Handle all-NaN channels in calc_adc_params

changelog.d/adc-all-nan-channel.rst

@@ -0,0 +1,2 @@
+**Fix writing channels that are entirely NaN**
+  ``wrsamp`` and ``calc_adc_params`` no longer fail with ``cannot convert float NaN to integer`` when a channel contains only NaN values, and no longer emit an "All-NaN slice encountered" warning for such channels.

src/wfdb/io/_signal.py

@@ -748,7 +748,7 @@ def calc_adc_gain_baseline(self, ch, minvals, maxvals):
         # Figure out digital samples used to store physical samples
 
         # If the entire signal is NAN, gain/baseline won't be used
-        if pmin == np.nan:
+        if np.isnan(pmin):
             adc_gain = 1
             baseline = 1
         # If the signal is just one value, store one digital value.
@@ -829,9 +829,10 @@ def calc_adc_params(self):
                 raise ValueError("Signal contains inf. Cannot perform adc.")
 
             # min and max ignoring nans, unless whole channel is NAN.
-            # copy as 64-bit float to avoid precision loss
-            minvals = np.nanmin(self.p_signal, axis=0).astype("float64")
-            maxvals = np.nanmax(self.p_signal, axis=0).astype("float64")
+            # fmin/fmax behave like nanmin/nanmax without warning about
+            # all-NaN channels. Copy as 64-bit float to avoid precision loss.
+            minvals = np.fmin.reduce(self.p_signal, axis=0).astype("float64")
+            maxvals = np.fmax.reduce(self.p_signal, axis=0).astype("float64")
 
             for ch in range(np.shape(self.p_signal)[1]):
                 adc_gain, baseline = self.calc_adc_gain_baseline(ch, minvals, maxvals)
@@ -843,8 +844,8 @@ def calc_adc_params(self):
             maxvals = []
             for ch in self.e_p_signal:
                 # Copy as float for precise arithmetic
-                minvals.append(float(np.nanmin(ch)))
-                maxvals.append(float(np.nanmax(ch)))
+                minvals.append(float(np.fmin.reduce(ch)))
+                maxvals.append(float(np.fmax.reduce(ch)))
 
             if any(x == math.inf for x in minvals) or any(
                 x == math.inf for x in maxvals

tests/test_record.py

@@ -1615,6 +1615,40 @@ def test_adc_gain_min_boundary(self, temp_path):
         expected_gain = (32767 - (-2147483648)) / (base_value + 1.5)
         np.testing.assert_allclose(record.adc_gain[0], expected_gain, rtol=1e-3)
 
+    @pytest.mark.filterwarnings("error::RuntimeWarning")
+    def test_all_nan_channel(self, temp_path):
+        """Write and read back a signal with a channel that is entirely NaN."""
+        p_signal = np.array(
+            [
+                [np.nan, 0.5],
+                [np.nan, -0.25],
+                [np.nan, np.nan],
+            ]
+        )
+
+        record = wfdb.Record(p_signal=p_signal, fmt=["16", "16"])
+        adc_gain, baseline = record.calc_adc_params()
+        assert adc_gain[0] == 1
+        assert baseline[0] == 1
+
+        record = wfdb.Record(e_p_signal=list(p_signal.transpose()), fmt=["16", "16"])
+        assert record.calc_adc_params() == (adc_gain, baseline)
+
+        wfdb.wrsamp(
+            "test_all_nan_channel",
+            fs=250,
+            sig_name=["I", "II"],
+            units=["mV", "mV"],
+            p_signal=p_signal,
+            fmt=["16", "16"],
+            write_dir=temp_path,
+        )
+        record = wfdb.rdrecord(os.path.join(temp_path, "test_all_nan_channel"))
+        assert np.isnan(record.p_signal[:, 0]).all()
+        np.testing.assert_allclose(
+            record.p_signal[:, 1], p_signal[:, 1], atol=1 / record.adc_gain[1]
+        )
+
 
 class TestSigCohesion:
     """Tests for the digital range check in check_sig_cohesion."""