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849505e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 | import numpy as np
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
from matplotlib.colors import BoundaryNorm
from matplotlib.cm import ScalarMappable
# ========== 1. Generate random global-like data ==========
np.random.seed(42)
nlon, nlat, nt = 64, 32, 5
lon = np.linspace(-180, 180, nlon)
lat = np.linspace(-90, 90, nlat)
true_state = 0.012 + 0.004 * np.sin(np.deg2rad(lat[:, None])) * np.cos(np.deg2rad(lon[None, :]/2))
true_state = np.stack([true_state + 0.001*np.random.randn(nlat, nlon) for _ in range(nt)], axis=0)
pred_state = true_state + 0.0015 * np.random.randn(nt, nlat, nlon)
abs_err = np.abs(pred_state - true_state)
# ========== 2. Layout configuration ==========
# 删除 Observations 行
row_labels = ["True State", "Tensor-Var Result", "Absolute Error"]
col_times = ["2018-01-01\n00:00", "2018-01-02\n00:00", "2018-01-03\n00:00", "2018-01-04\n00:00", "2018-01-05\n00:00"]
nrows, ncols = len(row_labels), len(col_times)
fig, axes = plt.subplots(
nrows, ncols, figsize=(18, 8),
subplot_kw={'projection': ccrs.Robinson()},
constrained_layout=False
)
# 增加列距和行距
plt.subplots_adjust(wspace=0.15, hspace=0.15)
cmap_main = plt.cm.RdBu_r
cmap_error = plt.cm.Blues
vmin_main, vmax_main = 0.005, 0.02
vmin_err, vmax_err = 0.0, 0.004
# ========== 3. Plot each panel ==========
for i in range(nrows):
for j in range(ncols):
ax = axes[i, j]
ax.coastlines(linewidth=0.4)
ax.gridlines(draw_labels=False, color='gray', linestyle=':', alpha=0.3)
if i == 0:
data = true_state[j]
levels = np.linspace(vmin_main, vmax_main, 15)
cmap = cmap_main
norm = BoundaryNorm(levels, cmap.N)
elif i == 1:
data = pred_state[j]
levels = np.linspace(vmin_main, vmax_main, 15)
cmap = cmap_main
norm = BoundaryNorm(levels, cmap.N)
elif i == 2:
data = abs_err[j]
levels = np.linspace(vmin_err, vmax_err, 10)
cmap = cmap_error
norm = BoundaryNorm(levels, cmap.N)
im = ax.contourf(lon, lat, data, levels=levels, cmap=cmap,
transform=ccrs.PlateCarree(), extend='both')
# 列标题
if i == 0:
ax.set_title(col_times[j], fontsize=14, fontweight='bold', pad=20)
# 行标签（旋转90°加粗放在行左侧中间）
if j == 0:
axes[i, 0].text(-0.12, 0.5, row_labels[i],
transform=axes[i, 0].transAxes,
ha='center', va='center',
fontsize=12, fontweight='bold',
rotation=90)
# 每个子图单独添加 colorbar（横向放在下面）
sm = ScalarMappable(norm=norm, cmap=cmap)
cbar = fig.colorbar(sm, ax=ax, orientation='horizontal',
fraction=0.05, pad=0.04, aspect=25)
# 调整 colorbar tick 间隔
ticks = np.linspace(levels[0], levels[-1], num=6) # 只显示6个刻度
cbar.set_ticks(ticks)
cbar.ax.tick_params(labelsize=7)
# if i == 2:
# cbar.set_label('Absolute Error', fontsize=8)
# else:
# cbar.set_label('Value', fontsize=8)
# ========== 4. Save figure ==========
plt.savefig("era5_like_cartopy_layout.pdf", dpi=100, bbox_inches="tight")
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