def test_prase_header_string_tie_point():
in_str = "* 33922 model_tie_point (6d) (0.0, 0.0, 0.0, 368090.77975000005, 3956071.13823,"
out_dict = geotiff._prase_header_string(in_str)
assert out_dict['tie_point'] == (368090.77975000005, 3956071.13823)
in_str = "* 33922 model_tie_point (6d) (0.0, 0.0, 0.0, 368090.77975000005, 3956071.13823, 0"
out_dict = geotiff._prase_header_string(in_str)
assert out_dict['tie_point'] == (368090.77975000005, 3956071.13823)
def test_prase_header_string_proj_normal(capsys):
in_str = "* 34737 geo_ascii_params (30s) b'WGS 84 / UTM zone 54N|WGS 84|'"
out_dict = geotiff._prase_header_string(in_str)
captured = capsys.readouterr()
assert f"[io][geotiff][GeoCorrd] Comprehense [{in_str}]" in captured.out
assert out_dict['proj'] == pyproj.CRS.from_epsg(32654)
def test_gis2pixel2gis():
geo_head_txt = """
TIFF file: 200423_G_M600pro_transparent_mosaic_group1.tif, 411 MiB, little endian, bigtiff
Series 0: 31255x19436x4, uint8, YXS, 1 pages, not mem-mappable
Page 0: 31255x19436x4, uint8, 8 bit, rgb, lzw
* 256 image_width (1H) 19436
* 257 image_length (1H) 31255
* 258 bits_per_sample (4H) (8, 8, 8, 8)
* 259 compression (1H) 5
* 262 photometric (1H) 2
* 273 strip_offsets (31255Q) (500650, 501114, 501578, 502042, 502506, 502970, 5
* 277 samples_per_pixel (1H) 4
* 278 rows_per_strip (1H) 1
* 279 strip_byte_counts (31255Q) (464, 464, 464, 464, 464, 464, 464, 464, 464,
* 284 planar_configuration (1H) 1
* 305 software (12s) b'pix4dmapper'
* 317 predictor (1H) 2
* 338 extra_samples (1H) 2
* 339 sample_format (4H) (1, 1, 1, 1)
* 33550 model_pixel_scale (3d) (0.001, 0.001, 0.0)
* 33922 model_tie_point (6d) (0.0, 0.0, 0.0, 484576.70205, 3862285.5109300003,
* 34735 geo_key_directory (32H) (1, 1, 0, 7, 1024, 0, 1, 1, 1025, 0, 1, 1, 1026
* 34737 geo_ascii_params (30s) b'WGS 84 / UTM zone 53N|WGS 84|'
"""
gis_coord = np.asarray([[ 484593.67474654, 3862259.42413431],
[ 484593.41064743, 3862259.92582402],
[ 484593.64841806, 3862260.06515117],
[ 484593.93077419, 3862259.55455913],
[ 484593.67474654, 3862259.42413431]])
header = geotiff._prase_header_string(geo_head_txt)
expected_pixel = np.asarray([[16972, 26086],
[16708, 25585],
[16946, 25445],
[17228, 25956],
[16972, 26086]])
pixel_coord = geotiff.geo2pixel(gis_coord, header)
np.testing.assert_almost_equal(pixel_coord, expected_pixel)
gis_revert = geotiff.pixel2geo(pixel_coord, header)
np.testing.assert_almost_equal(gis_revert, gis_coord, decimal=3)
def test_prase_header_string_width():
out_dict = geotiff._prase_header_string("* 256 image_width (1H) 13503")
assert out_dict['width'] == 13503
def test_prase_header_string_proj_error(capsys):
# should raise error because WGS 84 / UTM ... should be full
out_dict = geotiff._prase_header_string("* 34737 geo_ascii_params (30s) b'UTM zone 54N|WGS 84|'")
captured = capsys.readouterr()
assert '[io][geotiff][GeoCorrd] Generation failed, because [Input is not a CRS: UTM zone 54N]' in captured.out
assert out_dict['proj'] == None
def test_prase_header_string_nodata():
out_dict = geotiff._prase_header_string("* 42113 gdal_nodata (7s) b'-10000'")
assert out_dict['nodata'] == -10000
def test_prase_header_string_scale():
in_str = "* 33550 model_pixel_scale (3d) (0.0029700000000000004, 0.0029700000000000004, 0"
out_dict = geotiff._prase_header_string(in_str)
assert out_dict['scale'] == (0.0029700000000000004, 0.0029700000000000004)
def test_prase_header_string_length():
out_dict = geotiff._prase_header_string("* 257 image_length (1H) 19866")
assert out_dict['length'] == 19866