[#159] updating unit tests for add_bins()

datastock/tests/test_01_DataStock.py

@@ -350,63 +350,14 @@ def test08_domain_ref(self):
         lk = list(domain.keys())
         assert all([isinstance(dout[k0]['ind'], np.ndarray) for k0 in lk])
 
-    def test09_binning(self):
-
-        bins = np.linspace(1, 5, 8)
-        lk = [
-            ('y', 'nx', bins, 0, False, False, 'y_bin0'),
-            ('y', 'nx', bins, 0, True, False, 'y_bin1'),
-            ('y', 'nx', 'x', 0, False, True, 'y_bin2'),
-            ('y', 'nx', 'x', 0, True, True, 'y_bin3'),
-            ('prof0', 'x', 'nt0', 1, False, True, 'p0_bin0'),
-            ('prof0', 'x', 'nt0', 1, True, True, 'p0_bin1'),
-            ('prof0-bis', 'prof0', 'x', [0, 1], False, True, 'p1_bin0'),
-        ]
-
-        for ii, (k0, kr, kb, ax, integ, store, kbin) in enumerate(lk):
-            dout = self.st.binning(
-                data=k0,
-                bin_data0=kr,
-                bins0=kb,
-                axis=ax,
-                integrate=integ,
-                store=store,
-                store_keys=kbin,
-                safety_ratio=0.95,
-                returnas=True,
-            )
-
-            if np.isscalar(ax):
-                ax = [ax]
-
-            if isinstance(kb, str):
-                if kb in self.st.ddata:
-                    nb = self.st.ddata[kb]['data'].size
-                else:
-                    nb = self.st.dref[kb]['size']
-            else:
-                nb = bins.size
-
-            k0 = list(dout.keys())[0]
-            shape = [
-                ss for ii, ss in enumerate(self.st.ddata[k0]['data'].shape)
-                if ii not in ax
-            ]
-
-            shape.insert(ax[0], nb)
-            if dout[k0]['data'].shape != tuple(shape):
-                shstr = dout[k0]['data'].shape
-                msg = (
-                    "Mismatching shapes for case {ii}!\n"
-                    f"\t- dout['{k0}']['data'].shape = {shstr}\n"
-                    f"\t- expected: {tuple(shape)}"
-                )
-                raise Exception(msg)
-
-    def test10_add_bins(self):
+    def test09_add_bins(self):
         _input.add_bins(self.coll)
 
-    def test10_interpolate(self):
+    def test10_binning(self):
+        # _input.binning(self.coll)
+        pass
+
+    def test11_interpolate(self):
 
         lk = ['y', 'y', 'prof0', 'prof0', 'prof0', '3d']
         lref = [None, 'nx', 't0', ['nt0', 'nx'], ['t0', 'x'], ['t0', 'x']]

datastock/tests/test_input.py

@@ -23,25 +23,83 @@ def add_bins(coll):
     # -------------------------
 
     # linear uniform 1d
-    coll.add_bins('bin0', edges=np.linspace(0, 1, 10), units='m')
+    coll.add_bins('b1d_lin', edges=np.linspace(0, 1, 10), units='m')
 
     # log uniform 1d
-    coll.add_bins(edges=np.logspace(0, 1, 10), units='eV')
+    coll.add_bins('b1d_log', edges=np.logspace(0, 1, 10), units='eV')
 
     # non-uniform 1d
-    coll.add_bins(edges=np.r_[1, 2, 5, 10, 12, 20], units='s')
+    coll.add_bins('b2d_rand', edges=np.r_[1, 2, 5, 10, 12, 20], units='s')
 
     # linear uniform 2d
-    coll.add_bins('bin0', edges=np.linspace(0, 1, 10), units='m')
-
-    # log uniform 2d
-    coll.add_bins(edges=np.logspace(0, 1, 10), units='eV')
-
-    # non-uniform 2d
-    coll.add_bins(edges=np.r_[1, 2, 5, 10, 12, 20], units='s')
+    coll.add_bins(
+        'b2d_lin',
+        edges=(np.linspace(0, 1, 10), np.linspace(0, 3, 20)),
+        units='m',
+    )
+
+    # log uniform mix 2d
+    coll.add_bins(
+        'b2d_mix',
+        edges=(np.logspace(0, 1, 10), np.pi*np.r_[0, 0.5, 1, 1.2, 1.5, 2]),
+        units=('eV', 'rad'),
+    )
 
     # -------------------------
     # define bins pre-existing
     # -------------------------
 
     return
+
+
+def binning(coll):
+    bins = np.linspace(1, 5, 8)
+    lk = [
+        ('y', 'nx', bins, 0, False, False, 'y_bin0'),
+        ('y', 'nx', bins, 0, True, False, 'y_bin1'),
+        ('y', 'nx', 'x', 0, False, True, 'y_bin2'),
+        ('y', 'nx', 'x', 0, True, True, 'y_bin3'),
+        ('prof0', 'x', 'nt0', 1, False, True, 'p0_bin0'),
+        ('prof0', 'x', 'nt0', 1, True, True, 'p0_bin1'),
+        ('prof0-bis', 'prof0', 'x', [0, 1], False, True, 'p1_bin0'),
+    ]
+
+    for ii, (k0, kr, kb, ax, integ, store, kbin) in enumerate(lk):
+        dout = coll.binning(
+            data=k0,
+            bin_data0=kr,
+            bins0=kb,
+            axis=ax,
+            integrate=integ,
+            store=store,
+            store_keys=kbin,
+            safety_ratio=0.95,
+            returnas=True,
+        )
+
+        if np.isscalar(ax):
+            ax = [ax]
+
+        if isinstance(kb, str):
+            if kb in coll.ddata:
+                nb = coll.ddata[kb]['data'].size
+            else:
+                nb = coll.dref[kb]['size']
+        else:
+            nb = bins.size
+
+        k0 = list(dout.keys())[0]
+        shape = [
+            ss for ii, ss in enumerate(coll.ddata[k0]['data'].shape)
+            if ii not in ax
+        ]
+
+        shape.insert(ax[0], nb)
+        if dout[k0]['data'].shape != tuple(shape):
+            shstr = dout[k0]['data'].shape
+            msg = (
+                "Mismatching shapes for case {ii}!\n"
+                f"\t- dout['{k0}']['data'].shape = {shstr}\n"
+                f"\t- expected: {tuple(shape)}"
+            )
+            raise Exception(msg)