.random.RandomState(51423)
data = state.rand(len(lat), len(lon))

# Plot data both without and with globe=True
for globe in (False, True):
    string = 'with' if globe else 'without'
    gs = pplt.GridSpec(nrows=2, ncols=2)
    fig = pplt.figure(refwidth=2.5)
    for i, ss in enumerate(gs):
        ax = fig.subplot(ss, proj='kav7', basemap=(i % 2))
        cmap = ('sunset', 'sunrise')[i % 2]
        if i > 1:
            ax.pcolor(lon, lat, data, cmap=cmap, globe=globe, extend='both')
        else:
            m = ax.contourf(lon, lat, data, cmap=cmap, globe=globe, extend='both')
            fig.colorbar(m, loc='b', span=i + 1, label='values', extendsize='1.7em')
    fig.format(
        suptitle=f'Geophysical data {string} global coverage',
        toplabels=('Cartopy example', 'Basemap example'),
        leftlabels=('Filled contours', 'Grid boxes'),
        toplabelweight='normal', leftlabelweight='normal',
        coast=True, lonlines=90,
        abc='A.', abcloc='ul', abcborder=False,
    )