Refactor dims._assign_axes()

This commit refactors the dims.assign_axes() method to (1)
drop the use of EnumeratedAxis (until additional metadata mechanisms
are available) and (2) resolves a bug with handling singleton
dimensions.

(1) Some plugins, like BoneJ, look specifically for DefaultLinearAxis
when performing some calculations. While EnumeratedAxis works
technically, it is not supported (likely) by most plugins. Additionally,
ImageJ2 seems to always return DefaultLinearAxis. Until we can match
an EnmeratedAxis, it does not make a lot of sense to default to using
it. Especially if there are issues downstream like BoneJ.

(2) When calculating the scale for a singleton dimension, the coordinate
array only has one value. Thus attempting to calculate the slope from
the first two entries of the coord array is not possible. Instead, we
assign the scale to 1 for all singleton dimensions.

Author: elevans

src/imagej/dims.py

@@ -2,12 +2,12 @@
 Utility functions for querying and manipulating dimensional axis metadata.
 """
 import logging
-from typing import List, Tuple, Union
+from typing import List, Sequence, Tuple
 
 import numpy as np
 import scyjava as sj
 import xarray as xr
-from jpype import JException, JObject
+from jpype import JObject
 
 from imagej._java import jc
 from imagej.images import is_arraylike as _is_arraylike
@@ -179,7 +179,7 @@ def prioritize_rai_axes_order(
 
 def _assign_axes(
     xarr: xr.DataArray,
-) -> List[Union["jc.DefaultLinearAxis", "jc.EnumeratedAxis"]]:
+) -> Sequence["jc.DefaultLinearAxis"]:
     """
     Obtain xarray axes names, origin, scale and convert into ImageJ Axis. Supports both
     DefaultLinearAxis and the newer EnumeratedAxis.
@@ -205,25 +205,8 @@ def _assign_axes(
                 jc.Double(np.double(x)) for x in np.arrange(len(xarr.coords[dim]))
             ]
 
-        # assign calibrated axis type -- checks for imagej metadata
-        if "imagej" in xarr.attrs.keys():
-            ij_dim = _convert_dim(dim, "java")
-            if ij_dim + "_cal_axis_type" in xarr.attrs["imagej"].keys():
-                scale_type = xarr.attrs["imagej"][ij_dim + "_cal_axis_type"]
-                if scale_type == "linear":
-                    jaxis = _get_linear_axis(ax_type, sj.to_java(doub_coords))
-                if scale_type == "enumerated":
-                    try:
-                        EnumeratedAxis = _get_enumerated_axis()
-                    except (JException, TypeError):
-                        EnumeratedAxis = None
-                    if EnumeratedAxis is not None:
-                        jaxis = EnumeratedAxis(ax_type, sj.to_java(doub_coords))
-                    else:
-                        jaxis = _get_linear_axis(ax_type, sj.to_java(doub_coords))
-        else:
-            # default to DefaultLinearAxis always if no `scale_type` key in attr
-            jaxis = _get_linear_axis(ax_type, sj.to_java(doub_coords))
+        # create linear axes for data
+        jaxis = _get_default_linear_axis(ax_type, doub_coords)
 
         axes[ax_num] = jaxis
 
@@ -321,6 +304,20 @@ def _get_enumerated_axis():
     return sj.jimport("net.imagej.axis.EnumeratedAxis")
 
 
+def _get_default_linear_axis(axis_type: "jc.AxisType", values):
+    """
+    Get an instance of a DefaultLinearAxis.
+    """
+    origin = values[0]
+    # calculate the slope using the values/coord array
+    if len(values) <= 1:
+        scale = 1
+    else:
+        scale = values[1] - values[0]
+
+    return jc.DefaultLinearAxis(axis_type, scale, origin)
+
+
 def _get_linear_axis(axis_type: "jc.AxisType", values):
     """Get linear axis.
 
@@ -483,30 +480,3 @@ def _to_ijdim(key: str) -> str:
         return ijdims[key]
     else:
         return key
-
-
-def _cal_axis_type_to_str(key) -> str:
-    """
-    Convert a CalibratedAxis type (e.g. net.imagej.axis.DefaultLinearAxis) to
-    a string.
-    """
-    cal_axis_types = {
-        jc.ChapmanRichardsAxis: "ChapmanRichardsAxis",
-        jc.DefaultLinearAxis: "DefaultLinearAxis",
-        jc.EnumeratedAxis: "EnumeratedAxis",
-        jc.ExponentialAxis: "ExponentialAxis",
-        jc.ExponentialRecoveryAxis: "ExponentialRecoveryAxis",
-        jc.GammaVariateAxis: "GammaVariateAxis",
-        jc.GaussianAxis: "GaussianAxis",
-        jc.IdentityAxis: "IdentityAxis",
-        jc.InverseRodbardAxis: "InverseRodbardAxis",
-        jc.LogLinearAxis: "LogLinearAxis",
-        jc.PolynomialAxis: "PolynomialAxis",
-        jc.PowerAxis: "PowerAxis",
-        jc.RodbardAxis: "RodbardAxis",
-    }
-
-    if key.__class__ in cal_axis_types:
-        return cal_axis_types[key.__class__]
-    else:
-        return "unknown"