Cleanup debug prints

Author: BrianMichell

src/mdio/builder/dataset_builder.py

@@ -125,32 +125,9 @@ def push_dimension(self, dimension: NamedDimension, position: int, new_dim_chunk
             msg = "New dimension chunk size must be greater than 0"
             raise ValueError(msg)
 
-        # print("###########################STATE BEFORE INSERTING DIMENSION ###########################")
-        # for d in self._dimensions:
-        #     print(d.model_dump_json())
-        # for c in self._coordinates:
-        #     print(c.model_dump_json())
-        # for v in self._variables:
-        #     print(v.model_dump_json())
-        # print("########################################################################################")
-
-
         # In-place insertion of the dimension to the existing list of dimensions
         self._dimensions.insert(position, dimension)
 
-        # def propogate_dimension(variable: Variable, position: int, new_dim_chunk_size: int) -> Variable:
-        #     """Propogates the dimension to the variable or coordinate."""
-        #     if len(variable.dimensions) <= position:
-        #         # Don't do anything if the new dimension is not within the Variable's domain
-        #         return variable
-        #     if variable.name == "trace_mask":
-        #         # Special case for trace_mask. Don't do anything.
-        #         return variable
-        #     # new_dimensions = variable.dimensions[:position] + (dimension,) + variable.dimensions[position:]
-        #     # new_chunk_sizes = variable.chunk_sizes[:position] + (new_dim_chunk_size,) + variable.chunk_sizes[position:]
-        #     new_dimensions = variable.dimensions[:position] + [dimension] + variable.dimensions[position:]
-        #     new_chunk_sizes = variable.chunk_sizes[:position] + [new_dim_chunk_size] + variable.chunk_sizes[position:]
-        #     return variable.model_copy(update={"dimensions": new_dimensions, "chunk_sizes": new_chunk_sizes})
         def propogate_dimension(variable: Variable, position: int, new_dim_chunk_size: int) -> Variable:
             """Propogates the dimension to the variable or coordinate."""
             from mdio.builder.schemas.chunk_grid import RegularChunkGrid, RegularChunkShape
@@ -160,8 +137,6 @@ def propogate_dimension(variable: Variable, position: int, new_dim_chunk_size: i
             if variable.name == "trace_mask":
                 # Special case for trace_mask. Don't do anything.
                 return variable
-            # new_dimensions = variable.dimensions[:position] + (dimension,) + variable.dimensions[position:]
-            # new_chunk_sizes = variable.chunk_sizes[:position] + (new_dim_chunk_size,) + variable.chunk_sizes[position:]
             new_dimensions = variable.dimensions[:position] + [dimension] + variable.dimensions[position:]
 
             # Get current chunk shape from metadata

src/mdio/converters/segy.py

@@ -514,13 +514,6 @@ def segy_to_mdio(  # noqa PLR0913
         header_dtype=to_structured_type(segy_spec.trace.header.dtype),
     )
 
-    # print(mdio_ds.model_dump_json())
-    for v in mdio_ds.variables:
-        print(f"Attempting to dump variable {v.name}... ", end="")
-        tmp = v.model_dump_json()
-        print("Good!")
-        # print(v.model_dump_json())
-
     _add_grid_override_to_metadata(dataset=mdio_ds, grid_overrides=grid_overrides)
 
     # Dynamically chunk the variables based on their type
@@ -530,6 +523,8 @@ def segy_to_mdio(  # noqa PLR0913
 
     xr_dataset: xr_Dataset = to_xarray_dataset(mdio_ds=mdio_ds)
 
+    print(xr_dataset)
+
     _, non_dim_coords = _get_coordinates(grid, segy_headers, mdio_template)
     xr_dataset, drop_vars_delayed = _populate_coordinates(
         dataset=xr_dataset,

src/mdio/segy/utilities.py

@@ -67,37 +67,20 @@ def get_grid_plan(  # noqa:  C901
     # Create filtered copy using numpy's field selection
     reduced_headers_subset = HeaderArray(headers_subset[fields_to_keep])
 
-    # print("="*100)
-    # print(headers_subset.to_dict().keys())
-    # print(headers_subset)
-    # print("="*100)
-
     # Handle grid overrides.
     override_handler = GridOverrider()
     headers_subset, horizontal_coordinates, chunksize = override_handler.run(
         # headers_subset,
         reduced_headers_subset,
-        horizontal_coordinates,
-        # horizontal_dimensions,
+        # horizontal_coordinates,
+        horizontal_dimensions,
         chunksize=chunksize,
         grid_overrides=grid_overrides,
     )
 
-    # print("="*100)
-    # print(headers_subset.to_dict().keys())
-    # print(headers_subset)
-    # print("="*100)
-
     if grid_overrides.get("HasDuplicates", False):
-        # print(f"Size of header subset: {headers_subset['trace'].size}")
-        # print("="*100)
-        # print(headers_subset)
-        # print("="*100)
         pos = len(template.dimension_names) - 1  # TODO: Implement the negative position case...
-        # template._queue_transform(lambda builder: builder.push_dimension(Dimension(coords=np.arange(headers_subset["trace"].size), name="trace"), position=pos, new_dim_chunk_size=1))
-        # template._queue_transform(lambda builder: builder.push_dimension(Dimension(coords=headers_subset["trace"].size, name="trace"), position=pos, new_dim_chunk_size=1))
         template._queue_transform(lambda builder: builder.push_dimension(NamedDimension(name="trace", size=headers_subset["trace"].size), position=pos, new_dim_chunk_size=1))
-        # horizontal_dimensions.append("trace")
         horizontal_dimensions = (*horizontal_dimensions, "trace")
 
     dimensions = []