How to use get_map() on a sub-axis?

[ErikSeras]

Hi, Merry Christmas¡.

Exploring some ways to graph GEE images I found this interesting example: Cartopy and Map Layout.

The example uses multiple axes to generate the following image:

I tried some cartoee module functions add_north_arrow() and add_scale_bar() and they work fine, but I don't know how to use get_map() on a sub-axis.

[giswqs]

This is a nice example. Do you have a sample notebook for testing? I like the legend and scale bar. We can probably incorporate these into cartoee.

[ErikSeras]

This is the code that summarizes the example, I tested it in Google Colab.

# Install
! sudo add-apt-repository -y ppa:ubuntugis/ubuntugis-unstable
! sudo apt-get update
! sudo apt-get install libudunits2-dev libgdal-dev libgeos-dev libproj-dev
! sudo apt-get install libprotobuf-dev protobuf-compiler libv8-dev libjq-dev

! pip install OWSLib

! pip install cartopy geemap

# all imports should go here
import pandas as pd
import sys
import os
import subprocess
import datetime
import platform
import datetime
import math

import matplotlib.pyplot as plt
#import seaborn as sb

from geemap import cartoee

import cartopy
import cartopy.crs as ccrs
from cartopy.io.img_tiles import OSM
import cartopy.feature as cfeature
from cartopy.io import shapereader
from cartopy.io.img_tiles import StamenTerrain
from cartopy.io.img_tiles import GoogleTiles
from owslib.wmts import WebMapTileService

from matplotlib.path import Path
import matplotlib.patheffects as PathEffects
from matplotlib import patheffects
import matplotlib.patches as mpatches
import matplotlib.lines as mlines

import numpy as np


fig = plt.figure(figsize=(10,12))

# ------------------------------- Surrounding frame ------------------------------
# set up frame full height, full width of figure, this must be called first

left = -0.05
bottom = -0.05
width = 1.1
height = 1.05
rect = [left,bottom,width,height]
ax3 = plt.axes(rect)



# turn on the spines we want, ie just the surrounding frame
plt.axis('off')


ax3.text(0.01,0.01,'© Don Cameron, 2017: net-analysis.com. '+
            'Map generated at '+datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), fontsize=8)



# ---------------------------------  Main Map -------------------------------------
#
# set up main map almost full height (allow room for title), right 80% of figure
BORDERS2_10m = cartopy.feature.NaturalEarthFeature(
    'cultural', 'admin_1_states_provinces','10m', edgecolor='black', facecolor='none'
)

LAND_10m = cartopy.feature.NaturalEarthFeature(
    'physical', 'land', '10m',edgecolor='face',facecolor=cartopy.feature.COLORS['land']
)

RIVERS_10m = cartopy.feature.NaturalEarthFeature(
    'physical', 'rivers_lake_centerlines', '10m',edgecolor=cartopy.feature.COLORS['water'],facecolor='none'
)

left = 0.2
bottom = 0
width = 0.8
height = 0.90
rect = [left,bottom,width,height]

ax = plt.axes(rect, projection=ccrs.PlateCarree())
ax.set_extent((150, 155, -30, -23))


ax.coastlines(resolution='10m', zorder=2)

#land polygons, including major islands, use cartopy default color
ax.add_feature(LAND_10m)
ax.add_feature(RIVERS_10m)
ax.add_feature(BORDERS2_10m, edgecolor='grey')

ax.stock_img()
# stock image is good enough for example, but OCEAN_10m could be used, but very slow
#       ax.add_feature(OCEAN_10m)

ax.gridlines(draw_labels=True, xlocs=[150, 152, 154, 155])

cartoee.add_scale_bar(ax, length=100, fontsize=16)
cartoee.add_north_arrow(ax, xy = (0.9, 0.95))


# ---------------------------------Locating Map ------------------------
#
# set up index map 20% height, left 16% of figure
left = 0
bottom = 0
width = 0.16
height = 0.2
rect = [left,bottom,width,height]


ax2 = plt.axes(rect, projection=ccrs.PlateCarree())
ax2.set_extent((110,160, -45, -10))
#  ax2.set_global()  will show the whole world as context

ax2.coastlines(resolution='110m', zorder=2)
ax2.add_feature(cfeature.LAND)
ax2.add_feature(cfeature.OCEAN)

ax2.gridlines()


lon0,lon1,lat0,lat1 = ax.get_extent()
box_x = [lon0, lon1, lon1, lon0, lon0]
box_y = [lat0, lat0, lat1, lat1, lat0]

plt.plot(box_x, box_y, color='red',  transform=ccrs.Geodetic())


# -------------------------------- Title -----------------------------
# set up map title top 4% of figure, right 80% of figure

left = 0.2
bottom = 0.95
width = 0.8
height = 0.04
rect = [left,bottom,width,height]
ax6 = plt.axes(rect)
ax6.text(0.5, 0.0,'Multi-Axes Map Example', ha='center', fontsize=20)
plt.axis('off')


# ------------------------------------  Legend -------------------------------------

# legends can be quite long, so set near top of map (0.4 - bottom + 0.5 height = 0.9 - near top)
left = 0
bottom = 0.4
width = 0.16
height = 0.5
rect = [left,bottom,width,height]
rect = [left,bottom,width,height]
ax5 = plt.axes(rect)

# create an array of color patches and associated names for drawing in a legend
# colors are the predefined colors for cartopy features (only for example, Cartopy names are unusual)
colors = sorted(cartopy.feature.COLORS.keys())

# handles is a list of patch handles
handles = []
# names is the list of corresponding labels to appear in the legend
names = []

# for each cartopy defined color, draw a patch, append handle to list, and append color name to names list
for c in colors:
    patch = mpatches.Patch(color=cfeature.COLORS[c], label=c)
    handles.append(patch)
    names.append(c)
#end for

# do some example lines with colors
river = mlines.Line2D([], [], color=cfeature.COLORS['water'], marker='',
                            markersize=15, label='river')
coast = mlines.Line2D([], [], color='black', marker='',
                            markersize=15, label='coast')
bdy  = mlines.Line2D([], [], color='grey', marker='',
                    markersize=15, label='state boundary')
handles.append(river)
handles.append(coast)
handles.append(bdy)
names.append('river')
names.append('coast')
names.append('state boundary')


# create legend
ax5.legend(handles, names)
ax5.set_title('Legend',loc='left')
plt.axis('off')

plt.savefig("test.png", bbox_inches='tight')

plt.show()

[giswqs]

Many thanks for providing the example! I was able to tweak it to plot Earth Engine data. This can probably be incorporated into the cartoee module.

https://github.com/giswqs/geemap/blob/master/examples/notebooks/cartoee_subplots.ipynb

[ErikSeras]

Thank you @giswqs.

[Jack-ee]

Dear Dr. Wu, Happy new year. I followed your example but got these errors (after calling update_package()). Here is the error message. [image: image.png]

…

On Fri, Jan 1, 2021 at 4:57 AM ErikSeras ***@***.***> wrote: Thank you @giswqs <https://github.com/giswqs>. — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#238 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AE5J3HU6VMIDBF2VXGY4YCLSXTQUDANCNFSM4VJNURHQ> .

[giswqs]

Your image attachment does not show up.

[Jack-ee]

[image: Untitled.png]

…

On Fri, Jan 1, 2021 at 9:14 AM Qiusheng Wu ***@***.***> wrote: Your image attachment does not show up. — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#238 (reply in thread)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AE5J3HSHXCTIMS4OD3PNOWDSXUOXVANCNFSM4VJNURHQ> .