How to create a scalebar using cartopy and matplotlib? - matplotlib

Question

in respect to the previous examples in stackoverflow, I searched for other alternatives in order to create a scalebar.
In my research, I verified that the Basemap class from mpl_toolkits.basemap see here. It has the "drawmapscale" method. This method has the option barstyle = 'fancy' for a more interesting scalebar drawing.
Therefore, I attempted to convert the "drawmapscale" from the Basemap into a cartopy version.
Nevertheless, the results were not positive, and I got error messages from the figure. I believe that the error is in the Transform of the data.
Here is the script:
import numpy as np
import matplotlib.pyplot as plt
import pyproj
import cartopy.crs as ccrs
from matplotlib import is_interactive
from cartopy.crs import (WGS84_SEMIMAJOR_AXIS, WGS84_SEMIMINOR_AXIS)
from pyproj import Transformer
class Scalebar():
def __init__(self,
ax,
suppress_ticks=True,
geographical_crs = 4326,
planar_crs = 5880,
fix_aspect=True,
anchor='C',
celestial=False,
round=False,
noticks=False,
metric_ccrs=ccrs.TransverseMercator()):
self.ax = ax
self.fix_aspect = fix_aspect
# setting metric ccrs for reference in the plotting
self.metric_ccrs = metric_ccrs
self.anchor = anchor
# geographic or celestial coords?
self.celestial = celestial
# map projection.
self.projection = ax.projection
self.geographical_crs = geographical_crs
self.planar_crs = planar_crs
self._initialized_axes = set()
self.round = round
# map boundary not yet drawn.
self._mapboundarydrawn = False
self.rmajor = np.float(ax.projection.globe.semimajor_axis or WGS84_SEMIMAJOR_AXIS)
self.rminor = np.float(ax.projection.globe.semiminor_axis or WGS84_SEMIMINOR_AXIS)
# set instance variables defining map region.
self.xmin = self.projection.boundary.bounds[0]
self.xmax = self.projection.boundary.bounds[2]
self.ymin = self.projection.boundary.bounds[1]
self.ymax = self.projection.boundary.bounds[3]
self._width = self.xmax - self.xmin
self._height = self.ymax - self.ymin
self.noticks = noticks
def __call__(self,x,y,
inverse=False
):
"""
Calling the class instance with the arguments lon, lat will
convert lon/lat (in degrees) to x/y map projection
coordinates (in meters).
If optional keyword ``inverse`` is True (default is False),
the inverse transformation from x/y to lon/lat is performed.
Input arguments:
lon, lat can be either scalar floats, sequences, or numpy arrays.
"""
if not inverse:
transformer = Transformer.from_crs("epsg:{0}".format(self.geographical_crs),
"epsg:{0}".format(self.planar_crs))
else:
transformer = Transformer.from_crs("epsg:{0}".format(self.planar_crs),
"epsg:{0}".format(self.geographical_crs))
return transformer.transform(x, y)
def drawmapscale(self,
lon,
lat,
length,
lon0=None,
lat0=None,
barstyle='simple',\
units='km',
fontsize=9,
yoffset=None,
labelstyle='simple',\
fontcolor='k',
fillcolor1='w',
fillcolor2='k',\
format='%d',
zorder=None,
linecolor=None,
linewidth=None):
"""
Draw a map scale at ``lon,lat`` of length ``length``
representing distance in the map
projection coordinates at ``lon0,lat0``.
.. tabularcolumns:: |l|L|
============== ====================================================
Keywords Description
============== ====================================================
units the units of the length argument (Default km).
barstyle ``simple`` or ``fancy`` (roughly corresponding
to the styles provided by Generic Mapping Tools).
Default ``simple``.
fontsize for map scale annotations, default 9.
fontcolor for map scale annotations, default black.
labelstyle ``simple`` (default) or ``fancy``. For
``fancy`` the map scale factor (ratio betwee
the actual distance and map projection distance
at lon0,lat0) and the value of lon0,lat0 are also
displayed on the top of the scale bar. For
``simple``, just the units are display on top
and the distance below the scale bar.
If equal to False, plot an empty label.
format a string formatter to format numeric values
yoffset yoffset controls how tall the scale bar is,
and how far the annotations are offset from the
scale bar. Default is 0.02 times the height of
the map (0.02*(self.ymax-self.ymin)).
fillcolor1(2) colors of the alternating filled regions
(default white and black). Only relevant for
'fancy' barstyle.
zorder sets the zorder for the map scale.
linecolor sets the color of the scale, by default, fontcolor
is used
linewidth linewidth for scale and ticks
============== ====================================================
Extra keyword ``ax`` can be used to override the default axis instance.
"""
# get current axes instance (if none specified).
ax = self.ax
# convert length to meters
lenlab = length
if units == 'km':
length = length*1000
elif units == 'mi':
length = length*1609.344
elif units == 'nmi':
length = length*1852
elif units == 'ft':
length = length*0.3048
elif units != 'm':
msg = "units must be 'm' (meters), 'km' (kilometers), "\
"'mi' (miles), 'nmi' (nautical miles), or 'ft' (feet)"
raise KeyError(msg)
# Setting the center coordinates of the axes:
xmin, xmax, ymin, ymax = self.ax.get_extent()
if lon0 == None:
lon0 = np.mean([xmin, xmax])
if lat0 == None:
lat0 = np.mean([ymin, ymax])
# reference point and center of scale.
x0,y0 = self(lon0,lat0)
print('\n\n Central coords prior to transform')
print('lon0,lat0: ', [lon0,lat0])
print('\n\n central coordinates after transform')
print('x0,y0: ', [x0,y0])
xc,yc = self(lon,lat)
print('\n\n positional coordinates prior to transform')
print('lon, lat: ', [lon,lat])
print('\n\n central coordinates after transform')
print('xc,yc: ', [xc,yc])
print('-'*20, '\n')
# make sure lon_0 between -180 and 180
lon_0 = ((lon0+360) % 360) - 360
if lat0>0:
if lon>0:
lonlatstr = u'%g\N{DEGREE SIGN}N, %g\N{DEGREE SIGN}E' % (lat0,lon_0)
elif lon<0:
lonlatstr = u'%g\N{DEGREE SIGN}N, %g\N{DEGREE SIGN}W' % (lat0,lon_0)
else:
lonlatstr = u'%g\N{DEGREE SIGN}, %g\N{DEGREE SIGN}W' % (lat0,lon_0)
else:
if lon>0:
lonlatstr = u'%g\N{DEGREE SIGN}S, %g\N{DEGREE SIGN}E' % (lat0,lon_0)
elif lon<0:
lonlatstr = u'%g\N{DEGREE SIGN}S, %g\N{DEGREE SIGN}W' % (lat0,lon_0)
else:
lonlatstr = u'%g\N{DEGREE SIGN}S, %g\N{DEGREE SIGN}' % (lat0,lon_0)
# left edge of scale
lon1,lat1 = self(x0-length/2,y0, inverse=True)
x1,y1 = self(lon1,lat1)
# right edge of scale
lon4,lat4 = self(x0+length/2,y0, inverse=True)
x4,y4 = self(lon4,lat4)
x1 = x1-x0+xc
y1 = y1-y0+yc
print('\n\n positional coordinates prior to transform')
print('lon1,lat1: ', [lon1,lat1])
print('\n\n positional coordinates prior to transform')
print('x1, y1: ', [x1,y1])
print()
print('\n\n central coordinates after transform')
print('lon4,lat4: ', [lon4,lat4])
print('-'*20, '\n')
print('\n\n central coordinates after transform')
print('x4,y4: ', [x4,y4])
print('-'*20, '\n')
x4 = x4-x0+xc
y4 = y4-y0+yc
if x1 > 1.e20 or x4 > 1.e20 or y1 > 1.e20 or y4 > 1.e20:
raise ValueError("scale bar positioned outside projection limb")
# scale factor for true distance
gc = pyproj.Geod(a=self.rmajor,b=self.rminor)
az12,az21,dist = gc.inv(lon1,lat1,lon4,lat4)
scalefact = dist/length
# label to put on top of scale bar.
if labelstyle=='simple':
labelstr = units
elif labelstyle == 'fancy':
labelstr = units+" (scale factor %4.2f at %s)"%(scalefact,lonlatstr)
elif labelstyle == False:
labelstr = ''
else:
raise KeyError("labelstyle must be 'simple' or 'fancy'")
# default y offset is 2 percent of map height.
if yoffset is None:
yoffset = 0.02*(self.ymax-self.ymin)
rets = [] # will hold all plot objects generated.
# set linecolor
if linecolor is None:
linecolor = fontcolor
# 'fancy' style
if barstyle == 'fancy':
#we need 5 sets of x coordinates (in map units)
#quarter scale
lon2,lat2 = self(x0-length/4,y0,inverse=True)
x2,y2 = self(lon2,lat2)
x2 = x2-x0+xc; y2 = y2-y0+yc
#three quarter scale
lon3,lat3 = self(x0+length/4,y0,inverse=True)
x3,y3 = self(lon3,lat3)
x3 = x3-x0+xc; y3 = y3-y0+yc
#plot top line
ytop = yc+yoffset/2
ybottom = yc-yoffset/2
ytick = ybottom - yoffset/2
ytext = ytick - yoffset/2
lontext , lattext = self(lon0,ytext, inverse=True)
#lon_top, lat_top = self(lon4,ytop,inverse=True)
#lon_top, lat_bottom = self(lon4,ybottom,inverse=True)
transform = self.metric_ccrs # this crs projection is meant to be for metric data
rets.append(self.plot([x1,x4],
[ytop,ytop],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
#plot bottom line
rets.append(self.plot([x1,x4],
[ybottom,ybottom],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
#plot left edge
rets.append(self.plot([x1,x1],
[ybottom,ytop],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
#plot right edge
rets.append(self.plot([x4,x4],
[ybottom,ytop],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
#make a filled black box from left edge to 1/4 way across
rets.append(ax.fill([x1,x2,x2,x1,x1],
[ytop,ytop,ybottom,ybottom,ytop],
transform=transform,
ec=fontcolor,
fc=fillcolor1)[0])
#make a filled white box from 1/4 way across to 1/2 way across
rets.append(ax.fill([x2,x0,x0,x2,x2],
[ytop,ytop,ybottom,ybottom,ytop],
transform=transform,
ec=fontcolor,
fc=fillcolor2)[0])
#make a filled white box from 1/2 way across to 3/4 way across
rets.append(ax.fill([x0,x3,x3,x0,x0],
[ytop,ytop,ybottom,ybottom,ytop],
transform=transform,
ec=fontcolor,
fc=fillcolor1)[0])
#make a filled white box from 3/4 way across to end
rets.append(ax.fill([x3,x4,x4,x3,x3],
[ytop,ytop,ybottom,ybottom,ytop],
transform=transform,
ec=fontcolor,
fc=fillcolor2)[0])
#plot 3 tick marks at left edge, center, and right edge
rets.append(self.plot([x1,x1],
[ytick,ybottom],
color=linecolor,
transform=transform,
linewidth=linewidth)[0])
rets.append(self.plot([x0,x0],
[ytick,ybottom],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
rets.append(self.plot([x4,x4],
[ytick,ybottom],
transform=transform,
color=linecolor,
linewidth=linewidth)[0])
#label 3 tick marks
rets.append(ax.text(x1,lattext,format % (0),\
horizontalalignment='center',\
verticalalignment='top',\
fontsize=fontsize,color=fontcolor))
rets.append(ax.text(x0,lattext,format % (0.5*lenlab),\
horizontalalignment='center',\
verticalalignment='top',\
fontsize=fontsize,color=fontcolor))
rets.append(ax.text(x4,lattext,format % (lenlab),\
horizontalalignment='center',\
verticalalignment='top',\
fontsize=fontsize,color=fontcolor))
#put units, scale factor on top
rets.append(ax.text(x0,ytop+yoffset/2,labelstr,\
horizontalalignment='center',\
verticalalignment='bottom',\
fontsize=fontsize,color=fontcolor))
# 'simple' style
elif barstyle == 'simple':
rets.append(self.plot([x1,x4],[yc,yc],color=linecolor, linewidth=linewidth)[0])
rets.append(self.plot([x1,x1],[yc-yoffset,yc+yoffset],color=linecolor, linewidth=linewidth)[0])
rets.append(self.plot([x4,x4],[yc-yoffset,yc+yoffset],color=linecolor, linewidth=linewidth)[0])
rets.append(ax.text(xc,yc-yoffset,format % lenlab,\
verticalalignment='top',horizontalalignment='center',\
fontsize=fontsize,color=fontcolor))
#put units, scale factor on top
rets.append(ax.text(xc,yc+yoffset,labelstr,\
horizontalalignment='center',\
verticalalignment='bottom',\
fontsize=fontsize,color=fontcolor))
else:
raise KeyError("barstyle must be 'simple' or 'fancy'")
if zorder is not None:
for ret in rets:
try:
ret.set_zorder(zorder)
except:
pass
return rets
def plot(self, *args, **kwargs):
"""
Draw lines and/or markers on the map
(see matplotlib.pyplot.plot documentation).
If ``latlon`` keyword is set to True, x,y are intrepreted as
longitude and latitude in degrees. Data and longitudes are
automatically shifted to match map projection region for cylindrical
and pseudocylindrical projections, and x,y are transformed to map
projection coordinates. If ``latlon`` is False (default), x and y
are assumed to be map projection coordinates.
Extra keyword ``ax`` can be used to override the default axis instance.
Other \**kwargs passed on to matplotlib.pyplot.plot.
"""
ax = self.ax
self._save_use_hold(ax, kwargs)
try:
ret = ax.plot(*args,
**kwargs)
finally:
self._restore_hold(ax)
# set axes limits to fit map region.
self.set_axes_limits(ax=ax)
# clip to map limbs
ret,c = self._cliplimb(ax,ret)
return ret
def _save_use_hold(self, ax, kwargs):
h = kwargs.pop('hold', None)
if hasattr(ax, '_hold'):
self._tmp_hold = ax._hold
if h is not None:
ax._hold = h
def _restore_hold(self, ax):
if hasattr(ax, '_hold'):
ax._hold = self._tmp_hold
def set_axes_limits(self,ax=None):
"""
Final step in Basemap method wrappers of Axes plotting methods:
Set axis limits, fix aspect ratio for map domain using current
or specified axes instance. This is done only once per axes
instance.
In interactive mode, this method always calls draw_if_interactive
before returning.
"""
# get current axes instance (if none specified).
ax = ax or self._check_ax()
# If we have already set the axes limits, and if the user
# has not defeated this by turning autoscaling back on,
# then all we need to do is plot if interactive.
if (hash(ax) in self._initialized_axes
and not ax.get_autoscalex_on()
and not ax.get_autoscaley_on()):
if is_interactive():
import matplotlib.pyplot as plt
plt.draw_if_interactive()
return
self._initialized_axes.add(hash(ax))
# Take control of axis scaling:
ax.set_autoscale_on(False)
# update data limits for map domain.
corners = ((self.xmin, self.ymin), (self.xmax, self.ymax))
ax.update_datalim(corners)
ax.set_xlim((self.xmin, self.xmax))
ax.set_ylim((self.ymin, self.ymax))
# if map boundary not yet drawn for elliptical maps, draw it with default values.
# make sure aspect ratio of map preserved.
# plot is re-centered in bounding rectangle.
# (anchor instance var determines where plot is placed)
if self.fix_aspect:
ax.set_aspect('equal',anchor=self.anchor)
else:
ax.set_aspect('auto',anchor=self.anchor)
# make sure axis ticks are turned off.
if self.noticks:
ax.set_xticks([])
ax.set_yticks([])
# force draw if in interactive mode.
if is_interactive():
import matplotlib.pyplot as plt
plt.draw_if_interactive()
def _cliplimb(self,ax,coll):
if not self._mapboundarydrawn:
return coll, None
c = self._mapboundarydrawn
if c not in ax.patches:
p = ax.add_patch(c)
#p.set_clip_on(False)
try:
coll.set_clip_path(c)
except:
for item in coll:
item.set_clip_path(c)
return coll,c
# now the test
from cartopy.mpl.gridliner import LONGITUDE_FORMATTER, LATITUDE_FORMATTER
import geopandas as gpd
def get_standard_gdf():
""" basic function for getting some geographical data in geopandas GeoDataFrame python's instance:
An example data can be downloaded from Brazilian IBGE:
ref: ftp://geoftp.ibge.gov.br/organizacao_do_territorio/malhas_territoriais/malhas_municipais/municipio_2017/Brasil/BR/br_municipios.zip
"""
gdf_path = r'C:\my_file_path\Shapefile.shp'
return gpd.read_file(gdf_path)
def format_ax(ax, projection, xlim, ylim):
ax.set_xlim(xlim)
ax.set_ylim(ylim)
ax.set_global()
ax.coastlines()
def main():
fig = plt.figure(figsize=(8, 10))
# Label axes of a Plate Carree projection with a central longitude of 180:
#for enum, proj in enumerate(['Mercator, PlateCarree']):
gdf = get_standard_gdf()
xmin, ymin, xmax, ymax = gdf.total_bounds
xlim = [xmin, xmax]
ylim = [ymin, ymax]
lon_c = np.mean(xlim)
lat_c = np.mean(ylim)
projection = ccrs.PlateCarree(central_longitude=0)
ax1 = fig.add_subplot(3, 1, 1,
projection=projection,
xlim=[xmin, xmax],
ylim=[ymin, ymax])
gdf.plot(ax=ax1, transform=projection)
format_ax(ax1, projection, xlim, ylim)
Grider = ax1.gridlines(draw_labels=True)
Grider.xformatter = LONGITUDE_FORMATTER
Grider.yformatter = LATITUDE_FORMATTER
Grider.xlabels_top = False
Grider.ylabels_right = False
# Label axes of a Mercator projection without degree symbols in the labels
# and formatting labels to include 1 decimal place:
ax2 = fig.add_subplot(3, 1, 2,
projection=ccrs.Mercator(),
xlim=[xmin, xmax],
ylim=[ymin, ymax])
gdf.plot(ax=ax2, transform=projection)
format_ax(ax2, projection, xlim, ylim)
Grider = ax2.gridlines(draw_labels=True)
Grider.xformatter = LONGITUDE_FORMATTER
Grider.yformatter = LATITUDE_FORMATTER
Grider.xlabels_top = False
Grider.ylabels_right = False
ax3 = fig.add_subplot(3, 1, 3,
projection=ccrs.Robinson(central_longitude=lon_c,
#central_latitude=lat_c
),
xlim=[xmin, xmax],
ylim=[ymin, ymax])
gdf.plot(ax=ax3, transform=projection)
format_ax(ax3, projection, xlim, ylim)
ax3.set_xticks([-180, -120, -60, 0, 60, 120, 180])
ax3.set_yticks([-78.5, -60, -25.5, 25.5, 60, 80])
ax3.xaxis.set_major_formatter(LONGITUDE_FORMATTER)
ax3.yaxis.set_major_formatter(LATITUDE_FORMATTER)
plt.draw()
return fig, fig.get_axes()
if __name__ == '__main__':
length = 1000
fig, axes = main()
gdf = get_standard_gdf()
xmin, ymin, xmax, ymax = gdf.total_bounds
xoff = 0.3 * (xmax - xmin)
yoff = 0.2 * (ymax - ymin)
for ax in axes:
if hasattr(ax, 'projection'):
x0, x1, y0, y1 = np.ravel(ax.get_extent())
Scaler = Scalebar(ax=ax,
metric_ccrs=ccrs.Geodetic())
Scaler.drawmapscale(lon = xmin+xoff,
lat = ymin + yoff,
length=length,
units = 'km',
barstyle='fancy',
yoffset=0.2 * (ymax - ymin)
)
fig.suptitle('Using Cartopy')
fig.show()
When the above code is run, the scalebar is misplaced in the geoaxes. The scalebar xticks are misplaced, and its yaxis height proportion is also wrong.
Here is an example: the geopandas is plotted in blue. Note that the scalebar is only visible in the second and third geoaxes.

Answer 1

I found a solution for the current problem.
For sake of brevety, the code is presented in here.
Feel free to check it out. The algorithm still requires some adjustment in order to support other cartopy projections.
Meanwhile, it can be applied to PlateCarree projection.