绘图|解决Cartopy Lambert投影坐标轴标签设置问题

bugsuse

发布于 2020-04-21 16:40:25

4.4K0

发布于 2020-04-21 16:40:25

python中有两个使用最频繁的地图绘图库：Basemap和Cartopy，两者各有优劣。由于Cartopy和matplotlib的兼容性更好，并且用户友好度更高，开始逐渐被人接受。但是Cartopy也有一些缺点，其中之一就是在设置坐标轴标签的时候对于非矩形投影无法设置标签，比如Lambert投影。

对于不受投影限制的绘图可以转换为PlateCarree投影或者Mercator投影，但对于有投影限制的绘图，比如WRF模式的后处理(虽然WRF模式也支持Mercator投影，但是大多数情况下还是使用的Lambert投影)就受限了。

在互联网游荡的时候偶然发现了一个用于解决此问题的脚本[注1]，然后测试了一下，发现基本能够完美解决Cartopy Lambert投影标签设置的问题。以下是脚本：

from copy import copy
import numpy as np
import shapely.geometry as sgeom
import cartopy.crs as ccrs

def find_side(ls, side):
    """
    Given a shapely LineString which is assumed to be rectangular, return the
    line corresponding to a given side of the rectangle.

    """
    minx, miny, maxx, maxy = ls.bounds
    points = {'left': [(minx, miny), (minx, maxy)],
              'right': [(maxx, miny), (maxx, maxy)],
              'bottom': [(minx, miny), (maxx, miny)],
              'top': [(minx, maxy), (maxx, maxy)],}
    return sgeom.LineString(points[side])

def lambert_xticks(ax, ticks):
    """Draw ticks on the bottom x-axis of a Lambert Conformal projection."""
    te = lambda xy: xy[0]
    lc = lambda t, n, b: np.vstack((np.zeros(n) + t, np.linspace(b[2], b[3], n))).T
    xticks, xticklabels = _lambert_ticks(ax, ticks, 'bottom', lc, te)
    ax.xaxis.tick_bottom()
    ax.set_xticks(xticks)
    ax.set_xticklabels([ax.xaxis.get_major_formatter()(xtick) for xtick in xticklabels])

def lambert_yticks(ax, ticks):
    """Draw ticks on the left y-axis of a Lamber Conformal projection."""
    te = lambda xy: xy[1]
    lc = lambda t, n, b: np.vstack((np.linspace(b[0], b[1], n), np.zeros(n) + t)).T
    yticks, yticklabels = _lambert_ticks(ax, ticks, 'left', lc, te)
    ax.yaxis.tick_left()
    ax.set_yticks(yticks)
    ax.set_yticklabels([ax.yaxis.get_major_formatter()(ytick) for ytick in yticklabels])

def _lambert_ticks(ax, ticks, tick_location, line_constructor, tick_extractor):
    """Get the tick locations and labels for an axis of a Lambert Conformal projection."""
    outline_patch = sgeom.LineString(ax.outline_patch.get_path().vertices.tolist())
    axis = find_side(outline_patch, tick_location)
    n_steps = 30
    extent = ax.get_extent(ccrs.PlateCarree())
    _ticks = []
    for t in ticks:
        xy = line_constructor(t, n_steps, extent)
        proj_xyz = ax.projection.transform_points(ccrs.Geodetic(), xy[:, 0], xy[:, 1])
        xyt = proj_xyz[..., :2]
        ls = sgeom.LineString(xyt.tolist())
        locs = axis.intersection(ls)
        if not locs:
            tick = [None]
        else:
            tick = tick_extractor(locs.xy)
        _ticks.append(tick[0])
    # Remove ticks that aren't visible:    
    ticklabels = copy(ticks)
    while True:
        try:
            index = _ticks.index(None)
        except ValueError:
            break
        _ticks.pop(index)
        ticklabels.pop(index)
    return _ticks, ticklabels

以下是测试结果：

import cartopy.crs as ccrs
import cartopy.feature as cfeature  
import cartopy.io.shapereader as shpreader
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER
import matplotlib.pyplot as plt

proj = ccrs.LambertConformal(central_longitude=117, central_latitude=26,
                             standard_parallels=(30, 60))

shpfn = 'bou2_4l.shp'
reader = shpreader.Reader(shpfn)
states_provinces = cfeature.ShapelyFeature(reader.geometries(), crs = ccrs.PlateCarree(), edgecolor = 'face', facecolor = 'None')

fig = plt.figure(figsize=(9, 9), frameon=True)

ax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=proj)

# Label axes of a Mercator projection without degree symbols in the labels
# and formatting labels to include 1 decimal place:
ax.set_extent([85, 135, 0, 55], crs=ccrs.PlateCarree())

#    ax.coastlines(resolution='50m')
ax.add_feature(states_provinces, edgecolor='black')
# *must* call draw in order to get the axis boundary used to add ticks:
fig.canvas.draw()

# Define gridline locations and draw the lines using cartopy's built-in gridliner:
xticks = list(range(60, 176, 10))
yticks = list(range(-5, 66, 10))
ax.gridlines(xlocs=xticks, ylocs=yticks)

# Label the end-points of the gridlines using the custom tick makers:
ax.xaxis.set_major_formatter(LONGITUDE_FORMATTER) 
ax.yaxis.set_major_formatter(LATITUDE_FORMATTER)
# xticks and yticks only is list
lambert_xticks(ax, xticks)  
lambert_yticks(ax, yticks)

plt.show()