def test_get_GDALRasterBand_if_bandID_is_given(self): n = Nansat(self.test_file_gcps, log_level=40, mapper=self.default_mapper) b = n.get_GDALRasterBand(bandID=1) arr = b.ReadAsArray() self.assertEqual(type(b), gdal.Band) self.assertEqual(type(arr), np.ndarray)
def test_get_GDALRasterBand(self): n = Nansat(self.test_file_gcps, logLevel=40) b = n.get_GDALRasterBand(1) arr = b.ReadAsArray() self.assertEqual(type(b), gdal.Band) self.assertEqual(type(arr), np.ndarray)
print 'Global Metadata:', n.get_metadata(), '\n' # set BandMetadata to the 1st band n.set_metadata(key='BandKey', value='BandVal', bandID=1) # get 1st Band Metadata print '1st Band Metadata:', n.get_metadata(bandID=1), '\n' # add a band from file (copy the 2nd band to the end (4th band) n.add_band(fileName=n.fileName, bandID=2) # add a band from numpy array (copy the 1st band to the end (5th band)) n.add_band(array=n[1], parameters={'name': 'Name1', 'info': 'copy from the 1st band array'}) # print band list n.list_bands() # get GDAL raster band (2nd band) band = n.get_GDALRasterBand(bandID=2) # Get band data and do some operations # -- Get data from 1st band as numpy array a = n[1] # -- Plot the array (pyplot image is save to a PNG file) plt.imshow(a);plt.colorbar();plt.savefig(oFileName + '01_imshow.png');plt.close() # -- Save as Matlab file savemat(oFileName + '01.mat', {'band_1': a}) # Resize the data to 50% n.resize(0.5) # make simple indexed image from 1st band with default colormap n.write_figure(oFileName + '02.png', clim='hist') # undo resize n.resize()