def test_calculate_ndvi(self):
from madmex.util import get_parent
from madmex.mapper.data import raster
from madmex.processing.raster import calculate_ndvi
import numpy
image = "/Users/erickpalacios/Documents/CONABIO/Tareas/4_RedisenioMadmex/5_Clasificacion/rapideyemapgrid/folder_test/rapideye/1649125/2014/2014-01-23/L3A/1649125_2014-01-23_RE4_3A_301519.tif"
gdal_format = "GTiff"
data_class = raster.Data(image, gdal_format)
array = data_class.read_data_file_as_array()
width, height, bands = data_class.get_attribute(raster.DATA_SHAPE)
feature_bands = numpy.zeros([2, width, height])
feature_bands[0, :, :] = calculate_ndvi(array[4, :, :], array[2, :, :])
feature_bands[1, :, :] = calculate_ndvi(array[3, :, :], array[2, :, :])
out = get_parent(image) + 'result_ndvi'
raster.create_raster_tiff_from_reference(data_class.metadata, out, feature_bands)
def test_calculate_ndvi(self):
from madmex.util import get_parent
from madmex.mapper.data import raster
from madmex.processing.raster import calculate_ndvi
import numpy
image = "/Users/erickpalacios/Documents/CONABIO/Tareas/4_RedisenioMadmex/5_Clasificacion/rapideyemapgrid/folder_test/rapideye/1649125/2014/2014-01-23/L3A/1649125_2014-01-23_RE4_3A_301519.tif"
gdal_format = "GTiff"
data_class = raster.Data(image, gdal_format)
array = data_class.read_data_file_as_array()
width, height, bands = data_class.get_attribute(raster.DATA_SHAPE)
feature_bands = numpy.zeros([2, width, height])
feature_bands[0, :, :] = calculate_ndvi(array[4, :, :], array[2, :, :])
feature_bands[1, :, :] = calculate_ndvi(array[3, :, :], array[2, :, :])
out = get_parent(image) + 'result_ndvi'
raster.create_raster_tiff_from_reference(data_class.metadata, out,
feature_bands)
clouds = self.masking_with_time_series(data, cloud_output_file, solar_zenith, solar_azimuth, geotransform, tile_id)
create_raster_from_reference(cloud_output_file,
clouds,
self.file_dictionary[_IMAGE],
data_type=NumericTypeCodeToGDALTypeCode(numpy.float32)
)
LOGGER.info('Cloud mask was created.')
if __name__ == '__main__':
#path = '/Users/amaury/Documents/rapideye/df/1447813/2012/2012-03-14/l3a'
#bundle = Bundle(path)
#print bundle.get_files()
#print bundle.can_identify()
image = "/Users/agutierrez/Documents/rapideye/df/1447813/2012/2012-03-14/l3a/2012-03-14T182106_RE2_3A-NAC_11040070_149070.tif"
gdal_format = "GTiff"
data_class = raster.Data(image, gdal_format)
array = data_class.read_data_file_as_array()
width, height, bands = data_class.get_attribute(raster.DATA_SHAPE)
feature_bands = numpy.zeros([2, width, height])
from madmex.processing.raster import calculate_ndvi
feature_bands[0, :, :] = calculate_ndvi(array[4, :, :], array[2, :, :])
feature_bands[1, :, :] = calculate_ndvi(array[3, :, :], array[2, :, :])
out1 = get_parent(image) + 'result_ndvi_1.tif'
out2 = get_parent(image) + 'result_ndvi_2.tif'
create_raster_from_reference(out1, feature_bands[0, :, :], image)
create_raster_from_reference(out2, feature_bands[1, :, :], image)
print 'Done'
