def test_crop_vector_null(self):
"""Test case where vector intersection is null"""
source_path = os.path.join(testfile_path, '2states.geojson')
source = gaia.create(source_path)
tool_path = os.path.join(testfile_path, 'iraq_hospitals.geojson')
tool = gaia.create(tool_path)
cropped = crop(source, tool)
self.assertIsNone(cropped)
def test_crop_rgb_null(self):
"""Test with geometry that does not intersect"""
input_path = os.path.join(testfile_path, 'simplergb.tif')
input_raster = gaia.create(input_path)
input_path = os.path.join(testfile_path, 'iraq_hospitals.geojson')
input_vector = gaia.create(input_path)
cropped = crop(input_raster, input_vector)
self.assertIsNone(cropped)
def test_create_api(self):
"""
Test cropping (within process) for vector inputs
"""
path1 = os.path.join(testfile_path, 'iraq_hospitals.geojson')
path2 = os.path.join(testfile_path, 'baghdad_districts.geojson')
data1 = gaia.create(uri=path1)
data2 = gaia.create(uri=path2)
output = crop(data1, data2)
self.assertEquals(len(output.get_data()), 19)
def test_create_api(self):
"""
Test cropping (within process) for vector inputs
"""
path1 = os.path.join(testfile_path, 'iraq_hospitals.geojson')
path2 = os.path.join(testfile_path, 'baghdad_districts.geojson')
data1 = gaia.create(path1)
data2 = gaia.create(path2)
output = crop(data1, data2)
self.assertEqual(len(output.get_data()), 19)
def test_crop_rgb_bigger(self):
"""Test with geometry partially outside raster bounds"""
input_path = os.path.join(testfile_path, 'simplergb.tif')
input_raster = gaia.create(input_path)
bounds = input_raster.get_metadata().get('bounds').get('coordinates')
bounds = bounds[0]
x = (bounds[0][0] + bounds[2][0]) / 2.0
y = (bounds[0][1] + bounds[2][1]) / 2.0
dx = 1.0 * (bounds[2][0] - bounds[0][0])
dy = 1.0 * (bounds[2][1] - bounds[0][1])
poly = [[
[x, y], [x, y-dy], [x+dx, y-dy], [x+dx, y]
]]
geometry = geojson.Polygon(poly)
crop_geom = gaia.create(geometry)
cropped_raster = crop(input_raster, crop_geom)
self.assertIsNotNone(cropped_raster)
def test_crop_rgb(self):
"""
Test cropping raster data with RGB bands
"""
input_path = os.path.join(testfile_path, 'simplergb.tif')
input_raster = gaia.create(input_path)
# Generate crop geometry from raster bounds
bounds = input_raster.get_metadata().get('bounds').get('coordinates')
bounds = bounds[0]
x = (bounds[0][0] + bounds[2][0]) / 2.0
y = (bounds[0][1] + bounds[2][1]) / 2.0
dx = 0.12 * (bounds[2][0] - bounds[0][0])
dy = 0.16 * (bounds[2][1] - bounds[0][1])
poly = [[[x, y], [x + dx, y + dy], [x - dx, y + dy], [x - dx, y - dy],
[x + dx, y - dy]]]
geometry = geojson.Polygon(poly)
crop_geom = gaia.create(geometry)
cropped_raster = crop(input_raster, crop_geom)
self.assertIsNotNone(cropped_raster)
def crop_task(self, target_file, target_driver, by_file, name):
import gaia
from gaia import preprocess
target_file = copyfile(target_file,
getTempFileNameWithExtention(target_driver))
by_file = copyfile(by_file, getTempFileNameWithExtention('GeoJSON'))
target = gaia.create(target_file)
by_file = gaia.create(by_file)
cropped = preprocess.crop(target, by_file)
tempName = getTempFileNameWithExtention(target_driver, name)
# A bug with geopandas and fiona that throws an error like
# fiona.errors.GeometryTypeValidationError: Record's geometry type does not match collection schema's geometry type: 'MultiPolygon' != 'Polygon'
if (target_driver == 'GeoJSON'):
with open(tempName, 'w') as f:
f.write(cropped.get_data().to_json())
else:
gaia.save(cropped, tempName)
return tempName
def test_crop_rgb(self):
"""
Test cropping raster data with RGB bands
"""
input_path = os.path.join(testfile_path, 'simplergb.tif')
input_raster = gaia.create(input_path)
# Generate crop geometry from raster bounds
bounds = input_raster.get_metadata().get('bounds').get('coordinates')
bounds = bounds[0]
x = (bounds[0][0] + bounds[2][0]) / 2.0
y = (bounds[0][1] + bounds[2][1]) / 2.0
dx = 0.12 * (bounds[2][0] - bounds[0][0])
dy = 0.16 * (bounds[2][1] - bounds[0][1])
poly = [[
[x, y], [x+dx, y+dy], [x-dx, y+dy], [x-dx, y-dy], [x+dx, y-dy]
]]
geometry = geojson.Polygon(poly)
crop_geom = gaia.create(geometry)
cropped_raster = crop(input_raster, crop_geom)
self.assertIsNotNone(cropped_raster)
from __future__ import print_function
import os
from zipfile import ZipFile
import gaia
from gaia import preprocess
src_folder = os.path.dirname(__file__)
data_folder = os.path.join(src_folder, os.pardir, os.pardir, 'tests', 'data')
## Vector crop
print('VECTOR')
# Load 2 datasets
hospitals = gaia.create(os.path.join(data_folder, 'iraq_hospitals.geojson'))
districts = gaia.create(os.path.join(data_folder, 'baghdad_districts.geojson'))
# Apply crop
print('Before crop (vector)', districts.get_data().shape)
vector_crop = preprocess.crop(hospitals, districts)
print('After crop (vector)', vector_crop.get_data().shape)
#print(cropped.get_data().head())
vector_filename = 'cropped.geojson'
gaia.save(vector_crop, vector_filename)
print('Wrote file {}'.format(vector_filename))
# Readback file and print some info
readback = gaia.create(vector_filename)
print('After readback (vector)', readback.get_data().shape)
#print(readback.get_data().head())
# except StopIteration:
# raise GaiaException('User/Private folder not found')
# gaia_list = gc.listFolder(
# private_folder['_id'], parentFolderType='folder', name='gaia')
# try:
# gaia_folder = next(gaia_list)
# except StopIteration:
# # Create folder
# gaia_folder = TBD()
# API option 1: create internal url
datastore_url = datastore.lookup_url('Public/DEM_bare_earth.tif')
print(datastore_url)
dataset = gaia.create(datastore_url)
# API option 2: pass in tuple as the data source
# data_source = (datastore, 'Public/DEM_bare_earth.tif')
# dataset = gaia.create(data_source)
meta = dataset.get_metadata()
print()
print(json.dumps(meta, sort_keys=True, indent=2))
print('Input dataset width {}, height {}'.format(meta['width'],
meta['height']))
# Generate crop geometry (small!)
bounds = meta.get('bounds', {}).get('coordinates')[0]
assert bounds, 'Dataset bounds missing'
# print()
# raise GaiaException('User/Private folder not found')
# gaia_list = gc.listFolder(
# private_folder['_id'], parentFolderType='folder', name='gaia')
# try:
# gaia_folder = next(gaia_list)
# except StopIteration:
# # Create folder
# gaia_folder = TBD()
# API option 1: create internal url
datastore_url = datastore.lookup_url('Public/DEM_bare_earth.tif')
print(datastore_url)
dataset = gaia.create(datastore_url)
# API option 2: pass in tuple as the data source
# data_source = (datastore, 'Public/DEM_bare_earth.tif')
# dataset = gaia.create(data_source)
meta = dataset.get_metadata()
print()
print(json.dumps(meta, sort_keys=True, indent=2))
print('Input dataset width {}, height {}'.format(meta['width'], meta['height']))
# Generate crop geometry (small!)
bounds = meta.get('bounds',{}).get('coordinates')[0]
assert bounds, 'Dataset bounds missing'
# print()
# print(bounds)
from __future__ import print_function
import os
from zipfile import ZipFile
import gaia
from gaia import preprocess
src_folder = os.path.dirname(__file__)
data_folder = os.path.join(src_folder, os.pardir, os.pardir, 'tests', 'data')
## Vector crop
print('VECTOR')
# Load 2 datasets
hospitals = gaia.create(os.path.join(data_folder, 'iraq_hospitals.geojson'))
districts = gaia.create(os.path.join(data_folder, 'baghdad_districts.geojson'))
# Apply crop
print('Before crop (vector)', districts.get_data().shape)
vector_crop = preprocess.crop(hospitals, districts)
print('After crop (vector)', vector_crop.get_data().shape)
#print(cropped.get_data().head())
vector_filename = 'cropped.geojson'
gaia.save(vector_crop, vector_filename)
print('Wrote file {}'.format(vector_filename))
# Readback file and print some info
readback = gaia.create(vector_filename)
print('After readback (vector)', readback.get_data().shape)