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Commit d4c12285 authored by Daniel Scheffler's avatar Daniel Scheffler
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Merge branch 'revision/revise_coord_trafo' into 'master' 

Revision/revise coord trafo

See merge request !24
parents 9c15a700 c5d501ff
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HISTORY.rst
View file @ d4c12285
......@@ -2,6 +2,18 @@
History
=======
0.16.2 (2020-11-18)
-------------------
* Fixed issue of remaining coverage artifacts after running 'make clean-test.
* Revised coord_trafo.py. This fixes an issue that caused pixelToLatLon() to return Lon/Lat instead of Lat/Lon.
* Fixed mapXY2imXY() and imXY2mapXY().
* Added Test_mapXY2imXY(), Test_imXY2mapXY(), Test_pixelToLatLon(), Test_latLonToPixel().
* Removed GDAL dataset input parameters from some functions.
* Revised code style and some docstrings. Added some typehints.
* Bugfix for always raising a RuntimeWarning in fill_holes_within_poly().
0.16.1 (2020-11-03)
-------------------
......
Makefile
View file @ d4c12285
......@@ -43,10 +43,10 @@ clean-pyc: ## remove Python file artifacts
find . -name '__pycache__' -exec rm -fr {} +
clean-test: ## remove test and coverage artifacts
## don't include 'coverage erase' lib here because clean-test is also executed during package setup and coverage is
## only a test requirement
## don't call coverage erase here because make install calls make clean which calls make clean-test
## -> since make install should run without the test requirements we can't use coverage erase here
rm -fr .tox/
rm -f .coverage
rm -fr .coverage.*
rm -fr htmlcov/
rm -fr nosetests.html
rm -fr nosetests.xml
......
py_tools_ds/geo/coord_calc.py
View file @ d4c12285
......@@ -31,18 +31,15 @@ from shapely.geometry import Polygon
__author__ = "Daniel Scheffler"
def get_corner_coordinates(gdal_ds=None, gt=None, cols=None, rows=None):
def get_corner_coordinates(gt, cols, rows):
"""Returns (ULxy, LLxy, LRxy, URxy) in the same coordinate units like the given geotransform."""
assert gdal_ds or (gt and cols and rows), \
"GEOP.get_corner_coordinates: Missing argument! Please provide either 'gdal_ds' or 'gt', 'cols' AND 'rows'."
gdal_ds_GT = gdal_ds.GetGeoTransform() if gdal_ds else gt
ext = []
xarr = [0, gdal_ds.RasterXSize if gdal_ds else cols]
yarr = [0, gdal_ds.RasterYSize if gdal_ds else rows]
xarr = [0, cols]
yarr = [0, rows]
for px in xarr:
for py in yarr:
x = gdal_ds_GT[0] + (px * gdal_ds_GT[1]) + (py * gdal_ds_GT[2])
y = gdal_ds_GT[3] + (px * gdal_ds_GT[4]) + (py * gdal_ds_GT[5])
x = gt[0] + (px * gt[1]) + (py * gt[2])
y = gt[3] + (px * gt[4]) + (py * gt[5])
ext.append([x, y])
yarr.reverse()
return ext
......
py_tools_ds/geo/coord_trafo.py
View file @ d4c12285
......@@ -24,38 +24,47 @@
import pyproj
import numpy as np
from shapely.ops import transform
from typing import Union # noqa F401 # flake8 issue
from typing import Union, Sequence, List # noqa F401 # flake8 issue
from osgeo import gdal, osr
__author__ = "Daniel Scheffler"
def transform_utm_to_wgs84(easting, northing, zone, south=False):
# type: (float, float, int, bool) -> (float, float)
"""Transform an UTM coordinate to lon, lat, altitude."""
UTM = pyproj.Proj(proj='utm', zone=abs(zone), ellps='WGS84', south=(zone < 0 or south))
UTM = pyproj.Proj(proj='utm',
zone=abs(zone),
ellps='WGS84',
south=(zone < 0 or south))
return UTM(easting, northing, inverse=True)
def get_utm_zone(longitude):
# type: (float) -> int
"""Get the UTM zone corresponding to the given longitude."""
return int(1 + (longitude + 180.0) / 6.0)
def transform_wgs84_to_utm(lon, lat, zone=None):
""" returns easting, northing, altitude. If zone is not set it is derived automatically.
:param lon:
:param lat:
:param zone:
# type: (float, float, int) -> (float, float)
"""Return easting, northing, altitude for the given Lon/Lat coordinate.
:param lon: longitude
:param lat: latitude
:param zone: UTM zone (if not set it is derived automatically)
"""
if not (-180. <= lon <= 180. and -90. <= lat <= 90.):
raise ValueError((lon, lat), 'Input coordinates for transform_wgs84_to_utm() out of range.')
UTM = pyproj.Proj(proj='utm', zone=get_utm_zone(lon) if zone is None else zone, ellps='WGS84')
UTM = pyproj.Proj(proj='utm',
zone=get_utm_zone(lon) if zone is None else zone,
ellps='WGS84')
return UTM(lon, lat)
def transform_any_prj(prj_src, prj_tgt, x, y):
"""Transforms X/Y data from any source projection to any target projection.
# type: (Union[str, int], Union[str, int], float, float) -> (float, float)
"""Transform X/Y data from any source projection to any target projection.
:param prj_src: GDAL projection as WKT string or EPSG code ('epsg:1234' or <EPSG_int>)
:param prj_tgt: GDAL projection as WKT string or EPSG code ('epsg:1234' or <EPSG_int>)
......@@ -70,7 +79,9 @@ def transform_any_prj(prj_src, prj_tgt, x, y):
def transform_coordArray(prj_src, prj_tgt, Xarr, Yarr, Zarr=None):
"""Transforms geolocation arrays from one projection into another.
# type: (str, str, np.ndarray, np.ndarray, np.ndarray) -> Sequence[np.ndarray]
"""Transform a geolocation array from one projection into another.
HINT: This function is faster than transform_any_prj but works only for geolocation arrays.
:param prj_src: WKT string
......@@ -113,166 +124,136 @@ def transform_coordArray(prj_src, prj_tgt, Xarr, Yarr, Zarr=None):
def mapXY2imXY(mapXY, gt):
# type: (tuple, Union[list, tuple]) -> Union[tuple, np.ndarray]
"""Translates given geo coordinates into pixel locations according to the given image geotransform.
# type: (Union[tuple, np.ndarray], Sequence) -> Union[tuple, np.ndarray]
"""Translate the given geo coordinates into pixel locations according to the given image geotransform.
:param mapXY: <tuple, np.ndarray> The geo coordinates to be translated in the form (x,y) or as np.ndarray [Nx1].
:param gt: <list> GDAL geotransform
:returns: <tuple, np.ndarray> image coordinate tuple X/Y (column, row) or np.ndarray [Nx2]
"""
if isinstance(mapXY, np.ndarray):
if mapXY.ndim == 1:
ndim = mapXY.ndim
if ndim == 1:
mapXY = mapXY.reshape(1, 2)
assert mapXY.shape[1] == 2, 'An array in shape [Nx2] is needed. Got shape %s.' % mapXY.shape
imXY = np.empty_like(mapXY)
imXY = np.empty_like(mapXY, dtype=np.float)
imXY[:, 0] = (mapXY[:, 0] - gt[0]) / gt[1]
imXY[:, 1] = (mapXY[:, 1] - gt[3]) / gt[5]
return imXY
return imXY if ndim > 1 else imXY.flatten()
else:
return (mapXY[0] - gt[0]) / gt[1], (mapXY[1] - gt[3]) / gt[5]
return (mapXY[0] - gt[0]) / gt[1],\
(mapXY[1] - gt[3]) / gt[5]
def imXY2mapXY(imXY, gt):
# type: (tuple, Union[list, tuple]) -> Union[tuple, np.ndarray]
"""Translates given pixel locations into geo coordinates according to the given image geotransform.
# type: (Union[tuple, np.ndarray], Sequence) -> Union[tuple, np.ndarray]
"""Translate the given pixel X/Y locations into geo coordinates according to the given image geotransform.
:param imXY: <tuple, np.ndarray> The image coordinates to be translated in the form (x,y) or as np.ndarray [Nx1].
:param gt: <list> GDAL geotransform
:returns: <tuple, np.ndarray> geo coordinate tuple X/Y (mapX, mapY) or np.ndarray [Nx2]
"""
if isinstance(imXY, np.ndarray):
ndim = imXY.ndim
if imXY.ndim == 1:
imXY = imXY.reshape(1, 2)
assert imXY.shape[1] == 2, 'An array in shape [Nx2] is needed. Got shape %s.' % imXY.shape
imXY = np.empty_like(imXY)
imXY[:, 0] = gt[0] + imXY[:, 0] * abs(gt[1])
imXY[:, 1] = gt[3] - imXY[:, 1] * abs(gt[5])
return imXY
mapXY = np.empty_like(imXY, dtype=np.float)
mapXY[:, 0] = gt[0] + imXY[:, 0] * abs(gt[1])
mapXY[:, 1] = gt[3] - imXY[:, 1] * abs(gt[5])
return mapXY if ndim > 1 else mapXY.flatten()
else:
return (gt[0] + imXY[0] * abs(gt[1])), (gt[3] - imXY[1] * abs(gt[5]))
return (gt[0] + imXY[0] * abs(gt[1])),\
(gt[3] - imXY[1] * abs(gt[5]))
def mapYX2imYX(mapYX, gt):
return (mapYX[0] - gt[3]) / gt[5], (mapYX[1] - gt[0]) / gt[1]
return (mapYX[0] - gt[3]) / gt[5],\
(mapYX[1] - gt[0]) / gt[1]
def imYX2mapYX(imYX, gt):
return gt[3] - (imYX[0] * abs(gt[5])), gt[0] + (imYX[1] * gt[1])
return gt[3] - (imYX[0] * abs(gt[5])),\
gt[0] + (imYX[1] * gt[1])
def pixelToMapYX(pixelCoords, path_im=None, geotransform=None, projection=None):
assert path_im or geotransform and projection, \
"pixelToMapYX: Missing argument! Please provide either 'path_im' or 'geotransform' AND 'projection'."
if geotransform and projection:
gt, proj = geotransform, projection
else:
ds = gdal.Open(path_im)
gt, proj = ds.GetGeoTransform(), ds.GetProjection()
def pixelToMapYX(pixelCoords, geotransform, projection):
# MapXYPairs = imXY2mapXY(np.array(pixelPairs), geotransform)
# Create a spatial reference object
srs = osr.SpatialReference()
srs.ImportFromWkt(proj)
srs.ImportFromWkt(projection)
# Set up the coordinate transformation object
ct = osr.CoordinateTransformation(srs, srs)
mapYmapXPairs = []
pixelCoords = [pixelCoords] if not type(pixelCoords[0]) in [list, tuple] else pixelCoords
for point in pixelCoords:
# Translate the pixel pairs into untranslated points
u_mapX = point[0] * gt[1] + gt[0]
u_mapY = point[1] * gt[5] + gt[3]
# Transform the points to the space
(mapX, mapY, holder) = ct.TransformPoint(u_mapX, u_mapY)
# Add the point to our return array
mapYmapXPairs.append([mapY, mapX])
mapXYPairs = [ct.TransformPoint(pixX * geotransform[1] + geotransform[0],
pixY * geotransform[5] + geotransform[3])[:2]
for pixX, pixY in pixelCoords]
return mapYmapXPairs
return [[mapY, mapX] for mapX, mapY in mapXYPairs]
def pixelToLatLon(pixelPairs, path_im=None, geotransform=None, projection=None):
"""The following method translates given pixel locations into latitude/longitude locations on a given GEOTIF
This method does not take into account pixel size and assumes a high enough
image resolution for pixel size to be insignificant
def pixelToLatLon(pixelPairs, geotransform, projection):
# type: (List[Sequence[float, float]], Sequence, str) -> List[Sequence[float, float]]
"""Translate the given pixel X/Y locations into latitude/longitude locations.
:param pixelPairs: Image coordinate pairs to be translated in the form [[x1,y1],[x2,y2]]
:param path_im: The file location of the input image
:param geotransform: GDAL GeoTransform
:param projection: GDAL Projection
:param projection: WKT string
:returns: The lat/lon translation of the pixel pairings in the form [[lat1,lon1],[lat2,lon2]]
"""
assert path_im or geotransform and projection, \
"GEOP.pixelToLatLon: Missing argument! Please provide either 'path_im' or 'geotransform' AND 'projection'."
if geotransform and projection:
gt, proj = geotransform, projection
else:
ds = gdal.Open(path_im)
gt, proj = ds.GetGeoTransform(), ds.GetProjection()
MapXYPairs = imXY2mapXY(np.array(pixelPairs), geotransform)
lons, lats = transform_any_prj(projection, 4326, MapXYPairs[:, 0], MapXYPairs[:, 1])
# validate output lat/lon values
if not (-180 <= np.min(lons) <= 180) or not (-180 <= np.max(lons) <= 180):
raise RuntimeError('Output longitude values out of bounds.')
if not (-90 <= np.min(lats) <= 90) or not (-90 <= np.max(lats) <= 90):
raise RuntimeError('Output latitudes values out of bounds.')
LatLonPairs = np.vstack([lats, lons]).T.tolist()
return LatLonPairs
# Create a spatial reference object for the dataset
srs = osr.SpatialReference()
srs.ImportFromWkt(proj)
# Set up the coordinate transformation object
srsLatLong = srs.CloneGeogCS()
ct = osr.CoordinateTransformation(srs, srsLatLong)
# Go through all the point pairs and translate them to pixel pairings
latLonPairs = []
for point in pixelPairs:
# Translate the pixel pairs into untranslated points
ulon = point[0] * gt[1] + gt[0]
ulat = point[1] * gt[5] + gt[3]
# Transform the points to the space
(lon, lat, holder) = ct.TransformPoint(ulon, ulat)
# Add the point to our return array
latLonPairs.append([lat, lon])
return latLonPairs
def latLonToPixel(latLonPairs, path_im=None, geotransform=None, projection=None):
"""The following method translates given latitude/longitude pairs into pixel locations on a given GEOTIF
This method does not take into account pixel size and assumes a high enough
image resolution for pixel size to be insignificant
def latLonToPixel(latLonPairs, geotransform, projection):
# type: (List[Sequence[float, float]], Sequence, str) -> List[Sequence[float, float]]
"""Translate the given latitude/longitude pairs into pixel X/Y locations.
:param latLonPairs: The decimal lat/lon pairings to be translated in the form [[lat1,lon1],[lat2,lon2]]
:param path_im: The file location of the input image
:param geotransform: GDAL GeoTransform
:param projection: GDAL Projection
:param projection: WKT string
:return: The pixel translation of the lat/lon pairings in the form [[x1,y1],[x2,y2]]
"""
assert path_im or geotransform and projection, \
"GEOP.latLonToPixel: Missing argument! Please provide either 'path_im' or 'geotransform' AND 'projection'."
if geotransform and projection:
gt, proj = geotransform, projection
else:
ds = gdal.Open(path_im)
gt, proj = ds.GetGeoTransform(), ds.GetProjection()
# Load the image dataset
# Create a spatial reference object for the dataset
srs = osr.SpatialReference()
srs.ImportFromWkt(proj)
# Set up the coordinate transformation object
srsLatLong = srs.CloneGeogCS()
ct = osr.CoordinateTransformation(srsLatLong, srs)
# Go through all the point pairs and translate them to latitude/longitude pairings
pixelPairs = []
for point in latLonPairs:
# Change the point locations into the GeoTransform space
(point[1], point[0], holder) = ct.TransformPoint(point[1], point[0])
# Translate the x and y coordinates into pixel values
x = (point[1] - gt[0]) / gt[1]
y = (point[0] - gt[3]) / gt[5]
# Add the point to our return array
pixelPairs.append([int(x), int(y)])
latLonArr = np.array(latLonPairs)
# validate input lat/lon values
if not (-180 <= np.min(latLonArr[:, 1]) <= 180) or not (-180 <= np.max(latLonArr[:, 1]) <= 180):
raise ValueError('Longitude value out of bounds.')
if not (-90 <= np.min(latLonArr[:, 0]) <= 90) or not (-90 <= np.max(latLonArr[:, 0]) <= 90):
raise ValueError('Latitude value out of bounds.')
mapXs, mapYs = transform_any_prj(4326, projection, latLonArr[:, 1], latLonArr[:, 0])
imXYarr = mapXY2imXY(np.vstack([mapXs, mapYs]).T, geotransform)
pixelPairs = imXYarr.tolist()
return pixelPairs
def lonlat_to_pixel(lon, lat, inverse_geo_transform):
"""Translates the given lon, lat to the grid pixel coordinates in data array (zero start)"""
"""Translate the given lon, lat to the grid pixel coordinates in data array (zero start)."""
# transform to utm
utm_x, utm_y, utm_z = transform_wgs84_to_utm(lon, lat)
# apply inverse geo tranform
utm_x, utm_y = transform_wgs84_to_utm(lon, lat)
# apply inverse geo transform
pixel_x, pixel_y = gdal.ApplyGeoTransform(inverse_geo_transform, utm_x, utm_y)
pixel_x = int(pixel_x) - 1 # adjust to 0 start for array
pixel_y = int(pixel_y) - 1 # adjust to 0 start for array
return pixel_x, abs(pixel_y) # y pixel is likly a negative value given geo_transform
......@@ -291,7 +272,7 @@ def transform_GCPlist(gcpList, prj_src, prj_tgt):
def reproject_shapelyGeometry(shapelyGeometry, prj_src, prj_tgt):
"""Reprojects any shapely geometry from one projection to another.
"""Reproject any shapely geometry from one projection to another.
:param shapelyGeometry: any shapely geometry instance
:param prj_src: GDAL projection as WKT string or EPSG code ('epsg:1234' or <EPSG_int>)
......
py_tools_ds/geo/projection.py
View file @ d4c12285
......@@ -156,11 +156,11 @@ def WKT2EPSG(wkt):
return CRS.from_wkt(wkt.replace('\n', '').replace('\r', '').replace(' ', '')).to_epsg()
def get_UTMzone(ds=None, prj=None):
assert ds or prj, "Specify at least one of the arguments 'ds' or 'prj'"
def get_UTMzone(prj):
# type: (str) -> Union[int, None]
if isProjectedOrGeographic(prj) == 'projected':
srs = osr.SpatialReference()
srs.ImportFromWkt(ds.GetProjection() if ds else prj)
srs.ImportFromWkt(prj)
return srs.GetUTMZone()
else:
return None
......
py_tools_ds/geo/raster/reproject.py
View file @ d4c12285
......@@ -132,7 +132,6 @@ def warp_ndarray_rasterio(ndarray, in_gt, in_prj, out_prj, out_gt=None, outRowsC
else: # outRowsCols is None and outUL is None: use in_gt
left, bottom, right, top = gt2bounds(in_gt, rows, cols)
# ,im_xmax,im_ymin,im_ymax = corner_coord_to_minmax(get_corner_coordinates(self.ds_im2shift))
elif out_extent:
left, bottom, right, top = out_extent
......@@ -158,8 +157,8 @@ def warp_ndarray_rasterio(ndarray, in_gt, in_prj, out_prj, out_gt=None, outRowsC
raise NotImplementedError('Different projections are currently not supported.')
else: # ('projected','geographic')
px_size_LatLon = np.array(pixelToLatLon([1, 1], geotransform=in_gt, projection=in_prj)) - \
np.array(pixelToLatLon([0, 0], geotransform=in_gt, projection=in_prj))
px_size_LatLon = np.array(pixelToLatLon([[1, 1]], geotransform=in_gt, projection=in_prj)) - \
np.array(pixelToLatLon([[0, 0]], geotransform=in_gt, projection=in_prj))
out_res = tuple(reversed(abs(px_size_LatLon)))
print('OUT_RES NOCHMAL CHECKEN: ', out_res)
......
py_tools_ds/geo/vector/conversion.py
View file @ d4c12285
......@@ -56,8 +56,18 @@ def shapelyImPoly_to_shapelyMapPoly(shapelyBox, gt):
def shapelyBox2BoxYX(shapelyBox, coord_type='image'):
xmin, ymin, xmax, ymax = shapelyBox.bounds
assert coord_type in ['image', 'map']
UL_YX, UR_YX, LR_YX, LL_YX = ((ymin, xmin), (ymin, xmax), (ymax, xmax), (ymax, xmin)) if coord_type == 'image' else\
((ymax, xmin), (ymax, xmax), (ymin, xmax), (ymin, xmin))
if coord_type == 'image':
UL_YX = ymin, xmin
UR_YX = ymin, xmax
LR_YX = ymax, xmax
LL_YX = ymax, xmin
else:
UL_YX = ymax, xmin
UR_YX = ymax, xmax
LR_YX = ymin, xmax
LL_YX = ymin, xmin
return UL_YX, UR_YX, LR_YX, LL_YX
......
py_tools_ds/geo/vector/topology.py
View file @ d4c12285
......@@ -198,7 +198,7 @@ def fill_holes_within_poly(poly):
GDF_row.geometry.equals(largest_poly_filled),
axis=1)
if False in gdf.within_or_equal:
if False in gdf.within_or_equal.values:
n_disjunct_polys = int(np.sum(~gdf.within_or_equal))
warnings.warn(RuntimeWarning('The given MultiPolygon contains %d disjunct polygone(s) outside of the '
'largest polygone. fill_holes_within_poly() will only return the largest '
......
tests/test_geo/test_coord_trafo.py
View file @ d4c12285
......@@ -34,13 +34,53 @@ from unittest import TestCase, main
from shapely.geometry import Polygon
import numpy as np
from py_tools_ds.geo.coord_trafo import reproject_shapelyGeometry, transform_any_prj
poly_local = Polygon([(5708.2, -3006), (5708, -3262), (5452, -3262), (5452, -3006), (5708, -3006)])
ll_x, ll_y = (10.701359, 47.54536)
utm_x, utm_y = (628023.1302739962, 5267173.503313034)
from py_tools_ds.geo.projection import EPSG2WKT
from py_tools_ds.geo.coord_trafo import (
imXY2mapXY, mapXY2imXY,
pixelToLatLon, latLonToPixel,
reproject_shapelyGeometry,
transform_any_prj,
get_utm_zone
)
poly_local = Polygon([(5708, -3006),
(5708, -3262),
(5452, -3262),
(5452, -3006),
(5708, -3006)])
ll_x, ll_y = (10.701359,
47.54536)
utm_x, utm_y = (628023.1302739962,
5267173.503313034)
geotransform_utm = (331185.0, 30.0, -0.0, 5840115.0, -0.0, -30.0)
wkt_utm = \
"""
PROJCS["WGS 84 / UTM zone 33N",
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84", 6378137, 298.257223563,
AUTHORITY["EPSG", "7030"]],
AUTHORITY["EPSG", "6326"]],
PRIMEM["Greenwich", 0,
AUTHORITY["EPSG", "8901"]],
UNIT["degree", 0.0174532925199433,
AUTHORITY["EPSG", "9122"]],
AUTHORITY["EPSG", "4326"]],
PROJECTION["Transverse_Mercator"],
PARAMETER["latitude_of_origin", 0],
PARAMETER["central_meridian", 15],
PARAMETER["scale_factor", 0.9996],
PARAMETER["false_easting", 500000],
PARAMETER["false_northing", 0],
UNIT["metre", 1,
AUTHORITY["EPSG", "9001"]],
AXIS["Easting", EAST],
AXIS["Northing", NORTH],
AUTHORITY["EPSG", "32633"]]
"""
wkt_utm = ' '.join(wkt_utm.split())
class Test_reproject_shapelyGeometry(TestCase):
......@@ -60,5 +100,150 @@ class Test_transform_any_prj(TestCase):
np.array([utm_x, utm_y]))))
def get_utm_gt_prj_from_lonlat(lon, lat):
utmepsg = int(f"32{6 if lat > 0 else 7}{get_utm_zone(lon)}")
utmx, utmy = transform_any_prj(4326, utmepsg, lon, lat)
gt = (utmx, 30, 0, utmy, 0, -30)
prj = EPSG2WKT(utmepsg)
return gt, prj
class Test_mapXY2imXY(TestCase):
def test_singlecoord_tuple_at_origin(self):
out = mapXY2imXY((331185.0, 5840115.0), geotransform_utm)
self.assertIsInstance(out, tuple)
self.assertEqual(out, (0, 0))
def test_singlecoord_tuple_at_1_1(self):
out = mapXY2imXY((331215.0, 5840085.0), geotransform_utm)
self.assertIsInstance(out, tuple)
self.assertEqual(out, (1, 1))
def test_singlecoord_nparray_at_1_1(self):
out = mapXY2imXY(np.array([331215.0, 5840085.0]), geotransform_utm)
self.assertIsInstance(out, np.ndarray)
self.assertTrue(np.array_equal(out, np.array([1, 1])))
def test_multicoords_nparray(self):
out = mapXY2imXY(np.array([[331185.0, 5840115.0],
[331215.0, 5840085.0]]), geotransform_utm)
self.assertIsInstance(out, np.ndarray)
self.assertTrue(np.array_equal(out, np.array([[0, 0], [1, 1]])))
def test_tuple_ndarray_outputConsistency(self):
tupleout = mapXY2imXY((331215.0, 5840085.0), geotransform_utm)
npout = mapXY2imXY(np.array([331215.0, 5840085.0]), geotransform_utm)
self.assertTrue(np.array_equal(np.array(tupleout),
npout))
class Test_imXY2mapXY(TestCase):
def test_singlecoord_tuple_at_origin(self):
out = imXY2mapXY((0, 0), geotransform_utm)
self.assertIsInstance(out, tuple)
self.assertEqual(out, (331185.0, 5840115.0))
def test_singlecoord_tuple_at_1_1(self):
out = imXY2mapXY((1, 1), geotransform_utm)
self.assertIsInstance(out, tuple)
self.assertEqual(out, (331215.0, 5840085.0))
def test_singlecoord_nparray_at_1_1(self):
out = imXY2mapXY(np.array([1, 1]), geotransform_utm)
self.assertIsInstance(out, np.ndarray)
self.assertTrue(np.array_equal(out, np.array([331215.0, 5840085.0])))
def test_multicoords_nparray(self):
out = imXY2mapXY(np.array([[0, 0], [1, 1]]), geotransform_utm)
self.assertIsInstance(out, np.ndarray)
self.assertTrue(np.array_equal(out, np.array([[331185.0, 5840115.0],
[331215.0, 5840085.0]])))
def test_tuple_ndarray_outputConsistency(self):
tupleout = imXY2mapXY((1, 1), geotransform_utm)
npout = imXY2mapXY(np.array([1, 1]), geotransform_utm)
self.assertTrue(np.array_equal(np.array(tupleout),
npout))
class Test_pixelToLatLon(TestCase):
def test_standard_case(self):
latlonPairs = pixelToLatLon([(0, 0)], geotransform=geotransform_utm, projection=wkt_utm)
self.assertIsInstance(latlonPairs, list)
self.assertEqual(len(latlonPairs), 1)
def test_negative_imcoords(self):
latlonPairs = pixelToLatLon([(-10, -10)], geotransform=geotransform_utm, projection=wkt_utm)
self.assertIsInstance(latlonPairs, list)
self.assertEqual(len(latlonPairs), 1)
def test_negative_lon(self):
for lon, lat in [(-1, 30), (-89, -30), (-90, -30