log clip_zero default revert to False, and only apply if data dtype s…

…upports it.

src/ezmsg/sigproc/math/log.py

@@ -12,7 +12,7 @@
 @consumer
 def log(
     base: float = 10.0,
-    clip_zero: bool = True,
+    clip_zero: bool = False,
 ) -> typing.Generator[AxisArray, AxisArray, None]:
     """
     Take the logarithm of the data. See :obj:`np.log` for more details.
@@ -29,7 +29,11 @@ def log(
     log_base = np.log(base)
     while True:
         msg_in: AxisArray = yield msg_out
-        if clip_zero:
+        if (
+            clip_zero
+            and np.any(msg_in.data <= 0)
+            and np.issubdtype(msg_in.data.dtype, np.floating)
+        ):
             msg_in.data = np.clip(
                 msg_in.data, a_min=np.finfo(msg_in.data.dtype).tiny, a_max=None
             )

tests/test_math.py

@@ -62,13 +62,17 @@ def test_invert():
 
 
 @pytest.mark.parametrize("base", [np.e, 2, 10])
-def test_log(base: float):
+@pytest.mark.parametrize("dtype", [int, float])
+@pytest.mark.parametrize("clip", [False, True])
+def test_log(base: float, dtype, clip: bool):
     n_times = 130
     n_chans = 255
-    in_dat = np.arange(n_times * n_chans).reshape(n_times, n_chans)
+    in_dat = np.arange(n_times * n_chans).reshape(n_times, n_chans).astype(dtype)
     msg_in = AxisArray(in_dat, dims=["time", "ch"])
-    proc = log(base)
+    proc = log(base, clip_zero=clip)
     msg_out = proc.send(msg_in)
+    if clip and dtype is float:
+        in_dat = np.clip(in_dat, a_min=np.finfo(msg_in.data.dtype).tiny, a_max=None)
     assert np.array_equal(msg_out.data, np.log(in_dat) / np.log(base))