Speed up resample_melody_series (#218)

docs/changes.rst

@@ -12,6 +12,7 @@ v0.4
 - `#208`_: refactored file/buffer loading
 - `#210`_: added `io.load_tempo`
 - `#212`_: added frame-wise blind-source separation evaluation
+- `#218`_: speed up `melody.resample_melody_series` when times are equivalent
 
 .. _#189: https://github.com/craffel/mir_eval/issues/189
 .. _#195: https://github.com/craffel/mir_eval/issues/195
@@ -40,7 +41,7 @@ v0.2
 - `#103`_: incomplete files passed to `melody.evaluate` should warn
 - `#109`_: `STRICT_BASS_INTERVALS` is now an argument to `chord.encode`
 - `#122`_: improved handling of corner cases in beat tracking
-- `#136`_: improved test coverage 
+- `#136`_: improved test coverage
 - `#138`_: PEP8 compliance
 - `#139`_: converted documentation to numpydoc style
 - `#147`_: fixed a rounding error in segment intervals

mir_eval/melody.py

@@ -189,9 +189,12 @@ def constant_hop_timebase(hop, end_time):
 
 def resample_melody_series(times, frequencies, voicing,
                            times_new, kind='linear'):
-    """Resamples frequency and voicing time series to a new timescale.  Maintains
+    """Resamples frequency and voicing time series to a new timescale. Maintains
     any zero ("unvoiced") values in frequencies.
 
+    If ``times`` and ``times_new`` are equivalent, no resampling will be
+    performed.
+
     Parameters
     ----------
     times : np.ndarray
@@ -214,6 +217,10 @@ def resample_melody_series(times, frequencies, voicing,
         Boolean voicing array resampled to new timebase
 
     """
+    # If the timebases are already the same, no need to interpolate
+    if times.shape == times_new.shape and np.allclose(times, times_new):
+        return frequencies, voicing.astype(np.bool)
+
     # Warn when the delta between the original times is not constant,
     # unless times[0] == 0. and frequencies[0] == frequencies[1] (see logic at
     # the beginning of to_cent_voicing)

tests/test_melody.py

@@ -60,6 +60,21 @@ def test_resample_melody_series():
     assert np.allclose(res_voicing, expected_voicing)
 
 
+def test_resample_melody_series_same_times():
+    # Check the case where the time bases are identical
+    times = np.array([0.0, 0.1, 0.2, 0.3])
+    times_new = np.array([0.0, 0.1, 0.2, 0.3])
+    cents = np.array([2., 0., -1., 1.])
+    voicing = np.array([0, 0, 1, 1])
+    expected_cents = np.array([2., 0., -1., 1.])
+    expected_voicing = np.array([False, False, True, True])
+    (res_cents,
+     res_voicing) = mir_eval.melody.resample_melody_series(times, cents,
+                                                           voicing, times_new)
+    assert np.allclose(res_cents, expected_cents)
+    assert np.allclose(res_voicing, expected_voicing)
+
+
 def test_to_cent_voicing():
     # We'll just test a few values from one of the test annotations
     ref_file = sorted(glob.glob(REF_GLOB))[0]