power_spectrum: force integer downsampling factors

Since calibration dictionaries coming from BL are usually floats, it can be confusing when you get an error somewhere internally in `calculate_power_spectrum` when you pass a float that is losslessly convertible to integer. This fixes that, while still disallowing non-integer downsampling ratios.

changelog.md

@@ -6,6 +6,10 @@
 
 * Added [`PowerSpectrum.compress()`](https://lumicks-pylake.readthedocs.io/en/latest/_api/lumicks.pylake.force_calibration.power_spectrum.PowerSpectrum.html#lumicks.pylake.force_calibration.power_spectrum.PowerSpectrum.compress#) to discard high frequency spectral data for a downsampled spectrum to conserve memory.
 
+#### Improvements
+
+* Force `num_points_per_block` to be integer when down-sampling a [`PowerSpectrum`](https://lumicks-pylake.readthedocs.io/en/latest/_api/lumicks.pylake.force_calibration.power_spectrum.PowerSpectrum.html).
+
 ## v1.6.0 | t.b.d.
 
 #### New features

lumicks/pylake/force_calibration/power_spectrum.py

@@ -264,13 +264,19 @@ def downsampled_by(self, factor, reduce=np.mean) -> "PowerSpectrum":
             (Deprecated) Function to use for down-sampling the data. Only `np.mean` will be
             supported going forward.
         """
+        if int(factor) != factor:
+            raise NotImplementedError("Only integer downsampling factors are supported")
+        else:
+            factor = int(factor)
+
         if reduce != np.mean:
             warnings.warn(
                 DeprecationWarning(
                     "Providing other reduction functions than `np.mean` is deprecated and will be "
                     "removed in a future version of Pylake"
                 )
             )
+
             return PowerSpectrum(
                 downsample(self.frequency, factor, reduce),
                 downsample(self.power, factor, reduce),

lumicks/pylake/force_calibration/tests/test_power_spectrum.py

@@ -390,3 +390,15 @@ def test_compress():
     assert compressed._num_points_per_block == 100
     np.testing.assert_allclose(ps_downsampled.frequency, ps_downsampled.frequency)
     np.testing.assert_allclose(compressed.power, ps_downsampled.power)
+
+
+def test_integer_num_points_per_block():
+    ps = PowerSpectrum(np.arange(500), np.arange(500), 78125, total_duration=1)
+    ps_ds = ps.downsampled_by(10.0)
+    ps_ds_int = ps.downsampled_by(10)
+    np.testing.assert_allclose(ps_ds.power, ps_ds_int.power)
+
+    with pytest.raises(
+        NotImplementedError, match="Only integer downsampling factors are supported"
+    ):
+        ps.downsampled_by(10.00001)