def mnf(data):
'''
Description: Minimum Noise Fraction (MNF) wrapper for pysptools implementation
Rationale: Removes noise while preserving information
'''
# Convert Series to ndarray
if issubclass(type(data), pd.Series) or isinstance(data, Spectra):
np_data = data.to_numpy()
elif issubclass(type(data), np.ndarray):
np_data = data
else:
raise ValueError("Input for MNF must inherit from pd.Series or np.ndarray")
# Ensure 3 dimensional input for MNF
num_dimensions = len(np_data.shape)
if num_dimensions == 2:
# Add arbitrary 3rd dimension
cube_data = np.expand_dims(np_data, axis=0)
elif num_dimensions == 3:
cube_data = np_data
else:
raise ValueError("Input must be 2 or 3 dimensional")
# Open and apply MNF module
pysp_mnf = MNF()
res = pysp_mnf.apply(cube_data)
# Return result in dimensionality of input
if num_dimensions == 2:
return np.squeeze(res, axis=0)
else:
return res
def test_mnf_rotation(self):
'''MNF rotation should achieve an expected result.'''
file_path = os.path.join(self.test_dir, 'multi7_raster.tiff')
ds = gdal.Open(file_path)
nodata = ds.GetRasterBand(1).GetNoDataValue()
hsi = ds.ReadAsArray().transpose()
hsi[hsi == nodata] = 0
mnf = MNF()
hsi_post_mnf = mnf.apply(hsi)
self.assertEqual(int(hsi_post_mnf.diagonal()[0].sum()), 132)
def test_endmember_search_by_maximum_angle(self):
'''Should be able to search for endmembers by maximum solid angle.'''
rast, gt, wkt = as_array(os.path.join(self.test_dir, 'multi7_raster.tiff'))
hsi = rast.transpose()
hsi[hsi==-9999] = 0
mnf = MNF()
hsi_post_mnf = mnf.apply(hsi)
# Test that sequence/ array type works
ref_target = (342683, 4703919)
result = endmembers_by_maximum_angle(hsi_post_mnf.T, self.cases['Vegetation'],
ref_target, gt=gt, wkt=wkt, dd=False)
self.assertTrue(isinstance(result[0], np.ndarray))
def mnf_rotation(rast, nodata=-9999):
'''
Applies the MNF rotation to an HSI data cube. Arguments:
rast A NumPy raster array
nodata The NoData value
'''
hsi = rast.copy().transpose()
hsi[hsi == nodata] = 0 # Remap any lingering NoData values
# Apply the Minimum Noise Fraction (MNF) rotation
mnf = MNF()
hsi_post_mnf = mnf.apply(hsi)
hsi = None
return hsi_post_mnf
def test_ppi_endmember_extraction(self):
'''
Extraction by PPI, following an MNF rotation, should achieve an
expected result.
'''
file_path = os.path.join(self.test_dir, 'multi7_raster.tiff')
ds = gdal.Open(file_path)
ppi = PPI()
nodata = ds.GetRasterBand(1).GetNoDataValue()
hsi = ds.ReadAsArray().transpose()
hsi[hsi == nodata] = 0
mnf = MNF()
hsi_post_mnf = mnf.apply(hsi)
members = ppi.extract(hsi_post_mnf[..., 0:3], 3, numSkewers=10000)
self.assertEqual(int(members.sum()), 934)