Merge pull request #46 from chrishavlin/fix_axis_flipping

apply the reversal with xr commands when reading

Author: chrishavlin

HISTORY.md

@@ -1,8 +1,14 @@
 # History
 
+## 0.1.4 (2023-03-21)
+
+Bug fix release.
+
+### Fixes:
+* fix coordinate flipping bug (PR [46](https://github.com/data-exp-lab/yt_xarray/pull/46))
 ## 0.1.3 (2023-03-10)
 
-Bug fix release. 
+Bug fix release.
 
 ### Fixes:
 * handle the case where data coordinate lengths are 1 (PR [41](https://github.com/data-exp-lab/yt_xarray/pull/41))

setup.cfg

@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.1.3
+current_version = 0.1.4
 commit = True
 tag = True
 

setup.py

@@ -41,6 +41,6 @@
     test_suite="tests",
     tests_require=test_requirements,
     url="https://github.com/data-exp-lab/yt_xarray",
-    version="0.1.3",
+    version="0.1.4",
     zip_safe=False,
 )

yt_xarray/__init__.py

@@ -2,11 +2,10 @@
 
 __author__ = """Chris Havlin"""
 __email__ = "[email protected]"
-__version__ = "0.1.3"
+__version__ = "0.1.4"
 
 
-# import the yt frontend and the xarray accessor so they are registered with
-# their respective codes
+# import the the xarray accessor so it is registered with xarray
 
 from .accessor import YtAccessor
 from .accessor._xr_to_yt import known_coord_aliases

yt_xarray/accessor/_readers.py

@@ -81,15 +81,15 @@ def _reader(grid, field_name):
         # load into memory (if its not) as xr DataArray
         datavals = datavals.load()
 
+        # reverse axis ordering if needed
+        for axname in sel_info.reverse_axis_names:
+            dimvals = getattr(datavals, axname)
+            datavals = datavals.sel({axname: dimvals[::-1]})
+
         if interp_required:
             # interpolate from nodes to cell centers across all remaining dims
             datavals = _xr_to_yt._interpolate_to_cell_centers(datavals)
 
-        # final flips to account for all the index reversing
-        for idim in range(sel_info.ndims):
-            if sel_info.reverse_axis[idim]:
-                datavals = np.flip(datavals, axis=idim)
-
         # return the plain values
         vals = datavals.values.astype(np.float64)
         if sel_info.ndims == 2:

yt_xarray/accessor/_xr_to_yt.py

@@ -132,6 +132,7 @@ def _process_selection(self, xr_ds):
         cell_widths = []  # cell widths after selection
         grid_type = _GridType.UNIFORM  # start with uniform assumption
         reverse_axis = []  # axes must be positive-monitonic for yt
+        reverse_axis_names = []
         global_dims = []  # the global shape
         for c in full_coords:
             coord_da = getattr(xr_ds, c)  # the full coordinate data array
@@ -140,6 +141,8 @@ def _process_selection(self, xr_ds):
             if coord_da.size > 1:
                 rev_ax = coord_da[1] <= coord_da[0]
                 reverse_axis.append(bool(rev_ax.values))
+                if rev_ax:
+                    reverse_axis_names.append(c)
 
             # store the global ranges
             global_dims.append(coord_da.size)
@@ -204,6 +207,7 @@ def _process_selection(self, xr_ds):
         self.grid_type = grid_type
         self.cell_widths = cell_widths
         self.reverse_axis = reverse_axis
+        self.reverse_axis_names = reverse_axis_names
         self.global_dims = np.array(global_dims)
         # self.coord_selected_arrays = coord_selected_arrays
 
@@ -250,9 +254,15 @@ def _validate_fields(self, xr_ds, fields: List[str]) -> List[str]:
 
     def select_from_xr(self, xr_ds, field):
         if self.sel_dict_type == "isel":
-            return xr_ds[field].isel(self.sel_dict)
+            vars = xr_ds[field].isel(self.sel_dict)
         else:
-            return xr_ds[field].sel(self.sel_dict)
+            vars = xr_ds[field].sel(self.sel_dict)
+
+        for axname in self.reverse_axis_names:
+            dimvals = getattr(vars, axname)
+            vars = vars.sel({axname: dimvals[::-1]})
+
+        return vars
 
     def interp_validation(self, geometry):
         # checks if yt will need to interpolate to cell center
@@ -439,12 +449,6 @@ def _load_full_field_from_xr(
 
     if interp_required:
         vals = _interpolate_to_cell_centers(vals)
-    if any(sel_info.reverse_axis):
-        # if any dims are in decreaseing order, flip that axis
-        # after reading in the data
-        for idim, flip_it in enumerate(sel_info.reverse_axis):
-            if flip_it:
-                vals = np.flip(vals, axis=idim)
 
     vals = vals.values.astype(np.float64)
     if sel_info.ndims == 2: