Python Nansat.add_band方法代码示例

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
    def test_export_gcps_complex_to_netcdf(self):
        ''' Should export file with GCPs and write correct complex bands'''
        n0 = Nansat(self.test_file_gcps, logLevel=40)
        b0 = n0['L_469']

        n1 = Nansat(domain=n0)
        n1.add_band(b0.astype('complex64'),
                    parameters={'name': 'L_469'})

        tmpfilename = os.path.join(ntd.tmp_data_path, 'nansat_export_gcps_complex.nc')
        n1.export(tmpfilename)

        ncf = netcdf_file(tmpfilename)
        self.assertTrue(os.path.exists(tmpfilename))
        self.assertTrue('GCPX' in ncf.variables)
        self.assertTrue('GCPY' in ncf.variables)
        self.assertTrue('GCPPixel' in ncf.variables)
        self.assertTrue('GCPLine' in ncf.variables)

        n2 = Nansat(tmpfilename)
        b2 = n2['L_469']
        np.testing.assert_allclose(b0, b2)

        lon0, lat0 = n0.get_geolocation_grids()
        lon2, lat2 = n1.get_geolocation_grids()
        np.testing.assert_allclose(lon0, lon2)
        np.testing.assert_allclose(lat0, lat2)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_get_item_inf_expressions(self):
     ''' inf should be replaced with nan '''
     d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
     n = Nansat(domain=d, logLevel=40)
     arr = np.empty((500, 500))
     n.add_band(arr, {'expression': 'np.array([0,1,2,3,np.inf,5,6,7])'})
     self.assertIsInstance(n[1], np.ndarray)
     self.assertTrue(np.isnan(n[1][4]))

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_dont_export2thredds_gcps(self):
     n = Nansat(self.test_file_gcps, log_level=40, mapper=self.default_mapper)
     n2 = Nansat.from_domain(n)
     n.add_band(np.ones(n2.shape(), np.float32))
     tmpfilename = os.path.join(self.tmp_data_path,
                                'nansat_export2thredds.nc')
     self.assertRaises(ValueError, n2.export2thredds, tmpfilename,
                       ['L_645'])

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_dont_export2thredds_gcps(self):
     n = Nansat(self.test_file_gcps, logLevel=40)
     n2 = Nansat(domain=n)
     n.add_band(np.ones(n2.shape(), np.float32))
     tmpfilename = os.path.join(ntd.tmp_data_path,
                                'nansat_export2thredds.nc')
     self.assertRaises(OptionError, n2.export2thredds, tmpfilename,
                       ['L_645'])

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
    def test_add_band(self):
        d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
        arr = np.random.randn(500, 500)
        n = Nansat(domain=d, logLevel=40)
        n.add_band(arr, {'name': 'band1'})

        self.assertEqual(type(n), Nansat)
        self.assertEqual(type(n[1]), np.ndarray)
        self.assertEqual(n.get_metadata('name', 1), 'band1')
        self.assertEqual(n[1].shape, (500, 500))

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
    def test_add_subvrts_only_to_one_nansat(self):
        d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
        arr = np.random.randn(500, 500)

        n1 = Nansat(domain=d, logLevel=40)
        n2 = Nansat(domain=d, logLevel=40)
        n1.add_band(arr, {'name': 'band1'})

        self.assertEqual(type(n1.vrt.bandVRTs), dict)
        self.assertTrue(len(n1.vrt.bandVRTs) > 0)
        self.assertEqual(n2.vrt.bandVRTs, {})

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_get_item_basic_expressions(self):
     ''' Testing get_item with some basic expressions '''
     d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
     n = Nansat(domain=d, logLevel=40)
     arr = np.empty((500, 500))
     n.add_band(arr, {'expression': '1+1'})
     n.add_band(arr, {'expression': 'np.random.randn(500, 500)'})
     self.assertIsInstance(n[1], int)
     self.assertIsInstance(n[2], np.ndarray)
     self.assertEqual(n[1], 2)
     self.assertEqual(len(n[2]), 500)
     self.assertEqual(len(n[2][0]), 500)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_export_selected_bands(self):
     n = Nansat(self.test_file_gcps)
     resfile = 'tmp.nc'
     new_band = np.random.randn(n.shape()[0], n.shape()[1])
     n.add_band(new_band, {'name': 'newBand'})
     # Test with band numbers
     n.export(resfile, bands=[4, 2])
     self.assertTrue(os.path.exists(resfile))
     nn = Nansat(resfile)
     self.assertTrue(nn.has_band('newBand'))
     self.assertTrue(nn.has_band('L_555'))
     os.unlink(resfile)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
    def test_export2thredds_longlat_list(self):
        d = Domain("+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs",
                   "-te 27 70 31 72 -ts 200 200")
        n = Nansat(domain=d)
        n.add_band(np.ones(d.shape(), np.float32),
                   parameters={'name': 'L_469'})
        n.set_metadata('time_coverage_start', '2016-01-19')

        tmpfilename = os.path.join(ntd.tmp_data_path,
                                   'nansat_export2thredds_longlat.nc')
        n.export2thredds(tmpfilename, ['L_469'])
        ncI = netcdf_file(tmpfilename, 'r')
        ncIVar = ncI.variables['L_469']
        self.assertTrue(ncIVar.grid_mapping in ncI.variables.keys())

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
    def test_add_band_and_reproject(self):
        ''' Should add band and swath mask
        and return 0 in areas out of swath '''
        n = Nansat(self.test_file_gcps, logLevel=40)
        d = Domain(4326, "-te 27 70 30 72 -ts 500 500")
        n.add_band(np.ones(n.shape()))
        n.reproject(d)
        b1 = n[1]
        b4 = n[4]

        self.assertTrue(n.has_band('swathmask'))
        self.assertTrue(b1[0, 0] == 0)
        self.assertTrue(b1[300, 300] > 0)
        self.assertTrue(np.isnan(b4[0, 0]))
        self.assertTrue(b4[300, 300] == 1.)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_export_netcdf(self):
     """ Test export and following import of data with bands containing np.nan values """
     n = Nansat(self.test_file_gcps, mapper=self.default_mapper)
     arrNoNaN = np.random.randn(n.shape()[0], n.shape()[1])
     n.add_band(arrNoNaN, {'name': 'testBandNoNaN'})
     arrWithNaN = arrNoNaN.copy()
     arrWithNaN[int(n.shape()[0] / 2.) - 10:int(n.shape()[0] / 2 + 10),
                int(n.shape()[1] / 2.) - 10:int(n.shape()[1] / 2 + 10)] = np.nan
     n.add_band(arrWithNaN, {'name': 'testBandWithNaN'})
     n.export(self.tmp_filename)
     exported = Nansat(self.tmp_filename, mapper=self.default_mapper)
     earrNoNaN = exported['testBandNoNaN']
     # Use allclose to allow some roundoff errors
     self.assertTrue(np.allclose(arrNoNaN, earrNoNaN))
     earrWithNaN = exported['testBandWithNaN']
     np.testing.assert_allclose(arrWithNaN, earrWithNaN)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_repr_basic(self):
     ''' repr should include some basic elements '''
     d = Domain(4326, "-te 25 70 35 72 -ts 500 500")
     n = Nansat(domain=d, logLevel=40)
     arr = np.empty((500, 500))
     exp = 'np.array([0,1,2,3,np.inf,5,6,7])'
     n.add_band(arr, {'expression': exp})
     n_repr = repr(n)
     self.assertIn(exp, n_repr, 'The expressions should be in repr')
     self.assertIn('SourceFilename', n_repr)
     self.assertIn('/vsimem/', n_repr)
     self.assertIn('500 x 500', n_repr)
     self.assertIn('Projection:', n_repr)
     self.assertIn('25', n_repr)
     self.assertIn('72', n_repr)
     self.assertIn('35', n_repr)
     self.assertIn('70', n_repr)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
 def test_export_netcdf(self):
     ''' Test export and following import of data with bands containing
     np.nan values
     '''
     n = Nansat(self.test_file_gcps)
     arrNoNaN = np.random.randn(n.shape()[0], n.shape()[1])
     n.add_band(arrNoNaN, {'name': 'testBandNoNaN'})
     arrWithNaN = arrNoNaN.copy()
     arrWithNaN[n.shape()[0] / 2 - 10:n.shape()[0] / 2 + 10,
                n.shape()[1] / 2 - 10:n.shape()[1] / 2 + 10] = np.nan
     n.add_band(arrWithNaN, {'name': 'testBandWithNaN'})
     n.export(self.tmpfilename)
     exported = Nansat(self.tmpfilename)
     earrNoNaN = exported['testBandNoNaN']
     # Use allclose to allow some roundoff errors
     self.assertTrue(np.allclose(arrNoNaN, earrNoNaN))
     earrWithNaN = exported['testBandWithNaN']
     np.testing.assert_allclose(arrWithNaN, earrWithNaN)
     os.unlink(self.tmpfilename)

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
def boreali_processing(obj,  final_path):
    wavelen = [412, 443, 469, 488, 531, 547, 555, 645, 667, 678]
    cpa_limits = [0.01, 2,
                  0.01, 1,
                  0.01, 1, 10]
    b = Boreali('michigan', wavelen)

    n = Nansat(obj)
    dom = Domain('+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs', '-lle -86.3 44.6 -85.2 45.3 -ts 300 200')
    n.reproject(dom)
    theta = numpy.zeros_like(n[2])
    custom_n = Nansat(domain=n)
    band_rrs_numbers = list(map(lambda x: n._get_band_number('Rrs_' + str(x)),
                                wavelen))

    for index in range(0, len(wavelen)):
        # Преобразуем в Rrsw
        rrsw = n[band_rrs_numbers[index]] / (0.52 + 1.7 * n[band_rrs_numbers[index]])
        custom_n.add_band(rrsw, parameters={'name': 'Rrsw_' + str(wavelen[index]),
                                            'units': 'sr-1',
                                            'wavelength': wavelen[index]})

    custom_n = create_mask(custom_n)
    cpa = b.process(custom_n, cpa_limits, mask=custom_n['mask'], theta=theta, threads=4)

    custom_n.add_band(array=cpa[0], parameters={'name': 'chl',
                                                'long_name': 'Chlorophyl-a',
                                                'units': 'mg m-3'})
    custom_n.add_band(array=cpa[1], parameters={'name': 'tsm',
                                                'long_name': 'Total suspended matter',
                                                'units': 'g m-3'})
    custom_n.add_band(array=cpa[2], parameters={'name': 'doc',
                                                'long_name': 'Dissolved organic carbon',
                                                'units': 'gC m-3'})
    custom_n.add_band(array=cpa[3], parameters={'name': 'mse',
                                                'long_name': 'Root Mean Square Error',
                                                'units': 'sr-1'})
    custom_n.add_band(array=cpa[4], parameters={'name': 'mask',
                                                'long_name': 'L2 Boreali mask',
                                                'units': '1'})

    custom_n.export(final_path + obj.split('/')[-1] + 'cpa_deep.nc')

    fig_params = {'legend': True,
                  'LEGEND_HEIGHT': 0.5,
                  'NAME_LOCATION_Y': 0,
                  'mask_array': cpa[4],
                  'mask_lut': {1: [255, 255, 255], 2: [128, 128, 128], 4: [200, 200, 255]}}
    custom_n.write_figure(final_path + obj.split('/')[-1] + 'chl_deep.png', 'chl', clim=[0, 1.], **fig_params)
    custom_n.write_figure(final_path + obj.split('/')[-1] + 'tsm_deep.png', 'tsm', clim=[0, 1.], **fig_params)
    custom_n.write_figure(final_path + obj.split('/')[-1] + 'doc_deep.png', 'doc', clim=[0, .2], **fig_params)
    custom_n.write_figure(final_path + obj.split('/')[-1] + 'mse_deep.png', 'mse', clim=[1e-5, 1e-2], logarithm=True, **fig_params)
    n.write_figure(final_path + obj.split('/')[-1] + 'rgb_deep.png',
                   [16, 14, 6],
                   clim=[[0, 0, 0], [0.006, 0.04, 0.024]],
                   mask_array=cpa[4],
                   mask_lut={2: [128, 128, 128]})

# 需要导入模块: from nansat import Nansat [as 别名]
# 或者: from nansat.Nansat import add_band [as 别名]
print n.shape()

# get list with coordinates of the object corners
print n.get_corners()

# get lists with coordinates of the object borders
print n.get_border()

raw_counts = n[1]
inc_angle = n[2]

#~ sigma0 = n[3]

sigma0 = raw_counts**2.0 * sin(deg2rad(inc_angle))
sigma0 = 10*log10(sigma0)
n.add_band(bandID=4, array=sigma0)

# 1. Remove speckle noise (using Lee-Wiener filter)
speckle_filter('wiener', 7)

# Reprojected image into Lat/Lon WGS84 (Simple Cylindrical) projection
# 1. Cancel previous reprojection
# 2. Get corners of the image and the pixel resolution
# 3. Create Domain with stereographic projection, corner coordinates and resolution 1000m
# 4. Reproject
# 5. Write image
n.reproject() # 1.
lons, lats = n.get_corners() # 2.
pxlRes = distancelib.getPixelResolution(array(lats), array(lons), n.shape(), units="deg")
srsString = "+proj=latlong +datum=WGS84 +ellps=WGS84 +no_defs"
#~ extentString = '-lle %f %f %f %f -ts 3000 3000' % (min(lons), min(lats), max(lons), max(lats))