Implementation of first and last reduction (#1093)

* implement append, create and finalize methods for first() reduction

* implement append, create, finalize for last() reduction

* add numba.jit() decorator

* add cuda=False parameter to last finalize() method

* fix missing whitespace after ","

* update NotImplementedError message for _combine() method in first/last reduction

* added tests for first/last reduction on pandas DF

* Update datashader/reductions.py

add whitespace characters

Co-authored-by: Ian Thomas <ianthomas23@gmail.com>

* Update datashader/tests/test_pandas.py

compare directly the numpy arrays in testing

Co-authored-by: Ian Thomas <ianthomas23@gmail.com>

* Update datashader/reductions.py

add whitespace character

Co-authored-by: Ian Thomas <ianthomas23@gmail.com>

* compare the numpy arrays directly for first() and last() reduction's tests

Co-authored-by: Ian Thomas <ianthomas23@gmail.com>

datashader/reductions.py

@@ -875,20 +875,22 @@ class first(Reduction):
     _dshape = dshape(Option(ct.float64))
 
     @staticmethod
-    def _append(x, y, agg):
-        raise NotImplementedError("first is currently implemented only for rasters")
+    @ngjit
+    def _append(x, y, agg, field):
+        if not isnull(field) and isnull(agg[y, x]):
+            agg[y, x] = field
 
     @staticmethod
     def _create(shape, array_module):
-        raise NotImplementedError("first is currently implemented only for rasters")
+        return array_module.full(shape, np.nan)
 
     @staticmethod
     def _combine(aggs):
-        raise NotImplementedError("first is currently implemented only for rasters")
+        raise NotImplementedError("first is not implemented for dask DataFrames")
 
     @staticmethod
-    def _finalize(bases, **kwargs):
-        raise NotImplementedError("first is currently implemented only for rasters")
+    def _finalize(bases, cuda=False, **kwargs):
+        return xr.DataArray(bases[0], **kwargs)
 
 
 
@@ -909,20 +911,22 @@ class last(Reduction):
     _dshape = dshape(Option(ct.float64))
 
     @staticmethod
-    def _append(x, y, agg):
-        raise NotImplementedError("last is currently implemented only for rasters")
+    @ngjit
+    def _append(x, y, agg, field):
+        if not isnull(field):
+            agg[y, x] = field
 
     @staticmethod
     def _create(shape, array_module):
-        raise NotImplementedError("last is currently implemented only for rasters")
+        return array_module.full(shape, np.nan)
 
     @staticmethod
     def _combine(aggs):
-        raise NotImplementedError("last is currently implemented only for rasters")
+        raise NotImplementedError("last is not implemented for dask DataFrames")
 
     @staticmethod
-    def _finalize(bases, **kwargs):
-        raise NotImplementedError("last is currently implemented only for rasters")
+    def _finalize(bases, cuda=False, **kwargs):
+        return xr.DataArray(bases[0], **kwargs)
 
 
 

datashader/tests/test_pandas.py

@@ -546,6 +546,37 @@ def test_categorical_std(df):
         assert_eq_xr(agg, out)
 
 
+def test_first():
+    df = pd.DataFrame({'x': [4, 0, 2, 2, 5, 2],
+                       'y': [0, 4, 5, 1, 1, 3],
+                       'z': [100, 101, 102, 103, 104, 105]})
+    cvs = ds.Canvas(plot_height=5, plot_width=5)
+    agg = cvs.line(df, 'x', 'y', agg=ds.first('z'))
+    sol = np.array([
+        [np.nan, np.nan, np.nan, np.nan, 100.],
+        [np.nan, np.nan, 102., 100., 103.],
+        [np.nan, np.nan, 100., 104., np.nan],
+        [np.nan, 100., 102., np.nan, np.nan],
+        [100., 101., 101., np.nan, np.nan]], dtype='float64')
+
+    assert_eq_ndarray(agg, sol)
+
+
+def test_last():
+    df = pd.DataFrame({'x': [4, 0, 2, 2, 5, 2],
+                       'y': [0, 4, 5, 1, 1, 3],
+                       'z': [100, 101, 102, 103, 104, 105]})
+    cvs = ds.Canvas(plot_height=5, plot_width=5)
+    agg = cvs.line(df, 'x', 'y', agg=ds.last('z'))
+    sol = np.array([
+        [np.nan, np.nan, np.nan, np.nan, 100.],
+        [np.nan, np.nan, 102., 103., 103.],
+        [np.nan, np.nan, 102., 104., np.nan],
+        [np.nan, 100., 104., np.nan, np.nan],
+        [100., 101., 101., np.nan, np.nan]], dtype='float64')
+
+    assert_eq_ndarray(agg, sol)
+
 @pytest.mark.parametrize('df', dfs)
 def test_multiple_aggregates(df):
     agg = c.points(df, 'x', 'y',