Labelling grid lines on a Lambert Conformal projection

In response to the StackOverflow question here:


  • The map boundary must be rectangular, otherwise the detection of which axis to label will be broken.
  • Requires cartopy >= 0.12
In [1]:
from copy import copy

%matplotlib inline
import as ccrs
from cartopy.mpl.gridliner import LATITUDE_FORMATTER, LONGITUDE_FORMATTER
import matplotlib.pyplot as plt
import numpy as np
import shapely.geometry as sgeom
In [2]:
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.set_xticklabels([ax.xaxis.get_major_formatter()(xtick) for xtick in xticklabels])

def lambert_yticks(ax, ticks):
    """Draw ricks 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.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]
            tick = tick_extractor(locs.xy)
    # Remove ticks that aren't visible:    
    ticklabels = copy(ticks)
    while True:
            index = _ticks.index(None)
        except ValueError:
    return _ticks, ticklabels
In [3]:
# Create a Lambert Conformal projection:
proj = ccrs.LambertConformal(central_longitude=13.3333, central_latitude=47.5,
                             false_easting=400000, false_northing=400000,
                             standard_parallels=(46, 49))

# Draw a set of axes with coastlines:
fig = plt.figure(figsize=(9, 9), frameon=True)
ax = fig.add_axes([0.08, 0.05, 0.8, 0.94], projection=proj)
ax.set_extent([-5, 31, 42, 55], crs=ccrs.PlateCarree())

# *must* call draw in order to get the axis boundary used to add ticks:

# Define gridline locations and draw the lines using cartopy's built-in gridliner:
xticks = [-110, -50, -40, -30, -20, -11, 0, 10, 20, 30, 40, 50]
yticks = [10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80]
ax.gridlines(xlocs=xticks, ylocs=yticks)

# Label the end-points of the gridlines using the custom tick makers:
lambert_xticks(ax, xticks)
lambert_yticks(ax, yticks)