#!/usr/bin/env python3

# This program is a direct translation of the sample program
# "write_ndvi.c" bundled with the EPR-API distribution.
#
# Source code of the C program is available at:
# https://github.com/bcdev/epr-api/blob/master/src/examples/write_ndvi.c


"""Example for using the epr-api.

Demonstrates how to open a MERIS L1b product and calculate the NDVI.

This example does not demonstrate how to write good and safe code.
It is reduced to the essentials for working with the epr-api.

Calling sequence::

    $ python3 write_ndvi.py <envisat-product> <output-file>

for example::

    $ python3 write_ndvi.py MER_RR__1P_test.N1 my_ndvi.raw

"""

import sys
import struct
import logging

import epr


def main(*argv):
    if not argv:
        argv = sys.argv

    if len(argv) != 3:
        print(
            """"
Usage:
  python3 write_ndvi <envisat-product> <output-file>

where envisat-product is the input filename
and output-file is the output filename.

Example:

  MER_RR__1P_TEST.N1 my_ndvi.raw

"""
        )
        sys.exit(1)

    # Open the product
    with epr.open(argv[1]) as product:
        # The NDVI shall be calculated using bands 6 and 8.
        band1_name = "radiance_6"
        band2_name = "radiance_10"

        band1 = product.get_band(band1_name)
        band2 = product.get_band(band2_name)

        # Allocate memory for the rasters
        width = product.get_scene_width()
        height = product.get_scene_height()
        subsampling_x = 1
        subsampling_y = 1
        raster1 = band1.create_compatible_raster(
            width, height, subsampling_x, subsampling_y
        )
        raster2 = band2.create_compatible_raster(
            width, height, subsampling_x, subsampling_y
        )

        # Read the radiance into the raster.
        offset_x = 0
        offset_y = 0

        logging.info("read %r data", band1_name)
        band1.read_raster(offset_x, offset_y, raster1)

        logging.info("read %r data", band2_name)
        band2.read_raster(offset_x, offset_y, raster2)

        # Open the output file
        logging.info("write ndvi to %r", argv[2])
        with open(argv[2], "wb") as out_stream:
            # Loop over all pixel and calculate the NDVI.
            #
            # @NOTE: looping over data matrices is not the best soluton.
            #        It is done here just for demostrative purposes
            for j in range(height):
                for i in range(width):
                    rad1 = raster1.get_pixel(i, j)
                    rad2 = raster2.get_pixel(i, j)
                    if (rad1 + rad2) != 0.0:
                        ndvi = (rad2 - rad1) / (rad2 + rad1)
                    else:
                        ndvi = -1.0
                    out_stream.write(struct.pack("f", ndvi))
            logging.info("ndvi was written success")


if __name__ == "__main__":
    main()