apply upstream PR 101

CHANGELOG.md

@@ -6,6 +6,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [PEP 440](https://www.python.org/dev/peps/pep-0440/)
 and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.20.0]
+### Changed
+* The M11/M12 variables produced by the hyp3_autorift and s1_correction workflows will be written as `float32` instead of the previous compressed `int16` variables that did not take advantage of the full dynamic range and thus lost a significant amount of precision.
+
 ## [0.19.0]
 ### Changed
 * Orbits are now downloaded using `s1_orbits` rather than `hyp3lib`.

environment.yml

@@ -9,7 +9,7 @@ dependencies:
   - python>=3.9,<3.10  # Top pin to fix ISCE2 incompatibility: https://github.com/isce-framework/isce2/issues/458
   - pip
   # For packaging, and testing
-  - build
+  - python-build
   - flake8
   - flake8-import-order
   - flake8-blind-except
@@ -36,4 +36,4 @@ dependencies:
   - requests
   - scipy
   - xarray
-  - s1_orbits
+  - s1_orbits

src/hyp3_autorift/s1_isce2.py

@@ -162,7 +162,7 @@ def write_conversion_file(
     else:
         raise Exception(f'Projection {srs.GetAttrValue("PROJECTION")} not recognized for this program')
 
-    var = nc_outfile.createVariable('M11', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
+    var = nc_outfile.createVariable('M11', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
                                     zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
     var.setncattr('standard_name', 'conversion_matrix_element_11')
     var.setncattr(
@@ -176,19 +176,10 @@ def write_conversion_file(
     var.setncattr('dr_to_vr_factor_description', 'multiplicative factor that converts slant range '
                                                  'pixel displacement dr to slant range velocity vr')
 
-    x1 = np.nanmin(M11[:])
-    x2 = np.nanmax(M11[:])
-    y1 = -50
-    y2 = 50
-
-    C = [(y2 - y1) / (x2 - x1), y1 - x1 * (y2 - y1) / (x2 - x1)]
-    var.setncattr('scale_factor', np.float32(1 / C[0]))
-    var.setncattr('add_offset', np.float32(-C[1] / C[0]))
-
-    M11[noDataMask] = NoDataValue * np.float32(1 / C[0]) + np.float32(-C[1] / C[0])
+    M11[noDataMask] = NoDataValue
     var[:] = M11
 
-    var = nc_outfile.createVariable('M12', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
+    var = nc_outfile.createVariable('M12', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
                                     zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
     var.setncattr('standard_name', 'conversion_matrix_element_12')
     var.setncattr(
@@ -202,16 +193,7 @@ def write_conversion_file(
     var.setncattr('dr_to_vr_factor_description',
                   'multiplicative factor that converts slant range pixel displacement dr to slant range velocity vr')
 
-    x1 = np.nanmin(M12[:])
-    x2 = np.nanmax(M12[:])
-    y1 = -50
-    y2 = 50
-
-    C = [(y2 - y1) / (x2 - x1), y1 - x1 * (y2 - y1) / (x2 - x1)]
-    var.setncattr('scale_factor', np.float32(1 / C[0]))
-    var.setncattr('add_offset', np.float32(-C[1] / C[0]))
-
-    M12[noDataMask] = NoDataValue * np.float32(1 / C[0]) + np.float32(-C[1] / C[0])
+    M12[noDataMask] = NoDataValue
     var[:] = M12
 
     nc_outfile.sync()

src/hyp3_autorift/vend/CHANGES-UPSTREAM-101.diff

@@ -0,0 +1,60 @@
+diff --git netcdf_output.py netcdf_output.py
+--- netcdf_output.py
++++ netcdf_output.py
+@@ -1092,7 +1092,7 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
+         # # var.setncattr('missing_value', np.int16(NoDataValue))
+
+
+-        var = nc_outfile.createVariable('M11', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
++        var = nc_outfile.createVariable('M11', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
+                                         zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
+         var.setncattr('standard_name', 'conversion_matrix_element_11')
+         var.setncattr('description', 'conversion matrix element (1st row, 1st column) that can be multiplied with vx '
+@@ -1105,25 +1105,14 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
+
+         M11 = offset2vy_2 / (offset2vx_1 * offset2vy_2 - offset2vx_2 * offset2vy_1) / scale_factor_1
+
+-        x1 = np.nanmin(M11[:])
+-        x2 = np.nanmax(M11[:])
+-        y1 = -50
+-        y2 = 50
+-
+-        C = [(y2-y1)/(x2-x1), y1-x1*(y2-y1)/(x2-x1)]
+-        # M11 = C[0]*M11+C[1]
+-        var.setncattr('scale_factor', np.float32(1/C[0]))
+-        var.setncattr('add_offset', np.float32(-C[1]/C[0]))
+-
+-        M11[noDataMask] = NoDataValue * np.float32(1/C[0]) + np.float32(-C[1]/C[0])
+-        # M11[noDataMask] = NoDataValue
++        M11[noDataMask] = NoDataValue
+         var[:] = M11
+         # var[:] = np.round(np.clip(M11, -32768, 32767)).astype(np.int16)
+         # var[:] = np.clip(M11, -3.4028235e+38, 3.4028235e+38).astype(np.float32)
+         # var.setncattr('missing_value',np.int16(NoDataValue))
+
+
+-        var = nc_outfile.createVariable('M12', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
++        var = nc_outfile.createVariable('M12', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
+                                         zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
+         var.setncattr('standard_name', 'conversion_matrix_element_12')
+         var.setncattr('description', 'conversion matrix element (1st row, 2nd column) that can be multiplied with vy '
+@@ -1137,18 +1126,7 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
+
+         M12 = -offset2vx_2 / (offset2vx_1 * offset2vy_2 - offset2vx_2 * offset2vy_1) / scale_factor_1
+
+-        x1 = np.nanmin(M12[:])
+-        x2 = np.nanmax(M12[:])
+-        y1 = -50
+-        y2 = 50
+-
+-        C = [(y2 - y1) / (x2 - x1), y1 - x1 * (y2 - y1) / (x2 - x1)]
+-        # M12 = C[0]*M12+C[1]
+-        var.setncattr('scale_factor', np.float32(1/C[0]))
+-        var.setncattr('add_offset', np.float32(-C[1]/C[0]))
+-
+-        M12[noDataMask] = NoDataValue * np.float32(1/C[0]) + np.float32(-C[1]/C[0])
+-        # M12[noDataMask] = NoDataValue
++        M12[noDataMask] = NoDataValue
+         var[:] = M12
+         # var[:] = np.round(np.clip(M12, -32768, 32767)).astype(np.int16)
+         # var[:] = np.clip(M12, -3.4028235e+38, 3.4028235e+38).astype(np.float32)

src/hyp3_autorift/vend/README.md

@@ -74,3 +74,6 @@ We've replaced it  with `hyp3_autorift.s1_isce2.get_topsinsar_config`.
     to make it easier for users to correct for ionosphere streaks without needing to know the scale
     factor. These changes have been [proposed upstream](https://github.com/nasa-jpl/autoRIFT/pull/92) and should be
     applied in the next `nasa-jpl/autoRIFT` release.
+12. The changes listed in `CHANGES-UPSTREAM-12.diff` were applied from upstream ([nasa-jpl/autorift#101](https://github.com/nasa-jpl/autorift/pull/101))
+    in [ASFHyP3/hyp3-autorift#291](https://github.com/ASFHyP3/hyp3-autorift/pull/291) so that M11/M12 variables are
+    output as `float32` instead of compressed `int16` variables which did not even use the full dynamic range.

src/hyp3_autorift/vend/netcdf_output.py

@@ -1102,7 +1102,7 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
         # # var.setncattr('missing_value', np.int16(NoDataValue))
 
 
-        var = nc_outfile.createVariable('M11', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
+        var = nc_outfile.createVariable('M11', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
                                         zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
         var.setncattr('standard_name', 'conversion_matrix_element_11')
         var.setncattr('description', 'conversion matrix element (1st row, 1st column) that can be multiplied with vx '
@@ -1115,25 +1115,14 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
 
         M11 = offset2vy_2 / (offset2vx_1 * offset2vy_2 - offset2vx_2 * offset2vy_1) / scale_factor_1
 
-        x1 = np.nanmin(M11[:])
-        x2 = np.nanmax(M11[:])
-        y1 = -50
-        y2 = 50
-
-        C = [(y2-y1)/(x2-x1), y1-x1*(y2-y1)/(x2-x1)]
-        # M11 = C[0]*M11+C[1]
-        var.setncattr('scale_factor', np.float32(1/C[0]))
-        var.setncattr('add_offset', np.float32(-C[1]/C[0]))
-
-        M11[noDataMask] = NoDataValue * np.float32(1/C[0]) + np.float32(-C[1]/C[0])
-        # M11[noDataMask] = NoDataValue
+        M11[noDataMask] = NoDataValue
         var[:] = M11
         # var[:] = np.round(np.clip(M11, -32768, 32767)).astype(np.int16)
         # var[:] = np.clip(M11, -3.4028235e+38, 3.4028235e+38).astype(np.float32)
         # var.setncattr('missing_value',np.int16(NoDataValue))
 
 
-        var = nc_outfile.createVariable('M12', np.dtype('int16'), ('y', 'x'), fill_value=NoDataValue,
+        var = nc_outfile.createVariable('M12', np.dtype('float32'), ('y', 'x'), fill_value=NoDataValue,
                                         zlib=True, complevel=2, shuffle=True, chunksizes=ChunkSize)
         var.setncattr('standard_name', 'conversion_matrix_element_12')
         var.setncattr('description', 'conversion matrix element (1st row, 2nd column) that can be multiplied with vy '
@@ -1147,18 +1136,7 @@ def netCDF_packaging(VX, VY, DX, DY, INTERPMASK, CHIPSIZEX, CHIPSIZEY, SSM, SSM1
 
         M12 = -offset2vx_2 / (offset2vx_1 * offset2vy_2 - offset2vx_2 * offset2vy_1) / scale_factor_1
 
-        x1 = np.nanmin(M12[:])
-        x2 = np.nanmax(M12[:])
-        y1 = -50
-        y2 = 50
-
-        C = [(y2 - y1) / (x2 - x1), y1 - x1 * (y2 - y1) / (x2 - x1)]
-        # M12 = C[0]*M12+C[1]
-        var.setncattr('scale_factor', np.float32(1/C[0]))
-        var.setncattr('add_offset', np.float32(-C[1]/C[0]))
-
-        M12[noDataMask] = NoDataValue * np.float32(1/C[0]) + np.float32(-C[1]/C[0])
-        # M12[noDataMask] = NoDataValue
+        M12[noDataMask] = NoDataValue
         var[:] = M12
         # var[:] = np.round(np.clip(M12, -32768, 32767)).astype(np.int16)
         # var[:] = np.clip(M12, -3.4028235e+38, 3.4028235e+38).astype(np.float32)