# !pip install cartopy scipy
# !pip install geemap

%pylab inline

import ee
import geemap
import matplotlib.pyplot as plt

# import the cartoee functionality from geemap
from geemap import cartoee

geemap.ee_initialize()

# get an image
srtm = ee.Image("CGIAR/SRTM90_V4")

# geospatial region in format [E,S,W,N]
region = [180, -60, -180, 85]  # define bounding box to request data
vis = {"min": 0, "max": 3000}  # define visualization parameters for image

fig = plt.figure(figsize=(15, 10))

# use cartoee to get a map
ax = cartoee.get_map(srtm, region=region, vis_params=vis)

# add a colorbar to the map using the visualization params we passed to the map
cartoee.add_colorbar(ax, vis, loc="bottom", label="Elevation", orientation="horizontal")

# add gridlines to the map at a specified interval
cartoee.add_gridlines(ax, interval=[60, 30], linestyle=":")

# add coastlines using the cartopy api
ax.coastlines(color="red")

plt.show()

fig = plt.figure(figsize=(15, 10))

cmap = "gist_earth"  # colormap we want to use
# cmap = "terrain"

# use cartoee to get a map
ax = cartoee.get_map(srtm, region=region, vis_params=vis, cmap=cmap)

# add a colorbar to the map using the visualization params we passed to the map
cartoee.add_colorbar(
    ax, vis, cmap=cmap, loc="right", label="Elevation", orientation="vertical"
)

# add gridlines to the map at a specified interval
cartoee.add_gridlines(ax, interval=[60, 30], linestyle="--")

# add coastlines using the cartopy api
ax.coastlines(color="red")

ax.set_title(label="Global Elevation Map", fontsize=15)

plt.show()

# get a landsat image to visualize
image = ee.Image("LANDSAT/LC08/C01/T1_SR/LC08_044034_20140318")

# define the visualization parameters to view
vis = {"bands": ["B5", "B4", "B3"], "min": 0, "max": 5000, "gamma": 1.3}

fig = plt.figure(figsize=(15, 10))

# use cartoee to get a map
ax = cartoee.get_map(image, vis_params=vis)

# pad the view for some visual appeal
cartoee.pad_view(ax)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.5, xtick_rotation=45, linestyle=":")

# add the coastline
ax.coastlines(color="yellow")

plt.show()

fig = plt.figure(figsize=(15, 10))

# here is the bounding box of the map extent we want to use
# formatted a [E,S,W,N]
zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178]

# plot the map over the region of interest
ax = cartoee.get_map(image, vis_params=vis, region=zoom_region)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=45, linestyle=":")

# add coastline
ax.coastlines(color="yellow")

plt.show()

fig = plt.figure(figsize=(15, 10))

# here is the bounding box of the map extent we want to use
# formatted a [E,S,W,N]
zoom_region = [-121.8025, 37.3458, -122.6265, 37.9178]

# plot the map over the region of interest
ax = cartoee.get_map(image, vis_params=vis, region=zoom_region)

# add the gridlines and specify that the xtick labels be rotated 45 degrees
cartoee.add_gridlines(ax, interval=0.15, xtick_rotation=45, linestyle=":")

# add coastline
ax.coastlines(color="yellow")

# add north arrow
cartoee.add_north_arrow(
    ax, text="N", xy=(0.05, 0.25), text_color="white", arrow_color="white", fontsize=20
)

# add scale bar
cartoee.add_scale_bar_lite(
    ax, length=10, xy=(0.1, 0.05), fontsize=20, color="white", unit="km"
)

ax.set_title(label="Landsat False Color Composite (Band 5/4/3)", fontsize=15)

plt.show()