def test_a_star_search_snap(input_data_with_nans):
agg, start, goal = input_data_with_nans
# no barriers
barriers = []
# no snap
no_snap_path_agg = a_star_search(agg, start, goal, barriers, 'lon', 'lat')
# no path, all cells in path_agg are nans
np.testing.assert_array_equal(no_snap_path_agg, np.nan)
# set snap_start = True, snap_goal = False
snap_start_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True)
# no path, all cells in path_agg are nans
np.testing.assert_array_equal(snap_start_path_agg, np.nan)
# set snap_start = False, snap_goal = True
snap_goal_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_goal=True)
# no path, all cells in path_agg are nans
np.testing.assert_array_equal(snap_goal_path_agg, np.nan)
def test_a_star_search_connectivity(input_data_with_nans,
result_8_connectivity,
result_4_connectivity):
agg, start, goal = input_data_with_nans
# no barriers
barriers = []
# set snap_start = True, snap_goal = True
# 8-connectivity as default
path_agg_8 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True)
np.testing.assert_allclose(path_agg_8,
result_8_connectivity,
equal_nan=True)
# 4-connectivity
path_agg_4 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True,
connectivity=4)
np.testing.assert_allclose(path_agg_4,
result_4_connectivity,
equal_nan=True)
def test_a_star_search():
agg = xr.DataArray(np.array([[1, 1, 0, 0], [1, 1, 0, 0], [0, 1, 2, 2],
[1, 0, 2, 0], [0, 2, 2, 2]]),
dims=['lat', 'lon'])
height, width = agg.shape
_lon = np.linspace(0, width - 1, width)
_lat = np.linspace(0, height - 1, height)
agg['lon'] = _lon
agg['lat'] = _lat
barriers = []
# no barriers, there always path from a start location to a goal location
for x0 in _lon:
for y0 in _lat:
start = (x0, y0)
for x1 in _lon:
for y1 in _lat:
goal = (x1, y1)
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
assert isinstance(path_agg, xr.DataArray)
assert type(path_agg.values[0][0]) == np.float64
assert path_agg.shape == agg.shape
assert path_agg.dims == agg.dims
assert path_agg.attrs == agg.attrs
for c in path_agg.coords:
assert (path_agg[c] == agg.coords[c]).all()
assert np.nanmax(path_agg) >= 0 and np.nanmin(
path_agg) == 0
barriers = [1]
# set pixels with value 1 as barriers,
# cannot go from (0, 0) to anywhere since it is surrounded by 1s
start = (0, 0)
for x1 in _lon:
for y1 in _lat:
goal = (x1, y1)
if goal != start:
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
assert isinstance(path_agg, xr.DataArray)
assert type(path_agg.values[0][0]) == np.float64
assert path_agg.shape == agg.shape
assert path_agg.dims == agg.dims
assert path_agg.attrs == agg.attrs
for c in path_agg.coords:
assert (path_agg[c] == agg.coords[c]).all()
# no path, all cells in path_agg are nans
assert np.isnan(path_agg).all()
def test_a_star_search_with_barriers(input_data):
agg = input_data
barriers = [1]
# set pixels with value 1 as barriers,
# cannot go from (0, 0) to anywhere since it is surrounded by 1s
start = (0, 0)
for x1 in agg['lon']:
for y1 in agg['lat']:
goal = (y1, x1)
if (goal != start):
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
# no path, all cells in path_agg are nans
expected_results = np.full(agg.shape, np.nan)
general_output_checks(agg, path_agg, expected_results)
def test_a_star_search_no_barriers(input_data):
agg = input_data
barriers = []
# no barriers, there always path from a start location to a goal location
for x0 in agg['lon']:
for y0 in agg['lat']:
start = (y0, x0)
for x1 in agg['lon']:
for y1 in agg['lat']:
goal = (y1, x1)
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
general_output_checks(agg, path_agg)
assert type(path_agg.values[0][0]) == np.float64
if start == goal:
assert np.nanmax(path_agg) == 0
assert np.nanmin(path_agg) == 0
else:
assert np.nanmax(path_agg) > 0
assert np.nanmin(path_agg) == 0
def test_a_star_search():
agg = xr.DataArray(np.array([[0, 1, 0, 0], [1, 1, 0, 0], [0, 1, 2, 2],
[1, 0, 2, 0], [0, 2, 2, 2]]),
dims=['lat', 'lon'])
# add crs for tests
agg = _add_EPSG4326_crs_to_da(agg)
height, width = agg.shape
_lon = np.linspace(0, width - 1, width)
_lat = np.linspace(0, height - 1, height)
agg['lon'] = _lon
agg['lat'] = _lat
barriers = []
# no barriers, there always path from a start location to a goal location
for x0 in _lon:
for y0 in _lat:
start = (x0, y0)
for x1 in _lon:
for y1 in _lat:
goal = (x1, y1)
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
assert isinstance(path_agg, xr.DataArray)
assert type(path_agg.values[0][0]) == np.float64
assert path_agg.shape == agg.shape
assert path_agg.dims == agg.dims
assert path_agg.attrs == agg.attrs
for c in path_agg.coords:
assert (path_agg[c] == agg.coords[c]).all()
if start == goal:
assert np.nanmax(path_agg) == 0 and \
np.nanmin(path_agg) == 0
else:
assert np.nanmax(path_agg) > 0 and \
np.nanmin(path_agg) == 0
barriers = [1]
# set pixels with value 1 as barriers,
# cannot go from (0, 0) to anywhere since it is surrounded by 1s
start = (0, 0)
for x1 in _lon:
for y1 in _lat:
goal = (x1, y1)
if goal != start:
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
assert isinstance(path_agg, xr.DataArray)
assert type(path_agg.values[0][0]) == np.float64
assert path_agg.shape == agg.shape
assert path_agg.dims == agg.dims
assert path_agg.attrs == agg.attrs
for c in path_agg.coords:
assert (path_agg[c] == agg.coords[c]).all()
# no path, all cells in path_agg are nans
assert np.isnan(path_agg).all()
# test with nans
agg = xr.DataArray(np.array([[0, 1, 0, 0], [1, 1, np.nan, 0], [0, 1, 2, 2],
[1, 0, 2, 0], [0, np.nan, 2, 2]]),
dims=['lat', 'lon'])
height, width = agg.shape
_lon = np.linspace(0, width - 1, width)
_lat = np.linspace(0, height - 1, height)
agg['lon'] = _lon
agg['lat'] = _lat
# start and end at a nan pixel, coordinate in (lon, lat) format
# in this example, each pixel is a unit of lon and lat,
# start = (2, 1) corresponds to pixel at (1, 2),
# goal = (1, 4) corresponds to pixel at (4, 1)
start = (2, 1)
goal = (1, 4)
# no barriers
barriers = []
# no snap
no_snap_path_agg = a_star_search(agg, start, goal, barriers, 'lon', 'lat')
# no path, all cells in path_agg are nans
assert np.isnan(no_snap_path_agg).all()
# set snap_start = True, snap_goal = False
snap_start_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True)
# no path, all cells in path_agg are nans
assert np.isnan(snap_start_path_agg).all()
# set snap_start = False, snap_goal = True
snap_goal_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_goal=True)
# no path, all cells in path_agg are nans
assert np.isnan(snap_goal_path_agg).all()
# set snap_start = True, snap_goal = True
# 8-connectivity as default
path_agg_8 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True)
# path exists
expected_result_8 = np.array([[np.nan, np.nan, 0., np.nan],
[np.nan, 1.41421356, np.nan, np.nan],
[np.nan, 2.41421356, np.nan, np.nan],
[np.nan, 3.41421356, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]])
assert ((np.isnan(path_agg_8) & np.isnan(expected_result_8)) |
(abs(path_agg_8 - expected_result_8) <= 1e-5)).all()
# 4-connectivity
path_agg_4 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True,
connectivity=4)
# path exists
expected_result_4 = np.array([[np.nan, 1, 0., np.nan],
[np.nan, 2, np.nan, np.nan],
[np.nan, 3, np.nan, np.nan],
[np.nan, 4, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]])
assert ((np.isnan(path_agg_4) & np.isnan(expected_result_4)) |
(abs(path_agg_4 - expected_result_4) <= 1e-5)).all()
def test_a_star_search():
agg = xr.DataArray(np.array([[0, 1, 0, 0], [1, 1, 0, 0], [0, 1, 2, 2],
[1, 0, 2, 0], [0, 2, 2, 2]]),
dims=['lat', 'lon'])
height, width = agg.shape
_lon = np.linspace(0, width - 1, width)
_lat = np.linspace(height - 1, 0, height)
agg['lon'] = _lon
agg['lat'] = _lat
barriers = []
# no barriers, there always path from a start location to a goal location
for x0 in _lon:
for y0 in _lat:
start = (y0, x0)
for x1 in _lon:
for y1 in _lat:
goal = (y1, x1)
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
general_output_checks(agg, path_agg)
assert type(path_agg.values[0][0]) == np.float64
if start == goal:
assert np.nanmax(path_agg) == 0
assert np.nanmin(path_agg) == 0
else:
assert np.nanmax(path_agg) > 0
assert np.nanmin(path_agg) == 0
barriers = [1]
# set pixels with value 1 as barriers,
# cannot go from (0, 0) to anywhere since it is surrounded by 1s
start = (4, 0)
for x1 in _lon:
for y1 in _lat:
goal = (y1, x1)
if (goal != start):
path_agg = a_star_search(agg, start, goal, barriers, 'lon',
'lat')
# no path, all cells in path_agg are nans
expected_results = np.full(agg.shape, np.nan)
general_output_checks(agg, path_agg, expected_results)
# test with nans
agg = xr.DataArray(np.array([[0, 1, 0, 0], [1, 1, np.nan, 0], [0, 1, 2, 2],
[1, 0, 2, 0], [0, np.nan, 2, 2]]),
dims=['lat', 'lon'])
height, width = agg.shape
_lon = np.linspace(0, width - 1, width)
_lat = np.linspace(0, height - 1, height)
agg['lon'] = _lon
agg['lat'] = _lat
# start and end at a nan pixel, coordinate in (lat, lon) format
start = (1, 2)
goal = (4, 1)
# no barriers
barriers = []
# no snap
no_snap_path_agg = a_star_search(agg, start, goal, barriers, 'lon', 'lat')
# no path, all cells in path_agg are nans
assert np.isnan(no_snap_path_agg).all()
# set snap_start = True, snap_goal = False
snap_start_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True)
# no path, all cells in path_agg are nans
assert np.isnan(snap_start_path_agg).all()
# set snap_start = False, snap_goal = True
snap_goal_path_agg = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_goal=True)
# no path, all cells in path_agg are nans
assert np.isnan(snap_goal_path_agg).all()
# set snap_start = True, snap_goal = True
# 8-connectivity as default
path_agg_8 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True)
# path exists
expected_result_8 = np.array([[np.nan, np.nan, 0., np.nan],
[np.nan, 1.41421356, np.nan, np.nan],
[np.nan, 2.41421356, np.nan, np.nan],
[np.nan, 3.41421356, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]])
assert ((np.isnan(path_agg_8) & np.isnan(expected_result_8)) |
(abs(path_agg_8 - expected_result_8) <= 1e-5)).all()
# 4-connectivity
path_agg_4 = a_star_search(agg,
start,
goal,
barriers,
'lon',
'lat',
snap_start=True,
snap_goal=True,
connectivity=4)
# path exists
expected_result_4 = np.array([[np.nan, 1, 0., np.nan],
[np.nan, 2, np.nan, np.nan],
[np.nan, 3, np.nan, np.nan],
[np.nan, 4, np.nan, np.nan],
[np.nan, np.nan, np.nan, np.nan]])
assert ((np.isnan(path_agg_4) & np.isnan(expected_result_4)) |
(abs(path_agg_4 - expected_result_4) <= 1e-5)).all()