/usr/lib/python2.7/dist-packages/cartopy/tests/mpl/test_images.py is in python-cartopy 0.14.2+dfsg1-2build3.
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#
# This file is part of cartopy.
#
# cartopy is free software: you can redistribute it and/or modify it under
# the terms of the GNU Lesser General Public License as published by the
# Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# cartopy is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with cartopy. If not, see <https://www.gnu.org/licenses/>.
from __future__ import (absolute_import, division, print_function)
import os
import types
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image
import shapely.geometry as sgeom
from cartopy import config
import cartopy.crs as ccrs
import cartopy.io.img_tiles as cimgt
from cartopy.tests.mpl import ImageTesting
import cartopy.tests.test_img_nest as ctest_nest
import cartopy.tests.test_img_tiles as ctest_tiles
NATURAL_EARTH_IMG = os.path.join(config["repo_data_dir"],
'raster', 'natural_earth',
'50-natural-earth-1-downsampled.png')
REGIONAL_IMG = os.path.join(config['repo_data_dir'], 'raster', 'sample',
'Miriam.A2012270.2050.2km.jpg')
# We have an exceptionally large tolerance for the web_tiles test.
# The basemap changes on a regular basis (for seasons) and we really only
# care that it is putting images onto the map which are roughly correct.
@ImageTesting(['web_tiles'], tolerance=2)
def test_web_tiles():
extent = [-15, 0.1, 50, 60]
target_domain = sgeom.Polygon([[extent[0], extent[1]],
[extent[2], extent[1]],
[extent[2], extent[3]],
[extent[0], extent[3]],
[extent[0], extent[1]]])
map_prj = cimgt.GoogleTiles().crs
ax = plt.subplot(3, 2, 1, projection=map_prj)
gt = cimgt.GoogleTiles()
gt._image_url = types.MethodType(ctest_tiles.GOOGLE_IMAGE_URL_REPLACEMENT,
gt)
img, extent, origin = gt.image_for_domain(target_domain, 1)
ax.imshow(np.array(img), extent=extent, transform=gt.crs,
interpolation='bilinear', origin=origin)
ax.coastlines(color='white')
ax = plt.subplot(3, 2, 2, projection=map_prj)
qt = cimgt.QuadtreeTiles()
img, extent, origin = qt.image_for_domain(target_domain, 1)
ax.imshow(np.array(img), extent=extent, transform=qt.crs,
interpolation='bilinear', origin=origin)
ax.coastlines(color='white')
ax = plt.subplot(3, 2, 3, projection=map_prj)
mq_osm = cimgt.MapQuestOSM()
img, extent, origin = mq_osm.image_for_domain(target_domain, 1)
ax.imshow(np.array(img), extent=extent, transform=mq_osm.crs,
interpolation='bilinear', origin=origin)
ax.coastlines()
ax = plt.subplot(3, 2, 4, projection=map_prj)
mq_oa = cimgt.MapQuestOpenAerial()
img, extent, origin = mq_oa.image_for_domain(target_domain, 1)
ax.imshow(np.array(img), extent=extent, transform=mq_oa.crs,
interpolation='bilinear', origin=origin)
ax.coastlines()
ax = plt.subplot(3, 2, 5, projection=map_prj)
osm = cimgt.OSM()
img, extent, origin = osm.image_for_domain(target_domain, 1)
ax.imshow(np.array(img), extent=extent, transform=osm.crs,
interpolation='bilinear', origin=origin)
ax.coastlines()
@ImageTesting(['image_nest'], tolerance=1.5)
def test_image_nest():
nest_z0_z1 = ctest_nest.gen_nest()
ax = plt.axes(projection=ccrs.Mercator())
shper_globe = ccrs.Globe(semimajor_axis=np.rad2deg(1))
spher_merc = ccrs.Mercator(globe=shper_globe)
ax.set_extent([-45, 45, -45, 90], spher_merc)
ax.coastlines()
ax.add_image(nest_z0_z1, 'aerial z1 test')
@ImageTesting(['image_merge'])
def test_image_merge():
# tests the basic image merging functionality
tiles = []
for i in range(1, 4):
for j in range(0, 3):
tiles.append((i, j, 2))
gt = cimgt.GoogleTiles()
gt._image_url = types.MethodType(ctest_tiles.GOOGLE_IMAGE_URL_REPLACEMENT,
gt)
images_to_merge = []
for tile in tiles:
img, extent, origin = gt.get_image(tile)
img = np.array(img)
x = np.linspace(extent[0], extent[1], img.shape[1], endpoint=False)
y = np.linspace(extent[2], extent[3], img.shape[0], endpoint=False)
images_to_merge.append([img, x, y, origin])
img, extent, origin = cimgt._merge_tiles(images_to_merge)
ax = plt.axes(projection=gt.crs)
ax.set_global()
ax.coastlines()
plt.imshow(img, origin=origin, extent=extent, alpha=0.5)
@ImageTesting(['imshow_natural_earth_ortho'])
def test_imshow():
source_proj = ccrs.PlateCarree()
img = plt.imread(NATURAL_EARTH_IMG)
# Convert the image to a byte array, rather than float, which is the
# form that JPG images would be loaded with imread.
img = (img * 255).astype('uint8')
ax = plt.axes(projection=ccrs.Orthographic())
ax.imshow(img, origin='upper', transform=source_proj,
extent=[-180, 180, -90, 90])
@ImageTesting(['imshow_regional_projected'])
def test_imshow_projected():
source_proj = ccrs.PlateCarree()
img_extent = (-120.67660000000001, -106.32104523100001,
13.2301484511245, 30.766899999999502)
img = plt.imread(REGIONAL_IMG)
ax = plt.axes(projection=ccrs.LambertConformal())
ax.set_extent(img_extent, crs=source_proj)
ax.coastlines(resolution='50m')
ax.imshow(img, extent=img_extent, origin='upper', transform=source_proj)
@ImageTesting(['imshow_natural_earth_ortho'], tolerance=0.7)
def test_stock_img():
ax = plt.axes(projection=ccrs.Orthographic())
ax.stock_img()
@ImageTesting(['imshow_natural_earth_ortho'])
def test_pil_Image():
img = Image.open(NATURAL_EARTH_IMG)
source_proj = ccrs.PlateCarree()
ax = plt.axes(projection=ccrs.Orthographic())
ax.imshow(img, origin='upper', transform=source_proj,
extent=[-180, 180, -90, 90])
if __name__ == '__main__':
import nose
nose.runmodule(argv=['-sv', '--with-doctest'], exit=False)
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