Refactor python API about rio-pansharpen HOT 2 CLOSED

These are the current steps I am taking to refactor the current worker script in the refactor_api branch and PR #13

• Renaming current pansharpen function to calculate_landsat_pansharpen. This function handles:
• reading, updating input meta data
• writing the result of pansharpening (derived by _pansharpen_worker) into each window respectively via riomucho.
• _pansharpen_worker function is the riomucho worker for pansharpening. It is responsible for:
  • Reading panchromatic band data, determines the datatype for the panchromatic band from meta data
  • Determining RGB window sizes (includes padding)
  • Determining affines for pan, RGB windows
  • Reading RGB data
  • Passing necessary arguments to the new pansharpen function to perform pansharpening
  • rescaling pansharpened array to destination datatype
• new pansharpen is the pansharpening python API (data-in, data-out, no IO) that performs pansharpening operations:
  • Takes ndarrays (RGB bands, pan band), and arguments (Affine transforms) etc
  • Creates a mask of pixels where any channel is 0 (nodata)
  • Apply the mask to each of the RGB bands
  • Perform pansharpening using the specified algorithm. Default is Brovey.
  • Returns ndarray, 3D with shape == (3, panband_height, panband_width)

The biggest advantage for refactoring the current pansharpening script into a pure function, separating IO from array operations is so that we can easily write unit tests that specifically test for array operations:

def test_create_apply_mask(arr):
  .
  .
def test_upsample(masked_arr, pan.shape, pan.shape, rgb_affine, r_crs, pan_affine, dst_crs)
  .
  .
def test_Brovey(arr1, arr2, weight, dtype):
  .
  .
def test_rescale(arr):
  .
  .

cc @dnomadb @perrygeo @celoyd @mapbox/satellite

from rio-pansharpen.

🚢 in PR #13

from rio-pansharpen.